Decoding 2.3 million ECGs: interpretable deep learning for advancing cardiovascular diagnosis and mortality risk stratification.

Aims: Electrocardiogram (ECG) is widely considered the primary test for evaluating cardiovascular diseases. However, the use of artificial intelligence (AI) to advance these medical practices and learn new clinical insights from ECGs remains largely unexplored. We hypothesize that AI models with a specific design can provide fine-grained interpretation of ECGs to advance cardiovascular diagnosis, stratify mortality risks, and identify new clinically useful information. Methods and results: Utilizing a data set of 2 322 513 ECGs collected from 1 558 772 patients with 7 years follow-up, we developed a deep-learning model with state-of-the-art granularity for the interpretable diagnosis of cardiac abnormalities, gender identification, and hypertension screening solely from ECGs, which are then used to stratify the risk of mortality. The model achieved the area under the receiver operating characteristic curve (AUC) scores of 0.998 (95% confidence interval (CI), 0.995-0.999), 0.964 (95% CI, 0.963-0.965), and 0.839 (95% CI, 0.837-0.841) for the three diagnostic tasks separately. Using ECG-predicted results, we find high risks of mortality for subjects with sinus tachycardia (adjusted hazard ratio (HR) of 2.24, 1.96-2.57), and atrial fibrillation (adjusted HR of 2.22, 1.99-2.48). We further use salient morphologies produced by the deep-learning model to identify key ECG leads that achieved similar performance for the three diagnoses, and we find that the V1 ECG lead is important for hypertension screening and mortality risk stratification of hypertensive cohorts, with an AUC of 0.816 (0.814-0.818) and a univariate HR of 1.70 (1.61-1.79) for the two tasks separately. Conclusion: Using ECGs alone, our developed model showed cardiologist-level accuracy in interpretable cardiac diagnosis and the advancement in mortality risk stratification. In addition, it demonstrated the potential to facilitate clinical knowledge discovery for gender and hypertension detection which are not readily available.

Association between Negative Life Events and Somatic Symptoms: A Mediation Model through Self-Esteem and Depression.

The purpose of this study was to investigate the serial multiple mediation of self-esteem and depression in the relationship between negative life events and somatic symptoms in Chinese medical students. We recruited a total of 3383 medical students for this study, and used the Patient Health Questionnaire-15 to assess the somatic symptoms of subjects; the Adolescent Self-Rating Life Events Check List to assess negative life events; the Rosenberg Self-Esteem Scale to assess self-esteem; and the Patient Health Questionnaire for depression. Descriptive analysis and statistical tests were then performed on the collected data. We showed that 39.17% of the medical students had mild somatic symptoms, 24.14% had moderate somatic symptoms, and 5.66% had severe somatic symptoms; we observed significant differences in somatic symptoms among genders, living expenses, and one-child. For negative life events, interpersonal stress was the most important predictor of somatization during the regression analysis. In addition, we observed significance for both the direct and part of the indirect paths from negative life events to somatic symptoms using mediation model analysis. However, we noted that there was no significance for the path through negative life events and self-esteem to somatic symptoms. This study revealed a high prevalence of somatic symptoms among Chinese medical students, and the findings suggested that interventions aimed at reducing somatization in this population should consider the impact of negative life events, particularly those related to interpersonal stress. One potential approach to mitigating the effects of negative life events on somatization is to enhance self-esteem and decrease the level of depression among medical students.

Sleep quality and creativity in Chinese college student during the COVID-19 pandemic: The mediating role of executive function.

Background: COVID-19 has impacted adolescents' interpersonal relationships, life attitudes, and mental health during the past 3 years. However, previous studies predominantly focused on negative problems, while few studies assessed the situation of teenagers from the perspective of positive psychology. Therefore, this study explores the creativity level of Chinese college students during the COVID-19 pandemic, the relationship between sleep quality and creativity, and the mediating role of executive function. Method: A cross-sectional study was conducted across six colleges in Heilongjiang in China, with a sample of 4,258 college students recruited via stratified cluster sampling. Data were collected through an online survey. A mediation model was constructed, and SPSS PROCESS macro was used to analyze the data. Results: The creativity score of Chinese college students during the COVID-19 pandemic was 106.48 ± 13.61. Correlation analysis demonstrated that sleep quality correlated negatively with creativity (r = -0.08, P < 0.01) but positively with executive function (r=0.45, P < 0.01), whilst executive function correlated negatively with creativity (r = -0.10, P < 0.01). Moreover, the mediation model revealed that executive function partially mediated the relationship between sleep quality and creativity in college students (indirect effect = -0.017, SE = 0.004, 95% CI = [-0.025, -0.008]). Executive function accounted for 48.6% of the variance in college students' creativity. Conclusion: School administrators should implement measures such as sleep education to enhance students' sleep quality. Concurrently, curriculum and assessment implementation should enhance executive function. Such measures can contribute to improved student creativity, thus helping students overcome the negative emotional impact of the COVID-19 pandemic.

