Cytochrome P-450 CYP2C19 genetic polymorphism and its relation with clopidogrel resistance.

Objectives: To find out the prevalence of CYP2C19*2 genetic polymorphism in ischaemic heart disease patients, and to determine its relation with clopidogrel resistance in different genotype groups. METHODS: The cross-sectional study was conducted from August 2015 to December 2019 at the Army Medical College, National University of Medical Sciences, Rawalpindi, Pakistan, and comprised ischaemic heart disease patients of either gender who were on clopidogrel therapy. CYP2C19*2 genotyping of all the patients was carried out through polymerase chain reaction-restriction fragment length polymorphism. Platelet aggregation analysis was done using a light transmission aggregometer. Data was analysed using SPSS 23. RESULTS: Of the 390 patients, 232(59.5%) were males and 158(40.5%) were females. The overall age range was 16-82 years. Clinical indications of clopidogrel were angina 198(50.8%), myocardial infarction 146(37.4%) and acute coronary syndrome 46(11.8%). CYP2C19*2 genotyping showed that 196(50.24%) patients were homozygous wild type carriers (GG or *1/*1), 159(40.8%) were heterozygous carriers (GA or *1/*2), and 35(9%) were homozygous polymorphic allele carriers (AA or *2/*2). Platelet aggregation studies showed that there were 157(80.1%) clopidogrel responders and 39(19.9%) clopidogrel-resistant patients among GG carriers, 118(74.2%) clopidogrel responders and 41(25.8%) clopidogrel-resistant among GA carriers, and 18(51.4%) clopidogrel responders and 17(48.6%) clopidogrel-resistant among AA carriers (p=0.001). Intergroup mean platelet aggregation was significantly different (p=0.025). Allelic frequency of dominant allele *1 and polymorphic variant allele *2 was 0.706(70.6%) and 0.294(29.4), respectively. CONCLUSIONS: Homozygous and heterozygous carriers of CYP2C19 allele *2 was found to have higher prevalence of clopidogrel resistance in the studied population.

A Machine Learning Approach for Continuous Mining of Nonidentifiable Smartphone Data to Create a Novel Digital Biomarker Detecting Generalized Anxiety Disorder: Prospective Cohort Study.

BACKGROUND: Anxiety is one of the leading causes of mental health disability around the world. Currently, a majority of the population who experience anxiety go undiagnosed or untreated. New and innovative ways of diagnosing and monitoring anxiety have emerged using smartphone sensor-based monitoring as a metric for the management of anxiety. This is a novel study as it adds to the field of research through the use of nonidentifiable smartphone usage to help detect and monitor anxiety remotely and in a continuous and passive manner. OBJECTIVE: This study aims to evaluate the accuracy of a novel mental behavioral profiling metric derived from smartphone usage for the identification and tracking of generalized anxiety disorder (GAD). METHODS: Smartphone data and self-reported 7-item GAD anxiety assessments were collected from 229 participants using an Android operating system smartphone in an observational study over an average of 14 days (SD 29.8). A total of 34 features were mined to be constructed as a potential digital phenotyping marker from continuous smartphone usage data. We further analyzed the correlation of these digital behavioral markers against each item of the 7-item Generalized Anxiety Disorder Scale (GAD-7) and its influence on the predictions of machine learning algorithms. RESULTS: A total of 229 participants were recruited in this study who had completed the GAD-7 assessment and had at least one set of passive digital data collected within a 24-hour period. The mean GAD-7 score was 11.8 (SD 5.7). Regression modeling was tested against classification modeling and the highest prediction accuracy was achieved from a binary XGBoost classification model (precision of 73%-81%; recall of 68%-87%; F1-score of 71%-79%; accuracy of 76%; area under the curve of 80%). Nonparametric permutation testing with Pearson correlation results indicated that the proposed metric (Mental Health Similarity Score [MHSS]) had a colinear relationship between GAD-7 Items 1, 3 and 7. CONCLUSIONS: The proposed MHSS metric demonstrates the feasibility of using passively collected nonintrusive smartphone data and machine learning-based data mining techniques to track an individuals' daily anxiety levels with a 76% accuracy that directly relates to the GAD-7 scale.

Dysregulated Autophagy Leads to Oxidative Stress and Aberrant Expression of ABC Transporters in Women with Early Miscarriage.

Early miscarriage (EMC) is a devastating obstetrical complication. ATP-binding cassette (ABC) transporters mediate cholesterol transfer across the placenta and enhance cell survival by effluxing substrates from target cells in the presence of stressors. Recent evidence reports an intricate interplay between autophagy and ABC transporters. We hypothesized that dysregulated autophagy and oxidative stress (OS) in the placenta leads to abnormal expression of membrane transporters contributing to poor pregnancy survival in EMC. We determined mRNA and protein expression of autophagy genes (Beclin-1/Bcl-2/LC3I/LC3II/p62) and ABC transporters (ABCA1/ABCG1/ABCG2) in placentae from EMC patients (n = 20), term controls (n = 19), first trimester (n = 6), and term controls (n = 5) controls. Oxidative/antioxidant status and biomarkers of oxidative damage were evaluated in maternal serum and placentae from EMC and healthy controls. In EMC, placental expression of LC3II/LC3I as well as of the key autophagy regulatory proteins Beclin-1 and Bcl-2 were reduced, whereas p62 was increased. Both in the serum and placentae of EMC patients, total OS was elevated reflected by increased oxidative damage markers (8-OHdG/malondialdehyde/carbonyl formation) accompanied by diminished levels of total antioxidant status, catalase, and total glutathione. Furthermore, we found reduced ABCG1 and increased ABCG2 expression. These findings suggest that a decreased autophagy status triggers Bcl-2-dependent OS leading to macromolecule damage in EMC placentae. The decreased expression of ABCG1 contributes to reduced cholesterol export to the growing fetus. Increasing ABCG2 expression could represent a protective feedback mechanism under inhibited autophagy conditions. In conclusion, dysregulated autophagy combined with increased oxidative toxicity and aberrant expression of placental ABC transporters affects materno-fetal health in EMC.