| Literature DB >> 31049877 |
Keliane Liberman1, Rose Njemini1, Yvette Luiking2, Louis N Forti1, Sjors Verlaan3, Jürgen M Bauer4, Robert Memelink1,5, Kirsten Brandt6, Lorenzo M Donini7, Marcello Maggio8, Tony Mets1, Sander L J Wijers2, Cornel Sieber9, Tommy Cederholm10, Ivan Bautmans11.
Abstract
BACKGROUND: A chronic low-grade inflammatory profile (CLIP) is associated with sarcopenia in older adults. Protein and Vitamin (Vit)D have immune-modulatory potential, but evidence for effects of nutritional supplementation on CLIP is limited. AIM: To investigate whether 13 weeks of nutritional supplementation of VitD and leucine-enriched whey protein affected CLIP in subjects enrolled in the PROVIDE-study, as a secondary analysis.Entities:
Keywords: Aged; Cytokines; Dietary supplements; Leucine; Vitamin D; Whey proteins
Mesh:
Substances:
Year: 2019 PMID: 31049877 PMCID: PMC6583678 DOI: 10.1007/s40520-019-01208-4
Source DB: PubMed Journal: Aging Clin Exp Res ISSN: 1594-0667 Impact factor: 3.636
Fig. 1Flow chart
Participants’ baseline characteristics
| Active | Control | Between groups | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Male | Female | Male | Female | ||||||||
|
| Mean ± SD |
| Mean ± SD |
| Mean ± SD |
| Mean ± SD | ||||
| Age (years) | 62 | 77.87 ± 6.60 | 115 | 77.17 ± 6.66 | 0.50 | 66 | 78.02 ± 7.45 | 122 | 78.00 ± 6.70 | 0.99 | 0.40 |
| MMSE (score 0–30) | 62 | 27.94 ± 2.34 | 113 | 28.58 ± 1.43 | 0.03 | 66 | 27.94 ± 3.18 | 121 | 28.63 ± 1.41 | 0.04 | 0.86 |
| BMI (kg/m2) | 62 | 26.27 ± 2.29 | 115 | 25.85 ± 2.69 | 0.30 | 66 | 26.73 ± 2.72 | 122 | 25.95 ± 2.79 | 0.07 | 0.42 |
| Handgrip strength (kg) | 62 | 25.81 ± 7.40 | 114 | 16.53 ± 5.70 | < 0.01 | 66 | 26.17 ± 7.18 | 121 | 16.54 ± 5.29 | < 0.01 | 0.87 |
| SPPB total score (0–9) | 62 | 7.77 ± 1.94 | 115 | 7.33 ± 1.90 | 0.14 | 66 | 7.61 ± 1.92 | 122 | 7.44 ± 1.90 | 0.58 | 0.94 |
| PASE (score 0–793) | 62 | 93.74 ± 64.59 | 113 | 107.70 ± 75.06 | 0.22 | 66 | 113.74 ± 94.24 | 118 | 92.56 ± 58.07 | 0.06 | 0.73 |
| Fat mass (%) | 50 | 30.99 ± 5.31 | 98 | 39.53 ± 5.03 | < 0.01 | 53 | 31.34 ± 4.43 | 111 | 39.45 ± 4.92 | < 0.01 | 0.76 |
| ALM (kg) | 58 | 21.99 ± 3.16 | 105 | 15.72 ± 2.70 | < 0.01 | 58 | 21.44 ± 2.89 | 115 | 15.51 ± 2.30 | < 0.01 | 0.29 |
| NSAID use ( | 6 | 4 | 0.10◊ | 2 | 4 | 1.00◊ | 0.31◊ | ||||
| 25(OH)D (nmol/l) | 62 | 53.22 ± 24.22 | 115 | 49.83 ± 22.27 | 0.35 | 63 | 51.76 ± 19.02 | 122 | 50.81 ± 22.96 | 0.78 | 0.96 |
| Dietary VitD intake (µg/day) | 52 | 3.38 ± 3.14 | 103 | 2.93 ± 2.85 | 0.37 | 52 | 2.89 ± 5.56 | 110 | 3.79 ± 4.21 | 0.26 | 0.35 |
| Dietary protein intake (g/kg body weight/day) | 62 | 1.00 ± 0.28 | 108 | 1.06 ± 0.31 | 0.17 | 65 | 0.96 ± 0.23 | 116 | 1.03 ± 0.31 | 0.12 | 0.26 |
| Pre-albumin (g/l) | 62 | 0.27 ± 0.07 | 115 | 0.25 ± 0.04 | 0.19 | 63 | 0.27 ± 0.048 | 122 | 0.26 ± 0.06 | 0.14 | 0.53 |
| Log_sTNFR1 (ng/ml) | 62 | 0.43 ± 0.13 | 115 | 0.44 ± 0.13 | 0.44 | 66 | 0.48 ± 0.15 | 122 | 0.45 ± 0.15 | 0.16 | 0.08 |