Exploration of Psychological Mechanism of Smartphone Addiction Among International Students of China by Selecting the Framework of the I-PACE Model.

The I-PACE (interaction of person-affect-cognition-execution) model explains that the causes of addiction are the result of individual susceptibility (genetic and personality), psychopathological factors (negative emotions), and cognitive and affective factor interaction. The issue of smartphone addiction and its emerging effects are now becoming an essential social enigma. This study is aimed at exploring how personal, affective, cognitive, and execution factors accelerate the mechanism of smartphone addiction among international students. Randomly selected, six hundred international students have constituted the population for our study. All participants were asked to complete self-administered questionnaires. The questionnaire included demographics (gender, place of stay, educational level, and reason for smartphone usage), Mobile Phone Addiction Index, Loneliness Scale (UCLA), Rosenberg Self-Esteem Scale, Beck Depression Inventory, Perceived Stress Scale, Eysenck Personality Questionnaire, and Simplified Coping Style Questionnaire. Statistical analysis was performed using SPSS. 20.3% (n = 122) of international students are agonized with smartphone addiction, while 79.7% (n = 478) use smartphones at an average level. Students' place of stay, neuroticism personality, social desirability, self-esteem, loneliness, depression, perceived stress, and passive coping are associated with smartphone addiction. Loneliness and depression show a strong positive significant correlation, among other variables while loneliness, neurotic personality, depression, low self-esteem, stress, and passive coping are risk factors for smartphone addiction. This study reveals that international students are a high-risk group for smartphone addiction. It has a great deal of impact on students' behavior and psyche. Multiple social, psychological, affective, and cognitive factors affect smartphone addiction. It would be beneficial to direct the students to limit their phone usage and indulge in other healthy physical activities to complete academic goals.

Roles of Anxiety and Depression in Predicting Cardiovascular Disease Among Patients With Type 2 Diabetes Mellitus: A Machine Learning Approach.

Cardiovascular disease (CVD) is a major complication of type 2 diabetes mellitus (T2DM). In addition to traditional risk factors, psychological determinants play an important role in CVD risk. This study applied Deep Neural Network (DNN) to develop a CVD risk prediction model and explored the bio-psycho-social contributors to the CVD risk among patients with T2DM. From 2017 to 2020, 834 patients with T2DM were recruited from the Department of Endocrinology, Affiliated Hospital of Harbin Medical University, China. In this cross-sectional study, the patients' bio-psycho-social information was collected through clinical examinations and questionnaires. The dataset was randomly split into a 75% train set and a 25% test set. DNN was implemented at the best performance on the train set and applied on the test set. The receiver operating characteristic curve (ROC) analysis was used to evaluate the model performance. Of participants, 272 (32.6%) were diagnosed with CVD. The developed ensemble model for CVD risk achieved an area under curve score of 0.91, accuracy of 87.50%, sensitivity of 88.06%, and specificity of 87.23%. Among patients with T2DM, the top five predictors in the CVD risk model were body mass index, anxiety, depression, total cholesterol, and systolic blood pressure. In summary, machine learning models can provide an automated identification mechanism for patients at CVD risk. Integrated treatment measures should be taken in health management, including clinical care, mental health improvement, and health behavior promotion.

The Impact of Transformational Leadership on Physicians' Performance in China: A Cross-Level Mediation Model.

