Fine-mapping the effects of Alzheimer's disease risk loci on brain morphology

Distinctive whole-brain cell types predict tissue damage patterns in thirteen neurodegenerative conditions

For over a century, brain research narrative has mainly centered on neuron cells. Accordingly, most neurodegenerative studies focus on neuronal dysfunction and their selective vulnerability, while we lack comprehensive analyses of other major cell types' contribution. By unifying spatial gene expression, structural MRI, and cell deconvolution, here we describe how the human brain distribution of canonical cell types extensively predicts tissue damage in 13 neurodegenerative conditions, including early- and late-onset Alzheimer's disease, Parkinson's disease, dementia with Lewy bodies, amyotrophic lateral sclerosis, mutations in presenilin-1, and 3 clinical variants of frontotemporal lobar degeneration (behavioral variant, semantic and non-fluent primary progressive aphasia) along with associated three-repeat and four-repeat tauopathies and TDP43 proteinopathies types A and C. We reconstructed comprehensive whole-brain reference maps of cellular abundance for six major cell types and identified characteristic axes of spatial overlapping with atrophy. Our results support the strong mediating role of non-neuronal cells, primarily microglia and astrocytes, in spatial vulnerability to tissue loss in neurodegeneration, with distinct and shared across-disorder pathomechanisms. These observations provide critical insights into the multicellular pathophysiology underlying spatiotemporal advance in neurodegeneration. Notably, they also emphasize the need to exceed the current neuro-centric view of brain diseases, supporting the imperative for cell-specific therapeutic targets in neurodegeneration.

A comprehensive analysis of APOE genotype effects on human brain structure in the UK Biobank

Alzheimer's disease (AD) risk is increased in carriers of the apolipoprotein E (APOE) ε4 allele and decreased in ε2 allele carriers compared with the ε3ε3 genotype. The aim of this study was to determine whether: the APOE genotype affects brain grey (GM) or white matter (WM) structure; and if differences exist, the age when they become apparent and whether there are differential effects by sex. We used cross-sectional magnetic resonance imaging data from ~43,000 (28,494 after pre-processing) white British cognitively healthy participants (7,446 APOE ε4 carriers) aged 45-80 years from the UK Biobank cohort and investigated image-derived phenotypes (IDPs). We observed no statistically significant effects of APOE genotype on GM structure volumes or median T2* in subcortical structures, a measure related to iron content. The volume of white matter hyperintensities differed significantly between APOE genotype groups with higher volumes in APOE ε4ε4 (effect size 0.14 standard deviations [SD]) and ε3ε4 carriers (effect size 0.04 SD) but no differences in ε2 carriers compared with ε3ε3 carriers. WM integrity measures in the dorsal (mean diffusivity [MD]) and ventral cingulum (MD and intracellular volume fraction), posterior thalamic radiation (MD and isotropic volume fraction) and sagittal stratum (MD) indicated lower integrity in APOE ε4ε4 carriers (effect sizes around 0.2-0.3 SD) and ε3ε4 (effect sizes around 0.05 SD) carriers but no differences in ε2 carriers compared with the APOE ε3ε3 genotype. Effects did not differ between men and women. APOE ε4 homozygotes had lower WM integrity specifically at older ages with a steeper decline of WM integrity from the age of 60 that corresponds to around 5 years greater "brain age". APOE genotype affects various white matters measures, which might be indicative of preclinical AD processes. This hypothesis can be assessed in future when clinical outcomes become available.

Higher fresh fruit intake relates to larger grey matter volumes in areas involved in dementia and depression: A UK Biobank study

