MS4A Cluster in Alzheimer's Disease

Variants in the MS4A cluster interact with soluble TREM2 expression on biomarkers of neuropathology

Recent evidence suggests that Alzheimer's disease (AD) genetic risk variants (rs1582763 and rs6591561) of the MS4A locus are genome-wide significant regulators of soluble TREM2 levels such that the minor allele of the protective variant (rs1582763) is associated with higher sTREM2 and lower AD risk while the minor allele of (rs6591561) relates to lower sTREM2 and higher AD risk. Our group previously found that higher sTREM2 relates to higher Aβ40, worse blood-brain barrier (BBB) integrity (measured with the CSF/plasma albumin ratio), and higher CSF tau, suggesting strong associations with amyloid abundance and both BBB and neurodegeneration complicate interpretation. We expand on this work by leveraging these common variants as genetic tools to tune the interpretation of high CSF sTREM2, and by exploring the potential modifying role of these variants on the well-established associations between CSF sTREM2 as well as TREM2 transcript levels in the brain with AD neuropathology. Biomarker analyses leveraged data from the Vanderbilt Memory & Aging Project (n = 127, age = 72 ± 6.43) and were replicated in the Alzheimer's Disease Neuroimaging Initiative (n = 399, age = 73 ± 7.39). Autopsy analyses were performed leveraging data from the Religious Orders Study and Rush Memory and Aging Project (n = 577, age = 89 ± 6.46). We found that the protective variant rs1582763 attenuated the association between CSF sTREM2 and Aβ40 (β = -0.44, p-value = 0.017) and replicated this interaction in ADNI (β = -0.27, p = 0.017). We did not observe this same interaction effect between TREM2 mRNA levels and Aβ peptides in brain (Aβ total β = -0.14, p = 0.629; Aβ1-38, β = 0.11, p = 0.200). In contrast to the effects on Aβ, the minor allele of this same variant seemed to enhance the association with blood-brain barrier dysfunction (β = 7.0e-4, p = 0.009), suggesting that elevated sTREM2 may carry a much different interpretation in carriers vs. non-carriers of this allele. When evaluating the risk variant (rs6591561) across datasets, we did not observe a statistically significant interaction against any outcome in VMAP and observed opposing directions of associations in ADNI and ROS/MAP on Aβ levels. Together, our results suggest that the protective effect of rs1582763 may act by decoupling the associations between sTREM2 and amyloid abundance, providing important mechanistic insight into sTREM2 changes and highlighting the need to incorporate genetic context into the analysis of sTREM2 levels, particularly if leveraged as a clinical biomarker of disease in the future.

Inflammation and Brain Structure in Alzheimer's Disease and Other Neurodegenerative Disorders: a Mendelian Randomization Study

Previous in vitro and post-mortem studies have reported the role of inflammation in neurodegenerative disorders. However, the association between inflammation and brain structure in vivo and the transcriptome-driven functional basis with relevance to neurodegenerative disorders remains elusive. The aim of the present study is to identify the association among inflammation, brain structure, and neurodegenerative disorders at genetic and transcriptomic levels. Genetic variants associated with inflammatory cytokines were selected from the latest and largest genome-wide association studies of European ancestry. Neurodegenerative disorders including Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and dementia with Lewy bodies (DLB) and brain structure imaging measures were selected as the outcomes. Two-sample Mendelian randomization analyses were conducted to identify the causal associations. Single-nucleus transcriptome data of the occipitotemporal cortex was further analyzed to identify the differential expressed genes in AD, which were tested for biological processes and protein interaction network. MR analysis indicated that genetically predicted TREM2 and sTREM2 were significantly associated with AD (TREM2: z-score = -9.088, p-value = 1.02 × 10-19; sTREM2: z-score = -7.495, p-value = 6.61 × 10-14). The present study found no evidence to support the causal associations between other inflammatory cytokines and the risks of AD, PD, ALS, or DLB. Genetically predicted TREM2 was significantly associated with the cortical thickness of inferior temporal (z-score = -4.238, p-value = 2.26 × 10-5) and pole temporal (z-score = -4.549, p-value = 5.40 × 10-6). In the occipitotemporal cortex samples, microglia were the main source of TREM2 gene and showed increasing expression of genes associated with inflammation and immunity. The present study has leveraged genetic and transcriptomic data to identify the association among TREM2, temporal lobe, and AD and the underlying cellular and molecular basis, thus providing a new perspective on the role of TREM2 in AD and insights into the complex associations among inflammation, brain structure, and neurodegenerative disorders, particularly AD.

