Diffusion imaging genomics provides novel insight into early mechanisms of cerebral small vessel disease.

Cerebral small vessel disease (cSVD) is a leading cause of stroke and dementia. Genetic risk loci for white matter hyperintensities (WMH), the most common MRI-marker of cSVD in older age, were recently shown to be significantly associated with white matter (WM) microstructure on diffusion tensor imaging (signal-based) in young adults. To provide new insights into these early changes in WM microstructure and their relation with cSVD, we sought to explore the genetic underpinnings of cutting-edge tissue-based diffusion imaging markers across the adult lifespan. We conducted a genome-wide association study of neurite orientation dispersion and density imaging (NODDI) markers in young adults (i-Share study: N = 1 758, (mean[range]) 22.1[18-35] years), with follow-up in young middle-aged (Rhineland Study: N = 714, 35.2[30-40] years) and late middle-aged to older individuals (UK Biobank: N = 33 224, 64.3[45-82] years). We identified 21 loci associated with NODDI markers across brain regions in young adults. The most robust association, replicated in both follow-up cohorts, was with Neurite Density Index (NDI) at chr5q14.3, a known WMH locus in VCAN. Two additional loci were replicated in UK Biobank, at chr17q21.2 with NDI, and chr19q13.12 with Orientation Dispersion Index (ODI). Transcriptome-wide association studies showed associations of STAT3 expression in arterial and adipose tissue (chr17q21.2) with NDI, and of several genes at chr19q13.12 with ODI. Genetic susceptibility to larger WMH volume, but not to vascular risk factors, was significantly associated with decreased NDI in young adults, especially in regions known to harbor WMH in older age. Individually, seven of 25 known WMH risk loci were associated with NDI in young adults. In conclusion, we identified multiple novel genetic risk loci associated with NODDI markers, particularly NDI, in early adulthood. These point to possible early-life mechanisms underlying cSVD and to processes involving remyelination, neurodevelopment and neurodegeneration, with a potential for novel approaches to prevention.

Peripheral whole blood microRNA expression in relation to vascular function: a population-based study.

BACKGROUND: As key regulators of gene expression, microRNAs affect many cardiovascular mechanisms and have been associated with several cardiovascular diseases. In this study, we aimed to investigate the relation of whole blood microRNAs with several quantitative measurements of vascular function, and explore their biological role through an integrative microRNA-gene expression analysis. METHODS: Peripheral whole blood microRNA expression was assessed through RNA-Seq in 2606 participants (45.8% men, mean age: 53.93, age range: 30 to 95 years) from the Rhineland Study, an ongoing population-based cohort study in Bonn, Germany. Weighted gene co-expression network analysis was used to cluster microRNAs with highly correlated expression levels into 14 modules. Through linear regression models, we investigated the association between each module's expression and quantitative markers of vascular health, including pulse wave velocity, total arterial compliance index, cardiac index, stroke index, systemic vascular resistance index, reactive skin hyperemia and white matter hyperintensity burden. For each module associated with at least one trait, one or more hub-microRNAs driving the association were defined. Hub-microRNAs were further characterized through mapping to putative target genes followed by gene ontology pathway analysis. RESULTS: Four modules, represented by hub-microRNAs miR-320 family, miR-378 family, miR-3605-3p, miR-6747-3p, miR-6786-3p, and miR-330-5p, were associated with total arterial compliance index. Importantly, the miR-320 family module was also associated with white matter hyperintensity burden, an effect partially mediated through arterial compliance. Furthermore, hub-microRNA miR-192-5p was related to cardiac index. Functional analysis corroborated the relevance of the identified microRNAs for vascular function by revealing, among others, enrichment for pathways involved in blood vessel morphogenesis and development, angiogenesis, telomere organization and maintenance, and insulin secretion. CONCLUSIONS: We identified several microRNAs robustly associated with cardiovascular function, especially arterial compliance and cardiac output. Moreover, our results highlight miR-320 as a regulator of cerebrovascular damage, partly through modulation of vascular function. As many of these microRNAs were involved in biological processes related to vasculature development and aging, our results contribute to the understanding of vascular physiology and provide putative targets for cardiovascular disease prevention.

Rapid submillimeter QSM and R2* mapping using interleaved multishot 3D-EPI at 7 and 3 Tesla.

