Heritability estimates of cortical anatomy:The influence and reliability of different estimation strategies

Twin study designs have been previously used to investigate the heritability of neuroanatomical measures, such as regional cortical volumes. Volume can be fractionated into surface area and cortical thickness, where both measures are considered to have independent genetic and environmental bases. Region of interest (ROI) and vertex-wise approaches have been used to calculate heritability of cortical thickness and surface area in twin studies. In our study, we estimate heritability using the Human Connectome Project magnetic resonance imaging dataset composed of healthy young twin and non-twin siblings (mean age of 29, sample size of 757). Both ROI and vertex-wise methods were used to compare regional heritability of cortical thickness and surface area. Heritability estimates were controlled for age, sex, and total ipsilateral surface area or mean cortical thickness. In both approaches, heritability estimates of cortical thickness and surface area were lower when accounting for average ipsilateral cortical thickness and total surface area respectively. When comparing both approaches at a regional level, the vertex-wise approach showed higher surface area and lower cortical thickness heritability estimates compared to the ROI approach. The calcarine fissure had the highest surface area heritability estimate (ROI: 44%, vertex-wise: 50%) and posterior cingulate gyrus had the highest cortical thickness heritability (ROI: 50%, vertex-wise 40%). We also observed that limitations in image processing and variability in spatial averaging errors based on regional size may make obtaining true estimates of cortical thickness and surface area challenging in smaller regions. It is important to identify which approach is best suited to estimate heritability based on the research hypothesis and the size of the regions being investigated

Heritability of hippocampal subfield volumes using a twin and non-twin siblings design

The hippocampus is composed of distinct subfields linked to diverse functions and disorders. The subfields can be mapped using high-resolution magnetic resonance images, and their volumes can potentially be used as quantitative phenotypes for genetic investigation of hippocampal function. We estimated the heritability of hippocampus subfield volumes of 465 subjects from the Human Connectome Project (twins and non-twin siblings) using two methods. The first used a univariate model to estimate heritability with and without adjustment for total brain volume (TBV) and ipsilateral hippocampal volume to determine if heritability was uniquely attributable to subfield volume rather than confounds that attributed to global volumes. We observed the right: subiculum, cornu ammonis 2/3, and cornu ammonis 4/dentate gyrus subfields had the highest significant heritability estimates after adjusting for ipsilateral hippocampal volume. In the second analysis, we used a bivariate model to investigate the shared heritability and genetic correlation of the subfield volumes with TBV and ipsilateral hippocampal volume. Genetic correlation demonstrates shared genetic architecture between phenotypes and shared heritability is what proportion of the genetic architecture of one trait is shared by the other. Highest genetic correlations were between subfield volumes and ipsilateral hippocampal volume than with TBV. The pattern was opposite for shared heritability suggesting that subfields share greater proportion of the genetic architecture with TBV than with ipsilateral hippocampal volume. The relationship between the genetic architecture of TBV, hippocampal volume, and of individual subfields should be accounted for when using hippocampal subfield volumes as quantitative phenotypes for imaging genetics studies. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc

Patterns of gray matter atrophy in genetic frontotemporal dementia: results from the GENFI study.

Frontotemporal dementia (FTD) is a highly heritable condition with multiple genetic causes. In this study, similarities and differences of gray matter (GM) atrophy patterns were assessed among 3 common forms of genetic FTD (mutations in C9orf72, GRN, and MAPT). Participants from the Genetic FTD Initiative (GENFI) cohort with a suitable volumetric T1 magnetic resonance imaging scan were included (319): 144 nonmutation carriers, 128 presymptomatic mutation carriers, and 47 clinically affected mutation carriers. Cross-sectional differences in GM volume between noncarriers and carriers were analyzed using voxel-based morphometry. In the affected carriers, each genetic mutation group exhibited unique areas of atrophy but also a shared network involving the insula, orbitofrontal lobe, and anterior cingulate. Presymptomatic GM atrophy was observed particularly in the thalamus and cerebellum in the C9orf72 group, the anterior and medial temporal lobes in MAPT, and the posterior frontal and parietal lobes as well as striatum in GRN. Across all presymptomatic carriers, there were significant decreases in the anterior insula. These results suggest that although there are important differences in atrophy patterns for each group (which can be seen presymptomatically), there are also similarities (a fronto-insula-anterior cingulate network) that help explain the clinical commonalities of the disease

Improved Segmentation of the Intracranial and Ventricular Volumes in Populations with Cerebrovascular Lesions and Atrophy Using 3D CNNs