Transformation of non-neuritic into neuritic plaques during AD progression drives cortical spread of tau pathology via regenerative failure

Extracellular amyloid-β (Aβ) plaques and intracellular aggregates of tau protein in form of neurofibrillary tangles (NFT) are pathological hallmarks of Alzheimer's disease (AD). The exact mechanism how these two protein aggregates interact in AD is still a matter of debate. Neuritic plaques (NP), a subset of Aβ plaques containing dystrophic neurites (DN), are suggested to be unique to AD and might play a role in the interaction of Aβ and tau. Quantifying NP and non-NP in postmortem brain specimens from patients with increasing severity of AD neuropathological changes (ADNC), we demonstrate that the total number of Aβ plaques and NP increase, while the number of non-NP stagnates. Furthermore, investigating the correlation between NP and NFT, we identified unexpected brain region-specific differences when comparing cases with increasingly more severe ADNC. In neocortical regions NFT counts increase in parallel with NP counts during the progression of ADNC, while this correlation is not observed in hippocampus. These data support the notion that non-NP are transformed into NP during the progression of ADNC and indicate that NP might drive cortical NFT formation. Next, using spatial transcriptomics, we analyzed the gene expression profile of the microenvironment around non-NP and NP. We identified an upregulation of neuronal systems and Ca-dependent event pathways around NP compared to non-NP. We speculate that the upregulation of these transcripts may hint at a compensatory mechanism underlying NP formation. Our studies suggest that the transformation of non-NP to NP is a key event in ADNC progression and points to regenerative failure as a potential driving force of this process.

Exploring the Disease-Associated Microglia State in Amyotrophic Lateral Sclerosis

BACKGROUND

Neuroinflammation, and specifically microglia, plays an important but not-yet well-understood role in the pathophysiology of amyotrophic lateral sclerosis (ALS), constituting a potential therapeutic target for the disease. Recent studies have described the involvement of different microglial transcriptional patterns throughout neurodegenerative processes, identifying a new state of microglia: disease-associated microglia (DAM). The aim of this study is to investigate expression patterns of microglial-related genes in ALS spinal cord.

METHODS

We analyzed mRNA expression levels via RT-qPCR of several microglia-related genes in their homeostatic and DAM state in postmortem tissue (anterior horn of the spinal cord) from 20 subjects with ALS-TDP43 and 19 controls donors from the Navarrabiomed Biobank.

RESULTS

The expression levels of TREM2, MS4A, CD33, APOE and TYROBP were found to be elevated in the spinal cord from ALS subjects versus controls (p-value < 0.05). However, no statistically significant gene expression differences were observed for TMEM119, SPP1 and LPL.

CONCLUSIONS

This study suggests that a DAM-mediated inflammatory response is present in ALS, and TREM2 plays a significant role in immune function of microglia. It also supports the role of C33 and MS4A in the physiopathology of ALS.

Brain structure and allelic associations in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD), the most prevalent form of dementia, affects 6.5 million Americans and over 50 million people globally. Clinical, genetic, and phenotypic studies of dementia provide some insights of the observed progressive neurodegenerative processes, however, the mechanisms underlying AD onset remain enigmatic.

AIMS

This paper examines late-onset dementia-related cognitive impairment utilizing neuroimaging-genetics biomarker associations.

MATERIALS AND METHODS

The participants, ages 65-85, included 266 healthy controls (HC), 572 volunteers with mild cognitive impairment (MCI), and 188 Alzheimer's disease (AD) patients. Genotype dosage data for AD-associated single nucleotide polymorphisms (SNPs) were extracted from the imputed ADNI genetics archive using sample-major additive coding. Such 29 SNPs were selected, representing a subset of independent SNPs reported to be highly associated with AD in a recent AD meta-GWAS study by Jansen and colleagues.

RESULTS

We identified the significant correlations between the 29 genomic markers (GMs) and the 200 neuroimaging markers (NIMs). The odds ratios and relative risks for AD and MCI (relative to HC) were predicted using multinomial linear models.

DISCUSSION

In the HC and MCI cohorts, mainly cortical thickness measures were associated with GMs, whereas the AD cohort exhibited different GM-NIM relations. Network patterns within the HC and AD groups were distinct in cortical thickness, volume, and proportion of White to Gray Matter (pct), but not in the MCI cohort. Multinomial linear models of clinical diagnosis showed precisely the specific NIMs and GMs that were most impactful in discriminating between AD and HC, and between MCI and HC.

CONCLUSION

This study suggests that advanced analytics provide mechanisms for exploring the interrelations between morphometric indicators and GMs. The findings may facilitate further clinical investigations of phenotypic associations that support deep systematic understanding of AD pathogenesis.

scEpiLock: A Weakly Supervised Learning Framework for cis-Regulatory Element Localization and Variant Impact Quantification for Single-Cell Epigenetic Data

Recent advances in single-cell transposase-accessible chromatin using a sequencing assay (scATAC-seq) allow cellular heterogeneity dissection and regulatory landscape reconstruction with an unprecedented resolution. However, compared to bulk-sequencing, its ultra-high missingness remarkably reduces usable reads in each cell type, resulting in broader, fuzzier peak boundary definitions and limiting our ability to pinpoint functional regions and interpret variant impacts precisely. We propose a weakly supervised learning method, scEpiLock, to directly identify core functional regions from coarse peak labels and quantify variant impacts in a cell-type-specific manner. First, scEpiLock uses a multi-label classifier to predict chromatin accessibility via a deep convolutional neural network. Then, its weakly supervised object detection module further refines the peak boundary definition using gradient-weighted class activation mapping (Grad-CAM). Finally, scEpiLock provides cell-type-specific variant impacts within a given peak region. We applied scEpiLock to various scATAC-seq datasets and found that it achieves an area under receiver operating characteristic curve (AUC) of ~0.9 and an area under precision recall (AUPR) above 0.7. Besides, scEpiLock’s object detection condenses coarse peaks to only ⅓ of their original size while still reporting higher conservation scores. In addition, we applied scEpiLock on brain scATAC-seq data and reported several genome-wide association studies (GWAS) variants disrupting regulatory elements around known risk genes for Alzheimer’s disease, demonstrating its potential to provide cell-type-specific biological insights in disease studies.

