Association between NME8 locus polymorphism and cognitive decline, cerebrospinal fluid and neuroimaging biomarkers in Alzheimer's disease

Exploring the Genetic Landscape of Mild Behavioral Impairment as an Early Marker of Cognitive Decline: An Updated Review Focusing on Alzheimer's Disease

The clinical features and pathophysiology of neuropsychiatric symptoms (NPSs) in dementia have been extensively studied. However, the genetic architecture and underlying neurobiological mechanisms of NPSs at preclinical stages of cognitive decline and Alzheimer's disease (AD) remain largely unknown. Mild behavioral impairment (MBI) represents an at-risk state for incident cognitive impairment and is defined by the emergence of persistent NPSs among non-demented individuals in later life. These NPSs include affective dysregulation, decreased motivation, impulse dyscontrol, abnormal perception and thought content, and social inappropriateness. Accumulating evidence has recently begun to shed more light on the genetic background of MBI, focusing on its potential association with genetic factors related to AD. The Apolipoprotein E (APOE) genotype and the MS4A locus have been associated with affective dysregulation, ZCWPW1 with social inappropriateness and psychosis, BIN1 and EPHA1 with psychosis, and NME8 with apathy. The association between MBI and polygenic risk scores (PRSs) in terms of AD dementia has been also explored. Potential implicated mechanisms include neuroinflammation, synaptic dysfunction, epigenetic modifications, oxidative stress responses, proteosomal impairment, and abnormal immune responses. In this review, we summarize and critically discuss the available evidence on the genetic background of MBI with an emphasis on AD, aiming to gain insights into the potential underlying neurobiological mechanisms, which till now remain largely unexplored. In addition, we propose future areas of research in this emerging field, with the aim to better understand the molecular pathophysiology of MBI and its genetic links with cognitive decline.

Identification and validation of hub genes and molecular classifications associated with chronic myeloid leukemia

Background

Chronic myeloid leukemia (CML) is a kind of malignant blood tumor, which is prone to drug resistance and relapse. This study aimed to identify novel diagnostic and therapeutic targets for CML.

Methods

Differentially expressed genes (DEGs) were obtained by differential analysis of the CML cohort in the GEO database. Weighted gene co-expression network analysis (WGCNA) was used to identify CML-related co-expressed genes. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to screen hub genes and construct a risk score model based on hub genes. Consensus clustering algorithm was used for the identification of molecular subtypes. Clinical samples and in vitro experiments were used to verify the expression and biological function of hub genes.

Results

A total of 378 DEGs were identified by differential analysis. 369 CML-related genes were identified by WGCNA analysis, which were mainly enriched in metabolism-related signaling pathways. In addition, CML-related genes are mainly involved in immune regulation and anti-tumor immunity, suggesting that CML has some immunodeficiency. Immune infiltration analysis confirmed the reduced infiltration of immune killer cells such as CD8+ T cells in CML samples. 6 hub genes (LINC01268, NME8, DMXL2, CXXC5, SCD and FBN1) were identified by LASSO regression analysis. The receiver operating characteristic (ROC) curve confirmed the high diagnostic value of the hub genes in the analysis and validation cohorts, and the risk score model further improved the diagnostic accuracy. hub genes were also associated with cell proliferation, cycle, and metabolic pathway activity. Two molecular subtypes, Cluster A and Cluster B, were identified based on hub gene expression. Cluster B has a lower risk score, higher levels of CD8+ T cell and activated dendritic cell infiltration, and immune checkpoint expression, and is more sensitive to commonly used tyrosine kinase inhibitors. Finally, our clinical samples validated the expression and diagnostic efficacy of hub genes, and the knockdown of LINC01268 inhibited the proliferation of CML cells, and promoted apoptosis.

Conclusion

Through WGCNA analysis and LASSO regression analysis, our study provides a new target for CML diagnosis and treatment, and provides a basis for further CML research.

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.

Association of the top 20 Alzheimer's disease risk genes with [18F]flortaucipir PET

Introduction

We previously reported genetic associations of the top Alzheimer's disease (AD) risk alleles with amyloid deposition and neurodegeneration. Here, we report the association of these variants with [18F]flortaucipir standardized uptake value ratio (SUVR).

Methods

We analyzed the [18F]flortaucipir scans of 352 cognitively normal (CN), 160 mild cognitive impairment (MCI), and 54 dementia (DEM) participants from Alzheimer's Disease Neuroimaging Initiative (ADNI)2 and 3. We ran step-wise regression with log-transformed [18F]flortaucipir meta-region of interest SUVR as the outcome measure and genetic variants, age, sex, and apolipoprotein E (APOE) ε4 as predictors. The results were visualized using parametric mapping at familywise error cluster-level-corrected P < .05.

Results

APOE ε4 showed significant (P < .05) associations with tau deposition across all disease stages. Other significantly associated genes include variants in ABCA7 in CN, CR1 in MCI, BIN1 and CASS4 in MCI and dementia participants.

Discussion

We found significant associations to tau deposition for ABCA7, BIN1, CASS4, and CR1, in addition to APOE ε4. These four variants have been previously associated with tau metabolism through model systems.