| Log_IL8 (pg/ml) | 62 | 0.61 ± 0.26 | 115 | 0.56 ± 0.28 | 0.32 | 66 | 0.64 ± 0.30 | 122 | 0.61 ± 0.27 | 0.52 | 0.15 |
| Log_IL1RA (pg/ml) | 62 | 1.88 ± 0.48 | 115 | 1.98 ± 0.37 | 0.12 | 66 | 1.95 ± 0.39 | 122 | 1.95 ± 0.45 | 0.96 | 0.97 |
| Log_IL-6 (pg/ml) | 62 | 0.29 ± 0.37 | 115 | 0.26 ± 0.46 | 0.65 | 66 | 0.29 ± 0.48 | 122 | 0.28 ± 0.44 | 0.75 | 0.85 |
| Log_CRP (mg/l) | 62 | 0.40 ± 0.53 | 115 | 0.26 ± 0.43 | 0.05 | 63 | 0.25 ± 0.50 | 122 | 0.31 ± 0.46 | 0.41 | 0.68 |
BMI body mass index (weight/height2), SPPB Short Physical Performance Battery, PASE Physical Activity Scale for the Elderly, ALM appendicular lean mass, NSAID non-steroidal anti-inflammatory drugs
°Unpaired t test
◊Fischer exact test
Associations between baseline inflammatory parameters, and vitamin D and protein status and intake, functional status, and fat mass
| VitD intake (µg/day) | 25(OH)D (nmol/l) | Protein intake (g/kg body weight) | Pre-albumin (g/l) | SPPB (score 0–9) | Fat mass (kg) | PASE (score 0–793) | |
|---|---|---|---|---|---|---|---|
| Log_sTNFR1 (ng/ml) | − 0.09 | − 0.07 | 0.02 | − 0.065 | − 0.27** | − 0.05 | − 0.25** |
| Log_IL8 (pg/ml) | − 0.19** | − 0.12* | 0.05 | − 0.136** | − 0.20** | − 0.19** | − 0.16** |
| Log_IL1RA (pg/ml) | 0.07 | − 0.06 | − 0.07 | − 0.083 | − 0.10 | 0.07 | − 0.11* |
| Log_IL6 (pg/ml) | − 0.04 | − 0.09 | 0.04 | − 0.173** | − 0.14** | 0.01 | − 0.15** |
| Log_CRP (mg/l) | − 0.08 | − 0.05 | − 0.07 | − 0.166** | − 0.14** | 0.18** | − 0.13* |
Pearson correlation coefficients **p < 0.01, * p < 0.05
Fig. 2Effects of active versus control intervention on inflammatory markers. a IL-6, b sTNFR1, c IL-8, d IL1Ra, e CRP bars represent mean values ± 1SD corrected for mean dietary VitD intake as a covariate. Repeated measures ANCOVA; †significantly different from baseline p < 0.05
Explanatory regression analysis for changes in IL-6 after 13-weeks
| 95.0% Confidence interval for | ||||
|---|---|---|---|---|
| Lower bound | Upper bound | |||
| Change in Log_IL6 | ||||
| (Constant) | 0.114 | 0.099 | − 0.022 | 0.250 |
| Dietary VitD intake | − 0.002 | 0.812 | − 0.016 | 0.013 |
| Dietary protein intake | < 0.001 | 0.830 | − 0.002 | 0.002 |
| Change in circulating pre-albumin | − 1.685 | 0.002 | − 2.766 | − 0.604 |
| Change in circulating 25(OH)D | − 0.002 | 0.105 | − 0.004 | < 0.001 |
A multiple linear regression model was computed with change in Log_IL6 as dependent variable, and mean dietary intake of VitD and protein, as well as change in pre-albumin and circulating 25(OH)D values as predictors. Only the change in circulating pre-albumin was significantly associated with changes in Log_IL-6 after 13 weeks; in fact, higher increase in circulating pre-albumin was associated with lower changes in Log_IL6 (B coefficient = − 1.685, p = 0.002), independently from the other factors entered in the model