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Frontiers in Neurology 2021Parkinson's disease (PD) is a common, chronic, progressive, debilitating neurodegenerative disease. The current levodopa treatment requires the addition of other drugs,...
Parkinson's disease (PD) is a common, chronic, progressive, debilitating neurodegenerative disease. The current levodopa treatment requires the addition of other drugs, such as catechol-O-methyl transferase (COMT) inhibitors, to alleviate motor fluctuations in advanced PD. Therefore, a theoretical reference for treatment is urgently needed. In this study, an appropriate search strategy was used to screen eligible studies on different drugs to treat patients with PD from the Embase, PubMed, and Cochrane Library. The publication dates were from January 1990 to June 2021. We integrated eligible randomized controlled trials, and statistical analysis was performed on three kinds of effectiveness outcomes and two types of safety outcomes. We assessed the average difference or odds ratio between each drug and placebo and summarized them as the average and 95% confidence interval (CI), respectively. In terms of efficacy, entacapone (mean difference [MD], 0.64 h; 95% CI, 0.29-1.0), opicapone (MD, 0.92 h; 95% CI, 0.35-1.5), and tolcapone (MD, 3.2 h; 95% CI, 2.1-4.2) increased patients' total ON-time compared to placebo. Tolcapone (MD, -100 mg; 95% CI -160 to -45) reduced the total daily dose of levodopa therapy. None of these three drugs was found to have statistical significance in mean change from baseline in UPDRS part III scores when compared with others. In terms of safety, tolcapone (MD, 3.8; 95% CI, 2.1-6.8), opicapone (MD, 3.7; 95% CI, 2-7.2), and entacapone (MD, 2.2; 95% CI, 1.5-3.3) increased the number of cases of dyskinesia compared to placebo. Entacapone (MD, 1.7; 95% CI, 1.3-2.2) and tolcapone (MD, 4.3; 95% CI, 1.3-15) were more likely to cause adverse events than placebo. In conclusion, opicapone showed higher efficiency and fewer safety problems in five indicators we selected when compared with the other two drugs.
PubMed: 34630283
DOI: 10.3389/fneur.2021.707723 -
Progress in Neuro-psychopharmacology &... Feb 2024SETD1A encodes a histone methyltransferase involved in various cell cycle regulatory processes. Loss-of-function SETD1A variants have been associated with numerous... (Review)
Review
OBJECTIVE
SETD1A encodes a histone methyltransferase involved in various cell cycle regulatory processes. Loss-of-function SETD1A variants have been associated with numerous neurodevelopmental phenotypes, including intellectual disability and schizophrenia. While the association between rare coding variants in SETD1A and schizophrenia has achieved genome-wide significance by rare variant burden testing, only a few studies have described the psychiatric phenomenology of such individuals in detail. This systematic review and case report aims to characterize the neurodevelopmental and psychiatric phenotypes of SETD1A variant-associated schizophrenia.
METHODS
A PubMed search was completed in July 2022 and updated in May 2023. Only studies that reported individuals with a SETD1A variant as well as a primary psychotic disorder were ultimately included. Additionally, another two previously unpublished cases of SETD1A variant-associated psychosis from our own sequencing cohort are described.
RESULTS
The search yielded 32 articles. While 15 articles met inclusion criteria, only five provided case descriptions. In total, phenotypic information was available for 11 individuals, in addition to our own two unpublished cases. Our findings suggest that although individuals with SETD1A variant-associated schizophrenia may share a number of common features, phenotypic variability nonetheless exists. Moreover, although such individuals may exhibit numerous other neurodevelopmental features suggestive of the syndrome, their psychiatric presentations appear to be similar to those of general schizophrenia populations.
CONCLUSIONS
Loss-of-function SETD1A variants may underlie the development of psychosis in a small percentage of individuals with schizophrenia. Identifying such individuals may become increasingly important, given the potential for advances in precision medicine treatment approaches.
Topics: Humans; Genetic Predisposition to Disease; Intellectual Disability; Phenotype; Psychotic Disorders; Schizophrenia
PubMed: 37918557
DOI: 10.1016/j.pnpbp.2023.110888 -
Frontiers in Genetics 2019There is a continued debate and inconsistent findings in previous literature about the relationship of catechol-O-methyltransferase (COMT) and Parkinson's disease (PD)...
