Five genes identified as prognostic markers for colorectal cancer through the integration of genome-wide association study and expression quantitative trait loci data

Background: Colorectal cancer (CRC) is a prominent form of cancer globally, ranking second in terms of prevalence and serving as a leading cause of cancer-related deaths, but the underlying biological interpretation remains largely unknown. Methods: We used the summary data-based Mendelian randomization method to integrate CRC genome-wide association studies (ncase = 7062; ncontrol = 195,745) and expression quantitative trait loci summary data in peripheral whole blood (Consortium for Architecture of Gene Expression: n = 2765; Genotype-Tissue Expression [v8]: n = 755) and colon tissue (colon-transverse: n = 406; colon-sigmoid: n = 373) and identified related genes. Results: Genes ABTB1, CYP21A2, NLRP1, PHKG1 and PIP5K1C have emerged as significant prognostic markers for CRC patient survival. Functional analysis revealed their involvement in cancer cell migration and invasion mechanisms, providing valuable insights for the development of future anti-CRC drugs. Conclusion: We successfully identified five CRC risk genes, providing new insights and research directions for the effective mechanisms of CRC.

New Insights into Risk Genes and Their Candidates in Multiple Sclerosis

Oligodendrocytes are central nervous system glial cells that wrap neuronal axons with their differentiated myelin membranes as biological insulators. There has recently been an emerging concept that multiple sclerosis could be triggered and promoted by various risk genes that appear likely to contribute to the degeneration of oligodendrocytes. Despite the known involvement of vitamin D, immunity, and inflammatory cytokines in disease progression, the common causes and key genetic mechanisms remain unknown. Herein, we focus on recently identified risk factors and risk genes in the background of multiple sclerosis and discuss their relationships.

De-coding genetic risk variants in type 1 diabetes

The conceptual basis for a genetic predisposition underlying the risk for developing type 1 diabetes (T1D) predates modern human molecular genetics. Over half of the genetic risk has been attributed to the human leukocyte antigen (HLA) class II gene region and to the insulin (INS) gene locus - both thought to confer direction of autoreactivity and tissue specificity. Notwithstanding, questions still remain regarding the functional contributions of a vast array of minor polygenic risk variants scattered throughout the genome that likely influence disease heterogeneity and clinical outcomes. Herein, we summarize the available literature related to the T1D-associated coding variants defined at the time of this review, for the genes PTPN22, IFIH1, SH2B3, CD226, TYK2, FUT2, SIRPG, CTLA4, CTSH and UBASH3A. Data from genotype-selected human cohorts are summarized, and studies from the non-obese diabetic (NOD) mouse are presented to describe the functional impact of these variants in relation to innate and adaptive immunity as well as to β-cell fragility, with expression profiles in tissues and peripheral blood highlighted. The contribution of each variant to progression through T1D staging, including environmental interactions, are discussed with consideration of how their respective protein products may serve as attractive targets for precision medicine-based therapeutics to prevent or suspend the development of T1D.

Network and Pathway-Based Integrated Analysis Identified a Novel "rs28457673-miR-15/16/195/424/497 Family-IGF1R-MAPK Signaling Pathway" Axis Associated With Post-stroke Depression

Single-nucleotide polymorphisms (SNPs) of microRNA (miRNA) (miRSNP) are SNPs located on miRNA genes or miRNA target sites, which have been supposed to be involved in the development of central nervous system diseases by interfering with miRNA-mediated regulatory functions. However, the association of miRSNP with post-stroke depression (PSD) has not been well-investigated. In this study, we collected 54 PSD risk genes via manual literature-mining and integrated PSD-related risk pathways based on multiple public databases. Furthermore, we systematically screened candidate functional miRSNPs for PSD and integrated a miRSNP-based PSD-associated pathway network, which included 99 miRNAs that target 12 PSD risk pathways. We also reviewed the association between three risk pathways and PSD pathogenetic mechanism thoroughly. Combining literature mining and network analysis, our results proposed an underlying mechanism of "miRSNP → miRNA → risk gene → pathway" axis effects on PSD pathogenesis, especially for rs28457673 (miR-15/16/195/424/497 family) → IGF1R → hsa04010 (MAPK signaling pathway). Our studies revealed a functional role in genetic modifier at the system level in the pathogenesis of PSD, which might provide further information for the miRSNP studies in PSD.