Comprehensive Analysis of Expression and Prognostic Value of MS4As in Glioma

Glioma is the most common malignancy of the nervous system with high mortality rates. The MS4A family members have been reported as potential prognostic biomarkers in several cancers; however, the relationship between the MS4A family and glioma has not been clearly confirmed. In our study, we explored the prognostic value of MS4As as well as their potential pro-cancer mechanisms of glioma. Using bioinformatics analysis methods based on the data from public databases, we found that the expression of MS4A4A, MS4A4E, MS4A6A, MS4A7, TMEM176A, and TMEM176B was significantly overexpressed in glioma tissues compared with that of normal tissues. The Kaplan–Meier method and Cox proportional hazards models revealed that high levels of MS4As can be associated with a poorer prognosis; TMEM176A, TMEM176B, age, WHO grade, and IDH status were identified as independent prognostic factors. Enrichment analysis predicted that MS4As were related to tumor-related pathways and immune response, which might regulate the process of MS4As promoting tumorigenesis. Additionally, we analyzed the correlations of MS4A expression with immune cells and immune inhibitory molecules. Finally, data from the cell culture suggested that knockdown of the TMEM176B gene contributes to the decreased proliferation and migration of glioma cells. In conclusion, MS4A4A, MS4A4E, MS4A6A, MS4A7, TMEM176A, and TMEM176B may act as potential diagnostic or prognostic biomarkers in glioma and play a role in forming the immune microenvironment in gliomas.

A hidden layer of structural variation in transposable elements reveals potential genetic modifiers in human disease-risk loci

Genome-wide association studies (GWAS) have been highly informative in discovering disease-associated loci but are not designed to capture all structural variations in the human genome. Using long-read sequencing data, we discovered widespread structural variation within SINE-VNTR-Alu (SVA) elements, a class of great ape-specific transposable elements with gene-regulatory roles, which represents a major source of structural variability in the human population. We highlight the presence of structurally variable SVAs (SV-SVAs) in neurological disease-associated loci, and we further associate SV-SVAs to disease-associated SNPs and differential gene expression using luciferase assays and expression quantitative trait loci data. Finally, we genetically deleted SV-SVAs in the BIN1 and CD2AP Alzheimer's disease-associated risk loci and in the BCKDK Parkinson's disease-associated risk locus and assessed multiple aspects of their gene-regulatory influence in a human neuronal context. Together, this study reveals a novel layer of genetic variation in transposable elements that may contribute to identification of the structural variants that are the actual drivers of disease associations of GWAS loci.

Functional insight into LOAD-associated microglial response genes

Alzheimer's disease (AD) is characterized by the presence of amyloid beta (Aβ) plaques and neurofibrillary tangles (NFTs), neuronal and synaptic loss and inflammation of the central nervous system (CNS). The majority of AD research has been dedicated to the understanding of two major AD hallmarks (i.e. Aβ and NFTs); however, recent genome-wide association studies (GWAS) data indicate neuroinflammation as having a critical role in late-onset AD (LOAD) development, thus unveiling a novel avenue for AD therapeutics. Recent evidence has provided much support to the innate immune system's involvement with AD progression; however, much remains to be uncovered regarding the role of glial cells, specifically microglia, in AD. Moreover, numerous variants in immune and/or microglia-related genes have been identified in whole-genome sequencing and GWAS analyses, including such genes as TREM2, CD33, APOE, API1, MS4A, ABCA7, BIN1, CLU, CR1, INPP5D, PICALM and PLCG2. In this review, we aim to provide an insight into the function of the major LOAD-associated microglia response genes.

Single-Cell Sequencing Analysis of the db/db Mouse Hippocampus Reveals Cell-Type-Specific Insights Into the Pathobiology of Diabetes-Associated Cognitive Dysfunction

Diabetes-associated cognitive decline (DCD), is one of the complications of diabetes, which is characterized by a series of neurophysiological and pathological abnormalities. However, the exact pathogenesis of DCD is still unknown. Single-cell RNA sequencing (scRNA-seq) could discover unusual subpopulations, explore functional heterogeneity and identify signaling pathways and potential markers. The aim of this research was to provide deeper opinion into molecular and cellular changes underlying DCD, identify different cellular types of the diabetic mice hippocampus at single-cell level, and elucidate the factors mediating the pathogenesis of DCD. To elucidate cell specific gene expression changes in the hippocampus of diabetic encephalopathy. Single-cell RNA sequencing of hippocampus from db/m and db/db mice was carried out. Subclustering analysis was performed to further describe microglial cell subpopulations. Interestingly using immunohistochemistry, these findings were confirmed at the protein level. Single cell analysis yielded transcriptome data for 14621 hippocampal cells and defined 11 different cell types. Analysis of differentially expressed genes in the microglia compartments indicated that infection- and immune system process- associated terms, oxidative stress and inflammation play vital roles in the progression of DCD. Compared with db/m mouse, experiments at the protein level supported the activation of microglia, increased expression of inflammatory factors and oxidative stress damage in the hippocampus of db/db mouse. In addition, a major finding of our research was the subpopulation of microglia that express genes related to pro-inflammatory disease-associated microglia (DAM). Our research reveals pathological alterations of inflammation and oxidative stress mediated hippocampal damage in the db/db mice, and may provide potential diagnostic biomarkers and therapeutic interventions for DCD.

