Neural function in DCC mutation carriers with and without mirror movements

Abstract

Objective

Recently identified mutations of the axon guidance molecule receptor gene, DCC, present an opportunity to investigate, in living human brain, mechanisms affecting neural connectivity and the basis of mirror movements, involuntary contralateral responses that mirror voluntary unilateral actions. We hypothesized that haploinsufficient DCC ^+/− mutation carriers with mirror movements would exhibit decreased DCC mRNA expression, a functional ipsilateral corticospinal tract, greater “mirroring” motor representations, and reduced interhemispheric inhibition. DCC ^+/− mutation carriers without mirror movements might exhibit some of these features.

Methods

The participants (n = 52) included 13 DCC ^+/− mutation carriers with mirror movements, 7 DCC ^+/− mutation carriers without mirror movements, 13 relatives without the mutation or mirror movements, and 19 unrelated healthy volunteers. The multimodal approach comprised quantitative real time polymerase chain reaction, transcranial magnetic stimulation (TMS), functional magnetic resonance imaging (fMRI) under resting and task conditions, and measures of white matter integrity.

Results

Mirror movements were associated with reduced DCC mRNA expression, increased ipsilateral TMS‐induced motor evoked potentials, increased fMRI responses in the mirroring M1 and cerebellum, and markedly reduced interhemispheric inhibition. The DCC ^+/− mutation, irrespective of mirror movements, was associated with reduced functional connectivity and white matter integrity.

Interpretation

Diverse connectivity abnormalities were identified in mutation carriers with and without mirror movements, but corticospinal effects and decreased peripheral DCC mRNA appeared driven by the mirror movement phenotype. ANN NEUROL 2019;85:433–442.

The axon guidance molecule receptor, DCC (deleted in colorectal cancer), plays a critical role in directing normal decussation of corticospinal tract (CST) and commissural pathways. In homozygous DCC mutant mice, the ensuing failure of axonal interhemispheric crossing is associated with a lack of asymmetric movements.1 Similar to the murine motor phenotype, humans with DCC mutations exhibit mirror movements (MM); that is, voluntary actions on one side of the body elicit simultaneous involuntary movements on the contralateral side.2

The human DCC mutation–related MM are substantially more pronounced than the smaller MM that are commonly exhibited by young children and then, at around age 10 years, disappear following maturation of the corpus callosum (CC) and the development of normal interhemispheric inhibition (IHI).3 Also unlike healthy children, adults with severe congenital MM exhibit evidence of a pronounced ipsilateral CST,4, 5, 6, 7, 8 and among the recently identified DCC mutation carriers, some have agenesis of the CC, MM, both phenotypes, or neither phenotype.8, 9, 10

A number of important features in DCC mutation carriers remain unknown. It is unknown whether they exhibit abnormal motor cortex activations, motor system connectivity, or interhemispheric function. The neurophysiological phenotype of DCC mutation carriers without MM is unknown. There is currently no explanation to account for the partial penetrance of MM among mutation carriers.

To map in detail the neurocircuitry of DCC mutation–related MM, we have completed multimodal neuroimaging in 33 members of a large, 4‐generational Quebec family with a DCC frameshift mutation (NM_005215.3, c.1140 + 1G > A). This mutation results from abnormal skipping of exon 6, leading to a premature stop codon that encodes a truncated DCC protein that fails to bind to its ligand, netrin.2 Our a priori predictions were that, relative to controls, DCC mutation carriers with MM would exhibit an increased functional ipsilateral CST, increased “mirroring” motor representations, reduced IHI, alterations in motor and interhemispheric anatomical and functional connectivity, and decreased DCC mRNA expression. Finally, we sought to determine the effects of the DCC mutation, potentially distinct from the effects of MM.

Subjects and Methods

Participants

Fifty‐two volunteers participated in the study (Table 1, Fig 1). This included 13 DCC haploinsufficient individuals with MM (DCC ^+/− /MM⁺), 7 DCC haploinsufficient individuals without MM (DCC ^+/− /MM⁻), and 13 relatives with neither the mutation nor MM (DCC ^+/+ /MM⁻); 19 unrelated healthy volunteers (UHVs) were tested to control for DCC familial features unrelated to the mutation. Participant safety screening procedures were completed prior to magnetic resonance imaging (MRI) and transcranial magnetic stimulation (TMS). All participants gave written informed consent, and the protocol was carried out in accordance with the Declaration of Helsinki and approved by the relevant research ethics committees.

