Edited by: David Warburton, Children’s Hospital Los Angeles, USA
Reviewed by: Bernadette Marie Levesque, Boston University, USA; Hans Fuchs, University Medical Center Freiburg, Germany
Specialty section: This article was submitted to Neonatology, a section of the journal Frontiers in Pediatrics
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Provision of adequate nutrients is critical for proper growth and development of the neonate, yet the impact of breastfeeding versus formula feeding on neural maturation has to be fully determined. Using the piglet as a model for the human infant, our objective was to compare neurodevelopment of piglets that were either sow-reared (SR) or artificially reared (AR) in an artificial setting.
Over a 25-day feeding study, piglets (1.5 ± 0.2 kg initial bodyweight) were either SR (
Diffusion tensor imaging, an MRI sequence that characterizes brain microstructure, revealed that SR piglets had greater (
Overall, increases in brain metabolite concentrations, coupled with greater FA values in WM tracts and volume differences in GM of specific brain regions, suggest differences in myelin development and cell proliferation in SR versus AR piglets.
Early-life nutrition, whether provided as human milk, infant formula, or a combination of the two, may influence structural brain development, as well as subsequent cognitive and behavioral development of the child. Epidemiological findings suggest variable impact between breastfeeding and formula feeding on motor development, problem solving skills, and social outcomes (
Magnetic resonance imaging (MRI) techniques allow for a non-invasive means of assessing brain development throughout a period when brain growth is highly dynamic and susceptible to nutrient interventions. However, challenges in pediatric neuroimaging including subject anxiety and discomfort, inability to restrict movement, and the need for imaging during non-sedated sleep often make acquisition of useable data quite difficult (
Use of MRI techniques in the artificially reared (AR) piglet has previously established the piglet as a clinically relevant translational model for the human infant (
Thirty-nine naturally farrowed piglets (intact males,
Per agricultural protocols, all piglets were identified at birth using ear notches, and needle teeth were removed to prevent harm to littermates and the sow. Moreover, piglets received a supplemental iron injection at day 1 of age, but did not undergo other agricultural processing (i.e., tail docking and castrations). Approximately 5 ml of
Artificially reared piglets were fed infant formula modified to meet or exceed the nutrient requirements of the piglet (
All piglets underwent MRI procedures at 21 ± 2 days of age at the Beckman Institute Biomedical Imaging Center using a Siemens MAGNETOM Trio 3-T MRI, with a Siemens 12-channel head coil. Each piglet underwent imaging protocols only once, but scans for each cohort were completed over multiple days due to timing constraints. Piglets were randomly assigned a scan date and order to avoid bias. The piglet neuroimaging protocol included three magnetization prepared rapid gradient echo (MPRAGE) sequences and diffusion