Common Alzheimer's disease risk variant within the CLU gene affects white matter microstructure in young adults

Astrocyte-derived clusterin disrupts glial physiology to obstruct remyelination in mouse models of demyelinating diseases

Multiple sclerosis (MS) is a debilitating demyelinating disease characterized by remyelination failure attributed to inadequate oligodendrocyte precursor cells (OPCs) differentiation and aberrant astrogliosis. A comprehensive cell atlas reanalysis of clinical specimens brings to light heightened clusterin (CLU) expression in a specific astrocyte subtype links to active lesions in MS patients. Our investigation reveals elevated astrocytic CLU levels in both active lesions of patient tissues and female murine MS models. CLU administration stimulates primary astrocyte proliferation while concurrently impeding astrocyte-mediated clearance of myelin debris. Intriguingly, CLU overload directly impedes OPC differentiation and induces OPCs and OLs apoptosis. Mechanistically, CLU suppresses PI3K-AKT signaling in primary OPCs via very low-density lipoprotein receptor. Pharmacological activation of AKT rescues the damage inflicted by excess CLU on OPCs and ameliorates demyelination in the corpus callosum. Furthermore, conditional knockout of CLU emerges as a promising intervention, showcasing improved remyelination processes and reduced severity in murine MS models.

The Association between Individual Food Groups, Limbic System White Matter Tracts, and Episodic Memory: Initial Data from the Aiginition Longitudinal Biomarker Investigation of Neurodegeneration (ALBION) Study

(1) Background: Many studies link food intake with clinical cognitive outcomes, but evidence for brain biomarkers, such as memory-related limbic white matter (WM) tracts, is limited. We examined the association between food groups, limbic WM tracts integrity, and memory performance in community-dwelling individuals. (2) Methods: We included 117 non-demented individuals (ALBION study). Verbal and visual episodic memory tests were administered, and a composite z-score was calculated. Diffusion tensor imaging tractography was applied for limbic WM tracts (fornix-FX, cingulum bundle-CB, uncinate fasciculus-UF, hippocampal perforant pathway zone-hPPZ). Food intake was evaluated through four 24-h recalls. We applied linear regression models adjusted for demographics and energy intake. (3) Results: We found significant associations between (a) higher low-to-moderate alcohol intake and higher FX fractional anisotropy (FA), (b) higher full-fat dairy intake and lower hPPZ FA, and (c) higher red meat and cold cuts intake and lower hPPZ FA. None of the food groups was associated with memory performance. (4) Conclusions: Despite non-significant associations between food groups and memory, possibly due to participants' cognitive profile and/or compensatory mechanisms, the study documented a possible beneficial role of low-to-moderate alcohol and a harmful role of full-fat dairy and red meat and cold cuts on limbic WM tracts.

Alzheimer's disease protective allele of Clusterin modulates neuronal excitability through lipid-droplet-mediated neuron-glia communication

Genome-wide association studies (GWAS) of Alzheimer's disease (AD) have identified a plethora of risk loci. However, the disease variants/genes and the underlying mechanisms remain largely unknown. For a strong AD-associated locus near Clusterin (CLU), we tied an AD protective allele to a role of neuronal CLU in promoting neuron excitability through lipid-mediated neuron-glia communication. We identified a putative causal SNP of CLU that impacts neuron-specific chromatin accessibility to transcription-factor(s), with the AD protective allele upregulating neuronal CLU and promoting neuron excitability. Transcriptomic analysis and functional studies in induced pluripotent stem cell (iPSC)-derived neurons co-cultured with mouse astrocytes show that neuronal CLU facilitates neuron-to-glia lipid transfer and astrocytic lipid droplet formation coupled with reactive oxygen species (ROS) accumulation. These changes cause astrocytes to uptake less glutamate thereby altering neuron excitability. Our study provides insights into how CLU confers resilience to AD through neuron-glia interactions.

Genetic biomarkers of cognitive impairment and dementia of potential interest in CKD patients

This review discusses genetic variants associated with cognitive dysfunction in chronic kidney disease (CKD) patients, emphasising the limited research in this area. Four studies have explored genetic markers of cognitive dysfunction in CKD, with findings suggesting shared genetic biomarkers between Alzheimer's Disease and CKD.Because of the limited specific research on genetic markers of cognitive dysfunction and dementia in CKD, we extracted data from the current literature studies on genetic markers in the general population that may be relevant to the CKD population. These markers include Apolipoprotein E (APOE), Complement Receptor 1 (CR1), Clusterin (CLU), Sortilin-related receptor 1 (SORL1), Catechol-O-methyltransferase (COMT), and Brain-derived neurotrophic factor (BDNF), all of which are known to be associated with cognitive dysfunction and dementia in other populations. These genes play various roles in lipid metabolism, inflammation, Aβ clearance, and neuronal function, making them potential candidates for studying cognitive decline in CKD patients.CKD-specific research is needed to understand the role of these genetic markers in CKD-related cognitive dysfunction. Investigating how these genes influence cognitive decline in CKD patients could provide valuable insights into early detection, targeted interventions, and personalised treatment strategies. Overall, genetic studies to enhance our understanding and management of cognitive dysfunction in CKD represent a clinical research priority in this population.

Oligomeric amyloid beta prevents myelination in a clusterin-dependent manner

Background

White matter loss is a well-documented phenomenon in Alzheimer's disease (AD) patients that has been recognized for decades. However, the underlying reasons for the failure of oligodendrocyte progenitor cells (OPCs) to repair myelin deficits in these patients remain elusive. A single nucleotide polymorphism (SNP) in Clusterin has been identified as a risk factor for late-onset Alzheimer's disease and linked to a decrease in white matter integrity in healthy adults, but its specific role in oligodendrocyte function and myelin maintenance in Alzheimer's disease pathology remains unclear.

Methods

To investigate the impact of Clusterin on OPCs in the context of Alzheimer's disease, we employed a combination of immunofluorescence and transmission electron microscopy techniques, primary culture of OPCs, and an animal model of Alzheimer's disease.

Results

Our findings demonstrate that Clusterin, a risk factor for late-onset AD, is produced by OPCs and inhibits their differentiation into oligodendrocytes. Specifically, we observed upregulation of Clusterin in OPCs in the 5xFAD mouse model of AD. We also found that the phagocytosis of debris, including amyloid beta (Aβ), myelin, and apoptotic cells leads to the upregulation of Clusterin in OPCs. In vivo experiments confirmed that Aβ oligomers stimulate Clusterin upregulation and that OPCs are capable of phagocytosing Aβ. Furthermore, we discovered that Clusterin significantly inhibits OPC differentiation and hinders the production of myelin proteins. Finally, we demonstrate that Clusterin inhibits OPC differentiation by reducing the production of IL-9 by OPCs.

Conclusion

Our data suggest that Clusterin may play a key role in the impaired myelin repair observed in AD and could serve as a promising therapeutic target for addressing AD-associated cognitive decline.

The interaction effects of age, APOE and common environmental risk factors on human brain structure

Mounting evidence suggests considerable diversity in brain aging trajectories, primarily arising from the complex interplay between age, genetic, and environmental risk factors, leading to distinct patterns of micro- and macro-cerebral aging. The underlying mechanisms of such effects still remain unclear. We conducted a comprehensive association analysis between cerebral structural measures and prevalent risk factors, using data from 36,969 UK Biobank subjects aged 44-81. Participants were assessed for brain volume, white matter diffusivity, Apolipoprotein E (APOE) genotypes, polygenic risk scores, lifestyles, and socioeconomic status. We examined genetic and environmental effects and their interactions with age and sex, and identified 726 signals, with education, alcohol, and smoking affecting most brain regions. Our analysis revealed negative age-APOE-ε4 and positive age-APOE-ε2 interaction effects, respectively, especially in females on the volume of amygdala, positive age-sex-APOE-ε4 interaction on the cerebellar volume, positive age-excessive-alcohol interaction effect on the mean diffusivity of the splenium of the corpus callosum, positive age-healthy-diet interaction effect on the paracentral volume, and negative APOE-ε4-moderate-alcohol interaction effects on the axial diffusivity of the superior fronto-occipital fasciculus. These findings highlight the need of considering age, sex, genetic, and environmental joint effects in elucidating normal or abnormal brain aging.