There is a continued debate and inconsistent findings in previous literature about the relationship of catechol-O-methyltransferase (COMT) and Parkinson's disease (PD) susceptibility as well as cognitive dysfunction. To substantiate this existing gap, we comprehensively examine COMT genotype effects on the development of PD and test the hypothesis that the Met158 allele of the COMT gene is associated with cognitive dysfunction by conducting a meta-analysis review. PubMed/MEDLINE, Embase, Cochrane databases search (18/30/08) yielded 49 included studies. Data were extracted by two reviewers and included COMT genotype, publication year, diagnostic status, ancestry, the proportion of male participants, and whether genotype frequencies were consistent with Hardy-Weinberg equilibrium. Unadjusted odds ratios (ORs) were used to derive pooled estimates of PD risk overall and in subgroups defined by ethnicity, gender, and onset of disease. Moreover, the association of certain cognitive domains in PD and COMT gene type was explored. Meta-analyses were performed using random-effect models and value-based methods. All statistical tests were two-sided. The present study was registered with PROSPERO (CRD42018087323). In the current studies, we found no association between COMT Val158/108Met polymorphism and PD susceptibility. However, the gender-stratified analyses revealed marginally significant effects in heterozygote model analyses in women ( = 0.053). In addition, stratification according to onset of PD also shows significant effects of COMT Val158/108Met polymorphism on late-onset population both in recessive ( = 0.017) and allelic ( = 0.017) genetic models. For the intelligence quotient (IQ) score and Unified Parkinson Disease Rating Scale III (UPDRS III), there was no evidence for genetic association, except in subgroup analyses in Asian populations (IQ score, = 0.016; UPDRS III, < 0.001). The COMT Val158/108Met polymorphism is associated with the risk for PD in female or late-onset PD. Methionine/methionine carriers of Asian population performed significantly worse than the valine allele carriers in IQ score and UPDRS III.
PubMed: 31354790
DOI: 10.3389/fgene.2019.00644 -
Bioscience Reports Mar 2020O6-methylguanine-DNA methyltransferase (MGMT) is a specific DNA damage reversal repair protein. The influence of MGMT status on alkylating agent sensitivity in patients... (Meta-Analysis)
Meta-Analysis
BACKGROUND
O6-methylguanine-DNA methyltransferase (MGMT) is a specific DNA damage reversal repair protein. The influence of MGMT status on alkylating agent sensitivity in patients with neuroendocrine neoplasms (NENs) is controversial. We conducted a meta-analysis to assess the influence of MGMT status on the therapeutic sensitivity of alkylating agents in patients with NENs.
METHODS
We searched PubMed, EmBase, and Cochrane library public databases through 3 July 2019. The objective response rate (ORR) was the outcome data of interest. Subgroup analysis was performed according based on MGMT methylation and expression of MGMT protein.
RESULTS
Eleven studies were included in the meta-analysis. The proportion of patients with NENs that achieved an ORR after alkylating agent treatment was higher in the MGMT-deficient group than the non-deficient group (OR: 5.00; 95% CI: 3.04-8.22; P < 0.001; I2: 3%). Similar results were noted in the MGMT methylation and MGMT protein expression subgroups.
CONCLUSION
Patients with NENs and MGMT methylation or low protein expression had a higher ORR proportion than patients without MGMT methylation or high protein expression. The MGMT status can be used as a biological indicator of the response to alkylating agent treatment in patients with NENs.
Topics: Antineoplastic Agents, Alkylating; DNA Methylation; DNA Modification Methylases; DNA Repair Enzymes; Humans; Neuroendocrine Tumors; Promoter Regions, Genetic; Treatment Outcome; Tumor Suppressor Proteins
PubMed: 32141507
DOI: 10.1042/BSR20194127 -
Cancer Control : Journal of the Moffitt... 2021Recent studies have shown that methyltransferase-like 3, a catalytic enzyme that is predominant in the N6-methyladenosine methyltransferase system, is abnormally... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Recent studies have shown that methyltransferase-like 3, a catalytic enzyme that is predominant in the N6-methyladenosine methyltransferase system, is abnormally expressed in various types of carcinoma and is correlated with poorer prognosis. However, the clinical functions of methyltransferase-like 3 in the prognosis of tumors are not fully understood.