tensor imaging (DTI) to assess brain macrostructure and microstructure, respectively, as well as magnetic resonance spectroscopy (MRS) to obtain brain metabolite concentrations. In preparation for MRI procedures, anesthesia was induced using an intramuscular injection of telazol:ketamine:xylazine (50.0 mg of tiletamine plus 50.0 mg of zolazepam reconstituted with 2.50 mL ketamine (100 g/L) and 2.5 mL xylazine (100 g/L); Zoetis, Florham Park, NJ, USA) administered at 0.022 mL/kg BW, and maintained with inhalation of isoflurane (98% O2, 2% isoflurane). Piglets were immobilized during all MRI procedures. Visual observation of a subject’s well-being as well as observations of heart rate, PO2, and percent of isoflurane were recorded every 5 min during the procedure, and every 10 min post-procedure until animals recovered. Total scan time for each pig was approximately 60 min. Imaging techniques are briefly described below, while detailed methods for manual brain segmentation, volumetric assessment, voxel-based morphometry (VBM), and DTI were previously described (
A T1-weighted MPRAGE sequence was used to obtain anatomic images of the piglet brain, with a 0.7 isotropic voxel size. Three repetitions were acquired and averaged using SPM8 in Matlab 8.3, and brains were manually extracted using FMRIB Software Library (FSL) (FMRIB Centre, Oxford, UK). The following sequence-specific parameters were used to acquire T1-weighted MPRAGE data: TR = 1900 ms; TE = 2.49 ms; 224 slices; FOV = 180 mm; flip angle = 9°. Methods for MPRAGE averaging, manual brain extraction were previously described (
Voxel-based morphometry analysis was performed, to assess gray matter (GM) and WM tissue concentrations using SPM8 software (Wellcome Department of Clinical Neurology, London, UK). Manually extracted brains were aligned to piglet brain atlas space using a 12-parameter affine transformation. The “Segment” function of SPM and piglet-specific prior probability tissue maps were then used to segment the brains into GM and WM. The DARTEL toolbox was used with piglet-specific specifications that included changing the bounding box of −30.1 to 30.1, −35 to 44.8, −28 to 31.5, and a voxel size of 0.7 mm3. After the non-linear transformation of the data in the DARTEL procedure, flow fields were created and converted to warp files. The warp files generated were then applied to the subject’s GM and WM. The modulated data were smoothed with a 4-mm full-width half maximum (FWHM) and were subjected to VBM procedures using the statistical non-parametric methods toolbox (SnPM). For VBM analyses, two-sample permutation
For volumetric assessments, individual brains were segmented into 19 different regions of interest (ROIs) using the piglet brain atlas. Total brain and individual region volume analysis was performed in which an inverse warp file for each ROI was generated from the DARTEL-generated warp files for each region using the using the SPM software. Generation of region-specific warp files was previously described (
Diffusion tensor imaging was used to assess WM maturation and axonal tract integrity using
