The Effect of Angiotensin Converting Enzyme (ACE) I/D Polymorphism on Atherosclerotic Cardiovascular Disease and Cardiovascular Mortality Risk in Non-Hemodialyzed Chronic Kidney Disease: The Mediating Role of Plasma ACE Level

Predicting early-stage coronary artery disease using machine learning and routine clinical biomarkers improved by augmented virtual data

Aims

Coronary artery disease (CAD) is a highly prevalent disease with modifiable risk factors. In patients with suspected obstructive CAD, evaluating the pre-test probability model is crucial for diagnosis, although its accuracy remains controversial. Machine learning (ML) predictive models can help clinicians detect CAD early and improve outcomes. This study aimed to identify early-stage CAD using ML in conjunction with a panel of clinical and laboratory tests.

Methods and results

The study sample included 3316 patients enrolled in the Ludwigshafen Risk and Cardiovascular Health (LURIC) study. A comprehensive array of attributes was considered, and an ML pipeline was developed. Subsequently, we utilized five approaches to generating high-quality virtual patient data to improve the performance of the artificial intelligence models. An extension study was carried out using data from the Young Finns Study (YFS) to assess the results' generalizability. Upon applying virtual augmented data, accuracy increased by approximately 5%, from 0.75 to -0.79 for random forests (RFs), and from 0.76 to -0.80 for Gradient Boosting (GB). Sensitivity showed a significant boost for RFs, rising by about 9.4% (0.81-0.89), while GB exhibited a 4.8% increase (0.83-0.87). Specificity showed a significant boost for RFs, rising by ∼24% (from 0.55 to 0.70), while GB exhibited a 37% increase (from 0.51 to 0.74). The extension analysis aligned with the initial study.

Conclusion

Accurate predictions of angiographic CAD can be obtained using a set of routine laboratory markers, age, sex, and smoking status, holding the potential to limit the need for invasive diagnostic techniques. The extension analysis in the YFS demonstrated the potential of these findings in a younger population, and it confirmed applicability to atherosclerotic vascular disease.

Analysis of angiotensin II type 1 receptor and osteoprotegerin gene polymorphism on the risk of cardiovascular mortality risk and progressivity of chronic kidney disease

BACKGROUND

Chronic kidney disease (CKD) is a significant global public health issue with increased risk of atherosclerotic cardiovascular disease (ASCVD) and cardiovascular mortality. Single nucleotide polymorphisms (SNPs) on angiotensin II type 1 receptor (AT1R) A1166C and osteoprotegerin (OPG) C950T gene have received significant attention as a genetic risk factor for cardiovascular disease and CKD.

METHODS

This was a cross-sectional study involving 75 adults with CKD recruited from Nephrology Outpatient Clinics of Universitas Airlangga Hospital, Surabaya, Indonesia. Demographic data was obtained from interviews and medical records. The "CKD Patch" application was used to asses ASCVD and cardiovascular mortality risk scores. Statistical analysis was performed by using SPSS version 26.

RESULTS

We detected four different AT1R gene polymorphisms (A1166C, A1160C, G1170T, and G1181C) and two OPG gene polymorphisms (T950C and G1181C) in Indonesian CKD patients. A1160C and G1181C polymorphisms were novel SNPs, newly discovered in this research. No significant association was found between AT1R SNPs and kidney prognostic markers or ASCVD risk/mortality risk scores. However, for OPG C950T we found that TT genotype had a significantly higher ACR than TC or CC genotype (P=0.032). As for OPG G1181C, we found that GG genotype had a higher serum creatinine and albumin to creatinine ratio compared to GC and CC genotypes (P=0.004 and 0.029, respectively). Genotype GC for OPG G1181C was also shown to be protective for having better kidney markers and lowest cardiovascular mortality risk compared to GG and CC genotypes (P=0.018 and 0.032, respectively).

