Association Study of Genetic Variants in Calcium Signaling-Related Genes With Cardiovascular Diseases

PTPRD gene variant rs10739150: A potential game-changer in hypertension diagnosis

BACKGROUND

High blood pressure, also known as hypertension (HTN), is a complicated disorder that is controlled by a complex network of physiological processes. Untreated hypertension is associated with increased death incidence, rise the need for understanding the genetic basis affecting hypertension susceptibility and development. The current study sought to identify the genetic association between twelve single nucleotide polymorphisms (SNPs) within seven candidate genes (NOS3, NOS1AP, REN, PLA2G4A, TCF7L, ADRB1, and PTPRD).

METHODS

The current study included 200 Jordanian individuals diagnosed with hypertension, compared to 224 healthy controls. Whole blood samples were drawn from each individual for DNA isolation and genotyping. The SNPStats tool was used to assess haplotype, genotype, and allele frequencies by the mean of chi-square (χ2).

RESULTS

Except for rs10739150 of PTPRD (P = 0.0003), the genotypic and allelic distribution of the SNP was identical between patients and controls. The prevalence of the G/G genotype in healthy controls (45.5%) was lower than in hypertension patients (64.3%), suggesting that it might be a risk factor for the disease. PTPRD TTC genetic haplotypes were strongly linked with hypertension (P = 0.003, OR = 4.03).

CONCLUSION

This study provides a comprehensive understanding of the involvement of rs10739150 within the PTPRD gene in hypertension. This new knowledge could potentially transform the way we approach hypertension diagnosis, providing an accurate diagnostic tool for classifying individuals who are at a higher risk of developing this condition.

Developing and evaluating pediatric phecodes (Peds-Phecodes) for high-throughput phenotyping using electronic health records

OBJECTIVE

Pediatric patients have different diseases and outcomes than adults; however, existing phecodes do not capture the distinctive pediatric spectrum of disease. We aim to develop specialized pediatric phecodes (Peds-Phecodes) to enable efficient, large-scale phenotypic analyses of pediatric patients.

MATERIALS AND METHODS

We adopted a hybrid data- and knowledge-driven approach leveraging electronic health records (EHRs) and genetic data from Vanderbilt University Medical Center to modify the most recent version of phecodes to better capture pediatric phenotypes. First, we compared the prevalence of patient diagnoses in pediatric and adult populations to identify disease phenotypes differentially affecting children and adults. We then used clinical domain knowledge to remove phecodes representing phenotypes unlikely to affect pediatric patients and create new phecodes for phenotypes relevant to the pediatric population. We further compared phenome-wide association study (PheWAS) outcomes replicating known pediatric genotype-phenotype associations between Peds-Phecodes and phecodes.

RESULTS

The Peds-Phecodes aggregate 15 533 ICD-9-CM codes and 82 949 ICD-10-CM codes into 2051 distinct phecodes. Peds-Phecodes replicated more known pediatric genotype-phenotype associations than phecodes (248 vs 192 out of 687 SNPs, P < .001).

DISCUSSION

We introduce Peds-Phecodes, a high-throughput EHR phenotyping tool tailored for use in pediatric populations. We successfully validated the Peds-Phecodes using genetic replication studies. Our findings also reveal the potential use of Peds-Phecodes in detecting novel genotype-phenotype associations for pediatric conditions. We expect that Peds-Phecodes will facilitate large-scale phenomic and genomic analyses in pediatric populations.

CONCLUSION

Peds-Phecodes capture higher-quality pediatric phenotypes and deliver superior PheWAS outcomes compared to phecodes.

