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Total hippocampal volume has been consistently linked to cognitive function and dementia. Yet, given its complex and parcellated internal structure, the role of subregions of the hippocampus in cognition and risk of dementia remains relatively underexplored. We studied subregions of the hippocampus in a large population-based cohort to further understand their role in cognitive impairment and dementia risk. We studied 5035 dementia- and stroke-free persons from the Rotterdam Study, aged over 45 years. All participants underwent magnetic resonance imaging (1.5 T) between 2005 and 2015. Automatic segmentation of the hippocampus and 12 of its subregions was performed using the FreeSurfer software (version 6.0). A cognitive test battery was performed, and participants were followed up for the development of dementia until 2015. Associations of hippocampal subregion volumes with cognition and incident dementia were examined using linear and Cox regression models, respectively. All analyses were adjusted for age, sex, education, and total hippocampal volume. Mean age was 64.3 years (SD 10.6) with 56% women. Smaller volumes of the hippocampal fimbria, presubiculum and subiculum showed the strongest associations with poor performance on several cognitive domains, including executive function but not memory. During a mean follow-up of 5.5 years, 76 persons developed dementia. Smaller subiculum volume was associated with risk of dementia adjusted for total volume (hazard ratio per SD decrease in volume: 1.75, 95% confidence interval 1.35; 2.26). In a community-dwelling non-demented population, we describe patterns of association between hippocampal subregions with cognition and risk of dementia. Specifically, the subiculum was associated with both poorer cognition and higher risk of dementia. •Hippocampal subregions were related to many cognitive domains.•The subiculum and pre-subiculum displayed strong relations to executive dysfunction.•Smaller subiculum volume was associated to risk of incident dementia.•The subiculum relation to dementia risk remained stable over the follow-up period.

Background Vascular dementia is a common disorder resulting in considerable morbidity and mortality. Determining the extent to which genes play a role in disease susceptibility and their pathophysiological mechanisms could improve our understanding of vascular dementia, leading to a potential translation of this knowledge to clinical practice. Discussion In this review, we discuss what is currently known about the genetics of vascular dementia. The identification of causal genes remains limited to monogenic forms of the disease, with findings for sporadic vascular dementia being less robust. However, progress in genetic research on associated phenotypes, such as cerebral small vessel disease, Alzheimer’s disease, and stroke, have the potential to inform on the genetics of vascular dementia. We conclude by providing an overview of future developments in the field and how such work could impact patients and clinicians. Conclusion The genetic background of vascular dementia is well established for monogenic disorders, but remains relatively obscure for the sporadic form. More work is needed for providing robust findings that might eventually lead to clinical translation.

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.

Background: Epigenetic biomarkers, particularly CpG methylation, are increasingly employed in clinical and forensic settings. However, we still lack a cost-effective, sensitive, medium-scale method for the analysis of hundreds to thousands of user-defined CpGs suitable for minute DNA input amounts (<10 ng). In this study, motivated by promising results in the genetics field, we investigated single-molecule molecular inversion probes (smMIPs) for simultaneous analysis of hundreds of CpGs by using an example set of 514 age-associated CpGs (Zhang model). Methods: First, we developed a novel smMIP design tool to suit bisulfite-converted DNA (Locksmith). Then, to optimize the capture process, we performed single-probe capture for ten selected, representative smMIPs. Based on this pilot, the full smMIP panel was tested under varying capture conditions, including hybridization and elongation temperature, smMIP and template DNA amounts, dNTP concentration and elongation time. Results: Overall, we found that the capture efficiency was highly probe-(and hence, sequence-) dependent, with a heterogeneous coverage distribution across CpGs higher than the 1000-fold range. Considering CpGs with at least 20X coverage, we yielded robust methylation detection with levels comparable to those obtained from the gold standard EPIC microarray analysis (Pearsons’s r: 0.96). Conclusions: The observed low specificity and uniformity indicate that smMIPs in their current form are not compatible with the lowered complexity of bisulfite-converted DNA.

