To the Editor: 5q spinal muscular atrophy (5qSMA) is an autosomal recessive neuromuscular disorder caused by the lack of the survival motor neuron (SMN) protein encoded by the SMN1 gene, located at 5q11.2–q13.3.[1] The incidence is 1/10,000–1/6000 live births, and the mutation carrier rate in China is 1/42.[1] Spinal muscular atrophy (SMA) is mainly divided into four subtypes: SMA type I, II, III, and IV, based on the motor milestones ever achieved. Types I–III occur in children,[1] which often result in progressive muscular atrophy and weakness as well as multi-system dysfunction, including nutritional and metabolic issues.[2] Children with SMA may have hidden nutritional and lipid imbalances, despite normal body appearance and anthropometric measurements, making it difficult to detect early and intervene. Fewer studies have elucidated both the nutritional status and lipid metabolism in SMA patients,[2] especially in Asia, which may have some of the highest numbers of SMA patients in the world. To inform the development of targeted nutritional management strategies, this study aimed to investigate the nutritional status and serum lipid profile characteristics in children with SMA, based on a hospital-based case-control study in China. This study was approved by the Ethics Committee of Children's Hospital of Zhejiang University School of Medicine (No. 2019-IRB-171). Written informed consent was obtained from all the patients and their legal guardians. This study was a retrospective review of data from 91 children with SMA types I–III admitted to our clinic and 91 age- and gender-matched healthy children who visited physical examination center of the hospital from July 2019 to May 2022. All the patients were diagnosed as 5qSMA by the gold standard genetic testing method[1] and had no family history of any related disease. Patients with unclear diagnosis or classification and without complete clinical data were excluded. None of the children were treated with disease-modifying treatment drugs or other drug therapies at the time of data recording. No one was on gastrostomy tube feeds or ventilatory assistance. All the patients enrolled in our study had taken the same examinations on anthropometrics and clinical parameters, such as weight, height, serum lipid levels, and so on. Anthropometric data were described by Z scores for weight for age (WAZ), height for age (HAZ), weight for height (WHZ), and body mass index-for-age Z-scores (BAZ/BMIZ) and appropriate reference standards.[3] An abnormal concentration of lipids or lipoproteins in the serum is collectively referred to as dyslipidemia.[4] Additionally, total cholesterol (TC)/high-density lipoprotein (HDL), low-density lipoprotein (LDL)/HDL, and apolipoprotein (Apo) B/Apo A1 are defined as predictive indicators of dyslipidemia-related disease risk with a greater informative value than that of isolated lipid parameters, especially for the risk of cardiovascular diseases (CVDs).[5] Patients over 3 years old who could cooperate also completed the analysis for body composition, including lean body mass (LBM), lean body mass index (LBMI), fat mass (FM), fat mass percentage (FM%), fat mass index (FMI), and bone mineral density (BMD), by dual-energy X-ray absorptiometry (DXA). All the indicators were compared based on the reference value.[6] The differences between two paired samples of normal distribution were evaluated using the paired-samples t-test. Differences between two sets of independent samples of normal distribution were evaluated using the independent-samples t-test, while those of skewed distribution were evaluated using the Mann–Whitney U test. The differences in the percentages between groups were compared using the cross-tabulation chi-squared test. One-way analysis of variance was used to analyze serum lipid data of normal distribution among the type I–III SMA groups and the Kruskal–Wallis test was used for those of skewed distribution. Pearson correlations were calculated between specific body composition and serum lipid indicators among patients with SMA. Statistical analyses were performed using SPSS Statistics (version 26.0, BMI SPSS Inc., Armonk, NY, USA), and P values <0.05 were considered statistically significant. A total of 91 patients with SMA were included, and they all came from the families in the relatively developed