Non‑synonymous polymorphisms in the HRC and ADRB1 genes may be associated with all‑cause death in patients with non‑ischemic heart failure

Sudden cardiac death (SCD) is an unpredictable and common mode of death in patients with heart failure (HF). Alterations in calcium handling may lead to malignant arrhythmias, resulting in SCD, and variants in calcium signaling-related genes have a significant association with SCD. Therefore, the aim of the present retrospective cohort study was to investigate the association of Ser96Ala [histidine-rich calcium-binding protein (HRC)], Ser49Gly [β1-adrenergic receptor (ADRB1)], Arg389Gly (ADRB1) and Gly1886Ser [ryanodine receptor 2 (RYR2)] polymorphisms with serious arrhythmic events and overall mortality in patients with HF with reduced left ventricular ejection fraction of non-ischemic etiology. In total, 136 patients with HF underwent physical examination, routine laboratory tests, non-invasive assessment of cardiac function and an invasive electrophysiological study. The primary outcome was the occurrence of serious arrhythmic events, set as either SCD or appropriate implantable cardioverter-defibrillator (ICD) therapy, and the secondary outcome was all-cause death. During a median follow-up of 37 months, arrhythmic events occurred in 26 patients (19%) and 41 patients (30%) died. Patients carrying the Ser allele of the Ser96Ala polymorphism in HRC had worse survival than those with the Ala/Ala genotype (log-rank P=0.043). Despite the difference in survival time, the Ala/Ala genotype was not associated with all-cause death in the regression analysis [unadjusted hazard ratio (HR)=0.17; 95% CI, 0.02-1.21]. Regarding the Ser49Gly and Arg389Gly polymorphisms in ADRB1, homozygosity for the major alleles at both sites (Ser49Ser and Arg389Arg) was associated with a two-fold increased risk of all-cause death compared with the other genotype combinations (unadjusted HR=1.98; 95% CI, 1.02-3.82). However, this association was lost after controlling for clinical covariates. No association was observed for the Gly1886Ser polymorphism in RYR2. Overall, the present findings are concurrent with the hypothesis that the Ser96Ala (HRC), Ser49Gly (ADRB1) and Arg389Gly (ADRB1) polymorphisms may be associated with HF prognosis. In particular, the Ser96Ala polymorphism might aid in risk stratification and patient selection for ICD implantation.

Developing and Evaluating Pediatric Phecodes (Peds-Phecodes) for High-Throughput Phenotyping Using Electronic Health Records

Objective

Pediatric patients have different diseases and outcomes than adults; however, existing phecodes do not capture the distinctive pediatric spectrum of disease. We aim to develop specialized pediatric phecodes (Peds-Phecodes) to enable efficient, large-scale phenotypic analyses of pediatric patients.

Materials and Methods

We adopted a hybrid data- and knowledge-driven approach leveraging electronic health records (EHRs) and genetic data from Vanderbilt University Medical Center to modify the most recent version of phecodes to better capture pediatric phenotypes. First, we compared the prevalence of patient diagnoses in pediatric and adult populations to identify disease phenotypes differentially affecting children and adults. We then used clinical domain knowledge to remove phecodes representing phenotypes unlikely to affect pediatric patients and create new phecodes for phenotypes relevant to the pediatric population. We further compared phenome-wide association study (PheWAS) outcomes replicating known pediatric genotype-phenotype associations between Peds-Phecodes and phecodes.

Results

The Peds-Phecodes aggregate 15,533 ICD-9-CM codes and 82,949 ICD-10-CM codes into 2,051 distinct phecodes. Peds-Phecodes replicated more known pediatric genotype-phenotype associations than phecodes (248 versus 192 out of 687 SNPs, p<0.001).

Discussion

We introduce Peds-Phecodes, a high-throughput EHR phenotyping tool tailored for use in pediatric populations. We successfully validated the Peds-Phecodes using genetic replication studies. Our findings also reveal the potential use of Peds-Phecodes in detecting novel genotype-phenotype associations for pediatric conditions. We expect that Peds-Phecodes will facilitate large-scale phenomic and genomic analyses in pediatric populations.

Conclusion

Peds-Phecodes capture higher-quality pediatric phenotypes and deliver superior PheWAS outcomes compared to phecodes.