ABSTRACT
Methylmalonic acidemia (MMA) and propionic acidemia (PA) are inherited metabolic disorders affecting valine and isoleucine catabolism. Long‐term therapy mainly involves dietary protein restriction. An amino acid mixture (AAM, medical food) free of the precursor amino acids is frequently used, especially when protein intake does not reach World Health Organization (WHO) recommendations. However, its clinical impact on disease control and patient outcomes remains unclear. Our study aimed to retrospectively review the dietary prescriptions in a cohort of vitamin B12‐unresponsive MMA and PA patients and to analyze their impact on clinical and laboratory parameters. Clinical data, anthropometric measurements and dietary prescriptions were collected from the patients' medical and dietary files. We included 71 patients (38 MMA and 33 PA). Fifty‐nine percent of the patients' dietary prescriptions did not reach the safe WHO‐recommended daily total protein intake. Among these, 28% included AAM supplementation versus 62% in the group of patients that met the WHO recommendations (p < 0.001). AAM was associated with a decrease in mean plasma concentrations of isoleucine and valine. These plasma amino acid concentrations were corrected by isoleucine and valine supplementation; however, leucine/isoleucine and leucine/valine ratios remained elevated in comparison to patients without AAM. Nutritional and clinical scores were worsened by AAM supplementation. We found that MMA/PA patients receiving AAM tend to have altered plasma amino acid concentrations, raising concerns about potential long‐term deleterious consequences of AAM. We recommend prioritizing natural protein intake over AAM when possible, and if not, to carefully monitor and moderately supplement valine and isoleucine to prevent deficiencies.
Keywords: low‐protein diet, medical food, methylmalonic acidemia, MMA, organic acidemia, organic aciduria, PA, propionic acidemia
1. Introduction
Methylmalonic acidemia (MMA, OMIM #251000) and propionic acidemia (PA, OMIM #606054) are inherited metabolic disorders (organic acidemia or aciduria, OA) affecting the catabolism of the branched‐chain amino acids (BCAA) valine and isoleucine. Although leucine is not directly implicated in the enzymatic block, its metabolism and plasma concentrations may be indirectly influenced through shared pathways and competitive interactions within the BCAA pool, particularly under amino acid mixture (AAM) supplementation. These defects induce an accumulation of toxic metabolites upstream of the metabolic block and a lack of succinyl‐CoA, which is essential for the citric acid cycle [1].
Patients with severe neonatal‐onset OA present with metabolic ketoacidosis, hyperammonemia and encephalopathy leading to coma within the first few days of life following a symptom‐free interval. Late‐onset patients may present at any age through a wide array of symptoms [1]. Multiple organs are targeted by the disease, with a great risk of neurological symptoms (from cognitive impairment to Leigh syndrome or coma), but also a risk of cardiomyopathy (mostly in PA) and kidney failure (mostly in MMA) [2, 3, 4]. Such chronic complications are thought to be ascribed to the accumulation of toxic metabolites and/or secondary mitochondrial dysfunction [5, 6, 7].
Acute management is urgently required in case of neurological attack, both at disease onset and during further metabolic decompensations. It may include extra‐corporeal depuration and prevention of catabolism through intravenous glucose and lipid infusion without protein, along with various detoxifying drugs such as l‐carnitine, vitamin B12 (for MMA), and ammonia scavengers in the setting of hyperammonaemia. Long‐term treatment aims at reducing the accumulation of toxic metabolites while, at the same time, maintaining normal physical development and nutritional status, and preventing catabolism [8]. Most patients have strict dietary protein restriction involving specific dietary products throughout their life. The cornerstone of such treatment is the limitation of natural proteins, thereby reducing the intake of essential amino acids that are precursors of toxic organic acids—mainly valine and isoleucine, which have the greatest metabolic impact, and methionine and threonine, which play a smaller role as their catabolic flux into propionyl‐CoA is quantitatively lower than for valine and isoleucine [5]. This diet must provide the recommended daily allowance (RDA) and the estimated safe and adequate daily dietary intake of minerals and vitamins, following the principles of pediatric dietetics [9]. In neonatal MMA and PA, dietary protein is generally restricted to adequate age‐related safe levels. Later in life, the balance between protein malnutrition and metabolic disequilibrium can be challenging in neonatal onset MMA and PA patients, in whom natural protein daily intake falls below safe levels. In such patients, an amino acid mixture (AAM), a medical food free of valine, isoleucine, methionine, and threonine, can be added to the diet to supply additional nitrogen and other essential and nonessential amino acids, in order to promote a protein‐sparing anabolic effect [10]. Regardless, the benefits of such AAM on disease course and outcomes have not been evaluated in OA [11, 12, 13, 14]. As a result, while initial recommendations suggested using AAM to achieve total protein goals in patients [10], the latest version of the guidelines advised more caution regarding their use and emphasized that they should not replace an adequate amount of natural protein [8, 15]. Additionally, single amino acid (SAA, namely valine and isoleucine) supplements are used in MMA and PA to mitigate their deficiencies, which could increase catabolism, hence leading to the accumulation of toxic metabolites [16, 17, 18].
In order to evaluate the effects of AAM and more generally of the dietary treatment in OA, we retrospectively reviewed the dietary prescriptions in a French cohort of MMA and PA patients from 2 different Paris metabolic disease centers, and analyzed their impact on the clinical and biochemical course and outcomes.
2. Material and Methods
2.1. Patients
We included patients with vitamin B12‐unresponsive MMA and PA followed in the reference center for inborn errors of metabolism in Necker‐Enfants Malades hospital (Paris) and Robert‐Debré hospital (Paris). Of note, both centers merged into one single center (Necker) in 2019. According to French legislation, during medical consultations and routine care, we informed the patients and/or their parents or legal representatives that their medical data could be collected for research purposes. Unless specifically declined, their non‐objection was considered as consent, and that was notified in their medical record. All data were anonymized and stored in a secure, password‐protected database, and remained confidential, in accordance with the French and European legislation and regulations on data protection.
2.2. Data Collection
Clinical data, anthropometric measurements and dietary prescriptions were collected from the patients' medical and dietary files. Data were recorded following any changes in dietary prescription. Data from periods of acute metabolic decompensations and after liver and/or kidney transplantation were excluded. The study included all MMA and PA patients from January 1, 1992, to March 31, 2021, except for the deceased patients. MMA diagnosis was confirmed by molecular analysis in all MMA patients (biallelic variants in MMUT or MMAB). For most PA patients, molecular analysis revealed biallelic variants in PPCA or PCCB, while in a few older cases, diagnosis was based solely on characteristic PA metabolite profiles.
Patients were classified into two categories based on the age at onset of the disease: neonatal‐onset before 28 days of life, and later‐onset afterwards. Patients diagnosed pre‐symptomatically (either prenatally or at birth) due to family history were categorized as neonatal or late‐onset based on the age at which their affected sibling (index case) was diagnosed.
We selected the ages of 3 (defined as the visit schedule between 3 and 4.5 years), 6 (defined as the visit schedule between 6 and 7 years prior to school entry), 11 (defined as the visit schedule between 11.5 and 12 years), and 16 years (defined as the visit schedule between 15.5 and 18 years), as “key” ages for conducting outcome‐related analyses.