Table 1.

Participant Characteristics

	Group
Characteristic	DCC +/−/MM+	DCC +/−/MM−	DCC +/+/MM−	UHV	Statistical Test, 4 Groups
Ntotal	13	7	13	19
NMRI	11	7	12	19
Ntask‐fMRI	11	7	12	18
Nrs‐fcMRI	10	7	12	14
NTMS	12	7	12	14
Age, mean ± SD	44.4 ± 16.9	49.6 ± 14.9	37.9 ± 13.2	41.4 ± 16.3	F 3, 48 = 0.96, p = 0.42
Sex, M:F	9:4	2:5	5:8	10:9	χ2 3 = 3.95, p = 0.27
Handedness	11 right, 2 left	5 right, 2 left	10 right, 3 left	19 right	χ2 3 = 5.40, p = 0.15

DCC ^+/−/MM⁻ mutation carriers without MM; DCC ^+/−/MM⁺ = mutation carriers with MM; DCC ^+/+/MM⁻ = relatives without the mutation or MM; F = female; M = male; MRI = magnetic resonance imaging; rs‐fcMRI = resting state functional connectivity MRI; SD = standard deviation; TMS = transcranial magnetic stimulation; UHV = unrelated healthy volunteers; MM = mirror movements.

Figure 1.

Pedigree of Quebec family. Full red indicates DCC ^+/−/MM⁺; half red indicates DCC ^+/−/MM⁻, blue indicates DCC ^+/+/MM⁻ relatives, white designates those who did not undergo genetic testing. Asterisks (*) indicate previously genotyped individuals who did not participate in the present study. Crossed lines designate deceased. Squares and circles are males and females, respectively. [Color figure can be viewed at www.annalsofneurology.org]

Genetics

Participants who had not been genotyped previously2 were characterized for DCC variants. Genotyping was unavailable for 1 UHV, who only completed the MRI, and excluding this individual did not alter the findings. Coding exons and the exon–intron boundaries of DCC were screened for mutations based on sequence (NM_005215; UCSC March 2006 Assembly HG 18). Primers were the same as used previously.2 Polymerase chain reaction (PCR) products were sequenced on the ABI 3700 sequencer at the Genome Quebec Centre for Innovation according to the manufacturer's recommended protocol (Applied Biosystems, Foster City, CA). Sequences were aligned and analyzed using SeqMan 4.03 (DNASTAR, Madison, WI) and Mutation Surveyor v3.1 (SoftGenetics, State College, PA).

Mirror Movements

Prior to testing, 2 self‐adhesive electrodes were placed on the first dorsal interosseous (FDI) muscle bilaterally and a ground electrode was positioned on the right wrist. The electromyographic (EMG) signal was amplified using a Powerlab 4/30 system (ADInstruments, Colorado Springs, CO), filtered with a bandpass of 20 to 1,000 Hz, and digitized at a sampling rate of 4 kHz. First, seated participants were asked to relax their arms with their palms facing upward, supported by their legs. They were instructed to respond to an auditory signal by pressing, then releasing, a small stress ball 3 times with one hand while the other hand was at rest. This protocol was performed for both hands and repeated 5 times. To assess subtler MM, a protocol known to generate physiological MM (pMM) in healthy participants was performed.3 Participants were instructed to maintain a tonic contraction with one hand (using the minimal strength needed to hold a pencil without dropping it). Meanwhile, participants were required to respond to an auditory signal with their other hand by performing a voluntary phasic pinch contraction. This was performed 20 times for both hands. pMM were defined as a significant increase in the background EMG activity of the hand maintaining the tonic contraction, starting at the moment of the phasic contraction and lasting 100 milliseconds, compared to 1,000 milliseconds of background activity prior to the phasic contraction. Data were expressed as the ratio of EMG activity in the tonically contracting hand during phasic contraction of the contralateral hand over background activity preceding phasic contraction. The data from both hemispheres were averaged.