The benefits of consuming fruits and vegetables are widely accepted. While previous studies suggest a protective role of fruits and vegetables against a variety of diseases such as dementia and depression, the biological mechanisms/effects remain unclear. Here we investigated the effect of fruit and vegetable consumption on brain structure. Particularly on grey matter (GM) and white matter (WM) volumes, regional GM volumes and subcortical volumes. Cross-sectional imaging data from UK Biobank cohort was used. A total of 9925 participants (Mean age 62.4 ± 7.5 years, 51.1 % men) were included in the present analysis. Measures included fruit and vegetable intake, other dietary patterns and a number of selected lifestyle factors and clinical data. Brain volumes were derived from structural brain magnetic resonance imaging. General linear model was used to study the associations between brain volumes and fruit/vegetable intakes. After adjusting for selected confounding factors, salad/raw vegetable intake showed a positive association with total white matter volume, fresh fruit intake showed a negative association with total grey matter (GM) volume. Regional GM analyses showed that higher fresh fruit intake was associated with larger GM volume in the left hippocampus, right temporal occipital fusiform cortex, left postcentral gyrus, right precentral gyrus, and right juxtapositional lobule cortex. We conclude that fruit and vegetable consumption seems to specifically modulate brain volumes. In particular, fresh fruit intake may have a protective role in specific cortical areas such as the hippocampus, areas robustly involved in the pathophysiology of dementia and depression.

Cortical anatomical variations, gene expression profiles, and clinical phenotypes in patients with schizophrenia

BACKGROUND AND HYPOTHESIS

Schizophrenia (SZ) patients display significant structural brain abnormalities; nevertheless, the genetic mechanisms regulating cortical anatomical variations and their correlation with the disease phenotype are still ambiguous.

STUDY DESIGN

We characterized anatomical variation using a surface-based method derived from structural magnetic resonance imaging of patients with SZ and age- and sex-matched healthy controls (HCs). Partial least-squares regression was performed across cortex regions between anatomical variation and average transcriptional profiles of SZ risk genes and all qualified genes from the Allen Human Brain Atlas. The morphological features of each brain region were correlated to symptomology variables in patients with SZ using partial correlation analysis.

STUDY RESULTS

A total of 203 SZ and 201 HCs were included in the final analysis. We observed significant variation of 55 regions of cortical thickness, 23 regions of volume, 7 regions of area, and 55 regions of local gyrification index (LGI) between SZ and HC groups. Expression profiles of 4 SZ risk genes and 96 genes from all qualified genes showed a correlation to anatomical variability, however, after multiple comparisons, the correlations were no longer significant. LGI variability in multiple frontal subregions was associated with specific symptoms of SZ, whereas cognitive function involving attention/vigilance was linked to LGI variability across nine brain regions.

CONCLUSIONS

Cortical anatomical variation of patients with schizophrenia is associated with gene transcriptome profiles as well as clinical phenotypes.

Association between ABCA7 gene polymorphisms and Parkinson's disease susceptibility in a northern Chinese Han population

OBJECTIVE

As a typical member of the ABC transporter superfamily, ABCA7 has been shown to play an important role in stalling the pathogenesis of neurodegenerative disorders through maintaining the normal microglial function, regulating cellular responses to inflammation and ER stress, and modulating lipid metabolism. Variants in the ABCA7 locus have been hypothesized to be correlated with the genetic predisposition of several neurodegenerative disorders. The goal of this study was to examine whether there is a link between three specific single nucleotide polymorphisms in the ABCA7 gene, namely, rs3764650, rs4147929, and rs3752246, with the risk of developing Parkinson's disease (PD) in a northern Chinese Han community.

METHODS

In this case-control study, we recruited 821 participants, including 411 patients with sporadic PD and 410 independent, healthy controls. A Polymerase Chain Reaction-Restriction Fragment Length Polymorphism genotyping assay was used to identify polymorphisms of the three selected single nucleotide polymorphisms (rs3764650, rs4147929, and rs3752246) of the ABCA7 gene. Sanger sequencing was further applied to identify the accuracy of the genotyping results. The chi-square test was used to compare the frequencies of alleles and genotypes in patients and controls. Odds ratios and 95% confidence intervals were calculated using logistic regression.

RESULTS

We found significant between-group differences in the alleles (A vs. G, nominal P = 0.014) and dominant models (AA + GA vs. GG, nominal P = 0.015) of rs4147929. Subgroup analysis showed that the frequency of the rs4147929 A allele in male patients with PD was significantly higher than that in male controls (nominal P = 0.036). For the rs3752246 polymorphism, the frequency of the G allele was significantly higher in patients with PD than in controls, and the dominant model fit the data best when considering the nominal P-values (nominal P = 0.019, nominal P = 0.033, respectively). Differences in G allele and genotypes frequencies between patients and controls remained significant in women (nominal P = 0.032 for allele, nominal P = 0.015 for genotype), as well as in individuals aged more than 50 years (nominal P = 0.044, nominal P = 0.020, respectively). No significant differences were observed in allele or genotype frequencies between patients with PD and healthy controls for rs3764650. The frequency of the TCG (rs3764650-rs3752246-rs4147929) haplotype was significantly lower in the PD group than in the healthy control group (odds ratio = 0.772; 95% confidence interval = 0.634-0.940; P = 0.011).