PURPOSE: To explore the high signal-to-noise ratio (SNR) efficiency of interleaved multishot 3D-EPI with standard image reconstruction for fast and robust high-resolution whole-brain quantitative susceptibility (QSM) and R 2 ∗ $$ {R}_2^{\ast } $$ mapping at 7 and 3T. METHODS: Single- and multi-TE segmented 3D-EPI is combined with conventional CAIPIRINHA undersampling for up to 72-fold effective gradient echo (GRE) imaging acceleration. Across multiple averages, scan parameters are varied (e.g., dual-polarity frequency-encoding) to additionally correct for B 0 $$ {\mathrm{B}}_0 $$ -induced artifacts, geometric distortions and motion retrospectively. A comparison to established GRE protocols is made. Resolutions range from 1.4 mm isotropic (1 multi-TE average in 36 s) up to 0.4 mm isotropic (2 single-TE averages in approximately 6 min) with whole-head coverage. RESULTS: Only 1-4 averages are needed for sufficient SNR with 3D-EPI, depending on resolution and field strength. Fast scanning and small voxels together with retrospective corrections result in substantially reduced image artifacts, which improves susceptibility and R 2 ∗ $$ {R}_2^{\ast } $$ mapping. Additionally, much finer details are obtained in susceptibility-weighted image projections through significantly reduced partial voluming. CONCLUSION: Using interleaved multishot 3D-EPI, single-TE and multi-TE data can readily be acquired 10 times faster than with conventional, accelerated GRE imaging. Even 0.4 mm isotropic whole-head QSM within 6 min becomes feasible at 7T. At 3T, motion-robust 0.8 mm isotropic whole-brain QSM and R 2 ∗ $$ {R}_2^{\ast } $$ mapping with no apparent distortion in less than 7 min becomes clinically feasible. Stronger gradient systems may allow for even higher effective acceleration rates through larger EPI factors while maintaining optimal contrast.

Epigenetic and integrative cross-omics analyses of cerebral white matter hyperintensities on MRI.

Cerebral white matter hyperintensities on MRI are markers of cerebral small vessel disease, a major risk factor for dementia and stroke. Despite the successful identification of multiple genetic variants associated with this highly heritable condition, its genetic architecture remains incompletely understood. More specifically, the role of DNA methylation has received little attention. We investigated the association between white matter hyperintensity burden and DNA methylation in blood at ∼450 000 cytosine-phosphate-guanine (CpG) sites in 9732 middle-aged to older adults from 14 community-based studies. Single CpG and region-based association analyses were carried out. Functional annotation and integrative cross-omics analyses were performed to identify novel genes underlying the relationship between DNA methylation and white matter hyperintensities. We identified 12 single CpG and 46 region-based DNA methylation associations with white matter hyperintensity burden. Our top discovery single CpG, cg24202936 (P = 7.6 × 10-8), was associated with F2 expression in blood (P = 6.4 × 10-5) and co-localized with FOLH1 expression in brain (posterior probability = 0.75). Our top differentially methylated regions were in PRMT1 and in CCDC144NL-AS1, which were also represented in single CpG associations (cg17417856 and cg06809326, respectively). Through Mendelian randomization analyses cg06809326 was putatively associated with white matter hyperintensity burden (P = 0.03) and expression of CCDC144NL-AS1 possibly mediated this association. Differentially methylated region analysis, joint epigenetic association analysis and multi-omics co-localization analysis consistently identified a role of DNA methylation near SH3PXD2A, a locus previously identified in genome-wide association studies of white matter hyperintensities. Gene set enrichment analyses revealed functions of the identified DNA methylation loci in the blood-brain barrier and in the immune response. Integrative cross-omics analysis identified 19 key regulatory genes in two networks related to extracellular matrix organization, and lipid and lipoprotein metabolism. A drug-repositioning analysis indicated antihyperlipidaemic agents, more specifically peroxisome proliferator-activated receptor-alpha, as possible target drugs for white matter hyperintensities. Our epigenome-wide association study and integrative cross-omics analyses implicate novel genes influencing white matter hyperintensity burden, which converged on pathways related to the immune response and to a compromised blood-brain barrier possibly due to disrupted cell-cell and cell-extracellular matrix interactions. The results also suggest that antihyperlipidaemic therapy may contribute to lowering risk for white matter hyperintensities possibly through protection against blood-brain barrier disruption.

