White matter tract integrity and intelligence in patients with mental retardation and healthy adults
Introduction
Researchers have long attempted to determine the biological basis of intelligence using available neuroimaging techniques. With the use of structural imaging technique, several research teams, using different scan protocols, populations and intellectual measures, have shown positive correlations between intelligence quotient (IQ) and total brain volumes (Andreasen et al., 1993, Ivanovic et al., 2004, McDaniel, 2005, Plomin and Kosslyn, 2001, Reiss et al., 1996, Tisserand et al., 2001, Witelson et al., 2006). Recent studies using voxel-based morphometry have demonstrated correlations between IQ and some specific brain regions, which involve in frontal (Colom et al., 2006, Frangou et al., 2004, Gong et al., 2005, Haier et al., 2004, Haier et al., 2005, Thompson et al., 2001, Wilke et al., 2003), parietal (Colom et al., 2006, Haier et al., 2004, Haier et al., 2005), temporal(Colom et al., 2006, Haier et al., 2004) and occipital (Colom et al., 2006, Haier et al., 2004) lobes. Functional brain imaging techniques can reveal activated regions that probably support intelligent behavior. Using positron emission tomography (PET), a study has found that only lateral frontal cortex was consistently activated during three different intelligence tasks when compared with control tasks (Duncan et al., 2000). However, many other functional imaging studies have shown that good test performance recruited more brain areas (Gray et al., 2003, Haier et al., 1988, Prabhakaran et al., 1997), which suggests multiple brain regions related to intelligence. Most of the above studies support the association between brain gray matter and IQ, but the association between the integrity of brain white matter tracts and IQ in healthy adults remains largely unknown.
The brain white matter can be quantitatively assessed by the technique of diffusion tensor imaging (DTI), which measures the random motion of water molecules and provides information about the size, orientation, and geometry of brain tissue (Basser et al., 1994, Le Bihan, 2003). Pathological processes, which change the microstructural environment, such as neuronal size, extracellular space and tissue integrity, result in altered diffusion (Anderson et al., 1996, Sevick et al., 1992, Yu et al., 2007). The integrity of white matter tracts can be assessed by fractional anisotropy (FA), an indicator of myelination and axonal thickness. With the advent of the technique of tractography, brain white matter tracts can be visualized in vivo and extracted from the surrounding structures (Basser et al., 2000, Jones et al., 1999), which makes the tract-based analysis of diffusion indices possible.
Using the technique of DTI, the association between white matter integrity and IQ has been investigated in many situations, such as in normal children (Schmithorst et al., 2005), adolescents with very low birth weight (Skranes et al., 2007), malignant phenylketonuria (Peng et al., 2004), fragile X syndrome (Barnea-Goraly et al., 2003), schizotypal personality disorder (Nakamura et al., 2005), and multiple sclerosis (Rovaris et al., 2002). They found that the IQ scores were correlated with the white matter integrity of different brain regions in different situations. However, the damage of the integrity of the white matter tracts in patients with mental retardation (MR) and the association between the integrity of white matter tracts and IQ in normal adults have not been investigated, especially using the DTI-based tract analysis.
To investigate the correlations between IQ and the integrity of white matter tracts, we chose the corpus callosum (CC), cingulum, uncinate fasciculus (UF), optic radiation (OR) and corticospinal tract (CST) as tracts of interest because they are the main white matter tracts of the brain and are large enough to be reliably reconstructed by diffusion tensor tractography. We intend to determine the relationship between IQ and white matter tract integrity from two aspects. One is to compare the differences of the integrity of these tracts among MR patients, general intelligence (GI: FSIQ < 120) and high intelligence (HI: FSIQ ≥ 120) controls to determine which white matter tracts are damaged in MR group relative to healthy groups and in GI group relative to HI group. The other is to directly correlate IQ with the integrity of these tracts in a relatively large population controlling for sex, age and group.
Section snippets
Subjects
Study approval was acquired from the ethical committee of Xuanwu Hospital of Capital Medical University. Parents of the MR patients and all of the healthy controls provided written informed consent after the study had been fully explained to them. Ninety-four right-handed (Oldfield, 1971) subjects participated in the study, including 15 MR patients (10 men and 5 women; mean age 23.5 ± 3.4 years, range 18-33 years) and 79 healthy volunteers (44 men and 35 women, mean age 23.8 ± 3.9 years; range
Reproducibility analysis
The CC, UF, cingulum, OR and CST were well reconstructed in all subjects (Fig. 2), in a manner consistent with the description of known anatomy, which indicates the reliability of the tractography method used. The ICC of the FA was 98.53% for the CC, 96.87% for the CC1, 97.36% for the CC2, 97.19% for the CC3, 97.85% for the left UF, 97.47% for the right UF, 98.32% for the left cingulum, 97.89% for the right cingulum, 96.49% for the left OR, 96.73% for the right OR, 97.88% for the left CST and
Discussion
In this study, we investigated the association between intelligence and the integrity of brain white matter tracts using DTI-based tract analysis. We found that healthy controls showed superior integrity than MR patients in the CC, UF, OR and CST, however, HI subjects only showed superior integrity than GI subjects in the right UF. We also found significant correlations between FSIQ scores and the average FA of the right and left UF, genu and truncus of CC, bilateral OR and left CST in the
Acknowledgments
This study was partly supported by Natural Science Foundation of China (Nos. 30670601, 30570509, 30425004), Beijing Scientific and Technological New Star Program (2005B21), and the National Key Basic Research and Development Program (973), Grant No. 2004CB318107.
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