Phenylketonuria is an inherited autosomal recessive disease of phenylalanine (Phe) metabolism resulting from variants in genes-encoding phenylalanine hydroxylase. Phenylalanine hydroxylase transforms Phe into tyrosine (Tyr) on the condition that cofactors tetrahydrobiopterin, molecular oxygen, and iron are presented in the environment [1]. Disorders of Phe metabolism cause a significant increase in the concentration of Phe in the blood and brain tissue, which may lead to various neurocognitive and neuromotor disorders, if not treated in the neonatal period [2,3,4,5]. Dietary treatment is administered to prevent the development of the adverse effects of phenylketonuria, which is extremely important. Currently, the dietary treatment is supplemented with other amino acids (AAs) in conjunction with the restricted Phe intake to support growth and to maintain a healthy body composition that forms the basis of treatment [2, 6]. In patients with phenylketonuria who receive the dietary treatment, the plasma Phe levels of 120–360 μmol/L are targeted for children aged <12 years, while the plasma Phe levels of 120–600 μmol/L are targeted for children aged ≥12 years [2, 7, 8].
An accurate analysis of the types and amounts of AAs is extremely important in determining the efficacy of dietary treatment administered to phenylketonurics. Liquid chromatography–mass spectrometry (LC-MS) is an analytical technique widely used for AA analysis. Recently, LC-MS has been further developed, and a method comprising a combination of two mass analyzers in one mass spectrometry instrument (LC-MS/MS) has been used [9,10,11].
AAs and their derivatives may play a role in the pathophysiology of neuropsychiatric disorders through variations in molecular mechanisms [12, 13]. Through LC-MS/MS analysis, the plasma levels of various AAs, such as γ-aminobutyric acid (GABA), glycine (Gly), glutamic acid (Glu), and asparagine (Asn), which play important roles in the central nervous system (CNS), can be easily measured. In phenylketonurics, various neurological problems may develop with the increased Phe level in the blood and brain tissue [14, 15].
We sought to investigate the effects of the increased plasma level of Phe on the levels of other AAs in the plasma (especially excitatory and inhibitory AAs) and whether the levels of other AAs can be used as support parameters for follow-up of patients.
After approval of the study protocol by the Harran University Ethics Committee for Human Research (certificate of approval No. E40428; approval date October 4, 2018, session 10/40428) following the Declaration of Helsinki and its contemporary amendments, and after obtaining written informed consent to participate in the study from the parents of all patients and controls included, we conducted a study in a community in Sanliurfa province, Turkey. All participants with phenylketonuria included in the study were followed up regularly from October 15, 2017 to October 15, 2018 in the pediatric metabolic diseases clinic. Data were obtained retrospectively from each phenylketonuria patient's medical record at the time of their most recent visit, which included age, sex, height, weight, adherence to dietary treatment, and plasma AA analysis results. Blood samples were collected from age-matched healthy control patient-participants attending the Pediatric Metabolism Disorders clinic but with normal results and volunteered by their parents in the month from 15 October 2018 to 15 November 2018, and data were obtained, which included age, sex, height, weight, and plasma AA analysis results on the same day. The phenylketonurics were divided into 2 groups according to their adherence to dietary treatment: those who adhered [diet compliant (DC)] and who had not adhered to their diet [diet incompliant (DIC)], and plasma AA analysis results were compared with those of healthy children in the control group. The participants included in the control group were selected from among healthy children who did not have any disease or pathological condition. The patients in the DC group were selected among the patients who had the target plasma levels of Phe (<12 years 120–360 μmol/L, ≥ 12 years 120–600 μmol/L) in all 3 consecutive follow-up examinations within the last 6 months. The patients in the DIC group were selected among the patients who exceeded the target plasma levels of Phe (<12 years >360 μmol/L, ≥ 12 years >600 μmol/L) as determined in all 3 consecutive follow-up examinations within the last 6 months. Patients who did not attend the follow-up examinations (3 times in the last 6 months) were excluded from the study. The plasma samples taken for the LC-MS/MS analysis were analyzed immediately after they are collected. Informed consent from the parents of all participants included in the study was obtained and documented before the venous blood samples were taken.