Quantifying MR head motion in the Rhineland Study - A robust method for population cohorts.

Head motion during MR acquisition reduces image quality and has been shown to bias neuromorphometric analysis. The quantification of head motion, therefore, has both neuroscientific as well as clinical applications, for example, to control for motion in statistical analyses of brain morphology, or as a variable of interest in neurological studies. The accuracy of markerless optical head tracking, however, is largely unexplored. Furthermore, no quantitative analysis of head motion in a general, mostly healthy population cohort exists thus far. In this work, we present a robust registration method for the alignment of depth camera data that sensitively estimates even small head movements of compliant participants. Our method outperforms the vendor-supplied method in three validation experiments: 1. similarity to fMRI motion traces as a low-frequency reference, 2. recovery of the independently acquired breathing signal as a high-frequency reference, and 3. correlation with image-based quality metrics in structural T1-weighted MRI. In addition to the core algorithm, we establish an analysis pipeline that computes average motion scores per time interval or per sequence for inclusion in downstream analyses. We apply the pipeline in the Rhineland Study, a large population cohort study, where we replicate age and body mass index (BMI) as motion correlates and show that head motion significantly increases over the duration of the scan session. We observe weak, yet significant interactions between this within-session increase and age, BMI, and sex. High correlations between fMRI and camera-based motion scores of proceeding sequences further suggest that fMRI motion estimates can be used as a surrogate score in the absence of better measures to control for motion in statistical analyses.

Visual impairment and retinal and brain neurodegeneration: A population-based study.

Visual impairment and retinal neurodegeneration are intrinsically connected and both have been associated with cognitive impairment and brain atrophy, but the underlying mechanisms remain unclear. To investigate whether transneuronal degeneration is implicated, we systematically assessed the relation between visual function and retinal, visual pathway, hippocampal and brain degeneration. We analyzed baseline data from 3316 eligible Rhineland Study participants with visual acuity (VA), optical coherence tomography (OCT), and magnetic resonance imaging (MRI) data available. Regional volumes, cortical volume, and fractional anisotropy (FA) were derived from T1-weighted and diffusion-weighted 3 T MRI scans. Statistical analyses were performed using multivariable linear regression and structural equation modeling. VA and ganglion cell layer (GCL) thinning were both associated with global brain atrophy (SD effect size [95% CI] -0.090 [-0.118 to -0.062] and 0.066 [0.053-0.080], respectively), and hippocampal atrophy (-0.029 [-0.055 to -0.003] and 0.114 [0.087-0.141], respectively). The effect of VA on whole brain and hippocampal volume was partly mediated by retinal neurodegeneration. Similarly, the effect of retinal neurodegeneration on brain and hippocampal atrophy was mediated through intermediate visual tracts, accounting for 5.2%-23.9% of the effect. Visual impairment and retinal neurodegeneration were robustly associated with worse brain atrophy, FA, and hippocampal atrophy, partly mediated through disintegration of intermediate visual tracts. Our findings support the use of OCT-derived retinal measures as markers of neurodegeneration, and indicate that both general and transneuronal neurodegeneration along the visual pathway, partly reflecting visual impairment, account for the association between retinal neurodegeneration and brain atrophy.

Polygenic risk scores for schizophrenia are associated with oculomotor endophenotypes.

BACKGROUND: Schizophrenia is a heterogeneous disorder with substantial heritability. The use of endophenotypes may help clarify its aetiology. Measures from the smooth pursuit and antisaccade eye movement tasks have been identified as endophenotypes for schizophrenia in twin and family studies. However, the genetic basis of the overlap between schizophrenia and these oculomotor markers is largely unknown. Here, we tested whether schizophrenia polygenic risk scores (PRS) were associated with oculomotor performance in the general population. METHODS: Analyses were based on the data of 2956 participants (aged 30-95) of the Rhineland Study, a community-based cohort study in Bonn, Germany. Genotyping was performed on Omni-2.5 exome arrays. Using summary statistics from a recent meta-analysis based on the two largest schizophrenia genome-wide association studies to date, we quantified genetic risk for schizophrenia by creating PRS at different p value thresholds for genetic markers. We examined associations between PRS and oculomotor performance using multivariable regression models. RESULTS: Higher PRS were associated with higher antisaccade error rate and latency, and lower antisaccade amplitude gain. PRS showed inconsistent patterns of association with smooth pursuit velocity gain and were not associated with saccade rate during smooth pursuit or performance on a prosaccade control task. CONCLUSIONS: There is an overlap between genetic determinants of schizophrenia and oculomotor endophenotypes. Our findings suggest that the mechanisms that underlie schizophrenia also affect oculomotor function in the general population.