The Differential Influence of Immune, Endocytotic, and Lipid Metabolism Genes on Amyloid Deposition and Neurodegeneration in Subjects at Risk of Alzheimer's Disease

BACKGROUND

Over 20 single-nucleotide polymorphisms (SNPs) are associated with increased risk of Alzheimer's disease (AD). We categorized these loci into immunity, lipid metabolism, and endocytosis pathways, and associated the polygenic risk scores (PRS) calculated, with AD biomarkers in mild cognitive impairment (MCI) subjects.

OBJECTIVE

The aim of this study was to identify associations between pathway-specific PRS and AD biomarkers in patients with MCI and healthy controls.

METHODS

AD biomarkers ([18F]Florbetapir-PET SUVR, FDG-PET SUVR, hippocampal volume, CSF tau and amyloid-β levels) and neurocognitive tests scores were obtained in 258 healthy controls and 451 MCI subjects from the ADNI dataset at baseline and at 24-month follow up. Pathway-related (immunity, lipid metabolism, and endocytosis) and total polygenic risk scores were calculated from 20 SNPs. Multiple linear regression analysis was used to test predictive value of the polygenic risk scores over longitudinal biomarker and cognitive changes.

RESULTS

Higher immune risk score was associated with worse cognitive measures and reduced glucose metabolism. Higher lipid risk score was associated with increased amyloid deposition and cortical hypometabolism. Total, immune, and lipid scores were associated with significant changes in cognitive measures, amyloid deposition, and brain metabolism.

CONCLUSION

Polygenic risk scores highlights the influence of specific genes on amyloid-dependent and independent pathways; and these pathways could be differentially influenced by lipid and immune scores respectively.

Association of Alzheimer's Disease Genetic Risk Loci with Cognitive Performance and Decline: A Systematic Review

The association of Apolipoprotein E (APOE) with late-onset Alzheimer's disease (LOAD) and cognitive endophenotypes of aging has been widely investigated. There is increasing interest in evaluating the association of other LOAD risk loci with cognitive performance and decline. The results of these studies have been inconsistent and inconclusive. We conducted a systematic review of studies investigating the association of non-APOE LOAD risk loci with cognitive performance in older adults. Studies published from January 2009 to April 2018 were identified through a PubMed database search using keywords and by scanning reference lists. Studies were included if they were either cross-sectional or longitudinal in design, included at least one genome-wide significant LOAD risk loci or a genetic risk score, and had one objective measure of cognition. Quality assessment of the studies was conducted using the quality of genetic studies (Q-Genie) tool. Of 2,466 studies reviewed, 49 met inclusion criteria. Fifteen percent of the associations between non-APOE LOAD risk loci and cognition were significant. However, these associations were not replicated across studies, and the majority were rendered non-significant when adjusting for multiple testing. One-third of the studies included genetic risk scores, and these were typically significant only when APOE was included. The findings of this systematic review do not support a consistent association between individual non-APOE LOAD risk and cognitive performance or decline. However, evidence suggests that aggregate LOAD genetic risk exerts deleterious effects on decline in episodic memory and global cognition.

Association of Polygenic Risk Score with Age at Onset and Cerebrospinal Fluid Biomarkers of Alzheimer's Disease in a Chinese Cohort

To evaluate whether the polygenic profile modifies the development of sporadic Alzheimer's disease (sAD) and pathological biomarkers in cerebrospinal fluid (CSF), 462 sAD patients and 463 age-matched cognitively normal (CN) controls were genotyped for 35 single-nucleotide polymorphisms (SNPs) that are significantly associated with sAD. Then, the alleles found to be associated with sAD were used to build polygenic risk score (PRS) models to represent the genetic risk. Receiver operating characteristic (ROC) analyses and the Cox proportional hazards model were used to evaluate the predictive value of PRS for the sAD risk and age at onset. We measured the CSF levels of Aβ42, Aβ42/Aβ40, total tau (T-tau), and phosphorylated tau (P-tau) in a subgroup (60 sAD and 200 CN participants), and analyzed their relationships with the PRSs. We found that 14 SNPs, including SNPs in the APOE, BIN1, CD33, EPHA1, SORL1, and TOMM40 genes, were associated with sAD risk in our cohort. The PRS models built with these SNPs showed potential for discriminating sAD patients from CN controls, and were able to predict the incidence rate of sAD and age at onset. Furthermore, the PRSs were correlated with the CSF levels of Aβ42, Aβ42/Aβ40, T-tau, and P-tau. Our study suggests that PRS models hold promise for assessing the genetic risk and development of AD. As genetic risk profiles vary among populations, large-scale genome-wide sequencing studies are urgently needed to identify the genetic risk loci of sAD in Chinese populations to build accurate PRS models for clinical practice.