Abstract Introduction Virchow-Robin spaces (VRS), or perivascular spaces, are compartments of interstitial fluid enclosing cerebral blood vessels and are potential imaging markers of various underlying brain pathologies. Despite a growing interest in the study of enlarged VRS, the heterogeneity in rating and quantification methods combined with small sample sizes have so far hampered advancement in the field. Methods The Uniform Neuro-Imaging of Virchow-Robin Spaces Enlargement (UNIVRSE) consortium was established with primary aims to harmonize rating and analysis ( www.uconsortium.org ). The UNIVRSE consortium brings together 13sub cohorts from five countries, totaling 16,000 subjects and over 25,000 scans. Eight different magnetic resonance imaging protocols were used in the consortium. Results VRS rating was harmonized using a validated protocol that was developed by the two founding members, with high reliability independent of scanner type, rater experience, or concomitant brain pathology. Initial analyses revealed risk factors for enlarged VRS including increased age, sex, high blood pressure, brain infarcts, and white matter lesions, but this varied by brain region. Discussion Early collaborative efforts between cohort studies with respect to data harmonization and joint analyses can advance the field of population (neuro)imaging. The UNIVRSE consortium will focus efforts on other potential correlates of enlarged VRS, including genetics, cognition, stroke, and 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.

Background Commissural tracts are the white matter fibre bundles intercommunicating left and right brain hemispheres. They integrate many cognitive functions such as memory, verbal processing, motor and perceptual skills. Also, commissures connect specific layers of cortical neurons that are also lost in Alzheimer’s disease (AD) and other neurodegenerative disorders. Although highly heritable, commissures´ specific genetic determinants remain obscure. We aim to investigate the genetic determinants of the human anterior commissure. Given its presumed role in neurodegeneration, we aim to further provide mechanistic insights into neurological conditions that may result from its dysfunction. Method Two‐stage genome‐wide association study, (GWAS) (N=18,828) of the size of the anterior commissure. The discovery sample included seven cohorts (N=7,935) and was meta‐analyzed with ten replication cohorts (N=10,893). The size of the anterior commissure was manually derived from magnetic resonance imaging (1.5T/3T) with at least T1/T2‐weighted sequences. The genetic data was assessed through genotyping using SNP microarrays. We used voxel‐based morphometry to determine which regions are connected by the anterior commissure. To prove a functional validation of the identified variants, we performed a series of in silico experiments, including the study of the spatial expression patterns in human brains, quantitative trait loci (QTL), enrichment analysis and pleiotropy with neurodegenerative diseases. Result we identified six independent variants at four loci (p‐values from 4.1x10‐8 to 9.4x10‐22). We mapped the loci to probable causal genes involved in axon guidance (EPHA3 and SEMA6A), cognitive disorders (CTNND2), and growth factor signaling (RIT2). Voxel‐based morphometry revealed distinct associations of the variants with connected grey matter regions in the brain. We found enrichment for H3K4me1 peaks (marking enhancer sites), introns, and conserved sequences, as well as cell‐type‐specific annotations from the central nervous system and cardiovascular system. Furthermore, we identified pleiotropy between genes known to increase risk of neurodegenerative conditions including frontotemporal lobar degeneration gene TMEM106B. Variants associated to this gene have been related to dementia development. Conclusion these results shed light on the genetic architecture of commissural tracts and establish the size of the anterior commissure as a relevant biomarker of neurodegeneration.