Dietary prescriptions included the intake of natural proteins, AAM, and single valine and/or isoleucine (SAA). We assumed that 1.2 g of AAM is equivalent to 1 g of protein and “total proteins” referred to the sum of natural protein and such protein equivalent. Total protein intake was calculated as natural protein intake (g) + 0.8 × amino acid mixture (AAM) (g/day). Isoleucine and valine supplementation were not included in the total protein intake. Natural and total protein intakes were calculated per kilogram of body weight and compared to appropriate age and sex established RDA. RDA for protein intake was based on the Institute of Medicine Dietary Reference Intakes for protein and amino acids [19]. The latter RDA being approximately equivalent to the safe level of protein intake according to WHO/FAO guidelines [9, 20].
Plasma amino acid profiles reflecting the dietary prescription were collected sequentially, in conjunction with change in dietary management, in a fasting state (more than 3 h following the last meal). The mean values for each study period were used for the analyses.
2.3. Clinical and Nutritional Evaluations
We defined two scores based on clinical and nutritional evolution, respectively (Table 1).
TABLE 1.
Clinical and nutritional composite scores.
| 0 point | 1 point | 2 points | |
|---|---|---|---|
| Clinical score | |||
| Cardiac signs | — | LVEF < 50% | Anticongestive treatment for heart failure |
| Renal signs | — | Calculated (on cystatin C) or measured (iohexol clearance) GFR < 60 mL/min/1.73 m2 | Chronic dialysis |
| Pancreatic signs | — | 1 acute pancreatitis | > 1 acute pancreatitis |
| Neurocognitive evaluation | — | Specialized schooling | Special needs: impossibility of attending specialized schooling and/or severe intellectual disability |
| Psychiatric signs | — | — | Hallucinations or any behavioral issues, severe autistic features |
| Motor signs | Extrapyramidal syndrome | ||
| Hearing signs | Sensorineural hearing loss | ||
| Eye signs | Optic atrophy or optic neuritis | ||
| Metabolic decompensations | — | > 5 days of hospitalization a | — |
| Severe decompensation | — | Stay in intensive care unit without extra renal depuration a | Stay in intensive care unit with extra renal depuration a |
| Treatment escalation | — | — | Ammonium scavengers a |
| Nutritional score | |||
| Height | — | < −2 SD | |
| Growth hormone treatment | — | Growth hormone | — |
| Enteral feeding | — | Enteral feeding | — |
| Laboratory parameters | — | serum albumin (1 point) and/or vitamins (B12; B9) (1 point)/trace elements (Cu, Zn, Se) (1 point) below the lower limit of normal | |
Abbreviation: LVEF, left ventricular ejection fraction.
Numbers of days of hospitalization in the conventional department or in the intensive care unit and use of specific treatment were taken into account during the period with a given nutritional care.
The clinical severity score included relevant items for organ failures and quality of disease control ranging from 0 to 21.
A nutritional score was built based on anthropometric measurements (1 point if height was below −2 standard deviations), use of growth hormone (1 point), serum albumin levels, and/or vitamins and/or trace elements below the lower limit of normal (1 point for each of the two items), and the use of enteral feeding (1 point). This score ranged from 0 to 6, with higher scores indicating worse nutritional status.
2.4. Statistical Analysis
GraphPad Prism version 5.0 was used for statistical analysis (GraphPad Software, San Diego, CA). Mann–Whitney test was used to compare two groups and Kruskal–Wallis test was used for comparisons between 3 groups or more. Ordinal logistic regression using R (version 4.4.1) module polr from package MASS (version 7.3–61) analyzed associations between several variables such as type of disease, onset time, age at the time of scoring, natural protein intake, AAM intake, and the nutritional and clinical score. Spearman's correlation was applied to evaluate associations between two quantitative variables.
3. Results
3.1. Cohort Description at Diagnosis
Seventy‐one patients were included, comprising 38 with MMA and 33 with PA (Table 2). Five patients were diagnosed pre‐symptomatically, either prenatally or at birth, due to family history. For the other patients, the diagnosis was suspected based on clinical signs and symptoms such as coma or hypotonia, ketoacidosis, and hyperammonemia. The median age at diagnosis was 15 days of life [min = 1; max = 2192] with no significant differences between MMA and PA (p = 0.8567) (Table 2). Considering the neonatal form as patients diagnosed before 28 days of life, 23/38 (61%) MMA patients and 21/33 (64%) PA patients had a neonatal form, while 15/38 (39%) MMA patients and 12/33 (36%) PA patients had a late‐onset form. The diagnosis was confirmed by the typical biochemical profile showing an increase of urine organic acids (methylmalonic acid or propionic acid, propionylglycine and methylcitrate for MMA and PA respectively) and the presence of pathogenic and/or likely pathogenic variants in the MMUT, MMAB (MMA), PCCA, PCCB (PA) genes and/or in vitro functional tests.
TABLE 2.
Cohort description.
| All | Neonatal MMA | Neonatal PA | Late onset MMA | Late onset PA | |
|---|---|---|---|---|---|
| Patients (N) | 71 | 23 | 21 | 15 | 12 |
| Age at diagnosis median [min; max] (days) | 15 [1–2192] | 3.5 [1–22] | 8 [2–28] | 252 [107–2192] | 290 [46–1644] |
| Presymptomatic diagnosis (N) | 5 | 2 | 0 | 1 | 2 |
| Extra corporal depuration at diagnosis (n/N) | 18/71 | 6/23 | 9/21 | 2/15 | 1/12 |
In addition to the usual treatments, extra‐corporeal epuration was required at diagnosis during the initial decompensation in 18/71 (25%) patients: 6/23 (26%) neonatal MMA, 9/21 (42%) neonatal PA, 2/15 (13%) late‐onset MMA and 1/12 (8%) late‐onset PA.
3.2. Clinical and Nutritional Courses of MMA and PA Patients
Data regarding clinical course was available for 55 patients at 3 years of age, 49 patients at 6 years of age, 41 patients at 11 years of age, and 26 patients at 16 years of age (Figure 1). Persistent heart failure requiring treatment was observed almost exclusively in PA during the follow‐up while kidney failure was mainly observed in MMA (52% [20/38] MMA and 18% [6/33] PA patients) (Figure 1B,D). Cognitive impairment was also more frequent in PA than in MMA patients (Figure 1C).
FIGURE 1.