Validation of self-reported medication use applying untargeted mass spectrometry-based metabolomics techniques in the Rhineland study.

AIMS: To assess the validity of self-reported continuous medication use with drug metabolites measured in plasma by using untargeted mass spectrometric techniques. METHODS: In a population-based cohort in Bonn, Germany, we compared interview-based, self-reported medication intake with drug-specific metabolites measured in plasma (based on participants who completed their study visits between March 2016 and February 2020). Analyses were done stratified by sex and age (<65 years vs ≥65 years). Cohen's kappa (κ) statistics with 95% confidence intervals (CI) were calculated. RESULTS: A total of 13 drugs used to treat hypertension, gout, diabetes, epilepsy and depression were analysed in a sample of 4386 individuals (mean age 55 years, 56.1% women). Eleven drugs showed almost perfect agreement (κ > 0.8), whereas sitagliptin and hydrochlorothiazide showed substantial (κ = 0.8, 95% CI 0.71-0.90) and moderate agreement (κ = 0.61, 95% CI 0.56-0.66), respectively. Frequency of use allowed sex- and age-stratified analyses for eight and nine drugs, respectively. For five drugs, concordance tended to be higher for women than for men. For most drugs, concordance was higher among individuals aged ≥65 years than among individuals aged <65 years, but these age-related differences were not statistically significant. CONCLUSION: High concordance rates between self-reported drug use and metabolites measured in plasma suggest that self-reported drug use is reliable and accurate for assessing drug use.

Incidental findings on 3 T neuroimaging: cross-sectional observations from the population-based Rhineland Study.

PURPOSE: Development of best practices for dealing with incidental findings on neuroimaging requires insight in their frequency and clinical relevance. METHODS: Here, we delineate prevalence estimates with 95% confidence intervals and clinical management of incidental findings, based on the first 3589 participants of the population-based Rhineland Study (age range 30-95 years) who underwent 3 Tesla structural neuroimaging (3D, 0.8 mm3 isotropic resolution). Two trained raters independently assessed all scans for abnormalities, with confirmation and adjudication where needed by neuroradiologists. Participants were referred for diagnostic work-up depending on the potential benefit. RESULTS: Of 3589 participants (mean age 55 ± 14 years, 2072 women), 867 had at least one possible incidental finding (24.2%). Most common were pituitary abnormalities (12.3%), arachnoid cysts (4.1%), developmental venous anomalies (2.5%), non-acute infarcts (1.8%), cavernomas (1.0%), and meningiomas (0.7%). Forty-six participants were informed about their findings, which was hitherto unknown in 40 of them (1.1%). Of these, in 19 participants (48%), a wait-and-see policy was applied and nine (23%) received treatment, while lesions in the remainder were benign, could not be confirmed, or the participant refused to inform us about their clinical diagnosis. CONCLUSION: Nearly one-quarter of participants had an incidental finding, but only 5% of those required referral, that mostly remained without direct clinical consequences.

The Associations of Hearing Sensitivity and Different Cognitive Functions with Perception of Speech-in-Noise.