Single‐Pulse TMS

TMS was delivered through an 8 cm figure‐of‐eight coil connected to a Magstim 200 stimulator (Magstim, Whitland, UK) with a monophasic current waveform in a posterior–anterior orientation. The coil was positioned flat on the scalp at an angle of 45° from the midline. Single‐pulse stimulation was performed over the hand area of primary motor cortex (M1) at the optimal position (hot spot) eliciting motor evoked potentials (MEPs) of maximal amplitude in the contralateral FDI muscle. The hot spot was marked on the scalp with a pen to ensure stable coil positioning throughout the experiment. Stimulation intensity was adjusted to elicit contralateral MEPs of 1 mV amplitude. MEPs were recorded using Scope v4.0 software (ADInstruments). The EMG signal was filtered with a bandwidth of 20 to 1,000 Hz and digitized at a sampling rate of 4 kHz. Single‐pulse stimulation was performed over the hand area of M1 while participants were at rest with eyes open, 10 times for each hemisphere, and MEPs were recorded bilaterally in the FDI muscle to confirm the presence or absence of mirror MEPs in all participants. Peak‐to‐peak amplitudes of contralateral and ipsilateral MEPs were measured and averaged offline. Relative amplitudes of ipsilateral and contralateral MEPs were expressed as an ipsilateral coefficient (ipsilateral MEP amplitude/contralateral MEP amplitude). MEP traces were monitored online to ensure that no muscle activity in the 100‐millisecond window prior to TMS was present. Trials with prestimulus activity were discarded and repeated, and were < 1% of all trials. The data from both hemispheres were averaged. Contralateral and ipsilateral TMS‐induced MEP latencies were also measured, from TMS pulse to MEP onset.

Double‐Coil TMS

IHI was measured using a protocol described by Ferbert and collaborators using two 50 mm custom‐made coils connected to 2 Magstim 200 stimulators.11 Each coil was placed over its respective M1 hot spot over the right and left hemispheres. The intensity of each TMS pulse was adjusted to elicit MEPs of approximately 1 mV contralaterally. A test stimulus was preceded by a conditioning stimulus applied 40 milliseconds earlier. IHI was measured for left‐to‐right and right‐to‐left directions of inhibition. IHI was expressed as the ratio of double stimulation MEPs over single‐pulse MEPs. The data for both directions were averaged.

MRI Parameters

Participants underwent anatomical, diffusion‐weighted, resting‐state functional, and 2 identical task functional MRI (fMRI) acquisitions in a scanning session using a 3 T Siemens (Erlangen, Germany) Magnetom Trio MRI scanner (32 channel head coil). The high‐resolution, T1‐weighted anatomical acquisition parameters were as follows: inversion time/repetition time (TR)/echo time (TE) = 900/2,300/2.98 milliseconds, flip angle = 9°, slice thickness = 1.0 mm (1 mm isotropic voxel size), with a field of view (FOV) of 256 × 256 mm² and duration of 9 minutes 50 seconds. Participants underwent diffusion tensor imaging (DTI) using a single‐shot spin‐echo echo‐planar pulse sequence with multidirectional diffusion weighting (TR/TE = 12,000/89 milliseconds, 90 contiguous axial slices with an isotropic 2 mm resolution, FOV = 256 × 256 mm², matrix size = 128 × 128 with partial Fourier reconstructed to 6/8). Diffusion weighting was distributed evenly on the unit hemisphere using 64 noncollinear gradients and a b value of 1,000. One additional volume with no diffusion weighting (ie, b value = 0) was acquired in the beginning of the acquisition. The task fMRI acquisition parameters were as follows: TR/TE = 1,500/30 milliseconds, flip angle = 90°, slice thickness = 4.0 mm (4 mm isotropic voxel size), slices = 28, FOV = 256 × 256 mm², and duration of 6 minutes 8 seconds. The resting state fMRI acquisition parameters were as follows: TR/TE = 2,000/30 milliseconds, flip angle = 90°, slice thickness = 4.0 mm (4 mm isotropic voxel size), slices = 38, FOV = 256 × 256 mm², and duration of 6 minutes 8 seconds.