METHODS
We identified studies by searching PubMed, Web of Science, and MedRvix for literature (up to June 30, 2020), and collected a total of 9 studies with 1257 patients for this meta-analysis. The cancer types included gastric cancer, breast cancer, non-small cell lung cancer, bladder cancer, colorectal cancer and ovarian. We further used The Cancer Genome Atlas dataset to validate the results.
RESULTS
High methyltransferase-like 3 expression clearly predicted a worse outcome (high vs. low methyltransferase-like 3 expression group; hazard ratio = 2.09, 95% confidence interval 1.53-2.89, = 0.0001). Moreover, methyltransferase-like 3 expression was associated with differentiation (moderate + poor vs. well, pooled odds ratio = 1.76, 95% confidence interval 1.32-2.35, = 0.0001), and gender (male vs. female, pooled odds ratio = 0.73, 95% confidence interval 0.55-0.97, = 0.029).
CONCLUSION
Our results suggest that methyltransferase-like 3 upregulation is significantly associated with poor prognosis and could potentially function as a tumor biomarker in cancer prognosis.
Topics: Adenosine; Female; Humans; Male; Methyltransferases; Neoplasms; Prognosis; Survival Analysis
PubMed: 33631954
DOI: 10.1177/1073274821997455 -
Journal of Cancer Research and Clinical... Jan 2024Accurate and non-invasive estimation of MGMT promoter methylation status in glioblastoma (GBM) patients is of paramount clinical importance, as it is a predictive... (Review)
Review
BACKGROUND
Accurate and non-invasive estimation of MGMT promoter methylation status in glioblastoma (GBM) patients is of paramount clinical importance, as it is a predictive biomarker associated with improved overall survival (OS). In response to the clinical need, recent studies have focused on the development of non-invasive artificial intelligence (AI)-based methods for MGMT estimation. In this systematic review, we not only delve into the technical aspects of these AI-driven MGMT estimation methods but also emphasize their profound clinical implications. Specifically, we explore the potential impact of accurate non-invasive MGMT estimation on GBM patient care and treatment decisions.
METHODS
Employing a PRISMA search strategy, we identified 33 relevant studies from reputable databases, including PubMed, ScienceDirect, Google Scholar, and IEEE Explore. These studies were comprehensively assessed using 21 diverse attributes, encompassing factors such as types of imaging modalities, machine learning (ML) methods, and cohort sizes, with clear rationales for attribute scoring. Subsequently, we ranked these studies and established a cutoff value to categorize them into low-bias and high-bias groups.
RESULTS
By analyzing the 'cumulative plot of mean score' and the 'frequency plot curve' of the studies, we determined a cutoff value of 6.00. A higher mean score indicated a lower risk of bias, with studies scoring above the cutoff mark categorized as low-bias (73%), while 27% fell into the high-bias category.
CONCLUSION
Our findings underscore the immense potential of AI-based machine learning (ML) and deep learning (DL) methods in non-invasively determining MGMT promoter methylation status. Importantly, the clinical significance of these AI-driven advancements lies in their capacity to transform GBM patient care by providing accurate and timely information for treatment decisions. However, the translation of these technical advancements into clinical practice presents challenges, including the need for large multi-institutional cohorts and the integration of diverse data types. Addressing these challenges will be critical in realizing the full potential of AI in improving the reliability and accessibility of MGMT estimation while lowering the risk of bias in clinical decision-making.
Topics: Humans; Glioblastoma; Artificial Intelligence; Reproducibility of Results; DNA Methylation; Brain Neoplasms; DNA Modification Methylases; DNA Repair Enzymes; DNA; Tumor Suppressor Proteins
PubMed: 38291266
DOI: 10.1007/s00432-023-05566-5 -
Medicine Nov 2020The results of published articles on the relationship between the Val158Met polymorphism in the (Catechol-O-methyltransferase) COMT gene and the susceptibility of... (Meta-Analysis)
Meta-Analysis
BACKGROUND
The results of published articles on the relationship between the Val158Met polymorphism in the (Catechol-O-methyltransferase) COMT gene and the susceptibility of attention-deficit hyperactive disorder (ADHD) are controversial. We conducted an updated meta-analysis of case-control studies to assess the relationship between Val158Met polymorphism in COMT gene and ADHD susceptibility.