For plasma AA analysis, we used a Quantitative Amino Acids Analysis kit (Jasem, Istanbul, Turkey). Venous blood samples (2 mL) were collected into heparinized tubes and centrifuged. After separating 50 μL of the centrifuged plasma and placing it into a tube (Eppendorf, Hamburg, Germany), 50 μL of AA internal standard (ISTD) was added to it and the mixture was vortexed for 5 s. Finally, 700 μL of Reagent-1 (protein precipitation reagent for plasma; Jasem) was added and the mixture was again vortexed for 5 s, then centrifuged at 4 °C (model NF-1200R, rotor: RA 200, catalog No. B50 016; Nüve, Ankara, Turkey) at 10,000 rpm (18,405 ×
Statistical analyses were performed using IBM SPSS Statistics for Windows (version 24.0; IBM Corp). Descriptive statistics were summarized as number, percentage, mean, and standard deviation. The suitability of the variables to the normal distribution was investigated using visual (histogram and probability charts) and analytical methods (Kolmogorov–Smirnov). Normally distributed data were analyzed using a one-way analysis of variance (ANOVA), with post hoc Bonferroni correction. Analysis of variables without normal distribution was performed using a Kruskal–Wallis test. Categorical variables were analyzed using a Pearson chi-square or Fisher exact test (when any of the theoretical values observed on a 2 × 2 table was <5). Significance was accepted at a level of
We included 150 patients evaluated by the clinic for pediatric metabolic diseases and met the study criteria. Of the patients, 56% were boys and 44% were girls. At the time of admission to our clinic, the mean age of the patients was 6.55 ± 4.35 years (range 0–16). There were 44 (29%) patients in the DC group and 56 (37%) patients in the DIC group, and 50 (34%) patients in the control group. When the groups were analyzed in terms of sex, weight for height percentile distribution, and mean age values, they were found to be similar (
Sociodemographic characteristics of the patients
Sex (male/female) | 30/26 | 27/17 | 27/23 | 0.69† |
Age (mean | 6.57 | 6.75 | 6.36 | 0.15‡ |
Parental consanguinity | ||||
Yes/no n (%) | 49 (87.5)/7 (12.5) | 33 (75)/11 (25) | 11 (22)/39 (78) | <0.001† |
Refugee status | ||||
Yes/no n (%) | 16 (29)/40 (71) | 4 (9)/40 (91) | 5 (10)/45 (90) | 0.01† |
Lenght percentile (n) | 0.96§ | |||
3–10 p | 8 | 5 | 5 | |
10–25 p | 10 | 8 | 13 | |
25–50 p | 14 | 14 | 16 | |
50–75 p | 9 | 5 | 5 | |
75–90 p | 6 | 6 | 6 | |
90–97 p | 5 | 5 | 5 | |
Weight percentile (n) | 0.82§ | |||
3–10 p | 6 | 5 | 5 | |
10–25 p | 10 | 8 | 13 | |
25–50 p | 12 | 14 | 17 | |
50–75 p | 12 | 7 | 5 | |
75–90 p | 9 | 5 | 5 | |
90–97 p | 7 | 5 | 5 |
Pearson chi-square test;
one-way ANOVA;
Fisher exact test;
SD: standard deviation.