Alzheimer's Disease: Models and Molecular Mechanisms Informing Disease and Treatments

Alzheimer's Disease (AD) is a complex neurodegenerative disease resulting in progressive loss of memory, language and motor abilities caused by cortical and hippocampal degeneration. This review captures the landscape of understanding of AD pathology, diagnostics, and current therapies. Two major mechanisms direct AD pathology: (1) accumulation of amyloid β (Aβ) plaque and (2) tau-derived neurofibrillary tangles (NFT). The most common variants in the Aβ pathway in APP, PSEN1, and PSEN2 are largely responsible for early-onset AD (EOAD), while MAPT, APOE, TREM2 and ABCA7 have a modifying effect on late-onset AD (LOAD). More recent studies implicate chaperone proteins and Aβ degrading proteins in AD. Several tests, such as cognitive function, brain imaging, and cerebral spinal fluid (CSF) and blood tests, are used for AD diagnosis. Additionally, several biomarkers seem to have a unique AD specific combination of expression and could potentially be used in improved, less invasive diagnostics. In addition to genetic perturbations, environmental influences, such as altered gut microbiome signatures, affect AD. Effective AD treatments have been challenging to develop. Currently, there are several FDA approved drugs (cholinesterase inhibitors, Aß-targeting antibodies and an NMDA antagonist) that could mitigate AD rate of decline and symptoms of distress.

Astrocytic response mediated by the CLU risk allele inhibits OPC proliferation and myelination in a human iPSC model

The C allele of rs11136000 variant in the clusterin (CLU) gene represents the third strongest known genetic risk factor for late-onset Alzheimer's disease. However, whether this single-nucleotide polymorphism (SNP) is functional and what the underlying mechanisms are remain unclear. In this study, the CLU rs11136000 SNP is identified as a functional variant by a small-scale CRISPR-Cas9 screen. Astrocytes derived from isogenic induced pluripotent stem cells (iPSCs) carrying the "C" or "T" allele of the CLU rs11136000 SNP exhibit different CLU expression levels. TAR DNA-binding protein-43 (TDP-43) preferentially binds to the "C" allele to promote CLU expression and exacerbate inflammation. The interferon response and CXCL10 expression are elevated in cytokine-treated C/C astrocytes, leading to inhibition of oligodendrocyte progenitor cell (OPC) proliferation and myelination. Accordingly, elevated CLU and CXCL10 but reduced myelin basic protein (MBP) expression are detected in human brains of C/C carriers. Our study uncovers a mechanism underlying reduced white matter integrity observed in the CLU rs11136000 risk "C" allele carriers.

Neuronal Hyperactivation in EEG Data during Cognitive Tasks Is Related to the Apolipoprotein J/Clusterin Genotype in Nondemented Adults

The clusterin (CLU) rs11136000 CC genotype is a probable risk factor for Alzheimer's disease (AD). CLU, also known as the apolipoprotein J gene, shares certain properties with the apolipoprotein E (APOE) gene with a well-established relationship with AD. This study aimed to determine whether the electrophysiological patterns of brain activation during the letter fluency task (LFT) depend on CLU genotypes in adults without dementia. Previous studies have shown that LFT performance involves activation of the frontal cortex. We examined EEG alpha1 and alpha2 band desynchronization in the frontal regions during the LFT in 94 nondemented individuals stratified by CLU (rs11136000) genotype. Starting at 30 years of age, CLU CC carriers exhibited more pronounced task-related alpha2 desynchronization than CLU CT&TT carriers in the absence of any differences in LFT performance. In CLU CC carriers, alpha2 desynchronization was significantly correlated with age. Increased task-related activation in individuals at genetic risk for AD may reflect greater "effort" to perform the task and/or neuronal hyperexcitability. The results show that the CLU genotype is associated with neuronal hyperactivation in the frontal cortex during cognitive tasks performances in nondemented individuals, suggesting systematic vulnerability of LFT related cognitive networks in people carrying unfavorable CLU alleles.

Localized White Matter Tract Integrity Measured by Diffusion Tensor Imaging Is Altered in People with Mild Cognitive Impairment and Associated with Dual-Task and Single-Task Gait Speed

BACKGROUND

Altered white matter (WM) tract integrity may contribute to mild cognitive impairment (MCI) and gait abnormalities.

OBJECTIVE

The purpose of this study was to determine whether diffusion tensor imaging (DTI) metrics were altered in specific portions of WM tracts in people with MCI and to determine whether gait speed variations were associated with the specific DTI metric changes.

METHODS

DTI was acquired in 44 people with MCI and 40 cognitively normal elderly controls (CNCs). Fractional anisotropy (FA) and radial diffusivity (RD) were measured along 18 major brain WM tracts using probabilistic tractography. The average FA and RD along the tracts were compared between the groups using MANCOVA and post-hoc tests. The tracts with FA or RD differences between the groups were examined using an along-tract exploratory analysis to identify locations that differed between the groups. Associations between FA and RD in whole tracts and in the segments of the tracts that differed between the groups and usual/dual-task gait velocities and gross cognition were examined.

RESULTS

Lower FA and higher RD was observed in right cingulum-cingulate gyrus endings (rh.ccg) of the MCI group compared to the CNC group. These changes were localized to the posterior portions of the rh.ccg and correlated with gait velocities.

CONCLUSION

Lower FA and higher RD in the posterior portion of the rh.ccg adjacent to the posterior cingulate suggests decreased microstructural integrity in the MCI group. The correlation of these metrics with gait velocities suggests an important role for this tract in maintaining normal cognitive-motor function.

Single-cell transcriptomics captures features of human midbrain development and dopamine neuron diversity in brain organoids

Three-dimensional brain organoids have emerged as a valuable model system for studies of human brain development and pathology. Here we establish a midbrain organoid culture system to study the developmental trajectory from pluripotent stem cells to mature dopamine neurons. Using single cell RNA sequencing, we identify the presence of three molecularly distinct subtypes of human dopamine neurons with high similarity to those in developing and adult human midbrain. However, despite significant advancements in the field, the use of brain organoids can be limited by issues of reproducibility and incomplete maturation which was also observed in this study. We therefore designed bioengineered ventral midbrain organoids supported by recombinant spider-silk microfibers functionalized with full-length human laminin. We show that silk organoids reproduce key molecular aspects of dopamine neurogenesis and reduce inter-organoid variability in terms of cell type composition and dopamine neuron formation.

Identification of pleiotropy at the gene level between psychiatric disorders and related traits

Major mental disorders are highly prevalent and make a substantial contribution to the global disease burden. It is known that mental disorders share clinical characteristics, and genome-wide association studies (GWASs) have recently provided evidence for shared genetic factors as well. Genetic overlaps are usually identified at the single-marker level. Here, we aimed to identify genetic overlaps at the gene level between 7 mental disorders (schizophrenia, autism spectrum disorder, major depressive disorder, anorexia nervosa, ADHD, bipolar disorder and anxiety), 8 brain morphometric traits, 2 cognitive traits (educational attainment and general cognitive function) and 9 personality traits (subjective well-being, depressive symptoms, neuroticism, extraversion, openness to experience, agreeableness and conscientiousness, children's aggressive behaviour, loneliness) based on publicly available GWASs. We performed systematic conditional regression analyses to identify independent signals and select loci associated with more than one trait. We identified 48 genes containing independent markers associated with several traits (pleiotropy at the gene level). We also report 9 genes with different markers that show independent associations with single traits (allelic heterogeneity). This study demonstrates that mental disorders and related traits do show pleiotropy at the gene level as well as the single-marker level. The identification of these genes might be important for prioritizing further deep genotyping, functional studies, or drug targeting.