Resting State Functional Connectivity MRI

Resting state functional connectivity MRI (rs‐fcMRI) data were processed as described previously,12, 13 including slice‐acquisition–dependent time shifts, head motion correction, atlas registration, spatial smoothing (6 mm full width at half maximum [FWHM]), low‐pass temporal filtering (f < 0.08 Hz), and removal of confounding variables by linear regression including head motion, the whole‐brain (global) signal, and signals from the ventricles and white matter (WM). A metric of overall movement was also computed for use as a covariate by computing the root mean square of the rotation, translation, and displacement of the brain relative to the time point before it, then averaging across all time points.14 A priori regions of interest (ROIs; 6 mm radius spheres) were generated in the left and right M1 (Montreal Neurological Institute [MNI] coordinates: −41, −20, 62 and 41, −20, 62) based on a prior fMRI study of hand movements.15 A priori ROIs were also generated in the left and right cerebellum (MNI coordinates: −20, −52, −24 and 17, −52, −24) based on prior functional connectivity with left and right M1.15 rs‐fcMRI between motor ROIs (1 comparison), between motor and cerebellar ROIs (4 comparisons), and between motor ROIs and all other brain voxels were computed.12 For statistical comparisons, correlation coefficients (r values) from each subject were converted to a normal distribution using Fisher r to z transform. For the fMRI 2nd level analyses, a full factorial using the same design described below in the Statistical Analyses section with the addition of total movement during the MRI as a covariate was run in SPM12. Because generalized estimating equations (GEEs) are not possible with Statistical Parametric Mapping (SPM), family was instead entered as a fixed factor.

Task fMRI

fMRI analyses were conducted using SPM 12 software (Wellcome Department of Imaging Neuroscience, University College London, London, UK). fMRI images were slice‐time corrected, realigned, coregistered to the T1 image, segmented, normalized to standardized MNI space, and spatially smoothed with an 8 mm FWHM Gaussian kernel. For each participant, a general linear model was generated in SPM per task, consisting of the following conditions: (1) motor activity and rest and (2) somatosensory stimulation and rest, which were convolved with the hemodynamic response function. For group analyses, single‐subject contrast images were entered into a random effect model. Block design motor and somatosensory fMRI tasks comprised 18 seconds of activity (motor: opening and closing right index finger and thumb; somatosensory: tactile stimulation on distal phalanx of right index finger) followed by 18 seconds of rest, for a total of 10 blocks per condition. The somatosensory stimulation was conducted using circular domes (25 mm diameter), fabricated from solid plastic with deep rectangular grooves cut into the surface (3 mm equidistant grooves and bars; JVP Domes; Stoelting Co, Wood Dale, IL). The left arm, hand, and fingers were restrained throughout. For the motor task, as with the rs‐fcMRI analysis, a priori ROIs (6 mm radius spheres) were generated in the left and right M1 (MNI coordinates: −41, −20, 62 and 41, −20, 62) as well as the left and right cerebellum (MNI coordinates: −20, −52, −24 and 17, −52, −24). For the somatosensory task, a priori ROIs (6 mm radius spheres) were generated in the left and right somatosensory cortex (MNI coordinates: −42, −35, 65 and 42, −35, 65). Additionally, a single‐blind investigator manually segmented the hand knob region of M1 using the McConnell Brain Imaging Centre MINC tool, Display.16 Following quality control, verifying the coregistration of each participant's T1 image, “default” left hand knob ROI, and right hand–induced motor task functional activation, 2 participants were excluded. Finally, mean beta weights were extracted from ROIs using MarsBar 0.44. As for the rs‐fcMRI data, a full factorial using the same design described below in the Statistical Analyses section was run in SPM12 for the fMRI 2nd‐level analyses, and family was entered as a fixed factor, because GEEs are not possible with SPM.

