- Email: [email protected]
Age-related neuroanatomical differences from the juvenile period to adulthood in mother-reared macaques (Macaca radiata)
BR A IN RE S EA RCH 1 2 26 ( 20 0 8 ) 5 6 –60
a v a i l a b l e a t w w w. s c i e n c e d i r e c t . c o m
w w w. e l s e v i e r. c o m / l o c a t e / b r a i n r e s
Research Report
Age-related neuroanatomical differences from the juvenile period to adulthood in mother-reared macaques (Macaca radiata) Peter J. Pierre a,b , William D. Hopkins c,d , Jarred P. Taglialatela d , Cynthia J. Lees e , Allyson J. Bennett a,b,⁎ a
Department of Physiology and Pharmacology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA Department of Pediatrics, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA c Department of Psychology, Agnes Scott College, Atlanta, GA, USA d Yerkes National Research Center, Emory University, Atlanta, GA, USA e Department of Pathology, Section on Comparative Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA b
A R T I C LE I N FO
AB S T R A C T
Article history:
Basic data on age-related neuroanatomical changes across the juvenile to adult period in
Accepted 2 June 2008
nonhuman primates is sparse, and this gap in knowledge is a serious impediment to
Available online 9 June 2008
translational research aimed at understanding brain development across the lifespan. In this study, magnetic resonance images were analyzed for fifteen mother-reared, socially-
Keywords:
housed bonnet macaques (Macaca radiata) in three age groups: juvenile, adolescent, and
Brain
adult. These data are the first to show age-related changes in gray:white matter ratio and
Monkey
corpus callosum size in bonnet macaques. Juvenile monkeys had higher overall gray:white
Development
matter ratio as compared to adolescent and adult monkeys. Corpus callosum (CC) size
Magnetic resonance imaging (MRI)
varied significantly as a function of age and CC region. Total brain volume was significantly
Maturation
lower for juvenile monkeys as compared to both adolescents and adults. These results are
Bonnet macaque
consistent in pattern with age-related changes in gray:white matter ratio and regional CC differences observed in humans. Continued study of the animals in this cross-sectional study will provide an important means of determining whether differences observed between age groups reflect developmental differences due to variation in the rate of maturation of CC regions. © 2008 Elsevier B.V. All rights reserved.
1.
Introduction
Human research has identified patterns of neuroanatomical change consistent with the changes in behavioral, cognitive,
and socioaffective development throughout the prepubescent to adult period (Paus et al., 2001). Nonhuman primates' relatively long lifespan, extended infancy, and social cognition parallel many aspects of human development (Machado and
⁎ Corresponding author. Department of Physiology and Pharmacology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA. Fax: +1 336 716 1515. E-mail address: [email protected] (A.J. Bennett). 0006-8993/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.brainres.2008.06.001
BR A IN RE S E A RCH 1 2 26 ( 20 0 8 ) 5 6 –6 0
Bachevalier, 2003). What is not as well-described are parallel neuroanatomical changes across the lifecourse in nonhuman primates. A great deal of foundational research has addressed neural development in nonhuman primates. While earlier studies were terminal and cross-sectional, rapid advances and widespread availability of relatively low-cost noninvasive technologies for brain measurement provide new opportunities for characterizing brain development and age-related changes. In both human and nonhuman primates, postnatal neural development is characterized by a pattern of structural connectivity which is expressed by little initial differentiation between gray and white matter as measured by structural imaging. Gray:white matter differentiation occurs in a matter of months, with white matter proliferating in a pattern from ventral to dorsal, from ventral deep structures and areas associated with sensori-motor function, to the dorsal association areas of the occipital, temporal and frontal areas. Recent studies using structural magnetic resonance imaging (MRI) point to a linear increase in white matter and nonlinear changes in cortical gray matter across development in humans (Courchesne et al., 2000). The human brain has an “adult appearance” in terms of gray:white matter differentiation when assessed with structural MRI at approximately 1 year of life (Paus et al., 2001; Almli et al., 2007). Increases in brain volume continue through adolescence, with developmental curves peaking at roughly 12 years of age for frontal and parietal lobes, and at approximately 16 years of age in the temporal lobe (Giedd et al., 1999). The rapid nature of the process of structural development in the human is evident in the fact that brain size approaches 80–90% of adult volume by 5 years of age; importantly, however, white matter expansion and gray matter changes occur into the third decade of development. Very few nonhuman primate studies have used magnetic resonance imaging (MRI) to characterize age-related differences in brain composition and morphology; however, those studies that have addressed age differences demonstrate the expected close similarities between human and nonhuman primate. In a seminal longitudinal study using MRI to uncover developmental changes in brain tissue composition from 1week to 4 years of age in rhesus monkeys, Malkova et al. (2006) reported a 126% increase in white matter between 3 months and 4 years of age, with the largest proportion of the increase occurring in the first year of life. In female rhesus monkeys aged 5–27 years old, Andersen et al. (1999) reported linear decreases in brain volume, with declines in gray:white matter ratio indicating that the decreases were primarily due to loss of gray matter. The gray:white matter ratio was significantly lower in middle-aged (12–17 years) and old (21–27 years) monkeys as compared to the younger group (5–8 years). The decline in gray:white matter ratio slowed after 15 years of age. Specific regions of interest also show morphological changes with age. For example, in human subjects Giedd and others report that the corpus callosum (CC) reaches adult-like volume at 10–14 years of age (for review see, Lenroot et al., 2006; Toga et al., 2006). The corpus callosum, a subcortical structure involved inter-hemispheric communication (Sperry, 1964), is a particularly important target for developmental research because it plays a role in many of the cognitive processes that change between childhood and adulthood. In addition, recent diffusion
57
tensor imaging studies have shown that the connectivity of homotopic fibers that transverse the CC are comparable between humans and rhesus monkeys (Hofer et al., 2008). In humans, the CC increases in size and its structural development is plastic across development (Thompson et al., 2000). Few studies have used MRI to examine age-related changes in CC size in monkeys. In rhesus monkeys, Franklin et al. report both increases in CC area from 8 months to 4.5 years of age (Franklin et al., 2000), as well as sex differences in CC morphology. The majority of nonhuman primate brain imaging studies have focused on rhesus macaques and chimpanzees. The study described here is part of an effort to examine brain morphology and composition in a colony of normally-reared, socially-housed bonnet macaques (Macaca radiata). In this initial study, we provide cross-sectional data from juvenile, adolescent, and adult animals to determine age-related differences in key aspects of brain morphology: total brain volume, gray:white matter ratio, and corpus callosum area.