Characterization of Brain Iron Deposition Pattern and Its Association With Genetic Risk Factor in Alzheimer's Disease Using Susceptibility-Weighted Imaging

The presence of iron is an important factor for normal brain functions, whereas excessive deposition of iron may impair normal cognitive function in the brain and lead to Alzheimer’s disease (AD). MRI has been widely applied to characterize brain structural and functional changes caused by AD. However, the effectiveness of using susceptibility-weighted imaging (SWI) for the analysis of brain iron deposition is still unclear, especially within the context of early AD diagnosis. Thus, in this study, we aim to explore the relationship between brain iron deposition measured by SWI with the progression of AD using various feature selection and classification methods. The proposed model was evaluated on a 69-subject SWI imaging dataset consisting of 24 AD patients, 21 mild cognitive impairment patients, and 24 normal controls. The identified AD progression-related regions were then compared with the regions reported from previous genetic association studies, and we observed considerable overlap between these two. Further, we have identified a new potential AD-related gene (MEF2C) closely related to the interaction between iron deposition and AD progression in the brain.

Imaging Genetics Study Based on a Temporal Group Sparse Regression and Additive Model for Biomarker Detection of Alzheimer's Disease

Imaging genetics is an effective tool used to detect potential biomarkers of Alzheimer's disease (AD) in imaging and genetic data. Most existing imaging genetics methods analyze the association between brain imaging quantitative traits (QTs) and genetic data [e.g., single nucleotide polymorphism (SNP)] by using a linear model, ignoring correlations between a set of QTs and SNP groups, and disregarding the varied associations between longitudinal imaging QTs and SNPs. To solve these problems, we propose a novel temporal group sparsity regression and additive model (T-GSRAM) to identify associations between longitudinal imaging QTs and SNPs for detection of potential AD biomarkers. We first construct a nonparametric regression model to analyze the nonlinear association between QTs and SNPs, which can accurately model the complex influence of SNPs on QTs. We then use longitudinal QTs to identify the trajectory of imaging genetic patterns over time. Moreover, the SNP information of group and individual levels are incorporated into the proposed method to boost the power of biomarker detection. Finally, we propose an efficient algorithm to solve the whole T-GSRAM model. We evaluated our method using simulation data and real data obtained from AD neuroimaging initiative. Experimental results show that our proposed method outperforms several state-of-the-art methods in terms of the receiver operating characteristic curves and area under the curve. Moreover, the detection of AD-related genes and QTs has been confirmed in previous studies, thereby further verifying the effectiveness of our approach and helping understand the genetic basis over time during disease progression.

Genome-wide variant-based study of genetic effects with the largest neuroanatomic coverage

BACKGROUND

Brain image genetics provides enormous opportunities for examining the effects of genetic variations on the brain. Many studies have shown that the structure, function, and abnormality (e.g., those related to Alzheimer's disease) of the brain are heritable. However, which genetic variations contribute to these phenotypic changes is not completely clear. Advances in neuroimaging and genetics have led us to obtain detailed brain anatomy and genome-wide information. These data offer us new opportunities to identify genetic variations such as single nucleotide polymorphisms (SNPs) that affect brain structure. In this paper, we perform a genome-wide variant-based study, and aim to identify top SNPs or SNP sets which have genetic effects with the largest neuroanotomic coverage at both voxel and region-of-interest (ROI) levels. Based on the voxelwise genome-wide association study (GWAS) results, we used the exhaustive search to find the top SNPs or SNP sets that have the largest voxel-based or ROI-based neuroanatomic coverage. For SNP sets with >2 SNPs, we proposed an efficient genetic algorithm to identify top SNP sets that can cover all ROIs or a specific ROI.

RESULTS

We identified an ensemble of top SNPs, SNP-pairs and SNP-sets, whose effects have the largest neuroanatomic coverage. Experimental results on real imaging genetics data show that the proposed genetic algorithm is superior to the exhaustive search in terms of computational time for identifying top SNP-sets.

CONCLUSIONS

We proposed and applied an informatics strategy to identify top SNPs, SNP-pairs and SNP-sets that have genetic effects with the largest neuroanatomic coverage. The proposed genetic algorithm offers an efficient solution to accomplish the task, especially for identifying top SNP-sets.

Clusterin secreted from astrocyte promotes excitatory synaptic transmission and ameliorates Alzheimer's disease neuropathology

Background

Genome-wide association studies have established clusterin (CLU) as a genetic modifier for late-onset Alzheimer’s disease (AD). Both protective and risk alleles have been identified which may be associated with its expression levels. However, the physiological function of clusterin in the central nervous system remains largely unknown.

Methods

We examined Clu expression in mouse brains by immunohistochemistry and high-resolution imaging. We performed electrophysiological recordings and morphological analysis of dendritic spines in wild-type and Clu knockout mice. We tested synaptic function of astrocytic Clu using neuron-glia co-cultures and by AAV-mediated astroglial Clu expression in vivo. Finally, we investigated the role of astrocytic Clu on synaptic properties and amyloid pathology in 5xFAD transgenic mouse model of AD.

Results

We show that astrocyte secreted Clu co-localizes with presynaptic puncta of excitatory neurons. Loss of Clu led to impaired presynaptic function and reduced spine density in vivo. Neurons co-cultured with Clu-overexpressing astrocytes or treated with conditioned media from HEK293 cells transfected with Clu displayed enhanced excitatory neurotransmission. AAV-mediated astroglial Clu expression promoted excitatory neurotransmission in wild-type mice and rescued synaptic deficits in Clu knockout mice. Overexpression of Clu in the astrocytes of 5xFAD mice led to reduced Aβ pathology and fully rescued the synaptic deficits.

Conclusion

We identify Clu as an astrocyte-derived synaptogenic and anti-amyloid factor; the combination of these activities may influence the progression of late-onset AD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13024-021-00426-7.

Clusterin as a Potential Biomarker of Obesity-Related Alzheimer's Disease Risk

Over 35% of the adult US population is obese. In turn, excess adiposity increases the risk of multiple complications including type 2 diabetes (T2D), insulin resistance, and cardiovascular disease; yet, obesity also independently heightens risk of Alzheimer's Disease (AD), even after adjusting for other important confounding risk factors including blood pressure, sociodemographics, cholesterol levels, smoking status, and Apolipoprotein E (ApoE) genotype. Among patients over the age of 65 with dementia, 37% have coexisting diabetes, and an estimated 7.3% of cases of AD are directly attributable to midlife obesity. Clusterin, also known as apolipoprotein J (ApoJ), is a multifunctional glycoprotein that acts as a molecular chaperone, assisting folding of secreted proteins. Clusterin has been implicated in several physiological and pathological states, including AD, metabolic disease, and cardiovascular disease. Despite long-standing interest in elucidating clusterin's relationship with amyloid beta (Aβ) aggregation/clearance and toxicity, significant knowledge gaps still exist. Altered clusterin expression and protein levels have been linked with cognitive and memory function, disrupted central nervous system lipid flux, as well as pathogenic brain structure; and its role in cardiometabolic disease suggests that it may be a link between insulin resistance, dyslipidemia, and AD. Here, we briefly highlight clusterin's relevance to AD by presenting existing evidence linking clusterin to AD and cardiometabolic disease, and discussing its potential utility as a biomarker for AD in the presence of obesity-related metabolic disease.