Microglia in Alzheimer's Disease: A Target for Therapeutic Intervention

Alzheimer’s disease (AD) is one of the most common types of age-related dementia worldwide. In addition to extracellular amyloid plaques and intracellular neurofibrillary tangles, dysregulated microglia also play deleterious roles in the AD pathogenesis. Numerous studies have demonstrated that unbridled microglial activity induces a chronic neuroinflammatory environment, promotes β-amyloid accumulation and tau pathology, and impairs microglia-associated mitophagy. Thus, targeting microglia may pave the way for new therapeutic interventions. This review provides a thorough overview of the pathophysiological role of the microglia in AD and illustrates the potential avenues for microglia-targeted therapies, including microglial modification, immunoreceptors, and anti-inflammatory drugs.

Differential expression and regulation of MS4A family members in myeloid cells in physiological and pathological conditions

The MS4A gene family encodes 18 tetraspanin-like proteins, most of which with unknown function. MS4A1 (CD20), MS4A2 (FcεRIβ), MS4A3 (HTm4), and MS4A4A play important roles in immunity, whereas expression and function of other members of the family are unknown. The present investigation was designed to obtain an expression fingerprint of MS4A family members, using bioinformatics analysis of public databases, RT-PCR, and protein analysis when possible. MS4A3, MS4A4A, MS4A4E, MS4A6A, MS4A7, and MS4A14 were expressed by myeloid cells. MS4A6A and MS4A14 were expressed in circulating monocytes and decreased during monocyte-to-Mϕ differentiation in parallel with an increase in MS4A4A expression. Analysis of gene expression regulation revealed a strong induction of MS4A4A, MS4A6A, MS4A7, and MS4A4E by glucocorticoid hormones. Consistently with in vitro findings, MS4A4A and MS4A7 were expressed in tissue Mϕs from COVID-19 and rheumatoid arthritis patients. Interestingly, MS4A3, selectively expressed in myeloid precursors, was found to be a marker of immature circulating neutrophils, a cellular population associated to COVID-19 severe disease. The results reported here show that members of the MS4A family are differentially expressed and regulated during myelomonocytic differentiation, and call for assessment of their functional role and value as therapeutic targets.

Genetic Variability in Molecular Pathways Implicated in Alzheimer's Disease: A Comprehensive Review

Alzheimer's disease (AD) is a complex neurodegenerative disease, affecting a significant part of the population. The majority of AD cases occur in the elderly with a typical age of onset of the disease above 65 years. AD presents a major burden for the healthcare system and since population is rapidly aging, the burden of the disease will increase in the future. However, no effective drug treatment for a full-blown disease has been developed to date. The genetic background of AD is extensively studied; numerous genome-wide association studies (GWAS) identified significant genes associated with increased risk of AD development. This review summarizes more than 100 risk loci. Many of them may serve as biomarkers of AD progression, even in the preclinical stage of the disease. Furthermore, we used GWAS data to identify key pathways of AD pathogenesis: cellular processes, metabolic processes, biological regulation, localization, transport, regulation of cellular processes, and neurological system processes. Gene clustering into molecular pathways can provide background for identification of novel molecular targets and may support the development of tailored and personalized treatment of AD.

Single-cell epigenomic analyses implicate candidate causal variants at inherited risk loci for Alzheimer's and Parkinson's diseases

Genome-wide association studies of neurological diseases have identified thousands of variants associated with disease phenotypes. However, most of these variants do not alter coding sequences, making it difficult to assign their function. Here, we present a multi-omic epigenetic atlas of the adult human brain through profiling of single-cell chromatin accessibility landscapes and three-dimensional chromatin interactions of diverse adult brain regions across a cohort of cognitively healthy individuals. We developed a machine-learning classifier to integrate this multi-omic framework and predict dozens of functional SNPs for Alzheimer's and Parkinson's diseases, nominating target genes and cell types for previously orphaned loci from genome-wide association studies. Moreover, we dissected the complex inverted haplotype of the MAPT (encoding tau) Parkinson's disease risk locus, identifying putative ectopic regulatory interactions in neurons that may mediate this disease association. This work expands understanding of inherited variation and provides a roadmap for the epigenomic dissection of causal regulatory variation in disease.

CoMM-S2: a collaborative mixed model using summary statistics in transcriptome-wide association studies

MOTIVATION

Although genome-wide association studies (GWAS) have deepened our understanding of the genetic architecture of complex traits, the mechanistic links that underlie how genetic variants cause complex traits remains elusive. To advance our understanding of the underlying mechanistic links, various consortia have collected a vast volume of genomic data that enable us to investigate the role that genetic variants play in gene expression regulation. Recently, a collaborative mixed model (CoMM) was proposed to jointly interrogate genome on complex traits by integrating both the GWAS dataset and the expression quantitative trait loci (eQTL) dataset. Although CoMM is a powerful approach that leverages regulatory information while accounting for the uncertainty in using an eQTL dataset, it requires individual-level GWAS data and cannot fully make use of widely available GWAS summary statistics. Therefore, statistically efficient methods that leverages transcriptome information using only summary statistics information from GWAS data are required.