2.
Results
2.1.
Total brain volume
Age and sex accounted for a significant proportion of variance in total brain volume, R2 =0.54, F(2,14)=6.94, p=0.01. Age predicted total brain volume, β=0.107, SE=0.04, standardized β=0.59, t(11)= 3.00, p=0.01, while sex was marginally associated with differences, β = −6.37, SE = 2.99, standardized β = −0.42, t(11) = −2.12, p=0.055. Juveniles brains were significantly smaller (mean ± SE = 69.15 ± 2.17) than adolescents' (mean ±SE= 82.26 ± 2.18) or adults' brains (mean±SE=78.80±1.90). Follow-up tests showed that juveniles' brains were significantly smaller than those of adolescents (p=0.002; Fisher's Least Significant Difference test) and adults (p=0.02), but adolescents and adults did not differ in total brain volume.
2.2.
Gray:white matter ratio
Age, but not sex, accounted for significant differences in gray; white matter ratio, R2 = 0.64, F(2,14) = 10.80, p = 0.002; age (β =
Fig. 1 – Mean gray:white matter ratio for juvenile, adolescent, and adult bonnet macaques. Error bars are S.E.M. **p = 0.01, ***p = 0.001.
58
BR A IN RE S EA RCH 1 2 26 ( 20 0 8 ) 5 6 –60
−0.003, SE = 0.001, standardized β = − 0.79, t(11) = − 4.59, p = 0.0006) and sex (β = −0.03, SE = 0.05, standardized β = 0.095, p = 0.59). Gray:white matter ratio decreased with age (Fig. 1), F(2,12) = 10.44, p = 0.002. Follow-up tests showed that juveniles' gray:white matter ratio was significantly higher than that of adolescents (p = 0.01) and adults (p = 0.001; Fisher's Least Significant Difference test). Gray:white matter ratio was not significantly different in adolescents as compared to adults (p = 0.20).
2.3.
Corpus callosum
Corpus callosum area differed significantly by age group and across its five subdivisions, F(2,12)=12.39, p=0.001 and F(4,48)= 31.02, p<0.0001, respectively. These results, along with a region by age interaction, F(8,48)=2.64, p=0.02 are illustrated in Fig. 2. The genu area did not differ as a function of age (p = 0.79). Follow-up tests showed significant differences between the age groups for the rostral midbody (rMB), F(2,12) = 5.21, p = 0.02, with larger areas for adults compared to juveniles (p = 0.007) and adolescents (p = 0.055) and no difference between juveniles and adolescents. Similarly, the medial midbody (mMB) area was significantly different as a function of age, F(2,12) = 5.93, p = 0.02, with greater size in adults as compared to juveniles (p = 0.005). There was a nonsignificant trend of greater size in adults compared to adolescents (p = 0.11) and no difference in size for adolescents as compared to juveniles (p = 0.14). A significant age difference was also evident in the caudal midbody (cMB), F(2,12) = 8.33, p = 0.005. The cMB was significantly smaller in juveniles than in adolescents (p = 0.02) or adults (p = 0.003), but did not differ between adolescents and adults. Finally, age differences in the splenium area [F(2,12) = 24.29, p < 0.001] were similar to those of the rostral and medial midbody, with significantly larger areas in adults compared to both juveniles (p < 0.0001) and adolescents (p < 0.0003), and no difference between juveniles and adolescents in splenium size
Fig. 2 – Mean corpus callosum area for juvenile, adolescent, and adult groups for each of the five CC subdivisions: the genu, rostral midbody (rMB), medial midbody (mMB), caudal midbody (cMB), and splenium. In order to control for differences in brain volume, the square root of the area of each CC region was calculated in ratio to the cubic root of the total brain volume (see Smith, 2005). Error bars are S.E.M. + p = 0.055, *p < 0.05, **p < 0.01, ***p < 0.001,****p < 0.0001.
