Biomarkers for isolated congenital heart disease based on maternal amniotic fluid metabolomics analysis

In this study, the distribution characteristics of amniotic fluid metabolites in CHDs and the controls were obtained through untargeted metabolomics detection. Possible biomarkers for CHD occurrence or development were screened. We also explored the possible mechanisms for differential metabolites in the occurrence of CHD. Our results provide basic data resources into congenital heart disease from a new perspective.

Congenital heart disease is one of the most common birth defects [1], and the diagnosis of the disease is overly dependent on the technical level of ultrasonography [5].

Metabolomics is an extension of genomics that can more intuitively reflect the profiling of metabolites in biofluids, cells and tissues and it is routinely applied as a tool for biomarker discovery [27]. Owing to innovative developments in informatics and analytical technologies and the integration of orthogonal biological approaches, it has become possible to expand metabolomic analyses to understand the systems-level effects of metabolites, which can be used for CHD screening or to explore the mechanism of occurrence and development of CHD.

A previousstudy conducted a serum metabolomics study on children with congenital heart disease and found that 13 metabolites showed a significant increasing or decreasing trend. Taurine, glutamine, and glutamate presented considerable diagnostic value for the diagnosis of CHD [16]. Some researchers performed metabolomics detection on the serum of patients with congenital bicuspid aortic valve (BAV) and controls [15]. A predictive model for estimating group BAV was established and those studies supported the value of serum-based metabolomic profiling methods as an adjunct tool for screening large populations.

However, these studies used infant or childhood serum samples as material to explore the relationship between metabolites and CHD, and it is relatively rare to study the occurrence of CHD through biological samples obtained from pregnant mothers. Previous studies reported that maternal serum [17], urine [18, 19], and amniotic fluid (AF) [20] were used to detect metabolites by [1] H NMR or GC–MS technology. However, these methods for detecting metabolites are more limited than those detected by UHPLC‒MS.

Amniotic fluid, as the growing environment of the fetus, is relatively stable in the middle and late pregnancy stages. Compared with maternal blood, urine and other samples, it can better reflect the actual metabolic state of the fetus. The urine excreted by the fetus after the second trimester is an important source of amniotic fluid, and the metabolites in the fetus will be reflected in the amniotic fluid with the excretion of urine. The sources of amniotic fluid in the second and third trimesters are basically similar. Amniotic fluid not only provides a mechanical buffer for the fetus to prevent limb adhesion but also provides nutrients and growth factors, transports metabolites, and more. At the same time, the physiological and biochemical levels of the amniotic fluid reflect the health status of the fetus. Accurate and sensitive details of birth defect-related metabolites and their respective biochemical pathways can be obtained through amniotic fluid metabolomics, which also allows a better understanding of the overall pathophysiology of affected pregnancies.

A total of 2472 metabolites were identified using the UHPLC-QTOF-MS untargeted metabolomics detection in this study. Many new metabolites were found compared to previous studies, which mostly used NMR or GC-TOF–MS methods, and could only detect hundreds of metabolites [17,18,19,20]. UHPLC is increasingly displacing conventional high performance liquid chromatography [28] LC–MS is the main workhorse of metabolomics owing to its high degree of analytical sensitivity and specificity when measuring diverse chemistry in complex biological samples [29]. The untargeted metabolomics detection method can identify as many metabolites as possible by comparing characteristic peak ions with standard databases, and useing semiquantitative metabolite content to obtain high-throughput metabolomics data [28]. Untargeted metabolomics is a powerful tool that can provide new clues for prenatal diagnosis [14]。It will be helpful for discovering affected metabolic pathways, revealing disease pathogenesis, and identifying potential biomarkers [27].

The method of combining the fold change, the P value of the t-test and the VIP value of the OPLS-DA model was utilized to screen the differential metabolites, and the machine algorithm of randomForest (RF) was exploited to screen the biomarkers. The randomForest is an ensemble learning method that operates by constructing a collection of decision trees [30], and for variable selection, it performs well across sample sizes [31]. In addition, a receiver operating characteristic (ROC) curve was used to estimate the area under the curve (AUC) score and 95% confidence interval (95% CI) of each selected marker. We also evaluated the combined differentuation ability of these makers using a logistic regression model. The results show that PE(MonoMe(11,5)/MonoMe(13,5)), 4-[N-(p-Coumaroyl) serotonin-4’’-yl] -N-feruloylserotonin and 2,6-Di-tert-butylbenzoquinone in maternal amniotic fluid perform well in distinguishing cases from controls.

