Heritability of white matter fiber tract shapes: A HARDI study of 198 twins

Genetic analysis of diffusion tensor images (DTI) shows great promise in revealing specific genetic variants that affect brain integrity and connectivity. Most genetic studies of DTI analyze voxel-based diffusivity indices in the image space (such as 3D maps of fractional anisotropy) and overlook tract geometry. Here we propose an automated workflow to cluster fibers using a white matter probabilistic atlas and perform genetic analysis on the shape characteristics of fiber tracts. We apply our approach to large study of 4-Tesla high angular resolution diffusion imaging (HARDI) data from 198 healthy, young adult twins (age: 20-30). Illustrative results show heritability for the shapes of several major tracts, as color-coded maps.

The arcuate fasciculus: an along-tract analysis with white matter probabilistic tractography

Il cervello umano è composto da una rete complessa, formata da fasci di assoni, che connettono le diverse aree cerebrali. Il fascio arcuato collega l’area imputata alla com- prensione del linguaggio con quella dedicata alla sua produzione. Il fascio arcuato è presente in entrambi gli emisferi cerebrali, anche se spesso è utilizzato prevalente- mente il sinistro. In questa tesi sono state valutate, in un campione di soggetti sani, le differenze tra fascio arcuato destro e sinistro, utilizzando la trattografia, metodica avanzata e non invasiva che permette la ricostruzione della traiettoria delle fibre con immagini RM (Risonanza Magnetica) pesate in diffusione. A questo scopo ho utilizzato un algoritmo probabilistico, che permette la stima di probabilità di connessione della fibra in oggetto con le diverse aree cerebrali, anche nelle sedi di incrocio con fibre di fasci diversi. Grazie all’implementazione di questo metodo, è stato possibile ottenere una ricostruzione accurata del fascio arcuato, an- che nell’emisfero destro dove è spesso critica, tanto da non essere possibile con altri algoritmi trattografici. Parametrizzando poi la geometria del tratto ho diviso il fascio arcuato in venti seg- menti e ho confrontato i parametri delle misure di diffusione, valutate nell’emisfero destro e sinistro. Da queste analisi emerge un’ampia variabilità nella geometria dell’arcuato, sia tra diversi soggetti che diversi emisferi. Nell’emisfero destro l’arcuato incrocia maggiormente fibre appartenenti ad altri fasci. Nell’emisfero sinistro le fibre dell’arcuato sono più compatte e si misura anche una maggiore connettività con altre aree del cervello coinvolte nelle funzioni linguistiche. Nella seconda fase dello studio ho applicato la stessa metodica in due pazienti con lesioni cerebrali, con l’obiettivo di testare il danno del fascio arcuato ipsilaterale alla lesione e stimare se nell’emisfero controlaterale si innescassero meccanismi di plastic- ità strutturale. Questa metodica può essere implementata, in un gruppo di pazienti omogenei, per identificare marcatori RM diagnostici nella fase di pianificazione pre- chirurgica e marcatori RM prognostici di recupero funzionale del linguaggio.

Labeling white matter tracts in hardi by fusing multiple tract atlases with applications to genetics

Accurate identification of white matter structures and segmentation of fibers into tracts is important in neuroimaging and has many potential applications. Even so, it is not trivial because whole brain tractography generates hundreds of thousands of streamlines that include many false positive fibers. We developed and tested an automatic tract labeling algorithm to segment anatomically meaningful tracts from diffusion weighted images. Our multi-atlas method incorporates information from multiple hand-labeled fiber tract atlases. In validations, we showed that the method outperformed the standard ROI-based labeling using a deformable, parcellated atlas. Finally, we show a high-throughput application of the method to genetic population studies. We use the sub-voxel diffusion information from fibers in the clustered tracts based on 105-gradient HARDI scans of 86 young normal twins. The whole workflow shows promise for larger population studies in the future.

