Anomalous White Matter Structure and the Effect of Age in Down Syndrome Patients

Abstract

Background: Neural tissue alterations in Down syndrome are fully expressed at relatively late developmental stages. In addition, there is an early presence of neurodegenerative changes in the late life stages.

Objective: The aims of this study were both to characterize white matter abnormalities in the brain of adult Down syndrome patients using diffusion tensor imaging (DTI) and to investigate whether degenerative alterations in white matter structure are detectable before dementia is clinically evident.

Methods: Forty-five adult non-demented Down syndrome patients showing a wide age range (18–52 years) and a matched 45-subject control group were assessed. DTI fractional anisotropy (FA) brain maps were generated and selected cognitive tests were administered.

Results: Compared with healthy controls, non-demented Down syndrome patients showed lower DTI FA in white matter involving the major pathways, but with more severe alterations in the frontal-subcortical circuits. White matter FA decreased with age at a similar rate in both DS and control groups.

Conclusions: Our results contribute to characterizing the expression of white matter structural alterations in adult Down syndrome. However, an accelerated aging effect was not demonstrated, which may suggest that the FA measurements used are not sufficiently sensitive or, alternatively, age-related white matter neurodegeneration is not obvious prior to overt clinical dementia.

Keywords

Accelerated aging diffusion tensor imaging magnetic resonance imaging neurodegeneration

INTRODUCTION

Although research in Down syndrome has substantially progressed in the understanding of basic mechanisms via which gene overexpression interferes with brain development, there is less information as to the general organization of the adult brain and the effect of age [1, 2]. The brain contains billion of neurons that communicate with each other via axons to create complex neural networks. The structural mapping of these networks is essential for understanding brain function [3]. However, although new imaging techniques have emerged in recent years, our knowledge of structural connectivity in Down syndrome is still limited.

Diffusion tensor imaging (DTI) is a noninvasive method that provides information about the microstructural properties of brain tissue by measuring the magnitude and direction of water molecule diffusion [4]. In white matter, the diffusion of water molecules is less restricted along the long axis of a group of aligned tissue fibers than perpendicular to it. This condition of directionally-dependent diffusion is referred to as “anisotropic”. The most commonly used measure for diffusion anisotropy is fractional anisotropy (FA), which serves to characterize white matter tracts by mapping directional diffusion restrictions related mainly to fiber density, axonal diameter and myelination degree [3, 4].

DTI has been used to characterize both age-related changes and disease [5 –8]. Results from leading studies have shown that age-related changes are associated with FA decreases [5]. DTI findings have been validated by postmortem histological studies showing that advanced age is linked to alterations of almost all white matter components. Segments of axons degenerate and swell, myelin becomes less compact and glial cells accumulate cellular debris, form glial scars and increase in number [9 –11].

In Down syndrome, a number of magnetic resonance imaging (MRI) studies have identified a variety of anatomical [12 –17] and functional [18, 19] alterations. The frontal lobes [16, 20] and related circuits [18, 19], as representative of late maturing structures, generally show the most relevant alteration. By contrast, some studies have reported a relative preservation of tissue volume in temporal and parietal regions [16 , 21]. Nevertheless, white matter alterations and their functional significance have not been fully characterized using FA measurements. There is one previous study indicating that white matter in adult Down syndrome is abnormal in terms of FA, particularly when dementia is clinically evident [22]. Nevertheless, the number of Down syndrome patients without dementia was small in this study (n = 10) and the study design did not allow a distinction between the effect of aging and pre-existing changes. It is not currently evident whether the neurodegenerative effect on white matter structure is detectable before dementia is expressed. If this were indeed the case, age-related FA changes could serve as early markers of neurodegeneration, which could be of high practical interest given the difficulty in identifying the cognitive deficits related to dementia in a population with significant baseline alteration in cognition[1, 2].

The aims of this study were both to characterize white matter abnormalities in the brain of adult non-demented Down syndrome patients using DTI and to investigate whether degenerative changes in white matter structure are detectable before dementia becomes clinically evident. We predicted that Down syndrome patients would exhibit both widespread FA reduction in white matter and an accelerated aging effect, and that the alteration would be associated with poorer cognitive performance.

METHODS

Participants

Sixty-eight Down syndrome patients were initially recruited in the study. Candidates were recruited from the community via parent organizations and underwent comprehensive medical, psychiatric, neuropsychological, and laboratory evaluation. Individuals with seizure or neurological disease (other than Down syndrome) and non-stable medical conditions were not considered eligible. Participants were selected on the basis of age (18 years old and upwards), Down syndrome confirmed by karyotype, capability to understand MRI instructions, follow commands and keep still, and also optimal attitude and willingness (patients and parents) to participate. Five patients did not complete the image acquisition protocol and a further 18 subjects were ultimately excluded due to head motion during MRI (see below). The final sample, therefore, included 45 relatively high-functioning Down syndrome patients (29 females, 16 males) with genotype-confirmed trisomy 21 and a mean±SD age of 35.3±10.8 years, range 18–52 (Table 1). The included and excluded patient subgroups did not significantly differ as to age, performance IQ, semantic fluency, and working memory. Excluded patients, however, were predominantly males (6 females, 17 males).

