Even with remarkable advances in therapeutic modalities and strategies, high mortality risk remains a major issue in patients with cardiovascular diseases receiving care in the ICU (1). Recently, the Southall and Brent Revisited study and the British Women’s Health and Heart Study showed that higher phenylalanine levels are associated with increased cardiovascular risk (2). Delles et al (3) demonstrated that elevated phenylalanine levels predicted heart failure-related hospitalization in community cohorts at cardiovascular risk based on the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) trial and the Finland National FINRISK Health Survey cohort. Further investigations in patients with heart failure revealed that higher phenylalanine levels were associated with a higher 1-year event rate of rehospitalization or mortality (4,5). All evidence suggests that hyperphenylalaninemia is a prognostic biomarker for poor outcomes, rather than just an essential amino acid in patients with cardiovascular diseases.

Hyperphenylalaninemia is well known in phenylketonuria, a congenital metabolic disorder caused by genetic defects in phenylalanine hydroxylase or its cofactor, 5,6,7,8-tetrahydrobiopterin (BH4), which belongs to the complex system of pteridine production and recycling (6). Currently, extensive genetic screening worldwide powerfully identifies patients with phenylketonuria at the neonatal stage. In the cardiac ICU, all patients are adults without phenylketonuria. Intriguingly, our recent study found mild-to-moderate hyperphenylalaninemia in patients with heart failure receiving care in the ICU and related it to a remarkable increase in mortality risk (7). However, the associated mechanisms were unknown.

Phenylalanine elevation was associated with impaired liver and kidney function, inflammation, and muscle breakdown in noncritical patients (8) but was not well explored in critical patients. On the other hand, Wannemacher et al (9) noted that phenylalanine levels increased in many, but not all, patients with acute myocardial infarction or sepsis. Recent studies have demonstrated that the prognostic value of phenylalanine is strong and independent of all traditional risk factors and risk stratification scores in different cohorts (2,3,5,7,10). These findings led to the hypotheses that genetic polymorphisms exist in the phenylalanine metabolism pathway and that the gene-associated hyperphenylalaninemia presents only in response to critical stress. Full exploration of all related links and mechanisms may help develop innovative strategies for lowering the mortality risk in critical care.

The aims of this study were as follows: 1) to investigate the prognostic value of stress hyperphenylalaninemia (SHP) in patients facing critical illness in the cardiac ICU; 2) to explore the associates of SHP, including clinical variables and genetic variants; 3) to assess the associations between genetic variants and dysregulation in the pteridine system and the changes in phenylalanine concentrations in response to stress; and 4) to propose the clinical implications of our findings in critical care.

METHODS Patient Enrollment

From October 2017 to May 2021, patients with cardiovascular diseases were consecutively enrolled at the cardiac ICU of Chang Gung Memorial Hospital based on the following inclusion criteria: they 1) had Acute Physiology And Chronic Health Evaluation (APACHE II) scores greater than or equal to 15 or were intubated due to respiratory failure, 2) were needed to stay in the ICU greater than 48 hours, and 3) were older than 20 years old. The exclusion criteria were as follows: 1) patients with comorbid disorders other than the main cause for admission that might compromise their survival within 3 months, such as terminal stage cancer or 2) patients who died before baseline phenylalanine measurement. All patients provided informed consent. Ethical approval was granted by the institutional Review Board of Chang Gung Memorial Hospital (201507968B0, 201701750B0, 201801514B0, 202000831B0). Details are provided in the Supplementary Methods (https://links.lww.com/CCM/H178).