PE(MonoMe(11,5)/MonoMe(13,5)), also called 13-(3-methyl-5-pentylfuran-2-yl) tridecanoate, a kind of dimethylfuran fatty acid, is abundant in fish oil and is easily oxidized and degraded [32]. There are few reports about this chemical, but it has been found to be decreased in patients with gastrointestinal diseases [33]. 4-[N-(p-Coumaroyl)serotonin-4’’-yl]-N-feruloylserotonin is a serotonin derivative with a trace distribution in medicinal plants such as safflower [23]. It has strong scavenging free radicals and anti-lipid peroxidation ability, antitumor activity, anti-inflammatory and bacteriostatic effects, and it inhibits the production of melanin and other functional activities. This substance has the potential for the study of atherosclerosis and aortic wall distention [24]. 2,6-Di-tert-butylbenzoquinone, a cyclic NIAS originating from food packaging, has not been found to be associated with disease occurrence. However, a similar substance 2,5-di-(tert-butyl)-1,4-benzohydroquinone, is a reversible inhibitor of cardiac cells through intracellular Ca2+ handling in ventricular myocytes [34]. Among the ten most important metabolites, methylglutarylcarnitine was also reported detected differentially in CHD patients and controls [17]. Deficiency of 3- methylglutarylcarnitine affects the metabolism of leucine as well as ketogenesis. This disorder is one of an increasing list of inborn errors of metabolism that present clinically, such as metabolic syndrome (MetS), risk of developing cardiovascular disease (CVD) and type 2 diabetes [35].

This study found that the differential metabolites were mainly concentrated in several metabolic pathways, and it was inferred that aldosterone synthesis, drug metabolism, nicotinate and nicotinamide metabolism played very important roles in the occurrence and development of CHD. The secretion of aldosterone is mainly regulated by renin-angiotensin, a hormone that regulates the blood volume in the human body. It maintains water balance by regulating the reabsorption of sodium in kidneys. Excessive circulating and tissue angiotensin II (AngII) and aldosterone levels lead to a profibrotic, proinflammatory, and hypertrophic milieu [36] that causes remodeling and dysfunction of cardiovascular and renal tissues [37]. Nicotinate and nicotinamide are collectively referred to as vitamin 22. Nicotinamide forms coenzyme I and coenzyme II with ribose, phosphate and adenine in the body. They are the coenzymes of many dehydrogenases and are associated with many metabolic processes including glucose glycolysis, fat metabolism, and pyruvate metabolism, which are closely related to the formation of high-energy phosphate bonds [38]. As the major coenzyme in fuel oxidation and oxidative phosphorylation and a substrate for enzyme responses to energy stress and oxidative stress, nicotinamide adenine dinucleotide (NAD +) is emerging as a metabolic target in a number of diseases including heart failure. Niacin turns into niacinamide in the body to play the above role. In addition, niacin also has a strong peripheral vasodilator effect. Nicotinamide adenine dinucleotide (NAD) is synthesized de novo from tryptophan through the kynurenine pathway. The patients showed treduced levels of circulating NAD. Defects similar to those in the patients developed in the embryos of Haao-null or Kynu-null mice owing to NAD deficiency. The prevention of NAD deficiency during gestation could prevent these defects [39]. These results would provide additional new metabolite data sources for the CHD, and suggest a new idea for further mechanistic exploration of CHD.

Of course, this study also has some shortcomings: the sample size is relatively small, and the metabolite differences between CHD subtypes could not be analyzed comparatively. The basic characteristics the of cases and controls are somewhat inconsistent due to the limited collection of samples in biobanks, which may interfere with the results. In addition, only internal data were used in the validation model, and no external database was used for verification. Future studies should focus on larger sample sizes for in-depth analysis and validation. This study will provide certain directions and ideas for future studies.

留言 (0)

沒有登入
gif