RESULTS

In this study, we propose a novel probabilistic model, CoMM-S2, to examine the mechanistic role that genetic variants play, by using only GWAS summary statistics instead of individual-level GWAS data. Similar to CoMM which uses individual-level GWAS data, CoMM-S2 combines two models: the first model examines the relationship between gene expression and genotype, while the second model examines the relationship between the phenotype and the predicted gene expression from the first model. Distinct from CoMM, CoMM-S2 requires only GWAS summary statistics. Using both simulation studies and real data analysis, we demonstrate that even though CoMM-S2 utilizes GWAS summary statistics, it has comparable performance as CoMM, which uses individual-level GWAS data.

AVAILABILITY AND IMPLEMENTATION

The implement of CoMM-S2 is included in the CoMM package that can be downloaded from https://github.com/gordonliu810822/CoMM.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The role of innate immunity in Alzheimer's disease

The amyloid hypothesis has dominated Alzheimer's disease (AD) research for almost 30 years. This hypothesis hinges on the predominant clinical role of the amyloid beta (Aβ) peptide in propagating neurofibrillary tangles (NFTs) and eventual cognitive impairment in AD. Recent research in the AD field has identified the brain-resident macrophages, known as microglia, and their receptors as integral regulators of both the initiation and propagation of inflammation, Aβ accumulation, neuronal loss, and memory decline in AD. Emerging studies have also begun to reveal critical roles for distinct innate immune pathways in AD pathogenesis, which has led to great interest in harnessing the innate immune response as a therapeutic strategy to treat AD. In this review, we will highlight recent advancements in our understanding of innate immunity and inflammation in AD onset and progression. Additionally, there has been mounting evidence suggesting pivotal contributions of environmental factors and lifestyle choices in AD pathogenesis. Therefore, we will also discuss recent findings, suggesting that many of these AD risk factors influence AD progression via modulation of microglia and immune responses.

Friend, Foe or Both? Immune Activity in Alzheimer's Disease

Alzheimer's disease (AD) is marked by the presence of amyloid beta (Aβ) plaques, neurofibrillary tangles (NFT), neuronal death and synaptic loss, and inflammation in the brain. AD research has, in large part, been dedicated to the understanding of Aβ and NFT deposition as well as to the pharmacological reduction of these hallmarks. However, recent GWAS data indicates neuroinflammation plays a critical role in AD development, thereby redirecting research efforts toward unveiling the complexities of AD-associated neuroinflammation. It is clear that the innate immune system is intimately associated with AD progression, however, the specific roles of glia and neuroinflammation in AD pathology remain to be described. Moreover, inflammatory processes have largely been painted as detrimental to AD pathology, when in fact, many immune mechanisms such as phagocytosis aid in the reduction of AD pathologies. In this review, we aim to outline the delicate balance between the beneficial and detrimental aspects of immune activation in AD as a more thorough understanding of these processes is critical to development of effective therapeutics for AD.

Genome-Wide Association Studies for Cerebrospinal Fluid Soluble TREM2 in Alzheimer's Disease

Alzheimer’s disease (AD) is the most common form of dementia. Rare variants in triggering receptor expressed on myeloid cells 2 (TREM2) have been identified as risk factors for AD. Soluble TREM2 (sTREM2) in the cerebrospinal fluid (CSF) is a potential and novel biomarker of neuroinflammation implicated in the onset and progression of AD. To explore the roles of CSF sTREM2 on the pathogenesis of AD, we performed genome-wide association studies (GWAS) by using the data from Alzheimer’s Disease Neuroimaging Initiative (ADNI). We found CSF sTREM2 levels were elevated with the disease stages, but there was no significant difference between that of AD patients and normal participants. CSF sTREM2 was positively correlated with CSF total tau and phosphorylated-tau levels (ρ > 0.35, p < 1e-06; ρ > 0.32, p < 1e-05, respectively) for all disease states. We identified the most significant CSF sTREM2 related locus was rs7232 (FDR = 3.01e-08), a missense variant in MS4A6A gene of chromosome 11. Moreover, we also detected rs7232 was highly associated with MS4A6A gene expression (FDR = 1.37e-18). In addition, our pathway analysis for our significant GWAS results showed that biological processes for regulation of viruses and immune response were highly overrepresented or enriched. Our study suggests that CSF sTREM2 plays an informative role in AD progression. Moreover, CSF sTREM2 and AD is highly related to viral infections and immune response.

New genetic players in late-onset Alzheimer's disease: Findings of genome-wide association studies

Late-onset Alzheimer's disease (LOAD) or sporadic AD is the most common form of AD. The precise pathogenetic changes that trigger the development of AD remain largely unknown. Large-scale genome-wide association studies (GWASs) have identified single-nucleotide polymorphisms in multiple genes which are associated with AD; most notably, these are ABCA7, bridging integrator 1(B1N1), triggering receptor expressed on myeloid cells 2 (TREM2), CD33, clusterin (CLU), complement receptor 1 (CRI), ephrin type-A receptor 1 (EPHA1), membrane-spanning 4-domains, subfamily A (MS4A) and phosphatidylinositol binding clathrin assembly protein (PICALM) genes. The proteins coded by the candidate genes participate in a variety of cellular processes such as oxidative balance, protein metabolism, cholesterol metabolism and synaptic function. This review summarizes the major gene loci affecting LOAD identified by large GWASs. Tentative mechanisms have also been elaborated in various studies by which the proteins coded by these genes may exert a role in AD pathogenesis have also been elaborated. The review suggests that these may together affect LOAD pathogenesis in a complementary fashion.