METHODS
A comprehensive literature search was conducted to identify all the case-control studies on the relationship between the COMT gene Val158Met polymorphism and ADHD susceptibility. According to the heterogeneity test results among studies evaluated with I, the fixed effect model or random effect model was selected as the pooling method. Meta-regression as well as sensitive analysis were used to explore possible causes of between-study heterogeneity. The funnel plot and Harbord test were used to estimate publication bias.
RESULTS
Finally, seventeen studies that met the inclusion criteria were included. The Val158Met genotype distributions of COMT gene in controls were in Hardy-Weinberg equilibrium in all studies. In general, there was no significant association between the COMT gene Val158Met polymorphism and ADHD susceptibility in dominant, recessive, and codominant models. The recessive genetic model (I = 60.8%) showed strong heterogeneity among studies, and still no significant association was found after sensitivity analysis. Subgroup analysis stratified by ethnicity (Asian and Caucasian) also showed that there was no significant association in the above-mentioned three models.
CONCLUSIONS
This updated meta-analysis indicated that the Val158Met polymorphism in the COMT gene may not be related to the risk of ADHD. Further researches are needed to confirm these results.
Topics: Attention Deficit Disorder with Hyperactivity; Catechol O-Methyltransferase; Genetic Predisposition to Disease; Genotype; Humans; Polymorphism, Single Nucleotide
PubMed: 33235119
DOI: 10.1097/MD.0000000000023400 -
PloS One 2022Analytic approaches to clinical validation of results from preclinical models are important in assessment of their relevance to human disease. This systematic review...
INTRODUCTION
Analytic approaches to clinical validation of results from preclinical models are important in assessment of their relevance to human disease. This systematic review examined consistency in reporting of glioblastoma cohorts from The Cancer Genome Atlas (TCGA) or Chinese Glioma Genome Atlas (CGGA) and assessed whether studies included patient characteristics in their survival analyses.
METHODS
We searched Embase and Medline on 02Feb21 for studies using preclinical models of glioblastoma published after Jan2008 that used data from TCGA or CGGA to validate the association between at least one molecular marker and overall survival in adult patients with glioblastoma. Main data items included cohort characteristics, statistical significance of the survival analysis, and model covariates.
RESULTS
There were 58 eligible studies from 1,751 non-duplicate records investigating 126 individual molecular markers. In 14 studies published between 2017 and 2020 using TCGA RNA microarray data that should have the same cohort, the median number of patients was 464.5 (interquartile range 220.5-525). Of the 15 molecular markers that underwent more than one univariable or multivariable survival analyses, five had discrepancies between studies. Covariates used in the 17 studies that used multivariable survival analyses were age (76.5%), pre-operative functional status (35.3%), sex (29.4%) MGMT promoter methylation (29.4%), radiotherapy (23.5%), chemotherapy (17.6%), IDH mutation (17.6%) and extent of resection (5.9%).
CONCLUSION
Preclinical glioblastoma studies that used TCGA for validation did not provide sufficient information about their cohort selection and there were inconsistent results. Transparency in reporting and the use of analytic approaches that adjust for clinical variables can improve the reproducibility between studies.
Topics: Adult; Brain Neoplasms; DNA Methylation; DNA Modification Methylases; DNA Repair Enzymes; Glioblastoma; Glioma; Humans; Prognosis; Reproducibility of Results
PubMed: 35231064
DOI: 10.1371/journal.pone.0264740 -
European Radiology Feb 2024To evaluate the methodological quality and diagnostic accuracy of MRI-based radiomic studies predicting O6-methylguanine-DNA methyltransferase (MGMT) promoter...
OBJECTIVES
To evaluate the methodological quality and diagnostic accuracy of MRI-based radiomic studies predicting O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status in gliomas.