Study Design

This study consecutively enrolled 497 patients with plasma phenylalanine measured at baseline and twice a week (study flow diagram provided in Supplementary Fig. 1, https://links.lww.com/CCM/H178). In the 356 patients enrolled from October 2017 to March 2020, we performed gene array in 270 patients to explore genetic polymorphisms associated with SHP (phenylalanine level ≥ 11.2 μmol/dL, based on the cutoff value for at-risk status published in our previous ICU study) (7). As planned, these 270 participants included 130 patients with maximal phenylalanine levels (Pmax) greater than or equal to 11.2 μmol/dL and 140 patients with Pmax less than 8.5 μmol/dL (based on the upper limit of the normal range: 4.87–8.54 μmol/dL; mean: 6.78 μmol/dL) (7). Patients receiving hemodialysis 24 hours before or during blood sample collection were excluded to avoid the effects of hemodialysis on phenylalanine concentrations in the gene study. After identifying the association between SHP and genetic polymorphisms at the pathway of BH4 production and recycling, we enrolled 141 consecutive patients from March 2020 to May 2021 to analyze the correlations between genetic polymorphisms and pteridine levels. For the whole cohort (n = 497), we analyzed the prognostic value of phenylalanine concentration and genetic polymorphisms in the ICU.

Analysis of Pteridines in Plasma

Concentrations of biopterin, 7,8-dihydrobiopterin (BH2), and BH4 were quantified by liquid chromatography tandem mass spectrometry (UPLC-MS/MS). For biopterin, BH2 and BH4, methods of oxidation by acid iodine and alkaline iodine (11,12) and UPLC-MS/MS were modified from previous studies (13,14).

Follow-up Program

Follow-up data were prospectively obtained from hospital records and personal communication with the patients’ physicians. Patients were followed until death or a maximum of 90 days. The primary endpoint was death of all causes.

Statistical Analyses

We presented receiver operating characteristic curve, the area under the curve, hazard ratios (HRs), odds ratios (ORs), and 95% CIs. The Genetic Risk Score (GRS) (range, 0–5) was the sum of the values from 0 to 2 for dominant genes and from 0 to 1 for recessive genes, based on the number of risk alleles. We estimated the necessary sample size using the genetic association power calculator (15). A minimum sample size of 250 was required to achieve 80% power to detect the differences between two groups, with an effect size of 0.25, an OR of 1.5, and an alpha of 0.05.

Detailed methods are provided in the Sup-plementary Materials (https://links.lww.com/CCM/H178).

RESULTS Baseline Characteristics of All Study Patients

The baseline characteristics for 497 patients are shown in Table 1. These patients were admitted to the ICU for the following conditions: 237 patients (47.7%) for cardiac reasons (e.g., coronary artery disease, myocardial infarction, heart failure, or other cardiovascular diseases); 104 patients (21%) for infection; 84 patients (16.9%) for pulmonary diseases; 38 patients (7.6%) for gastrointestinal bleeding; and 34 patients (6.8%) for other conditions. Phenylalanine concentrations ranged from 3.81 to 53.4 μmol/dL.