White matter integrity measured by fractional anisotropy correlates poorly with actual individual fiber anisotropy

Fractional anisotropy (FA), a very widely used measure of fiber integrity based on diffusion tensor imaging (DTI), is a problematic concept as it is influenced by several quantities including the number of dominant fiber directions within each voxel, each fiber's anisotropy, and partial volume effects from neighboring gray matter. High-angular resolution diffusion imaging (HARDI) can resolve more complex diffusion geometries than standard DTI, including fibers crossing or mixing. The tensor distribution function (TDF) can be used to reconstruct multiple underlying fibers per voxel, representing the diffusion profile as a probabilistic mixture of tensors. Here we found that DTIderived mean diffusivity (MD) correlates well with actual individual fiber MD, but DTI-derived FA correlates poorly with actual individual fiber anisotropy, and may be suboptimal when used to detect disease processes that affect myelination. Analysis of the TDFs revealed that almost 40% of voxels in the white matter had more than one dominant fiber present. To more accurately assess fiber integrity in these cases, we here propose the differential diffusivity (DD), which measures the average anisotropy based on all dominant directions in each voxel.

Automatic clustering and population analysis of white matter tracts using maximum density paths

We introduce a framework for population analysis of white matter tracts based on diffusion-weighted images of the brain. The framework enables extraction of fibers from high angular resolution diffusion images (HARDI); clustering of the fibers based partly on prior knowledge from an atlas; representation of the fiber bundles compactly using a path following points of highest density (maximum density path; MDP); and registration of these paths together using geodesic curve matching to find local correspondences across a population. We demonstrate our method on 4-Tesla HARDI scans from 565 young adults to compute localized statistics across 50 white matter tracts based on fractional anisotropy (FA). Experimental results show increased sensitivity in the determination of genetic influences on principal fiber tracts compared to the tract-based spatial statistics (TBSS) method. Our results show that the MDP representation reveals important parts of the white matter structure and considerably reduces the dimensionality over comparable fiber matching approaches.

Cortico-cortical white matter motor pathway microstructure is related to psychomotor retardation in major depressive disorder

Alterations of brain structure and function have been associated with psychomotor retardation in major depressive disorder (MDD). However, the association of motor behaviour and white matter integrity of motor pathways in MDD is unclear. The aim of the present study was to first investigate structural connectivity of white matter motor pathways in MDD. Second, we explore the relation of objectively measured motor activity and white matter integrity of motor pathways in MDD. Therefore, 21 patients with MDD and 21 healthy controls matched for age, gender, education and body mass index underwent diffusion tensor imaging and 24 hour actigraphy (measure of the activity level) the same day. Applying a probabilistic fibre tracking approach we extracted connection pathways between the dorsolateral prefrontal cortex (dlPFC), the rostral anterior cingulate cortex (rACC), the pre-supplementary motor area (pre-SMA), the SMA-proper, the primary motor cortex (M1), the caudate nucleus, the putamen, the pallidum and the thalamus. Patients had lower activity levels and demonstrated increased mean diffusivity (MD) in pathways linking left pre-SMA and SMA-proper, and right SMA-proper and M1. Exploratory analyses point to a positive association of activity level and mean-fractional anisotropy in the right rACC-pre-SMA connection in MDD. Only MDD patients with low activity levels had a negative linear association of activity level and mean-MD in the left dlPFC-pre-SMA connection. Our results point to structural alterations of cortico-cortical white matter motor pathways in MDD. Altered white matter organisation of rACC-pre-SMA and dlPFC-pre-SMA pathways may contribute to movement initiation in MDD.