Associations between CLU polymorphisms and memory performance: The role of serum lipids in Alzheimer's disease

CLU encoding clusterin, has been reported to associate with Alzherimer's disease (AD) by genome-wide association studies (GWAS) based on Caucasian populations. Our previous case-control study has independently confirmed the disease association of CLU in Chinese population. Since little is known about the underlying mechanism of CLU in AD, we have conducted this study to investigate whether the genetic impact of CLU polymorphisms on cognitive functioning is via serum lipid's dysfunction. Three GWAS previously published CLU polymorphisms including rs2279590, rs11136000 and rs9331888, were genotyped in 689 subjects. Serum levels of triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were measured and tested as mediators. Delayed Word Recall Test (DWRT) was used to evaluate subjects' memory performance. Multiple mediation analysis, a nonparametric procedure to create confidence interval, was performed according to Preacher and Hayes's Bootstrapping method. Our findings suggested significant correlation between CLU polymorphism and DWRT scores for rs11136000 (p = 0.045) after adjustment for age, gender, body mass index, and APOEε4 status, with borderline significant correlation for rs2279590 (p = 0.058). Both T allele of rs11136000 and A allele of rs2279590 were negatively correlated with serum TG levels (p = 0.003; p = 0.001, separately). Moreover, A allele of rs2279590 was positively correlated with serum HDL-C levels (p = 0.015). Consistent with our hypotheses, the genetic impact of CLU polymorphisms on memory performance were partially mediated through TG (rs11136000 95% CI [-0.099,-0.003] and rs2279590 95% CI [-0.104, -0.004]), but not through HDL-C and LDL-C. Our findings indicate CLU polymorphisms may modify AD susceptibility through lipid metabolic pathway.

Single Nucleotide Polymorphisms in Alzheimer's Disease Risk Genes Are Associated with Intrinsic Connectivity in Middle Age

BACKGROUND

It is critical to identify individuals at risk for Alzheimer's disease (AD) earlier in the disease time course, such as middle age and preferably well prior to the onset of clinical symptoms, when intervention efforts may be more successful. Genome-wide association and candidate gene studies have identified single nucleotide polymorphisms (SNPs) in APOE, CLU, CR1, PICALM, and SORL1 that confer increased risk of AD.

OBJECTIVE

In the current study, we investigated the associations between SNPs in these genes and resting-state functional connectivity within the default mode network (DMN), frontoparietal network (FPN), and executive control network (ECN) in healthy, non-demented middle-aged adults (age 40 -60; N = 123; 74 females).

METHODS

Resting state networks of interest were identified through independent components analysis using a template-matching procedure and individual spatial maps and time courses were extracted using dual regression.

RESULTS

Within the posterior DMN, functional connectivity was associated with CR1 rs1408077 and CLU rs9331888 polymorphisms (p's < 0.05). FPN connectivity was associated with CR1 rs1408077, CLU rs1136000, SORL1 rs641120, and SORL1 rs689021 (p's < 0.05). Functional connectivity within the ECN was associated with the CLU rs11136000 (p < 0.05). There were no APOE- or PICALM-related differences in any of the networks investigated (p's > 0.05).

CONCLUSION

This is the first demonstration of the relationship between intrinsic network connectivity and AD risk alleles in CLU, CR1, and SORL1 in healthy, middle-aged adults. These SNPs should be considered in future investigations aimed at identifying potential preclinical biomarkers for AD.

Phosphodiesterase 4D Gene Modifies the Functional Network of Patients With Mild Cognitive Impairment and Alzheimer's Disease

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that is affected by several genetic variants. It has been demonstrated that genetic variants affect brain organization and function. In this study, using whole genome-wide association studies (GWAS), we analyzed the functional magnetic resonance imaging and genetic data from the Alzheimer’s Disease Neuroimaging Initiative dataset (ADNI) dataset and identified genetic variants associated with the topology of the functional brain network http://www.adni-info.org. We found three novel loci (rs2409627, rs9647533, and rs11955845) in an intron of the phosphodiesterase 4D (PDE4D) gene that contribute to abnormalities in the topological organization of the functional network. In particular, compared to the wild-type genotype, the subjects carrying the PDE4D variants had altered network properties, including a significantly reduced clustering coefficient, small-worldness, global and local efficiency, a significantly enhanced path length and a normalized path length. In addition, we found that all global brain network attributes were affected by PDE4D variants to different extents as the disease progressed. Additionally, brain regions with alterations in nodal efficiency due to the variations in PDE4D were predominant in the limbic lobe, temporal lobe and frontal lobes. PDE4D has a great effect on memory consolidation and cognition through long-term potentiation (LTP) effects and/or the promotion of inflammatory effects. PDE4D variants might be a main reasons underlyling for the abnormal topological properties and cognitive impairment. Furthermore, we speculated that PDE4D is a risk factor for neural degenerative diseases and provided important clues for the earlier detection and therapeutic intervention for AD.

Antenatal Hypoxia Accelerates the Onset of Alzheimer's Disease Pathology in 5xFAD Mouse Model

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder associated with cognitive impairment and later dementia among the elderly. Mounting evidence shows that adverse maternal environments during the fetal development increase the risk of diseases later in life including neurological disorders, and suggests an early origin in the development of AD-related dementia (ADRD) in utero. In the present study, we investigated the impact of antenatal hypoxia and fetal stress on the initiation of AD-related pathology in offspring of 5xFAD mice. We showed that fetal hypoxia significantly reduced brain and body weight in the fetal and the early postnatal period, which recovered in young adult mice. Using spontaneous Y-maze, novel object recognition (NOR), and open field (OF) tasks, we found that antenatal hypoxia exacerbated cognitive decline in offspring of 5xFAD compared with normoxia control. Of interest, fetal hypoxia did not alter intraneuronal soluble amyloid-β (Aβ) oligomer accumulation in the cortex and hippocampus in 5xFAD mouse offspring, indicating that antenatal hypoxia increased the vulnerability of the brain to synaptotoxic Aβ in the disease onset later in life. Consistent with the early occurrence of cognitive decline, we found synapse loss but not neuronal death in the cerebral cortex in 5xFAD but not wild-type (WT) offspring exposed to antenatal hypoxia. Furthermore, we also demonstrated that antenatal hypoxia significantly increased microglial number and activation, and reactive astrogliosis in the cerebral cortex in WT offspring. Moreover, antenatal hypoxia resulted in an exacerbated increase of microgliosis and astrogliosis in the early stage of AD in 5xFAD offspring. Together, our study reveals a causative link between fetal stress and the accelerated onset of AD-related pathology, and provides mechanistic insights into the developmental origin of aging-related neurodegenerative disorders.

Imaging Alzheimer's genetic risk using diffusion MRI: A systematic review

Diffusion magnetic resonance imaging (dMRI) is an imaging technique which probes the random motion of water molecules in tissues and has been widely applied to investigate changes in white matter microstructure in Alzheimer's Disease. This paper aims to systematically review studies that examined the effect of Alzheimer's risk genes on white matter microstructure. We assimilated findings from 37 studies and reviewed their diffusion pre-processing and analysis methods. Most studies estimate the diffusion tensor (DT) and compare derived quantitative measures such as fractional anisotropy and mean diffusivity between groups. Those with increased AD genetic risk are associated with reduced anisotropy and increased diffusivity across the brain, most notably the temporal and frontal lobes, cingulum and corpus callosum. Structural abnormalities are most evident amongst those with established Alzheimer's Disease. Recent studies employ signal representations and analysis frameworks beyond DT MRI but show that dMRI overall lacks specificity to disease pathology. However, as the field advances, these techniques may prove useful in pre-symptomatic diagnosis or staging of Alzheimer's disease.

The Structure and Function of α, β and γ-Secretase as Therapeutic Target Enzymes in the Development of Alzheimer’s Disease: A Review

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Alzheimer's disease is a progressive neurodegenerative disorder that affects the central nervous system. There are several factors that cause AD, like, intracellular hyperphosphorylated Tau tangles, collection of extracellular Amyloid-β42 and generation of reactive oxygen species due to mitochondrial dysfunction. This review analyses the most active target of AD and both types of AD-like early-onset AD and late-onset AD. BACE1 is a β-secretase involved in the cleavage of amyloid precursor protein and the pathogenesis of Alzheimer's disease. The presenilin proteins play a critical role in the pathogenesis of Alzheimer malady by intervening the intramembranous cleavage of amyloid precursor protein and the generation of amyloid β. The two homologous proteins PS1 and PS2 speak to the reactant subunits of particular γ-secretase edifices that intercede an assortment of cellular processes. Natural products are common molecular platforms in drug development in AD. Many natural products are being tested in various animal model systems for their role as a potential therapeutic target in AD. Presently, there are a few theories clarifying the early mechanisms of AD pathogenesis. Recently, research advancements in the field of nanotechnology, which utilize macromolecular strategies to make drugs in nanoscale measurements, offer nanotechnology-based diagnostic tools and drug carriers which are highly sensitive for effective drug targeting in the treatment of Alzheimer’s disease.