Masks for each ROI from the atlas were non-linearly transformed into the MPRAGE space of each individual pig, and a linear transform was then applied to transfer each ROI into DTI space. A threshold of 0.5 was applied to each ROI, and the data were dilated twice. For each individual ROI, an FA threshold of 0.15 was applied to ensure that we included only WM in that ROI despite the mask expansion.
Magnetic resonance spectroscopy was used to non-invasively quantify metabolites both in hippocampi and in intervening tissue. The MRS spin-echo chemical shift sequence was used with a voxel size of 12 mm × 25 mm × 12 mm and centered over the left and right dorsal hippocampi (Figure
Overall, numerical data (i.e., brain volumes, DTI, and MRS) were subjected to an analysis of variance (ANOVA) with main effects of treatment and sex using the MIXED procedure in SAS v 9.4. Replicate cohort of pigs was included as a random variable, and the threshold of significance was set at
Piglet weights were not different between (
Estimation of absolute whole brain volumes revealed larger (
Absolute (mm3) |
Relative (%TBV) |
|||||||
---|---|---|---|---|---|---|---|---|
Brain region | AR | SR | Treatment | Sex | AR | SR | Treatment | Sex |
Whole brain | 58730 ± 3046 | 73199 ± 3458 | <0.001 | 0.163 | – | – | – | – |
Gray matter | 29677 ± 786 | 34585 ± 939 | <0.001 | 0.202 | 50.87 ± 1.412 | 48.25 ± 1.831 | 0.128 | 0.021 |
White matter | 11155 ± 517 | 13999 ± 586 | <0.001 | 0.108 | 19.07 ± 0.518 | 19.43 ± 0.719 | 0.619 | 0.008 |
Cerebral aqueduct | 117 ± 2.0 | 118 ± 3.3 | 0.643 | 0.351 | 0.20 ± 0.009 | 0.17 ± 0.011 | <0.001 | 0.622 |
Cerebellum | 4581 ± 138 | 5372 ± 154 | <0.001 | 0.821 | 7.85 ± 0.185 | 7.47 ± 0.248 | 0.120 | 0.081 |
Corpus callosum | 1032 ± 29.5 | 1167 ± 34.5 | <0.001 | 0.198 | 1.77 ± 0.054 | 1.62 ± 0.066 | 0.010 | 0.016 |
Caudate | 522 ± 15.3 | 552 ± 17.7 | 0.025 | 0.187 | 0.90 ± 0.034 | 0.77 ± 0.039 | <0.001 | 0.031 |
Fourth ventricle | 138 ± 2.69 | 151 ± 3.66 | <0.001 | 0.611 | 0.24 ± 0.010 | 0.21 ± 0.012 | 0.01 | 0.397 |
Hypothalamus | 529 ± 14.1 | 602 ± 16.0 | <0.001 | 0.377 | 0.91 ± 0.033 | 0.84 ± 0.038 | 0.015 | 0.04 |
Internal capsule | 4734 ± 168 | 5641 ± 189 | <0.001 | 0.131 | 8.12 ± 0.235 | 7.85 ± 0.305 | 0.342 | 0.018 |
Left cortex | 16364 ± 385 | 18504 ± 437 | <0.001 | 0.216 | 28.07 ± 0.769 | 25.80 ± 0.942 | 0.007 | 0.019 |
Left hippocampus | 574 ± 12.9 | 627 ± 15.4 | <0.001 | 0.906 | 0.99 ± 0.032 | 0.87 ± 0.039 | 0.001 | 0.185 |
Lateral ventricle | 1117 ± 21.5 | 1110 ± 33.1 | 0.854 | 0.868 | 1.93 ± 0.098 | 1.55 ± 0.112 | <0.001 | 0.42 |
Midbrain | 2975 ± 71.5 | 3318 ± 80.6 | <0.001 | 0.532 | 5.11 ± 0.151 | 4.62 ± 0.181 | 0.002 | 0.055 |
Medulla | 2377 ± 62.5 | 2744 ± 70.4 | <0.001 | 0.399 | 4.08 ± 0.108 | 3.83 ± 0.141 | 0.064 | 0.054 |
Olfactory bulb | 2948 ± 59.1 | 3332 ± 71.7 | <0.001 | 0.261 | 5.06 ± 0.131 | 4.65 ± 0.167 | 0.010 | 0.024 |
Pons | 849 ± 16.7 | 918 ± 18.4 | <0.001 | 0.454 | 1.46 ± 0.047 | 1.29 ± 0.057 | 0.001 | 0.093 |
Putamen | 1130 ± 31.0 | 1301 ± 36.2 | <0.001 | 0.086 | 1.94 ± 0.062 | 1.81 ± 0.077 | 0.061 | 0.016 |
Right cortex | 15479 ± 346 | 17588 ± 394 | <0.001 | 0.204 | 26.56 ± 0.747 | 24.53 ± 0.911 | 0.011 | 0.021 |
Right hippocampus | 631 ± 16.2 | 700 ± 19.3 | <0.001 | 0.819 | 1.08 ± 0.036 | 0.97 ± 0.042 | 0.002 | 0.098 |