Successful segmentation of the total intracranial vault (ICV) and ventricles is of critical importance when studying neurodegeneration through neuroimaging. We present iCVMapper and VentMapper, robust algorithms that use a convolutional neural network (CNN) to segment the ICV and ventricles from both single and multi-contrast MRI data. Our models were trained on a large dataset from two multi-site studies (N = 528 subjects for ICV, N = 501 for ventricular segmentation) consisting of older adults with varying degrees of cerebrovascular lesions and atrophy, which pose significant challenges for most segmentation approaches. The models were tested on 238 participants, including subjects with vascular cognitive impairment and high white matter hyperintensity burden. Two of the three test sets came from studies not used in the training dataset. We assessed our algorithms relative to four state-of-the-art ICV extraction methods (MONSTR, BET, Deep Extraction, FreeSurfer, DeepMedic), as well as two ventricular segmentation tools (FreeSurfer, DeepMedic). Our multi-contrast models outperformed other methods across many of the evaluation metrics, with average Dice coefficients of 0.98 and 0.96 for ICV and ventricular segmentation respectively. Both models were also the most time efficient, segmenting the structures in orders of magnitude faster than some of the other available methods. Our networks showed an increased accuracy with the use of a conditional random field (CRF) as a post-processing step. We further validated both segmentation models, highlighting their robustness to images with lower resolution and signal-to-noise ratio, compared to tested techniques. The pipeline and models are available at: https://icvmapp3r.readthedocs.io and https://ventmapp3r.readthedocs.io to enable further investigation of the roles of ICV and ventricles in relation to normal aging and neurodegeneration in large multi-site studies

Downregulation of exosomal miR-204-5p and miR-632 as a biomarker for FTD: A GENFI study

Objective: To determine whether exosomal microRNAs (miRNAs) in cerebrospinal fluid (CSF) of patients with frontotemporal dementia (FTD) can serve as diagnostic biomarkers, we assessed miRNA expression in the Genetic Frontotemporal Dementia Initiative (GENFI) cohort and in sporadic FTD. Methods: GENFI participants were either carriers of a pathogenic mutation in progranulin, chromosome 9 open reading frame 72 or microtubule-associated protein tau or were at risk of carrying a mutation because a first-degree relative was a known symptomatic mutation carrier. Exosomes were isolated from CSF of 23 presymptomatic and 15 symptomatic mutation carriers and 11 healthy non-mutation carriers. Expression of 752 miRNAs was measured using quantitative PCR (qPCR) arrays and validated by qPCR using individual primers. MiRNAs found differentially expressed in symptomatic compared with presymptomatic mutation carriers were further evaluated in a cohort of 17 patients with sporadic FTD, 13 patients with sporadic Alzheimer's disease (AD) and 10 healthy controls (HCs) of similar age. Results: In the GENFI cohort, miR-204-5p and miR-632 were significantly decreased in symptomatic compared with presymptomatic mutation carriers. Decrease of miR-204-5p and miR-632 revealed receiver operator characteristics with an area of 0.89 (90% CI 0.79 to 0.98) and 0.81 (90% CI 0.68 to 0.93), respectively, and when combined an area of 0.93 (90% CI 0.87 to 0.99). In sporadic FTD, only miR-632 was significantly decreased compared with AD and HCs. Decrease of miR-632 revealed an area of 0.90 (90% CI 0.81 to 0.98). Conclusions: Exosomal miR-204-5p and miR-632 have potential as diagnostic biomarkers for genetic FTD and miR-632 also for sporadic FTD

APOE-ɛ4, white matter hyperintensities, and cognition in Alzheimer and Lewy body dementia