Diffusion‐Weighted Imaging of CC

Images were denoised using NLMEANS denoising17 as implemented in Dipy.18 Magnetic field inhomogeneities were corrected using the N4 correction from ANTS.19 A brain mask was extracted using BET from the FSL toolkit,20, 21 which was used in conjunction with the FSL Eddy tool to correct for motion, eddy currents, and susceptibility artifacts.20, 22 The T1 images were also denoised using NLMEANS, field inhomogeneities were corrected (N4 correction), and a brain mask was extracted (BET). The diffusion‐weighted imaging (DWI) datasets were then upsampled to 1 × 1 × 1 resolution, and tensor‐based diffusion metrics were computed using Dipy. Fiber orientation distribution functions were estimated using a fixed response function, set to correspond to a pure myelinated axon response (15, 4, 4 × 10⁻⁴ mm²/s). The T1 image was registered to the upsampled DWI using ANTS. A WM mask was segmented from the registered T1 using ANTS and was used for deterministic and probabilistic local tracking (as defined by Descoteaux et al23), which was run using 5 seeds per voxel of the WM mask, only keeping streamlines reaching the gray matter. Step size was 0.5 mm. Following generation of the whole‐brain tractogram, bundles composing the CC were automatically extracted using a modified version of the RecoBundles algorithm. In this algorithm, the whole‐brain tractogram was first registered to the atlas,24 and bundles were individually extracted based on centroids and distances to the atlas.25 The atlas comprises 20 major WM bundles, presegmented on 4 different healthy subjects from the Human Connectome Project dataset. Those segmentations were validated by 2 neuroanatomists for consistency with generally accepted anatomical definitions, and were used as references for the segmentation process. Subparts of the CC were segmented from the reference subject into 7 subparts as previously defined.26 Fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) values were extracted for each CC segment.

Lymphoblastoid Cell Line Growth, RNA Extraction, and Quantitative Real Time PCR

DCC mRNA expression was measured by performing RNA extraction followed by quantitative real time PCR, as previously described,27 using lymphoblastoid cell lines (LCLs) extracted from blood collected from the participants. LCLs established by transformation with Epstein–Barr virus were grown using standard protocols.28 Total RNA was isolated from the lymphoblastoid cell lines with the miRNeasy Micro Kit protocol (Qiagen, Toronto, Ontario, Canada). All RNA samples were determined to have 260/280 and 260/230 values ≥1.8, using the Nanodrop 1000 system (Thermo Fisher Scientific, Toronto, Ontario, Canada). Reverse transcription for DCC mRNA (2 mg) was performed using the High‐Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Toronto, Ontario, Canada). Real time PCR using TaqMan probes (Thermo Fisher Scientific) was carried out with an Applied Biosystems QuantStudio 6‐Flex Real Time PCR system. Data for DCC mRNA expression were analyzed by using the absolute quantitation standard curve method. Real time PCR was run in technical triplicates. The LCL sample (n = 37) included 10 DCC ^+/−/MM⁺, 6 DCC ^+/−/MM⁻, 11 DCC ^+/+/MM⁻, and 10 UHVs. This included 4 previously genotyped individuals (2 DCC ^+/−/MM⁻ and 2 DCC ^+/+/MM⁻) who did not participate in the present neuroimaging study. Four outliers were removed, as identified by GraphPad (La Jolla, CA) Prism 7’s ROUT test for definitive outliers (Q = 0.1%).

Statistical Analyses

Using SPSS20, ipsilateral EMG data, physiological MM, ipsilateral/contralateral MEP coefficients, IHI, fiber integrity of the CC, fMRI motor responses, and DCC mRNA expression were each analyzed using GEEs, with an exchangeable working correlation matrix. These analyses coded for the 2 fixed factors of (1) the presence of MM and (2) the presence of the DCC mutation. To control for the correlations among family members, driven by shared genetics and environments, we defined clusters by the branches within the Quebec family, descending from the earliest generation. Moreover, each unrelated healthy volunteer comprised their own cluster. Additionally, age was used as a covariate due to previously reported age‐related effects of DCC29, 30, 31 and of the motor system, as assessed with MRI and TMS.32, 33, 34 For the EMG, ipsilateral/contralateral MEP coefficients, and physiological MM analyses, the data did not satisfy assumptions of normality and consequently were log‐transformed. Log transformations were not appropriate for the task fMRI or DCC mRNA data, due to negative values and the transformations rendering the data less Gaussian. However, sensitivity analyses and inspection of the residuals revealed that these data were approximately normal. The MD, RD, and AD of the CC values were highly non‐normal, as indicated by normality tests and plots, and were unimproved by log transformations. Therefore, these data were not appropriate for GEE analyses and no significant effects were detected following sensitivity analyses, comprising the removal of the most extreme outliers, identified using Prism 7’s ROUT test for definitive outliers (Q = 0.1%).