A control group of 45 healthy volunteers were selected matched for age with the patient sample (34.6±10.0 years, range 19–51) and showing similar sex distribution (Table 1). Participants were either friends or family of subjects participating in the current and other studies, or were recruited from local advertisements. A complete medical interview was carried out to exclude individuals with relevant medical or neurological disorders, cerebrovascular risk factors, substance abuse, psychiatric disease, or undergoing medical treatment. In all included control subjects, the brain showed a normal appearance on high resolution anatomical MRI scans.

This study was conducted according to the principles expressed in the Declaration of Helsinki. Anxiolytics were not administered in this study. The study protocol was approved by the Clinical Research Ethical Committee of the Parc de Salut Mar of Barcelona. Written informed consent was obtained from parents and control subjects. Verbal or written assent was additionally obtained from Down syndrome patients.

Cognitive testing

Selected cognitive assessment in all Down syndrome patients included Performance IQ estimated with the Kaufman Brief Intelligent Test, Second Edition (K-BIT) [23] matrices subtest as a general cognitive assessment, the Wechsler Adult Intelligence Scale (WAIS) backward digit span task as one of conventional measurements of working memory [24], and semantic fluency as a sensitive measurement of verbal output [25].

Additionally, each patient underwent comprehensive neurological and psychiatric history and subsequent tailored neuropsychological testing to clinically rule out the presence of dementia (and mild cognitive impairment, MCI) in terms of cognitive deterioration overlapping with developmental cognitive deficits associated with Down syndrome. Clinical diagnosis (or exclusion) of dementia in Down syndrome by experienced clinicians is recommended as being more accurate and reliable than operative diagnostic tools at a relatively early stage of the disease [26]. Nevertheless, apart from expert clinical diagnosis (by SE and SdS), no patient met International Classification of Diseases (ICD)-10 [27] or Diagnostic and Statistical Manual of Mental Disorder-IV-Text Revision (DSM-IV-TR) [28] criteria for dementia. A total of 3 patients, however, did meet criteria for mild MCI [29], adapted to adults with intellectual disability [30]. The clinical diagnosis of MCI in these 3 cases was established by an experienced neuropsychologist (SEC) on the basis of (i) a report of cognitive impairment by the patient (confirmed by a reliable informant) or by a reliable informant that implies a change from previous capacities, (ii) abnormal performance in the corresponding neuropsychological testing, and (iii) no clinically relevant decline in overall adaptive skills and insufficient ICD-10 and DSM-IV-TR criteria for dementia.

MRI acquisition

A 1.5 Tesla Signa Excite System (General Electric, Milwaukee, WI, USA) equipped with an eight-channel phased-array head coil and single-shot echoplanar imaging (EPI) software was used. Diffusion-weighted scans were obtained using spin-echo single-shot echo-planar sequences of 25 directions with a B-factor of 1000 s/mm². Acquisition parameters were repetition time 8300 ms; echo time 94 ms; thickness 5 mm, no gap; pulse angle 90°; field of view 26 cm; 128×128 acquisition matrix reconstructed into a 256×256 matrix, and scan duration was 3 m 52 s. Twenty-six slices were prescribed parallel to the anterior-posterior commissure line covering the whole brain. Participants were instructed to relax, stay awake and lie still.

Image preprocessing

DTI was processed using Functional MRI of the Brain (FMRIB) Software Library 5.0 (FSL), developed by the Analysis Group at the Oxford Centre for FMRIB [31]. Diffusion-weighted images were aligned to the B0 image using affine registration and corrected for motion and eddy current distortions (“Eddy Current Correction” option in the FMRIB Diffusion Toolbox [FDT] version 2.0 in FSL). A whole-brain mask, generated with the FSL Brain Extracting Tool, was applied to the DTI images. Subsequently, we estimated FA maps using FDT in FSL by local fitting of the diffusion tensor model at each voxel (“dtifit”). FA maps were then aligned to a common target (FMRIB58_FA template) using Tract-Based Spatial Statistics [32], re-sliced to a 1 mm×1 mm×1 mm anatomical resolution and normalized to standard MNI space via the FMRIB58_FA template using the FMRIB’s Non-linear Registration Tool. All the images were visually inspected by a trained researcher before and after the preprocessing steps to avoid the inclusion of poor-quality images. An additional rigorous image quality control was carried out to identify potential effects of head motion on raw images, which involved the visual inspection of each DTI slice for all 25 DTI volumes in all participants. The effect of motion can generally be observed as signal loss in the whole or a part of one slice compared with the other slices. Volumes with slices showing signal loss (greater than ∼10% compared with slices normal in signal and measured using the conventional MRIcron display tool) or residual artifacts were identified by an expert researcher. DTI full examinations showing more than 5 degraded volumes were discarded. A total of 18 participants were removed from the DTI analysis on the basis of this criterion (in addition to 5 cases showing gross image degradation). The final DTI sample involved 45 patients with a mean±SD of 23.0 (92%)±1.6 optimal-quality volumes.