Thalamus | 2960 ± 65.1 | 3340 ± 76.4 | <0.001 | 0.176 | 5.09 ± 0.162 | 4.66 ± 0.198 | 0.013 | 0.035 |
Third ventricle | 207 ± 4.21 | 216 ± 5.56 | 0.104 | 0.829 | 0.36 ± 0.014 | 0.30 ± 0.016 | <0.001 | 0.197 |
Voxel-based morphometry analysis of GM concentrations revealed higher regional peak intensities (
Comparison | Anatomic region | Cluster (voxels) | Peak-level ( |
Pseudo- |
|||
---|---|---|---|---|---|---|---|
SR > AR | Right cortex | 657 | 0.0002 | 14 | 3 | 10 | 5.44 |
Right cortex |
0.0008 | 10 | 12 | 13 | 3.07 | ||
Olfactory | 417 | 0.0004 | −4 | 25 | −8 | 5.29 | |
Undefined | 85 | 0.0002 | −9 | 8 | −4 | 5.26 | |
Right cortex | 356 | 0.0004 | 10 | 7 | −6 | 5.26 | |
Cerebellum | 398 | 0.0002 | 2 | −23 | 4 | 5.2 | |
Undefined | 1032 | 0.0008 | 6 | 34 | −1 | 5.06 | |
Cerebellum | 149 | 0.0008 | −7 | −20 | 0 | 4.18 | |
Left cortex | 203 | 0.0002 | −4 | 24 | 3 | 3.96 | |
Left cortex | 164 | 0.0004 | −12 | 4 | 10 | 3.88 | |
Undefined | 74 | 0.0006 | 5 | 24 | 4 | 3.69 | |
Medulla | 60 | 0.0008 | 3 | −22 | −15 | 3.62 | |
Cerebellum | 24 | 0.0008 | 9 | −20 | −2 | 3.03 | |
AR > SR | Right cortex | 2149 | 0.0002 | 17 | 14 | 10 | 7.98 |
Left cortex | 1619 | 0.0002 | −16 | 14 | 10 | 6.54 | |
Left cortex |
0.0004 | −13 | 24 | 8 | 5.33 | ||
Caudate | 469 | 0.0008 | 5 | 10 | 7 | 4.82 | |
Left cortex | 272 | 0.0002 | −17 | −1 | −4 | 4.49 | |
Right cortex | 148 | 0.0004 | 3 | 24 | 13 | 4.29 | |
Right cortex | 463 | 0.0008 | 6 | 17 | 17 | 4.04 | |
Left cortex | 315 | 0.0002 | −4 | 19 | 17 | 4.01 | |
Left cortex | 97 | 0.0008 | −17 | 6 | 14 | 3.51 | |
Left cortex | 56 | 0.0002 | 1 | 10 | 15 | 3.36 | |
Right cortex | 90 | 0.0002 | 21 | −5 | 5 | 3.02 | |
Undefined | 53 | 0.0004 | −10 | −2 | 8 | 2.88 | |
Right cortex | 23 | 0.0008 | 20 | 5 | 13 | 2.74 |
Comparison | Anatomic region | Cluster (voxels) | Peak-level ( |
Pseudo- |
|||
---|---|---|---|---|---|---|---|
SR > AR | Right cortex | 522 | 0.0008 | 10 | 10 | 15 | 5.66 |
Right cortex | 1211 | 0.0002 | 3 | 34 | 1 | 5.45 | |
Left cortex | 191 | 0.0006 | −10 | 6 | 17 | 4.93 | |
Thalamus | 94 | 0.0004 | −8 | −1 | −1 | 4.68 | |
Olfactory | 272 | 0.0006 | 4 | 23 | −8 | 4.34 | |
Right cortex | 22 | 0.0008 | 6 | 20 | 15 | 3.27 | |
Undefined | 24 | 0.0006 | 1 | −27 | −8 | 0.09 | |
AR > SR | Right cortex | 1553 | 0.0002 | 17 | 20 | 10 | 6.05 |
Left cortex | 1863 | 0.0002 | −15 | 24 | 10 | 5.9 | |
Left cortex |
0.0002 | −7 | 28 | 13 | 3.23 | ||
Cerebellum | 80 | 0.0006 | −7 | −15 | −1 | 5.37 | |
Internal capsule | 117 | 0.0002 | 7 | 13 | 6 | 5.17 | |
Undefined | 285 | 0.0008 | −6 | 15 | 5 | 5 | |
Right cortex | 348 | 0.0006 | 10 | 9 | −5 | 4.96 | |
Right cortex | 514 | 0.0002 | 14 | −18 | 6 | 4.39 | |
Midbrain | 224 | 0.0002 | 0 | −2 | −5 | 4.11 | |
Internal capsule | 77 | 0.0004 | 10 | 8 | 3 | 4.1 | |
Midbrain | 79 | 0.0008 | 5 | −5 | 3 | 2.68 | |
Right cortex | 483 | 0.0008 | 13 | 30 | 9 | 2.62 | |
Medulla | 252 | 0.0008 | 2 | −12 | −17 | 2.61 | |
Undefined | 28 | 0.0006 | −4 | −4 | 4 | 2.41 | |
Cerebellum | 31 | 0.0008 | −4 | −18 | 4 | 2.26 | |
Right cortex | 50 | 0.0008 | 6 | 16 | 19 | 1.42 |
Due to excessive motion, two piglets (one AR male and one SR female) were not included in this analysis. Diffusion tensor analysis revealed higher (