Transformational leadership has been becoming increasingly vital to the provision of high-quality health care, particularly during major public health emergencies. The present study aims to investigate the impact of transformational leadership on physicians' performance and explore the cross-level underlying mechanisms with achievement motivations and coping styles among Chinese physicians. During 2017-2019, 1,527 physicians of 101 departments were recruited from six hospitals in China with a cluster random sampling method. Participants completed several questionnaires regarding their job performance, achievement motivations, coping styles, and transformational leadership. Multilevel mediation effects were tested using cross-level path analysis. The result of this study indicated that transformational leadership was applied well in Chinese medical settings with a score of 101.56 ± 6.42. The hierarchical linear model showed that transformational leadership had a cross-level direct positive effect on physicians' performance (ß = 1.524, p < 0.05). Furthermore, results of cross-level path analyses revealed that transformational leadership contributed to physicians' performance by sequentially influencing achievement motivations first and then coping styles. In addition, the path "transformational leadership → positive coping (PC) style → physicians' performance" showed the strongest cross-level indirect effect. In summary, public health leaders should enhance physicians' performance by promoting individual development, especially achievement motivation and PC style.

Social Support and Suicide Risk Among Chinese University Students: A Mental Health Perspective.

Background: World Health Organization recognizes suicide as a public health priority. This study aimed to investigate the risk life events which led university students to consider suicide and explore the protective mechanism of social support (including subjective support, objective support, and support utilization) on suicide risk. Methods: Three thousand nine hundred and seventy-two university students were recruited in Harbin, China. Social Support Rating Scale, Self-Rating Anxiety Scale, the Beck Depression Inventory, and the 25-item scale of suicide acceptability were used to collect participants' information. Descriptive statistics, Pearson's correlation, and mediation analysis were employed for statistical analysis. Results: "Drug addict," "infected with HIV," and "incurable illness" were the top three events that led university students to consider suicide. Social support played an important protective role against suicide risk. Subjective support and support utilization had total effects on suicide acceptability, including direct and indirect effects. Anxiety (indirect effect = -0.022, 95% CI = -0.037 ~ -0.009) and depressive symptoms (indirect effect = -0.197, 95% CI = -0.228 ~ -0.163) mediated the relationship between subjective support and suicide acceptability; meanwhile, the association between support utilization and suicide acceptability was mediated by anxiety (indirect effect = -0.054, 95% CI = -0.088 ~ -0.024) and depressive symptoms (indirect effect = -0.486, 95% CI = -0.558 ~ -0.422). However, the protective impact of objective support worked totally through decreasing anxiety (indirect effect = -0.018, 95% CI = -0.035 ~ -0.006) and depressive symptoms (indirect effect = -0.196, 95% CI = -0.246 ~ -0.143). Moreover, the mediation effects of depressive symptoms had stronger power than anxiety in the impact of social support on suicide risk. Conclusions: Among Chinese university students, suicide acceptability was elevated when there was a health scare. Social support effectively reduced suicide risk via decreasing anxiety and depressive symptoms. From the mental health perspective, families, peers, teachers, and communities should work together to establish a better social support system for university students, if necessary, help them to seek professional psychological services.

Evaluating Rehabilitation Progress Using Motion Features Identified by Machine Learning.

Evaluating progress throughout a patient's rehabilitation episode is critical for determining the effectiveness of the selected treatments and is an essential ingredient in personalised and evidence-based rehabilitation practice. The evaluation process is complex due to the inherently large human variations in motor recovery and the limitations of commonly used clinical measurement tools. Information recorded during a robot-assisted rehabilitation process can provide an effective means to continuously quantitatively assess movement performance and rehabilitation progress. However, selecting appropriate motion features for rehabilitation evaluation has always been challenging. This paper exploits unsupervised feature learning techniques to reduce the complexity of building the evaluation model of patients' progress. A new feature learning technique is developed to select the most significant features from a large amount of kinematic features measured from robotics, providing clinically useful information to health practitioners with reduction of modeling complexity. A novel indicator that uses monotonicity and trendability is proposed to evaluate kinematic features. The data used to develop the feature selection technique consist of kinematic data from robot-aided rehabilitation for a population of stroke patients. The selected kinematic features allow for human variations across a population of patients as well as over the sequence of rehabilitation sessions. The study is based on data records pertaining to 41 stroke patients using three different robot assisted exercises for upper limb rehabilitation. Consistent with the literature, the results indicate that features based on movement smoothness are the best measures among 17 kinematic features suitable to evaluate rehabilitation progress.

Relationship between Illness Perception and Depressive Symptoms among Type 2 Diabetes Mellitus Patients in China: A Mediating Role of Coping Style.

