Impacts of ACE insertion/deletion variant on cardiometabolic risk factors, premature coronary artery disease, and severity of coronary lesions

Angiotensin-converting enzyme (ACE) is closely related to cardiometabolic risk factors and atherosclerosis. This study aims to investigate whether the insertion/deletion (I/D) variant of ACE gene impacts cardiometabolic risk factors, premature coronary artery disease (PCAD), and severity of coronary lesions. PubMed, Cochrane Library, Central, CINAHL, and ClinicalTrials.gov were searched until December 22, 2023. 94,270 individuals were included for the analysis. Carriers of DD genotype had higher levels of triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), and waist circumference (WC) than carriers of II or ID genotypes. In addition, carriers of DD genotype were at high risk of PCAD and multiple vessel lesions. The impacts of ACE I/D variant on lipid levels were significant in American individuals but stronger in male individuals. In contrast, the impacts of ACE I/D variant on PCAD and severity of coronary lesions were primarily significant in Caucasian individuals. This study indicates that the ACE I/D variant has a slight but significant impact on cardiometabolic risk factors, PCAD, and severity of coronary lesions. Angiotensin-converting enzyme inhibitors (ACEI) may benefit high-risk populations with ACE DD genotype to prevent PCAD and multiple vessel lesions.PROSPERO registration number: CRD42023426732.

Why patients with familial hypercholesterolemia are at high cardiovascular risk? Beyond LDL-C levels

Familial hypercholesterolemia (FH) is a common genetic cause of elevated low-density lipoprotein cholesterol (LDL-C) due to defective clearance of circulating LDL particles. All FH patients are at high risk for premature cardiovascular disease (CVD) events due to their genetically determined lifelong exposure to high LDL-C levels. However, different rates of CVD events have been reported in FH patients, even among those with the same genetic mutations and comparable LDL-C levels. Hence, additional CVD risk modifiers, beyond LDL-C, may contribute to increase CVD risk in the FH population. In this review, we discuss the overall CVD risk burden of the FH population. Additionally, we revise the prognostic impact of several traditional and emerging predictors of CVD risk and we provide an overview of the role of specific tools to stratify CVD risk in FH patients in order to ensure them a more personalized treatment approach.

C-type lectin family XIV members and angiogenesis

The growth and metastasis of tumors is dependent on angiogenesis. C-type lectins are carbohydrate-binding proteins with a diverse range of functions. The C-type lectin family XIV members are transmembrane glycoproteins, and all four members of this family have been reported to regulate angiogenesis, although the detailed mechanism of action has yet to be completely elucidated. They interact with extracellular matrix proteins and mediate cell-cell adhesion by their lectin-like domain. The aim of the present study was to summarize the available information on the function and mechanism of C-type lectin family XIV in angiogenesis and discuss their potential as targets for cancer therapy.

Predicting cardiovascular disease in familial hypercholesterolemia

PURPOSE OF REVIEW

Familial hypercholesterolemia is a frequent genetic disease associated with a high lifetime risk of cardiovascular disease (CVD). Statins are the cornerstone of treatment of familial hypercholesterolemia; however, with the advent of novel LDL-cholesterol lowering therapies, it has become necessary to identify familial hypercholesterolemia subjects presenting a significant residual CVD risk. The aim of this review is to provide an update on the recent literature concerning cardiovascular risk stratification in familial hypercholesterolemia.

RECENT FINDINGS

Recently, several clinical and genetic factors have been shown to be independent predictors of CVD in familial hypercholesterolemia. These include clinical scores such as the Montreal-FH-SCORE, novel protein biomarkers, carotid plaque score and genetic predictors such as genetic risk scores as well as single-nucleotide polymorphisms.

SUMMARY

Although there has been recent progress in cardiovascular risk stratification in familial hypercholesterolemia, there is still a need to further refine our knowledge concerning phenotype modifiers in this disease. Indeed, current known predictors do not explain the entirety of cardiovascular risk. More precise individual risk stratification in familial hypercholesterolemia could help to better tailor the proper therapy for each patient.

Tailored therapy of ACE inhibitors in stable coronary artery disease: pharmacogenetic profiling of treatment benefit

Angiotensin-converting enzyme (ACE) inhibitors are among the most commonly used drugs in stable coronary artery disease as these agents have been proven to be effective for reducing the risk of cardiovascular morbidity and mortality. As with other drugs, individual variation in treatment benefit is likely. Such heterogeneity could be used to target ACE-inhibitor therapy to those patients most likely to benefit from treatment. However, prior attempts to target ACE-inhibitor therapy to those patients who are most likely to benefit of such prophylactic treatment in secondary prevention using clinical characteristics or the level of baseline risk appeared not to be useful. A new approach of 'tailored therapy' could be to integrate more patient-specific characteristics, such as the genetic information of patients. Pharmacogenetic research of ACE inhibitors in coronary artery disease patients is at a formative stage, and studies are limited. The Perindopril Genetic association (PERGENE) study is a large pharmacogenetic substudy of the randomized placebo-controlled European trial On Reduction of Cardiac Events with Perindopril in Patients with Stable Coronary Artery disease (EUROPA) trial, aimed to assess the feasibility of pharmacogenetic profiling of ACE-inhibitor therapy by perindopril. This article summarizes the recent findings of the PERGENE study and pharmacogenetic research of the treatment benefit of perindopril in stable coronary artery disease.