White matter microstructure alterations of the medial forebrain bundle in melancholic depression

BACKGROUND The medial forebrain bundle (MFB) is a key structure of the reward system and connects the ventral tegmental area (VTA) with the nucleus accumbens (NAcc), the medial and lateral orbitofrontal cortex (mOFC, lOFC) and the dorsolateral prefrontal cortex (dlPFC). Previous diffusion tensor imaging (DTI) studies in major depressive disorder point to white matter alterations of regions which may be incorporated in the MFB. Therefore, it was the aim of our study to probe white matter integrity of the MFB using a DTI-based probabilistic fibre tracking approach. METHODS 22 patients with major depressive disorder (MDD) (12 melancholic-MDD patients, 10 non-melancholic-MDD patients) and 21 healthy controls underwent DTI scans. We used a bilateral probabilistic fibre tracking approach to extract pathways between the VTA and NACC, mOFC, lOFC, dlPFC respectively. Mean fractional anisotropy (FA) values were used to compare structural connectivity between groups. RESULTS Mean-FA did not differ between healthy controls and all MDD patients. Compared to healthy controls melancholic MDD-patients had reduced mean-FA in right VTA-lOFC and VTA-dlPFC connections. Furthermore, melancholic-MDD patients had lower mean-FA than non-melancholic MDD-patients in the right VTA-lOFC connection. Mean-FA of these pathways correlated negatively with depression scale rating scores. LIMITATIONS Due to the small sample size and heterogeneous age group comparisons between melancholic and non-melancholic MDD-patients should be regarded as preliminary. CONCLUSIONS Our results suggest that the melancholic subtype of MDD is characterized by white matter microstructure alterations of the MFB. White matter microstructure is associated with both depression severity and anhedonia.

White matter pathway organization of the reward system is related to positive and negative symptoms in schizophrenia

The reward systemin schizophrenia has been linked to the emergence of delusions on the one hand and to negative symptoms such as affective flattening on the other hand. Previous Diffusion Tensor Imaging (DTI) studies reported white matter microstructure alterations of regions related to the reward system. The present study aimed at extending these findings by specifically investigating connection pathways of the reward system in schizophrenia. Therefore, 24 patients with schizophrenia and 22 healthy controls matched for age and gender underwent DTI-scans. Using a probabilistic fiber tracking approachwe bilaterally extracted pathways connecting the ventral tegmental area (VTA) with the nucleus accumbens (NAcc), themedial and lateral orbitofrontal cortices (mOFC, lOFC), the dorsolateral prefrontal cortex (dlPFC) and the amygdala; as well as pathways connecting NAcc with mOFC, lOFC, dlPFC and amygdala resulting in a total of 18 connections. Probability indices forming part of a bundle of interest (PIBI) were compared between groups using independent t-tests. In 6 connection pathways PIBI-valueswere increased in schizophrenia. In 3 of these pathways the spatial extension of connection pathways was decreased. In schizophrenia patients, there was a negative correlation of PIBI-values and PANSS negative scores in the left VTA–amygdala and in the left NAcc–mOFC connection. A sum score of delusions and hallucinations correlated positively with PIBI-values of the left amygdala–NAcc connection. Structural organization of specific segments ofwhite matter pathways of the reward systemin schizophrenia may contribute to the emergence of delusions and negative symptoms in schizophrenia.

Relationship of a variant in the NTRK1 gene to white matter microstructure in young adults

The NTRK1 gene (also known as TRKA) encodes a high-affinity receptor for NGF, a neurotrophin involved in nervous system development and myelination. NTRK1 has been implicated in neurological function via links between the T allele at rs6336 (NTRK1-T) and schizophrenia risk. A variant in the neurotrophin gene, BDNF, was previously associated with white matter integrity in young adults, highlighting the importantce of neurotrophins to white matter development. We hypothesized that NTRK1-T would relate to lower fractional anisotropy in healthy adults. We scanned 391 healthy adult human twins and their siblings (mean age: 23.6 ± 2.2 years; 31 NTRK1-T carriers, 360 non-carriers) using 105-gradient diffusion tensor imaging at 4 tesla. We evaluated in brain white matter how NTRK1-T and NTRK1 rs4661063 allele A (rs4661063-A, which is in moderate linkage disequilibrium with rs6336) related to voxelwise fractional anisotropy-acommondiffusion tensor imaging measure of white matter microstructure. We used mixed-model regression to control for family relatedness, age, and sex. The sample was split in half to test reproducibility of results. The false discovery rate method corrected for voxelwise multiple comparisons. NTRK1-T and rs4661063-A correlated with lower white matter fractional anisotropy, independent of age and sex (multiple-comparisons corrected: false discovery rate critical p=0.038 forNTRK1-Tand0.013 for rs4661063-A). In each half-sample, theNTRK1-T effectwasreplicated in the cingulum, corpus callosum, superior and inferior longitudinal fasciculi, inferior fronto-occipital fasciculus, superior corona radiata, and uncinate fasciculus. Our results suggest that NTRK1-T is important for developing white matter microstructure.

