Characterization of SNPs in the dopamine-β-hydroxylase gene providing new insights into its structure-function relationship

Risk and Resilience Variants in the Retinoic Acid Metabolic and Developmental Pathways Associated with Risk of FASD Outcomes

Fetal Alcohol Spectrum Disorder (FASD) is a common neurodevelopmental disorder that affects an estimated 2-5% of North Americans. FASD is induced by prenatal alcohol exposure (PAE) during pregnancy and while there is a clear genetic contribution, few genetic factors are currently identified or understood. In this study, using a candidate gene approach, we performed a genetic variant analysis of retinoic acid (RA) metabolic and developmental signaling pathway genes on whole exome sequencing data of 23 FASD-diagnosed individuals. We found risk and resilience alleles in ADH and ALDH genes known to normally be involved in alcohol detoxification at the expense of RA production, causing RA deficiency, following PAE. Risk and resilience variants were also identified in RA-regulated developmental pathway genes, especially in SHH and WNT pathways. Notably, we also identified significant variants in the causative genes of rare neurodevelopmental disorders sharing comorbidities with FASD, including STRA6 (Matthew-Wood), SOX9 (Campomelic Dysplasia), FDG1 (Aarskog), and 22q11.2 deletion syndrome (TBX1). Although this is a small exploratory study, the findings support PAE-induced RA deficiency as a major etiology underlying FASD and suggest risk and resilience variants may be suitable biomarkers to determine the risk of FASD outcomes following PAE.

Translational bioinformatics approach to combat cardiovascular disease and cancers

Bioinformatics is an interconnected subject of science dealing with diverse fields including biology, chemistry, physics, statistics, mathematics, and computer science as the key fields to answer complicated physiological problems. Key intention of bioinformatics is to store, analyze, organize, and retrieve essential information about genome, proteome, transcriptome, metabolome, as well as organisms to investigate the biological system along with its dynamics, if any. The outcome of bioinformatics depends on the type, quantity, and quality of the raw data provided and the algorithm employed to analyze the same. Despite several approved medicines available, cardiovascular disorders (CVDs) and cancers comprises of the two leading causes of human deaths. Understanding the unknown facts of both these non-communicable disorders is inevitable to discover new pathways, find new drug targets, and eventually newer drugs to combat them successfully. Since, all these goals involve complex investigation and handling of various types of macro- and small- molecules of the human body, bioinformatics plays a key role in such processes. Results from such investigation has direct human application and thus we call this filed as translational bioinformatics. Current book chapter thus deals with diverse scope and applications of this translational bioinformatics to find cure, diagnosis, and understanding the mechanisms of CVDs and cancers. Developing complex yet small or long algorithms to address such problems is very common in translational bioinformatics. Structure-based drug discovery or AI-guided invention of novel antibodies that too with super-high accuracy, speed, and involvement of considerably low amount of investment are some of the astonishing features of the translational bioinformatics and its applications in the fields of CVDs and cancers.

Effect of rs1108580 of DBH and rs1006737 of CACNA1C on Cognition and Tardive Dyskinesia in a North Indian Schizophrenia Cohort

Genetic perturbations in dopamine neurotransmission and calcium signaling pathways are implicated in the etiology of schizophrenia. We aimed to test the association of a functional splice variant each in Dopamine β-Hydroxylase (DBH; rs1108580) and Calcium voltage-gated channel subunit alpha1 C (CACNA1C; rs1006737) genes in these pathways with schizophrenia (506 cases, 443 controls); Abnormal Involuntary Movement Scale (AIMS) scores in subjects assessed for tardive dyskinesia (76 TD-positive, 95 TD-negative) and Penn Computerized Neurocognitive Battery (PennCNB) scores (334 cases, 234 controls). The effect of smoking status and SNP genotypes on AIMS scores were assessed using ANOVA; health status and SNP genotypes on three performance functions of PennCNB cognitive domains were assessed by ANCOVA with age and sex as covariates. Association with Positive and Negative Syndrome Scale (PANSS) scores in the TD cohort and cognitive scores in healthy controls of the cognition cohort were tested by linear regression. None of the markers were associated with schizophrenia. Smoking status [F(2, 139) = 10.6; p = 5 × 10-5], rs1006737 [F(2, 139) = 7.1; p = 0.001], TD status*smoking [F(2, 139) = 8.0; p = 5.0 × 10-4] and smoking status*rs1006737 [F(4, 139) = 2.7; p = 0.03] had an effect on AIMS score. Furthermore, rs1006737 was associated with orofacial [F(2, 139) = 4.6; p = 0.01] and limb-truncal TD [(F(2, 139) = 3.8; p = 0.02]. Main effect of rs1108580 on working memoryprocessing speed [F(2, 544) = 3.8; p = 0.03] and rs1006737 on spatial abilityefficiency [F(1, 550) = 9.4; p = 0.02] was identified. Health status*rs1006737 interaction had an effect on spatial memoryprocessing speed [F(1, 550) = 6.9; p = 0.01]. Allelic/genotypic association (p = 0.01/0.03) of rs1006737 with disorganized/concrete factor and allelic association of rs1108580 (p = 0.04) with a depressive factor of PANSS was observed in the TD-negative subcohort. Allelic association of rs1006737 with sensorimotor dexterityaccuracy (p = 0.03), attentionefficiency (p = 0.05), and spatial abilityefficiency (p = 0.02); allelic association of rs1108580 with face memoryaccuracy (p = 0.05) and emotionefficiency (p = 0.05); and allelic/genotypic association with emotionaccuracy (p = 0.003/0.009) were observed in healthy controls of the cognition cohort. These association findings may have direct implications for personalized medicine and cognitive remediation.