Translating associations between common kidney diseases and genetic variation into the clinic

Studies of the genetics of common diseases have revealed multiple risk alleles associated with end-stage renal disease, albuminuria, serum creatinine, diabetes, coronary heart disease, and increased triglyceride levels. These associations have prompted further basic science research, which has led to the discovery of novel pathways and a better understanding of the pathophysiology of common diseases. Currently, the ability to translate these discoveries into clinical practice is limited by the small effect size of these risk alleles and a lack of studies showing meaningful impact of genetic variation on risk assessment and clinical outcomes. Advances in genetic testing will continue to yield highly significant associations but translation into clinical practice will require effective collaboration between physicians and basic and social scientists. Rigorous clinical trials eventually will reveal which combination of genetic tests improves risk stratification and identifies individuals most likely to benefit from specific prevention strategies and therapies.

Pathway genetic load allows simultaneous evaluation of multiple genetic associations

OBJECTIVE

Despite the general success of genome-wide association studies, much heritability remains unidentified in many disease states. Some of this 'missing' heritability may lie in epistatic interactions among multiple loci, which are typically ignored. We utilized a method for simultaneous evaluation of epistatic interactions between allelic variations within genes confined to a single pathway, which we have termed as pathway genetic load (PGL).

METHODS

In separate analyses, we evaluated the risk for sepsis and for death associated with alleles at six loci in the TLR4 signaling and response pathway previously known or suspected to be linked to the development of sepsis after traumatic injury. We evaluated 155 patients with > or =15% TBSA burns and without significant non-burn trauma [ISS < or =16], traumatic or anoxic brain injury or spinal cord injury, who survived > 48 h post-admission. Clinical data were collected prospectively and candidate genotypes were determined by TaqMan assay.

RESULTS

After adjustment for burn size, inhalation injury, age, gender and race, PGL was associated with increased probability for complicated sepsis (aOR=1.59; 95%CI=1.11-2.29; p=0.011) and death (aOR=1.75; 95%CI=1.11-2.76; p=0.017).

CONCLUSION

Relative size and variability of aORs indicate greater power to detect genetic associations with PGL compared to the analysis of loci individually by multivariate logistic regression.

Genome-based prediction of common diseases: methodological considerations for future research

The translation of emerging genomic knowledge into public health and clinical care is one of the major challenges for the coming decades. At the moment, genome-based prediction of common diseases, such as type 2 diabetes, coronary heart disease and cancer, is still not informative. Our understanding of the genetic basis of multifactorial diseases is improving, but the currently identified susceptibility variants contribute only marginally to the development of disease. At the same time, an increasing number of companies are offering personalized lifestyle and health recommendations on the basis of individual genetic profiles. This discrepancy between the limited predictive value and the commercial availability of genetic profiles highlights the need for a critical appraisal of the usefulness of genome-based applications in clinical and public health care. Anticipating the discovery of a large number of genetic variants in the near future, we need to prepare a framework for the design and analysis of studies aiming to evaluate the clinical validity and utility of genetic tests. In this article, we review recent studies on the predictive value of genetic profiling from a methodological perspective and address issues around the choice of the study population, the construction of genetic profiles, the measurement of the predictive value, calibration and validation of prediction models, and assessment of clinical utility. Careful consideration of these issues will contribute to the knowledge base that is needed to identify useful genome-based applications for implementation in clinical and public health practice.

Usefulness of genetic polymorphisms and conventional risk factors to predict coronary heart disease in patients with familial hypercholesterolemia

Familial hypercholesterolemia (FH) is an autosomal dominant disorder with an associated high risk of coronary heart disease (CHD). The considerable variation in age of onset of CHD in patients with FH is believed to arise from conventional risk factors, as well as genetic variation other than in the low-density lipoprotein receptor gene. The degree to which currently known genetic variants can improve the prediction of CHD risk beyond conventional risk factors in this disorder was investigated. Fourteen genetic variants recently identified for association with CHD in a Dutch FH population were considered. Prediction models were constructed using Cox proportional hazards models, and predictive value was assessed using a concordance statistic (c statistic). A total of 1,337 patients with FH were completely genotyped for all genetic variants. Hazard ratios of the genetic variants ranged from 0.61 to 0.74 and 1.24 to 2.33. The c statistic of the CHD prediction model based on genetic variants was 0.59, denoting little discrimination. The model based on conventional risk factors had a c statistic of 0.75, denoting moderate discrimination. Adding genetic test results to this model increased the c statistic to 0.76. In conclusion, the contribution of 14 genetic variants to the prediction of CHD risk in patients with FH was limited. To improve genome-based prediction of CHD, larger numbers of genetic variants need to be identified that either on their own or in gene-gene interaction have substantial effects on CHD risk.

Genome-based prediction of common diseases: advances and prospects

Common diseases such as type 2 diabetes and coronary heart disease result from a complex interplay of genetic and environmental factors. Recent developments in genomics research have boosted progress in the discovery of susceptibility genes and fueled expectations about opportunities of genetic profiling for personalizing medicine. Personalized medicine requires a test that fairly accurately predicts disease risk, particularly when interventions are invasive, expensive or have major side effects. Recent studies on the prediction of common diseases based on multiple genetic variants alone or in addition to traditional disease risk factors showed limited predictive value so far, but all have investigated only a limited number of susceptibility variants. New gene discoveries from genome-wide association studies will certainly further improve the prediction of common diseases, but the question is whether this improvement is sufficient to enable personalized medicine. In this paper, we argue that new gene discoveries may not evidently improve the prediction of common diseases to a degree that it will change the management of individuals at increased risk. Substantial improvements may only be expected if we manage to understand the complete causal mechanisms of common diseases to a similar extent as we understand those of monogenic disorders. Genomics research will contribute to this understanding, but it is likely that the complexity of complex diseases may ultimately limit the opportunities for accurate prediction of disease in asymptomatic individuals as unraveling their complete causal pathways may be impossible.