Clinical course of MMA and PA patients. Complications of MMA and PA patients during follow‐up: (A) short stature/requirement for growth hormone treatment, (B) kidney failure, (C) cognitive impairment, (D) heart failure. Data were available for 55 patients at 3 years of age (17 neonatal‐onset MMA, 17 neonatal PA patients, 12 late‐onset MMA, 9 late‐onset PA, respectively), 49 patients at 6 years of age (10 neonatal‐onset MMA, 17 neonatal PA patients, 11 late‐onset MMA, 11 late‐onset PA, respectively), 41 patients at 11 years of age (10 neonatal‐onset MMA, 14 neonatal PA patients, 19 late‐onset MMA, 8 late‐onset PA, respectively), 26 patients at 16 year of age (6 neonatal‐onset MMA, 10 neonatal PA patients, 10 late‐onset MMA, 5 late‐onset PA, respectively) and the all cohort at the last follow‐up visit (23 neonatal‐onset MMA, 21 neonatal PA patients, 15 late‐onset MMA, 12 late‐onset PA, respectively). Short stature was defined by height < −2 SD. Kidney failure was defined by calculated GFR (based on cystatin C) or measured GFR (iohexol clearance when available) < 60 mL/min/1.73 m2. Cognitive impairment was defined by the following criteria impossibility to attend specialized schooling with special needs for nursing home and/or severe intellectual disability and/or psychiatric symptoms. Heart failure was defined by permanent heart impairment with left ventricular ejection fraction < 50% with a need for a specific treatment for cardiac insufficiency.
To further explore the nutritional and clinical courses, we developed two scores: a clinical score and a nutritional score, which were studied throughout the disease's course (see Methods) (Figure 2).
FIGURE 2.
Clinical and nutritional course of MMA and PA patients. Evolution of clinical and nutritional scores according to diagnosis (MMA and PA) (A, C) or according to age of onset (B, D). Multiple group comparisons were made using Kruskall–Wallis test. Comparison between two groups were made using Mann–Whitney test.
Overall, PA patients exhibited a worse clinical score compared to MMA patients (p < 0.0001) (Figure 2A). Age at onset also played a significant role, with neonatal‐onset MMA and PA patients showing higher overall clinical and nutritional scores compared to late‐onset patients (p < 0.0001) (Figure 2B,D). This difference was significant across the cohort as a whole, though not consistently at each individual age point. Complications and clinical deterioration occurred as part of the natural course of OA. Clinical scores tended to increase with age, with a statistically significant worsening between the first visit and age 3 in MMA and between the first visit and age 11 in PA (Figure 2A). Although the absolute increase in MMA scores was modest (0.5 points on a 21‐point scale), it reached statistical significance, indicating a mild but measurable progression of disease burden. No patients in the cohort exhibited the maximum severity clinical score, reflecting overall moderate disease severity. The apparent drop in PA scores at age 16 likely reflects the small number of patients in this age category rather than a true improvement in clinical status. The nutritional severity score also showed a significant increase with age, particularly in MMA patients, with a notable deterioration observed at 6 years of age (Figure 2C). Although the absolute change was modest, it reflects a measurable worsening of nutritional status over time. Of note, the absence of neonatal‐onset data at 16 years (Figure 2B,D) is explained by the fact that neonatal patients had not reached the age of 16 yet and/or missing data hence precluding the calculation of scores. Interestingly, the nutritional score showed a different pattern between neonatal and late‐onset forms, with late‐onset patients having a significantly lower score at the first visit that progressively increased to achieve a comparable value to neonatal‐onset patients at 6 and 11 years of age (Figure 2D).
3.3. Dietary Management of MMA and PA Patients
Details on dietary prescriptions corresponding to 1294 prescriptions (all visits included) in the 71 patients are presented in Table 3.
TABLE 3.
Detailed dietary management of MMA and PA patients.
| All | MMA | PA | p | Neonatal onset | Late onset | p | |
|---|---|---|---|---|---|---|---|
| Prescriptions (N) | 1294 | 630 | 664 | 821 | 473 | ||
| Natural protein intake | |||||||
| Intake (g/kg/day) (mean ± SD) | 0.77 ± 0.33 | 0.76 ± 0.34 | 0.78 ± 0.32 | 0.289 a | 0.69 ± 0.24 | 0.91 ± 0.40 | < 0.0001 a |
| Intake (% WHO safety recommendations) (mean ± SD) | 81 ± 33 | 78 ± 33 | 83 ± 33 | 0.025 a | 70 ± 20 | 99 ± 43 | < 0.0001 a |
| % prescriptions < 75% WHO safety recommendation (n/N [%]) | 679/1294 (52%) | 359/630 (57%) | 320/664 (48%) | 0.002 b | 542/821 (66%) | 137/473 (29%) | < 0.0001 b |
| % prescriptions < 100% WHO safety recommendation (n/N [%]) | 1065/1294 (82%) | 544/630 (86%) | 521/664 (78%) | < 0.0001 b | 762/821 (92%) | 303/473 (64%) | < 0.0001 b |
| AAM supplementation* | |||||||
| AAM (n/N [%]) | 548 (42%) | 240/630 (38%) | 308/664 (46%) | 0.003 b | 448/821 (55%) | 100/473 (21%) | < 0.001 b |
| AAM (g/day) (mean ± SD) | 4.1 ± 5.6 | 3.3 ± 5.1 | 4.8 ± 6.2 | < 0.001 a | 5.3 ± 6.1 | 2.0 ± 4.4 | < 0.001 a |
| Total protein intake | |||||||
| Intake (g/kg/day) (mean ± SD) | 0.93 ± 0.37 | 0.91 ± 0.39 | 0.95 ± 41 | 0.084 a | 0.89 ± 0.32 | 1.00 ± 0.42 | < 0.0001 a |
| Intake (% WHO safety recommendations) (mean ± SD) | 98 ± 40 | 95 ± 41 | 102 ± 39 | 0.004 a | 93 ± 35 | 108 ± 46 | < 0.0001 a |
| % prescriptions < 75% WHO safety recommendation (n/N [%]) | 387/1294 (30%) | 221/630 (35%) | 166/664 (25%) | < 0.001 b | 292/821 (36%) | 95/473 (20%) | < 0.0001 b |
| % prescriptions < 100% WHO safety recommendation (n/N [%]) | 777/1294 (60%) | 409/630 (65%) | 368/664 (55%) | 0.0004 | 527/821 (64%) | 250/473 (53%) | < 0.0001 b |
| Valine supplementation | |||||||
| Prescriptions (n/N [%]) | 148/1294 (11%) | 85/630 (13%) | 63/664 (9%) | 0.02 b | 113/821 (14%) | 35/473 (7%) | 0.0005 b |
| Dosage (mg/day) (mean ± SD) | 350 ± 192 | 393 ± 196 | 307 ± 181 | 0.017 a | 351 ± 167 | 396+/−276 | 0.070 a |
| Isoleucine supplementation | |||||||
| Prescriptions (n/N [%]) | 213/1294 (16%) | 111/630 (18%) | 102/664 (15%) | 0.273 b | 175/821 (21%) | 38/473 (8%) | < 0.0001 b |
| Dosage (mg/day) (mean ± SD) | 261 ± 185 | 370 ± 204 | 305 ± 160 | < 0.001 a | 338 ± 174 | 374 ± 244 | 0.131 a |
Note: Bold values indicate satistical significance.
AAM were prescribed from 0.6 to 25 years of age.
Student t test.
Chi‐square test.