CONCLUSION

The rs4147929 polymorphism was significantly associated with PD susceptibility in the northern Chinese Han population. The A allele of rs4147929 was a risk factor for developing PD. The TCG haplotype presented a protective role in the pathogenesis of PD. Further studies using larger sample sizes, considering different clinical and biochemical parameters such as the cognitive status of subjects at the same time, are warranted to better clarify the effects of these common variants on the pathogenesis and development of PD.

Neural correlates of orbital telorism

Orbital telorism, the interocular distance, is clinically informative and in extremes is considered a minor physical anomaly. While its extremes, hypo- and hypertelorism, have been linked to disorders often related to cognitive ability, little is known about the neural correlates of normal variation of telorism within the general population. We derived measures of orbital telorism from cranial magnetic resonance imaging (MRI) by calculating the distance between the eyeball center of gravity in two population-based datasets (N = 5,653, N = 29,824; mean age 64.66, 63.75 years). This measure was found to be related to grey matter tissue density within numerous regions of the brain, including, but surprisingly not limited to, the frontal regions, in both positive and negative directions. Additionally, telorism was related to several cognitive functions, such as Purdue pegboard test (Beta, P-value (CI95%) -.02, 1.63 × 10^-7 (-.03:-.01)) and fluid intelligence (.02, 4.75 × 10^-6 (.01:0.02)), with some relationships driven by individuals with a smaller orbital telorism. This is reflective of the higher prevalence of hypotelorism in developmental disorders, specifically those that accompany lower cognitive lower functioning. This study suggests, despite previous links only made in clinical extremes, that orbital telorism holds some relation to structural brain development and cognitive function in the general population. This relationship is likely driven by shared developmental periods.

Imaging Transcriptomics of Brain Disorders

Noninvasive neuroimaging is a powerful tool for quantifying diverse aspects of brain structure and function in vivo, and it has been used extensively to map the neural changes associated with various brain disorders. However, most neuroimaging techniques offer only indirect measures of underlying pathological mechanisms. The recent development of anatomically comprehensive gene expression atlases has opened new opportunities for studying the transcriptional correlates of noninvasively measured neural phenotypes, offering a rich framework for evaluating pathophysiological hypotheses and putative mechanisms. Here, we provide an overview of some fundamental methods in imaging transcriptomics and outline their application to understanding brain disorders of neurodevelopment, adulthood, and neurodegeneration. Converging evidence indicates that spatial variations in gene expression are linked to normative changes in brain structure during age-related maturation and neurodegeneration that are in part associated with cell-specific gene expression markers of gene expression. Transcriptional correlates of disorder-related neuroimaging phenotypes are also linked to transcriptionally dysregulated genes identified in ex vivo analyses of patient brains. Modeling studies demonstrate that spatial patterns of gene expression are involved in regional vulnerability to neurodegeneration and the spread of disease across the brain. This growing body of work supports the utility of transcriptional atlases in testing hypotheses about the molecular mechanism driving disease-related changes in macroscopic neuroimaging phenotypes.