(p = 0.17). There were no sex differences in corpus callosum area, F(1,13) = 0.25, p = 0.62.
3.
Discussion
These data are the first to show age-related differences in gray:white matter ratio, total brain volume, and corpus callosum morphology in bonnet macaques ranging in age from juvenile to adult. The finding of higher gray:white matter ratio in juvenile as compared to adolescent and adult monkeys parallels similar decreases in gray matter volumes reported in humans during the pubertal transition (Toga et al., 2006). Our data are consistent with the report by Malkova et al. (2006) that white matter increases in rhesus monkeys across the infancy and through 5 years of age, and extend this finding to fully adult macaques. Corpus callosum size varied significantly as a function of age and region. Overall, after controlling for total brain volume, corpus callosum size increased with age. Only the genu failed to differ between the age groups. All other callosal regions were larger in adults as compared to juveniles. The medial midbody and splenium were larger in adults as compared to adolescents. Few differences were apparent between adolescents and juveniles. The sample size for this study is small and these results require further testing with a larger number of subjects; however, the results are consistent in pattern with age-related regional differences in CC size observed in humans. For example, Giedd et al. (1999) reported a dominance of posterior region increases in CC size during the pre-adult maturational period and speculated that the difference may be due to earlier maturation of the anterior regions. Our findings parallel this observation, with no differences between the age groups in the most anterior region of the CC (the genu) and pronounced differences between subadult and adult animals in the most posterior CC region, the splenium. Future longitudinal study of these animals will provide an important means of determining whether the differences observed between age groups reflect regional differences in maturation and development of the corpus callosum. In contrast to previous reports in rhesus (Franklin et al., 2000) and capuchin (Phillips et al., 2007) monkeys, we did not find sex differences in overall corpus callosum size, or any regionspecific differences. Our results are similar, however, to those reported from chimpanzees (Dunham and Hopkins, 2006). Sex differences in CC morphology are also found inconsistently in humans. Some of the mitigating factors influencing CC morphology in humans include handedness, age, and how the CC is quantified with respect to covariation with brain size (Driesen and Raz, 1995; Jancke and Steimetz, 1998). We did not include handedness as a variable in our analysis, and this might explain in part why our results differ from those of Phillips et al. (2007) and other studies. These present results must also be interpreted with some caution given the relatively small sample size for male-female comparisons. These are the first data to demonstrate morphological differences in the brains of juvenile, adolescent, and adult bonnet macaques that have been normally-reared with their mothers and in social groups. Previous studies of young monkeys have typically used animals separated from their mothers early in life and reared in a nursery (Malkova et al.,
BR A IN RE S E A RCH 1 2 26 ( 20 0 8 ) 5 6 –6 0
2006). Along with extensive evidence for behavioral, neurochemical, and physiological alterations in nursery-reared monkeys (Harlow and Harlow, 1965; for review Sanchez, Ladd, & Plotsky, 2001), there is also at least one report of differences in brain morphology between juvenile motherand nursery-reared rhesus monkeys (Sanchez et al., 1998). Sanchez et al. report decreased CC size in juvenile nurseryreared animals compared to their mother-reared counterparts. The results of our study of mother-reared monkeys, however, are congruent with those of Malkova et al. (2006) study of nursery-reared animals. Although differences in methodology and species preclude direct comparisons between the two studies, the results are similar in that both report increases in total brain volume and white matter across the juvenile to adult period, with adult-like values obtained in adolescence. It remains for future study to address by direct comparison whether nursery- and mother-reared monkeys differ in less global measures of the rate or pattern of brain maturation across the lifespan, and, particularly, whether these differences persist into adulthood. Taken together, the data reported here demonstrate agerelated changes in brain composition and morphology in bonnet macaques ranging in age from juvenile to full adult. The findings are largely consistent with previous reports in both human and nonhuman primates and provide evidence of decreases in gray:white matter ratio with age, as well as differences in CC size that vary by region between juvenile, adolescent, and adult monkeys. Our findings provide convergent evidence of age-related differences in brain morphology that parallel those uncovered in human studies. Nonetheless, it remains for future studies both to extend the findings to the infant development period and to use a longitudinal approach to uncover the pattern of brain maturation in macaques with normal social experience.
4.
Experimental procedures
4.1.
Subjects
High resolution anatomic MRI images were acquired and analyzed for sixteen bonnet macaques (M. radiata) reared by their mothers and living in social groups. The monkeys live in indoor:outdoor enclosures with multiple perches, structural, and manipulable enrichment. Four adults (2 male, 2 female; M = 123.61 months, SE = 4.29), four adolescents (2 male, 2 female, M = 55.97 months, SE = 10.96), and eight juveniles (4 male, 4 female; M = 18.29 months, SE = 2.40) were scanned. One adult male had a brain abnormality visible upon MRI and was therefore excluded from all analyses. All of the experimental procedures were conducted in accordance with the National Institute of Health Guide for the care and use of animal subjects and the experimental protocol was approved by the Wake Forest University School of Medicine Animal Care and Use Committee.