areas of southeast China, similar in economic level and with no ethnic difference. Eighty-five of them completed the dietary survey, of which 94.1% (80/85) had moderate or insufficient dietary intake, and their diet structure was reasonable [Supplementary Figures 1 and 2, https://links.lww.com/CM9/B931]. The clinical and anthropometric information of all participants were collected [Supplementary Tables 1–3, https://links.lww.com/CM9/B931]. A significantly higher prevalence of malnutrition (including under- and over-nutrition) was observed among patients (50.5%, 46/91) than among healthy control subjects (23.1%, 21/91) (P <0.01, Supplementary Table 4, https://links.lww.com/CM9/B931). Specifically, a greater difference was observed for under-nutrition, especially in patients with SMA types I and II. Patients with SMA type III had the highest level of malnutrition (especially obesity), reaching 58.1% (18/31), while patients with SMA type I had the highest level of under-nutrition (7/16, with 6/16 of underweight). According to the results, although a statistically significant difference in the mean levels of triglycerides (TG) was found between the SMA and control groups (1.07 ± 0.54 mmol/L vs. 0.82 ± 0.39 mmol/L; P <0.001) [Table 1], they both remained within the normal reference range.[4] Moreover, there was no obvious difference in serum lipid levels among different SMA subtypes or genders [Supplementary Table 5, https://links.lww.com/CM9/B931], which was also found among different genders with SMA types II and III. The levels of HDL and Apo A1 in the SMA group were significantly lower than those in the control group (P <0.001) [Table 1]. In addition, the proportion of the SMA group with HDL and Apo A1 levels lower than normal was higher than that of the control subjects (P <0.001) [Supplementary Table 6, https://links.lww.com/CM9/B931]. Overall, a total of 62.6% (57/91) of children with SMA had at least one abnormal serum lipid level, which was significantly higher than the corresponding percentage in the control group (34.1%, 31/91, P <0.001) [Supplementary Table 6, https://links.lww.com/CM9/B931], and this mostly was caused by the reduction of HDL and Apo A1 [Table 1]. This total comprised 18 cases (19.8%, 18/91) of under-nutrition, 30 cases (33.0%, 30/91) of the normal nutrition, and 9 cases (9.9%, 9/91) of over-nutrition. In addition, the indices of TC/HDL, LDL/HDL, Apo B/Apo A1, and the proportion of SMA patients with index levels elevated over the primary/secondary prevention of CVD risk level were also higher than those of the healthy control subjects (P <0.01) [Supplementary Table 6, https://links.lww.com/CM9/B931]. Table 1 - Comparison of serum lipid levels between patients with SMA and control subjects. Serum lipid profiles* SMA (n = 91) Control (n = 91) t † P value MD (95% CI‡) TG (mmol/L) 1.07 ± 0.54 0.82 ± 0.39 3.705 <0.001 0.25 (0.12, 0.38) TC (mmol/L) 4.34 ± 1.25 4.51 ± 0.77 –1.153 0.252 –0.17 (–0.45, 0.12) Lp(a) (mg/L) 53 (23, 130) 75 (38, 133) –0.771§ 0.440 0.21 (NA) HDL (g/L) 1.16 ± 0.29 1.39 ± 0.25 –6.075 <0.001 –0.23 (–0.30, 0.15) LDL (g/L) 2.65 ± 0.77 2.75 ± 0.54 –0.992 0.324 –0.09 (–0.28, 0.09) Apo Al (mmol/L) 1.20 ± 0.21 1.40 ± 0.14 –8.452 <0.001 –0.20 (–0.25, 0.15) Apo B (mmol/L) 0.74 ± 0.23 0.78 ± 0.16 –1.385 0.170 –0.04 (–0.10, 0.02) TC/HDL 3.98 ± 1.88 3.29 ± 0.53 3.707 <0.001 0.69 (0.32, 1.07) LDL/HDL 2.41 ± 0.90 2.01 ± 0.43 4.166 <0.001 0.40 (0.21, 0.59) Apo B/Apo A1 0.63 ± 0.22 0.56 ± 0.12 2.830 0.006 0.07 (0.02, 0.12) Data are shown as mean ± standard deviation, and median (Q1, Q3).*TG elevation is defined as TG >1.70 mmol/L; TC elevation is defined as TC >5.20 mmol/L; Lp(a) elevation is defined as Lp(a) >500 mg/L; HDL cholesterol decrease is defined as HDL <1.04 mmol/L; low-density lipoprotein (LDL) cholesterol elevation is defined as LDL >3.38 mmol/L; Apo A1 decrease is defined as Apo A1 <1.20 g/L; and Apo B elevation is defined as Apo B >0.90 g/L. The reference risk levels by gender for these three ratios in primary/secondary prevention of cardiovascular diseases were defined as follows: the TC/HDL >5.0/4.0 for males or >4.5/3.5 for females; the LDL/HDL >3.5/3.0 for males or >3.0/2.5 for females; and the Apo B/Apo A1 >1.0/0.8 for males or >0.9/0.7 for females. †t is referred to as the test statistic of the paired-samples t-test. ‡95% CI is referred to as the confidence interval of the mean level of the differences between each paired sample of the SMA and control groups.