OBJECTIVES: Impaired speech-in-noise perception affects individuals' daily lives and is a frequent symptom of age-related hearing loss, which is a common disabling condition and a health concern in aging populations. The relative impact of hearing sensitivity loss and different cognitive functions on speech-in-noise perception is not well understood. We aimed to assess to what extent hearing sensitivity and different cognitive functions were associated with sentence-in-noise performance across the adult lifespan. DESIGN: This study is based on data of 2585 participants of the Rhineland Study, which is a German community-based cohort study of persons of age 30 years and older. We assessed speech-in-noise with a sentence-in-noise test (Göttinger Satztest), hearing sensitivity thresholds (air conduction pure-tone audiometry [PTA] average of 0.5, 1, 2, and 4 kHz), and the following cognitive domains: crystallized intelligence (German Mehrfachwahl-Wortschatz-Intelligenztest, MWT-B), executive functioning (Trail Making Test B, TMT), working memory (Digit Span forward, DS), and long-term memory (Verbal Learning and Memory Test delayed recall; VLMT). We examined the association between hearing sensitivity and cognitive functions with sentence-in-noise perception using a multivariable linear regression model adjusted for age, sex, and multiple potential confounders. RESULTS: Better hearing sensitivity was associated with better speech-in-noise perception (0.25 signal noise ratio [SNR] dB HL decrease per 5 dB HL decrease in PTA; 95% confidence interval [CI]: 0.20 to 0.25; p < 0.001). Better cognitive performance was also associated with better speech-in-noise perception, but to a lesser extent. Crystallized intelligence (MWT-B) showed an effect size of -0.10 SNR dB HL decrease per SD (95% CI: -0.14 to -0.06; p < 0.001), executive functioning (TMT) of -0.08 SNR dB HL decrease per SD (95% CI: -0.13 to -0.03; p = 0.002), working memory (DS) of -0.04 SNR dB HL decrease per SD (95% CI: -0.08 to -0.003; p = 0.03), and long-term memory (VLMT) of -0.03 SNR dB HL decrease per SD (95% CI: -0.07 to 0.01; p = 0.12). The standardized effect of hearing sensitivity (ß = 0.34) on speech-in-noise perception was four to five times larger than the effects of crystallized intelligence (ß = -0.08) and executive functioning (ß = -0.06). CONCLUSIONS: Hearing sensitivity was the strongest determinant of sentence-in-noise perception in adults above the age of 30. We determined the relative effect of different cognitive functions on sentence-in-noise perception. Crystallized intelligence and executive functions showed stronger associations while working and long-term memory functions had much smaller independent effects. Our results contribute to the understanding of determinants of speech-in-noise perception in aging adults.

Automated olfactory bulb segmentation on high resolutional T2-weighted MRI.

The neuroimage analysis community has neglected the automated segmentation of the olfactory bulb (OB) despite its crucial role in olfactory function. The lack of an automatic processing method for the OB can be explained by its challenging properties (small size, location, and poor visibility on traditional MRI scans). Nonetheless, recent advances in MRI acquisition techniques and resolution have allowed raters to generate more reliable manual annotations. Furthermore, the high accuracy of deep learning methods for solving semantic segmentation problems provides us with an option to reliably assess even small structures. In this work, we introduce a novel, fast, and fully automated deep learning pipeline to accurately segment OB tissue on sub-millimeter T2-weighted (T2w) whole-brain MR images. To this end, we designed a three-stage pipeline: (1) Localization of a region containing both OBs using FastSurferCNN, (2) Segmentation of OB tissue within the localized region through four independent AttFastSurferCNN - a novel deep learning architecture with a self-attention mechanism to improve modeling of contextual information, and (3) Ensemble of the predicted label maps. For this work, both OBs were manually annotated in a total of 620 T2w images for training (n=357) and testing. The OB pipeline exhibits high performance in terms of boundary delineation, OB localization, and volume estimation across a wide range of ages in 203 participants of the Rhineland Study (Dice Score (Dice): 0.852, Volume Similarity (VS): 0.910, and Average Hausdorff Distance (AVD): 0.215 mm). Moreover, it also generalizes to scans of an independent dataset never encountered during training, the Human Connectome Project (HCP), with different acquisition parameters and demographics, evaluated in 30 cases at the native 0.7 mm HCP resolution (Dice: 0.738, VS: 0.790, and AVD: 0.340 mm), and the default 0.8 mm pipeline resolution (Dice: 0.782, VS: 0.858, and AVD: 0.268 mm). We extensively validated our pipeline not only with respect to segmentation accuracy but also to known OB volume effects, where it can sensitively replicate age effects (ß=-0.232, p<.01). Furthermore, our method can analyze a 3D volume in less than a minute (GPU) in an end-to-end fashion, providing a validated, efficient, and scalable solution for automatically assessing OB volumes.