Less than 20% of prescriptions met the 100% WHO safety level requirements for natural protein intake, and this decreased below 10% in neonatal‐onset patients, regardless of the disease (Table 3, Figure 3). Fifty‐two percent of prescriptions had a natural protein intake level below 75% of WHO safety level requirements, which increased to 66% in neonatal‐onset patients. Prescriptions for PA patients had significantly higher natural protein intake compared to MMA patients, although fewer prescriptions reached the 100% WHO safety level requirements.
FIGURE 3.
Dietary management of MMA and PA patients. Natural protein intake (A) and total protein intake (D) in MMA and PA patients. Natural protein intake (B) and total protein intake (E) in neonatal‐onset MMA and PA patients. Natural protein intake (C) and total protein intake (F) in late‐onset MMA and PA patients. Correlations were made using Spearmann correlation test.
Forty‐two percent of prescriptions included supplementation with medical food (AAM), which was significantly more prescribed in PA patients and in neonatal‐onset patients. AAM were prescribed from 0.6 to 25 years of age.
When considering AAM in addition to natural proteins, 60% of prescriptions were below the safe level of WHO requirements, with a higher frequency of MMA patients being below these safe levels compared to PA patients. Significantly, more neonatal‐onset patients had a total protein intake (including both natural protein intake and AAM) below the WHO safety recommendations than late‐onset patients. Total protein intake was also lower in MMA than in PA with a significantly lower prescription of AAM and at a lower dose. As expected, due to greater clinical severity, neonatal‐onset patients had lower natural protein intake than late‐onset patients. Despite a higher prescription and dosage of AAM in neonatal forms compared to late‐onset forms, total protein intake was significantly lower in patients with neonatal onset than in those with the late‐onset form (Figure 3).
Natural protein intake and total protein intake (expressed as a percentage of safe level WHO requirements) showed a decreasing trend over time, particularly in neonatal‐onset patients (Figure 3).
Isolated isoleucine and/or valine supplementation was provided to patients whose plasma concentrations of isoleucine and/or valine repeatedly fell below the lower normal limit. Valine or isoleucine was prescribed in 11% and 16% of prescriptions, respectively. Unexpectedly, despite receiving fewer prescriptions for AAM, MMA patients had higher prescriptions of valine and higher doses of both valine and isoleucine compared to PA patients (Table 3). Neonatal‐onset patients were prescribed isolated valine and isoleucine supplements more frequently, but at equivalent doses to those given to late‐onset patients.
3.4. Association of Clinical and Nutritional Disease Severity With Dietary Management
Natural protein intake decreased when clinical scores increased (i.e., more severe disease), showing a decrease in natural protein intake among more severely affected patients, regardless of the type of disease (Figure 4A,D); in keeping with this, the MMA patients with the higher clinical scores exhibited higher concentrations of plasma methylmalonic acid (Figure S1). Due to the lack of accurate laboratory parameters for PA follow‐up (imperfect reliability of PA urinary metabolites and no available routine plasma metabolite), we did not include PA patients in this analysis.
FIGURE 4.
Association of clinical disease severity and dietary management. Clinical score plotted against natural protein intake, total protein intake and amino acid mixture supplementation according to disease and age at onset. (A) Clinical score according to natural protein intake and disease (MMA/PA). (B) Clinical score according to total protein intake and disease (MMA/PA). (C) Clinical score according to amino acid mixture supplementation and disease (MMA/PA). (D) Clinical score according to natural protein intake and age at onset (neonatal‐onset/late‐onset). (E) Clinical score according to total protein intake and disease (neonatal‐onset/late‐onset). (F) Clinical score according to amino acid mixture supplementation and disease (neonatal‐onset/late‐onset). Multiple group comparison was made using Kruskall–Wallis test.
Total protein intake decreased with increasing clinical scores, although this change did not reach statistical significance in MMA patients (Figure 4B,E). The pattern was not strictly linear, with total protein intake increasing at lower to moderate clinical scores before declining at higher severity levels. An increase in clinical scores was associated with higher AAM intake (Figure 4C,F).
Natural protein intake decreased when nutritional scores increased regardless of the type of disease (Figure 5A,D), showing the potential impact of natural protein intake on nutritional complications. Interestingly, total protein intake did not show a significant association with the nutritional score in neonatal‐onset patients (Figure 5B,E). Nutritional score also showed upward variations when AAM intake increased in both PA and MMA patients, in neonatal and late‐onset forms (Figure 5C,F).
FIGURE 5.
Association of nutritional disease severity and dietary management. Nutritional score plotted against natural protein intake, total protein intake and amino acid mixture supplementation according to disease and age at onset. (A) Nutritional score according to natural protein intake and disease (MMA/PA). (B) Nutritional score according to total protein intake and disease (MMA/PA). (C) Nutritional score according to amino acid mixture supplementation and disease (MMA/PA). (D) Nutritional score according to natural protein intake and age at onset (neonatal‐onset/late‐onset). (E) Nutritional score according to total protein intake and disease (neonatal‐onset/late‐onset). (F) Nutritional score according to amino acid mixture supplementation and disease (neonatal‐onset/late‐onset). Multiple group comparison has been made using Kruskall–Wallis test.
3.5. Plasma Branched‐Chain Amino Acid Concentrations and Association With Dietary Management and Clinical and Nutritional Scores
Plasma BCAA and threonine concentrations were significantly lower in neonatal‐onset patients compared to late‐onset patients (Table 4). Threonine and phenylalanine concentrations were also significantly lower in PA versus MMA.
TABLE 4.
Laboratory parameters in MMA and PA patients.
| All | MMA | PA | p | Neonatal onset | Late onset | p | |
|---|---|---|---|---|---|---|---|
| Number of measurements (N) | 1320 | 643 | 677 | 821 | 473 | ||
| Isoleucine (μmol/L) (mean ± SD) (40–95 μmol/L) | 23 ± 18 | 23 ± 19 | 23 ± 18 | 0.338 | 20 ± 16 | 27 ± 21 | < 0.001 |
| Valine (μmol/L) (mean ± SD) (160–340 μmol/L) | 72 ± 57 | 75 ± 60 | 70 ± 54 | 0.109 | 61 ± 47 | 91 ± 67 | < 0.001 |
| Leucine (μmol/L) (mean ± SD) (80–180 μmol/L) | 48 ± 37 | 46 ± 37 | 48 ± 37 | 0.717 | 45 ± 36 | 52 ± 38 | 0.001 |
| Thréonine (μmol/L) (mean ± SD) (40–230 μmol/L) | 68 ± 55 | 72 ± 57 | 63 ± 51 | 0.002 | 62 ± 53 | 78 ± 57 | < 0.001 |
| Phenylalanine (μmol/L) (mean ± SD) (35–75 μmol/L) | 46 ± 11 | 49 ± 12 | 43 ± 9 | < 0.001 | 46 ± 11 | 46 ± 11 | 0.9972 |
Note: Comparisons between groups were made using Student t test. Bold values indicate statistical significance.