Prognostic role of mitochondrial pyruvate carrier in isocitrate dehydrogenase-mutant glioma

OBJECTIVE Gliomas are one of the most common types of primary brain tumors. Recent studies have supported the importance of key genetic alterations, including isocitrate dehydrogenase (IDH) mutations and 1p19q codeletion, in glioma prognosis. Mutant IDH produces 2-hydroxyglutarate from α-ketoglutarate, a key metabolite of the Krebs cycle. The mitochondrial pyruvate carrier (MPC) is composed of MPC1 and MPC2 subunits and is functionally essential for the Krebs cycle. The authors sought to explore the impact of MPC1 and MPC2 expression on patient prognosis. METHODS Genomic and clinical data in patients with lower-grade glioma (WHO grades II and III) from The Cancer Genome Atlas (TCGA) were evaluated using Kaplan-Meier analysis and hazards modeling. Validation was conducted with additional data sets, including glioblastoma. RESULTS A total of 286 patients with lower-grade glioma (mean age 42.7 ± 13.5 years, 55.6% males) included 54 cases of IDH-wild type (18.9%); 140 cases of IDH-mutant, 1p19q-intact (49.0%); and 85 cases of IDH-mutant, 1p19q-codeleted (29.7%) tumors. Kaplan-Meier analysis showed that an MPC1 z-score > 0 distinguished better survival, particularly in IDH-mutant (p < 0.01) but not IDH-wild type tumors. Conversely, an MPC2 z-score > 0 identified worsened survival, particularly in IDH-mutant (p < 0.01) but not IDH-wild type tumors. Consistently, neither MPC1 nor MPC2 was predictive in a glioblastoma data set containing 5% IDH-mutant cases. Within the IDH-stratified lower-grade glioma data set, MPC1 status distinguished improved survival in 1p19q-codeleted tumors (p < 0.05), whereas MPC2 expression delineated worsened survival in 1p19q-intact tumors (p < 0.01). A hazards model identified IDH and 1p19q status, age (p = 0.01, HR = 1.03), Karnofsky Performance Scale (KPS) score (p = 0.03, HR = 0.97), and MPC1 (p = 0.003, HR = 0.52) but not MPC2 (p = 0.38) as key variables affecting overall survival. Further validation confirmed MPC1 as an independent predictor of lower-grade glioma. A clinical risk score using IDH and 1p19q status, age, KPS score, and MPC1 and MPC2 z-scores defined 4 risk categories for lower-grade glioma; this score was validated using a secondary glioma data set. CONCLUSIONS These results support the importance of MPC, especially MPC1, in improving prognostication of IDH-mutant tumors. The generation of a risk score system directly translates this finding to clinical application; however, further research to improve the molecular understanding of the role of MPC in the metabologenomic regulation of gliomas is warranted.

Genetic Analyses of Alzheimer's Disease in China: Achievements and Perspectives

Since 2010, the Chinese have become one of the most aged populations in the world, leading to a severe burden of neurodegenerative disorders. Alzheimer's disease (AD) is the most prevalent neurodegenerative disease and has a high genetic heritability. In the past two decades, numerous genetic analyses, from linkage analyses and candidate gene studies to genome-wide association studies (GWASs) and next-generation sequencing studies, have identified dozens of AD susceptibility or causal genes. These studies have provided a comprehensive genetic view and contributed to the understanding of the pathological and molecular mechanisms of the disease. However, most of the recognized AD genetic risk factors have been reported in studies based on European populations or populations of European ancestry, and data about the genetics of AD from other populations has been very limited. As China has the largest AD population in the world and because of the remarkable genetic differences between the East and the West, deciphering the genetic basis and molecular mechanism in Chinese patients with AD may add key points to the full characterization of AD. In this review, we present an overview of the current state of AD genetic research in China, with an emphasis on genome-level studies. We also describe the challenges and opportunities for future advances, especially for in-depth collaborations, brain bank construction, and primate animal modeling. There is an urgent need to promote public awareness and increase our collaborations and data sharing.

Landscape of Conditional eQTL in Dorsolateral Prefrontal Cortex and Co-localization with Schizophrenia GWAS

Causal genes and variants within genome-wide association study (GWAS) loci can be identified by integrating GWAS statistics with expression quantitative trait loci (eQTL) and determining which variants underlie both GWAS and eQTL signals. Most analyses, however, consider only the marginal eQTL signal, rather than dissect this signal into multiple conditionally independent signals for each gene. Here we show that analyzing conditional eQTL signatures, which could be important under specific cellular or temporal contexts, leads to improved fine mapping of GWAS associations. Using genotypes and gene expression levels from post-mortem human brain samples (n = 467) reported by the CommonMind Consortium (CMC), we find that conditional eQTL are widespread; 63% of genes with primary eQTL also have conditional eQTL. In addition, genomic features associated with conditional eQTL are consistent with context-specific (e.g., tissue-, cell type-, or developmental time point-specific) regulation of gene expression. Integrating the 2014 Psychiatric Genomics Consortium schizophrenia (SCZ) GWAS and CMC primary and conditional eQTL data reveals 40 loci with strong evidence for co-localization (posterior probability > 0.8), including six loci with co-localization of conditional eQTL. Our co-localization analyses support previously reported genes, identify novel genes associated with schizophrenia risk, and provide specific hypotheses for their functional follow-up.