4.2.
Procedure
Subjects were given initial ketamine anesthesia (15 mg/kg, i.m.) and atropine (0.07 mg/kg, i.m.) and then were intubated and maintained under isofluorane (1.25%) throughout the scan. T1
59
structural images were acquired on a mobile imaging platform (Alliance Imaging, Inc.) with a 1.5 T GE echo-speed Horizon LX MR scanner and quadrature extremity coil (GE Medical Systems, Milwaukee, WI). Axial T1 weighted structural scans were acquired with a 3D spoiled gradient echo (3DSPGR) inversion recovery sequence with the following parameters: echo time (TE) 6.0 ms, repetition time (TR) 30 ms; flip angle 20°; receiver bandwidth 15.63 kHz; in-plane matrix size, 256 × 256; field of view, 18 cm; slice thickness, 1.0 mm; number of slices, 60.
4.3.
Data analysis
4.3.1.
Whole brain volume and gray:white matter segmentation
Initially, each brain was imported into FSL software and the skull removed from volume. Subsequently, the images were segmented into CSF, gray matter, and white matter using FSL. The axial segmented images were then imported into ANALYZE 7.0 software (Biomedical Imaging Resource: Mayo Foundation, Rochester, Minnesota) and the volumes of the gray and white matter were computed within the region-ofinterest function. The gray and white matter volumes included the cerebellum but not brain stem structures. Total brain volume and gray:white matter ratio were each subjected to multiple regression analysis with age and sex as independent variables.
4.3.2.
Corpus callosum measurements
The corpus callosum (CC) was measured in the mid-saggital slice. Using ANALYZE 7.0 software, a rectangular box was drawn around the CC, which divided the CC into 5 equally-spaced regions (Sanchez et al., 1998) that were traced manually with a mouse-controlled onscreen tool to quantify the area of each region. Subdivisions included: the genu, rostral midbody (rMB), medial midbody (mMB), caudal midbody (cMB), and splenium. In order to control for differences in brain volume, all subsequent analysis was performed with the square root of the area of each CC region calculated in ratio to the cubic root of the total brain volume (see Smith, 2005). Repeated-measures analysis of variance with age group (juvenile, adolescent, adult) as a between-groups factor was conducted on the CC area measures. Analysis of variance with Fisher's Least Significant Difference (LSD) were used as follow-up tests to determine statistically significant differences between age groups for each region.
Acknowledgments The authors gratefully acknowledge the technical contributions of Maria Blevins, Christopher Corcoran, and Jessica Christenson. We also appreciate Dr. Mark L. Laudenslager for his support `and discussions of the bonnet macaque colony. The research was supported by NIH grants AA11997 (AJB), AA13995 (AJB), AA013973 (MLL), NS42867 (WDH), and HD56232 (WDH).
REFERENCES
Almli, C.R., Rivkin, M.J., McKinstry, R.C., 2007. The NIH MRI study of normal brain development (objective-2): newborns, infants, toddlers, and preschoolers. Neuroimage, 35, 308–325.
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Andersen, A.H., Zhang, Z., Zhang, M., Gash, D.M., Avison, M.J., 1999. Age-associated changes in rhesus CNS composition identified by MRI. Brain Res 829, 90–98. Courchesne, E., Chisum, H.J., Townsend, J., Cowles, A., Covington, J., Egaas, B., Harwood, M., Hinds, S., Press, G.A., 2000. Normal brain development and aging: quantitative analysis at in vivo MR imaging in healthy volunteers. Radiology, 216, 672–682. Driesen, N.R., Raz, N., 1995. The influence of sex, age, and handedness on corpus callosal morphology: A meta-analysis. Psychobiology, 23, 240–247. Dunham, L.A., Hopkins, W.D., 2006. Sex and handedness effects on corpus callosum morphology in chimpanzees (Pan troglodytes). Behav Neurosci, 120, 1025–1032. Franklin, M.S., Kraemer, G.W., Shelton, S.E., Baker, E., Kalin, N.H., Uno, H., 2000. Gender differences in brain volume and size of corpus callosum and amygdala of rhesus monkey measured from MRI images. Brain Res 852, 263–267. Giedd, J.N., Blumenthal, J., Jeffries, N.O., Rajapakse, J.C., Vaituzis, A.C., Liu, H., Berry, Y.C., Tobin, M., Nelson, J., Castellanos, F.X., 1999. Development of the human corpus callosum during childhood and adolescence: a longitudinal MRI study. Prog Neuropsychopharmacol, 23, 571–588. Harlow, H.F., Harlow, M.K., 1965. Effects of various mother-infant relationships on rhesus monkey behaviors. In: Foss, B.M. (Ed.), Determinants of Infant Behaviour. Methuen & Co Ltd, London, pp. 15–36. Hofer, S., Merbolt, K.D., Tammer, R., Frahm, J., 2008. Rhesus monkey and human share a similar topography of the corpus callosum as revealed by diffusion tensor MRI in vivo. Cerebral Cortex 18, 1079–1084. Jancke, L., Steinmetz, H., 1998. Brain size: a possible source of interindividual variability corpus callosum morphology. In: Zaidel, E., Iacoboni, M., Pascual-Leone, A.P. (Eds.), The Role of the Corpus Callosum in Sensory-motor Integration: Anatomy, Physiology and Behavior. Plenum Press, New York.