Protective Variants in Alzheimer's Disease

PURPOSE OF REVIEW

Over the last decade over 40 loci have been associated with risk of Alzheimer's disease (AD). However, most studies have either focused on identifying risk loci or performing unbiased screens without a focus on protective variation in AD. Here, we provide a review of known protective variants in AD and their putative mechanisms of action. Additionally, we recommend strategies for finding new protective variants.

RECENT FINDINGS

Recent Genome-Wide Association Studies have identified both common and rare protective variants associated with AD. These include variants in or near APP, APOE, PLCG2, MS4A, MAPT-KANSL1, RAB10, ABCA1, CCL11, SORL1, NOCT, SCL24A4-RIN3, CASS4, EPHA1, SPPL2A, and NFIC.

SUMMARY

There are very few protective variants with functional evidence and a derived allele with a frequency below 20%. Additional fine mapping and multi-omic studies are needed to further validate and characterize known variants as well as specialized genome-wide scans to identify novel variants.

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.

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.

Single-Cell RNA Sequencing of Microglia throughout the Mouse Lifespan and in the Injured Brain Reveals Complex Cell-State Changes

Microglia, the resident immune cells of the brain, rapidly change states in response to their environment, but we lack molecular and functional signatures of different microglial populations. Here, we analyzed the RNA expression patterns of more than 76,000 individual microglia in mice during development, in old age, and after brain injury. Our analysis uncovered at least nine transcriptionally distinct microglial states, which expressed unique sets of genes and were localized in the brain using specific markers. The greatest microglial heterogeneity was found at young ages; however, several states-including chemokine-enriched inflammatory microglia-persisted throughout the lifespan or increased in the aged brain. Multiple reactive microglial subtypes were also found following demyelinating injury in mice, at least one of which was also found in human multiple sclerosis lesions. These distinct microglia signatures can be used to better understand microglia function and to identify and manipulate specific subpopulations in health and disease.

Re-thinking Alzheimer's disease therapeutic targets using gene-based tests

Background

Alzheimer's disease (AD) is a devastating condition with no known effective drug treatments. Existing drugs only alleviate symptoms. Given repeated expensive drug failures, we assessed systematically whether approved and investigational AD drugs are targeting products of genes strongly associated with AD and whether these genes are targeted by existing drugs for other indications which could be re-purposed.

Methods

We identified genes strongly associated with late-onset AD from the loci of genetic variants associated with AD at genome-wide-significance and from a gene-based test applied to the most extensively genotyped late-onset AD case (n = 17,008)-control (n = 37,154) study, the International Genomics of Alzheimer's Project. We used three gene-to-drug cross-references, Kyoto Encyclopedia of Genes and Genomes, Drugbank and Drug Repurposing Hub, to identify genetically validated targets of AD drugs and any existing drugs or nutraceuticals targeting products of the genes strongly associated with late-onset AD.

Findings

A total of 67 autosomal genes (forming 9 gene clusters) were identified as strongly associated with late-onset AD, 28 from the loci of single genetic variants, 51 from the gene-based test and 12 by both methods. Existing approved or investigational AD drugs did not target products of any of these 67 genes. Drugs for other indications targeted 11 of these genes, including immunosuppressive disease-modifying anti-rheumatic drugs targeting PTK2B gene products.

Interpretation

Approved and investigational AD drugs are not targeting products of genes strongly associated with late-onset AD. However, other drugs targeting products of these genes exist and could perhaps be re-purposing to combat late-onset AD after further scrutiny.

MS4A2-rs573790 Is Associated With Aspirin-Exacerbated Respiratory Disease: Replicative Study Using a Candidate Gene Strategy

Aspirin exacerbated respiratory disease (AERD) is a set of diseases of the unified airway, and its physiopathology is related to disruption of the metabolism of arachidonic acid (AA). Genetic association studies in AERD had explored single nucleotide polymorphism (SNPs) in several genes related to many mechanisms (AA metabolism, inflammation, drug metabolism, etc.) but most lack validation stages in second populations. Our aim is to evaluated whether contribution to susceptibility of SNPs reported in other populations are associated with AERD in Mexican Mestizo patients. We developed a replicative study in two stages. In the first, 381 SNPs selected by fine mapping of associated genes, (previously reported in the literature), were integrated into a microarray and tested in three groups (AERD, asthma and healthy controls -HC-) using the GoldenGate array. Results associated to risk based on genetic models [comparing: AERD vs. HC (comparison 1, C1), AERD vs. asthma (C2), and asthma vs. HC (C3)] were validated in the second stage in other population groups using qPCR. In the first stage, we identified 11 SNPs associated with risk in C1.The top SNPs were ACE-rs4309C (p = 0.0001) and MS4A2-rs573790C (p = 0.0002). In C2, we detected 14 SNPs, including ACE-rs4309C (p = 0.0001). In C3, we found MS4A2-rs573790C (p = 0.001). Using genetic models, C1 MS4A2-rs57370 CC (p = 0.001), and ACE-rs4309 CC (p = 0.002) had associations. In C2 ACE-rs4309 CC (p = 0.0001) and C3 MS4A2-rs573790 CC (p = 0.001) were also associate with risk. In the second stage, only MS4A2-rs573790 CC had significance in C1 and C3 (p = 0.008 and p = 0.03). We concluded that rs573790 in the MS4A2 gene is the only SNP that supports an association with AERD in Mexican Mestizo patients in both stages of the study.