Gene expression and DNA methylation are extensively coordinated with MRI-based brain microstructural characteristics

Cognitive function relies on both molecular levels and cellular structures. However, systematic relationships between these two components of cognitive function, and their joint contribution to disease, are largely unknown. We utilize postmortem neuroimaging in tandem with gene expression and DNA methylation, from 222 deeply-phenotyped persons in a longitudinal aging cohort. Expression of hundreds of genes and methylation at thousands of loci are related to the microstructure of extensive regions of this same set of brains, as assessed by MRI. The genes linked to brain microstructure perform functions related to cell motility, transcriptional regulation and nuclear processes, and are selectively associated with Alzheimer’s phenotypes. Similar methodology can be applied to other diseases to identify their joint molecular and structural basis, or to infer molecular levels in the brain on the basis of neuroimaging for precision medicine applications.

The Radiogenomics of Late-onset Alzheimer Disease

Radiogenomics, defined as the integrated analysis of radiologic imaging and genetic data, is a well-established tool shown to augment neuroimaging in the clinical diagnosis, prognostication, and scientific study of late-onset Alzheimer disease (LOAD). Early work using candidate single nucleotide polymorphisms (SNPs) identified genetic variation in APOE, BIN1, CLU, and CR1 as key modifiers of brain structure and function using magnetic resonance imaging (MRI). More recently, polygenic risk scores used in conjunction with MRI and positron emission tomography have shown great promise as a risk-stratification tool for clinical trials and care-management decisions. In addition, recent work using multimodal MRI and positron emission tomography as proxies of LOAD progression has identified novel risk variants that are enhancing our understanding of LOAD pathophysiology and progression. Herein, we highlight key studies and trends in the radiogenomics of LOAD over the past two decades and their implications for clinical practice and scientific research.

Brain clusterin protein isoforms and mitochondrial localization

Clusterin (CLU), or apolipoprotein J (ApoJ), is the third most predominant genetic risk factor associated with late-onset Alzheimer’s disease (LOAD). In this study, we use multiple rodent and human brain tissue and neural cell models to demonstrate that CLU is expressed as multiple isoforms that have distinct cellular or subcellular localizations in the brain. Of particular significance, we identify a non-glycosylated 45 kDa CLU isoform (mitoCLU) that is localized to the mitochondrial matrix and expressed in both rodent and human neurons and astrocytes. In addition, we show that rodent mitoCLU is translated from a non-canonical CUG (Leu) start site in Exon 3, a site that coincides with an AUG (Met) in human CLU. Last, we reveal that mitoCLU is present at the gene and protein level in the currently available CLU^–/– mouse model. Collectively, these data provide foundational knowledge that is integral in elucidating the relationship between CLU and the development of LOAD.

Evaluation of the Common Molecular Basis in Alzheimer's and Parkinson's Diseases

Alzheimer's disease (AD) and Parkinson's disease (PD) are the most common neurodegenerative disorders related to aging. Though several risk factors are shared between these two diseases, the exact relationship between them is still unknown. In this paper, we analyzed how these two diseases relate to each other from the genomic, epigenomic, and transcriptomic viewpoints. Using an extensive literature mining, we first accumulated the list of genes from major genome-wide association (GWAS) studies. Based on these GWAS studies, we observed that only one gene (HLA-DRB5) was shared between AD and PD. A subsequent literature search identified a few other genes involved in these two diseases, among which SIRT1 seemed to be the most prominent one. While we listed all the miRNAs that have been previously reported for AD and PD separately, we found only 15 different miRNAs that were reported in both diseases. In order to get better insights, we predicted the gene co-expression network for both AD and PD using network analysis algorithms applied to two GEO datasets. The network analysis revealed six clusters of genes related to AD and four clusters of genes related to PD; however, there was very low functional similarity between these clusters, pointing to insignificant similarity between AD and PD even at the level of affected biological processes. Finally, we postulated the putative epigenetic regulator modules that are common to AD and PD.

Data-Driven Analysis of Age, Sex, and Tissue Effects on Gene Expression Variability in Alzheimer's Disease

Alzheimer's disease (AD) has been categorized by the Centers for Disease Control and Prevention (CDC) as the 6^th leading cause of death in the United States. AD is a significant health-care burden because of its increased occurrence (specifically in the elderly population), and the lack of effective treatments and preventive methods. With an increase in life expectancy, the CDC expects AD cases to rise to 15 million by 2060. Aging has been previously associated with susceptibility to AD, and there are ongoing efforts to effectively differentiate between normal and AD age-related brain degeneration and memory loss. AD targets neuronal function and can cause neuronal loss due to the buildup of amyloid-beta plaques and intracellular neurofibrillary tangles. Our study aims to identify temporal changes within gene expression profiles of healthy controls and AD subjects. We conducted a meta-analysis using publicly available microarray expression data from AD and healthy cohorts. For our meta-analysis, we selected datasets that reported donor age and gender, and used Affymetrix and Illumina microarray platforms (8 datasets, 2,088 samples). Raw microarray expression data were re-analyzed, and normalized across arrays. We then performed an analysis of variance, using a linear model that incorporated age, tissue type, sex, and disease state as effects, as well as study to account for batch effects, and included binary interactions between factors. Our results identified 3,735 statistically significant (Bonferroni adjusted p < 0.05) gene expression differences between AD and healthy controls, which we filtered for biological effect (10% two-tailed quantiles of mean differences between groups) to obtain 352 genes. Interesting pathways identified as enriched comprised of neurodegenerative diseases pathways (including AD), and also mitochondrial translation and dysfunction, synaptic vesicle cycle and GABAergic synapse, and gene ontology terms enrichment in neuronal system, transmission across chemical synapses and mitochondrial translation. Overall our approach allowed us to effectively combine multiple available microarray datasets and identify gene expression differences between AD and healthy individuals including full age and tissue type considerations. Our findings provide potential gene and pathway associations that can be targeted to improve AD diagnostics and potentially treatment or prevention.

Clusterin in Alzheimer's Disease: Mechanisms, Genetics, and Lessons From Other Pathologies

Clusterin (CLU) or APOJ is a multifunctional glycoprotein that has been implicated in several physiological and pathological states, including Alzheimer's disease (AD). With a prominent extracellular chaperone function, additional roles have been discussed for clusterin, including lipid transport and immune modulation, and it is involved in pathways common to several diseases such as cell death and survival, oxidative stress, and proteotoxic stress. Although clusterin is normally a secreted protein, it has also been found intracellularly under certain stress conditions. Multiple hypotheses have been proposed regarding the origin of intracellular clusterin, including specific biogenic processes leading to alternative transcripts and protein isoforms, but these lines of research are incomplete and contradictory. Current consensus is that intracellular clusterin is most likely to have exited the secretory pathway at some point or to have re-entered the cell after secretion. Clusterin's relationship with amyloid beta (Aβ) has been of great interest to the AD field, including clusterin's apparent role in altering Aβ aggregation and/or clearance. Additionally, clusterin has been more recently identified as a mediator of Aβ toxicity, as evidenced by the neuroprotective effect of CLU knockdown and knockout in rodent and human iPSC-derived neurons. CLU is also the third most significant genetic risk factor for late onset AD and several variants have been identified in CLU. Although the exact contribution of these variants to altered AD risk is unclear, some have been linked to altered CLU expression at both mRNA and protein levels, altered cognitive and memory function, and altered brain structure. The apparent complexity of clusterin's biogenesis, the lack of clarity over the origin of the intracellular clusterin species, and the number of pathophysiological functions attributed to clusterin have all contributed to the challenge of understanding the role of clusterin in AD pathophysiology. Here, we highlight clusterin's relevance to AD by discussing the evidence linking clusterin to AD, as well as drawing parallels on how the role of clusterin in other diseases and pathways may help us understand its biological function(s) in association with AD.