Results

TMS and Electromyography

GEE analyses revealed that increased EMG activity in the mirroring hand during voluntary unilateral contractions was associated with the presence of MM (β = 0.829, 95% confidence interval [CI] = 0.457–1.201, p = 0.000013) but not with the DCC mutation (β = 0.156, 95% CI = −0.134 to 0.446, p = 0.293). Similarly, increases in the ratio of ipsilateral/contralateral MEPs induced by unilateral single‐pulse TMS of the M1 hand area were associated with MM (β = 1.666, 95% CI = 1.498–1.833, p < 0.00001) but, again, not the DCC mutation (β = −0.024, 95% CI = −0.290 to 0.243, p = 0.862).

The ipsilateral MEPs detected among the DCC ^+/−/MM⁺ participants occurred in 100% of trials. There was no effect of MM on the size of contralateral MEPs (F _{1, 40} = 0.0001, p = 0.99). Among the DCC ^+/−/MM⁺ participants, the amplitudes of ipsilateral MEPs, relative to contralateral MEPs, were smaller in 7 participants and larger in 5. Three participants presented ipsilateral MEPs that were > 5 times larger than their contralateral counterparts. Ipsilateral (mean [M] = 23.80, standard deviation [SD] = 3.05) and contralateral (M = 23.50, SD = 2.79) MEP latencies were nearly identical in the DCC ^+/−/MM⁺ group and not significantly different (F _1,11 = 2.2, p = 0.16), suggesting that the ipsilateral MEPs resulted from fast‐conducting, ipsilateral CST projections (Fig 2).

Figure 2.

Transcranial magnetic stimulation (TMS)/electromyography (EMG). (A) Raw EMG traces of TMS‐induced motor evoked potentials (MEPs) in a DCC ^+/−/mirror movements (MM)⁺ individual with larger MEPs in the hand contralateral to stimulation. Dashed lines indicate the onset of TMS‐induced MEPs. (B) Raw EMG traces of TMS‐induced MEPs and continuous EMG in a DCC ^+/−/MM⁺ individual with larger MEPs in the hand ipsilateral to stimulation.

Increased pMM were associated with MM (β = 0.437, 95% CI = 0.402–0.472, p < 0.00001). Again, these effects were uniquely associated with MM, as there were no significant effects of the DCC mutation on pMM (β = −0.007, 95% CI = −0.044 to 0.031, p = 0.735). Finally, reductions in IHI, indicated by increased responses following double‐coil TMS, were associated with MM (β = 0.531, 95% CI = 0.337–0.724, p < 0.00001). There were no significant effects of the DCC mutation on IHI (β = −0.028, 95% CI = −0.291 to 0.235, p = 0.833).

Resting State and Task fMRI

Functional connectivity was evaluated between our a priori ROIs (Fig 3). Between the right M1 and left M1, reduced functional connectivity was associated with the DCC mutation (β = −0.259, 95% CI = −0.517 to 0.000, p = 0.0497). Moreover, between the right M1 and left cerebellum, decreased connectivity was associated with the DCC mutation (β = −0.245, 95% CI = −0.436 to −0.054, p = 0.012) and increased connectivity was associated with MM (β = 0.245, 95% CI = 0.062–0.428, p = 0.009). See Table 2 for all pairwise connectivity values. A whole‐brain voxelwise search found no significant abnormalities (after familywise error [FWE] correction) in right M1 or left M1 connectivity.

Figure 3.

Resting state functional connectivity magnetic resonance imaging. A priori regions of interest are shown in the left and right primary motor cortex (i) and the left and right cerebellum (ii). Functional connectivity with the left primary motor cortex (iii) and right primary motor cortex (iv) is shown averaged across all participants. [Color figure can be viewed at www.annalsofneurology.org]

Table 2.

Pairwise Connectivity Values

Group	Right M1 to Left Cerebellum	Right M1 to Right Cerebellum	Right M1 to Left M1	Left M1 to Left Cerebellum	Left M1 to Right Cerebellum
DCC +/−/MM+	0.098	−0.110	0.707	0.075	0.062
DCC +/−/MM−	−0.087	−0.208	0.514	−0.037	−0.030
DCC +/+/MM−	0.173	−0.102	0.759	0.061	0.019
UHV	0.014	−0.052	0.818	−0.124	0.024

Average Fisher Z score values between a priori regions of interest for DCC ^+/−/MM⁺, DCC ^+/−/MM⁻, DCC ^+/+/MM⁻, and UHV.