TABLE 1. - Demographic and Laboratory Data Variables Whole Cohort Death SURVIVOR N = 497 N = 156 N = 341 p Age (yr) 71.3 ± 13.2 73.8 ± 11.7 70.2 ± 13.7 0.006 Male, n (%) 313 (63) 175 (64.8) 100 (70.9) 0.226 Acute Physiology And Chronic Health Evaluation II score 18.3 ± 5.91 21.1 ± 6.19 16.9 ± 5.29 < 0.001 Sequential Organ Failure Assessment  score 6.51 ± 3.25 8.26 ± 3.21 5.70 ± 2.95 < 0.001 Left ventricular ejection fraction (%) 56.0 ± 27.0 56.9 ± 29.8 55.6 ± 25.6 0.629 Body mass index (kg/m2) 24.6 ± 5.0 24.7 ± 5.38 24.5 ± 4.8 0.779 Noncardiac reason, n (%)a 260 (52.3) 96 (61.5) 164 (48.1) 0.005 Comorbidity, n (%)  Diabetes mellitus 234 (47.1) 77 (49.4) 157 (46.0) 0.492  Hypertension 324 (65.2) 106 (67.9) 218 (63.9) 0.383  Coronary disease 217 (43.7) 62 (39.7) 155 (45.5) 0.234  Atrial fibrillation 73 (14.7) 31 (19.9) 42 (12.3) 0.027  Chronic obstructive pulmonary  disease 41 (8.2) 9 (5.8) 32 (9.4) 0.174 Ventilator use, n (%) 341 (68.6) 121 (77.6) 220 (64.5) 0.004 Inotropic agent use, n (%) 159 (32) 69 (44.2) 90 (26.4) < 0.001 Days in ICU (d) 11.8 ± 9.51 14.0 ± 11.5 10.8 ± 8.30 0.002 Laboratory data  Hemoglobin (g/dL) 11.2 ± 5.77 10.5 ± 4.45 11.4 ± 6.27 0.093  C-reactive protein (mg/L) 30.3 (8.4–84.6) 51.8 (16.8–112) 23.5 (6.4–73.6) < 0.001  Cholesterol (mg/dL) 137 ± 54.4 117 ± 41.0 146 ± 57.3 < 0.001  Albumin (g/dL) 3.24 (2.80–3.68) 2.97 (2.61–3.40) 3.38 (2.98–3.77) < 0.001  Estimated glomerular filtration rate  (mL/min/1.73 m2) 38.0 (13.3–73.6) 28.7 (10.6–56.0) 40.0 (16.3–79.5) 0.005  Alanine aminotransferase (U/L) 30.0 (17.0–63.0) 29.5 (17.3–80.0) 30.0 (17.0–58.8) 0.562  Bilirubin, total (mg/dL) 0.5 (0.3–0.9) 0.6 (0.4–1.0) 0.5 (0.3–0.9) 0.132  Creatine kinase (U/L) 74.6 (25.0–223) 85.9 (22.8–268) 71.0 (26.0–200) 0.195  Phenylalanine (μmol/dL) 9.72 ± 5.18 12.01 ± 7.65 8.67 ± 2.99 < 0.001  Tyrosine (μmol/dL) 8.19 ± 5.49 9.85 ± 7.25 7.39 ± 4.17 < 0.001

aReasons for admission in ICU.

Data are expressed as the mean ± sd for variables with normal distribution, median (interquartile range) for variables with skewed distribution, and as n (percentage) for categorical variables.

Factors Associated With Mortality

During the 90-day follow-up period, 156 patients (31.4%) died. Factors associated with death frequency older age, higher APACHE II and Sequential Organ Failure Assessment (SOFA) scores, higher frequency of noncardiac reason for admission in ICU, atrial fibrillation, and higher levels of C-reactive protein and phenylalanine, but lower estimated glomerular filtration rate (eGFR) and lower levels of cholesterol and albumin (Table 1). Each increase of phenylalanine by 1 μmol/dL was associated with an 8.7% relative increase in mortality risk (HR = 1.087; 95% CI = 1.068–1.106; p < 0.001) (Supplementary Table 1, https://links.lww.com/CCM/H178). In multivariable analysis, phenylalanine level predicted 90-day mortality independent of age, reason for admission, atrial fibrillation, C-reactive protein, cholesterol, albumin, eGFR, and SOFA score (model 1) and APACHE II score (model 2).

SHP at baseline was noted in 114 patients (22.9%). In Figure 1A (left and right panels), the Kaplan-Meier curves revealed that baseline or maximal phenylalanine greater than or equal to 11.2 μmol/dL was associated with a lower accumulative survival rate, compared with baseline or maximal phenylalanine less than 11.2 μmol/dL. In the following studies, we focused on the genetic variants associated with SHP.

Figure 1.:

