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Heritability of white matter microstructure in late middle age: A twin study of tract-based fractional anisotropy and absolute diffusivity indices.

ABSTRACT: There is evidence that differences among individuals in white matter microstructure, as measured with diffusion tensor imaging (DTI), are under genetic control. However, little is known about the relative contribution of genetic and environmental effects on different diffusivity indices among late middle-aged adults. Here, we examined the magnitude of genetic influences for fractional anisotropy (FA), and mean (MD), axial (AD), and radial (RD) diffusivities in male twins aged 56-66 years old. Using an atlas-based registration approach to delineate individual white matter tracts, we investigated mean DTI-based indices within the corpus callosum, 12 bilateral tracts and all these regions of interest combined. All four diffusivity indices had high heritability at the global level (72%-80%). The magnitude of genetic effects in individual tracts varied from 0% to 82% for FA, 0% to 81% for MD, 8% to 77% for AD, and 0% to 80% for RD with most of the tracts showing significant heritability estimates. Despite the narrow age range of this community-based sample, age was correlated with all four diffusivity indices at the global level. In sum, all diffusion indices proved to have substantial heritability for most of the tracts and the heritability estimates were similar in magnitude for different diffusivity measures. Future studies could aim to discover the particular set of genes that underlie the significant heritability of white matter microstructure. Hum Brain Mapp 38:2026-2036, 2017. © 2017 Wiley Periodicals, Inc.

SUBMITTER: Vuoksimaa E

PROVIDER: S-EPMC5342936 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Heritability of white matter microstructure in late middle age: A twin study of tract-based fractional anisotropy and absolute diffusivity indices.

Vuoksimaa Eero E Panizzon Matthew S MS Hagler Donald J DJ Hatton Sean N SN Fennema-Notestine Christine C Rinker Daniel D Eyler Lisa T LT Franz Carol E CE Lyons Michael J MJ Neale Michael C MC Tsuang Ming T MT Dale Anders M AM Kremen William S WS

Human brain mapping 20161229 4

There is evidence that differences among individuals in white matter microstructure, as measured with diffusion tensor imaging (DTI), are under genetic control. However, little is known about the relative contribution of genetic and environmental effects on different diffusivity indices among late middle-aged adults. Here, we examined the magnitude of genetic influences for fractional anisotropy (FA), and mean (MD), axial (AD), and radial (RD) diffusivities in male twins aged 56-66 years old. Us ...[more]

PMID: 28032374

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Project description:BackgroundMean diffusivity (MD) and fractional anisotropy (FA) from diffusion MRI (dMRI) have been associated with cell density and tissue anisotropy across tumors, but it is unknown whether these associations persist at the microscopic level.PurposeTo quantify the degree to which cell density and anisotropy, as determined from histology, account for the intra-tumor variability of MD and FA in meningioma tumors. Furthermore, to clarify whether other histological features account for additional intra-tumor variability of dMRI parameters.Materials and methodsWe performed ex-vivo dMRI at 200 μm isotropic resolution and histological imaging of 16 excised meningioma tumor samples. Diffusion tensor imaging (DTI) was used to map MD and FA, as well as the in-plane FA (FAIP). Histology images were analyzed in terms of cell nuclei density (CD) and structure anisotropy (SA; obtained from structure tensor analysis) and were used separately in a regression analysis to predict MD and FAIP, respectively. A convolutional neural network (CNN) was also trained to predict the dMRI parameters from histology patches. The association between MRI and histology was analyzed in terms of out-of-sample (R2OS) on the intra-tumor level and within-sample R2 across tumors. Regions where the dMRI parameters were poorly predicted from histology were analyzed to identify features apart from CD and SA that could influence MD and FAIP, respectively.ResultsCell density assessed by histology poorly explained intra-tumor variability of MD at the mesoscopic level (200 μm), as median R2OS = 0.04 (interquartile range 0.01-0.26). Structure anisotropy explained more of the variation in FAIP (median R2OS = 0.31, 0.20-0.42). Samples with low R2OS for FAIP exhibited low variations throughout the samples and thus low explainable variability, however, this was not the case for MD. Across tumors, CD and SA were clearly associated with MD (R2 = 0.60) and FAIP (R2 = 0.81), respectively. In 37% of the samples (6 out of 16), cell density did not explain intra-tumor variability of MD when compared to the degree explained by the CNN. Tumor vascularization, psammoma bodies, microcysts, and tissue cohesivity were associated with bias in MD prediction based solely on CD. Our results support that FAIP is high in the presence of elongated and aligned cell structures, but low otherwise.ConclusionCell density and structure anisotropy account for variability in MD and FAIP across tumors but cell density does not explain MD variations within the tumor, which means that low or high values of MD locally may not always reflect high or low tumor cell density. Features beyond cell density need to be considered when interpreting MD.