Association of regulatory variants of dopamine β-hydroxylase with cognition and tardive dyskinesia in schizophrenia subjects

BACKGROUND

Dopamine-β-hydroxylase (DBH, EC 1.14.17.1), which converts dopamine to norepinephrine, is a candidate gene in neuropsychiatric diseases.

AIM

To assess the effect of regulatory variants in DBH on schizophrenia and its endophenotypes -cognition and tardive dyskinesia.

METHODS

We tested association of functional variants 19bp Ins/Del, rs1989787 and rs1611115 in DBH with i) schizophrenia (1236 cases, 1136 controls), ii) tardive dyskinesia (83 positive, 162 negative) and iii) performance functions of cognition (357 cases, 306 controls) estimated by the Penn Computerized Neurocognitive Battery.

RESULTS

A modest haplotypic (Ins-C; 19bp Ins/Del - rs1989787 C>T; p=0.04) association was observed with schizophrenia. We observed ~39% reduction in activity of 19bp Del allele on luciferase assay. Analysis of covariance revealed interactions of tardive dyskinesia status and: i) 19bp Ins/Del (genotypic, p=0.04) and ii) rs1989787 and rs1611115 (combined genotypic, p=0.004) on Abnormal Involuntary Movement Scale total score. Association of rs1611115 with positive and negative syndrome scale (PANSS) total score (p=0.05) and allelic/genotypic association with lower positive (p=0.03/0.04), general psychopathology (p=0.01/0.01) PANSS scales in tardive dyskinesia-positive; and allelic/genotypic (p=0.02/0.05) with higher score of depressive factors in tardive dyskinesia-negative subgroups were observed. Analysis of covariance with continuous variable of cognition showed interaction of health status with: i) rs1989787 on accuracy and efficiency (p=0.03) of abstraction and mental flexibility; ii) rs1611115 on accuracy of working memory and emotion (p=0.05); iii) 19bp Ins/Del on processing speed of emotion (p=0.03). Allelic/genotypic association of rs1989787 with spatial ability (p=0.02-0.05) among healthy controls; association of rs1611115 with Global Assessment Scale scores in the past month (p=0.05) among schizophrenia subjects of cognition cohort was also observed.

CONCLUSIONS

With modest genotype-phenotype correlations available for DBH variants, personalized treatment regimens based on DBH activity for ameliorating tardive dyskinesia and cognitive symptoms may be plausible.

Determination of Dopamine-β-hydroxylase Activity in Human Serum Using UHPLC-PDA Detection

Dopamine-β-hydroxylase (DBH, EC 1.14.17.1) is an enzyme with implications in various neuropsychiatric and cardiovascular diseases and is a known drug target. There is a dearth of cost effective and fast method for estimation of activity of this enzyme. A sensitive UHPLC based method for the estimation of DBH activity in human sera samples based on separation of substrate tyramine from the product octopamine in 3 min is described here. In this newly developed protocol, a Solid Phase Extraction (SPE) sample purification step prior to LC separation, selectively removes interferences from the reaction cocktail with almost no additional burden on analyte recovery. The response was found to be linear with an r² = 0.999. The coefficient of variation for assay precision was < 10% and recovery > 90%. As a proof of concept, DBH activity in sera from healthy human volunteers (n = 60) and schizophrenia subjects (n = 60) were successfully determined using this method. There was a significant decrease in sera DBH activity in subjects affected by schizophrenia (p < 0.05) as compared to healthy volunteers. This novel assay employing SPE to separate octopamine and tyramine from the cocktail matrix may have implications for categorising subjects into various risk groups for Schizophrenia, Parkinson's disease as well as in high throughput screening of inhibitors.