CONCLUSIONS

Increased ASCVD risk and mortality risk score was not found on individuals with AT1R gene SNPs. However, for OPG gene polymorphism, C950T and G1181C were associated with kidney progression and cardiovascular mortality.

Analysis of Genes Involved in Oxidative Stress and Iron Metabolism in Heart Failure: A Step Forward in Risk Stratification

INTRODUCTION

Heart failure (HF) is a clinical syndrome characterized by cardinal symptoms that may be accompanied by signs. It results from structural and/or functional abnormalities of the heart leading to elevated intracardiac pressures and/or inadequate cardiac output at rest and/or during exercise. The prevalence of iron deficiency and anemia justifies the current guidelines recommendation of screening. Genes HP, ACE, MTHFR, HFE, and CYBA are involved in oxidative mechanisms, iron metabolism, and hematologic homeostasis. This study investigates the contribution of variants Hp1/2 (HP), I/D (ACE), C677T (MTHFR), C282Y and H63D (HFE), and C242T (CYBA) to the development of HF, either independently or in epistasis.

METHODS

We used a database of 389 individuals, 143 HF patients, and 246 healthy controls. Genotypes were characterized through PAGE electrophoresis, PCR, PCR-RFLP, and multiplex-ARMS. Data analysis was performed with the SPSS® 26.0 software (IBM Corp., Armonk, NY).

RESULTS

We observed a significant association between the MTHFR gene and HF predisposition. The presence of allele T and genotype CT constituted risk, while genotype CC granted protection. Epistatic interactions revealed risk between genotype II of the ACE gene and genotypes CC (C282Y) or HH (H63D) of the HFE gene. Risk was also observed for interactions between genotype CC (CYBA)and genotypes 2-2 (HP), CT (MTHFR), or HH (HFE-H63D).

CONCLUSION

We concluded that genes HP, ACE, MTHFR, HFE, and CYBA contribute to the susceptibility for HF, individually or in epistasis. This study contributes to the clarification of the role that genes involved in oxidative mechanisms and iron metabolism play in the physiopathology of HF. It is, therefore, a step forward in risk stratification and personalized medicine.

Leiomyoma and the importance of genetic variation on genes related to the vasculature system - CβS, MTHFR, NOS3, CYBA, and ACE1

OBJECTIVE

The link between the systemic vasculature system and tumor biology is here investigated by studying the contribution of CβS (844ins68), MTHFR (677C > T), NOS3 (4a/4b), CYBA (C242T), and ACE1 (I/D) genes to leiomyoma onset, uterus and leiomyoma volumes.

METHODS

DNA samples from 130 women with leiomyomas and 527 from healthy women were genotyped by PCR or PCR-RFLP. Qui-square (χ2) or Fisher's exact test were used to test associations. All the mentioned tests were performed in IBM® SPSS® Statistics Version 28. Statistical significance was defined as a p-value < 0.05.

RESULTS

Results revealed that CβS (in the codominant and allelic models, p = 0.044 and, p = 0.015, OR = 1.791 [1.114-2.879], respectively), MTHFR (in the codominant, allelic and dominant models, p = 0.009, p = 0.002, OR = 0.585 [0.416-0.824] and p = 0.003, OR = 0.527 [0.346-0.802], respectively) and ACE1 (dominant model, p = 0.045, OR = 0.639 [0.411-0.992]) genes are associated with leiomyoma onset. NOS3 4a4a genotype is associated with a lower uterus volume (p = 0.004). This study also uncovers intriguing epistatic interactions among some genes that further accentuate their roles in disease modulation. Indeed, the epistatic interactions between the CC genotype (MTHFR) and (+/+) (CβS; p = 0.003), 4b4b (NOS3; p = 0.006, OR = 2.050 [1.223-3.439]) or DD (ACE1; p < 0.001, OR = 2.362 [1.438-3.880]) were shown to be associated with the disease, while 4a presence (NOS3) in epistasis with I presence (ACE1), increased the effect protection having just the I allele presence (p = 0.029, OR = 0.446 [0.214-0.930]).