Prognostic value of phenotype and genotype. A, The Kaplan-Meier curves for patients with phenylalanine level at baseline (Pbase) greater than or equal to 11.2 μmol/dL versus Pbase less than 11.2 μmol/dL (left panel) and for patients with maximal phenylalanine level during the stay in the ICU (Pmax) greater than or equal to11.2 μmol/dL versus Pmax less than11.2 μmol/dL (right panel). B, Synthesis and recycling pathways of the tetrahydrobiopterin (BH4) and pteridine system. C, The Kaplan-Meier curves for patients with Genetic Risk Score (GRS) greater than or equal to 2 versus GRS less than 2 in patients with Pbase less than 11.2 μmol/dL (left panel) and in patients with Pbase greater than or equal to 11.2 μmol/dL (right panel). Red color indicates identified genetic variants. AKR = aldose reductase, BH2 = dihydrobiopterin, CBR = carbonyl reductase, DHFR = dihydrofolate reductase, DHPR = dihydropteridine reductase, GTP = guanosine triphosphate, GTPCH = GTP cyclohydrilase, PAH = phenylalanine hydroxylase, PCD = pterin-4a-carbinolamine dehydratase, PTPS = 6-pyruvoyl tetrahydropterin sunthase, qBH2 = quinonoid BH2, SR = sepiapterin reductase. 1’-OXPH4 = 6-(1’-oxo-2’-hydroxypropyl)-tetrahydropterin, 2’-OXPH4 = 6-(1’-hydroxy-2’-oxopropyl)-tetrahydropterin.

Exploration of Genetic Polymorphisms in SHP

The baseline characteristics of the 270 patients are shown in Supplementary Table 2 (https://links.lww.com/CCM/H178). In the gene array, we focused on genetic polymorphisms in the pathways of phenylalanine metabolism and BH4 synthesis. According to the algorithm to separate patients with Pmax greater than or equal to 11.2 μmol/dL from those with less than 8.5 μmol/dL, 13 genetic polymorphisms were identified in eight genes (Supplementary Fig. 2 and Supple mentary Table 3, https://links.lww.com/CCM/H178). We finally selected three single-nucleotide polymorphisms located on the genes for BH4 production and recycling to construct the GRS, including rs20572, rs17395698, and rs319598 mapped on CBR1, AKR1C3, and PCBD2 genes, respectively (Fig. 1B) (described in the Statistical Analyses section and in the Supplementary Methods, https://links.lww.com/CCM/H178).

Genetic Polymorphisms and Clinical Factors Associated With SHP

In univariate analysis, factors with ability of discriminating patients with Pmax greater than or equal to11.2 μmol/dL from those with Pmax less than 85 μM included sex, eGFR, total bilirubin, creatine kinase, reason for admission, CBR1, PCBD2, AKR1C3, and GRS (Table 2). Multivariable analysis (model 1) revealed that CBR1, PCBD2, and AKR1C3 were able to discriminate these two patient groups after adjusting for sex, eGFR, total bilirubin, creatine kinase, and admission reasons. Model 2 showed that GRS, eGFR, total bilirubin, and admission reasons were independent factors related to Pmax. The area under the receiver operating characteristic of GRS was 0.71. Based on Youden’s index, the cutoff value for GRS was set at 2 (OR = 3.53; 95% CI = 2.06–6.15; p < 0.001), with a sensitivity of 84% and a specificity of 48% for identifying Pmax greater than or equal to 11.2 μmol/dL.

TABLE 2. - Univariate and Multivariable Analysis of Clinical Variables and Single Nucleotide Polymorphism Associated With Phenylalanine Level Greater Than or Equal to 11.2 μmol/dL Versus N = 270) Variables Univariate Multivariable (Model 1) Multivariable (Model 2) OR (95% CI) p OR (95% CI) p OR (95% CI) p Male 1.778 (1.070–2.955) 0.026 1.397 (0.764–2.553) 0.293 1.340 (0.741–2.422) 0.333 Noncardiac reasona 2.087 (1.200–3.630) 0.009 2.067 (1.603–5.848) 0.001 3.030 (1.590–5.747) 0.001 Estimated glomerular  filtration rate  (mL/min/1.73 m2) 0.994 (0.989–0.999) 0.023 0.991 (0.985–0.997) 0.002 0.991 (0.985–0.996) 0.02 Bilirubin, total (mg/dL) 1.378 (1.047–1.814) 0.022 1.413 (0.973–2.053) 0.069 1.454 (1.005–2.105) 0.047 Creatine kinase (log) 1.395 (1.035–1.880) 0.029 1.425 (0.974–2.085) 0.068 1.399 (0.965–2.027) 0.77 C-reactive Protein (log) 1.252 (0.875–1.793) 0.219 AKR1C3 7.611 (1.683–34.42) 0.002 8.804 (1.850–46.29) 0.008 PCBD2 1.995 (1.358–2.930) 0.001 2.500 (1.580–3.953) <0.001 CBR1 2.517 (1.597–3.965) <0.001 3.243 (1.886–5.578) <0.001 Genetic Risk Scoreb 2.593 (1.864–3.608) <0.001 2.940 (2.036–4.245) <0.001