Detecting genetic associations with brain imaging phenotypes in Alzheimer's disease via a novel structured KCCA approach

Neuroimaging genetics has become an important research topic since it can reveal complex associations between genetic variants (i.e. single nucleotide polymorphisms (SNPs) and the structures or functions of the human brain. However, existing kernel mapping is difficult to directly use the sparse representation method in the kernel feature space, which makes it difficult for most existing sparse canonical correlation analysis (SCCA) methods to be directly promoted in the kernel feature space. To bridge this gap, we adopt a novel alternating projected gradient approach, gradient KCCA (gradKCCA) model to develop a powerful model for exploring the intrinsic associations among genetic markers, imaging quantitative traits (QTs) of interest. Specifically, this model solves kernel canonical correlation (KCCA) with an additional constraint that projection directions have pre-images in the original data space, a sparsity-inducing variant of the model is achieved through controlling the [Formula: see text]-norm of the preimages of the projection directions. We evaluate this model using Alzheimer's disease Neuroimaging Initiative (ADNI) cohort to discover the relationships among SNPs from Alzheimer's disease (AD) risk gene APOE, imaging QTs extracted from structural magnetic resonance imaging (MRI) scans. Our results show that the algorithm not only outperforms the traditional KCCA method in terms of Root Mean Square Error (RMSE) and Correlation Coefficient (CC) but also identify the meaningful and relevant biomarkers of SNPs (e.g. rs157594 and rs405697), which are positively related to right Postcentral and right SupraMarginal brain regions in this study. Empirical results indicate its promising capability in revealing biologically meaningful neuroimaging genetics associations and improving the disease-related mechanistic understanding of AD.

Plasma lipids are associated with white matter microstructural changes and axonal degeneration

Dislipidemia is a risk factor for cognitive impairment. We studied the association between interindividual variability of plasma lipids and white matter (WM) microstructure, using diffusion tensor imaging (DTI) in 273 healthy adults. Special focus was placed on 7 regions of interest (ROI) which are structural components of cognitive neurocircuitry. We also investigated the effect of plasma lipids on cerebrospinal fluid (CSF) neurofilament light chain (NfL), an axonal degeneration marker. Low density lipoprotein (LDL) and triglyceride (TG) levels showed a negative association with axial diffusivity (AxD) in multiple regions. High density lipoproteins (HDL) showed a positive correlation. The association was independent of Apolipoprotein E (APOE) genotype, blood pressure or use of statins. LDL moderated the relation between NfL and AxD in the body of the corpus callosum (p = 0.041), right cingulum gyrus (p = 0.041), right fornix/stria terminalis (p = 0.025) and right superior longitudinal fasciculus (p = 0.020) and TG in the right inferior longitudinal fasciculus (p = 0.004) and left fornix/stria terminalis (p = 0.001). We conclude that plasma lipids are associated to WM microstructural changes and axonal degeneration and might represent a risk factor in the transition from healthy aging to disease.

Role of ABCA7 in Human Health and in Alzheimer's Disease

Several studies, including genome wide association studies (GWAS), have strongly suggested a central role for the ATP-binding cassette transporter subfamily A member 7 (ABCA7) in Alzheimer’s disease (AD). This ABC transporter is now considered as an important genetic determinant for late onset Alzheimer disease (LOAD) by regulating several molecular processes such as cholesterol metabolism and amyloid processing and clearance. In this review we shed light on these new functions and their cross-talk, explaining its implication in brain functioning, and therefore in AD onset and development.

Associations of Alzheimer's disease risk variants with gene expression, amyloidosis, tauopathy, and neurodegeneration

BACKGROUND

Genome-wide association studies have identified more than 30 Alzheimer's disease (AD) risk genes, although the detailed mechanism through which all these genes are associated with AD pathogenesis remains unknown. We comprehensively evaluate the roles of the variants in top 30 non-APOE AD risk genes, based on whether these variants were associated with altered mRNA transcript levels, as well as brain amyloidosis, tauopathy, and neurodegeneration.

METHODS

Human brain gene expression data were obtained from the UK Brain Expression Consortium (UKBEC), while other data used in our study were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. We examined the association of AD risk allele carrier status with the levels of gene expression in blood and brain regions and tested the association with brain amyloidosis, tauopathy, and neurodegeneration at baseline, using a multivariable linear regression model. Next, we analyzed the longitudinal effects of these variants on the change rates of pathology using a mixed effect model.

RESULTS

Altogether, 27 variants were detected to be associated with the altered expression of 21 nearby genes in blood and brain regions. Eleven variants (especially novel variants in ADAM10, IGHV1-68, and SLC24A4/RIN3) were associated with brain amyloidosis, 7 variants (especially in INPP5D, PTK2B) with brain tauopathy, and 8 variants (especially in ECHDC3, HS3ST1) with brain neurodegeneration. Variants in ADAMTS1, BZRAP1-AS1, CELF1, CD2AP, and SLC24A4/RIN3 participated in more than one cerebral pathological process.