Experimental treatment |
||||
---|---|---|---|---|
AR | SR | Treatment | Sex | |
White matter from atlas |
0.3000 ± 0.0011 | 0.3084 ± 0.0019 | 0.0005 | 0.6173 |
White matter from DTI |
0.2989 ± 0.0011 | 0.3091 ± 0.0019 | <0.0001 | 0.4217 |
Corpus callosum | 0.2766 ± 0.0034 | 0.2851 ± 0.0060 | 0.2253 | 0.3099 |
Internal capsule | 0.3839 ± 0.0044 | 0.4123 ± 0.0076 | 0.0029 | 0.1462 |
Left cortex | 0.2957 ± 0.0028 | 0.3106 ± 0.0050 | 0.0148 | 0.6764 |
Left hippocampus | 0.2701 ± 0.0049 | 0.2784 ± 0.0072 | 0.2754 | 0.1063 |
Right cortex | 0.2979 ± 0.0014 | 0.3084 ± 0.0023 | 0.0005 | 0.9841 |
Right hippocampus | 0.2719 ± 0.0034 | 0.2734 ± 0.0060 | 0.8233 | 0.0862 |
Thalamus | 0.3099 ± 0.0035 | 0.3204 ± 0.0053 | 0.0683 | 0.8425 |
White matter from atlas | 1.046 ± 0.019 | 1.007 ± 0.020 | 0.0005 | 0.3526 |
White matter from DTI | 1.008 ± 0.018 | 0.985 ± 0.02 | 0.0565 | 0.7453 |
Corpus callosum | 1.247 ± 0.021 | 1.205 ± 0.038 | 0.3345 | 0.8696 |
Internal capsule | 0.871 ± 0.004 | 0.870 ± 0.006 | 0.9798 | 0.4924 |
Left cortex | 1.030 ± 0.018 | 0.988 ± 0.030 | 0.2231 | 0.3477 |
Left hippocampus | 1.110 ± 0.046 | 1.088 ± 0.054 | 0.5886 | 0.5867 |
Right cortex | 1.000 ± 0.015 | 0.980 ± 0.016 | 0.0497 | 0.9418 |
Right hippocampus | 1.048 ± 0.024 | 1.082 ± 0.043 | 0.4883 | 0.0563 |
Thalamus | 0.911 ± 0.011 | 0.919 ± 0.016 | 0.6433 | 0.1602 |
White matter from atlas | 1.380 ± 0.022 | 1.339 ± 0.024 | 0.0005 | 0.2741 |
White matter from DTI | 1.330 ± 0.021 | 1.313 ± 0.023 | 0.1901 | 0.8264 |
Corpus callosum | 1.613 ± 0.031 | 1.566 ± 0.054 | 0.4594 | 0.8707 |
Internal capsule | 1.250 ± 0.006 | 1.287 ± 0.011 | 0.0062 | 0.5208 |
Left cortex | 1.354 ± 0.022 | 1.321 ± 0.034 | 0.3633 | 0.3737 |
Left hippocampus | 1.435 ± 0.057 | 1.423 ± 0.068 | 0.8086 | 0.9655 |
Right cortex | 1.318 ± 0.018 | 1.306 ± 0.019 | 0.2933 | 0.9194 |
Right hippocampus | 1.361 ± 0.033 | 1.397 ± 0.058 | 0.5869 | 0.0326 |
Thalamus | 1.222 ± 0.018 | 1.246 ± 0.026 | 0.3428 | 0.1686 |
White matter from atlas | 0.879 ± 0.017 | 0.841 ± 0.019 | 0.0005 | 0.4111 |
White matter from DTI | 0.847 ± 0.016 | 0.821 ± 0.018 | 0.0272 | 0.7058 |
Corpus callosum | 1.064 ± 0.017 | 1.024 ± 0.030 | 0.2512 | 0.6493 |
Internal capsule | 0.681 ± 0.005 | 0.662 ± 0.007 | 0.0226 | 0.1455 |
Left cortex | 0.868 ± 0.017 | 0.822 ± 0.029 | 0.1678 | 0.3403 |
Left hippocampus | 0.947 ± 0.041 | 0.921 ± 0.047 | 0.4526 | 0.3399 |
Right cortex | 0.840 ± 0.014 | 0.817 ± 0.015 | 0.0159 | 0.9480 |
Right hippocampus | 0.891 ± 0.021 | 0.926 ± 0.037 | 0.4098 | 0.1050 |
Thalamus | 0.756 ± 0.007 | 0.755 ± 0.012 | 0.9731 | 0.1922 |
Due to excessive motion, four piglets (two AR male and two SR female) were not included in this analysis. MRS analysis resulted in quantification of eight brain metabolites (Table
Experimental treatment |
||||
---|---|---|---|---|
Metabolite | AR | SR | Treatment | Sex |
Creatine + Phosphocreatine | 3.48 ± 0.090 (26) | 4.22 ± 0.162 (8) | <0.001 | 0.830 |
Glutamate | 5.70 ± 0.364 (26) | 5.30 ± 0.592 (5) | 0.484 | 0.005 |
Glutamate + Glutamine | 9.43 ± 0.480 (27) | 7.43 ± 0.772 (8) | 0.021 | 0.020 |
Glycerophosphocholine + Phosphocholine | 1.28 ± 0.045 (27) | 1.65 ± 0.083 (8) | 0.001 | 0.430 |