OBJECTIVE: The aims of the present study were to investigate the prevalence of depressive symptoms among type 2 diabetes mellitus (T2DM) patients in China and to explore how coping style influences the relationship between illness perception and depressive symptoms. METHODS: Nine hundred and thirty-nine T2DM patients were recruited from a grade 3 Class A hospital in Harbin, China, and asked to complete a demographic questionnaire as well as the Self-rating Depression Scale (SDS), Brief Illness Perception Questionnaire-Revised (IPQ-R), and Medical Coping Modes Questionnaire (MCMQ). Hierarchical linear regression analysis and the bootstrap method were preformed to examine if coping style influenced the relationship between illness perception and depression. RESULTS: The majority of patients (73.59%) exhibited depressive symptoms, including 37.27% with moderate and 6.71% with severe depressive symptoms. Depressive symptoms were more frequent in patients with complications (P < 0.05). A resignation coping style partially mediated the influence of illness perception on depressive symptoms. CONCLUSIONS: Interventions to improve coping style may reduce the prevalence or severity of depressive symptoms among T2DM patients, potentially enhancing treatment adherence and clinical outcome.

Association Between FoxO1, A2M, and TGF-ß1, Environmental Factors, and Major Depressive Disorder.

INTRODUCTION: Investigations of gene-environment (G×E) interactions in major depressive disorder (MDD) have been limited to hypothesis testing of candidate genes while poly-gene-environmental causation has not been adequately address. To this end, the present study analyzed the association between three candidate genes, two environmental factors, and MDD using a hypothesis-free testing approach. METHODS: A logistic regression model was used to analyze interaction effects; a hierarchical regression model was used to evaluate the effects of different genotypes and the dose-response effects of the environment; genetic risk score (GRS) was used to estimate the cumulative contribution of genetic factors to MDD; and protein-protein interaction (PPI) analyses were carried out to evaluate the relationship between candidate genes and top MDD susceptibility genes. RESULTS: Allelic association analyses revealed significant effects of the interaction between the candidate genes Forkhead box (Fox)O1, α2-macroglobulin (A2M), and transforming growth factor (TGF)-ß1 genes and the environment on MDD. Gene-gene (G×G) and gene-gene-environment (G×G×E) interactions in MDD were also included in the model. Hierarchical regression analysis showed that the effect of environmental factors on MDD was greater in homozygous than in heterozygous mutant genotypes of the FoxO1 and TGF-ß1 genes; a dose-response effect between environment and MDD on genotypes was also included in this model. Haplotype analyses revealed significant global and individual effects of haplotypes on MDD in the whole sample as well as in subgroups. There was a significant association between GRS and MDD (P = 0.029) and a GRS and environment interaction effect on MDD (P = 0.009). Candidate and top susceptibility genes were connected in PPI networks. CONCLUSIONS: FoxO1, A2M, and TGF-ß1 interact with environmental factors and with each other in MDD. Multi-factorial G×E interactions may be responsible for a higher explained variance and may be associated with causal factors and mechanisms that could inform new diagnosis and therapeutic strategies, which can contribute to the personalized medicine of MDD.

Factors influencing self-concept among adolescents infected with HIV: a cross-sectional survey in China.

OVERVIEW: The mental health problems of adolescents with human immunodeficiency virus (HIV) are important. It is of great significance to explore which factors can affect the self-evaluation and understanding of adolescents with HIV. OBJECTIVE: We found that adolescents with HIV have a lower level of self-concept than healthy adolescents. This study aimed to determine the factors influencing self-concept among adolescents with HIV in China. SETTING: A questionnaire was distributed among a total of 290 adolescents in Henan Province, China. One hundred and forty questionnaires were distributed in the case group (adolescents with HIV) and the control group (healthy adolescents) was issued 150 questionnaires.The Piers-Harris Children's Self-concept Scale, the Perceived Stress Scale, the Perceived Social Support Scale and the Simplified Coping Style Questionnaire were adapted for a Chinese population. Differences between the groups were tested for significance using Student's t-test, and analysis of variance was used to test continuous variables. The relationship between environmental personality factors and adolescent self-concept was examined by Pearson correlation analysis. Hierarchical linear regression analysis was used to model the effects of environmental personality factors on self-concept. RESULTS: The self-concept total score among adolescents with HIV was significantly lower than healthy adolescents (p<0.05). Hierarchical regression analysis indicated that age (ß=-0.19, t=-2.16, p=0.03), perceived stress (ß=-0.19, t=-2.22, p=0.03), perceived social support (ß=0.26, t=3.25, p=0.00), positive coping style (ß=0.50, t=5.75, p=0.00) and negative coping style (ß=-0.45, t=-5.33, p=0.00) were significantly associated with self-concept total scores. CONCLUSIONS: The self-concept of adolescents with HIV is related to perceived stress, perceived social support and coping style. These findings underline the significance of self-concept among adolescents infected with HIV.