CONCLUSIONS

Genetic variants might play functional roles and suggest potential mechanisms in AD pathogenesis, which opens doors to uncover novel targets for AD treatment.

CDH6 and HAGH protein levels in plasma associate with Alzheimer's disease in APOE ε4 carriers

Many Alzheimer’s disease (AD) genes including Apolipoprotein E (APOE) are found to be expressed in blood-derived macrophages and thus may alter blood protein levels. We measured 91 neuro-proteins in plasma from 316 participants of the Rotterdam Study (incident AD = 161) using Proximity Extension Ligation assay. We studied the association of plasma proteins with AD in the overall sample and stratified by APOE. Findings from the Rotterdam study were replicated in 186 AD patients of the BioFINDER study. We further evaluated the correlation of these protein biomarkers with total tau (t-tau), phosphorylated tau (p-tau) and amyloid-beta (Aβ) 42 levels in cerebrospinal fluid (CSF) in the Amsterdam Dementia Cohort (N = 441). Finally, we conducted a genome-wide association study (GWAS) to identify the genetic variants determining the blood levels of AD-associated proteins. Plasma levels of the proteins, CDH6 (β = 0.638, P = 3.33 × 10⁻⁴) and HAGH (β = 0.481, P = 7.20 × 10⁻⁴), were significantly elevated in APOE ε4 carrier AD patients. The findings in the Rotterdam Study were replicated in the BioFINDER study for both CDH6 (β = 1.365, P = 3.97 × 10⁻³) and HAGH proteins (β = 0.506, P = 9.31 × 10⁻⁷) when comparing cases and controls in APOE ε4 carriers. In the CSF, CDH6 levels were positively correlated with t-tau and p-tau in the total sample as well as in APOE ε4 stratum (P < 1 × 10⁻³). The HAGH protein was not detected in CSF. GWAS of plasma CDH6 protein levels showed significant association with a cis-regulatory locus (rs111283466, P = 1.92 × 10⁻⁹). CDH6 protein is implicated in cell adhesion and synaptogenesis while HAGH protein is related to the oxidative stress pathway. Our findings suggest that these pathways may be altered during presymptomatic AD and that CDH6 and HAGH may be new blood-based biomarkers.

Full exploitation of high dimensionality in brain imaging: The JPND working group statement and findings

Advances in technology enable increasing amounts of data collection from individuals for biomedical research. Such technologies, for example, in genetics and medical imaging, have also led to important scientific discoveries about health and disease. The combination of multiple types of high-throughput data for complex analyses, however, has been limited by analytical and logistic resources to handle high-dimensional data sets. In our previous EU Joint Programme-Neurodegenerative Disease Research (JPND) Working Group, called HD-READY, we developed methods that allowed successful combination of omics data with neuroimaging. Still, several issues remained to fully leverage high-dimensional multimodality data. For instance, high-dimensional features, such as voxels and vertices, which are common in neuroimaging, remain difficult to harmonize. In this Full-HD Working Group, we focused on such harmonization of high-dimensional neuroimaging phenotypes in combination with other omics data and how to make the resulting ultra-high-dimensional data easily accessible in neurodegeneration research.