Characterization of Nme5-Like Gene/Protein from the Red Alga Chondrus Crispus

The Nme gene/protein family of nucleoside diphosphate kinases (NDPK) was originally named after its member Nm23-H1/Nme1, the first identified metastasis suppressor. Human Nme proteins are divided in two groups. They all possess nucleoside diphosphate kinase domain (NDK). Group I (Nme1-Nme4) display a single type NDK domain, whereas Group II (Nme5-Nme9) display a single or several different NDK domains, associated or not associated with extra-domains. Data strongly suggest that, unlike Group I, none of the members of Group II display measurable NDPK activity, although some of them autophosphorylate. The multimeric form is required for the NDPK activity. Group I proteins are known to multimerize, while there are no data on the multimerization of Group II proteins. The Group II ancestral type protein was shown to be conserved in several species from three eukaryotic supergroups. Here, we analysed the Nme protein from an early branching eukaryotic lineage, the red alga Chondrus crispus. We show that the ancestral type protein, unlike its human homologue, was fully functional multimeric NDPK with high affinity to various types of DNA and dispersed localization throughout the eukaryotic cell. Its overexpression inhibits both cell proliferation and the anchorage-independent growth of cells in soft agar but fails to deregulate cell apoptosis. We conclude that the ancestral gene has changed during eukaryotic evolution, possibly in correlation with the protein function.

TREML2 Mutation Mediate Alzheimer's Disease Risk by Altering Neuronal Degeneration

A coding missense mutation (rs3747742) in triggering receptor expressed on myeloid cell-like 2 (TREML2) has been recently proposed as an important protective factor against Alzheimer’s disease (AD). However, the link between TREML2 and AD pathology remains unclear. Therefore, we explored the association of TREML2 rs3747742 with cognitive function, neuroimaging biomarkers and cerebrospinal fluid (CSF) biomarkers related to AD, including CSF total-tau (T-tau), phosphor-tau (P-tau), and amyloid-β (Aβ_1-42). As for cognitive function, related cognitive scores of Clinical Dementia Rating Sum of Boxes (CDRSB), Alzheimer’s Disease Assessment Scale-cognitive section 11 (ADAS-cog 11), Mini-Mental State Examination (MMSE), and Rey Auditory-Verbal Learning Test (RAVLT) were extracted. We used a multiple linear regression model to examine the association of TREML2 rs3747742 with the baseline variables. Furthermore, we also calculated the change rate of above variables influenced by TREML2 rs3747742 via applying a mixed-effects model over a 4-year follow-up. In this analysis, a total of 1,306 individuals from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database were included. Finally, we observed that only in AD patients, but not in normal controls or mild cognitive impairment (MCI) individuals, TREML2 rs3747742 exhibited a strong association with CSF total-tau levels at baseline (β = -22.1210, p = 0.0166) and 4-year follow-up (β = -0.3961, p = 0.0115). Furthermore, no associations were found with CSF Aβ_1-42 levels, P-tau levels, neuroimaging biomarkers and cognitive function neither for baseline variables nor for longitudinal data. Thus, this study indicated that TREML2 mediated the risk of AD through influencing AD-related neurodegeneration (abnormal T-tau levels) but not P-tau levels and Aβ pathology.

Translating Alzheimer's disease-associated polymorphisms into functional candidates: a survey of IGAP genes and SNPs

The International Genomics of Alzheimer's Project (IGAP) is a consortium for characterizing the genetic landscape of Alzheimer's disease (AD). The identified and/or confirmed 19 single-nucleotide polymorphisms (SNPs) associated with AD are located on non-coding DNA regions, and their functional impacts on AD are as yet poorly understood. We evaluated the roles of the IGAP SNPs by integrating data from many resources, based on whether the IGAP SNP was (1) a proxy for a coding SNP or (2) associated with altered mRNA transcript levels. For (1), we confirmed that 12 AD-associated coding common SNPs and five nonsynonymous rare variants are in linkage disequilibrium with the IGAP SNPs. For (2), the IGAP SNPs in CELF1 and MS4A6A were associated with expression of their neighboring genes, MYBPC3 and MS4A6A, respectively, in blood. The IGAP SNP in DSG2 was an expression quantitative trait loci (eQTL) for DLGAP1 and NETO1 in the human frontal cortex. The IGAP SNPs in ABCA7, CD2AP, and CD33 each acted as eQTL for AD-associated genes in brain. Our approach for identifying proxies and examining eQTL highlighted potentially impactful, novel gene regulatory phenomena pertinent to the AD phenotype.

Genetic Markers of Alzheimer's Disease

Alzheimer's disease is a complex and heterogeneous, severe neurodegenerative disorder and the predominant form of dementia, characterized by cognitive disturbances, behavioral and psychotic symptoms, progressive cognitive decline, disorientation, behavioral changes, and death. Genetic background of Alzheimer's disease differs between early-onset familial Alzheimer's disease, other cases of early-onset Alzheimer's disease, and late-onset Alzheimer's disease. Rare cases of early-onset familial Alzheimer's diseases are caused by high-penetrant mutations in genes coding for amyloid precursor protein, presenilin 1, and presenilin 2. Late-onset Alzheimer's disease is multifactorial and associated with many different genetic risk loci (>20), with the apolipoprotein E ε4 allele being a major genetic risk factor for late-onset Alzheimer's disease. Genetic and genomic studies offer insight into many additional genetic risk loci involved in the genetically complex nature of late-onset Alzheimer's disease. This review highlights the contributions of individual loci to the pathogenesis of Alzheimer's disease and suggests that their exact contribution is still not clear. Therefore, the use of genetic markers of Alzheimer's disease, for monitoring development, time course, treatment response, and prognosis of Alzheimer's disease, is still far away from the clinical application, because the contribution of genetic variations to the relative risk of developing Alzheimer's disease is limited. In the light of prediction and prevention of Alzheimer's disease, a novel approach could be found in the form of additive genetic risk scores, which combine additive effects of numerous susceptibility loci.