A Network of Genetic Effects on Non-Demented Cognitive Aging: Alzheimer's Genetic Risk (CLU + CR1 + PICALM) Intensifies Cognitive Aging Genetic Risk (COMT + BDNF) Selectively for APOEɛ4 Carriers

BACKGROUND

Trajectories of complex neurocognitive phenotypes in preclinical aging may be produced differentially through selective and interactive combinations of genetic risk.

OBJECTIVE

We organize three possible combinations into a "network" of genetic risk indices derived from polymorphisms associated with normal and impaired cognitive aging, as well as Alzheimer's disease (AD). Specifically, we assemble and examine three genetic clusters relevant to non-demented cognitive trajectories: 1) Apolipoprotein E (APOE), 2) a Cognitive Aging Genetic Risk Score (CA-GRS; Catechol-O-methyltransferase + Brain-derived neurotrophic factor), and 3) an AD-Genetic Risk Score (AD-GRS; Clusterin + Complement receptor 1 + Phosphatidylinositol-binding clathrin assembly protein).

METHOD

We use an accelerated longitudinal design (n = 634; age range = 55-95 years) to test whether AD-GRS (low versus high) moderates the effect of increasing CA-GRS risk on executive function (EF) performance and change as stratified by APOE status (ɛ4+ versus ɛ4-).

RESULTS

APOEɛ4 carriers with high AD-GRS had poorer EF performance at the centering age (75 years) and steeper 9-year decline with increasing CA-GRS but this association was not present in APOEɛ4 carriers with low AD-GRS.

CONCLUSIONS

APOEɛ4 carriers with high AD-GRS are at elevated risk of cognitive decline when they also possess higher CA-GRS risk. Genetic risk from both common cognitive aging and AD-related indices may interact in intensification networks to differentially predict (1) level and trajectories of EF decline and (2) potential selective vulnerability for transitions into impairment and dementia.

Spatial correlations exploitation based on nonlocal voxel-wise GWAS for biomarker detection of AD

Potential biomarker detection is a crucial area of study for the prediction, diagnosis, and monitoring of Alzheimer's disease (AD). The voxelwise genome-wide association study (vGWAS) is widely used in imaging genomics studies that is usually applied to the detection of AD biomarkers in both imaging and genetic data. However, performing vGWAS remains a challenge because of the computational complexity of the technique and our ignorance of the spatial correlations within the imaging data. In this paper, we propose a novel method based on the exploitation of spatial correlations that may help to detect potential AD biomarkers using a fast vGWAS. To incorporate spatial correlations, we applied a nonlocal method that supposed that a given voxel could be represented by weighting the sum of the other voxels. Three commonly used weighting methods were adopted to calculate the weights among different voxels in this study. Then, a fast vGWAS approach was used to assess the association between the image and the genetic data. The proposed method was estimated using both simulated and real data. In the simulation studies, we designed a set of experiments to evaluate the effectiveness of the nonlocal method for incorporating spatial correlations in vGWAS. The experiments showed that incorporating spatial correlations by the nonlocal method could improve the detecting accuracy of AD biomarkers. For real data, we successfully identified three genes, namely, ANK3, MEIS2, and TLR4, which have significant associations with mental retardation, learning disabilities and age according to previous research. These genes have profound impacts on AD or other neurodegenerative diseases. Our results indicated that our method might be an effective and valuable tool for detecting potential biomarkers of AD.

Spatial transcriptomic survey of human embryonic cerebral cortex by single-cell RNA-seq analysis

The cellular complexity of human brain development has been intensively investigated, although a regional characterization of the entire human cerebral cortex based on single-cell transcriptome analysis has not been reported. Here, we performed RNA-seq on over 4,000 individual cells from 22 brain regions of human mid-gestation embryos. We identified 29 cell sub-clusters, which showed different proportions in each region and the pons showed especially high percentage of astrocytes. Embryonic neurons were not as diverse as adult neurons, although they possessed important features of their destinies in adults. Neuron development was unsynchronized in the cerebral cortex, as dorsal regions appeared to be more mature than ventral regions at this stage. Region-specific genes were comprehensively identified in each neuronal sub-cluster, and a large proportion of these genes were neural disease related. Our results present a systematic landscape of the regionalized gene expression and neuron maturation of the human cerebral cortex.

Recent Progress in Alzheimer's Disease Research, Part 2: Genetics and Epidemiology

This is the second part of a three-part review series reviewing the most important advances in Alzheimer's disease (AD) research since 2010. This review covers the latest research on genetics and epidemiology. Epidemiological and genetic studies are revealing important insights into the etiology of, and factors that contribute to AD, as well as areas of priority for research into mechanisms and interventions. The widespread adoption of genome wide association studies has provided compelling evidence of the genetic complexity of AD with genes associated with such diverse physiological function as immunity and lipid metabolism being implicated in AD pathogenesis.

Untangling Genetic Risk for Alzheimer's Disease

Alzheimer's disease (AD) is a genetically heterogeneous neurodegenerative disorder caused by fully penetrant single gene mutations in a minority of cases, while the majority of cases are sporadic or show modest familial clustering. These cases are of late onset and likely result from the interaction of many genes and the environment. More than 30 loci have been implicated in AD by a combination of linkage, genome-wide association, and whole genome/exome sequencing. We have learned from these studies that perturbations in endolysosomal, lipid metabolism, and immune response pathways substantially contribute to sporadic AD pathogenesis. We review here current knowledge about functions of AD susceptibility genes, highlighting cells of the myeloid lineage as drivers of at least part of the genetic component in late-onset AD. Although targeted resequencing utilized for the identification of causal variants has discovered coding mutations in some AD-associated genes, a lot of risk variants lie in noncoding regions. Here we discuss the use of functional genomics approaches that integrate transcriptomic, epigenetic, and endophenotype traits with systems biology to annotate genetic variants, and to facilitate discovery of AD risk genes. Further validation in cell culture and mouse models will be necessary to establish causality for these genes. This knowledge will allow mechanism-based design of novel therapeutic interventions in AD and promises coherent implementation of treatment in a personalized manner.

Autophagy and Alzheimer's Disease: From Molecular Mechanisms to Therapeutic Implications

Alzheimer’s disease (AD) is the most common cause of progressive dementia in the elderly. It is characterized by a progressive and irreversible loss of cognitive abilities and formation of senile plaques, composed mainly of amyloid β (Aβ), and neurofibrillary tangles (NFTs), composed of tau protein, in the hippocampus and cortex of afflicted humans. In brains of AD patients the metabolism of Aβ is dysregulated, which leads to the accumulation and aggregation of Aβ. Metabolism of Aβ and tau proteins is crucially influenced by autophagy. Autophagy is a lysosome-dependent, homeostatic process, in which organelles and proteins are degraded and recycled into energy. Thus, dysfunction of autophagy is suggested to lead to the accretion of noxious proteins in the AD brain. In the present review, we describe the process of autophagy and its importance in AD. Additionally, we discuss mechanisms and genes linking autophagy and AD, i.e., the mTOR pathway, neuroinflammation, endocannabinoid system, ATG7, BCL2, BECN1, CDK5, CLU, CTSD, FOXO1, GFAP, ITPR1, MAPT, PSEN1, SNCA, UBQLN1, and UCHL1. We also present pharmacological agents acting via modulation of autophagy that may show promise in AD therapy. This review updates our knowledge on autophagy mechanisms proposing novel therapeutic targets for the treatment of AD.