M1 = primary motor cortex; MM = mirror movements; UHV = unrelated healthy volunteer.

Consistent with the reduction in IHI, increases in mirroring fMRI motor responses were associated with the presence of MM. Right hand–induced, right sphere–based M1 activations were associated with MM (β = 0.498, 95% CI = 0.073–0.922, p = 0.0215) and not the DCC mutation (β = −0.174, 95% CI = −0.446 to 0.099, p = 0.211; Fig 4). Similarly, in the right manually segmented hand area, increased right hand–induced activations were associated with MM (β = 0.462, 95% CI = 0.101–0.822, p = 0.012) and not with the DCC mutation (β = −0.138, 95% CI = −0.356 to 0.079, p = 0.212). Moreover, in the left cerebellum, increased right hand–induced activations were associated with MM (β = 0.398, 95% CI = 0.107–0.689, p = 0.007), whereas decreased activations were associated with the DCC mutation (β = −0.185, 95% CI = −0.366 to −0.004, p = 0.045). Small volume–corrected voxelwise analysis revealed a similar pattern of effects, whereby increased activation was associated with the presence of MM in the right M1 (t = 3.36, p _FWE = 0.009) and left cerebellum (t = 3.62, p _FWE = 0.005). Although these findings did not survive a whole‐brain correction, the peak activation sites and largest clusters across the whole brain (p < 0.001) were in the right motor cortex (t = 4.21, MNI coordinates: 38, −16, 40) and left cerebellum (t = 4.07, MNI coordinates: −26, −52, −16). As exploratory analyses, there were no significant effects identified in the analyses of the default left M1, left hand area, or right cerebellum (all p ≥ 0.20) or for the somatosensory task (all p ≥ 0.07).

Figure 4.

Task functional magnetic resonance imaging. (A–C) Increased right‐hand–induced activations associated with the presence of mirror movements in the ipsilateral (A) right primary motor cortex (M1) and (B) right M1 hand area, and in the contralateral (C) left cerebellum. (D) Peak activation sites in whole‐brain voxelwise analysis (p < 0.001) in left cerebellum and right M1. Raw data are plotted. MM = mirror movements; SEM = standard error of the mean; UHV = unrelated healthy volunteers. [Color figure can be viewed at www.annalsofneurology.org]

DTI and CC

Subtle reductions in FA were associated with the DCC mutation in the anterior midbody (β = −0.023, 95% CI = −0.042 to −0.003, p = 0.022), posterior midbody (β = −0.021, 95% CI = −0.036 to −0.005, p = 0.0078), isthmus (β = −0.017, 95% CI = −0.033 to 0.000, p = 0.048), and splenium (β = −0.016, 95% CI = −0.029 to −0.002, p = 0.021). Following sensitivity analyses of non‐normally distributed AD, MD, and RD data, no significant effects were identified in these measures. Partial agenesis of the CC with an absent rostrum was observed in 1 female DCC ^+/−/MM⁻ participant, as evaluated by a board‐certified neuroradiologist (Fig 5).

Figure 5.

Partial agenesis of the corpus callosum. (A) Partial agenesis of the corpus callosum in female individual with a DCC mutation and without mirror movements, revealing absence of the rostrum. (B) Female unrelated healthy volunteer without a DCC mutation or mirror movements, for comparison. [Color figure can be viewed at www.annalsofneurology.org]

DCC mRNA Expression

Quantitative real time PCR using RNA extracted from LCLs identified a significant reduction in DCC mRNA expression associated with the presence of MM (β = −1.056, 95% CI = −1.660 to −0.451, p = 0.00062). There was no significant effect of the DCC mutation alone (β = 0.265, 95% CI = −0.164 to 0.694, p = 0.226; Fig 6).

Figure 6.

