Distribution of iron in basal ganglia and visual cortices from infancy to adulthood
Poster No:
2070
Submission Type:
Abstract Submission
Authors:
Vaidehi Natu1, Clara Bacmeister1, Xiaoqian Yan2, Hua Wu1, Christina Tyagi1, Sarah Tung1, Bella Fascendini3, Nan Wang1, Mercedes Paredes4, Kalanit Grill-Spector1
Institutions:
1Stanford University, Stanford, CA, 2Fudan University, Shanghai, Fudan, 3Princeton University, Princeton, NJ, 4University of California, San Francisco, San Francisco, CA
First Author:
Co-Author(s):
Introduction:
Iron is an essential metal and micronutrient for brain health and generation of cortical myelin. It is well established that iron deficiency can lead to cognitive impairments like autism and motor learning difficulties in childhood. However, how iron develops postnatally in the human brain remains largely unknown.
Methods:
As higher R2* and R1 values are thought to be linearly related to higher iron content and higher tissue density, respectively, we obtained quantitative susceptibility mapping (QSM, χ), effective transverse relaxation rate (R2*[s-1]) and longitudinal relaxation rate (R1[s-1]) in 19 infants (age range: 16-479 days) and 20 adults (19-42 years), to estimate the development of iron in the basal ganglia (BG) nuclei and gray (cortical) and adjacent white matter of visual areas of the brain.
Results:
Our data reveal four main findings: First, in both basal ganglia nuclei and visual areas, R2* and R1 increase logarithmically with age. However, in adults, R2* is higher in the BG than visual cortex and there is differential development of R2* across BG and visual areas. Further, magnetic susceptibility (χ) reveals more paramagnetic (iron-like) properties in adults' than infants' BG, but diamagnetic (myelin-like) properties in visual cortex across age-groups. Second, we estimated the contribution of iron (CFe) from R2* and χ using empirical linear models[1] (Eqs. 1 and 2), putative iron levels from a prior postmortem study[2], and a least square solver: Eq1: R2*(cFe, cMy) = aFe * cFe + aMy * cMy + a0; Eq2: χ(cFe, cMy) = bFe * cFe + bMy * cMy + b0. We estimate model parameters using data from five adults, and then predict CFe in the remaining left out adults and infants. The predicted values of iron concentration were consistent with iron concentration reported in prior postmortem work[2]. Third, we find developmental differences in R2* and R1 across cortical depth in visual areas. In adults, R2* and R1 both increase from cortex to white matter, illustrating a corresponding relationship between the two microstructural properties across cortical depth. In newborns, however, both R2* and R1 tend to be higher in cortex than in white matter and this pattern reverses around 3 months for R1 and around one year for R2*, suggesting differential microstructural profiles during infancy. Finally, we validated R2* metrics with immunohistochemistry staining of ferritin (iron storage protein) in ex vivo infant and adult brain samples, finding increasing intensity of ferritin from infancy to adulthood in visual areas. This suggests that mechanistically ferritin might play a significant role in cortical and white matter development during infancy.
Conclusions:
Together our findings suggest that in vivo metrics of R2*, χ, and R1 can be used to estimate the development of iron in the brain and pave a way for estimating iron concentration in infant brains from in vivo measurements. These results open the opportunity for large scale measurements of iron development and are critical for establishing global standards to identify iron deficiency in brains of developing infants and provide effective postnatal care.
Lifespan Development:
Normal Brain Development: Fetus to Adolescence 2
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Normal Development
Novel Imaging Acquisition Methods:
Anatomical MRI
Perception, Attention and Motor Behavior:
Perception: Visual 1
Keywords:
Basal Ganglia
STRUCTURAL MRI
Vision
1|2Indicates the priority used for review
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2. Hallgren, B., & Sourander, P. (1958). The effect of age on the non-haemin iron in the human brain. Journal of Neurochemistry, 3, 41-51.