Lenroot, R.K., Giedd, J.N., 2006. Brain development in children and adolescents: insights from anatomical magnetic resonance imaging. Neurosci Biobehav Rev 30, 718–729. Machado, C.J., Bachevalier, J., 2003. Non-human primate models of childhood psychopathology: the promise and the limitations. J Child Psychol Psychiatry 44, 64–87. Malkova, L., Heuer, E., Saunders, R.C., 2006. Longitudinal magnetic resonance imaging study of rhesus monkey brain development. European Journal of Neuroscience 24, 3204–3212. Paus, T., Collins, D.L., Evans, A.C., Leonard, G., Pike, B., Zijdenbos, A., 2001. Maturation of white matter in the human brain: a review of magnetic resonance studies. Brain Res Bull 54, 255–266. Phillips, K.A., Sherwood, C.C., Lilak, A.L., 2007. Corpus callosum morphology in capuchin monkeys is influenced by sex and handedness, PLoS. ONE, 2, e792. Sanchez, M.M., Hearn, E.F., Do, D., Rilling, J.K., Herndon, J.G., 1998. Differential rearing affects corpus callosum size and cognitive function of rhesus monkeys. Brain Research, 812, 38–49. Sanchez, M.M., Ladd, C.O., Plotsky, P.M., 2001. Early adverse experience as a developmental risk factor for later psychopathology: evidence from rodent and primate models. Development and Psychopathology, 13, 419–449. Smith, R.J., 2005. Relative size versus controlling for size: interpretation of ratios in research on sexual dimorphism in the human corpus callosum. Current Anthropology, 46, 249–273. Sperry, R.W., 1964. The Great Cerebral Commissure. In: Coopersmith, S. (Ed.), Frontiers of Psychological Research. Scientific American, Inc., San Francisco, pp. 60–70. Thompson, P.M., Giedd, J.N., Woods, R.P., MacDonald, D., Evans, A.C., Toga, A.W., 2000. Growth patterns in the developing brain detected by using continuum mechanical tensor maps. Nature 404, 190–193. Toga, A.W., Thompson, P.M., Sowell, E.R., 2006. Mapping brain maturation. Trends Neurosci, 29, 148–159.
a v a i l a b l e a t w w w. s c i e n c e d i r e c t . c o m
w w w. e l s e v i e r. c o m / l o c a t e / b r a i n r e s
Research Report
Age-related neuroanatomical differences from the juvenile period to adulthood in mother-reared macaques (Macaca radiata) Peter J. Pierre a,b , William D. Hopkins c,d , Jarred P. Taglialatela d , Cynthia J. Lees e , Allyson J. Bennett a,b,⁎ a
Department of Physiology and Pharmacology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA Department of Pediatrics, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA c Department of Psychology, Agnes Scott College, Atlanta, GA, USA d Yerkes National Research Center, Emory University, Atlanta, GA, USA e Department of Pathology, Section on Comparative Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA b
A R T I C LE I N FO
AB S T R A C T
Article history:
Basic data on age-related neuroanatomical changes across the juvenile to adult period in
Accepted 2 June 2008
nonhuman primates is sparse, and this gap in knowledge is a serious impediment to
Available online 9 June 2008
translational research aimed at understanding brain development across the lifespan. In this study, magnetic resonance images were analyzed for fifteen mother-reared, socially-
Keywords:
housed bonnet macaques (Macaca radiata) in three age groups: juvenile, adolescent, and
Brain
adult. These data are the first to show age-related changes in gray:white matter ratio and
Monkey
corpus callosum size in bonnet macaques. Juvenile monkeys had higher overall gray:white
Development
matter ratio as compared to adolescent and adult monkeys. Corpus callosum (CC) size
Magnetic resonance imaging (MRI)
varied significantly as a function of age and CC region. Total brain volume was significantly
Maturation
lower for juvenile monkeys as compared to both adolescents and adults. These results are
Bonnet macaque
consistent in pattern with age-related changes in gray:white matter ratio and regional CC differences observed in humans. Continued study of the animals in this cross-sectional study will provide an important means of determining whether differences observed between age groups reflect developmental differences due to variation in the rate of maturation of CC regions. © 2008 Elsevier B.V. All rights reserved.
1.