After the full pre-processing, FA maps were transferred to the SPM8 platform and smoothed with an 8 mm Gaussian Kernel to carry out group statistical analyses.

Statistical analysis

Individual FA maps were included in second-level (group) SPM analyses using 2-sample t-test between the 45 Down syndrome patients and 45 healthy controls. Voxel-wise analyses in SPM were also performed to map the correlation between age and whole-brain FA measurements in both groups. Finally, voxel-wise analyses were performed to map the correlation between individual ratings in the selected cognitive tests and FA measurements in the Down syndrome group.

Results were considered significant with clusters of 1.032 ml (1,032 voxels) at a height threshold of p < 0.005, which satisfied the family-wise error (FWE) rate correction of P_FWE < 0.05 according to Monte Carlo simulations [33].

RESULTS

Fractional anisotropy differences between Down syndrome and control subjects

Down syndrome patients showed a widespread white matter FA reduction compared with healthy controls involving parts of the frontal lobes, semioval centers, corpus callosum, external capsule, internal capsule, putamen, thalamus, pyramidal tracts, and brainstem (Table 2). Therefore, the major brain pathways were affected, although the alterations were more severe in the frontal-subcortical circuits (Fig. 1). For example, 21 out of 25 sub-clusters showing the largest between-group differences (t > 5) involved the frontal-subcortical circuits and only 4 did not (χ² = 11.5, p < 0.001). In the opposite contrast, a region of significantly larger FA was found in Down syndrome at the temporo-parietal junction(Fig. 1).

Correlations with cognitive performance in Down syndrome

No significant correlations were found between FA measurements and both performance IQ (K-BIT matrices) and working memory scores (WAIS digit span). By contrast, FA showed significant positive correlation with semantic fluency (i.e., lower FA values, poorer performance) in a variety of regions involving the frontal lobes, corpus callosum, semioval centers, arcuate fasciculus, caudate nucleus, external capsule, thalamus, and hippocampus (Fig. 2 and Table 2).

Age-related effect on fractional anisotropy

In both groups, FA decreased as a function of age. Healthy controls showed FA age-related changes in the frontal lobes, corpus callosum, basal ganglia (caudate), thalamus, semioval centers, and pyramidal tracts (Fig. 3 and Table 2). In Down syndrome, significant correlations with age were found in the frontal lobes, left arcuate fasciculus, right external capsule, and hypothalamus (Fig. 3 and Table 2). We found no significant between-group differences relating to the strength of the correlations (i.e., no significant correlation interaction), which is illustrated in Fig. 4.

DISCUSSION

Our results indicate that white matter in Down syndrome patients showed generally lower FA compared with healthy participants. The most affected structures were the frontal lobes, subcortical white matter and some parts of the brainstem. Lower FA in Down syndrome was associated with poorer semantic fluency, which illustrates a degree of correspondence between white matter integrity and performance in patients. White matter FA did indeed decrease with age in both study groups, but we did not find the expected accelerated age effect in the Down syndrome group.

FA is a tissue measurement primarily independent of tissue volume that may generally express the extent to which an anatomical structure is composed of white matter tracts showing one dominant direction. In brain regions containing tracts with a single direction, FA increases as a result of brain maturation [4, 34]. In this context, our results indicate that Down syndrome subjects have a less developed white matter structure than controls in many white matter tracts. This is a remarkable finding due to the few studies based on DTI in non-demented Down syndrome patients. Our results are consistent with studies of brain anatomy showing generally reduced white matter volumes in Down syndrome compared with healthy controls [13, 16]. However, our data may further contribute to characterizing white matter alterations in Down syndrome in that they would indicate that the changes are not limited to general volume reductions, but may also implicate a less developed structural connectivity pattern.

Although FA abnormalities involved the major brain pathways, the frontal-subcortical circuits showed more severe alterations. As a general trend, the results are consistent with the profile of cognitive deficits in Down syndrome typically progressing with deep impairment in language production and executive functions, which are cognitive domains notably dependent on the frontal lobes [35 –37].