Insulin resistance accounts for metabolic syndrome-related alterations in brain structure.

Metabolic syndrome (MetS) is a major public health burden worldwide and associated with brain abnormalities. Although insulin resistance is considered a pivotal feature of MetS, its role in the pathogenesis of MetS-related brain alterations in the general population is unclear. Therefore, in 973 participants (mean age 52.5 years) of the population-based Rhineland Study, we assessed brain morphology in relation to MetS and insulin resistance, and evaluated to what extent the pattern of structural brain changes seen in MetS overlap with those associated with insulin resistance. Cortical reconstruction and volumetric segmentation were obtained from high-resolution brain images at 3 Tesla using FreeSurfer. The relations between metabolic measures and brain structure were assessed through (generalized) linear models. Both MetS and insulin resistance were associated with smaller cortical gray matter volume and thickness, but not with white matter or subcortical gray matter volume. Age- and sex-adjusted vertex-based brain morphometry demonstrated that MetS and insulin resistance were related to cortical thinning in a similar spatial pattern. Importantly, no independent effect of MetS on cortical gray matter was observed beyond the effect of insulin resistance. Our findings suggest that addressing insulin resistance is critical in the prevention of MetS-related brain changes in later life.

Polypharmacy, potentially inappropriate medication and pharmacogenomics drug exposure in the Rhineland Study.

AIM: High medication use may contribute to the efficiency of drug therapy in general, but it could also increase the burden of adverse drug reactions. We aimed to assess medication use and the prevalence of three risk factors for adverse drug reactions: the use of polypharmacy, potentially inappropriate medication in the elderly and pharmacogenomic polymorphisms affecting the metabolism of drugs. METHODS: Cross-sectional interview-based medication data (including over-the-counter drugs) was collected in a large population-based cohort (≥30 years of age) in Bonn, Germany. RESULTS: Analyses were based on the first 5000 participants of the Rhineland Study (mean age 55 years, 57% women). Of our participants, 66.0% reported the use of a drug regularly, which increased to 87.4% in participants aged ≥65 years (n = 1301). The rates of use of polypharmacy, potentially inappropriate medication and pharmacogenomic drugs were 15.9%, 6.4% and 20.5%, respectively. In participants <65 years, 16.0% (95% CI 14.8, 17.3) had at least one risk factor. In participants aged ≥65 years, 54.1% (95% CI 51.4, 56.8) had at least one and 27.4% (95% CI 25.0, 29.9) had at least two risk factors. Extrapolating these numbers to the German population implies that around 9 million of the 17 million individuals aged 65 years or older are potentially at an elevated risk for adverse drug reactions, of which 4.6 million are at a potentially highly elevated risk for adverse drug reactions. CONCLUSION: Our study shows that drug use is common and the individual risk for an adverse drug reaction in our population is high. This suggests room for improvement in general medication use.

FatSegNet: A fully automated deep learning pipeline for adipose tissue segmentation on abdominal dixon MRI.

PURPOSE: Introduce and validate a novel, fast, and fully automated deep learning pipeline (FatSegNet) to accurately identify, segment, and quantify visceral and subcutaneous adipose tissue (VAT and SAT) within a consistent, anatomically defined abdominal region on Dixon MRI scans. METHODS: FatSegNet is composed of three stages: (a) Consistent localization of the abdominal region using two 2D-Competitive Dense Fully Convolutional Networks (CDFNet), (b) Segmentation of adipose tissue on three views by independent CDFNets, and (c) View aggregation. FatSegNet is validated by: (1) comparison of segmentation accuracy (sixfold cross-validation), (2) test-retest reliability, (3) generalizability to randomly selected manually re-edited cases, and (4) replication of age and sex effects in the Rhineland Study-a large prospective population cohort. RESULTS: The CDFNet demonstrates increased accuracy and robustness compared to traditional deep learning networks. FatSegNet Dice score outperforms manual raters on VAT (0.850 vs. 0.788) and produces comparable results on SAT (0.975 vs. 0.982). The pipeline has excellent agreement for both test-retest (ICC VAT 0.998 and SAT 0.996) and manual re-editing (ICC VAT 0.999 and SAT 0.999). CONCLUSIONS: FatSegNet generalizes well to different body shapes, sensitively replicates known VAT and SAT volume effects in a large cohort study and permits localized analysis of fat compartments. Furthermore, it can reliably analyze a 3D Dixon MRI in ∼1 minute, providing an efficient and validated pipeline for abdominal adipose tissue analysis in the Rhineland Study.