Interactions Between Glycogen Synthase Kinase-3ß Gene Polymorphisms, Negative Life Events, and Susceptibility to Major Depressive Disorder in a Chinese Population.

Background: Recent studies suggest that glycogen synthase kinase (GSK)-3ß is involved in the development of major depressive disorder (MDD). The aim of this study was to investigate the interaction between GSK-3ß polymorphism (rs6438552, rs334558, and rs2199503) and negative life events in the pathogenesis of major depressive disorder (MDD). Methods: DNA genotyping was performed on peripheral blood leukocytes in 550 patients with MDD and 552 age- and gender-matched controls. The frequency and severity of negative life events were assessed by the Life Events Scale (LES). A chi-square method was employed to assess the gene-environment interaction (G × E). Results: Differences in rs6438552, rs334558, and rs2199503 genotype distributions were observed between MDD patients and controls. Significant G × E interactions between allelic variation of rs6438552, rs334558, and rs2199503 and negative life events were observed. Individuals with negative life events and carrying genotypes of rs6438552 A+, rs334558 A+, and rs2199503G+ have increased the risk of depression. Conclusions: These results indicate that interactions between the GSK-3ß rs6438552, rs334558, and rs2199503 polymorphisms and environment increases the risk of developing MDD.

Epistatic Interaction Between 5-HT1A and Vascular Endothelial Growth Factor Gene Polymorphisms in the Northern Chinese Han Population With Major Depressive Disorder.

Aims: Serotonin 1A receptor (5-HT1A) and vascular endothelial growth factor (VEGF) are widely expressed in the neurons of the hippocampus and have significant roles in the pathophysiological processes of major depressive disorders (MDDs). The present study was designed to examine 5-HT1A and VEGF gene polymorphisms and whether the gene-gene interaction of 5-HT1A and VEGF gene variants was associated with MDD. Methods: A total of 264 MDD patients and 264 healthy controls were included in the present genetic study. The rs6295, rs1364043, and rs878567 single-nucleotide polymorphisms (SNPs) in the 5-HT1A gene and the rs699947, rs833061, and rs2010963 SNPs in the VEGF gene were selected for genotypic analyses. The generalized multifactor dimensionality reduction method was employed to assess their interactions. Results: The genotype distributions of the two genes' respective SNPs were significantly different between patients and controls for 5-HT1A rs6295 (p = 0.041) and VEGF rs2010963 (p = 0.035); however, no significant allelic variation in 5-HT1A (rs6295, rs1364043, and rs878567) and VEGF (rs699947, rs833061, and rs2010963) was found. The interactions between 5-HT1A (rs6295, rs1364043, and rs878567) and VEGF (rs699947, rs833061, and rs2010963) had a cross-validation (CV) consistency of 10/10 and a p value of 0.0107, which was considered as the best generalized multifactor dimensionality reduction (GMDR) model. Conclusions: The interactions between 5-HT1A and VEGF gene polymorphisms may play a key role in the development of MDD in the Northern Chinese Han population.

The Interaction of TPH2 and 5-HT2A Polymorphisms on Major Depressive Disorder Susceptibility in a Chinese Han Population: A Case-Control Study.

Purpose: TPH2 and 5-HT2A appear to play vital roles in the homeostatic regulation of serotonin levels in the brain, their genetic variations may lead to impaired homeostatic regulation of serotonin resulting in abnormal levels of serotonin in the brain, thus predisposing individuals to MDD. However, research studies have yet to confirm which gene-gene interaction effect between TPH2 and 5-HT2A polymorphisms results in increased susceptibility to MDD. Methods: A total of 565 participants, consisting of 278 MDD patients and 287 healthy controls from the Chinese Han population, were recruited for the present study. Six single nucleotide polymorphisms (SNPs) of TPH2/5-HT2A were selected to assess their interaction by use of a generalized multifactor dimensionality reduction method. Results: A-allele carriers of rs11178997 and rs120074175 were more likely to suffer from MDD than T-allele carriers of rs11178997, or G-allele carriers of rs120074175. The interaction between TPH2 (rs120074175, rs11178997) and 5-HT2A (rs7997012) was considered as the best multi-locus model upon the MDD susceptibility. Conclusions: Our data identified an important effect of TPH2 genetic variants (rs11178997 and rs120074175) upon the risk of MDD, and suggested that the interaction of TPH2/5-HT2A polymorphism variants confer a greater susceptibility to MDD in Chinese Han population.