Introduction
Human research has identified patterns of neuroanatomical change consistent with the changes in behavioral, cognitive,
and socioaffective development throughout the prepubescent to adult period (Paus et al., 2001). Nonhuman primates' relatively long lifespan, extended infancy, and social cognition parallel many aspects of human development (Machado and
⁎ Corresponding author. Department of Physiology and Pharmacology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA. Fax: +1 336 716 1515. E-mail address: [email protected] (A.J. Bennett). 0006-8993/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.brainres.2008.06.001
BR A IN RE S E A RCH 1 2 26 ( 20 0 8 ) 5 6 –6 0
Bachevalier, 2003). What is not as well-described are parallel neuroanatomical changes across the lifecourse in nonhuman primates. A great deal of foundational research has addressed neural development in nonhuman primates. While earlier studies were terminal and cross-sectional, rapid advances and widespread availability of relatively low-cost noninvasive technologies for brain measurement provide new opportunities for characterizing brain development and age-related changes. In both human and nonhuman primates, postnatal neural development is characterized by a pattern of structural connectivity which is expressed by little initial differentiation between gray and white matter as measured by structural imaging. Gray:white matter differentiation occurs in a matter of months, with white matter proliferating in a pattern from ventral to dorsal, from ventral deep structures and areas associated with sensori-motor function, to the dorsal association areas of the occipital, temporal and frontal areas. Recent studies using structural magnetic resonance imaging (MRI) point to a linear increase in white matter and nonlinear changes in cortical gray matter across development in humans (Courchesne et al., 2000). The human brain has an “adult appearance” in terms of gray:white matter differentiation when assessed with structural MRI at approximately 1 year of life (Paus et al., 2001; Almli et al., 2007). Increases in brain volume continue through adolescence, with developmental curves peaking at roughly 12 years of age for frontal and parietal lobes, and at approximately 16 years of age in the temporal lobe (Giedd et al., 1999). The rapid nature of the process of structural development in the human is evident in the fact that brain size approaches 80–90% of adult volume by 5 years of age; importantly, however, white matter expansion and gray matter changes occur into the third decade of development. Very few nonhuman primate studies have used magnetic resonance imaging (MRI) to characterize age-related differences in brain composition and morphology; however, those studies that have addressed age differences demonstrate the expected close similarities between human and nonhuman primate. In a seminal longitudinal study using MRI to uncover developmental changes in brain tissue composition from 1week to 4 years of age in rhesus monkeys, Malkova et al. (2006) reported a 126% increase in white matter between 3 months and 4 years of age, with the largest proportion of the increase occurring in the first year of life. In female rhesus monkeys aged 5–27 years old, Andersen et al. (1999) reported linear decreases in brain volume, with declines in gray:white matter ratio indicating that the decreases were primarily due to loss of gray matter. The gray:white matter ratio was significantly lower in middle-aged (12–17 years) and old (21–27 years) monkeys as compared to the younger group (5–8 years). The decline in gray:white matter ratio slowed after 15 years of age. Specific regions of interest also show morphological changes with age. For example, in human subjects Giedd and others report that the corpus callosum (CC) reaches adult-like volume at 10–14 years of age (for review see, Lenroot et al., 2006; Toga et al., 2006). The corpus callosum, a subcortical structure involved inter-hemispheric communication (Sperry, 1964), is a particularly important target for developmental research because it plays a role in many of the cognitive processes that change between childhood and adulthood. In addition, recent diffusion
57
tensor imaging studies have shown that the connectivity of homotopic fibers that transverse the CC are comparable between humans and rhesus monkeys (Hofer et al., 2008). In humans, the CC increases in size and its structural development is plastic across development (Thompson et al., 2000). Few studies have used MRI to examine age-related changes in CC size in monkeys. In rhesus monkeys, Franklin et al. report both increases in CC area from 8 months to 4.5 years of age (Franklin et al., 2000), as well as sex differences in CC morphology. The majority of nonhuman primate brain imaging studies have focused on rhesus macaques and chimpanzees. The study described here is part of an effort to examine brain morphology and composition in a colony of normally-reared, socially-housed bonnet macaques (Macaca radiata). In this initial study, we provide cross-sectional data from juvenile, adolescent, and adult animals to determine age-related differences in key aspects of brain morphology: total brain volume, gray:white matter ratio, and corpus callosum area.
2.
Results
2.1.
Total brain volume
Age and sex accounted for a significant proportion of variance in total brain volume, R2 =0.54, F(2,14)=6.94, p=0.01. Age predicted total brain volume, β=0.107, SE=0.04, standardized β=0.59, t(11)= 3.00, p=0.01, while sex was marginally associated with differences, β = −6.37, SE = 2.99, standardized β = −0.42, t(11) = −2.12, p=0.055. Juveniles brains were significantly smaller (mean ± SE = 69.15 ± 2.17) than adolescents' (mean ±SE= 82.26 ± 2.18) or adults' brains (mean±SE=78.80±1.90). Follow-up tests showed that juveniles' brains were significantly smaller than those of adolescents (p=0.002; Fisher's Least Significant Difference test) and adults (p=0.02), but adolescents and adults did not differ in total brain volume.
2.2.
Gray:white matter ratio
Age, but not sex, accounted for significant differences in gray; white matter ratio, R2 = 0.64, F(2,14) = 10.80, p = 0.002; age (β =
Fig. 1 – Mean gray:white matter ratio for juvenile, adolescent, and adult bonnet macaques. Error bars are S.E.M. **p = 0.01, ***p = 0.001.