Single point mutation on the gene encoding dysbindin results in recognition deficits

The dystrobrevin-binding protein 1 (DTNBP1) gene is a candidate risk factor for schizophrenia and has been associated with cognitive ability in both patient populations and healthy controls. DTNBP1 encodes dysbindin protein, which is localized to synaptic sites and is reduced in the prefrontal cortex and hippocampus of patients with schizophrenia, indicating a potential role in schizophrenia etiology. Most studies of dysbindin function have focused on the sandy (sdy) mice that lack dysbindin protein and have a wide range of abnormalities. In this study, we examined dysbindin salt and pepper (spp) mice that possess a single point mutation on the Dtnbp1 gene predicted to reduce, but not eliminate, dysbindin expression. By western blot analysis, we found that spp homozygous (spp -/-) mutants had reduced dysbindin and synaptosomal-associated protein 25 (SNAP-25) in the prefrontal cortex, but unaltered levels in hippocampus. Behaviorally, spp mutants performed comparably to controls on a wide range of tasks assessing locomotion, anxiety, spatial recognition and working memory. However, spp -/- mice had selective deficits in tasks measuring novel object recognition and social novelty recognition. Our results indicate that reduced dysbindin and SNAP-25 protein in the prefrontal cortex of spp -/- is associated with selective impairments in recognition processing. These spp mice may prove useful as a novel mouse model to study cognitive deficits linked to dysbindin alterations. Our findings also suggest that aspects of recognition memory may be specifically influenced by DTNBP1 single nucleotide polymorphisms or risk haplotypes in humans and this connection should be further investigated.

Identifying miRNA-mRNA regulation network of chronic pancreatitis based on the significant functional expression

BACKGROUND

The aim of this study was to explore the underlying molecular mechanism and potential molecular biomarkers of chronic pancreatitis (CP) and construct a miRNA-mRNA regulation network.

METHODS

To explore the involvement of miRNAs in CP, we downloaded the miRNA and mRNA expression profiles of CP patients and healthy controls and identified the differentially expressed miRNAs and genes. Functional analysis was conducted and significant pathways were utilized. Finally, the miRNA-mRNA regulation network of CP was constructed.

RESULTS

A total of 44 miRNA risk gene pathway relationships were identified, and a complex regulation network was constructed with 3 genes (ABL1, MYC, and ANAPC13) having the highest degree in affecting the network of CP. Importantly, 4 risk genes (NOTCH3, COX5A, THBS1, and KARS) and 1 risk miRNA (hsa-miR-324-5p) were identified with high prediction accuracy.

CONCLUSIONS

In conclusion, we analyzed miRNAs and mRNAs expression profiles in CP, 1 risk miRNA, and 4 risk genes were identified with high prediction accuracy as biomarkers of CP. Although further evaluation in clinical study is needed, our findings provide new insights into the pathogenesis of CP and may improve the diagnosis and therapy by identifying novel targets.

Linkage between genotype and immunological phenotype in Crohn's disease

Understanding the mechanisms that drive uncontrolled inflammation in Crohn's disease (CD) remains one of the most pressing challenges in contemporary experimental medicine. Recently, a three-phased view on the pathogenesis of CD was proposed in which following the breakdown of intestinal epithelial barrier function, CD patients fail to clear the resulting infectious debris, provoking subsequent immune responses. This view on CD is attractive in that it is testable and allows better diagnosis of disease if proven correct, apart from opening a window on new therapeutic horizons. Here we shall argue, however, that this scheme may be an oversimplification in that it ignores the genetic diversity of CD and thus does not fully take into account the nature of the intestinal epithelium, which appears a non-passive actor in this disease.

Effects of Alzheimer's disease-associated risk loci on cerebrospinal fluid biomarkers and disease progression: a polygenic risk score approach

BACKGROUND

Several risk loci for Alzheimer's disease (AD) have been identified during recent years in large-scale genome-wide association studies. However, little is known about the mechanisms by which these loci influence AD pathogenesis.

OBJECTIVE

To investigate the individual and combined risk effects of the newly identified AD loci.