Factors associated with depression among HIV/AIDS children in China.

BACKGROUND: Depression in HIV/AIDS children not only worsens the progression and outcome of illness, but also impacts their quality of life, having a negative influence on society. The present study was conducted from a psychosocial perspective, considering children's social desirability, cognitive emotion regulation, and perceived social support to identify the factors influencing depression in HIV-infected children in China. METHODS: Participants were 155 children aged 8-18 years who were eligible to participate in this study assessing depression and associated risk factors using the Children's Depression Inventory, Cognitive Emotion Regulation Questionnaire, Multidimensional Scale of Perceived Social Support, and Children's Social Desirability scale. Hierarchical linear regression analysis was conducted to model the effects of social desirability, perceived social support, and cognitive emotion regulation on depression in HIV/AIDS children. RESULTS: Statistically significant linear relationships were found among social desirability, perceived social support, partial dimensions of cognitive emotion regulation, and children's depression scores. Perceived social support, planning and positive reappraisal were negatively related to the depression. Conversely, social desirability, catastrophizing and other-blame were positively associated with the depression. Linear regression analysis indicated that children's social desirability, perceived social support, and one dimension of cognitive emotion regulation (catastrophizing) were found to significantly predict depression. CONCLUSIONS: Psychosocial factors have an important influence on the depression experienced by HIV-infected children. Interventions from personal subjective psychosocial to reduce depression in HIV-infected children in China are warranted.

CACNA1C rs1006737, Threatening Life Events, and Gene-Environment Interaction Predict Major Depressive Disorder.

INTRODUCTION: CACNA1C rs1006737 is a novel variant in discovery of replicable associations in major depressive disorder (MDD). However, there have been no specific studies considered effect of environmental pathogens to date examining its clinical significance. In this study we investigated the interaction effect between CACNA1C rs1006737 polymorphism and threatening life events (TLEs) in MDD and carried out a meta-analysis of published findings. METHODS: A total of 1,177 consecutive participants were genotyped. Information on exposure to TLEs, socio-demographic data, and history of psychological problems among first-degree relatives was collected. MDD was diagnosed according to the Chinese version of the 24-item Hamilton Rating Scale for Depression. RESULTS: There was a significant interaction effect between CACNA1C rs1006737 polymorphism and TLEs in MDD. A dose-response relationship was found between CACNA1C rs1006737 genotypes and TLEs in MDD. The results of the meta-analysis showed that CACNA1C rs1006737 genotypes interacted with TLEs in MDD. CONCLUSION: CACNA1C rs1006737 genotype and previous exposure to TLEs interact to influence the risk of developing MDD. We propose that CACNA1C rs1006737 may represent a target for novel pharmacological therapies to prevent or treat MDD.

Meta-analysis of the interaction between serotonin transporter promoter variant, stress, and posttraumatic stress disorder.

Exposure to stress predicts the occurrence of posttraumatic stress disorder (PTSD) in individuals harboring the serotonin transporter promoter variant 5-HTTLPR. We carried out a meta-analysis of studies investigating the interaction between 5-HTTLPR, stress, and PTSD to clarify the interrelatedness of these factors. We reviewed all relevant studies published in English before May 2016. The Lipták-Stouffer z-score method for meta-analysis was applied to combined data. The z score was separately calculated for the stressful life events, childhood adversity, bi- and triallelic loci, and cross-sectional and longitudinal studies subgroups. A total of 14 studies with 15,883 subjects met our inclusion criteria. We found strong evidence that the presence of 5-HTTLPR influenced the relationship between stress and PTSD (P = 0.00003), with the strongest effects observed in the cross-sectional and longitudinal groups (P = 0.01 and 2.0 × 10-6, respectively). Stressful life events and childhood adversity separately interacted with 5-HTTLPR in PTSD (P = 2.0 × 10-8 and 0.003, respectively). When the studies were stratified by locus classification, the evidence was stronger for the triallelic (P = 4.0 × 10-8) than for the biallelic (P = 0.054) locus subgroup. There was strong evidence that 5-HTTLPR influences the relationship between stress and PTSD.