Glutathione | 2.34 ± 0.196 (16) | 2.29 ± 0.365 (5) | 0.897 | 0.646 |
Myo-inositol | 8.04 ± 0.240 (27) | 9.43 ± 0.409 (8) | 0.004 | 0.504 |
4.80 ± 0.185 (26) | 4.98 ± 0.286 (8) | 0.548 | 0.562 | |
5.27 ± 0.131 (26) | 5.66 ± 0.232 (8) | 0.150 | 0.458 |
This study employed MRI techniques to assess the impact of early life nutrition on macro- and microstructural development of the neonatal piglet brain. AR animals were raised on infant formula, altered to meet the nutrient requirements of the piglet, while SR animals received sow’s milk for the duration for the study. Quantification of neurodevelopmental differences between SR and AR piglets were characterized by employing three different MRI techniques. Analyses revealed larger whole brain volumes and proportionally smaller ROIs in SR piglets, differences in diffusion tensor measures between treatments, and altered concentrations of metabolites indicative of accelerated neurodevelopmental trajectory in SR piglets at approximately 3 weeks of age.
The authors acknowledge that the relative social isolation of AR piglets compared with their SR counterparts may be a confounding factor in this study. Group rearing was ruled out in favor of single housing, as metabolic outcomes are commonly required for studies involving assessment of novel compounds added to formula diets. To alleviate the potential impact of social isolation, AR piglets were given opportunities to engage in play with caretakers two to three times per day for the duration of the study. Furthermore, the AR piglet has previously been established as a normative model in nutrition studies (
Over the course of the study, piglet growth differed by dietary treatment. While AR piglets were smaller compared with SR piglets at time of MRI assessment, AR piglet weights tend to vary between studies and these weights are within the typical range observed for AR piglets (
While use of the piglet brain atlas allows for assessment of specific regions within the brain, the authors acknowledge that it is not as sensitive as human and rodent brain atlases. The piglet brain atlas is conservative in the brain regions that are parcellated, in which only easily defined brain regions were included. This inherently leaves interstitial tissue to not be included because it cannot be definitively attributed to specific brain regions. The observed relative values of brain regions in the SR piglets are consistently lower compared with AR piglets. Considering that SR piglets had larger whole brains, we propose that growth and expansion within unsampled space might be driving these decreases in relative values. Future research should focus on more extensive characterization of piglet brain regions to update the brain atlas and include more of the unaccounted interstitial space. Another limitation in our current VBM analysis protocol remains, as it does not allow for separation of cerebrospinal fluid (CSF) as a whole. Although ROI volumes for lateral, third, and fourth ventricle spaces were assessed and found to be higher in the AR group, a holistic picture of CSF-containing space is necessary to accurately interpret this result.