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−0.003, SE = 0.001, standardized β = − 0.79, t(11) = − 4.59, p = 0.0006) and sex (β = −0.03, SE = 0.05, standardized β = 0.095, p = 0.59). Gray:white matter ratio decreased with age (Fig. 1), F(2,12) = 10.44, p = 0.002. Follow-up tests showed that juveniles' gray:white matter ratio was significantly higher than that of adolescents (p = 0.01) and adults (p = 0.001; Fisher's Least Significant Difference test). Gray:white matter ratio was not significantly different in adolescents as compared to adults (p = 0.20).
2.3.
Corpus callosum
Corpus callosum area differed significantly by age group and across its five subdivisions, F(2,12)=12.39, p=0.001 and F(4,48)= 31.02, p<0.0001, respectively. These results, along with a region by age interaction, F(8,48)=2.64, p=0.02 are illustrated in Fig. 2. The genu area did not differ as a function of age (p = 0.79). Follow-up tests showed significant differences between the age groups for the rostral midbody (rMB), F(2,12) = 5.21, p = 0.02, with larger areas for adults compared to juveniles (p = 0.007) and adolescents (p = 0.055) and no difference between juveniles and adolescents. Similarly, the medial midbody (mMB) area was significantly different as a function of age, F(2,12) = 5.93, p = 0.02, with greater size in adults as compared to juveniles (p = 0.005). There was a nonsignificant trend of greater size in adults compared to adolescents (p = 0.11) and no difference in size for adolescents as compared to juveniles (p = 0.14). A significant age difference was also evident in the caudal midbody (cMB), F(2,12) = 8.33, p = 0.005. The cMB was significantly smaller in juveniles than in adolescents (p = 0.02) or adults (p = 0.003), but did not differ between adolescents and adults. Finally, age differences in the splenium area [F(2,12) = 24.29, p < 0.001] were similar to those of the rostral and medial midbody, with significantly larger areas in adults compared to both juveniles (p < 0.0001) and adolescents (p < 0.0003), and no difference between juveniles and adolescents in splenium size
Fig. 2 – Mean corpus callosum area for juvenile, adolescent, and adult groups for each of the five CC subdivisions: the genu, rostral midbody (rMB), medial midbody (mMB), caudal midbody (cMB), and splenium. In order to control for differences in brain volume, the square root of the area of each CC region was calculated in ratio to the cubic root of the total brain volume (see Smith, 2005). Error bars are S.E.M. + p = 0.055, *p < 0.05, **p < 0.01, ***p < 0.001,****p < 0.0001.
(p = 0.17). There were no sex differences in corpus callosum area, F(1,13) = 0.25, p = 0.62.
3.
Discussion
These data are the first to show age-related differences in gray:white matter ratio, total brain volume, and corpus callosum morphology in bonnet macaques ranging in age from juvenile to adult. The finding of higher gray:white matter ratio in juvenile as compared to adolescent and adult monkeys parallels similar decreases in gray matter volumes reported in humans during the pubertal transition (Toga et al., 2006). Our data are consistent with the report by Malkova et al. (2006) that white matter increases in rhesus monkeys across the infancy and through 5 years of age, and extend this finding to fully adult macaques. Corpus callosum size varied significantly as a function of age and region. Overall, after controlling for total brain volume, corpus callosum size increased with age. Only the genu failed to differ between the age groups. All other callosal regions were larger in adults as compared to juveniles. The medial midbody and splenium were larger in adults as compared to adolescents. Few differences were apparent between adolescents and juveniles. The sample size for this study is small and these results require further testing with a larger number of subjects; however, the results are consistent in pattern with age-related regional differences in CC size observed in humans. For example, Giedd et al. (1999) reported a dominance of posterior region increases in CC size during the pre-adult maturational period and speculated that the difference may be due to earlier maturation of the anterior regions. Our findings parallel this observation, with no differences between the age groups in the most anterior region of the CC (the genu) and pronounced differences between subadult and adult animals in the most posterior CC region, the splenium. Future longitudinal study of these animals will provide an important means of determining whether the differences observed between age groups reflect regional differences in maturation and development of the corpus callosum. In contrast to previous reports in rhesus (Franklin et al., 2000) and capuchin (Phillips et al., 2007) monkeys, we did not find sex differences in overall corpus callosum size, or any regionspecific differences. Our results are similar, however, to those reported from chimpanzees (Dunham and Hopkins, 2006). Sex differences in CC morphology are also found inconsistently in humans. Some of the mitigating factors influencing CC morphology in humans include handedness, age, and how the CC is quantified with respect to covariation with brain size (Driesen and Raz, 1995; Jancke and Steimetz, 1998). We did not include handedness as a variable in our analysis, and this might explain in part why our results differ from those of Phillips et al. (2007) and other studies. These present results must also be interpreted with some caution given the relatively small sample size for male-female comparisons. These are the first data to demonstrate morphological differences in the brains of juvenile, adolescent, and adult bonnet macaques that have been normally-reared with their mothers and in social groups. Previous studies of young monkeys have typically used animals separated from their mothers early in life and reared in a nursery (Malkova et al.,
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2006). Along with extensive evidence for behavioral, neurochemical, and physiological alterations in nursery-reared monkeys (Harlow and Harlow, 1965; for review Sanchez, Ladd, & Plotsky, 2001), there is also at least one report of differences in brain morphology between juvenile motherand nursery-reared rhesus monkeys (Sanchez et al., 1998). Sanchez et al. report decreased CC size in juvenile nurseryreared animals compared to their mother-reared counterparts. The results of our study of mother-reared monkeys, however, are congruent with those of Malkova et al. (2006) study of nursery-reared animals. Although differences in methodology and species preclude direct comparisons between the two studies, the results are similar in that both report increases in total brain volume and white matter across the juvenile to adult period, with adult-like values obtained in adolescence. It remains for future study to address by direct comparison whether nursery- and mother-reared monkeys differ in less global measures of the rate or pattern of brain maturation across the lifespan, and, particularly, whether these differences persist into adulthood. Taken together, the data reported here demonstrate agerelated changes in brain composition and morphology in bonnet macaques ranging in age from juvenile to full adult. The findings are largely consistent with previous reports in both human and nonhuman primates and provide evidence of decreases in gray:white matter ratio with age, as well as differences in CC size that vary by region between juvenile, adolescent, and adult monkeys. Our findings provide convergent evidence of age-related differences in brain morphology that parallel those uncovered in human studies. Nonetheless, it remains for future studies both to extend the findings to the infant development period and to use a longitudinal approach to uncover the pattern of brain maturation in macaques with normal social experience.