As expected, in patients without AAM or isolated amino acids (valine and/or isoleucine) supplementations, all BCAA (isoleucine, valine, and leucine) but also other essential amino acids such as threonine and phenylalanine were significantly correlated with the total protein intake (equivalent to the natural protein intake in this setting) (data not shown). To evaluate the impact of the medical food (AAM) or single amino acid supplementation (SAA) on BCAA, threonine and phenylalanine plasma concentrations, we normalized their respective plasma concentrations with natural protein intake and compared them according to the dietary modalities. Isoleucine, valine and threonine plasma concentrations, when normalized to natural protein intake, were significantly although moderately (15%–20%) lower in patients with AAM, suggesting that the addition of AAM per se may decrease these metabolite concentrations (Figure 6A,B,D). In comparison, plasma concentrations of leucine and phenylalanine at an equivalent amount of natural protein intake were significantly increased, reflecting the supply of these amino acids by AAM (Figure 6C,E).
FIGURE 6.
Plasma branched‐chain amino acid and other essential amino acids concentrations and association with dietary management. (A)–(C) Plasma isoleucine, valine, leucine. In order to compare the effect of amino acid mixture and of isolated amino acids supplementation, amino acids concentrations have been normalized by natural protein intake. (D) Plasma leucine/isoleucine ratio according to dietary parameters. Dotted gray line: Laboratory reference range for Leu/Val ratio. (E) Plasma leucine/valine ratio according to dietary parameters. Dotted gray line: Laboratory reference range for Leu/Val ratio. Group comparison has been made using Mann–Whitney test. NS: non‐significant.
In patients with AAM, the targeted supplementation of isoleucine and/or valine (SAA) restored isoleucine and valine plasma concentrations (normalized to natural protein intake) compared to patients without AAM (Figure 6A,B). In patients receiving SAA isoleucine and valine plasma concentrations (normalized to natural protein intake) were significantly correlated with the amount of isoleucine or valine taken by patients (mg/day) (Spearmann ρ = 0.2922 p < 0.001 and Spearmann ρ = 0.4171 p < 0.001 for isoleucine and valine, respectively). AAM was associated with moderately increased leucine levels, though with high variance, and also with increased Leu/Ile and Leu/Val ratios (25% and 43%, respectively) (Figure 6C–E). We found increased Leu/Ile and Leu/Val mean ratios well outside the reference intervals in patients with SAA, only partly corrected by selective re‐addition of Ile or Val, contrasting with strictly normal mean ratios in the absence of SAA.
Plasma isoleucine, valine, and leucine showed a modest upward trend with increasing clinical scores (Figure 7). Although this association was less pronounced for valine and isoleucine compared to leucine, the positive slope of the regression lines supports an overall upward direction of the relationship. Greater variability, particularly in neonatal‐onset patients (Figure S2), reflects underlying disease heterogeneity and may visually attenuate the trend without negating it.
FIGURE 7.
Plasma branched‐chain amino acid concentrations and association with clinical and nutritional scores. (A) Concentrations of plasma isoleucine according to clinical score. (B) Concentrations of plasma valine according to clinical score. (C) Concentrations of plasma leucine according to clinical score. (D) Concentrations of plasma isoleucine according to nutritional score. (E) Concentrations of plasma valine according to nutritional score. (F) Concentrations of plasma leucine according to nutritional score. Multiple group comparison has been made using Kruskall–Wallis test.
3.6. Predictors of Clinical and Nutritional Scores in MMA and PA Patients
We showed interactions between clinical and nutritional courses, dietary prescription including the use of AAM and/or SAA and plasma concentrations of BCAA. To discriminate independent factors, we used an ordinal logistic regression model with the following variables: age at the time of scoring, type of disease (MMA or PA), severity of the disease (neonatal‐onset or late‐onset), use of AAM (yes or no) and natural protein intake (% of WHO recommendations) (Table 5).
TABLE 5.
Ordinal logistic regression model to predict clinical and nutritional score in MMA and PA patients.
| Beta | IC 2.5% | IC97.5% | p | |
|---|---|---|---|---|
| Clinical score | ||||
| Age (years) | 0.1227 | 0.1056 | 0.1401 | < 0.0001 |
| Type of disease (PA or MMA) | 0.6029 | 0.3812 | 0.8256 | < 0.0001 |
| Age at diagnosis (late or neonatal) | −0.4338 | −0.6989 | −0.1589 | 0.0019 |
| Medical food, AAM (yes/no) | 0.7057 | 0.4744 | 0.938 | < 0.0001 |
| Natural protein (% of WHO recommendations) | −0.0169 | −0.0223 | −0.0116 | < 0.0001 |
| Nutritional score | ||||
| Type of disease (PA or MMA) | 0.0903 | −0.145 | 0.3258 | 0.4517 |
| Age (years) | 0.0986 | 0.0806 | 0.1168 | < 0.0001 |
| Age at diagnosis (late or neonatal) | −0.4153 | −0.6984 | −0.1339 | 0.0039 |
| Medical food, AAM (yes/no) | 0.7916 | 0.5432 | 1.0417 | < 0.0001 |
| Natural protein (% of WHO recommendations) | −0.0058 | −0.0113 | −0.0004 | 0.0378 |
Note: The following variables were entered in the model: age (years), type of disease (MMA = 1 or PA = 2), age at onset (neonatal‐onset = 1 or late‐onset = 2), use of amino acid mixture supplementation (yes = 1 or no = 0) and natural protein intake (% of WHO recommendations). Bold values indicate statistical significance.
Both clinical and nutritional scores were significantly increased with the AAM supplementation. Age at onset and at the time of scoring were associated with clinical and nutritional scores. PA patients had considerably worse clinical scores. A higher natural protein intake was significantly associated with better clinical and nutritional scores. However, the effect size was modest.
4. Discussion
In this study, we retrospectively analyzed the dietary prescriptions in a large cohort of MMA and PA patients and their impact on the clinical and biochemical outcomes. Here are the several main findings: (1) 60% of prescriptions did not reach the safe WHO recommended daily protein intake; (2) AAM improved total protein intake but were associated with lower plasma concentrations of isoleucine and valine compared to the absence of AAM; (3) Supplementations of isoleucine and valine (SAA) in patients receiving AAM restored comparable isoleucine and valine concentrations compared to patients not receiving AAM, but leucine was higher; (4) Both nutritional and clinical poor outcomes were statistically associated with AAM supplementation, albeit with a very small magnitude of effect. Our current study, conducted within a large cohort, confirms existing data [12, 16] and presents additional findings and correlations.
The dietary management of OA varies especially in some countries that are more prone to use AAM whereas others favor the use of natural proteins alone although natural or total protein intake are determined by individual tolerance in each individual patient [16]. Our data show a slightly higher percentage of patients below daily total protein intake WHO recommendation, compared to previous publications [13, 16, 21]. There is no explanation for this result as we adhered to management guidelines for OA. Perhaps this could be due to stricter therapeutic targets for biochemical markers (methylmalonic and 3‐hydroxypropionic acids in urine) and/or over representation of “severe” MMA/PA patients in our cohort therefore preventing from increasing the protein dietary intake. Regardless, the long‐term complications of the patients included in our cohort are comparable to the ones in the literature [1, 22, 23].