Differences due to sex were also observed in 11 of the 19 ROI assessed, characterized by larger relative volumes in female piglets when compared with males. Previous research using the piglet model revealed overall larger whole brain and regional volumes in males at sexual maturity, yet females reached maximum growth rate of brain regions at an earlier timepoint in the neurodevelopmental timeline (
Voxel-based morphometry analysis revealed volumetric differences in both absolute GM and WM volume concentrations between AR and SR groups. Overall, we observed highly significant differences as indicated by increases in GM volume in the frontal–cortical regions of AR animals. Most significant GM clusters observed in AR piglets were located bilaterally in the rostral part of the brain. Larger voxel clusters of WM were also evident in the left and right cortices of AR animals. Since neurons are largely established prenatally, followed by extensive growth, and expansion in the postnatal period, it is possible that the observed differences in tissue concentrations are due to altered rates of cortical expansion which is occurring at this stage in development (
Diffusion parameters were used to characterize the organization and structural integrity of axonal tracts in the piglet brain. Of these parameters, FA serves as an orientation independent means of assessing anistotropic diffusion of water molecules; providing an indirect, yet sensitive, means of assessing WM development (
Higher FA values of the atlas-generated WM, DTI-generated WM, internal capsule, and left and right cortices were observed in SR piglets when compared with AR piglets. While these results may be indicative of myelination, additional elements such as clustering of Na+ channels, quantification of pre-oligodendrocyte to immature oligodendrocyte ratio, and electrophysiological properties should be assessed before attributing these results solely to myelination (
In human infant studies, high FA and low MD values are observed in early-maturing fiber bundles, such as the internal capsule (
Furthermore, higher AD values present in the internal capsule of SR animals may indicate greater axonal connectivity, while lower AD values of the atlas-generated WM might indicate the effects of pruning. Pruning or competitive elimination refers to environmentally regulated changes in the density of synapses per unit of dendritic length, as well as axonal pruning (
Magnetic resonance spectroscopy provides a measurement of brain metabolites that serve as biomarkers for metabolic efficiency, energy storage, inflammation, structural integrity, and brain integrity (
Choline metabolites were also analyzed using MRS. Choline is important in neurodevelopment, as a precursor for the neurotransmitter acetylcholine, in cell membrane synthesis as a precursor of phosphatidylcholine, and is stored in cellular cytoplasm as phosphocholine. Our data suggest that glycerophosphocholine–phosphocholine levels were higher in SR animals, and this bound form of choline serves as choline storage molecules within the cell, which can then be used as a precursor in myelin synthesis (
Additionally, quantification of glutamate–glutamine (GLU–GLN) is indicative of the abundance of the excitatory neurotransmitter GLU, and the degree of glucose consumption in the brain (
To the best of our knowledge, this study is the first of its kind to characterize neurodevelopmental patterns of the SR piglet. Although only a single timepoint in the invariably changing neonatal neural network was studied, these data provide a foundation for establishing the SR piglet as a normative standard when using the AR piglet as a biomedical species for studying nutritional neuroscience. The authors note that differences in rearing environment and weight of piglets may have also had an impact on observed brain development outcomes. However, this style of rearing and the difference in weight between AR and SR are commonly observed in nutritional neuroscience studies using the piglet model. Thus, it is important to establish a baseline characterization in the brain development of these animals as their use in this field is of relevance. Notable evidence from our DTI measures indicates similarities between SR piglet brain development and breast-fed infant brain development, further justifying this animal model for translational research. Overall results of this study suggest SR piglets exhibit larger whole brain volumes and greater WM maturation at approximately 3 weeks of age compared with their AR counterparts. However, behavioral assessments are required to ascertain functional implications of these variations in brain macro- and microstructure. It is important to note that these data could lay a foundation for future nutritional neuroscience research using the piglet.
RD and C-SL were involved in project conceptualization. RJ and LA were involved in daily project activities. RJ, AM, LA, and RD were involved in data collection and data analysis. All authors were involved in data interpretation and manuscript preparation.
RD received grant funding from Abbott Nutrition. C-SL is an employee of Abbott Nutrition. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The authors would like to acknowledge the University of Illinois Imported Swine Research Laboratory farm staff for their contributions. We would like to also thank Drs. Matt Conrad and Brad Sutton for their knowledge and expertise in neuroimaging procedures, as well as the Beckman Imaging Center technicians for helping to acquire our MRI data. Additional thanks are owed to Antoinette Santos and Jasmine Nadhimi for their role in manual brain extractions. Many thanks to Abbott Nutrition for funding this study.
This project was funded by Abbott Nutrition.
% TBV, percent total brain volume; AD, axial diffusivity; AR, artificially reared; CR-PCR, creatine + phosphocreatine; DTI, diffusion tensor imaging; FA, fractional anisotropy; GLU–GLN, glutamate–glutamine; GM, gray matter; MD, mean diffusivity; MI, myo-inositol; MPRAGE, magnetization prepared rapid gradient echo; MRI, magnetic resonance imaging; MRS, magnetic resonance spectroscopy; RD, radial diffusivity; ROI, region of interest; SR, sow-reared; WM, white matter.