Variable dietary management of methylmalonic acidemia: metabolic and energetic correlations

Abstract

Background: Isolated methylmalonic acidemia (MMA) is managed by dietary protein restriction and medical food supplementation. Resting energy expenditure (REE) can be depressed in affected individuals for undefined reasons.

Objective: The objective was to document the spectrum of nutritional approaches used to treat patients with MMA, measure REE, and analyze the dependence of REE on body composition, biochemical, and nutritional variables.

Design: Twenty-nine patients with isolated MMA (22 mut, 5 cblA, 2 cblB; 15 males, 14 females; age range: 2-35 y) underwent evaluation. REE was measured with open-circuit calorimetry and compared with predicted values by using age-appropriate equations.

Results: Nutritional regimens were as follows: protein restriction with medical food (n = 17 of 29), protein restriction with medical food and supplemental isoleucine or valine (n = 5 of 29), or the use of natural protein alone for dietary needs (n = 7 of 29). Most mut patients had short stature and higher percentage fat mass compared with reference controls. Measured REE decreased to 74 ± 13.6% of predicted (P < 0.001) in the ≤ 18-y group (n = 22) and to 83 ± 11.1% (P = 0.004) in patients aged >18 y (n = 7). Linear regression modeling suggested that age (P = 0.001), creatinine clearance (P = 0.01), and height z score (P = 0.04) accounted for part of the variance of measured REE per kilogram of fat-free mass (model R² = 0.66, P < 0.0001).

Conclusions: There is wide variation in the dietary treatment of MMA. Standard predictive equations overestimate REE in this population primarily due to their altered body composition and decreased renal function. Defining actual energy needs will help optimize nutrition and protect individuals from overfeeding. This trial is registered at clinicaltrials.gov as NCT00078078.

Figures

FIGURE 1.

A: Weight-, height-, and BMI-for-age z scores for patients in the mut (methylmalonyl-coenzyme A) group of methylmalonic acidemia aged ≤20 y (n = 18) are depicted. Boxes represent the middle 50% of all cases per variable, whereas the remaining 50% is contained between the box and whiskers on each side. The single line inside each box represents the median of the entire data set. The location of this line suggests the skewness in the distribution, when noticeably shifted away from the center, as is the case particularly for the BMI-for-age z score in the mut subgroup. B: Percentage fat mass in males and females aged ≤18 y with the mut subtype of methylmalonic acidemia is depicted. Percentage fat mass was significantly higher in female patients with the mut subtype than in males (P < 0.001, t test). Female patients also had significantly higher percentage fat mass compared with the highest value for white females in the reference population [27.6 ± 6.1% (n = 46), depicted as solid lines ± dotted lines (P < 0.001, t test)] (14). Statistical analyses were performed by using SPSS version 17 (SPSS Inc, Chicago, IL).

FIGURE 2.

Measured and predicted resting energy expenditure (REE) and total kilocalories provided are presented in kilocalories per day for the entire patient population. A: Measured REE compared with predicted REE based on the Schofield equation (17) and total kilocalories per day provided to patients ≤18 y of age (n = 22). B: The same variables for patients >18 y of age in which predicted REE is calculated by the Harris-Benedict equation (20) (n = 7). Measured REE was lower than predicted by any of the equations as well as from the actual total calories provided in both age groups (P < 0.001 for both paired comparisons between measured REE and the values derived from each of the predictive equations as well as measured REE compared with total daily kilocalories provided, paired t test). Statistical analyses were performed by using SPSS version 17 (SPSS Inc, Chicago, IL).

FIGURE 3.

Bivariate correlations for patients in the mut (methylmalonyl-coenzyme A) subgroup with dual-energy X-ray absorptiometry data are depicted between REE (resting energy expenditure) per kilogram of FFM (fat-free mass) and creatinine clearance (mL · min−1 · 1.73 m−2; n = 19), total protein intake (g · kg−1 · d−1; n = 19), and height-for-age z score (age: ≤20 y; n = 15). Pearson's correlation coefficients and P values for each correlation are shown.