Evaluating the association between plasma amino acid concentrations and AAM supplementation is difficult in this type of study as patients benefiting from AAM were the most severe with the more restricted natural protein intakes. Consequently, absolute concentrations of toxic and restricted metabolites, valine and isoleucine were obviously lower in this population due to lower intake (data not shown). However, this trend was maintained even after normalization to natural protein intake (Figure 6). Our results thus strengthen previous data obtained by Manoli et al. and Molema et al. [12, 16] showing a significant impact of AAM on decreasing isoleucine and valine plasma concentrations. We also found that targeted supplementation of isoleucine and valine restored their plasma values. However, leucine tended to be higher as well as the leucine/isoleucine and leucine/valine ratios (Figure 6). High values of these ratios were suspected to be harmful through competition between BCAA for biological processes and signaling pathways [16]. However, it is unknown if the biochemical alterations that we have observed are large enough to be of clinical relevance.
Different hypotheses were formulated to explain the association between AAM supplementation and lower plasma isoleucine and valine concentrations. Leucine contained in the AAM could possibly increase α‐ketoisocaproate, which is an inhibitor of the branched‐chain ketoacid dehydrogenase kinase and therefore would induce the activation of branched‐chain amino acid dehydrogenase that would lead to higher catabolism of isoleucine and valine [24]. As another possibility, competition between the different BCAA may occur on their common intestinal transporter LAT1 [25, 26]. Another hypothesis could be an increase in protein anabolism in patients with AAM leading to decreased concentrations by consumption of restricted amino acids. However, a recent study suggested impaired protein synthesis in this population [27]. Medical foods for OA are the sole medical foods for inherited metabolic diseases with such an imbalance between leucine and the other BCAA [27].
It remains unknown whether low isoleucine and valine concentrations or the imbalance between them and leucine in AAM could possibly exert any deleterious clinical consequences. Molema and coworkers described an association between AAM supplementation and more “mitochondrial” complications in MMA patients [21]. AAM supplementation was also associated with a decrease in albumin plasma concentration in MMA and PA patients [28]. In a previous study, we demonstrated that lower isoleucine and valine plasma concentrations in patients with AAM supplementation were associated with lower height during puberty in OA patients compared to those without [29]. In our study, it was difficult to evaluate the association between AAM supplementation and outcome as AAM were often prescribed to the more severe patients. However, AAM supplementation appeared as a significant predictor of the worst outcomes of 2 composite scores evaluating clinical and nutritional status, independent from age of onset (neonatal/late), type of disease, and natural protein intake. Given the importance of this question, it would be appropriate to perform controlled or cross‐over clinical trials to address this issue.
The three BCAAs have long been known to exert similar properties. Leucine, in particular, was extensively studied demonstrating its multiple roles in skeletal muscle protein synthesis and anabolism [30, 31], satiety regulation [32], insulin secretion regulation [33]. A key mediator of the effects of leucine is the mTOR complex 1 (mTORC1) protein kinase. It is however established that the three BCAAs exhibit differential effects on the mTOR pathway potentially leading to distinct molecular and metabolic effects [34]. For example, isoleucine and valine were related to the activation of the fibroblast growth factor 21 (FGF21)–uncoupling protein 1 (UCP1) axis [35]. Previous studies in OA patients showed an increase of FGF21 associated with mitochondrial dysfunctions [36]. Decreased BCAA were also associated with cognitive impairment and Alzheimer's disease [37]. Furthermore, an imbalance ratio between BCAA could also impair protein anabolism. This was suggested by Saleemani et al. who have shown an increased total body protein synthesis in 8 propionic academia patients with less unbalanced AAM [27]. Therefore, it could be hypothesized that lower isoleucine and valine concentrations in patients receiving AAM could possibly play a role in worsening outcomes.
Since the initial concerns suggesting a decrease of isoleucine and valine plasma concentrations by AAM [12, 17], single amino acid supplementation of isoleucine and valine was implemented in the therapeutic management of OA patients exhibiting low plasma isoleucine and/or valine concentrations [12, 38, 39]. This is paradoxical and counterintuitive since isoleucine and valine are the precursors of the toxic metabolites accumulating in both MMA and PA. We showed herein that the supplementation with isoleucine and/or valine in patients with AAM allows restoring their plasma concentrations to levels similar to patients that do not receive AAM.
According to a study by Saleemani and coworkers, a ratio of leucine: isoleucine: valine between 1:0.26:0.28 and 1:0.35:0.4 appears to be optimal to promote protein synthesis in PA patients [27] as opposed to the actual composition of 1:0:0. This pleads for a further change in the composition of AAM. While waiting for these potential future changes in AAM BCAA composition, such modifications must be prescribed carefully when natural protein intake determined by individual tolerance does not allow achieving a safe protein intake, keeping in mind its potential harmful biochemical impact and its unknown possible contributions to long‐term clinical outcomes.
This study has several limitations. Its retrospective design spans a period during which clinical and dietary practices evolved, including the introduction of isolated valine and isoleucine supplementation. The association between AAM use and worse clinical or nutritional scores may possibly also reflect underlying disease severity rather than, or in addition to a direct causal effect. Likewise, the inclusion of enteral feeding in the nutritional score may capture disease severity—especially in neonatal‐onset forms—although some later‐onset patients also required enteral support. The exclusion of deceased patients may have introduced survival bias toward milder phenotypes. In addition, slight variability in sampling timing relative to AAM administration may have affected plasma amino acid concentrations [12], and other confounders such as genetic background, therapeutic interventions, and organ involvement could have influenced outcomes. These factors should be considered when interpreting the results. Finally, we did not use correction for multiple statistical testing.
5. Conclusions and Perspectives
This retrospective study reveals suggestive, potentially meaningful associations between medical food (AAM), plasma BCAA concentrations, and clinical and nutritional outcomes in MMA and PA. These findings reinforce the principle of prioritizing natural protein intake whenever clinically feasible and support a cautious, individualized use of AAM and SAA supplementation to prevent amino acid deficiencies.
5.1. Clinical Implications
These findings have direct implications for dietary management strategies in patients with MMA and PA. Based on our results, natural protein should be prioritized as the primary source of amino acids, aiming to achieve at least WHO safe levels whenever clinically feasible. When natural protein intake is insufficient to meet requirements, AAM should be introduced cautiously and at the lowest effective dose, recognizing its potential impact on BCAA profiles and clinical outcomes. Close biochemical monitoring of plasma valine and isoleucine concentrations is essential to guide the need for targeted SAA supplementation, which should be titrated to restore physiological levels without inducing imbalance in BCAA ratios. In severe mostly neonatal‐onset phenotypes, where dietary tolerance is particularly limited, clinicians should adopt a stepwise and individualized approach: (1) maximize tolerated natural protein intake, (2) supplement with AAM as needed to cover total protein requirements, and (3) adjust SAA dosing dynamically based on metabolic control and clinical response. This strategy may help to optimize growth and nutritional outcomes while minimizing the potential adverse effects associated with excessive reliance on medical foods.