In the analyses conducted, no significant difference was found between the DIC, DC, and control groups in terms of the mean Tau, Trp, Phe, Tyr, Leu, Met, Ile, Pro, Gln, Cit, Hc2, Cys, Cy2, Arg, OH-Lys, Orn, Lys, His, 3-MHIS, 1-MIHS, Val, Thr, Ser, Ala, Asp, or Hyp values (
Mean serum levels of amino acids in phenyketonuric patients and controls
Taurine | 72.46 ± 26.49 | 73.54 ± 30.14 | 79.69 ± 24.37 | 0.34 |
Tryptophan | 52.11 ± 23.1 | 53.67 ± 19.63 | 48.64 ± 14.29 | 0.43 |
Phenylalanine | 845.87 ± 380.03 | 162.68 ± 105.51 | 57.67 ± 16.76 | <0.001*** |
Tyrosine | 53.7 ± 40.12 | 54.33 ± 24.72 | 69.09 ± 26.96 | <0.001*** |
Leucine | 106.04 ± 55.11 | 94.27 ± 34.82 | 104.43 ± 33.26 | 0.35 |
Methionine | 25.26 ± 10.69 | 25.66 ± 7.68 | 28.13 ± 9.87 | 0.26 |
Isoleucine | 49.97 ± 24.4 | 41.98 ± 14.92 | 46.38 ± 17.95 | 0.14 |
Asparagine | 39.3 ± 16.89 | 56.33 ± 21.3 | 59.79 ± 20.64 | <0.001*** |
Proline | 213.87 ± 128.52 | 242.80 ± 103.59 | 246.58 ± 126.68 | 0.31 |
Glutamine | 481.21 ± 126.66 | 511.62 ± 124.11 | 467.61 ± 120.82 | 0.22 |
GABA | 0.96 ± 1.07 | 0.39 ± 0.7 | 0.32 ± 0.57 | <0.001*** |
Citrulline | 32.93 ± 10.9 | 29.35 ± 8.7 | 31.99 ± 14.95 | 0.31 |
Glutamic acid | 39.01 ± 22.94 | 80.47 ± 31.92 | 98.48 ± 42.54 | <0.001*** |
Homocystin | 0.14 (0–1.85) | 0.23 (0–0.99) | 0.18 (0–1.96) | 0.2 |
Cystathionine | 0.24 (0–0.85) | 0.3 (0–1.02) | 0.25 (0–1.36) | 0.67 |
Cystine | 30.46 ± 13.13 | 31.77 ± 11.84 | 30.08 ± 9.86 | 0.75 |
Arginine | 68.69 ± 25.75 | 72.84 ± 30.41 | 77.69 ± 27.13 | 0.25 |
Hydroxylysine | 1.23 (0–32.58) | 1.18 (0–19.97) | 1.25 (0–11.3) | 0.13 |
Ornithine | 69.99 ± 22.92 | 72.87 ± 31.58 | 79.32 ± 26.54 | 0.13 |
Lysine | 138.69 ± 63.3 | 127.94 ± 50.06 | 121.52 ± 37.65 | 0.65 |
Histidine | 58.14 ± 34.44 | 53.05 ± 21.52 | 50.82 ± 25.91 | 0.17 |
3-methylhistidine | 1.86 (0.36–16.8) | 1.71 (0.16–4.39) | 1.98 (0.30–5.95) | 0.34 |
1-methylhistidine | 1.35 (0.23–5.99) | 1.1 (0.48–7.47) | 1.04 (0.42–9.74) | 0.72 |
Valine | 190.56 ± 91.52 | 169.54 ± 62.43 | 171 ± 55.76 | 0.26 |
Threonine | 109.75 ± 56.74 | 117.71 ± 38.93 | 114.67 ± 45.54 | 0.70 |
Serine | 132.62 ± 40.3 | 140.07 ± 42.70 | 144.5 ± 31.99 | 0.30 |
Alanine | 321.10 ± 129.26 | 372.5 ± 136.02 | 345.72 ± 145.27 | 0.17 |
Aspartic acid | 11.91 ± 7.19 | 12.38 ± 6.98 | 13.1 ± 10.26 | 0.75 |
Glycine | 305.1 ± 105.19 | 202.82 ± 73.99 | 174.73 ± 102.28 | <0.001*** |
Hydroxyproline | 9.50 ± 3.35 | 9.94 ± 3.95 | 9.98 ± 2.35 | 0.7 |
SD, Standard deviation; GABA, γ-aminobutyric acid.
Mean ± SD and
Post hoc analysis of blood plasma amino acid levels with significant differences
Phenylalanine | <0.001 | <0.001 | <0.001 |
Tyrosine | >0.99 | <0.001 | 0.004 |
GABA | 0.005 | <0.001 | 0.92 |
Glycine | <0.001 | <0.001 | 0.47 |
Asparagine | <0.001 | <0.001 | 0.81 |
Glutamic acid | <0.001 | <0.001 | 0.06 |
DC, diet compatible group; DIC, diet incompatible group; GABA, γ-aminobutyric acid.
One-way ANOVA with Bonferroni post hoc correction applied.