Longitudinal Genotype-Phenotype Association Study through Temporal Structure Auto-Learning Predictive Model

With the rapid development of high-throughput genotyping and neuroimaging techniques, imaging genetics has drawn significant attention in the study of complex brain diseases such as Alzheimer's disease (AD). Research on the associations between genotype and phenotype improves the understanding of the genetic basis and biological mechanisms of brain structure and function. AD is a progressive neurodegenerative disease; therefore, the study on the relationship between single nucleotide polymorphism (SNP) and longitudinal variations of neuroimaging phenotype is crucial. Although some machine learning models have recently been proposed to capture longitudinal patterns in genotype-phenotype association studies, most machine-learning models base the learning on fixed structure among longitudinal prediction tasks rather than automatically learning the interrelationships. In response to this challenge, we propose a new automated time structure learning model to automatically reveal the longitudinal genotype-phenotype interactions and exploits such learned structure to enhance the phenotypic predictions. We proposed an efficient optimization algorithm for our model and provided rigorous theoretical convergence proof. We performed experiments on the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort for longitudinal phenotype prediction, including 3123 SNPs and 2 biomarkers (Voxel-Based Morphometry and FreeSurfer). The empirical results validate that our proposed model is superior to the counterparts. In addition, the best SNPs identified by our model have been replicated in the literature, which justifies our prediction.

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.

Late onset Alzheimer's disease genetics implicates microglial pathways in disease risk

Alzheimer's disease (AD) is a highly heritable complex disease with no current effective prevention or treatment. The majority of drugs developed for AD focus on the amyloid cascade hypothesis, which implicates Aß plaques as a causal factor in the disease. However, it is possible that other underexplored disease-associated pathways may be more fruitful targets for drug development. Findings from gene network analyses implicate immune networks as being enriched in AD; many of the genes in these networks fall within genomic regions that contain common and rare variants that are associated with increased risk of developing AD. Of these genes, several (including CR1, SPI1, the MS4As, TREM2, ABCA7, CD33, and INPP5D) are expressed by microglia, the resident immune cells of the brain. We summarize the gene network and genetics findings that implicate that these microglial genes are involved in AD, as well as several studies that have looked at the expression and function of these genes in microglia and in the context of AD. We propose that these genes are contributing to AD in a non-Aß-dependent fashion.

Longitudinal Genotype-Phenotype Association Study via Temporal Structure Auto-Learning Predictive Model

With rapid progress in high-throughput genotyping and neuroimaging, imaging genetics has gained significant attention in the research of complex brain disorders, such as Alzheimer's Disease (AD). The genotype-phenotype association study using imaging genetic data has the potential to reveal genetic basis and biological mechanism of brain structure and function. AD is a progressive neurodegenerative disease, thus, it is crucial to look into the relations between SNPs and longitudinal variations of neuroimaging phenotypes. Although some machine learning models were newly presented to capture the longitudinal patterns in genotype-phenotype association study, most of them required fixed longitudinal structures of prediction tasks and could not automatically learn the interrelations among longitudinal prediction tasks. To address this challenge, we proposed a novel temporal structure auto-learning model to automatically uncover longitudinal genotype-phenotype interrelations and utilized such interrelated structures to enhance phenotype prediction in the meantime. We conducted longitudinal phenotype prediction experiments on the ADNI cohort including 3,123 SNPs and 2 types of biomarkers, VBM and FreeSurfer. Empirical results demonstrated advantages of our proposed model over the counterparts. Moreover, available literature was identified for our top selected SNPs, which demonstrated the rationality of our prediction results. An executable program is available online at https://github.com/littleq1991/sparse_lowRank_regression.

MS4A4A: a novel cell surface marker for M2 macrophages and plasma cells

MS4A4A is a member of the membrane-spanning, four domain family, subfamily A (MS4A) that includes CD20 (MS4A1), FcRβ (MS4A2) and Htm4 (MS4A3). Like the first three members of this family, transcription of MS4A4A appears to be limited to hematopoietic cells. To evaluate expression of the MS4A4A protein in hematopoietic cell lineages and subsets we generated monoclonal antibodies against extracellular epitopes for use in flow cytometry. In human peripheral blood we found that MS4A4A is expressed at the plasma membrane in monocytes but not in granulocytes or lymphocytes. In vitro differentiation of monocytes demonstrated that MS4A4A is expressed in immature but not activated dendritic cells, and in macrophages generated in the presence of interleukin-4 ('alternatively activated' or M2 macrophages) but not by interferon-γ and lipopolysaccharide ('classically' activated or M1 macrophages). MS4A4A was expressed in the U937 monocytic cell line only after differentiation. In normal bone marrow, MS4A4A was expressed in mature monocytes but was undetected, or detected at only a low level, in myeloid/monocytic precursors, as well as their malignant counterparts in patients with various subtypes of myeloid leukemia. Although MS4A4A was not expressed in healthy B lymphocytes, it was highly expressed in normal plasma cells, CD138+ cells from multiple myeloma patients, and bone marrow B cells from a patient with mantle cell lymphoma. These findings suggest immunotherapeutic potential for MS4A4A antibodies in targeting alternatively activated macrophages such as tumor-associated macrophages, and in the treatment of multiple myeloma and mantle cell lymphoma.