Objective To determine if APOE ε4 influences the association between white matter hyperintensities (WMH) and cognitive impairment in Alzheimer disease (AD) and dementia with Lewy bodies (DLB). Methods A total of 289 patients (AD = 239; DLB = 50) underwent volumetric MRI, neuropsychological testing, and APOE ε4 genotyping. Total WMH volumes were quantified. Neuropsychological test scores were included in a confirmatory factor analysis to identify cognitive domains encompassing attention/executive functions, learning/memory, and language, and factor scores for each domain were calculated per participant. After testing interactions between WMH and APOE ε4 in the full sample, we tested associations of WMH with factor scores using linear regression models in APOE ε4 carriers (n = 167) and noncarriers (n = 122). We hypothesized that greater WMH volume would relate to worse cognition more strongly in APOE ε4 carriers. Findings were replicated in 198 patients with AD from the Alzheimer's Disease Neuroimaging Initiative (ADNI-I), and estimates from both samples were meta-analyzed. Results A significant interaction was observed between WMH and APOE ε4 for language, but not for memory or executive functions. Separate analyses in APOE ε4 carriers and noncarriers showed that greater WMH volume was associated with worse attention/executive functions, learning/memory, and language in APOE ε4 carriers only. In ADNI-I, greater WMH burden was associated with worse attention/executive functions and language in APOE ε4 carriers only. No significant associations were observed in noncarriers. Meta-analyses showed that greater WMH volume was associated with worse performance on all cognitive domains in APOE ε4 carriers only. Conclusion APOE ε4 may influence the association between WMH and cognitive performance in AD and DLB

Cognitive composites for genetic frontotemporal dementia: GENFI-Cog

Background: Clinical endpoints for upcoming therapeutic trials in frontotemporal dementia (FTD) are increasingly urgent. Cognitive composite scores are often used as endpoints but are lacking in genetic FTD. We aimed to create cognitive composite scores for genetic frontotemporal dementia (FTD) as well as recommendations for recruitment and duration in clinical trial design. Methods: A standardized neuropsychological test battery covering six cognitive domains was completed by 69 C9orf72, 41 GRN, and 28 MAPT mutation carriers with CDR® plus NACC-FTLD ≥ 0.5 and 275 controls. Logistic regression was used to identify the combination of tests that distinguished best between each mutation carrier group and controls. The composite scores were calculated from the weighted averages of test scores in the models based on the regression coefficients. Sample size estimates were calculated for individual cognitive tests and composites in a theoretical trial aimed at preventing progression from a prodromal stage (CDR® plus NACC-FTLD 0.5) to a fully symptomatic stage (CDR® plus NACC-FTLD ≥ 1). Time-to-event analysis was performed to determine how quickly mutation carriers progressed from CDR® plus NACC-FTLD = 0.5 to ≥ 1 (and therefore how long a trial would need to be). Results: The results from the logistic regression analyses resulted in different composite scores for each mutation carrier group (i.e. C9orf72, GRN, and MAPT). The estimated sample size to detect a treatment effect was lower for composite scores than for most individual tests. A Kaplan-Meier curve showed that after 3 years, ~ 50% of individuals had converted from CDR® plus NACC-FTLD 0.5 to ≥ 1, which means that the estimated effect size needs to be halved in sample size calculations as only half of the mutation carriers would be expected to progress from CDR® plus NACC FTLD 0.5 to ≥ 1 without treatment over that time period. Discussion: We created gene-specific cognitive composite scores for C9orf72, GRN, and MAPT mutation carriers, which resulted in substantially lower estimated sample sizes to detect a treatment effect than the individual cognitive tests. The GENFI-Cog composites have potential as cognitive endpoints for upcoming clinical trials. The results from this study provide recommendations for estimating sample size and trial duration

Investigating the contribution of white matter hyperintensities and cortical thickness to empathy in neurodegenerative and cerebrovascular diseases

Change in empathy is an increasingly recognised symptom of neurodegenerative diseases and contributes to caregiver burden and patient distress. Empathy impairment has been associated with brain atrophy but its relationship to white matter hyperintensities (WMH) is unknown. We aimed to investigate the relationships amongst WMH, brain atrophy, and empathy deficits in neurodegenerative and cerebrovascular diseases. Five hundred thirteen participants with Alzheimer’s disease/mild cognitive impairment, amyotrophic lateral sclerosis, frontotemporal dementia (FTD), Parkinson’s disease, or cerebrovascular disease (CVD) were included. Empathy was assessed using the Interpersonal Reactivity Index. WMH were measured using a semi-automatic segmentation and FreeSurfer was used to measure cortical thickness. A heterogeneous pattern of cortical thinning was found between groups, with FTD showing thinning in frontotemporal regions and CVD in left superior parietal, left insula, and left postcentral. Results from both univariate and multivariate analyses revealed that several variables were associated with empathy, particularly cortical thickness in the fronto-insulo-temporal and cingulate regions, sex (female), global cognition, and right parietal and occipital WMH. Our results suggest that cortical atrophy and WMH may be associated with empathy deficits in neurodegenerative and cerebrovascular diseases. Future work should consider investigating the longitudinal effects of WMH and atrophy on empathy deficits in neurodegenerative and cerebrovascular diseases