§ Here the –0.771 is referred to the test statistic Z of the Wilcoxon rank sum test. Apo: Apolipoprotein; MD: Mean difference; Lp(a): Lipoprotein a; SMA: Spinal muscular atrophy; TC: Total cholesterol; TG: Triglycerides. Body composition [Supplementary Table 7, https://links.lww.com/CM9/B931] was examined in 32 patients with SMA type II (16 males) and 28 patients with SMA type III (17 males). Compared with the reference value,[6] the patients' levels of FM% and FMI were much higher, and the levels of the LBMI were lower. However, no significant difference in body composition among different genders and between groups with normal serum lipid and with dyslipidemia in SMA type II and III patients was found [Supplementary Tables 8 and 9, https://links.lww.com/CM9/B931]. Through analysis, FMI and FM% were negatively correlated with the HDL (Pearson r = –0.450, P <0.001; r = –0.323, P = 0.012, respectively) [Supplementary Figure 3, https://links.lww.com/CM9/B931] and Apo A1 levels (r = –0.434, P = 0.001; r = –0.335, P = 0.009, respectively), with a stronger correlation between FMI and HDL or Apo A1 observed in patients with SMA type II (r = –0.593, P <0.001; r = –0.549, P = 0.001, respectively). Moreover, FMI was positively correlated with the LDL/HDL (r = 0.330, P = 0.010) and Apo B/Apo A1 (r = 0.340, P = 0.008) ratios, while FM% was also positively correlated with the two ratios (r = 0.344, P = 0.007; r = 0.425, P = 0.001, respectively). In this study, we comprehensively analyzed the clinical nutritional and serum lipid data in children with SMA and in healthy controls, which, to the best of our knowledge, is one of the few studies in this area . Overall, the prevalence of malnutrition in SMA children was significantly higher than that in the control subjects, especially for under-nutrition. Under the condition that the dietary intake is moderate or insufficient and dietary structure is balanced, 90.5% (54/60) of our patients, including patients with under-nutrition and whose height and weight were within the normal range, had a loss of muscle mass and an accumulation of FM, referred to as sarcopenic obesity (SO).[7] Children with higher FMI or FM% tended to have lower levels of HDL and Apo A1 and higher levels of the cardiovascular risk ratios, especially those children with SMA type II, indicating a potentially increased risk of developing CVDs, such as coronary heart disease and atherosclerosis, in these patients with SO. Nevertheless, no TG or TC abnormalities were observed in our patients — conditions that were reported several times in some western nations.[2] Consequently, lipid metabolism characteristics of SMA still remain to be clarified. With the popularization of disease-modifying drugs, individualized nutritional and lipid metabolic management together with drug therapy may help delay the progression of dyslipidemia and reduce the onset of related complications, such as CVD, in the future and improve the patients' quality of life. Additionally, since our study subjects were almost all children younger than 12 years old, we cannot evaluate the situation of juvenile patients who are in puberty. The case sample size in each SMA subtype was restricted for further refined analysis. Hence, further longitudinal studies are required to elucidate the dynamic changes in the nutritional and lipid metabolic status in patients with SMA. To conclude, children with SMA in China have malnutrition, combined with SO and dyslipidemia, which may increase the risk of CVDs. Thus, effective nutritional management requires further studies to help reduce the risk of related complications as much as possible. Acknowledgments The authors want to thank Mingjuan Jin for her contribution to the statistical methods. Funding This study was supported by grant from the Key Technologies Research and Development Program of Zhejiang Province (No. 2021C03099), Key R&D Program of Zhejiang Province (No. 2022C03167), National Natural Science Foundation (No. 82271735), Zhejiang Province Public Welfare Technology Application Research Project (No. LGC21H090001), and Scientific Research Fund of Zhejiang University (No. XY2022045). Conflicts of interest None.
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