Dementia Research Fit for the Planet: Reflections on Population Studies of Dementia for Researchers and Policy Makers Alike.

In recent years, a rapidly increasing collection of investigative methods in addition to changes in diagnostic criteria for dementia have followed "high-tech" trends in medicine, with the aim to better define the dementia syndrome and its biological substrates, mainly in order to predict risk prior to clinical expression. These approaches are not without challenge. A set of guidelines have been developed by a group of European experts in population-based cohort research through a series of workshops, funded by the Joint Program for Neurodegenerative Disorders (JPND). The aims of the guidelines are to assist policy makers and researchers to understand (1) What population studies for ageing populations should encompass and (2) How to interpret the findings from population studies. Such studies are essential to provide evidence relevant to the understanding of healthy and frail brain ageing, including the dementia syndrome for contemporary and future societies by drawing on the past.

Systemic and Ocular Determinants of Peripapillary Retinal Nerve Fiber Layer Thickness Measurements in the European Eye Epidemiology (E3) Population.

PURPOSE: To investigate systemic and ocular determinants of peripapillary retinal nerve fiber layer thickness (pRNFLT) in the European population. DESIGN: Cross-sectional meta-analysis. PARTICIPANTS: A total of 16 084 European adults from 8 cohort studies (mean age range, 56.9±12.3-82.1±4.2 years) of the European Eye Epidemiology (E3) consortium. METHODS: We examined associations with pRNFLT measured by spectral-domain OCT in each study using multivariable linear regression and pooled results using random effects meta-analysis. MAIN OUTCOME MEASURES: Determinants of pRNFLT. RESULTS: Mean pRNFLT ranged from 86.8±21.4 µm in the Rotterdam Study I to 104.7±12.5 µm in the Rotterdam Study III. We found the following factors to be associated with reduced pRNFLT: Older age (ß = -0.38 µm/year; 95% confidence interval [CI], -0.57 to -0.18), higher intraocular pressure (IOP) (ß = -0.36 µm/mmHg; 95% CI, -0.56 to -0.15), visual impairment (ß = -5.50 µm; 95% CI, -9.37 to -1.64), and history of systemic hypertension (ß = -0.54 µm; 95% CI, -1.01 to -0.07) and stroke (ß = -1.94 µm; 95% CI, -3.17 to -0.72). A suggestive, albeit nonsignificant, association was observed for dementia (ß = -3.11 µm; 95% CI, -6.22 to 0.01). Higher pRNFLT was associated with more hyperopic spherical equivalent (ß = 1.39 µm/diopter; 95% CI, 1.19-1.59) and smoking (ß = 1.53 µm; 95% CI, 1.00-2.06 for current smokers compared with never-smokers). CONCLUSIONS: In addition to previously described determinants such as age and refraction, we found that systemic vascular and neurovascular diseases were associated with reduced pRNFLT. These may be of clinical relevance, especially in glaucoma monitoring of patients with newly occurring vascular comorbidities.

Rapid whole-brain resting-state fMRI at 3 T: Efficiency-optimized three-dimensional EPI versus repetition time-matched simultaneous-multi-slice EPI.