Common Alzheimer's disease risk variant within the CLU gene affects white matter microstructure in young adults

There is a strong genetic risk for late-onset Alzheimer's disease (AD), but so far few gene variants have been identified that reliably contribute to that risk. A newly confirmed genetic risk allele C of the clusterin (CLU) gene variant rs11136000 is carried by ~88% of Caucasians. The C allele confers a 1.16 greater odds of developing late-onset AD than the T allele. AD patients have reductions in regional white matter integrity. We evaluated whether the CLU risk variant was similarly associated with lower white matter integrity in healthy young humans. Evidence of early brain differences would offer a target for intervention decades before symptom onset. We scanned 398 healthy young adults (mean age, 23.6 ± 2.2 years) with diffusion tensor imaging, a variation of magnetic resonance imaging sensitive to white matter integrity in the living brain. We assessed genetic associations using mixed-model regression at each point in the brain to map the profile of these associations with white matter integrity. Each C allele copy of the CLUvariant was associated with lower fractional anisotropy-a widely accepted measure of white matter integrity-in multiple brain regions, including several known to degenerate in AD. These regions included the splenium of the corpus callosum, the fornix, cingulum, and superior and inferior longitudinal fasciculi in both brain hemispheres. Young healthy carriers of the CLU gene risk variant showed a distinct profile of lower white matter integrity that may increase vulnerability to developing AD later in life.

Relation between variants in the neurotrophin receptor gene, NTRK3, and white matter integrity in healthy young adults

The NTRK3 gene (also known as TRKC) encodes a high affinity receptor for the neurotrophin 3'-nucleotidase (NT3), which is implicated in oligodendrocyte and myelin development. We previously found that white matter integrity in young adults is related to common variants in genes encoding neurotrophins and their receptors. This underscores the importance of neurotrophins for white matter development. NTRK3 variants are putative risk factors for schizophrenia, bipolar disorder, and obsessive-compulsive disorder hoarding, suggesting that some NTRK3 variants may affect the brain.To test this, we scanned 392 healthy adult twins and their siblings (mean age, 23.6. ±. 2.2. years; range: 20-29. years) with 105-gradient 4-Tesla diffusion tensor imaging (DTI). We identified 18 single nucleotide polymorphisms (SNPs) in the NTRK3 gene that have been associated with neuropsychiatric disorders. We used a multi-SNP model, adjusting for family relatedness, age, and sex, to relate these variants to voxelwise fractional anisotropy (FA) - a DTI measure of white matter integrity.FA was optimally predicted (based on the highest false discovery rate critical p), by five SNPs (rs1017412, rs2114252, rs16941261, rs3784406, and rs7176429; overall FDR critical p=. 0.028). Gene effects were widespread and included the corpus callosum genu and inferior longitudinal fasciculus - regions implicated in several neuropsychiatric disorders and previously associated with other neurotrophin-related genetic variants in an overlapping sample of subjects. NTRK3 genetic variants, and neurotrophins more generally, may influence white matter integrity in brain regions implicated in neuropsychiatric disorders.

Information-theoretic analysis of brain white matter fiber orientation distribution functions

We propose a new information-theoretic metric, the symmetric Kullback-Leibler divergence (sKL-divergence), to measure the difference between two water diffusivity profiles in high angular resolution diffusion imaging (HARDI). Water diffusivity profiles are modeled as probability density functions on the unit sphere, and the sKL-divergence is computed from a spherical harmonic series, which greatly reduces computational complexity. Adjustment of the orientation of diffusivity functions is essential when the image is being warped, so we propose a fast algorithm to determine the principal direction of diffusivity functions using principal component analysis (PCA). We compare sKL-divergence with other inner-product based cost functions using synthetic samples and real HARDI data, and show that the sKL-divergence is highly sensitive in detecting small differences between two diffusivity profiles and therefore shows promise for applications in the nonlinear registration and multisubject statistical analysis of HARDI data.

