Validating a Genomic Convergence and Network Analysis Approach Using Association Analysis of Identified Candidate Genes in Alzheimer's Disease

Association between KRAS mutation and alcohol consumption in Brazilian patients with colorectal cancer

Colorectal cancer (CRC) is a leading cause of morbidity and mortality worldwide. Detection before metastasis and efficient treatment of disease significantly improve patient survival and quality of life. However, limitations in diagnosis and postoperative surveillance are associated with low CRC detection and survival rates. Thus, this project aimed to evaluate the molecular profile of patients diagnosed with CRC, as molecular biomarkers constitute a new frontier for diagnosis, treatment and prognosis. Methods and Results: 42 patients were included in the study, predominantly male (59.5%), with a median age of 63 years (SD: 10.0; min: 41; max: 83). The majority of primary tumors were located in the rectum (38.1%), in the sigmoid (33.3%) and in the ascending (21.4%) colon. We evaluated the genes KRAS, NRAS, BRAF, EGFR and TP53 using Sanger sequencing. Somatic and germline mutations were found in the KRAS, EGFR and TP53 genes, with the most common somatic alteration being rs121913529 in KRAS. This variant was also strongly associated with alcoholism (p = 0.002). Furthermore, patients with somatic mutations in TP53 had significantly higher mortality compared to those with wild-type alleles (OR: 11.2; 95% CI 1.25-2.45). Conclusions: Our findings support a relationship between alcohol consumption and the rs121913529 mutation, which is classified as pathogenic for colorectal cancer. Thus, further studies investigating the link between alcohol consumption, colorectal carcinogenesis and tumor progression ought to be conducted.

Identification of neutrophil extracellular trap-related genes in Alzheimer's disease based on comprehensive bioinformatics analysis

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease. There are currently no effective interventions to slow down or prevent the occurrence and progression of AD. Neutrophil extracellular traps (NETs) have been proven to be tightly linked to AD. This project attempted to identify hub genes for AD based on NETs. Gene expression profiles of the training set and validation set were downloaded from the Gene Expression Omnibus (GEO) database, including non-demented (ND) controls and AD samples. NET-related genes (NETRGs) were collected from the literature. Differential analysis identified 21 AD differentially expressed NETRGs (AD-DE-NETRGs) majorly linked to functions such as defense response to bacterium as well as pathways including IL-17 signaling pathway, as evidenced by enrichment analyses of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Protein-protein interaction (PPI) network, Minutia Cylinder-Code (MCC) algorithm, and molecular complex detection (MCODE) algorithm in the CytoHubba plug-in were employed to identify five hub genes (NFKBIA, SOCS3, CCL2, TIMP1, ACTB). Their diagnostic ability was validated in the validation set using receiver operating characteristic (ROC) curves and gene differential expression analysis. A total of 16 miRNAs and 132 lncRNAs were predicted through the mirDIP and ENCORI databases, and a lncRNA-miRNA-mRNA regulatory network was constructed using Cytoscape software. Small molecular compounds such as Benzo(a)pyrene and Copper Sulfate were predicted to target hub genes using the CTD database. This project successfully identified five hub genes, which may serve as potential biomarkers for AD, proffering clues for new therapeutic targets.

Leveraging electronic health records and knowledge networks for Alzheimer's disease prediction and sex-specific biological insights

Identification of Alzheimer's disease (AD) onset risk can facilitate interventions before irreversible disease progression. We demonstrate that electronic health records from the University of California, San Francisco, followed by knowledge networks (for example, SPOKE) allow for (1) prediction of AD onset and (2) prioritization of biological hypotheses, and (3) contextualization of sex dimorphism. We trained random forest models and predicted AD onset on a cohort of 749 individuals with AD and 250,545 controls with a mean area under the receiver operating characteristic of 0.72 (7 years prior) to 0.81 (1 day prior). We further harnessed matched cohort models to identify conditions with predictive power before AD onset. Knowledge networks highlight shared genes between multiple top predictors and AD (for example, APOE, ACTB, IL6 and INS). Genetic colocalization analysis supports AD association with hyperlipidemia at the APOE locus, as well as a stronger female AD association with osteoporosis at a locus near MS4A6A. We therefore show how clinical data can be utilized for early AD prediction and identification of personalized biological hypotheses.