Association of Alzheimer's genetic loci with mild behavioral impairment

Mild behavioral impairment (MBI) describes the emergence of later-life neuropsychiatric symptoms (NPS) as an at-risk state for incident cognitive decline and dementia, and for some as a potential manifestation of prodromal dementia. How NPS mechanistically link to the development of mild cognitive impairment and Alzheimer's disease (AD) is not fully understood, with potential mechanisms including shared risk factors related to both NPS and cognitive impairment, or AD pathology promoting NPS. This is the first exploratory study to examine whether AD genetic loci as a genetic risk score (GRS), or individually, are a shared risk factor with MBI. Participants were 1,226 older adults (aged 72-79; 738 males; 763 normal cognition) from the Personality and Total Health Through Life project. MBI was approximated in accordance with Criterion 1 of the ISTAART-AA diagnostic criteria using a transformation algorithm for the neuropsychiatric inventory. A GRS was constructed from 25 AD risk loci. Binomial logistic regression adjusting for age, gender, and education examined the association between GRS and MBI. A higher GRS and APOE*ε4 were associated with increased likelihood of affective dysregulation. Nominally significant associations were observed between MS4A4A-rs4938933*C and MS4A6A-rs610932*G with a reduced likelihood of affective dysregulation; ZCWPW1-rs1476679*C with a reduced likelihood of social inappropriateness and abnormal perception/thought content; BIN1-rs744373*G and EPHA1-rs11767557*C with higher likelihood of abnormal perception/thought content; NME8-rs2718058*G with a reduced likelihood of decreased motivation. These preliminary findings suggest a common genetic etiology between MBI and traditionally recognized cognitive problems observed in AD and improve our understanding of the pathophysiological features underlying MBI.

Alzheimer's Disease-Related Polymorphisms in Shunt-Responsive Idiopathic Normal Pressure Hydrocephalus

BACKGROUND

Idiopathic normal pressure hydrocephalus (iNPH) is a late onset, surgically treated progressive brain disease caused by impaired cerebrospinal fluid dynamics and subsequent ventriculomegaly. Comorbid Alzheimer's disease (AD) seems to be frequent in iNPH.

OBJECTIVE

We aim to evaluate the role of AD-related polymorphisms in iNPH.

METHODS

Overall 188 shunt-operated iNPH patients and 688 controls without diagnosed neurodegenerative disease were included into analysis. Twenty-three single-nucleotide polymorphisms (SNPs FRMD4A [rs7081208_A, rs2446581_A, rs17314229_T], CR1, BIN, CD2AP, CLU, MS4A6A, MS4A4E, PICALM, ABCA7, CD33, INPP5D, HLA_DRB5, EPHA1, PTK2B, CELF1, SORL1, FERMT2, SLC24A, DSG2, CASS4, and NME8) adjusted to APOE were analyzed between groups by using binary logistic regression analysis. Neuroradiological characteristics and AD-related changes in the right frontal cortical brain biopsies were available for further analysis.

RESULTS

Logistic regression analysis adjusted to age, gender, and other SNPs indicated allelic variation of NME8 between iNPH patients and non-demented controls (p = 0.014). The allelic variation of NME8 was not related to the neuropathological changes in the brain biopsies of iNPH patients. However, periventricular white matter changes (p = 0.017) were more frequent in the iNPH patients with the AA-genotype, an identified risk factor of AD.

CONCLUSIONS

Our findings increase the evidence that iNPH is characterized by genetic and pathophysiological mechanisms independent from AD. Considering that NME8 plays a role in the ciliary function and displays SNP-related diversity in white matter changes, the mechanisms of NME8 in iNPH and other neurodegenerative processes are worth further study.

State of Play in Alzheimer's Disease Genetics

Alzheimer's disease (AD), the main form of dementia in the elderly, is the most common progressive neurodegenerative disease characterized by rapidly progressive cognitive dysfunction and behavior impairment. AD exhibits a considerable heritability and great advances have been made in approaches to searching the genetic etiology of AD. In AD genetic studies, methods have developed from classic linkage-based and candidate-gene-based association studies to genome-wide association studies (GWAS) and next generation sequencing (NGS). The identification of new susceptibility genes has provided deeper insights to understand the mechanisms underlying AD. In addition to searching novel genes associated with AD in large samples, the NGS technologies can also be used to shed light on the 'black matter' discovery even in smaller samples. The shift in AD genetics between traditional studies and individual sequencing will allow biomaterials of each patient as the central unit of genetic studies. This review will cover genetic findings in AD and consequences of AD genetic findings. Firstly, we will discuss the discovery of mutations in APP, PSEN1, PSEN2, APOE, and ADAM10. Then we will summarize and evaluate the information obtained from GWAS of AD. Finally, we will outline the efforts to identify rare variants associated with AD using NGS.

