Identification of genes related to mental disorders by text mining

Wu, Ying; Dang, Meilin; Li, Hongxia; Jin, Xing; Yang, Wenxiao

doi:10.1097/md.0000000000017504

Cited by 6 publications

(5 citation statements)

References 28 publications

(24 reference statements)

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“…To extract complex relevance, we set two variables in the antecedent, and we used minimum thresholds that define interestingness as those with confidence ≥80% [ 51 ]. This means that for all interesting rules ({A}→{B}) presented here, the consequent ({B}) occurred in ≥80% of all cases that showed morbidity in the antecedent ({A}).…”

Section: Methodsmentioning

confidence: 99%

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Combined abnormal muscle activity and pain-related factors affect disability in patients with chronic low back pain: An association rule analysis

et al. 2020

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Objectives In patients with chronic low back pain (CLBP), reduced lumbar flexion-relaxation and reduced variability of muscle activity distribution are reported as abnormal muscle activity. It is not known how abnormal muscle activity and pain-related factors are related to CLBP-based disability. Here, we performed an association rule analysis to investigated how CLBP disability, muscle activity, and pain-related factors in CLBP patients are related. Methods Surface electromyographic signals were recorded from over the bilateral lumbar erector spinae muscle with four-channel electrodes from 24 CLBP patients while they performed a trunk flexion re-extension task. We calculated the average value of muscle activities of all channels and then calculated the flexion relaxation ratio (FRR) and the spatial variability of muscle activities. We also assessed the pain-related factors and CLBP disability by a questionnaire method. A clustering association rules analysis was performed to determine the relationships among pain-related factors, the FRR, and the variability of muscle activity distribution. Results The association rules of severe CLBP disability were divisible into five classes, including ‘low FRR-related rules.’ The rules of the mild CLBP disability were divisible into four classes, including ‘high FRR-related rules’ and ‘high muscle variability-related rules.’ When we combined pain-related factors with the FRR and muscle variability, the relationship between abnormal FRR/muscle variability and CLBP disability became stronger. Discussion Our findings thus highlight the importance of focusing on not only the patients’ pain-related factors but also the abnormal motor control associated with CLBP, which causes CLBP disability.

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Section: Methodsmentioning

confidence: 99%

“…To extract complex relevance, we set two variables in the antecedent, and we used minimum thresholds that define interestingness as those with confidence �80% [51]. This means that for all interesting rules ({A}!…”

Section: Plos Onementioning

confidence: 99%

Combined abnormal muscle activity and pain-related factors affect disability in patients with chronic low back pain: An association rule analysis

et al. 2020

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“…In the literature, specifc genes and enzymes linked to the central nervous system have been proven to afect the etiological process of mental disorders [13] and substance abuse-induced dysregulation of neurotransmissions [14]. For instance, both mental disorders and abused substances, directly or indirectly, are altered by monoaminergic (both dopaminergic and serotonergic) pathways [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

MAOA uVNTR Polymorphism Influence on Older Adults Diagnosed with Diabetes Mellitus/Systemic Arterial Hypertension

Seixas

Freitas

Silva

et al. 2023

Journal of Aging Research

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Background. Monoamine oxidase (MAO) is involved in several biological processes associated with well-being and mental health, and alterations in its function might directly impact various mental disorders. Some mental disorders concomitantly occur in individuals with clinical characteristics, such as substance abuse and diabetes. Objective. To analyze the functional MAOA uVNTR polymorphism genotype frequency in an older adult population with diabetes mellitus/arterial hypertension and associate this frequency with clinical characteristics impacting daily life. Methodology. Older adults diagnosed with diabetes mellitus, systemic arterial hypertension, or both (DM/SAH) were selected and had their MAOA gene genotyped for uVNTR polymorphism. The revised Beck Depression Inventory (BDI) and a questionnaire were also applied to determine their mental health and clinical characteristics. Results. The allelic variants detected among the participants were the 2R, 3R, 4R, and 3R/4R heterozygous genotypes. Genotypes solely containing the 3R allele had patients who marked yes for smoking and alcoholism, and only those with the 3R genotypes (female 3R/3R homozygote or male 3R ∗ hemizygote) were significant. Although not statistically significant, only 3R and 3R/4R genotypes presented cases of severe depression per the revised BDI interpretations. Conclusion. The MAOA uVNTR polymorphism’s low-activity 3R allele presence in an older adult population diagnosed with DM/SAH may represent a risk for developing substance use (alcohol and smoking) dependence.

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“…Text mining involves several steps, including systematic extraction of information from various medical textual resources, visualization, and evaluation [ 11 ]. Text mining has been used in medical research to investigate chronic diseases, genetic disorders, and drug discovery [ 12 ]. Text mining is used to assess genes linked to chronic disease to better understand their biological function and role in disease manifestation [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

Decoding Diabetes Biomarkers and Related Molecular Mechanisms by Using Machine Learning, Text Mining, and Gene Expression Analysis

Elsherbini

Alsamman

Elsherbiny

et al. 2022

IJERPH

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The molecular basis of diabetes mellitus is yet to be fully elucidated. We aimed to identify the most frequently reported and differential expressed genes (DEGs) in diabetes by using bioinformatics approaches. Text mining was used to screen 40,225 article abstracts from diabetes literature. These studies highlighted 5939 diabetes-related genes spread across 22 human chromosomes, with 112 genes mentioned in more than 50 studies. Among these genes, HNF4A, PPARA, VEGFA, TCF7L2, HLA-DRB1, PPARG, NOS3, KCNJ11, PRKAA2, and HNF1A were mentioned in more than 200 articles. These genes are correlated with the regulation of glycogen and polysaccharide, adipogenesis, AGE/RAGE, and macrophage differentiation. Three datasets (44 patients and 57 controls) were subjected to gene expression analysis. The analysis revealed 135 significant DEGs, of which CEACAM6, ENPP4, HDAC5, HPCAL1, PARVG, STYXL1, VPS28, ZBTB33, ZFP37 and CCDC58 were the top 10 DEGs. These genes were enriched in aerobic respiration, T-cell antigen receptor pathway, tricarboxylic acid metabolic process, vitamin D receptor pathway, toll-like receptor signaling, and endoplasmic reticulum (ER) unfolded protein response. The results of text mining and gene expression analyses used as attribute values for machine learning (ML) analysis. The decision tree, extra-tree regressor and random forest algorithms were used in ML analysis to identify unique markers that could be used as diabetes diagnosis tools. These algorithms produced prediction models with accuracy ranges from 0.6364 to 0.88 and overall confidence interval (CI) of 95%. There were 39 biomarkers that could distinguish diabetic and non-diabetic patients, 12 of which were repeated multiple times. The majority of these genes are associated with stress response, signalling regulation, locomotion, cell motility, growth, and muscle adaptation. Machine learning algorithms highlighted the use of the HLA-DQB1 gene as a biomarker for diabetes early detection. Our data mining and gene expression analysis have provided useful information about potential biomarkers in diabetes.

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Identification of genes related to mental disorders by text mining

Abstract: Supplemental Digital Content is available in the text

Cited by 6 publications

References 28 publications

Combined abnormal muscle activity and pain-related factors affect disability in patients with chronic low back pain: An association rule analysis

Combined abnormal muscle activity and pain-related factors affect disability in patients with chronic low back pain: An association rule analysis

MAOA uVNTR Polymorphism Influence on Older Adults Diagnosed with Diabetes Mellitus/Systemic Arterial Hypertension

Decoding Diabetes Biomarkers and Related Molecular Mechanisms by Using Machine Learning, Text Mining, and Gene Expression Analysis

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