METHODS
PubMed Medline, EMBASE, and Web of Science were searched to identify MRI-based radiomic studies on MGMT methylation in gliomas published until December 31, 2022. Three raters evaluated the study methodological quality with Radiomics Quality Score (RQS, 16 components) and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis Or Diagnosis (TRIPOD, 22 items) scales. Risk of bias and applicability concerns were assessed with QUADAS-2 tool. A meta-analysis was performed to estimate the pooled area under the curve (AUC) and to assess inter-study heterogeneity.
RESULTS
We included 26 studies, published from 2016. The median RQS total score was 8 out of 36 (22%, range 8-44%). Thirteen studies performed external validation. All studies reported AUC or accuracy, but only 4 (15%) performed calibration and decision curve analysis. No studies performed phantom analysis, cost-effectiveness analysis, and prospective validation. The overall TRIPOD adherence score was between 50% and 70% in 16 studies and below 50% in 10 studies. The pooled AUC was 0.78 (95% CI, 0.73-0.83, I = 94.1%) with a high inter-study heterogeneity. Studies with external validation and including only WHO-grade IV gliomas had significantly lower AUC values (0.65; 95% CI, 0.57-0.73, p < 0.01).
CONCLUSIONS
Study RQS and adherence to TRIPOD guidelines was generally low. Radiomic prediction of MGMT methylation status showed great heterogeneity of results and lower performances in grade IV gliomas, which hinders its current implementation in clinical practice.
CLINICAL RELEVANCE STATEMENT
MGMT promoter methylation status appears to be variably correlated with MRI radiomic features; radiomic models are not sufficiently robust to be integrated into clinical practice to accurately predict MGMT promoter methylation status in patients with glioma before surgery.
KEY POINTS
• Adherence to the indications of TRIPOD guidelines was generally low, as was RQS total score. • MGMT promoter methylation status prediction with MRI radiomic features provided heterogeneous diagnostic accuracy results across studies. • Studies that included grade IV glioma only and performed external validation had significantly lower diagnostic accuracy than others.
PubMed: 38308012
DOI: 10.1007/s00330-024-10594-x -
BMC Genomics Dec 2022Modern human brains and skull shapes differ from other hominids. Brain growth disorders as micro- (ASPM, MCPH1) and macrocephaly (NFIX, GLI3) have been highlighted as...
BACKGROUND
Modern human brains and skull shapes differ from other hominids. Brain growth disorders as micro- (ASPM, MCPH1) and macrocephaly (NFIX, GLI3) have been highlighted as relevant for the evolution in humans due to the impact in early brain development. Genes associated with macrocephaly have been reported to cause this change, for example NSD1 which causes Sotos syndrome.
RESULTS
In this study we performed a systematic literature review, located the reported variants associated to Sotos syndrome along the gene domains, compared the sequences with close primates, calculated their similarity, Ka/Ks ratios, nucleotide diversity and selection, and analyzed the sequence and structural conservation with distant primates. We aimed to understand if NSD1 in humans differs from other primates since the evolution of NSD1 has not been analyzed in primates, nor if the localization of the mutations is limited to humans. Our study found that most variations causing Sotos syndrome are in exon 19, 22 and 10. In the primate comparison we did not detect Ka/Ks ratios > 1, but a high nucleotide diversity with non-synonymous variations in exons 10, 5, 9, 11 and 23, and sites under episodic selection in exon 5 and 23, and human, macaque/colobus/tarsier/galago and tarsier/lemur/colobus. Most of the domains are conserved in distant primates with a particular progressive development from a simple PWWP1 in O. garnetti to a complex structure in Human.
CONCLUSION
NSD1 is a chromatin modifier that suggests that the selection could influence brain development during modern human evolution and is not present in other primates; however, nowadays the nucleotide diversity is associated with Sotos syndrome.
Topics: Humans; Animals; Sotos Syndrome; Histone Methyltransferases; Histone-Lysine N-Methyltransferase; Tarsiidae; Colobus; Nuclear Proteins; Mutation; Exons; Hominidae; Megalencephaly; Nucleotides; Cytoskeletal Proteins; Cell Cycle Proteins
PubMed: 36550402
DOI: 10.1186/s12864-022-09071-w