Late Onset Alzheimer's Disease Risk Variants in Cognitive Decline: The PATH Through Life Study

Recent genome wide association studies have identified a number of single nucleotide polymorphisms associated with late onset Alzheimer's disease (LOAD). We examined the associations of 24 LOAD risk loci, individually and collectively as a genetic risk score, with cognitive function. We used data from 1,626 non-demented older Australians of European ancestry who were examined up to four times over 12 years on tests assessing episodic memory, working memory, vocabulary, and information processing speed. Linear mixed models were generated to examine associations between genetic factors and cognitive performance. Twelve SNPs were significantly associated with baseline cognitive performance (ABCA7, MS4A4E, SORL1), linear rate of change (APOE, ABCA7, INPP5D, ZCWPW1, CELF1), or quadratic rate of change (APOE, CLU, EPHA1, HLA-DRB5, INPP5D, FERMT2). In addition, a weighted genetic risk score was associated with linear rate of change in episodic memory and information processing speed. Our results suggest that a minority of AD related SNPs may be associated with non-clinical cognitive decline. Further research is required to verify these results and to examine the effect of preclinical AD in genetic association studies of cognitive decline. The identification of LOAD risk loci associated with non-clinical cognitive performance may help in screening for individuals at greater risk of cognitive decline.

MS4A6A genotypes are associated with the atrophy rates of Alzheimer's disease related brain structures

Membrane-spanning 4-domains, subfamily A, member 6A (MS4A6A) has been identified as susceptibility loci of Alzheimer's disease (AD) by several recent genome-wide association studies (GWAS), whereas little is known about the potential roles of these variants in the brain structure and function of AD. In this study, we included a total of 812 individuals from the Alzheimer's disease Neuroimaging Initiative (ADNI) database. Using multiple linear regression models, we found MS4A6A genotypes were strongly related to atrophy rate of left middle temporal (rs610932: Pc = 0.017, rs7232: Pc = 0.022), precuneus (rs610932: Pc = 0.015) and entorhinal (rs610932, Pc = 0.022) on MRI in the entire group. In the subgroup analysis, MS4A6A SNPs were significantly accelerated the percentage of volume loss of middle temporal, precuneus and entorhinal, especially in the MCI subgroup. These findings reveal that MS4A6A genotypes affect AD specific brain structures which supported the possible role of MS4A6A polymorphisms in influencing AD-related neuroimaging phenotypes.

NME8 rs2718058 polymorphism with Alzheimer's disease risk: a replication and meta-analysis

Recently, a large meta-analysis of five genome wide association studies (GWAS) has identified that a novel single nucleotide polymorphism (SNP) rs2718058, adjacent to gene NME8 on chromosome 7p14.1, was associated with late-onset Alzheimer's disease (LOAD) in Caucasians. However, the effect of rs2718058 on other populations remains unclear. In order to explore the relationship between rs2718058 and LOAD risk in a North Han Chinese population, we recruited 984 LOAD cases and 1354 healthy controls that matched for sex and age in this study. The results showed no significant differences in the genotypic or allelic distributions of rs2718058 polymorphism between LOAD cases and healthy controls, even though after stratification for APOE ε4 status and statistical adjustment for age, gender and APOE ε4 status (p > 0.05). However, a meta-analysis conducted in a sample of 82513 individuals confirmed a significant association between SNP rs2718058 and LOAD risk (OR = 1.08, 95%CI = 1.05-1.11) in the whole population. But there was still no positive results in Chinese subgroup (OR = 1.05, 95%CI = 0.93-1.17). In conclusion, the rs2718058 near gene NME8 on chromosome 7p14.1 might not play a major role in the genetic predisposition to LOAD in the North Han Chinese.

Exome Sequencing of Extended Families with Alzheimer's Disease Identifies Novel Genes Implicated in Cell Immunity and Neuronal Function

Objective

Alzheimer’s disease (AD) is a neurodegenerative disorder for which more than 20 genetic loci have been implicated to date. However, studies demonstrate not all genetic factors have been identified. Therefore, in this study we seek to identify additional rare variants and novel genes potentially contributing to AD.

Methods

Whole exome sequencing was performed on 23 multi-generational families with an average of eight affected subjects. Exome sequencing was filtered for rare, nonsynonymous and loss-of-function variants. Alterations predicted to have a functional consequence and located within either a previously reported AD gene, a linkage peak (LOD>2), or clustering in the same gene across multiple families, were prioritized.

Results

Rare variants were found in known AD risk genes including AKAP9, CD33, CR1, EPHA1, INPP5D, NME8, PSEN1, SORL1, TREM2 and UNC5C. Three families had five variants of interest in linkage regions with LOD>2. Genes with segregating alterations in these peaks include CD163L1 and CLECL1, two genes that have both been implicated in immunity, CTNNA1, which encodes a catenin in the cerebral cortex and MIEF1, a gene that may induce mitochondrial dysfunction and has the potential to damage neurons. Four genes were identified with alterations in more than one family include PLEKHG5, a gene that causes Charcot-Marie-Tooth disease and THBS2, which promotes synaptogenesis.

Conclusion

Utilizing large families with a heavy burden of disease allowed for the identification of rare variants co-segregating with disease. Variants were identified in both known AD risk genes and in novel genes.

Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials

INTRODUCTION

The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued development and standardization of methodologies for biomarkers and has provided an increased depth and breadth of data available to qualified researchers. This review summarizes the over 400 publications using ADNI data during 2014 and 2015.

METHODS

We used standard searches to find publications using ADNI data.

RESULTS

(1) Structural and functional changes, including subtle changes to hippocampal shape and texture, atrophy in areas outside of hippocampus, and disruption to functional networks, are detectable in presymptomatic subjects before hippocampal atrophy; (2) In subjects with abnormal β-amyloid deposition (Aβ+), biomarkers become abnormal in the order predicted by the amyloid cascade hypothesis; (3) Cognitive decline is more closely linked to tau than Aβ deposition; (4) Cerebrovascular risk factors may interact with Aβ to increase white-matter (WM) abnormalities which may accelerate Alzheimer's disease (AD) progression in conjunction with tau abnormalities; (5) Different patterns of atrophy are associated with impairment of memory and executive function and may underlie psychiatric symptoms; (6) Structural, functional, and metabolic network connectivities are disrupted as AD progresses. Models of prion-like spreading of Aβ pathology along WM tracts predict known patterns of cortical Aβ deposition and declines in glucose metabolism; (7) New AD risk and protective gene loci have been identified using biologically informed approaches; (8) Cognitively normal and mild cognitive impairment (MCI) subjects are heterogeneous and include groups typified not only by "classic" AD pathology but also by normal biomarkers, accelerated decline, and suspected non-Alzheimer's pathology; (9) Selection of subjects at risk of imminent decline on the basis of one or more pathologies improves the power of clinical trials; (10) Sensitivity of cognitive outcome measures to early changes in cognition has been improved and surrogate outcome measures using longitudinal structural magnetic resonance imaging may further reduce clinical trial cost and duration; (11) Advances in machine learning techniques such as neural networks have improved diagnostic and prognostic accuracy especially in challenges involving MCI subjects; and (12) Network connectivity measures and genetic variants show promise in multimodal classification and some classifiers using single modalities are rivaling multimodal classifiers.

DISCUSSION

Taken together, these studies fundamentally deepen our understanding of AD progression and its underlying genetic basis, which in turn informs and improves clinical trial design.

The effect of the top 20 Alzheimer disease risk genes on gray-matter density and FDG PET brain metabolism

INTRODUCTION

We analyzed the effects of the top 20 Alzheimer disease (AD) risk genes on gray-matter density (GMD) and metabolism.

METHODS

We ran stepwise linear regression analysis using posterior cingulate hypometabolism and medial temporal GMD as outcomes and all risk variants as predictors while controlling for age, gender, and APOE ε4 genotype. We explored the results in 3D using Statistical Parametric Mapping 8.

RESULTS

Significant predictors of brain GMD were SLC24A4/RIN3 in the pooled and mild cognitive impairment (MCI); ZCWPW1 in the MCI; and ABCA7, EPHA1, and INPP5D in the AD groups. Significant predictors of hypometabolism were EPHA1 in the pooled, and SLC24A4/RIN3, NME8, and CD2AP in the normal control group.

DISCUSSION

Multiple variants showed associations with GMD and brain metabolism. For most genes, the effects were limited to specific stages of the cognitive continuum, indicating that the genetic influences on brain metabolism and GMD in AD are complex and stage dependent.

High avidity HSV-1 antibodies correlate with absence of amnestic Mild Cognitive Impairment conversion to Alzheimer's disease

Amnestic Mild Cognitive Impairment (aMCI) is an alteration in cognitive abilities that can progress to Alzheimer's disease (AD), a condition in which herpes simplex type 1 (HSV-1) infection might play a pathogenetic role. Prognostic indexes capable of predicting aMCI conversion to AD are only partially understood. The objective of the present work is to verify whether HSV-1 immune responses is involved in conversion of aMCI to AD and correlate with grey matter brain morphometry. Two homogeneous groups of individuals who did or did not convert to AD over a 24-months period were selected after retrospective analysis of a cohort of patients with a diagnosis of aMCI. The selection of subjects was based on: a) clinical follow-up; b) neurocognitive evaluation at baseline and after 24months; c) availability of serum and DNA samples at baseline. 36 aMCI individuals, 21 of whom did (aMCI-converters) and 15 of whom did not (aMCI-non-converters) convert to AD, were included in the study. HSV-1 antibody (Ab) titers, avidity index and APOE genotyping were performed in all the enrolled individuals at baseline. Brain magnetic resonance imaging (MRI) by 1.5T scanner results at baseline were available as well in most (29/36) of these individuals. HSV-1-specific Ab titers were increased at baseline in aMCI-non-converters, and the avidity of these Ab was significantly higher in aMCI-non-converter compared to aMCI-converter (p=0.0018). Receiver operating characteristics analysis showed that HSV-1 avidity had a predictive value in distinguishing between aMCI-non-converters and aMCI-converters (p<0.0001). Notably, a positive correlation was detected as well between HSV-1 antibody titers and MRI-evaluated cortical volumes in the left hippocampus and amigdala (p_corr<0.05). In conclusion, stronger HSV-1-specific humoral responses associate with protection against AD conversion and better-preserved cortical volumes. These results reinforce the hypothesis for a role for HSV-1 in the pathogenesis of AD.