We also observed that Down syndrome individuals showed higher FA at the temporo-parietal junction. This observation is partly consistent with studies reporting relatively larger white matter volume in temporal and parietal regions [16 , 21], which may reflect a particular abnormality in white matter maturation. Indeed, in complex structures with tracts crossing in different directions (as in the temporo-parietal junction), higher FA may paradoxically denote less mature or less structured tissue [4, 34]. The multimodal temporo-parietal junction is certainly a complex area in terms of white matter connectivity. In Down syndrome, the pattern of connectivity would seem to be incomplete at this level. This event appears in parallel with a more general FA reduction in several other brain structures. In this general effect, the alteration may denote poor development of white matter pathways showing a predominant direction or a simplerstructure.

A relevant problem in evaluating cognitive abilities in Down syndrome is the notable lack of consistency and reproducibility of ratings in some neuropsychological tests [38]. We used the K-BIT matrices subtest to estimate general intelligence, the digit span to evaluate working memory and semantic verbal fluency to test verbal output. Only verbal fluency was associated with FA alterations in Down syndrome in a rather general manner, thus indicating a certain parallelism between the identified pattern of white matter alterations and cognitive performance. Nevertheless, we failed to find similar associations with performance IQ and working memory. We now, a posteriori, consider that these tests are not perhaps the most suitable to reliably predict brain alterations in Down syndrome. The development of more specific and sensitive tools to evaluate cognition in Down syndrome, as recently proposed [39], could be helpful in future studies.

Our study did not find significant between-group differences in age-related white matter changes. That is to say, although both groups suffered a variation of white matter structure with age, there were no between-group differences. In our Down syndrome group, none of the participants were diagnosed with Alzheimer’s disease and only 3 patients had MCI according to clinical criteria. Therefore, we were unable to demonstrate the anticipated premature aging effects on white matter using FA measurements, which contrast with positive findings in studies on familial Alzheimer’s disease (summarized in a recent report [40]). This brings us to the conclusion that DTI FA measurements are perhaps not sufficiently sensitive to capture brain pathology related to the acceleration of aging in subclinical populations. Alternatively, age-related white matter neurodegeneration may be a later event, which is not obvious prior to overt clinical dementia. In the study by Powell et al. [22], FA alterations were indeed more evident when dementia was clinically evident in Down syndrome patients.

It is important to mention, however, that the identified FA decrease with age in the control group is not the expression of the white matter structure involution or degeneration occurring in the senile brain (also expressed in the form of additional FA decrease [41]), as age in the control group showed a mean of 34.6 years and range 19–51 years. Age-related FA changes may better reflect the normal active evolution of white matter tracts in the adult brain. Our findings are consistent with previous studies in normal populations showing FA peaks from early 20 s to late 30 s and subsequent subtle FA decreases starting around mid-adulthood with notably different timings across different tracts [42]. FA studies in normal populations further emphasize early proposals that white matter remodeling is a biological process active over the entire lifespan [43, 44].

One challenge in the assessment of DTI is the control of head-motion effects on the measurement, which may be relevant in low-performance populations. We have considered this issue carefully and adopted several means to rigorously control such effects. We decided to exclude cases with detectable image degradation, as no correction procedure is wholly efficient once the images have been acquired. The regular use of MRI practice sessions with mock scanners may minimize the problem in future studies. A post-hoc analysis on DTI using less rigorous exclusion criteria (n = 54) showed similar but weakened DTI results, indicating that the data obtained in the more selective sample (n = 45) was most probably not due to motion effects. Although accurate control of head motion effects may be a strength of the study, it is important to mention that strict participant selection is also a limitation. In this context, our findings cannot generalize to all Down syndrome population, but conclusions should be limited to relatively highly performing individuals. A final limitation relates to using a 1.5-T system, as opposed to a 3-T system with higher MRI signal.

Conclusions

Results from our imaging approach indicate that the brain in relatively high-functioning Down syndrome patients shows generally lower FA, suggesting underdevelopment of white matter tracts. The altered white matter structure was associated with poorer performance at neuropsychological assessment. Finally, age-related reduction of FA did not significantly differ between the control group and our non-demented Down syndrome patients. Probably, the adopted DTI approach was not sufficiently sensitive to detect alterations related to the dementia process in subclinical stages of Alzheimer-like pathology. Further studies should focus on the temporal evolution of white matter structure involution and the development of dementia in Down syndrome adults and provide biomarkers for detecting early signs of premature aging.

Footnotes

ACKNOWLEDGMENTS

This study was supported in part by the Spanish Government (Grants SAF2010-19434, PI11/00744 and PI/120219) and the Jérôme Lejeune Foundation, Paris.

We thank the Fundació Catalana Síndrome de Down (FCSD, Spain) for their assistance with the recruitment of participants and the TESDAT Study Group members for their contribution (Lancet Neurology, May 12, 2016 ). We thank the Agency of University and Research Funding Management of the Catalonia Government for their participation in the context of Research Groups SGR 2009/1450 and SGR 2009/718.

Authors’ disclosures available online ([alz.com/manuscript-disclosures/161112r1]).

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