Genetics of white matter development: A DTI study of 705 twins and their siblings aged 12 to 29

White matter microstructure is under strong genetic control, yet it is largely unknown how genetic influences change from childhood into adulthood. In one of the largest brain mapping studies ever performed, we determined whether the genetic control over white matter architecture depends on age, sex, socioeconomic status (SES), and intelligence quotient (IQ). We assessed white matter integrity voxelwise using diffusion tensor imaging at high magnetic field (4-Tesla), in 705 twins and their siblings (age range 12-29; 290. M/415. F). White matter integrity was quantified using a widely accepted measure, fractional anisotropy (FA). We fitted gene-environment interaction models pointwise, to visualize brain regions where age, sex, SES and IQ modulate heritability of fiber integrity. We hypothesized that environmental factors would start to outweigh genetic factors during late childhood and adolescence. Genetic influences were greater in adolescence versus adulthood, and greater in males than in females. Socioeconomic status significantly interacted with genes that affect fiber integrity: heritability was higher in those with higher SES. In people with above-average IQ, genetic factors explained over 80% of the observed FA variability in the thalamus, genu, posterior internal capsule, and superior corona radiata. In those with below-average IQ, however, only around 40% FA variability in the same regions was attributable to genetic factors. Genes affect fiber integrity, but their effects vary with age, sex, SES and IQ. Gene-environment interactions are vital to consider in the search for specific genetic polymorphisms that affect brain integrity and connectivity.

Improving fluid registration through white matter segmentation in a twin study design

Robust and automatic non-rigid registration depends on many parameters that have not yet been systematically explored. Here we determined how tissue classification influences non-linear fluid registration of brain MRI. Twin data is ideal for studying this question, as volumetric correlations between corresponding brain regions that are under genetic control should be higher in monozygotic twins (MZ) who share 100% of their genes when compared to dizygotic twins (DZ) who share half their genes on average. When these substructure volumes are quantified using tensor-based morphometry, improved registration can be defined based on which method gives higher MZ twin correlations when compared to DZs, as registration errors tend to deplete these correlations. In a study of 92 subjects, higher effect sizes were found in cumulative distribution functions derived from statistical maps when performing tissue classification before fluid registration, versus fluidly registering the raw images. This gives empirical evidence in favor of pre-segmenting images for tensor-based morphometry.

Obesity gene NEGR1 associated with white matter integrity in healthy young adults

Obesity is a crucial public health issue in developed countries, with implications for cardiovascular and brain health as we age. A number of commonly-carried genetic variants are associated with obesity. Here we aim to see whether variants in obesity-associated genes - NEGR1, FTO, MTCH2, MC4R, LRRN6C, MAP2K5, FAIM2, SEC16B, ETV5, BDNF- AS, ATXN2L, ATP2A1, KCTD15, and TNN13K - are associated with white matter microstructural properties, assessed by high angular resolution diffusion imaging (HARDI) in young healthy adults between 20 and 30. years of age from the Queensland Twin Imaging study (QTIM). We began with a multi-locus approach testing how a number of common genetic risk factors for obesity at the single nucleotide polymorphism (SNP) level may jointly influence white matter integrity throughout the brain and found a wide spread genetic effect. Risk allele rs2815752 in NEGR1 was most associated with lower white matter integrity across a substantial portion of the brain. Across the area of significance in the bilateral posterior corona radiata, each additional copy of the risk allele was associated with a 2.2% lower average FA. This is the first study to find an association between an obesity risk gene and differences in white matter integrity. As our subjects were young and healthy, our results suggest that NEGR1 has effects on brain structure independent of its effect on obesity.