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

The neural substrate of genetic risk variants for Alzheimer's disease (AD) remains unknown. We studied their effect on healthy brain morphology to provide insight into disease etiology in the preclinical phase. We included 4071 nondemented, elderly participants of the population-based Rotterdam Study who underwent brain magnetic resonance imaging and genotyping. We performed voxel-based morphometry (VBM) on all gray-matter voxels for 19 previously identified, common AD risk variants. Whole-brain expression data from the Allen Human Brain Atlas was used to examine spatial overlap between VBM association results and expression of genes in AD risk loci regions. Brain regions most significantly associated with AD risk variants were the left postcentral gyrus with ABCA7 (rs4147929, p = 4.45 × 10^-6), right superior frontal gyrus by ZCWPW1 (rs1476679, p = 5.12 × 10^-6), and right postcentral gyrus by APOE (p = 6.91 × 10^-6). Although no individual voxel passed multiple-testing correction, we found significant spatial overlap between the effects of AD risk loci on VBM and the expression of genes (MEF2C, CLU, and SLC24A4) in the Allen Brain Atlas. Results are available online on www.imagene.nl/ADSNPs/. In this single largest imaging genetics data set worldwide, we found that AD risk loci affect cortical gray matter in several brain regions known to be involved in AD, as well as regions that have not been implicated before.

Effect of CLU genetic variants on cerebrospinal fluid and neuroimaging markers in healthy, mild cognitive impairment and Alzheimer's disease cohorts

The Clusterin (CLU) gene, also known as apolipoprotein J (ApoJ), is currently the third most associated late-onset Alzheimer's disease (LOAD) risk gene. However, little was known about the possible effect of CLU genetic variants on AD pathology in brain. Here, we evaluated the interaction between 7 CLU SNPs (covering 95% of genetic variations) and the role of CLU in β-amyloid (Aβ) deposition, AD-related structure atrophy, abnormal glucose metabolism on neuroimaging and CSF markers to clarify the possible approach by that CLU impacts AD. Finally, four loci (rs11136000, rs1532278, rs2279590, rs7982) showed significant associations with the Aβ deposition at the baseline level while genotypes of rs9331888 (P = 0.042) increased Aβ deposition. Besides, rs9331888 was significantly associated with baseline volume of left hippocampus (P = 0.014). We then further validated the association with Aβ deposition in the AD, mild cognitive impairment (MCI), normal control (NC) sub-groups. The results in sub-groups confirmed the association between CLU genotypes and Aβ deposition further. Our findings revealed that CLU genotypes could probably modulate the cerebral the Aβ loads on imaging and volume of hippocampus. These findings raise the possibility that the biological effects of CLU may be relatively confined to neuroimaging trait and hence may offer clues to AD.

Genes associated with Alzheimer's disease: an overview and current status

Alzheimer's disease (AD) is a progressive, neurodegenerative disease and the most common form of dementia in elderly people. It is an emerging public health problem that poses a huge societal burden. Linkage analysis was the first milestone in unraveling the mutations in APP, PSEN1, and PSEN2 that cause early-onset AD, followed by the discovery of apolipoprotein E-ε4 allele as the only one genetic risk factor for late-onset AD. Genome-wide association studies have revolutionized genetic research and have identified over 20 genetic loci associated with late-onset AD. Recently, next-generation sequencing technologies have enabled the identification of rare disease variants, including unmasking small mutations with intermediate risk of AD in PLD3, TREM2, UNC5C, AKAP9, and ADAM10. This review provides an overview of the genetic basis of AD and the relationship between these risk genes and the neuropathologic features of AD. An understanding of genetic mechanisms underlying AD pathogenesis and the potentially implicated pathways will lead to the development of novel treatment for this devastating disease.

Effects of HLA-DRB1/DQB1 Genetic Variants on Neuroimaging in Healthy, Mild Cognitive Impairment, and Alzheimer's Disease Cohorts

Alzheimer's disease (AD) is the most common form of dementia and exhibits a considerable level of heritability. Previous association studies gave evidence for the associations of HLA-DRB1/DQB1 alleles with AD. However, how and when the gene variants in HLA-DRB1/DQB1 function in AD pathogenesis has yet to be determined. Here, we firstly investigated the association of gene variants in HLA-DRB1/DQB1 alleles and AD related brain structure on magnetic resonance imaging (MRI) in a large sample from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We selected hippocampus, subregion, parahippocampus, posterior cingulate, precuneus, middle temporal, entorhinal cortex, and amygdala as regions of interest (ROIs). Twelve SNPs in HLA-DRB1/DQB1 were identified in the dataset following quality control measures. In the total group hybrid population analysis, our study (rs35445101, rs1130399, and rs28746809) were associated with the smaller baseline volume of the left posterior cingulate and rs2854275 was associated with the larger baseline volume of the left posterior cingulate. Furthermore, we detected the above four associations in mild cognitive impairment (MCI) sub-group analysis, and two risk loci (rs35445101 and rs1130399) were also the smaller baseline volume of the left posterior cingulate in (NC) sub-group analysis. Our study suggested that HLA-DRB1/DQB1 gene variants appeared to modulate the alteration of the left posterior cingulate volume, hence modulating the susceptibility of AD.