Correlation between ESR1 and APOE gene polymorphisms and risk of osteonecrosis of the femoral head: a case-control study

BACKGROUND

Osteonecrosis of the femoral head (ONFH) is a disease with a high disability rate, and genetic factors are closely related to its pathogenesis. This study aimed to investigate the possible correlation between ESR1 and APOE gene polymorphisms and the risk of ONFH.

METHODS

In this case-control study, the potential association between three genetic variants (rs2982573 C < T, rs10872678 C < T, and rs9322332 A < C) of the ESR1 gene and two genetic variants (rs7259620 A < G and rs769446 C < T) of the APOE gene with the risk of ONFH was investigated. Correlations between gene polymorphisms and ONFH risk were assessed using logistic regression analysis, with calculation of odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

The overall analysis demonstrated that rs9322332 in the ESR1 gene exhibited a correlation with a decreased risk of ONFH under the homozygous (AA vs.CC: OR = 0.69, 95% CI [0.53-0.90], p = 0.006), dominant (CA + AA vs. CC: OR = 0.70, 95% CI [0.54-0.90], p = 0.006), and additive (OR = 0.79, 95% CI [0.66-0.95], p = 0.013) models. The stratification analysis revealed that rs9322332 was linked to a lower risk of ONFH in subgroups characterized by individuals aged over 51 years and non-smokers. Nevertheless, there were no notable correlations found between ESR1 rs2982573 and rs10872678, as well as APOE rs7259620 and rs769446, with the risk of ONFH.

CONCLUSION

ESR1-rs9322332 is closely linked to a decreased risk of ONFH, thereby enhancing our understanding of the relationship between gene polymorphisms and ONFH.

ApoE gene polymorphisms and metals and their interactions with cognitive function

OBJECTIVE

To analyze the relationship between plasma metal elements, ApoE gene polymorphisms and the interaction between the two and impaired cognitive function in elderly population.

METHOD

A stratified sample was drawn according to the age of the study population, and 911 subjects were included. Baseline information and health indicators were obtained, and cognitive function status was assessed by health examination, a general questionnaire and Mini-Mental Status Examination. Plasma metal elements were measured, and SNP typing was performed. Binary logistic regression was used to analyze the factors influencing cognitive function status and the association between the SNP genetic pattern of the ApoE gene and cognitive function.

RESULTS

The differences in gene frequencies and genotype frequencies of the ApoE rs7412 and rs7259620 genotype frequencies were statistically different between the cognitive impairment group and the control group (P < 0.05). statistically differences were found for the codominant model in rs7412-TT compared with the CC genotype (OR = 3.112 (1.159-8.359), P = 0.024) and rs7259620-AA compared with the GG genotype (OR = 1.588 (1.007-2.504), P = 0.047). Statistically differences were found in the recessive models rs7412-TT compared with (CC + CT) (OR = 2.979 (1.112-7.978), P = 0.030), rs7259620-AA compared with (GG + GA), and rs405509-GG compared with (TT + TG) (OR = 1.548(1.022-2.344), P = 0.039) all of which increased the risk of developing cognitive impairment. The differences in plasma Fe, Cu, and Rb concentrations between the case and control groups were significant (P < 0.05). The regression results showed that the plasma Cd concentrations in the Q1 range was a protective factor for cognitive function compared with Q4 (0.510 (0.291-0.892), P = 0.018). Furthermore, there was a multiplicative interaction between the codominant and recessive models for the Q2 concentrations of Cd and the rs7259620 loci, and the difference was significant, indicating increased risk of developing cognitive impairment (codominant model OR = 3.577 (1.496-8.555), P = 0.004, recessive model OR = 3.505 (1.479-8.307), P = 0.004). There was also a multiplicative interaction between Cd and the recessive model at the rs405509 loci, and the difference was significant, indicating increased risk of developing cognitive impairment (OR = 3.169 (1.400-7.175), P = 0.006).

CONCLUSION

The ApoE rs7412, rs7259620 and rs405509 loci were associated with cognitive impairment in the elderly population, and there was an interaction between plasma metalloid Cd and the rs7259620 and rs405509 loci that increased the risk of cognitive impairment in the elderly population.