OR = odds ratio.

aReason for admission to ICU.

bA score based on the count of risk alleles in three single nucleotide polymorphisms (SNPs) (AKR1C3, PCBD2, and CBR1); model 1, multivariable analysis of each SNP adjusting for all confounding factors; model 2, multivariable analysis of genetic risk score adjusting for all confounding factors.

Genetic Polymorphisms Associated Plasma Pteridines

After genetic variants for SHP were noted in the pathway of BH4 production and recycling but not on the genes for phenylalanine hydroxylase, the correlation between genetic variants and plasma pteridine levels was investigated in 141 patients. The baseline characteristics for these patients with different GRSs are shown in Supplementary Table 4 (https://links.lww.com/CCM/H178). Along with the increase in GRS, we noted a significant trend of decrease in BH4, BH4/BH2, and BH4/total biopterin and increase in C-reactive protein and eGFR, but insignificant changes in BH2 (Fig. 2A–D) (Supplementary Table 4, https://links.lww.com/CCM/H178). Since previous studies showed that BH4/biopterin represents BH4 bioavailability better than BH4 alone (16), the correlation between GRS and BH4/total biopterin was analyzed. Linear regression analysis demonstrated that a higher GRS was associated with lower BH4/total biopterin (β = –0.22; p = 0.008). After adjusting for C-reactive protein and eGFR, GRS remained associated with BH4/total biopterin (β = –0.21; p = 0.016).

Figure 2.:

Genetic polymorphisms and plasma pteridines. The concentrations of tetrahydrobiopterin (BH4) (A), dihydrobiopterin (BH2) (B), ratio of BH4 to BH2 (C), and ratio of BH4 to (BH4+BH2) (D) in patients with different genetic risk scores.

Prognostic Value of Genetic Variants in Patients Without SHP at Baseline

In the whole study cohort (n = 497), the differences between patients with and without SHP are shown in Supple mentary Table 5 (https://links.lww.com/CCM/H178). Of the 383 patients without SHP at baseline, 218 (56.9%) and 165 (43.1%) had GRS less than 2 and greater than or equal to 2, respectively (Table 3). No significant difference between these two subgroups was noted in baseline characteristics. However, in response to stress during the ICU stay, phenylalanine became greater than or equal to 11.2 μmol/dL in 52 patients with GRS greater than or equal to 2 and in 35 with GRS less than 2 (31.5% vs 16.1%, respectively; p = 0.001), supporting the association between genetic variants and phenylalanine elevation. In univariate analysis, GRS greater than or equal to 2 predicted a higher mortality risk (HR = 1.759; 95% CI = 1.196–2.589; p = 0.004). Multivariable analysis revealed that GRS greater than or equal to 2 independently predicted mortality after adjusting for APACHE II scores (HR = 1.741; 95% CI = 1.183–2.562; p = 0.005) or for age, reason for admission, atrial fibrillation, C-reactive protein, albumin, and eGFR (HR = 1.689; 95% CI = 1.142–2.497; p = 0.009). The Kaplan-Meier curves show that GRS greater than or equal to 2 was associated with a lower survival rate, compared with GRS less than 2 (log rank = 8.48; p = 0.004) (Fig. 1C, left panel). There was a significant trend of increasing mortality rates along with the increase of GRS from 0 to 4 (p for trend = 0.004) (Supplementary Fig. 3, https://links.lww.com/CCM/H178).