State-of-the-art simultaneous-multi-slice (SMS-)EPI and 3D-EPI share several properties that benefit functional MRI acquisition. Both sequences employ equivalent parallel imaging undersampling with controlled aliasing to achieve high temporal sampling rates. As a volumetric imaging sequence, 3D-EPI offers additional means of acceleration complementary to 2D-CAIPIRINHA sampling, such as fast water excitation and elliptical sampling. We performed an application-oriented comparison between a tailored, six-fold CAIPIRINHA-accelerated 3D-EPI protocol at 530 ms temporal and 2.4 mm isotropic spatial resolution and an SMS-EPI protocol with identical spatial and temporal resolution for whole-brain resting-state fMRI at 3 T. The latter required eight-fold slice acceleration to compensate for the lack of elliptical sampling and fast water excitation. Both sequences used vendor-supplied on-line image reconstruction. We acquired test/retest resting-state fMRI scans in ten volunteers, with simultaneous acquisition of cardiac and respiration data, subsequently used for optional physiological noise removal (nuisance regression). We found that the 3D-EPI protocol has significantly increased temporal signal-to-noise ratio throughout the brain as compared to the SMS-EPI protocol, especially when employing motion and nuisance regression. Both sequence types reliably identified known functional networks with stronger functional connectivity values for the 3D-EPI protocol. We conclude that the more time-efficient 3D-EPI primarily benefits from reduced parallel imaging noise due to a higher, actual k-space sampling density compared to SMS-EPI. The resultant BOLD sensitivity increase makes 3D-EPI a valuable alternative to SMS-EPI for whole-brain fMRI at 3 T, with voxel sizes well below 3 mm isotropic and sampling rates high enough to separate dominant cardiac signals from BOLD signals in the frequency domain.

Less head motion during MRI under task than resting-state conditions.

Head motion reduces data quality of neuroimaging data. In three functional magnetic resonance imaging (MRI) experiments we demonstrate that people make less head movements under task than resting-state conditions. In Experiment 1, we observed less head motion during a memory encoding task than during the resting-state condition. In Experiment 2, using publicly shared data from the UCLA Consortium for Neuropsychiatric Phenomics LA5c Study, we again found less head motion during several active task conditions than during a resting-state condition, although some task conditions also showed comparable motion. In the healthy controls, we found more head motion in men than in women and more motion with increasing age. When comparing clinical groups, we found that patients with a clinical diagnosis of bipolar disorder, or schizophrenia, move more compared to healthy controls or patients with ADHD. Both these experiments had a fixed acquisition order across participants, and we could not rule out that a first or last scan during a session might be particularly prone to more head motion. Therefore, we conducted Experiment 3, in which we collected several task and resting-state fMRI runs with an acquisition order counter-balanced. The results of Experiment 3 show again less head motion during several task conditions than during rest. Together these experiments demonstrate that small head motions occur during MRI even with careful instruction to remain still and fixation with foam pillows, but that head motion is lower when participants are engaged in a cognitive task. These finding may inform the choice of functional runs when studying difficult-to-scan populations, such as children or certain patient populations. Our findings also indicate that differences in head motion complicate direct comparisons of measures of functional neuronal networks between task and resting-state fMRI because of potential differences in data quality. In practice, a task to reduce head motion might be especially useful when acquiring structural MRI data such as T1/T2-weighted and diffusion MRI in research and clinical settings.

Alzheimer's disease.

Although the prevalence of dementia continues to increase worldwide, incidence in the western world might have decreased as a result of better vascular care and improved brain health. Alzheimer's disease, the most prevalent cause of dementia, is still defined by the combined presence of amyloid and tau, but researchers are gradually moving away from the simple assumption of linear causality as proposed in the original amyloid hypothesis. Age-related, protective, and disease-promoting factors probably interact with the core mechanisms of the disease. Amyloid ß42, and tau proteins are established core cerebrospinal biomarkers; novel candidate biomarkers include amyloid ß oligomers and synaptic markers. MRI and fluorodeoxyglucose PET are established imaging techniques for diagnosis of Alzheimer's disease. Amyloid PET is gaining traction in the clinical arena, but validity and cost-effectiveness remain to be established. Tau PET might offer new insights and be of great help in differential diagnosis and selection of patients for trials. In the search for understanding the disease mechanism and keys to treatment, research is moving increasingly into the earliest phase of disease. Preclinical Alzheimer's disease is defined as biomarker evidence of Alzheimer's pathological changes in cognitively healthy individuals. Patients with subjective cognitive decline have been identified as a useful population in whom to look for preclinical Alzheimer's disease. Moderately positive results for interventions targeting several lifestyle factors in non-demented elderly patients and moderately positive interim results for lowering amyloid in pre-dementia Alzheimer's disease suggest that, ultimately, there will be a future in which specific anti-Alzheimer's therapy will be combined with lifestyle interventions targeting general brain health to jointly combat the disease. In this Seminar, we discuss the main developments in Alzheimer's research.