Project description:BackgroundDiffusion tensor imaging (DTI) magnetic resonance imaging (MRI) measuring fractional anisotropy (FA) and axial diffusivity (AD) may be a useful biomarker for monitoring changes in white matter after stroke, but its associations with upper-limb motor recovery have not been well studied. We aim to describe changes in the whole-brain FA and AD in five post-stroke patients in relation to kinematic measures of elbow flexion to better understand the relationship between FA and AD changes and clinico-kinematic measures of upper limb motor recovery.MethodsWe performed DTI MRI at two timepoints during the acute phase of stroke, measuring FA and AD across 48 different white matter tract regions in the brains of five hemiparetic patients with infarcts in the cortex, pons, basal ganglia, thalamus, and corona radiata. We tracked the progress of these patients using clinical Fugl-Meyer Assessments and kinematic measures of elbow flexion at the acute phase within 14 (mean: 9.4 ± 2.49) days of stroke symptom onset and at a follow-up appointment 2 weeks later (mean: 16 ± 1.54) days.ResultsChanges in FA and AD in 48 brain regions occurring during stroke rehabilitation are described in relation to motor recovery. In this case series, one patient with a hemipontine infarct showed an increase in FA of the ipsilateral and contralateral corticospinal tract, whereas other patients with lesions involving the corona radiata and middle cerebral artery showed widespread decreases in perilesional FA. On the whole, FA and AD seemed to behave inversely to each other.ConclusionsThis case series describes longitudinal changes in perilesional and remote FA and AD in relation to kinematic parameters of elbow flexion at the subacute post-stroke period. Although studies with larger sample sizes are needed, our findings indicate that longitudinally measured changes in DTI-based measurements of white matter microstructural integrity may aid in the prognostication of patients affected by motor stroke.

Project description:IntroductionDiffusion tensor imaging (DTI) assumes a single pool of anisotropically diffusing water to calculate fractional anisotropy (FA) and is commonly used to ascertain white matter (WM) deficits in schizophrenia. At higher b-values, diffusion-signal decay becomes bi-exponential, suggesting the presence of two, unrestricted and restricted, water pools. Theoretical work suggests that semi-permeable cellular membrane rather than the presence of two physical compartments is the cause. The permeability-diffusivity (PD) parameters measured from bi-exponential modeling may offer advantages, over traditional DTI-FA, in identifying WM deficits in schizophrenia.MethodsImaging was performed in N = 26/26 patients/controls (age = 20-61 years, average age = 40.5 ± 12.6). Imaging consisted of fifteen b-shells: b = 250-3800 s/mm(2) with 30 directions/shell, covering seven slices of mid-sagittal corpus callosum (CC) at 1.7 × 1.7 × 4.6 mm. 64-direction DTI was also collected. Permeability-diffusivity-index (PDI), the ratio of restricted to unrestricted apparent diffusion coefficients, and the fraction of unrestricted compartment (Mu) were calculated for CC and cingulate gray matter (GM). FA values for CC were calculated using tract-based-spatial-statistics.ResultsPatients had significantly reduced PDI in CC (p ≅ 10(- 4)) and cingulate GM (p = 0.002), while differences in CC FA were modest (p ≅ .03). There was no group-related difference in Mu. Additional theoretical-modeling analysis suggested that reduced PDI in patients may be caused by reduced cross-membrane water molecule exchanges.ConclusionPDI measurements for cerebral WM and GM yielded more robust patient-control differences than DTI-FA. Theoretical work offers an explanation that patient-control PDI differences should implicate abnormal active membrane permeability. This would implicate abnormal activities in ion-channels that use water as substrate for ion exchange, in cerebral tissues of schizophrenia patients.

Project description:BackgroundQuantitative maps obtained with diffusion weighted (DW) imaging, such as fractional anisotropy (FA) -calculated by fitting the diffusion tensor (DT) model to the data,-are very useful to study neurological diseases. To fit this map accurately, acquisition times of the order of several minutes are needed because many noncollinear DW volumes must be acquired to reduce directional biases. Deep learning (DL) can be used to reduce acquisition times by reducing the number of DW volumes. We already developed a DL network named "one-minute FA," which uses 10 DW volumes to obtain FA maps, maintaining the same characteristics and clinical sensitivity of the FA maps calculated with the standard method using more volumes. Recent publications have indicated that it is possible to train DL networks and obtain FA maps even with 4 DW input volumes, far less than the minimum number of directions for the mathematical estimation of the DT.MethodsHere we investigated the impact of reducing the number of DW input volumes to 4 or 7, and evaluated the performance and clinical sensitivity of the corresponding DL networks trained to calculate FA, while comparing results also with those using our one-minute FA. Each network training was performed on the human connectome project open-access dataset that has a high resolution and many DW volumes, used to fit a ground truth FA. To evaluate the generalizability of each network, they were tested on two external clinical datasets, not seen during training, and acquired on different scanners with different protocols, as previously done.ResultsUsing 4 or 7 DW volumes, it was possible to train DL networks to obtain FA maps with the same range of values as ground truth - map, only when using HCP test data; pathological sensitivity was lost when tested using the external clinical datasets: indeed in both cases, no consistent differences were found between patient groups. On the contrary, our "one-minute FA" did not suffer from the same problem.ConclusionWhen developing DL networks for reduced acquisition times, the ability to generalize and to generate quantitative biomarkers that provide clinical sensitivity must be addressed.

Dataset Information

Heritability of white matter microstructure in late middle age: A twin study of tract-based fractional anisotropy and absolute diffusivity indices.

Publications

Heritability of white matter microstructure in late middle age: A twin study of tract-based fractional anisotropy and absolute diffusivity indices.

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