A new common functional coding variant at the DDC gene change renal enzyme activity and modify renal dopamine function

An individualized Bayesian method for estimating genomic variants of hypertension

BACKGROUND

Genomic variants of the disease are often discovered nowadays through population-based genome-wide association studies (GWAS). Identifying genomic variations potentially underlying a phenotype, such as hypertension, in an individual is important for designing personalized treatment; however, population-level models, such as GWAS, may not capture all the important, individualized factors well. In addition, GWAS typically requires a large sample size to detect the association of low-frequency genomic variants with sufficient power. Here, we report an individualized Bayesian inference (IBI) algorithm for estimating the genomic variants that influence complex traits, such as hypertension, at the level of an individual (e.g., a patient). By modeling at the level of the individual, IBI seeks to find genomic variants observed in the individual's genome that provide a strong explanation of the phenotype observed in this individual.

RESULTS

We applied the IBI algorithm to the data from the Framingham Heart Study to explore the genomic influences of hypertension. Among the top-ranking variants identified by IBI and GWAS, there is a significant number of shared variants (intersection); the unique variants identified only by IBI tend to have relatively lower minor allele frequency than those identified by GWAS. In addition, IBI discovered more individualized and diverse variants that explain hypertension patients better than GWAS. Furthermore, IBI found several well-known low-frequency variants as well as genes related to blood pressure that GWAS missed in the same cohort. Finally, IBI identified top-ranked variants that predicted hypertension better than GWAS, according to the area under the ROC curve.

CONCLUSIONS

The results support IBI as a promising approach for complementing GWAS, especially in detecting low-frequency genomic variants as well as learning personalized genomic variants of clinical traits and disease, such as the complex trait of hypertension, to help advance precision medicine.

Deriving psychiatric symptom-based biomarkers from multivariate relationships between psychophysiological and biochemical measures

Identification of biomarkers for psychiatric disorders remains very challenging due to substantial symptom heterogeneity and diagnostic comorbidity, limiting the ability to map symptoms to underlying neurobiology. Dimensional symptom clusters, such as anhedonia, hyperarousal, etc., are complex and arise due to interactions of a multitude of complex biological relationships. The primary aim of the current investigation was to use multi-set canonical correlation analysis (mCCA) to derive biomarkers (biochemical, physiological) linked to dimensional symptoms across the anxiety and depressive spectrum. Active-duty service members (N = 2,592) completed standardized depression, anxiety and posttraumatic stress questionnaires and several psychophysiological and biochemical assays. Using this approach, we identified two phenotype associations between distinct physiological and biological phenotypes. One was characterized by symptoms of dysphoric arousal (anhedonia, anxiety, hypervigilance) which was associated with low blood pressure and startle reactivity. This finding is in line with previous studies suggesting blunted physiological reactivity is associated with subpopulations endorsing anxiety with comorbid depressive features. A second phenotype of anxious fatigue (high anxiety and reexperiencing/avoidance symptoms coupled with fatigue) was associated with elevated blood levels of norepinephrine and the inflammatory marker C-reactive protein in conjunction with high blood pressure. This second phenotype may describe populations in which inflammation and high sympathetic outflow might contribute to anxious fatigue. Overall, these findings support the growing consensus that distinct neuropsychiatric symptom patterns are associated with differential physiological and blood-based biological profiles and highlight the potential of mCCA to reveal important psychiatric symptom biomarkers from several psychophysiological and biochemical measures.

The Role of the Renal Dopaminergic System and Oxidative Stress in the Pathogenesis of Hypertension

The kidney is critical in the long-term regulation of blood pressure. Oxidative stress is one of the many factors that is accountable for the development of hypertension. The five dopamine receptor subtypes (D₁R–D₅R) have important roles in the regulation of blood pressure through several mechanisms, such as inhibition of oxidative stress. Dopamine receptors, including those expressed in the kidney, reduce oxidative stress by inhibiting the expression or action of receptors that increase oxidative stress. In addition, dopamine receptors stimulate the expression or action of receptors that decrease oxidative stress. This article examines the importance and relationship between the renal dopaminergic system and oxidative stress in the regulation of renal sodium handling and blood pressure. It discusses the current information on renal dopamine receptor-mediated antioxidative network, which includes the production of reactive oxygen species and abnormalities of renal dopamine receptors. Recognizing the mechanisms by which renal dopamine receptors regulate oxidative stress and their degree of influence on the pathogenesis of hypertension would further advance the understanding of the pathophysiology of hypertension.

Association between polymorphism in gene related to the dopamine circuit and motivations for drinking in patients with alcohol use disorder

The development of alcohol use disorder (AUD) is influenced by genetic, psychological, and social factors. However, the identification of the load of each of these factors and the association between them is still debatable. This study aimed to explore the load of the association between AUD and polymorphisms in genes of the dopaminergic system, as well as with drinking triggers. The study comprised 227 inpatients with AUD and 174 controls. The pattern and motivations for drinking were evaluated using the Alcohol Use Disorders Identification Test (AUDIT) and the Inventory of Drinking Situations (IDS). Analyses of genetic variation in genes encoding dopaminergic were performed using next generation sequencing. We observed an significant association between a polymorphism in DDC (rs11575457) and AUD. Positive reinforcement factors as urges/temptations to drink and pleasant emotion, in isolation, were the significantly related elements to drinking. In addition, negative (physical discomfort) and positive reinforcement factors (testing personal control; pleasant time with others) significantly reinforced the interaction with DDC genetic variant for increased odds of an individual presenting AUD. These results indicated a complex relationship between the dopaminergic system and the drug-seeking behavior profiles.

Renal Autocrine and Paracrine Signaling: A Story of Self-protection

Autocrine and paracrine signaling in the kidney adds an extra level of diversity and complexity to renal physiology. The extensive scientific production on the topic precludes easy understanding of the fundamental purpose of the vast number of molecules and systems that influence the renal function. This systematic review provides the broader pen strokes for a collected image of renal paracrine signaling. First, we recapitulate the essence of each paracrine system one by one. Thereafter the single components are merged into an overarching physiological concept. The presented survey shows that despite the diversity in the web of paracrine factors, the collected effect on renal function may not be complicated after all. In essence, paracrine activation provides an intelligent system that perceives minor perturbations and reacts with a coordinated and integrated tissue response that relieves the work load from the renal epithelia and favors diuresis and natriuresis. We suggest that the overall function of paracrine signaling is reno-protection and argue that renal paracrine signaling and self-regulation are two sides of the same coin. Thus local paracrine signaling is an intrinsic function of the kidney, and the overall renal effect of changes in blood pressure, volume load, and systemic hormones will always be tinted by its paracrine status.