TABLE 3. - Baseline Demographic and Laboratory Data in Patients With Different Baseline Phenylalanine Levels and Genetic Risk Scores (N = 497) Variables Baseline Phenylalanine < 11.2 μmol/dL Baseline Phenylalanine ≥ 11.2 μmol/dL GRS < 2 GRS ≥ 2 GRS < 2 GRS ≥ 2 N = 218 N = 165 p N = 57 N = 57 p Age (yr) 71.8 ± 13.3 72.9 ± 12.7 0.376 66.8 ± 12.2 69.6 ± 13.9 0.252 Male, n (%) 125 (57.3) 103 (62.4) 0.345 41 (71.9) 44 (77.2) 0.668 Acute Physiology And Chronic Health Evaluation II score 18.0 ± 5.62 18.4 ± 5.35 0.446 19.6 ± 7.34 17.4 ± 6.80 0.101 Sequential Organ Failure Assessment score 6.30 ± 3.20 6.36 ± 2.81 0.846 7.68 ± 3.84 6.53 ± 3.84 0.110 Left ventricular ejection fraction (%) 55.1 ± 19.4 60.3 ± 29.2 0.063 56.3 ± 43.1 46.5 ± 20.1 0.153 Body mass index (kg/m2) 23.8 (21.0–27.0) 24.4 (21.5–27.6) 0.347 24.3 (21.6–26.5) 23.4 (21.2–27.6) 0.738 Noncardiac, n (%)a 111 (50.9) 87 (52.7) 0.726 30 (52.6) 32 (56.1) 0.707 Comorbidity, n (%)  Diabetes mellitus 104 (47.7) 78 (47.3) 1.000 27 (47.4) 25 (43.9) 0.851  Hypertension 138 (63.3) 110 (66.7) 0.518 37 (64.9) 39 (68.4) 0.843  Coronary disease 100 (45.9) 62 (37.6) 0.117 27 (47.4) 28 (49.1) 1.000  Atrial fibrillation 30 (13.8) 27 (16.4) 0.562 9 (15.8) 7 (12.3) 0.788  Chronic obstructive pulmonary disease 20 (9.2) 14 (8.5) 0.858 2 (3.5) 5 (8.8) 0.438 Ventilator use, n (%) 155 (71.1) 116 (70.3) 0.910 39 (68.4) 31 (54.4) 0.178 Inotropic agent use, n (%) 65 (29.8) 48 (29.1) 0.910 29 (50.9) 17 (29.8) 0.035 Days in ICU (d) 10 (5–17) 10 (5–18) 0.595 9 (2–19) 6 (1–13) 0.087 Laboratory data  Hemoglobin (g/dL) 11.0 ± 4.1 11.6 ± 8.4 0.378 11.1 ± 3.5 10.5 ± 3.2 0.300  C-reactive protein (mg/L) 27.5 (7.1–78.2) 40.4 (10.7–100) 0.082 29.9 (11.7–75.5) 21.3 (7.0–63.6) 0.209  Cholesterol (mg/dL) 143.9 ± 63.8 135.2 ± 42.8 0.114 123.7 ± 50.9 127.8 ± 44.7 0.655  Albumin (g/dL) 3.4 ± 2.7 3.2 ± 0.61 0.377 3.0 ± 0.8 3.5 ± 1.5 0.034  Estimated glomerular filtration rate (mL/min/1.73 m2) 40.0 (15.3–72.8) 41.1 (12.8–80.6) 0.640 25.6 (11.4–49.5) 31.0 (9.99–80.3) 0.453  Bilirubin, total (mg/dL) 0.5 (0.3–0.8) 0.5 (0.3–0.7) 0.508 0.6 (0.5–1.5) 1 (0.5–1.9) 0.395  Creatine kinase (U/L) 72.0 (25.0–183) 62.3 (19.6–211) 0.604 119 (45.6–614) 91.3 (36.6–256) 0.306  Phenylalanine (μmol/dL) 7.70 ± 1.53 7.92 ± 1.69 0.190 17.25 ± 8.12 15.15 ± 6.41 0.127  Tyrosine (μmol/dL) 6.91 ± 2.69 6.91 ± 2.55 0.994 14.32 ± 9.76