HLA-A2 Alleles Mediate Alzheimer's Disease by Altering Hippocampal Volume

HLA-A is a locus of the major histocompatibility complex situated on chromosome 6p21.3. HLA-A has been shown to be associated with susceptibility to Alzheimer's disease (AD). In this study, we firstly investigated the association of gene variants in HLA-A and brain structures on MRI in a large sample from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to explore the effects of HLA-A on AD pathogenesis. We selected the hippocampus, parahippocampus, posterior cingulate, precuneus, middle temporal, entorhinal cortex, and amygdala as regions of interest (ROIs). In hybrid population analysis, our results showed a marginally significant association between rs9260168 and the atrophy of the left parahippocampus (P = 0.007, Pc = 0.054), rs3823342 and the atrophy of the left parahippocampus (P = 0.014, Pc = 0.054), rs76475517, which only exists in Caucasians with HLA-A23 or HLA-A24 alleles, and the atrophy of the right amygdala (P = 0.010, Pc = 0.085) at baseline. In particular, the haplotype (TGACAAGG), as a surrogate marker of HLA-A2, was founded to be positively associated with the atrophy of the right hippocampus (P = 0.047) at baseline. Furthermore, we detected the above four associations in mild cognitive impairment (MCI) subpopulation analysis. Our study provided preliminary evidences supporting HLA-A2 in Caucasians contribute to the risk of AD by modulating the alteration of hippocampal volume and HLA-A gene variants appear to play a role in altering AD-related brain structures on MRI.

Impacts of CD33 Genetic Variations on the Atrophy Rates of Hippocampus and Parahippocampal Gyrus in Normal Aging and Mild Cognitive Impairment

The cluster of differentiation 33 (CD33) has been proved as a susceptibility locus associated with late-onset Alzheimer's disease (LOAD) based on recent genetic studies. Numerous studies have shown that multiple neuroimaging measures are potent predictors of AD risk and progression, and these measures are also affected by genetic variations in AD. Figuring out the association between CD33 genetic variations and AD-related brain atrophy may shed light on the underlying mechanisms of CD33-related AD pathogenesis. Thus, we investigated the influence of CD33 genotypes on AD-related brain atrophy to clarify the possible means by which CD33 impacts AD. A total of 48 individuals with probable AD, 483 mild cognitive impairment, and 281 cognitively normal controls were recruited from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. We investigated the influence of CD33 SNPs on hippocampal volume, parahippocampal gyrus volume, posterior cingulate volume, middle temporal volume, hippocampus CA1 subregion volume, and entorhinal cortex thickness. We found that brain regions significantly affected by CD33 genetic variations were restricted to hippocampal and parahippocampal gyrus in hybrid population, which were further validated in subpopulation (MCI and NC) analysis. These findings reaffirm the importance of the hippocampal and parahippocampal gyrus in AD pathogenesis, and present evidences for the CD33 variations influence on the atrophy of specific AD-related brain structures. Our findings raise the possibility that CD33 polymorphisms contribute to the AD risk by altering the neuronal degeneration of hippocampal and parahippocampal gyrus.

Common and Rare Genetic Variants Associated With Alzheimer's Disease

Alzheimer's disease (AD) is one of the most devastating disorders. Despite the continuing increase of its incidence among aging populations, no effective cure has been developed mainly due to difficulties in early diagnosis of the disease before damaging of the brain, and the failure to explore its complex underlying molecular mechanisms. Recent technological advances in genome-wide association studies (GWAS) and high throughput next generation whole genome, and exome sequencing had deciphered many of AD-related loci, and discovered single nucleotide polymorphisms (SNPs) that are associated with altered AD molecular pathways. Highlighting altered molecular pathways linked to AD pathogenesis is crucial to identify novel diagnostic and therapeutic AD targets.

PET Imaging of Epigenetic Influences on Alzheimer's Disease

The precise role of environment-gene interactions (epigenetics) in the development and progression of Alzheimer's disease (AD) is unclear. This review focuses on the premise that radiotracer-specific PET imaging allows clinicians to visualize epigenetically influenced events and that such imaging may provide new, valuable insights for preventing, diagnosing, and treating AD. Current understanding of the role of epigenetics in AD and the principles underlying the use of PET radiotracers for in vivo diagnosis are reviewed. The relative efficacies of various PET radiotracers for visualizing the epigenetic influences on AD and their use for diagnosis are discussed. For example, [¹⁸F]FAHA demonstrates sites of differential HDAC activity, [¹⁸F]FDG indirectly illuminates sites of neuronal hypomethylation, and the carbon-11 isotope-containing Pittsburgh compound B ([¹¹C]PiB) images amyloid-beta plaque deposits. A definitive AD diagnosis is currently achievable only by postmortem histological observation of amyloid-beta plaques and tau neurofibrillary tangles. Therefore, reliable in vivo neuroimaging techniques could provide opportunities for early diagnosis and treatment of AD.