Memory Resilience to Alzheimer's Genetic Risk: Sex Effects in Predictor Profiles

Objectives

Apolipoprotein E (APOE) ɛ4 and Clusterin (CLU) C alleles are risk factors for Alzheimer's disease (AD) and episodic memory (EM) decline. Memory resilience occurs when genetically at-risk adults perform at high and sustained levels. We investigated whether (a) memory resilience to AD genetic risk is predicted by biological and other risk markers and (b) the prediction profiles vary by sex and AD risk variant.

Method

Using a longitudinal sample of nondemented adults (n = 642, aged 53-95) we focused on memory resilience (over 9 years) to 2 AD risk variants (APOE, CLU). Growth mixture models classified resilience. Random forest analysis, stratified by sex, tested the predictive importance of 22 nongenetic risk factors from 5 domains (n = 24-112).

Results

For both sexes, younger age, higher education, stronger grip, and everyday novel cognitive activity predicted memory resilience. For women, 9 factors from functional, health, mobility, and lifestyle domains were also predictive. For men, only fewer depressive symptoms was an additional important predictor. The prediction profiles were similar for APOE and CLU.

Discussion

Although several factors predicted resilience in both sexes, a greater number applied only to women. Sex-specific mechanisms and intervention targets are implied.

Signs and symptoms preceding the diagnosis of Alzheimer's disease: a systematic scoping review of literature from 1937 to 2016

OBJECTIVE

Late diagnosis of Alzheimer's disease (AD) may be due to diagnostic uncertainties. We aimed to determine the sequence and timing of the appearance of established early signs and symptoms in people who are subsequently diagnosed with AD.

METHODS

We used systematic review methodology to investigate the existing literature. Articles were reviewed in May 2016, using the following databases: MEDLINE, PsycINFO, CINAHL, British Nursing Index, PubMed central and the Cochrane library, with no language restriction. Data from the included articles were extracted independently by two authors and quality assessment was undertaken with the quality assessment and diagnostic accuracy tool-2 (QUADAS tool-2 quality assessment tool).

RESULTS

We found that depression and cognitive impairment were the first symptoms to appear in 98.5% and 99.1% of individuals in a study with late-onset AD (LOAD) and 9% and 80%, respectively, in early-onset AD (EOAD). Memory loss presented early and was experienced 12 years before the clinically defined AD dementia in the LOAD. However, the rapidly progressive late-onset AD presented predominantly with 35 non-established focal symptoms and signs including myoclonus (75%), disturbed gait (66%) and rigidity. These were misdiagnosed as symptoms of Creutzfeldt-Jacob disease (CJD) in all the cases. The participant with the lowest mini-mental state examination score of 25 remained stable for 2 years, which is consistent with the score of the healthy family members.

CONCLUSIONS

The findings of this review suggest that neurological and depressive behaviours are an early occurrence in EOAD with depressive and cognitive symptoms in the measure of semantic memory and conceptual formation in LOAD. Misdiagnosis of rapidly progressive AD as CJD and the familial memory score can be confounding factors while establishing a diagnosis. However, the study was limited by the fact that each one of the findings was based on a single study.

Reduced Cerebral White Matter Integrity Assessed by DTI in Cognitively Normal H63D-HFE Polymorphism Carriers

BACKGROUND AND PURPOSE

The H63D-HFE single nucleotide polymorphism (SNP) has been associated with brain iron dysregulation; however, the emergent role of this missense variant in brain structure and function has yet to be determined. Previous work has demonstrated that HFE SNP carriers have reduced white matter magnetic resonance imaging (MRI) proton relaxation rates. The mechanism by which white matter alterations perturb MRI relaxation is unknown as is how these metrics are related to myelin integrity.

METHODS

Fifteen subjects heterozygous for the HFE-H63D SNP and 25 controls with wild-type HFE had diffusion-weighted, anatomical MRIs taken, and underwent cognitive assessment. Fractional anisotropy (FA), mean diffusion (MD), and mode of anisotropy (MO) were calculated from the diffusion dataset to investigate the relationship between the H63D-HFE SNP and myelin integrity.

RESULTS

A decrease in FA, an increase in MD, and an increase in MO are demonstrated in multiple H63D-HFE polymorphism carrier white matter tracts. Regions with altered diffusion metrics are notably located in heavily myelinated white matter association fibers, such as the anterior corona radiata and longitudinal fasciculi.

CONCLUSIONS

The MRI data presented here demonstrate that H63D-HFE polymorphism carriers have diffusivity changes in white matter compared to wild-type subjects. The reduced integrity white matter tracts in H63D-HFE carriers are hypothesized to be related to increased susceptibility of these late-myelinating regions to cellular stress induced by oligodendrocyte iron dyshomeostasis.

Revolution of Resting-State Functional Neuroimaging Genetics in Alzheimer's Disease

The quest to comprehend genetic, biological, and symptomatic heterogeneity underlying Alzheimer's disease (AD) requires a deep understanding of mechanisms affecting complex brain systems. Neuroimaging genetics is an emerging field that provides a powerful way to analyze and characterize intermediate biological phenotypes of AD. Here, we describe recent studies showing the differential effect of genetic risk factors for AD on brain functional connectivity in cognitively normal, preclinical, prodromal, and AD dementia individuals. Functional neuroimaging genetics holds particular promise for the characterization of preclinical populations; target populations for disease prevention and modification trials. To this end, we emphasize the need for a paradigm shift towards integrative disease modeling and neuroimaging biomarker-guided precision medicine for AD and other neurodegenerative diseases.

Taming Alzheimer's disease: New perspectives, newer horizons

Alzheimer's disease (AD) is the leading cause of dementia. However, current therapies do not prevent progression of the disease. New research into the pathogenesis of the disease has brought about a greater understanding of the "amyloid cascade" and associated receptor abnormalities, the role of genetic factors, and revealed that the disease process commences 10 to 20 years prior to the appearance of clinical signs. This greater understanding of the disease has prompted development of novel disease-modifying therapies (DMTs) which may prevent onset or delay progression of the disease. Using genetic biomarkers like apolipoprotein E (ApoE) ε4, biochemical biomarkers like cerebrospinal fluid (CSF) amyloid and tau proteins, and imaging biomarkers like magnetic resonance imaging (MRI) and positron emission tomography (PET), it is now possible to detect preclinical AD and also monitor its progression in asymptomatic people. These biomarkers can be used in the selection of high-risk populations for clinical trials and also to monitor the efficacy and side-effects of DMT. To validate and standardize these biomarkers and select the most reliable, repeatable, easily available, cost-effective and complementary options is the challenge ahead.

Multimodal Brain Imaging Reveals Structural Differences in Alzheimer's Disease Polygenic Risk Carriers: A Study in Healthy Young Adults

BACKGROUND

Recent genome-wide association studies have identified genetic loci that jointly make a considerable contribution to risk of developing Alzheimer's disease (AD). Because neuropathological features of AD can be present several decades before disease onset, we investigated whether effects of polygenic risk are detectable by neuroimaging in young adults. We hypothesized that higher polygenic risk scores (PRSs) for AD would be associated with reduced volume of the hippocampus and other limbic and paralimbic areas. We further hypothesized that AD PRSs would affect the microstructure of fiber tracts connecting the hippocampus with other brain areas.

METHODS

We analyzed the association between AD PRSs and brain imaging parameters using T1-weighted structural (n = 272) and diffusion-weighted scans (n = 197).

RESULTS

We found a significant association between AD PRSs and left hippocampal volume, with higher risk associated with lower left hippocampal volume (p = .001). This effect remained when the APOE gene was excluded (p = .031), suggesting that the relationship between hippocampal volume and AD is the result of multiple genetic factors and not exclusively variability in the APOE gene. The diffusion tensor imaging analysis revealed that fractional anisotropy of the right cingulum was inversely correlated with AD PRSs (p = .009). We thus show that polygenic effects of AD risk variants on brain structure can already be detected in young adults.