DCC mRNA. Decreased DCC mRNA (quantity mean: DCC/glyceraldehyde‐3‐phosphate dehydrogenase) fold change, originating from both the functioning and mutated allele, is associated with the presence of mirror movements and not the DCC mutation. Raw data are plotted. MM = mirror movements; SEM = standard error of the mean; UHV = unrelated healthy volunteers. [Color figure can be viewed at www.annalsofneurology.org]

Discussion

The present study demonstrates that DCC ^+/− /MM⁺ participants exhibit diverse functional and anatomical connectivity alterations, including increased mirroring activations in motor regions and reduced IHI. Ipsilateral CSTs among the DCC ^+/− /MM⁺ individuals are strongly suggested by the similar latencies between TMS‐induced ipsilateral and contralateral MEPs. Strikingly, for the first time, we show distinct alterations of the motor system among DCC ^+/− mutation carriers, independently of MM. We also provide a possible mechanism underlying the partial penetrance of MM, as a reduction in peripheral DCC mRNA expression was only associated with the presence of MM and not the DCC mutation.

Contrary to what has been observed in RAD51 ^+/− /MM⁺ individuals,7 where mirror MEPs were elicited in no more than one‐third of TMS trials using 1.2x resting motor threshold intensity, mirror MEPs were induced in 100% of trials among DCC ^+/−/MM⁺ participants using a similar stimulation intensity at rest (1 mV MEP),35 consistent with recent reports.10 Therefore, it appears that downregulating DCC, compared to RAD51, has a larger impact on the development and excitability of the ipsilateral CST. Whereas DCC's role in guiding commissural and corticospinal axons has been characterized in vitro and in vivo,1, 10, 36, 37 RAD51 is less well understood but is expressed at the pyramidal decussation.38 Further elucidation of the molecular mechanisms is needed to explain phenotypic differences in CST between DCC and RAD51 mutation carriers.

Previous studies have indicated greater mirroring motor representations among individuals with MM,6, 7, 39 but our study restrained the mirroring arm, hand, and fingers, minimizing the possibility that the motor activation is simply an artifact of the movement in the mirroring hand. Instead, it appears that the reduced IHI results in increased mirroring motor representations. Our findings strongly suggest that unilateral motor control of the hand relies on selective corticospinal wiring between the motor cortex and contralateral hand, as well as on normal interhemispheric communication.

A previous report indicated that some DCC and RAD51 mutation carriers without visually apparent MM nonetheless exhibited subtle MM.40 In comparison, we did not detect any evidence of increased pMM in DCC ^+/− /MM⁻ individuals. However, we did identify evidence of reduced functional connectivity and WM integrity associated with the DCC ^+/− mutation (independent of mirror movements), suggesting a neurophysiologically altered motor system in individuals with an abnormal DCC gene.

Although only some DCC ^+/− carriers exhibit MM, both MM⁺ and MM⁻ DCC ^+/− groups exhibit alterations in CC tract architectures, including 1 DCC ^+/−/MM⁻ individual with partial agenesis of the CC. Thus, whereas decreased lateralization of the CST and movement‐induced motor representations depend upon the presence of MM, callosal abnormalities depend upon the presence of the DCC ^+/− mutation. Similarly, Marsh et al8 observed independent expression of MM and callosal agenesis among DCC ^+/− individuals. These differential effects of the DCC mutation might reflect individual differences in the regionally specific expression of DCC; for example, suppression of DCC within CST neurons is not sufficient to disrupt CST crossing but selective inhibition of DCC within commissural neurons is sufficient to disrupt callosal decussation.10 More generally, phenotypic differences between the 2 DCC ^+/− groups may be explained by more extensive and pervasive brain regional decreases in DCC expression, as suggested by the observation here that DCC mRNA reduction was associated with MM but not the DCC ^+/− mutation. Together, by identifying distinct phenotypes among DCC mutation carriers with and without MM, these findings affirm the critical role that DCC plays in the organization and function of commissural and CST fibers in humans.

Author Contributions

Conception and design of the study: A.D., C.B., M.S., R.J., F.L., G.R., A.P.‐L., M.F., C.F., M.L., H.T. Acquisition and analysis of data: D.E.V., V.B., A.T.‐B., D.C., A.C., N.J., S.M.L.C., K.L., D.A., F.D., Y.Z., D.T., R.L.P. Drafting a significant portion of the manuscript or figures: D.E.V., V.B., A.T.‐B., C.F., M.L., H.T.

Potential Conflicts of Interest

Nothing to report.