ABCA7 and EphA1 Genes Polymorphisms in Late-Onset Alzheimer's Disease

Large-scale genome-wide studies have revealed the role of several genes and their respective single-nucleotide polymorphisms (SNPs) in the pathophysiology of late-onset Alzheimer's disease (LOAD). Here, the frequencies of ABCA7 SNPs rs3764650 and rs4147929 and EphA1 SNP rs11771145 were assessed and compared in LOAD patients and healthy subjects. In a case-control study, 110 patients with LOAD (case) and 88 healthy unrelated age- and gender-matched individuals (control), both from Azeri descent, were enrolled. DNA was extracted from blood samples using the salting out method, and the genotyping was performed by RFLP-PCR for rs3764650, rs4147929, and rs11771145 polymorphisms. Electrophoresis was carried out on agarose gel. Sequencing was utilized for confirmation of the results. No differences were found in the frequencies of ABCA7 SNP rs3764650 and EphA1 SNP rs11771145 between healthy subjects and LOAD patients. However, a significant difference was revealed in the frequencies of AA (p = 0.042, OR = 0.150; 95%CI = 0.005-1.410) and GG (p = 0.009, OR = 1.716; 95%CI = 0.918-3.218) genotypes of ABCA7 SNP rs4147929 between the mentioned groups. This study showed that ABCA7 SNP rs4147929 might be a predisposing factor for LOAD. However, such an association was not found between ABCA7 SNP rs3764650 as well as EphA1 SNP rs11771145 and LOAD. These results must be confirmed in other ethnic groups.

Gray Matter Age Prediction as a Biomarker for Risk of Dementia

The gap between predicted brain age using magnetic resonance imaging (MRI) and chronological age may serve as a biomarker for early-stage neurodegeneration. However, owing to the lack of large longitudinal studies, it has been challenging to validate this link. We aimed to investigate the utility of such a gap as a risk biomarker for incident dementia using a deep learning approach for predicting brain age based on MRI-derived gray matter (GM). We built a convolutional neural network (CNN) model to predict brain age trained on 3,688 dementia-free participants of the Rotterdam Study (mean age 66 ± 11 y, 55% women). Logistic regressions and Cox proportional hazards were used to assess the association of the age gap with incident dementia, adjusted for age, sex, intracranial volume, GM volume, hippocampal volume, white matter hyperintensities, years of education, and APOE ε4 allele carriership. Additionally, we computed the attention maps, which shows which regions are important for age prediction. Logistic regression and Cox proportional hazard models showed that the age gap was significantly related to incident dementia (odds ratio [OR] = 1.11 and 95% confidence intervals [CI] = 1.05-1.16; hazard ratio [HR] = 1.11, and 95% CI = 1.06-1.15, respectively). Attention maps indicated that GM density around the amygdala and hippocampi primarily drove the age estimation. We showed that the gap between predicted and chronological brain age is a biomarker, complimentary to those that are known, associated with risk of dementia, and could possibly be used for early-stage dementia risk screening.

The role of ABCA7 in Alzheimer's disease: evidence from genomics, transcriptomics and methylomics

Genome-wide association studies (GWAS) originally identified ATP-binding cassette, sub-family A, member 7 (ABCA7), as a novel risk gene of Alzheimer’s disease (AD). Since then, accumulating evidence from in vitro, in vivo, and human-based studies has corroborated and extended this association, promoting ABCA7 as one of the most important risk genes of both early-onset and late-onset AD, harboring both common and rare risk variants with relatively large effect on AD risk. Within this review, we provide a comprehensive assessment of the literature on ABCA7, with a focus on AD-related human -omics studies (e.g. genomics, transcriptomics, and methylomics). In European and African American populations, indirect ABCA7 GWAS associations are explained by expansion of an ABCA7 variable number tandem repeat (VNTR), and a common premature termination codon (PTC) variant, respectively. Rare ABCA7 PTC variants are strongly enriched in AD patients, and some of these have displayed inheritance patterns resembling autosomal dominant AD. In addition, rare missense variants are more frequent in AD patients than healthy controls, whereas a common ABCA7 missense variant may protect from disease. Methylation at several CpG sites in the ABCA7 locus is significantly associated with AD. Furthermore, ABCA7 contains many different isoforms and ABCA7 splicing has been shown to associate with AD. Besides associations with disease status, these genetic and epigenetic ABCA7 markers also showed significant correlations with AD endophenotypes; in particular amyloid deposition and brain morphology. In conclusion, human-based –omics studies provide converging evidence of (partial) ABCA7 loss as an AD pathomechanism, and future studies should make clear if interventions on ABCA7 expression can serve as a valuable therapeutic target for AD.

High-Dimensional Mapping of Cognition to the Brain Using Voxel-Based Morphometry and Subcortical Shape Analysis

BACKGROUND

It is increasingly recognized that the complex functions of human cognition are not accurately represented by arbitrarily-defined anatomical brain regions. Given the considerable functional specialization within such regions, more fine-grained studies of brain structure could capture such localized associations. However, such analyses/studies in a large community-dwelling population are lacking.