CONCLUSIONS

We conclude that variation in genes related to the systemic vascular system can play a role in the onset and development of leiomyoma.

Review on Emerging Therapeutic Strategies for Managing Cardiovascular Disease

Cardiovascular disease (CVD) remains a foremost global health concern, necessitating ongoing exploration of innovative therapeutic strategies. This review surveys the latest developments in cardiovascular therapeutics, offering a comprehensive overview of emerging approaches poised to transform disease management. The examination begins by elucidating the current epidemiological landscape of CVD and the economic challenges it poses to healthcare systems. It proceeds to scrutinize the limitations of traditional therapies, emphasizing the need for progressive interventions. The core focus is on novel pharmacological interventions, including advancements in drug development, targeted therapies, and repurposing existing medications. The burgeoning field of gene therapy and its potential in addressing genetic predispositions to cardiovascular disorders are explored, alongside the integration of artificial intelligence and machine learning in risk assessment and treatment optimization. Non-pharmacological interventions take center stage, with an exploration of digital health technologies, wearable devices, and telemedicine as transformative tools in CVD management. Regenerative medicine and stem cell therapies, offering promises of tissue repair and functional recovery, are investigated for their potential impact on cardiac health. This review also delves into the interplay of lifestyle modifications, diet, exercise, and behavioral changes, emphasizing their pivotal role in cardiovascular health and disease prevention. As precision medicine gains prominence, this synthesis of emerging therapeutic modalities aims to guide clinicians and researchers in navigating the dynamic landscape of cardiovascular disease management, fostering a collective effort to alleviate the global burden of CVD and promote a healthier future.

Review on Molecular Mechanism of Hypertensive Nephropathy

Hypertension, a prevalent chronic ailment, has the potential to impair kidney function, and thereby resulting in hypertensive nephropathy. The escalating incidence of hypertensive nephropathy attributed to the aging population in urban areas, has emerged as a prominent cause of end-stage renal disease. Nevertheless, the intricate pathogenesis of hypertensive nephropathy poses considerable obstacles in terms of precise clinical diagnosis and treatment. This paper aims to consolidate the research findings on the pathogenesis of hypertensive nephropathy by focusing on the perspective of molecular biology.

The Role of Plasma Interleukin-6 Levels on Atherosclerotic Cardiovascular Disease and Cardiovascular Mortality Risk Scores in Javanese Patients with Chronic Kidney Disease

Interleukin-6 (IL-6) has been identified as an important pro-inflammatory factor involved in mediating the severity of chronic kidney disease (CKD). This study sought to determine the effect of plasma IL-6 levels on atherosclerotic cardiovascular disease (ASCVD) and cardiovascular mortality risk scores in Javanese CKD patients. We also analyzed the frequency of IL-6 G174C single nucleotide polymorphism (SNP) in the population. This study was a cross-sectional study involving seventy-three patients of Javanese ethnic origin with stable chronic kidney disease. We assessed the ASCVD risk score, cardiovascular mortality score, genotyping of IL-6 G174C SNP, and plasma IL-6 levels in these patients. The genotype distribution and allele frequencies of the IL-6 G174C SNP were predominated by the G genotype/allele (GG: 97.26%, GC: 1.37%, CC: 1.37%, G-allele: 97.95%, and C-allele: 2.05%). Despite the fact that plasma IL-6 levels did not directly affect cardiovascular mortality risk, further analysis revealed its direct effect on the ASCVD risk score (path coefficient = 0.184, p = 0.043, 95% CI = 0.018−0.380), which in turn affected cardiovascular mortality risk (path coefficient = 0.851, p = <0.01, 95% CI = 0.714−0.925). In conclusion, plasma IL-6 levels play important roles on ASCVD risk and cardiovascular mortality risk in Javanese patients with CKD.