CONCLUSIONS

This finding paves the way for further investigation of the effects of AD risk variants and may become useful for efforts to combine genotypic and phenotypic data for risk prediction and to enrich future prevention trials of AD.

Immunity factor contributes to altered brain functional networks in individuals at risk for Alzheimer's disease: Neuroimaging-genetic evidence

Clusterin (CLU) is recognized as a secreted protein that is related to the processes of inflammation and immunity in the pathogenesis of Alzheimer's disease (AD). The effects of the risk variant of the C allele at the rs11136000 locus of the CLU gene are associated with variations in the brain structure and function. However, the relationship of the CLU-C allele to architectural disruptions in resting-state networks in amnestic mild cognitive impairment (aMCI) subjects (i.e., individuals with elevated risk of AD) remains relatively unknown. Using resting-state functional magnetic resonance imaging and an imaging genetic approach, this study investigated whether individual brain functional networks, i.e., the default mode network (DMN) and the task-positive network, were modulated by the CLU-C allele (rs11136000) in 50 elderly participants, including 26 aMCI subjects and 24 healthy controls. CLU-by-aMCI interactions were associated with the information-bridging regions between resting-state networks rather than with the DMN itself, especially in cortical midline regions. Interestingly, the complex communications between resting-state networks were enhanced in aMCI subjects with the CLU rs11136000 CC genotype and were modulated by the degree of memory impairment, suggesting a reconstructed balance of the resting-state networks in these individuals with an elevated risk of AD. The neuroimaging-genetic evidence indicates that immunity factors may contribute to alterations in brain functional networks in aMCI. These findings add to the evidence that the CLU gene may represent a potential therapeutic target for slowing disease progression in AD.

Clusterin expression is upregulated following acute head injury and localizes to astrocytes in old head injury

There is mounting evidence linking traumatic brain injury (TBI) to neurodegeneration. Clusterin (apolipoprotein J or ApoJ) is a complement inhibitor that appears to have a neuroprotective effect in response to tissue damage and has been reported to be upregulated in Alzheimer's disease. Here we investigated the time course and cellular expression pattern of clusterin in human TBI. Tissue from 32 patients with TBI of varying survival times (from under 30 min to 10 months) was examined using immunohistochemistry for clusterin alongside other markers of neurodegeneration and neuroinflammation. TBI cases were compared to ischemic brain damage, Alzheimer's disease and controls. Double immunofluorescence was carried out in order to examine cellular expression. Clusterin was initially expressed in an axonal location less than 30 min following TBI and increased in intensity and the frequency of deposits with increasing survival time up to 24 h, after which it appeared to reduce in intensity but was still evident several weeks after injury. Clusterin was first evident in astrocytes after 45 min, being increasingly seen up to 48 h but remaining intense in TBI cases with long survival times. Our results suggest clusterin plays a role in modulating the inflammatory response of acute and chronic TBI and that it is a useful marker for TBI, particularly in cases with short survival times. Its prominent accumulation in astrocytes, alongside a mounting inflammatory response and activation of microglial cells supports a potential role in the neurodegenerative changes that occur as a result of TBI.

Possible relationship between common genetic variation and white matter development in a pilot study of preterm infants

BACKGROUND

The consequences of preterm birth are a major public health concern with high rates of ensuing multisystem morbidity, and uncertain biological mechanisms. Common genetic variation may mediate vulnerability to the insult of prematurity and provide opportunities to predict and modify risk.

OBJECTIVE

To gain novel biological and therapeutic insights from the integrated analysis of magnetic resonance imaging and genetic data, informed by prior knowledge.

METHODS

We apply our previously validated pathway-based statistical method and a novel network-based method to discover sources of common genetic variation associated with imaging features indicative of structural brain damage.

RESULTS

Lipid pathways were highly ranked by Pathways Sparse Reduced Rank Regression in a model examining the effect of prematurity, and PPAR (peroxisome proliferator-activated receptor) signaling was the highest ranked pathway once degree of prematurity was accounted for. Within the PPAR pathway, five genes were found by Graph Guided Group Lasso to be highly associated with the phenotype: aquaporin 7 (AQP7), malic enzyme 1, NADP(+)-dependent, cytosolic (ME1), perilipin 1 (PLIN1), solute carrier family 27 (fatty acid transporter), member 1 (SLC27A1), and acetyl-CoA acyltransferase 1 (ACAA1). Expression of four of these (ACAA1, AQP7, ME1, and SLC27A1) is controlled by a common transcription factor, early growth response 4 (EGR-4).

CONCLUSIONS

This suggests an important role for lipid pathways in influencing development of white matter in preterm infants, and in particular a significant role for interindividual genetic variation in PPAR signaling.

Apolipoprotein E and Clusterin can magnify effects of personality vulnerability on declarative memory performance in non-demented older adults

OBJECTIVES

Recent research has linked psychological (personality) factors and specific genetic risk polymorphisms to performance on neurocognitive phenotypes. We examined whether episodic or semantic memory performance is associated with (a) three personality traits (i.e. neuroticism, extraversion, and openness to experience), (b) two neurodegenerative-related polymorphisms (i.e. Apolipoprotein E (APOE; rs7412; rs429358), Clusterin (CLU; rs11136000)), and (c) cross-domain risk interactions (magnification effects).

METHODS

Linear growth models were examined to test independent associations between personality traits and declarative memory performance, and potential interaction effects with APOE and CLU genetic risk. Normal older adults (n = 282) with personality and genetic data from the Victoria Longitudinal Study were included at baseline and for up to 14 years of follow-up.

RESULTS

First, we observed that higher openness to experience levels were associated with better episodic and semantic memory. Second, three significant gene × personality interactions were associated with poorer memory performance at baseline. These synergistic effects are: (a) APOE allelic risk (ε4+) carriers with lower openness to experience levels, (b) CLU (no risk: T/T) homozygotes with higher extraversion levels, and (c) CLU (no risk: T/T) homozygotes with lower neuroticism levels.

CONCLUSIONS

Specific neurodegenerative-related genetic polymorphisms (i.e. APOE and CLU) moderate and magnify the risk contributed by selected personality trait levels (i.e. openness to experience, extraversion) on declarative memory performance in non-demented aging. Future research could target interactions of other personality traits and genetic polymorphisms in different clinical populations to predict other neurocognitive deficits or transitions to cognitive impairment and dementia.

An Alzheimer's Disease Genetic Risk Score Predicts Longitudinal Thinning of Hippocampal Complex Subregions in Healthy Older Adults

Variants at 21 genetic loci have been associated with an increased risk for Alzheimer's disease (AD). An important unresolved question is whether multiple genetic risk factors can be combined to increase the power to detect changes in neuroimaging biomarkers for AD. We acquired high-resolution structural images of the hippocampus in 66 healthy, older human subjects. For 45 of these subjects, longitudinal 2-year follow-up data were also available. We calculated an additive AD genetic risk score for each participant and contrasted this with a weighted risk score (WRS) approach. Each score included APOE (apolipoprotein E), CLU (clusterin), PICALM (phosphatidylinositol binding clathrin assembly protein), and family history of AD. Both unweighted risk score (URS) and WRS correlated strongly with the percentage change in thickness across the whole hippocampal complex (URS: r = -0.40; p = 0.003; WRS: r = -0.25, p = 0.048), driven by a strong relationship to entorhinal cortex thinning (URS: r = -0.35; p = 0.009; WRS: r = -0.35, p = 0.009). By contrast, at baseline the risk scores showed no relationship to thickness in any hippocampal complex subregion. These results provide compelling evidence that polygenic AD risk scores may be especially sensitive to structural change over time in regions affected early in AD, like the hippocampus and adjacent entorhinal cortex. This work also supports the paradigm of studying genetic risk for disease in healthy volunteers. Together, these findings will inform clinical trial design by supporting the idea that genetic prescreening in healthy control subjects can be useful to maximize the ability to detect an effect on a longitudinal neuroimaging endpoint, like hippocampal complex cortical thickness.