Differences in left ventricular functional adaptation to arterial stiffness and neurohormonal activation in patients with hypertension: a study with two-dimensional layer-specific speckle tracking echocardiography

Abstract Background Arterial stiffness increases pressure load to the left ventricle (LV), leading to LV hypertrophy and subendocardial ischemia. Neurohormones stimulate myocardial fibrosis and LV dysfunction. We aimed to explore the associations of arterial stiffness and plasma aldosterone with multi-directional, layer-specific LV, and left atrial (LA) mechanical function in hypertensive patients. Methods Layer-specific LV global longitudinal strain (GLS-trans, GLS-endo, GLS-epi), global circumferential strain (GCS-trans, GCS-endo, GCS-epi), LV torsional parameters, and LA global longitudinal strain (LA GLS) were analyzed by two-dimensional speckle tracking echocardiography in 195 hypertensive patients (110 men, mean age 55 years). Pulse wave velocity (PWV) was analyzed as a measure of arterial stiffness, and plasma aldosterone was measured for evaluation of neurohormonal activation. Results In a simple correlation, PWV significantly correlated with LV GLS-endo and LA GLS. Log aldosterone correlated with both LV GCS-endo and LV GCS-trans. Multiple regression analysis revealed that LV GLS-endo (β = 0.223, p = 0.031) and LA GLS (β = −0.311, p = 0.002) were independently correlated with PWV even after controlling for confounding factors. Conclusions In hypertensive patients without clinically apparent target organ damage, LV GLS, especially endocardium, and LA GLS were more dominantly affected by arterial stiffness because, among the three myocardial layers, the endocardium is most susceptible to pressure overload. Two-dimensional layer-specific speckle-tracking echocardiography sensitively detects LV mechanical dysfunction and provides pathophysiologic insights into LV mechanical adaptations in hypertension

Shared Genetic Background between Parkinson’s Disease and Schizophrenia: A Two-Sample Mendelian Randomization Study

Background and objectives: Parkinson’s disease (PD) and schizophrenia often share symptomatology. Psychotic symptoms are prevalent in patients with PD, and similar motor symptoms with extrapyramidal signs are frequently observed in antipsychotic-naïve patients with schizophrenia as well as premorbid families. However, few studies have examined the relationship between PD and schizophrenia. We performed this study to evaluate whether genetic variants which increase PD risk influence the risk of developing schizophrenia, and vice versa. Materials and Methods: Two-sample Mendelian randomization (TSMR) with summary statistics from large-scale genome-wide association studies (GWAS) was applied. Summary statistics were extracted for these instruments from GWAS of PD and schizophrenia; Results: We found an increase in the risk of schizophrenia per one-standard deviation (SD) increase in the genetically-predicted PD risk (inverse-variance weighted method, odds ratio = 1.10; 95% confidence interval, 1.05−1.15; p = 3.49 × 10−5). The association was consistent in sensitivity analyses, including multiple TSMR methods, analysis after removing outlier variants with potential pleiotropic effects, and analysis after applying multiple GWAS subthresholds. No relationships were evident between PD and smoking or other psychiatric disorders, including attention deficit hyperactivity disorder, autism spectrum disorder, bipolar affective disorder, major depressive disorder, Alzheimer’s disease, or alcohol dependence. However, we did not find a reverse relationship; genetic variants increasing schizophrenia risk did not alter the risk of PD; Conclusions: Overall, our findings suggest that increased genetic risk of PD can be associated with increased risk of schizophrenia. This association supports the intrinsic nature of the psychotic symptom in PD rather than medication or environmental effects. Future studies for possible comorbidities and shared genetic structure between the two diseases are warranted

Shared genetic architectures of subjective well-being in East Asian and European ancestry populations

Subjective well-being (SWB) has been explored in European ancestral populations; however, whether the SWB genetic architecture is shared across populations remains unclear. We conducted a cross-population genome-wide association study for SWB using samples from Korean (n = 110,919) and European (n = 563,176) ancestries. Five ancestry-specific loci and twelve cross-ancestry significant genomic loci were identified. One novel locus (rs12298541 near HMGA2) associated with SWB was also identified through the European meta-analysis. Significant cross-ancestry genetic correlation for SWB between samples was observed. Polygenic risk analysis in an independent Korean cohort (n = 22,455) demonstrated transferability between populations. Significant correlations between SWB and major depressive disorder, and significant enrichment of central nervous system-related polymorphisms heritability in both ancestry populations were found. Hence, large-scale cross-ancestry genome-wide association studies can advance our understanding of SWB genetic architecture and mental health

Leveraging genetic overlap between irritability and psychiatric disorders to identify genetic variants of major psychiatric disorders

Abstract Irritability is a heritable core mental trait associated with several psychiatric illnesses. However, the genomic basis of irritability is unclear. Therefore, this study aimed to 1) identify the genetic variants associated with irritability and investigate the associated biological pathways, genes, and tissues as well as single-nucleotide polymorphism (SNP)-based heritability; 2) explore the relationships between irritability and various traits, including psychiatric disorders; and 3) identify additional and shared genetic variants for irritability and psychiatric disorders. We conducted a genome-wide association study (GWAS) using 379,506 European samples (105,975 cases and 273,531 controls) from the UK Biobank. We utilized various post-GWAS analyses, including linkage disequilibrium score regression, the bivariate causal mixture model (MiXeR), and conditional and conjunctional false discovery rate approaches. This GWAS identified 15 independent loci associated with irritability; the total SNP heritability estimate was 4.19%. Genetic correlations with psychiatric disorders were most pronounced for major depressive disorder (MDD) and bipolar II disorder (BD II). MiXeR analysis revealed polygenic overlap with schizophrenia (SCZ), bipolar I disorder (BD I), and MDD. Conditional false discovery rate analyses identified additional loci associated with SCZ (number [n] of additional SNPs = 105), BD I (n = 54), MDD (n = 107), and irritability (n = 157). Conjunctional false discovery rate analyses identified 85, 41, and 198 shared loci between irritability and SCZ, BD I, and MDD, respectively. Multiple genetic loci were associated with irritability and three main psychiatric disorders. Given that irritability is a cross-disorder trait, these findings may help to elucidate the genomics of psychiatric disorders