Characterization of human bone morphogenetic protein gene variants for possible roles in congenital heart disease.

Congenital heart disease (CHD) is a complex illness with high rates of morbidity and mortality. In embryonic development, the heart is the first formed organ, which is strictly controlled by gene regulatory networks, including transcription factors, signaling pathways, epigenetic factors and microRNAs. Bone morphogenetic protein (BMP)-2 and -4 are essential in cardiogenesis as they can induce the expression of transcription factors, NKX2­5 and GATA binding protein 4, which are important in the development of the heart. The inhibition of BMP­2 and ­4 inhibits the late expression of NKX2-5 and affects cardiac differentiation. The aim of the present study was to investigate whether BMP-2 and ­4 variations may be associated with CHD in Chinese Han populations. The rs1049007, rs235768 and rs17563 single nucleotide polymorphisms (SNPs), which are genetic variations located within the translated region of the BMP-2 and -4, were evaluated in 230 patients with CHD from the Chinese Han population and 160 non-CHD control individuals. Statistical analyses were performed using the χ2 test, implemented using SPSS software (version 13.0). The Hardy-Weinberg equilibrium test was performed on the population using online Online Encyclopedia for Genetic Epidemiology studies software, and multiple-sequence alignments of the BMP proteins were performed using Vector NTI software. No statistically significant associations were identified between these genetic variations and the risk of CHD (rs1049007, P­value=0.560; rs235768, P­value=0.972; rs17563, P­value=0.787). In addition, no correlation was found between the patients with CHD and the non­CHD control individuals. Therefore, the rs1049007, rs235768 and rs17563 genetic variations of BMP-2 were not associated with CHD in the Chinese Han population.

Characterization of nodal/TGF-lefty signaling pathway gene variants for possible roles in congenital heart diseases.

BACKGROUND: Nodal/TGF-Lefty signaling pathway has important effects at early stages of differentiation of human embryonic stem cells in directing them to differentiate into different embryonic lineages. LEFTY, one of transforming growth factors in the Nodal/TGF-Lefty signaling pathway, plays an important role in the development of heart. The aim of this work was to find evidence on whether Lefty variations are associated with congenital heart diseases (CHD). METHODS: We sequenced the Lefty gene for 230 Chinese Han CHD patients and evaluated SNPs rs2295418, rs360057 and g.G169A, which are located within the translated regions of the genes. The statistical analyses were conducted using Chi-Square Tests as implemented in SPSS (version 13.0). The Hardy-Weinberg equilibrium test of the population was carried out using online software OEGE, and multiple-sequence alignments of LEFTY proteins were carried out using the Vector NTI software. RESULTS: Two heterozygous variants in Lefty1 gene, g.G169A and g.A1035C, and one heterozygous variant in Lefty2 gene, g.C925A, were identified. Statistical analyses showed that the rs2295418 (g.C925A) variant in Lefty2 gene was obviously associated with the risk of CHD (P value = 0.016<0.05). The genotype frequency of rs360057 (g.A1035C) variant in Lefty1 gene was associated with the risk of CHD (P value = 0.007<0.05), but the allele frequency was not (P value = 0.317>0.05). CONCLUSIONS: The SNP rs2295418 in the Lefty2 gene is associated with CHD in Chinese Han populations.

Spontaneous modulation of a dynamic balance between bacterial genomic stability and mutability: roles and molecular mechanisms of the genetic switch.

Bacteria need a high degree of genetic stability to maintain their species identities over long evolutionary times while retaining some mutability to adapt to the changing environment. It is a long unanswered question that how bacteria reconcile these seemingly contradictory biological properties. We hypothesized that certain mechanisms must maintain a dynamic balance between genetic stability and mutability for the survival and evolution of bacterial species. To identify such mechanisms, we analyzed bacterial genomes, focusing on the Salmonella mismatch repair (MMR) system. We found that the MMR gene mutL functions as a genetic switch through a slipped-strand mispairing mechanism, modulating and maintaining a dynamic balance between genetic stability and mutability during bacterial evolution. This mechanism allows bacteria to maintain their phylogenetic status, while also adapting to changing environments by acquiring novel traits. In this review, we outline the history of research into this genetic switch, from its discovery to the latest findings, and discuss its potential roles in the genomic evolution of bacteria.