5.2. Monitoring and Dietary Practice Considerations
Long‐term follow‐up should include regular monitoring of BCAA plasma concentrations and ratios to detect and correct imbalances early, even if their exact clinical significance remains to be clarified. Determination of individual protein tolerance should rely on a combination of clinical, nutritional, and biochemical parameters and be reassessed periodically, particularly during growth or metabolic instability. Recognizing that dietary practices vary between countries and healthcare systems, these insights should contribute to the future harmonization and potential revisions of international dietary guidelines for MMA and PA.
5.3. Future Research
Prospective studies would be needed to establish the causal effects of AAM use on metabolic and clinical outcomes. Such a trial could compare dietary strategies, standardize BCAA monitoring, and evaluate clinical endpoints, thereby providing stronger evidence to refine dietary recommendations and improve long‐term care for patients with MMA and PA.
Author Contributions
D.M. and A.I. participated in the study concept and design, acquisition of data, analysis and interpretation of the data and drafting of the manuscript. M.S., P.d.L., J.‐F.B., A.I., C.P. participated in the study concept and design of the manuscript and supervision of the study. M.S., P.d.L., J.‐F.B., A.I., C.P., C.O. contributed to the critical revision of the manuscript. A.I., A.B., C.P., J.‐B.A., J.B., C.‐M.B., M.A., C.B., S.D., S.D., B.S., E.L.G., A.d.C., C.O., M.D., A.S. participated in the acquisition of data.
Ethics Statement
This study has been carried out in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki).
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Appendix S1: Supporting information.
Acknowledgments
This work was supported by the Direction générale de l'offre de soins du ministère de la Santé (DGOS) through the National Rare Diseases Plan.
Margoses D., Imbard A., Pontoizeau C., et al., “Nutritional Management in Severe Methylmalonic and Propionic Acidemias: How Much Medical Food Is Too Much?,” Journal of Inherited Metabolic Disease 49, no. 1 (2026): e70114, 10.1002/jimd.70114.
Funding: The authors received no specific funding for this work.
Diane Margoses and Apolline Imbard equally contributed to the manuscript.
Academic Editor: Ina Knerr
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
References
- 1. Haijes H. A., Jans J. J. M., Tas S. Y., Verhoeven‐Duif N. M., and van Hasselt P. M., “Pathophysiology of Propionic and Methylmalonic Acidemias. Part 1: Complications,” Journal of Inherited Metabolic Disease 42 (2019): 730–744, 10.1002/JIMD.12129. [DOI] [PubMed] [Google Scholar]
- 2. Morath M. A., Okun J. G., Müller I. B., et al., “Neurodegeneration and Chronic Renal Failure in Methylmalonic Aciduria: A Pathophysiological Approach,” Journal of Inherited Metabolic Disease 31 (2008): 35–43, 10.1007/S10545-007-0571-5. [DOI] [PubMed] [Google Scholar]
- 3. Park K. C., Krywawych S., Richard E., Desviat L. R., and Swietach P., “Cardiac Complications of Propionic and Other Inherited Organic Acidemias,” Frontiers in Cardiovascular Medicine 7 (2020): 617451, 10.3389/FCVM.2020.617451. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Wajner M., “Neurological Manifestations of Organic Acidurias,” Nature Reviews. Neurology 15 (2019): 253–271, 10.1038/S41582-019-0161-9. [DOI] [PubMed] [Google Scholar]
- 5. Collado M. S., Armstrong A. J., Olson M., et al., “Biochemical and Anaplerotic Applications of In Vitro Models of Propionic Acidemia and Methylmalonic Acidemia Using Patient‐Derived Primary Hepatocytes,” Molecular Genetics and Metabolism 130 (2020): 183–196, 10.1016/J.YMGME.2020.05.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Luciani A. and Devuyst O., “Methylmalonyl Acidemia: From Mitochondrial Metabolism to Defective Mitophagy and Disease,” Autophagy 16 (2020): 1159–1161, 10.1080/15548627.2020.1753927. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Schwab M. A., Sauer S. W., Okun J. G., et al., “Secondary Mitochondrial Dysfunction in Propionic Aciduria: A Pathogenic Role for Endogenous Mitochondrial Toxins,” Biochemical Journal 398 (2006): 107–112, 10.1042/BJ20060221. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Forny P., Hörster F., Ballhausen D., et al., “Guidelines for the Diagnosis and Management of Methylmalonic Acidaemia and Propionic Acidaemia: First Revision,” Journal of Inherited Metabolic Disease 44 (2021): 566–592, 10.1002/JIMD.12370. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Joint WHO/FAO/UNU Expert Consultation , “Protein and Amino Acid Requirements in Human Nutrition. World Health Organ Tech Rep Ser 1–265, back cover” (2007). [PubMed]
- 10. Baumgartner M. R., Hörster F., Dionisi‐Vici C., et al., “Proposed Guidelines for the Diagnosis and Management of Methylmalonic and Propionic Acidemia,” Orphanet Journal of Rare Diseases 9 (2014): 130, 10.1186/S13023-014-0130-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Evans M., Truby H., and Boneh A., “The Relationship Between Dietary Intake, Growth, and Body Composition in Inborn Errors of Intermediary Protein Metabolism,” Journal of Pediatrics 188 (2017): 163–172, 10.1016/J.JPEDS.2017.05.048. [DOI] [PubMed] [Google Scholar]
- 12. Manoli I., Myles J. G., Sloan J. L., Shchelochkov O. A., and Venditti C. P., “A Critical Reappraisal of Dietary Practices in Methylmalonic Acidemia Raises Concerns About the Safety of Medical Foods. Part 1: Isolated Methylmalonic Acidemias,” Genetics in Medicine 18 (2016): 386–395, 10.1038/GIM.2015.102. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Pinto A., Evans S., Daly A., et al., “Dietary Practices in Methylmalonic Acidaemia: A European Survey,” Journal of Pediatric Endocrinology & Metabolism 33 (2020): 147–155, 10.1515/JPEM-2019-0277. [DOI] [PubMed] [Google Scholar]
- 14. Saleemani H., Egri C., Horvath G., Stockler‐Ipsiroglu S., and Elango R., “Dietary Management and Growth Outcomes in Children With Propionic Acidemia: A Natural History Study,” JIMD Report 61 (2021): 67–75, 10.1002/JMD2.12234. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Forny P., Hörster F., Baumgartner M. R., Kölker S., and Boy N., “How Guideline Development Has Informed Clinical Research for Organic Acidurias (Et Vice Versa),” Journal of Inherited Metabolic Disease 46 (2023): 520–535, 10.1002/JIMD.12586. [DOI] [PubMed] [Google Scholar]