Background Commissural tracts are the white matter fibre bundles intercommunicating left and right brain hemispheres. They integrate many cognitive functions such as memory, verbal processing, motor and perceptual skills. Also, commissures connect specific layers of cortical neurons that are also lost in Alzheimer’s disease (AD) and other neurodegenerative disorders. Although highly heritable, commissures´ specific genetic determinants remain obscure. We aim to investigate the genetic determinants of the human anterior commissure. Given its presumed role in neurodegeneration, we aim to further provide mechanistic insights into neurological conditions that may result from its dysfunction. Method Two‐stage genome‐wide association study, (GWAS) (N=18,828) of the size of the anterior commissure. The discovery sample included seven cohorts (N=7,935) and was meta‐analyzed with ten replication cohorts (N=10,893). The size of the anterior commissure was manually derived from magnetic resonance imaging (1.5T/3T) with at least T1/T2‐weighted sequences. The genetic data was assessed through genotyping using SNP microarrays. We used voxel‐based morphometry to determine which regions are connected by the anterior commissure. To prove a functional validation of the identified variants, we performed a series of in silico experiments, including the study of the spatial expression patterns in human brains, quantitative trait loci (QTL), enrichment analysis and pleiotropy with neurodegenerative diseases. Result we identified six independent variants at four loci (p‐values from 4.1x10‐8 to 9.4x10‐22). We mapped the loci to probable causal genes involved in axon guidance (EPHA3 and SEMA6A), cognitive disorders (CTNND2), and growth factor signaling (RIT2). Voxel‐based morphometry revealed distinct associations of the variants with connected grey matter regions in the brain. We found enrichment for H3K4me1 peaks (marking enhancer sites), introns, and conserved sequences, as well as cell‐type‐specific annotations from the central nervous system and cardiovascular system. Furthermore, we identified pleiotropy between genes known to increase risk of neurodegenerative conditions including frontotemporal lobar degeneration gene TMEM106B. Variants associated to this gene have been related to dementia development. Conclusion these results shed light on the genetic architecture of commissural tracts and establish the size of the anterior commissure as a relevant biomarker of neurodegeneration.

Background It is estimated that at least two‐thirds of the world lacks access to neuroimaging, including Magnetic Resonance Imaging (MRI). Yet neuroimaging is one of the most informative tools for neuroscience, potentially biasing advances toward populations with access to this technology. This is evident in Alzheimer’s disease (AD) research, where genetics and environment play important roles in disease development and treatment. Recent advances in low field MRI (LFMRI) have demonstrated the utility of this affordable and portable technology, despite lower image quality. Of the existing technologies, the OSII ONE developed by the open‐source imaging initiative is the only device that has been reproduced in low resource settings using primarily local resources. Here we highlight two pilot studies in Uganda and Paraguay to build and sustain OSII ONE devices for neuroimaging studies. We present preliminary results regarding construction, sustainability, and image processing for use in AD and offer suggestions for its inclusion as a tool to increase access to neuroimaging in low‐resource populations. Method An OSII ONE system was reproduced in Uganda and Paraguay. In Uganda, all system components were importanted and local human resource guided by international experts was used to complete the build. In Paraguay, only key physical components not available locally were imported and all available local components (including exclusively local human resources) were used for construction. Result While the Uganda build was completed more quickly (11 days in Uganda, 6 months in Paraguay), quality was maintained across sites despite difference in personnel and the use of local components in Paraguay. Both projects are maintained locally and current image processing methods could provide adequate quality for brain analysis in AD. Conclusion We show the feasibility LFMRI in lower resource settings. Despite the reduction in image quality, valuable structural information can be obtained, extending access to rural populations. This has significant implications for the future of AD imaging in global settings especially considering recent approval of disease modifying therapies that require safety monitoring with MRI. Future work collecting paired LFMRI and conventional MRI with AD patients in South America will further demonstrate the utility of this technology in the field.

The authors identified a protective genetic allele associated with lower PU.1 ( SPI1 ) expression in myeloid cells by conducting a genome-wide scan of Alzheimer's disease (AD). PU.1 binds the promoters of AD-associated genes (e.g., CD33 , MS4A4A & MS4A6A , TYROBP ) and modulates their expression, suggesting it may reduce AD risk by regulating myeloid cell gene expression. A genome-wide survival analysis of 14,406 Alzheimer's disease (AD) cases and 25,849 controls identified eight previously reported AD risk loci and 14 novel loci associated with age at onset. Linkage disequilibrium score regression of 220 cell types implicated the regulation of myeloid gene expression in AD risk. The minor allele of rs1057233 (G), within the previously reported CELF1 AD risk locus, showed association with delayed AD onset and lower expression of SPI1 in monocytes and macrophages. SPI1 encodes PU.1, a transcription factor critical for myeloid cell development and function. AD heritability was enriched within the PU.1 cistrome, implicating a myeloid PU.1 target gene network in AD. Finally, experimentally altered PU.1 levels affected the expression of mouse orthologs of many AD risk genes and the phagocytic activity of mouse microglial cells. Our results suggest that lower SPI1 expression reduces AD risk by regulating myeloid gene expression and cell function.