4.
Experimental procedures
4.1.
Subjects
High resolution anatomic MRI images were acquired and analyzed for sixteen bonnet macaques (M. radiata) reared by their mothers and living in social groups. The monkeys live in indoor:outdoor enclosures with multiple perches, structural, and manipulable enrichment. Four adults (2 male, 2 female; M = 123.61 months, SE = 4.29), four adolescents (2 male, 2 female, M = 55.97 months, SE = 10.96), and eight juveniles (4 male, 4 female; M = 18.29 months, SE = 2.40) were scanned. One adult male had a brain abnormality visible upon MRI and was therefore excluded from all analyses. All of the experimental procedures were conducted in accordance with the National Institute of Health Guide for the care and use of animal subjects and the experimental protocol was approved by the Wake Forest University School of Medicine Animal Care and Use Committee.
4.2.
Procedure
Subjects were given initial ketamine anesthesia (15 mg/kg, i.m.) and atropine (0.07 mg/kg, i.m.) and then were intubated and maintained under isofluorane (1.25%) throughout the scan. T1
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structural images were acquired on a mobile imaging platform (Alliance Imaging, Inc.) with a 1.5 T GE echo-speed Horizon LX MR scanner and quadrature extremity coil (GE Medical Systems, Milwaukee, WI). Axial T1 weighted structural scans were acquired with a 3D spoiled gradient echo (3DSPGR) inversion recovery sequence with the following parameters: echo time (TE) 6.0 ms, repetition time (TR) 30 ms; flip angle 20°; receiver bandwidth 15.63 kHz; in-plane matrix size, 256 × 256; field of view, 18 cm; slice thickness, 1.0 mm; number of slices, 60.
4.3.
Data analysis
4.3.1.
Whole brain volume and gray:white matter segmentation
Initially, each brain was imported into FSL software and the skull removed from volume. Subsequently, the images were segmented into CSF, gray matter, and white matter using FSL. The axial segmented images were then imported into ANALYZE 7.0 software (Biomedical Imaging Resource: Mayo Foundation, Rochester, Minnesota) and the volumes of the gray and white matter were computed within the region-ofinterest function. The gray and white matter volumes included the cerebellum but not brain stem structures. Total brain volume and gray:white matter ratio were each subjected to multiple regression analysis with age and sex as independent variables.
4.3.2.
Corpus callosum measurements
The corpus callosum (CC) was measured in the mid-saggital slice. Using ANALYZE 7.0 software, a rectangular box was drawn around the CC, which divided the CC into 5 equally-spaced regions (Sanchez et al., 1998) that were traced manually with a mouse-controlled onscreen tool to quantify the area of each region. Subdivisions included: the genu, rostral midbody (rMB), medial midbody (mMB), caudal midbody (cMB), and splenium. In order to control for differences in brain volume, all subsequent analysis was performed with the square root of the area of each CC region calculated in ratio to the cubic root of the total brain volume (see Smith, 2005). Repeated-measures analysis of variance with age group (juvenile, adolescent, adult) as a between-groups factor was conducted on the CC area measures. Analysis of variance with Fisher's Least Significant Difference (LSD) were used as follow-up tests to determine statistically significant differences between age groups for each region.
Acknowledgments The authors gratefully acknowledge the technical contributions of Maria Blevins, Christopher Corcoran, and Jessica Christenson. We also appreciate Dr. Mark L. Laudenslager for his support `and discussions of the bonnet macaque colony. The research was supported by NIH grants AA11997 (AJB), AA13995 (AJB), AA013973 (MLL), NS42867 (WDH), and HD56232 (WDH).
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