- 16. Molema F., Gleich F., Burgard P., et al., “Evaluation of Dietary Treatment and Amino Acid Supplementation in Organic Acidurias and Urea‐Cycle Disorders: On the Basis of Information From a European Multicenter Registry,” Journal of Inherited Metabolic Disease 42 (2019): 1162–1175, 10.1002/JIMD.12066. [DOI] [PubMed] [Google Scholar]
- 17. Touati G., Valayannopoulos V., Mention K., et al., “Methylmalonic and Propionic Acidurias: Management Without or With a Few Supplements of Specific Amino Acid Mixture,” Journal of Inherited Metabolic Disease 29 (2006): 288–298, 10.1007/S10545-006-0351-7. [DOI] [PubMed] [Google Scholar]
- 18. van Vliet D., Derks T. G., van Rijn M., et al., “Single Amino Acid Supplementation in Aminoacidopathies: A Systematic Review,” Orphanet Journal of Rare Diseases 9 (2014): 7, 10.1186/1750-1172-9-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Trumbo P., Schlicker S., Yates A. A., and Poos M., “Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein and Amino Acids,” Journal of the American Dietetic Association 102 (2002): 1621–1630, 10.1016/S0002-8223(02)90346-9. [DOI] [PubMed] [Google Scholar]
- 20. Wolfe R. R. and Miller S. L., “The Recommended Dietary Allowance of Protein: A Misunderstood Concept,” JAMA 299 (2008): 2891–2893, 10.1001/JAMA.299.24.2891. [DOI] [PubMed] [Google Scholar]
- 21. Molema F., Haijes H. A., Janssen M. C., et al., “High Protein Prescription in Methylmalonic and Propionic Acidemia Patients and Its Negative Association With Long‐Term Outcome,” Clinical Nutrition 40 (2021): 3622–3630, 10.1016/J.CLNU.2020.12.027. [DOI] [PubMed] [Google Scholar]
- 22. Dao M., Arnoux J. B., Bienaimé F., et al., “Long‐Term Renal Outcome in Methylmalonic Acidemia in Adolescents and Adults,” Orphanet Journal of Rare Diseases 16 (2021): 220, 10.1186/S13023-021-01851-Z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Tuncel A. T., Boy N., Morath M. A., Hörster F., Mütze U., and Kölker S., “Organic Acidurias in Adults: Late Complications and Management,” Journal of Inherited Metabolic Disease 41 (2018): 765–776, 10.1007/S10545-017-0135-2. [DOI] [PubMed] [Google Scholar]
- 24. Harper A. E., Miller R. H., and Block K. P., “Branched‐Chain Amino Acid Metabolism,” Annual Review of Nutrition 4 (1984): 409–454, 10.1146/ANNUREV.NU.04.070184.002205. [DOI] [PubMed] [Google Scholar]
- 25. Verrey F., “System L: Heteromeric Exchangers of Large, Neutral Amino Acids Involved in Directional Transport,” Pflügers Archiv 445 (2003): 529–533, 10.1007/S00424-002-0973-Z. [DOI] [PubMed] [Google Scholar]
- 26. Zhen H., Nakamura K., Kitaura Y., et al., “Regulation of the Plasma Amino Acid Profile by Leucine via the System L Amino Acid Transporter,” Bioscience, Biotechnology, and Biochemistry 79 (2015): 2057–2062, 10.1080/09168451.2015.1060845. [DOI] [PubMed] [Google Scholar]
- 27. Saleemani H., Horvath G., Stockler‐Ipsiroglu S., and Elango R., “Determining Ideal Balance Among Branched‐Chain Amino Acids in Medical Formula for Propionic Acidemia: A Proof of Concept Study in Healthy Children,” Molecular Genetics and Metabolism 135 (2022): 56–62, 10.1016/J.YMGME.2021.12.013. [DOI] [PubMed] [Google Scholar]
- 28. Mobarak A., Dawoud H., Nofal H., and Zoair A., “Clinical Course and Nutritional Management of Propionic and Methylmalonic Acidemias,” Journal of Nutrition and Metabolism 2020 (2020): 1–9, 10.1155/2020/8489707. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Busiah K., Roda C., Crosnier A. S., et al., “Pubertal Origin of Growth Retardation in Inborn Errors of Protein Metabolism: A Longitudinal Cohort Study,” Molecular Genetics and Metabolism 141 (2024): 108123, 10.1016/j.ymgme.2023.108123. [DOI] [PubMed] [Google Scholar]
- 30. Alvestrand A., Hagenfeldt L., Merli M., Oureshi A., and Eriksson L. S., “Influence of Leucine Infusion on Intracellular Amino Acids in Humans,” European Journal of Clinical Investigation 20 (1990): 293–298, 10.1111/J.1365-2362.1990.TB01858.X. [DOI] [PubMed] [Google Scholar]
- 31. Greiwe J. S., Kwon G., McDaniel M. L., and Semenkovich C. F., “Leucine and Insulin Activate p70 S6 Kinase Through Different Pathways in Human Skeletal Muscle,” American Journal of Physiology. Endocrinology and Metabolism 281 (2001): E466–E471, 10.1152/AJPENDO.2001.281.3.E466. [DOI] [PubMed] [Google Scholar]
- 32. Potier M., Darcel N., and Tomé D., “Protein, Amino Acids and the Control of Food Intake,” Current Opinion in Clinical Nutrition and Metabolic Care 12 (2009): 54–58, 10.1097/MCO.0B013E32831B9E01. [DOI] [PubMed] [Google Scholar]
- 33. Panten U., Christians J., Kriegstein E. V., et al., “Studies on the Mechanism of L‐Leucine‐And Alpha‐Ketoisocaproic Acid‐Induced Insulin Release From Perifused Isolated Pancreatic Islets,” Diabetologia 10 (1974): 149–154, 10.1007/BF01219672. [DOI] [PubMed] [Google Scholar]
- 34. Wolfson R. L., Chantranupong L., Saxton R. A., et al., “Sestrin2 Is a Leucine Sensor for the mTORC1 Pathway,” Science 351 (2016): 43–48, 10.1126/SCIENCE.AAB2674. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Yu D., Richardson N. E., Green C. L., et al., “The Adverse Metabolic Effects of Branched‐Chain Amino Acids Are Mediated by Isoleucine and Valine,” Cell Metabolism 33 (2021): 905–922.e6, 10.1016/J.CMET.2021.03.025. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Manoli I., Gebremariam A., McCoy S., et al., “Biomarkers to Predict Disease Progression and Therapeutic Response in Isolated Methylmalonic Acidemia,” Journal of Inherited Metabolic Disease 46 (2023): 554–572, 10.1002/JIMD.12636. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Ikeuchi T., Kanda M., Kitamura H., et al., “Decreased Circulating Branched‐Chain Amino Acids Are Associated With Development of Alzheimer's Disease in Elderly Individuals With Mild Cognitive Impairment,” Frontiers in Nutrition 9 (2022): 1040476, 10.3389/FNUT.2022.1040476. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Bernstein L. E., Burns C., Drumm M., Gaughan S., Sailer M., and P. R. Baker, II , “Impact on Isoleucine and Valine Supplementation When Decreasing Use of Medical Food in the Nutritional Management of Methylmalonic Acidemia,” Nutrients 12 (2020): 473, 10.3390/NU12020473. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Hauser N. S., Manoli I., Graf J. C., Sloan J., and Venditti C. P., “Variable Dietary Management of Methylmalonic Acidemia: Metabolic and Energetic Correlations,” American Journal of Clinical Nutrition 93 (2011): 47–56, 10.3945/AJCN.110.004341. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Appendix S1: Supporting information.
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.