Cerebrospinal fluid soluble TREM2 is higher in Alzheimer disease and associated with mutation status

Low frequency coding variants in TREM2 are associated with increased Alzheimer disease (AD) risk, while loss of functions mutations in the gene lead to an autosomal recessive early-onset dementia, named Nasu-Hakola disease (NHD). TREM2 can be detected as a soluble protein in cerebrospinal fluid (CSF) and plasma, and its CSF levels are elevated in inflammatory CNS diseases. We measured soluble TREM2 (sTREM2) in the CSF of a large AD case-control dataset (n = 180) and 40 TREM2 risk variant carriers to determine whether CSF sTREM2 levels are associated with AD status or mutation status. We also performed genetic studies to identify genetic variants associated with CSF sTREM2 levels. CSF, but not plasma, sTREM2 was highly correlated with CSF total tau and phosphorylated-tau levels (r = 0.35, P < 1×10(-4); r = 0.40, P < 1×10(-4), respectively), but not with CSF Aβ42. AD cases presented higher CSF sTREM2 levels than controls (P = 0.01). Carriers of NHD-associated TREM2 variants presented significantly lower CSF sTREM2 levels, supporting the hypothesis that these mutations lead to reduced protein production/function (R136Q, D87N, Q33X or T66M; P = 1×10(-3)). In contrast, CSF sTREM2 levels were significantly higher in R47H carriers compared to non-carriers (P = 6×10(-3)), suggesting that this variant does not impact protein expression and increases AD risk through a different pathogenic mechanism than NHD variants. In GWAS analyses for CSF sTREM2 levels the most significant signal was located on the MS4A gene locus (P = 5.45 × 10(-07)) corresponding to one of the SNPs reported to be associated with AD risk in this locus. Furthermore, SNPs involved in pathways related to virus cellular entry and vesicular trafficking were overrepresented, suggesting that CSF sTREM2 levels could be an informative phenotype for AD.

Microglial genes regulating neuroinflammation in the progression of Alzheimer's disease

Neuroinflammation is a pathological hallmark of Alzheimer's disease (AD), and microglia, the brain's resident phagocyte, are pivotal for the immune response observed in AD. Microglia act as sentinel and protective cells, but may become inappropriately reactive in AD to drive neuropathology. Recent Genome Wide Association Studies (GWAS) have identified more than 20 gene variants associated with an increased risk of late-onset AD (LOAD), the most prevalent form of AD [1]. The findings strongly implicate genes related to the immune response (CR1, CD33, MS4A, CLU, ABCA7, EPHA1 and HLA-DRB5-HLA-DRB1), endocytosis (BIN1, PICALM, CD2AP, EPHA1 and SORL1) and lipid biology (CLU, ABCA7 and SORL1) [2-8], and many encode proteins which are highly expressed in microglia [1]. Furthermore, recent identification of a low frequency mutation in the gene encoding the triggering receptor expressed in myeloid cells 2 protein (TREM2) confers increased risk of AD in LOAD cohorts with an effect size similar to that for APOE, until recently the only identified genetic risk factor associated with LOAD [9,10(••)] (Figure 1). The present review summarises our current understanding of the probable roles of microglial genes in the regulation of neuroinflammatory processes in AD and their relation to other processes affecting the disease's progression.

Calmodulin Binding Proteins and Alzheimer's Disease

The small, calcium-sensor protein, calmodulin, is ubiquitously expressed and central to cell function in all cell types. Here the literature linking calmodulin to Alzheimer's disease is reviewed. Several experimentally-verified calmodulin-binding proteins are involved in the formation of amyloid-β plaques including amyloid-β protein precursor, β-secretase, presenilin-1, and ADAM10. Many others possess potential calmodulin-binding domains that remain to be verified. Three calmodulin binding proteins are associated with the formation of neurofibrillary tangles: two kinases (CaMKII, CDK5) and one protein phosphatase (PP2B or calcineurin). Many of the genes recently identified by genome wide association studies and other studies encode proteins that contain putative calmodulin-binding domains but only a couple (e.g., APOE, BIN1) have been experimentally confirmed as calmodulin binding proteins. At least two receptors involved in calcium metabolism and linked to Alzheimer's disease (mAchR; NMDAR) have also been identified as calmodulin-binding proteins. In addition to this, many proteins that are involved in other cellular events intimately associated with Alzheimer's disease including calcium channel function, cholesterol metabolism, neuroinflammation, endocytosis, cell cycle events, and apoptosis have been tentatively or experimentally verified as calmodulin binding proteins. The use of calmodulin as a potential biomarker and as a therapeutic target is discussed.