OBJECTIVE

To perform a fine-mapping of cognitive ability to cortical and subcortical grey matter on magnetic resonance imaging (MRI).

METHODS

In 3,813 stroke-free and non-demented persons from the Rotterdam Study (mean age 69.1 (±8.8) years; 55.8% women) with cognitive assessments and brain MRI, we performed voxel-based morphometry and subcortical shape analysis on global cognition and separate tests that tapped into memory, information processing speed, fine motor speed, and executive function domains.

RESULTS

We found that the different cognitive tests significantly associated with grey matter density in differential but also overlapping brain regions, primarily in the left hemisphere. Clusters of significantly associated voxels with global cognition were located within multiple anatomic regions: left amygdala, hippocampus, parietal lobule, superior temporal gyrus, insula and posterior temporal lobe. Subcortical shape analysis revealed associations primarily within the head and tail of the caudate nucleus, putamen, ventral part of the thalamus, and nucleus accumbens, more equally distributed among the left and right hemisphere. Within the caudate nucleus both positive (head) as well as negative (tail) associations were observed with global cognition.

CONCLUSIONS

In a large population-based sample, we mapped cognitive performance to cortical and subcortical grey matter density using a hypothesis-free approach with high-dimensional neuroimaging. Leveraging the power of our large sample size, we confirmed well-known associations as well as identified novel brain regions related to cognition.

DNA methylation analysis on purified neurons and glia dissects age and Alzheimer's disease-specific changes in the human cortex

Background

Epigenome-wide association studies (EWAS) based on human brain samples allow a deep and direct understanding of epigenetic dysregulation in Alzheimer’s disease (AD). However, strong variation of cell-type proportions across brain tissue samples represents a significant source of data noise. Here, we report the first EWAS based on sorted neuronal and non-neuronal (mostly glia) nuclei from postmortem human brain tissues.

Results

We show that cell sorting strongly enhances the robust detection of disease-related DNA methylation changes even in a relatively small cohort. We identify numerous genes with cell-type-specific methylation signatures and document differential methylation dynamics associated with aging specifically in neurons such as CLU, SYNJ2 and NCOR2 or in glia RAI1,CXXC5 and INPP5A. Further, we found neuron or glia-specific associations with AD Braak stage progression at genes such as MCF2L, ANK1, MAP2, LRRC8B, STK32C and S100B. A comparison of our study with previous tissue-based EWAS validates multiple AD-associated DNA methylation signals and additionally specifies their origin to neuron, e.g., HOXA3 or glia (ANK1). In a meta-analysis, we reveal two novel previously unrecognized methylation changes at the key AD risk genes APP and ADAM17.

Conclusions

Our data highlight the complex interplay between disease, age and cell-type-specific methylation changes in AD risk genes thus offering new perspectives for the validation and interpretation of large EWAS results.

Electronic supplementary material

The online version of this article (10.1186/s13072-018-0211-3) contains supplementary material, which is available to authorized users.

Thinner retinal layers are associated with changes in the visual pathway: A population-based study

Increasing evidence shows that thinner retinal nerve fiber layer (RNFL) and ganglion cell layer (GCL), assessed on optical coherence tomography (OCT), are reflecting global brain atrophy. Yet, little is known on the relation of these layers with specific brain regions. Using voxel-based analysis, we aimed to unravel specific brain regions associated with these retinal layers. We included 2,235 persons (mean age: 67.3 years, 55% women) from the Rotterdam Study (2007-2012) who had gradable retinal OCT images and brain magnetic resonance imaging (MRI) scans, including diffusion tensor (DT) imaging. Thicknesses of peripapillary RNFL and perimacular GCL were measured using an automated segmentation algorithm. Voxel-based morphometry protocols were applied to process DT-MRI data. We investigated the association between retinal layer thickness with voxel-wise gray matter density and white matter microstructure by performing linear regression models. We found that thinner RNFL and GCL were associated with lower gray matter density in the visual cortex, and with lower fractional anisotropy and higher mean diffusivity in white matter tracts that are part of the optic radiation. Furthermore, thinner GCL was associated with lower gray matter density of the thalamus. Thinner RNFL and GCL are associated with gray and white matter changes in the visual pathway suggesting that retinal thinning on OCT may be specifically associated with changes in the visual pathway rather than with changes in the global brain. These findings may serve as a basis for understanding visual symptoms in elderly patients, patients with Alzheimer's disease, or patients with posterior cortical atrophy.