A significant difference was observed between the groups in the mean GABA, Gly, Glu and Asn levels (
The Pearson correlation analysis revealed a positive correlation between the GABA and Phe (
Correlation between plasma levels of phenylalanine and other amino acids
Phenylalanine–GABA | 0.462 | <0.001 |
Phenylalanine–glycine | 0.511 | <0.001 |
Phenylalanine–asparagine | −0.412 | <0.001 |
Phenylalanine–glutamic acid | −0.475 | <0.001 |
Numerous congenital metabolic diseases can be diagnosed by using a dried blood spot (heel prick) test in the early neonatal period. Early diagnosis of phenylketonuria is extremely important, especially as it is an important cause of preventable mental retardation. Phenylketonuria is common in geographical regions where consanguineous marriages, such as in Turkey and Iran, are frequent [16, 17]. We found that the rates of consanguineous marriages in the parents and a history of phenylketonuria in siblings were higher in children with classic phenylketonuria than they were in healthy children.
Compliance with dietary treatment is most effective in infancy and childhood [18]. The diet severely interferes with culturally normal eating habits, particularly in older children and adolescents, and this often results in problems with compliance with dietary treatment recommendations [5, 18]. In the present study, the ages of the patients in the DC and DIC groups were similar. We consider that sociocultural factors, such as seasonal agricultural work and refugee life, may affect this situation. Indeed, in the present study, we found that refugees were more common among the DIC group patients.
Especially in regions where phenylketonuria is more common, besides early diagnosis, close follow-up of patients is also necessary. Depending on the age of the patients and their adherence to the diet (blood Phe level), white matter abnormalities (WMA) may arise in the brain tissue of patients with phenylketonuria, and cognitive functions of children may be adversely affected [19,20,21]. Although the pathogenesis of resulting WMA and the severity of adversely affected cognitive functions have not been fully elucidated, it has been shown that WMA may regress within 6 months with decreased blood Phe levels [3, 19, 22]. Various scoring tests and cranial magnetic resonance imaging (MRI) techniques are used in the follow-up of a patient's cognitive functions [2].
While the blood Phe level can be measured precisely from venous blood using LC-MS/MS, many other variables can be measured simultaneously. One of these variables is the blood Tyr level. Current recommendations are to add Tyr to the diet in the treatment of patients with phenylketonuria [2]. In our study, the mean plasma Tyr levels in the patients with phenylketonuria (DIC and DC groups) were found to be lower than that of participants in the control group, suggesting that Tyr supplement added to the diet might be clinically beneficial in patients with phenylketonuria. In the present study, the plasma levels of neurotransmitter AAs, which are considered to play an important role in the CNS functions, have been investigated along with the blood Phe level. Yuan et al. [23] revealed that decreased GABA level and increased Asp, Glu, Tau, and
As is seen in various studies, plasma AA levels may vary in many diseases affecting the CNS. To our knowledge, the present study is the first to show the relationship between dietary compliance and plasma excitatory and inhibitory AA levels in patients with phenylketonuria. We found that the mean plasma GABA and Gly values were higher, and the mean plasma Glu and Asn values were lower in the DIC group than they were in the DC and control groups. As expected, no significant difference in levels between the DC and control groups was observed, except for the mean plasma levels of Phe and Tyr. A positive correlation was found between plasma Phe level and both GABA and Gly levels, whereas we found a negative correlation between plasma Phe levels and both Glu and Asn levels.
Our present study is limited because no intelligence test was performed on the patients in this situation, so any correlation between plasma Phe level and intelligence test score could not be evaluated. Failure to determine cerebrospinal fluid levels of neurotransmitters and lack of results of neuromotor development tests (e.g., Denver) of patients can be considered as a limitation. Socioeconomic parameters, such as parental education level and monthly income, which might affect dietary compliance, were not evaluated in the present study. Multicenter studies to be conducted with plasma AA analysis results of patients with phenylketonuria in different clinical centers are warranted.
High blood plasma levels of inhibitory AAs, such as GABA and Gly, and low plasma levels of excitatory AAs, such as Asn and Glu, were measured in patients in Sanliurfa province, Turkey, with phenylketonuria who did not follow their diets. The plasma levels of excitatory and inhibitory AAs may be used as auxiliary parameters in the follow-up of cognitive functions of patients with phenylketonuria. More extensive studies are needed to demonstrate any negative association of cognitive function and the plasma levels of these AAs.