METHODS

Association of 12 AD risk loci with AD and AD-related cerebrospinal fluid (CSF) biomarkers was assessed. Furthermore, a polygenic risk score combining the effect sizes of the top 22 risk loci in AD was calculated for each individual among the clinical and neuropathological cohorts. Effects of individual risk loci and polygenic risk scores were assessed in relation to CSF biomarker levels as well as neurofibrillary pathology and different biochemical measures related to AD pathogenesis obtained from the temporal cortex.

RESULTS

Polygenic risk scores associated with CSF amyloid-β42 (Aβ42) levels in the clinical cohort, and with soluble Aβ42 levels and γ-secretase activity in the neuropathological cohort. The γ-secretase effect was independent of APOE. APOE-ε4 associated with CSF Aβ42 (p < 0.001) levels. For the other risk loci, no significant associations with AD risk or CSF biomarkers were detected after multiple testing correction.

CONCLUSIONS

AD risk loci polygenically contribute to Aβ pathology in the CSF and temporal cortex, and this effect is potentially associated with increased γ-secretase activity.

Predictors of anti-VEGF treatment response in neovascular age-related macular degeneration

Currently available evidence on predictors of anti-vascular endothelial growth factor (VEGF) treatment response in neovascular age-related macular degeneration was reviewed. No meta-analysis of results is possible because of a lack of controlled and randomized trials, varying treatment regimes and outcome measures used, as well as suboptimal reporting. For genetic factors, most evidence to date has been generated for single nucleotide polymorphisms (SNPs) in the complement factor H (CFH), and VEGF-A genes. Just under half of the SNPs assessed in the CFH gene and 15% of the SNPs assessed in the VEGF gene were found to be associated with visual outcomes or the number of injections required during follow-up. Some evidence suggests association of worse treatment outcomes as well as a younger age at treatment onset with an increasing number of risk alleles in known risk genes (CFH and ARMS2/HTRA1) and polymorphisms in the VEGF-A gene. Clinical factors such as higher age, a better visual acuity (VA), a larger choroidal neovascularization (CNV) lesion at baseline, and a delay between symptom onset and initiation of treatment of more than 3 weeks also impact outcomes. Conversely, a worse acuity at baseline predicted more gain in vision. Overall, patients presenting with good acuity at baseline were more likely to have good VA at follow up, but the gain afforded by treatment was impacted by a ceiling effect. Most available evidence suggests a strong association of clinical factors such as age, baseline VA, and CNV lesion size with anti-VEGF treatment outcomes. No behavioral factors such as smoking influence treatment outcomes. Based on the studies conducted so far, the evidence suggests that underlying genotype of known AMD risk associated genes or of the VEGF-A gene have a limited effect, whereas presenting clinical factors appear to be more important in determining treatment outcomes.

MicroRNA dysregulation in neuropsychiatric disorders and cognitive dysfunction

MicroRNAs (miRNA), a class of non-coding RNAs, are emerging as important modulators of neuronal development, structure and function. A connection has been established between abnormalities in miRNA expression and miRNA-mediated gene regulation and psychiatric and neurodevelopmental disorders as well as cognitive dysfunction. Establishment of this connection has been driven by progress in elucidating the genetic etiology of these phenotypes and has provided a context to interpret additional supporting evidence accumulating from parallel expression profiling studies in brains and peripheral blood of patients. Here we review relevant evidence that supports this connection and explore possible mechanisms that underlie the contribution of individual miRNAs and miRNA-related pathways to the pathogenesis and pathophysiology of these complex clinical phenotypes. The existing evidence provides useful hypotheses for further investigation as well as important clues for identifying novel therapeutic targets.

Genome-wide association studies of schizophrenia: does bigger lead to better results?

PURPOSE OF REVIEW

Numerous genome-wide association studies (GWAS) of schizophrenia have been published in the past 6 years, with a number of key reports published in the last year. The studies have evolved in scale from small individual samples to large collaborative endeavors. This review aims to critically assess whether the results have improved as the sample size and scale of genetic association studies have grown.

RECENT FINDINGS

Genomic genotyping and increasing sample sizes for schizophrenia association studies have led to parallel increases in the number of risk genes discovered with high statistical confidence. Nearly 20 genes or loci have surpassed the genome-wide significance threshold (P = 5 × 10) in a single study, and several have been replicated in more than one GWAS.

SUMMARY

Identifying the genetic underpinnings of complex diseases offers insight into the etiological mechanisms leading to manifestation of the disease. New and more effective treatments for schizophrenia are desperately needed, and the ability to target the relevant biological processes grows with our understanding of the genes involved. As the size of GWAS samples has increased, more genes have been identified with high confidence that have begun to provide insight into the etiological and pathophysiological foundations of this disorder.