MEF2C mRNA expression and cognitive function in Japanese patients with Alzheimer's disease

AIM

Despite continuing research into Alzheimer's disease (AD), its pathological mechanisms and modulating factors remain unknown. Several genes influence AD pathogenesis by affecting inflammatory pathways. Myocyte-enhancer factor 2C (MEF2C) is one such candidate gene for AD.

METHODS

We examined MEF2C mRNA expression levels and methylation rates of CpG on its promoter region in peripheral leukocytes from Japanese AD patients compared with age- and sex-matched control subjects.

RESULTS

In peripheral leukocytes, MEF2C mRNA expression levels in AD subjects were significantly lower than those in control subjects (0.86 ± 0.25 vs 0.99 ± 0.27, respectively, P = 0.007) and were correlated with the Alzheimer's Disease Assessment Scale (r = -0.345, P = 0.049) and the Mini Mental State Examination (r = 0.324, P = 0.02). No significant differences were found in methylation rates between AD and control subjects.

CONCLUSION

MEF2C mRNA expression in leukocytes may be a biological marker for cognitive decline in AD.

A specific pattern of gray matter atrophy in Alzheimer's disease with depression

Considering the high incidence of depressive symptoms in Alzheimer's disease (AD), we conducted a large-sample study to investigate the pattern of gray matter (GM) abnormalities that differentiates depressive from non-depressive AD patients. We included 201 AD patients who underwent MRI assessment and categorized them into depressive and non-depressive subgroups based on the Geriatric Depression Scale (GDS; cut-off score: ≤9). We performed whole-brain voxel-based morphometry analysis in 173 patients after MRI quality control and used between-group comparisons and regression analysis models to analyze the volumetric data controlling for nuisance variables. Depressive AD patients had extensive GM volume loss mainly in the paracentral region, specifically in post- and pre-central gyrus, supplementary motor areas and thalamus compared to non-depressive patients. Similar findings were obtained for the group of 173 patients using regression analysis and GDS score as predictor variable. We provided the first clear demonstration of a unique pattern of GM atrophy that characterizes AD patients with depression which is consistent with regions implicated in the phenomenon of psychomotor retardation that characterizes depression.

Gray matter heritability in family-based and population-based studies using voxel-based morphometry

BACKGROUND

The combination of genetics and imaging has improved their understanding of the brain through studies of aggregate measures obtained from high-resolution structural imaging. Voxel-wise analyses have the potential to provide more detailed information of genetic influences on the brain. Here they report a large-scale study of the heritability of gray matter at voxel resolution (1 × 1 × 1 mm).

METHODS

Validated voxel-based morphometry (VBM) protocols were applied to process magnetic resonance imaging data of 3,239 unrelated subjects from a population-based study and 491 subjects from two family-based studies. Genome-wide genetic data was used to estimate voxel-wise gray matter heritability of the unrelated subjects and pedigree-structure was used to estimate heritability in families. They subsequently associated two genetic variants, known to be linked with subcortical brain volume, with most heritable voxels to determine if this would enhance their association signals.

RESULTS

Voxels significantly heritable in both estimates mapped to subcortical structures, but also voxels in the language areas of the left hemisphere were found significantly heritable. When comparing regional patterns of heritability, family-based estimates were higher than population-based estimates. However, regional consistency of the heritability measures across study designs was high (Pearson's correlation coefficient = 0.73, P = 2.6 × 10^-13 ). They further show enhancement of the association signal of two previously discovered genetic loci with subcortical volume by using only the most heritable voxels.

CONCLUSION

Gray matter voxel-wise heritability can be reliably estimated with different methods. Combining heritability estimates from multiple studies is feasible to construct reliable heritability maps of gray matter voxels. Hum Brain Mapp 38:2408-2423, 2017. © 2017 Wiley Periodicals, Inc.