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

Unraveling the genetic architecture of blood unfolded p-53 among non-demented elderlies: novel candidate genes for early Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a heritable neurodegenerative disease whose long asymptomatic phase makes the early diagnosis of it pivotal. Blood U-p53 has recently emerged as a superior predictive biomarker for AD in the early stages. We hypothesized that genetic variants associated with blood U-p53 could reveal novel loci and pathways involved in the early stages of AD.

RESULTS

We performed a blood U-p53 Genome-wide association study (GWAS) on 484 healthy and mild cognitively impaired subjects from the ADNI cohort using 612,843 Single nucleotide polymorphisms (SNPs). We performed a pathway analysis and prioritized candidate genes using an AD single-cell gene program. We fine-mapped the intergenic SNPs by leveraging a cell-type-specific enhancer-to-gene linking strategy using a brain single-cell multimodal dataset. We validated the candidate genes in an independent brain single-cell RNA-seq and the ADNI blood transcriptome datasets. The rs279686 between AASS and FEZF1 genes was the most significant SNP (p-value = 4.82 × 10-7). Suggestive pathways were related to the immune and nervous systems. Twenty-three candidate genes were prioritized at 27 suggestive loci. Fine-mapping of 5 intergenic loci yielded nine cell-specific candidate genes. Finally, 15 genes were validated in the independent single-cell RNA-seq dataset, and five were validated in the ADNI blood transcriptome dataset.

CONCLUSIONS

We underlined the importance of performing a GWAS on an early-stage biomarker of AD and leveraging functional omics datasets for pinpointing causal genes in AD. Our study prioritized nine genes (SORCS1, KIF5C, TMEFF2, TMEM63C, HLA-E, ATAT1, TUBB, ARID1B, and RUNX1) strongly implicated in the early stages of AD.

Multi-ancestry meta-analysis and fine-mapping in Alzheimer's disease

Genome-wide association studies (GWAS) of Alzheimer's disease are predominantly carried out in European ancestry individuals despite the known variation in genetic architecture and disease prevalence across global populations. We leveraged published GWAS summary statistics from European, East Asian, and African American populations, and an additional GWAS from a Caribbean Hispanic population using previously reported genotype data to perform the largest multi-ancestry GWAS meta-analysis of Alzheimer's disease and related dementias to date. This method allowed us to identify two independent novel disease-associated loci on chromosome 3. We also leveraged diverse haplotype structures to fine-map nine loci with a posterior probability >0.8 and globally assessed the heterogeneity of known risk factors across populations. Additionally, we compared the generalizability of multi-ancestry- and single-ancestry-derived polygenic risk scores in a three-way admixed Colombian population. Our findings highlight the importance of multi-ancestry representation in uncovering and understanding putative factors that contribute to risk of Alzheimer's disease and related dementias.

Predictive network analysis identifies JMJD6 and other potential key drivers in Alzheimer's disease

Despite decades of genetic studies on late-onset Alzheimer's disease, the underlying molecular mechanisms remain unclear. To better comprehend its complex etiology, we use an integrative approach to build robust predictive (causal) network models using two large human multi-omics datasets. We delineate bulk-tissue gene expression into single cell-type gene expression and integrate clinical and pathologic traits, single nucleotide variation, and deconvoluted gene expression for the construction of cell type-specific predictive network models. Here, we focus on neuron-specific network models and prioritize 19 predicted key drivers modulating Alzheimer's pathology, which we then validate by knockdown in human induced pluripotent stem cell-derived neurons. We find that neuronal knockdown of 10 of the 19 targets significantly modulates levels of amyloid-beta and/or phosphorylated tau peptides, most notably JMJD6. We also confirm our network structure by RNA sequencing in the neurons following knockdown of each of the 10 targets, which additionally predicts that they are upstream regulators of REST and VGF. Our work thus identifies robust neuronal key drivers of the Alzheimer's-associated network state which may represent therapeutic targets with relevance to both amyloid and tau pathology in Alzheimer's disease.

Soluble TREM2 in body fluid in Alzheimer's disease and Parkinson's disease

BACKGROUND

Previous studies showed conflicting results regarding soluble triggering receptor expressed on myeloid cells 2 (sTREM2) level alteration in body fluid in Alzheimer's disease (AD) and Parkinson's disease (PD).

METHODS

We applied the STATA 12.0 software to compute standard mean difference (SMD) and 95% confidence interval (CI).

RESULTS

The study showed elevated sTREM2 level in cerebrospinal fluid (CSF) in AD, mild cognitive impairment (MCI), and preclinical AD (pre-AD) patients, compared to healthy controls (HCs) with random effects models (AD: SMD 0.28, 95% CI 0.12 to 0.44, I² = 77.6%, p < 0.001; MCI: SMD 0.29, 95% CI 0.09 to 0.48, I² = 89.7%, p < 0.001; pre-AD: SMD 0.24, 95% CI 0.00 to 0.48, I² = 80.8%, p < 0.001). The study showed no significant difference in sTREM2 level in plasma between AD patients and HCs with a random effects model (SMD 0.06, 95% CI - 0.16 to 0.28, I² = 65.6%, p = 0.008). The study showed no significant difference in sTREM2 level in CSF or plasma between PD patients and HCs with random effects models (CSF: SMD 0.33, 95% CI - 0.02 to 0.67, I² = 85.6%, p < 0.001; plasma: SMD 0.37, 95% CI - 0.17 to 0.92, I² = 77.8%, p = 0.011).

CONCLUSIONS

In conclusion, the study highlighted the CSF sTREM2 as a promising biomarker in the different clinical stages of AD. More studies were essential to explore the CSF and plasmatic concentrations of sTREM2 alteration in PD.

Genome-wide association study of brain biochemical phenotypes reveals distinct genetic architecture of Alzheimer's disease related proteins

BACKGROUND

Alzheimer's disease (AD) is neuropathologically characterized by amyloid-beta (Aβ) plaques and neurofibrillary tangles. The main protein components of these hallmarks include Aβ40, Aβ42, tau, phosphor-tau, and APOE. We hypothesize that genetic variants influence the levels and solubility of these AD-related proteins in the brain; identifying these may provide key insights into disease pathogenesis.

METHODS

Genome-wide genotypes were collected from 441 AD cases, imputed to the haplotype reference consortium (HRC) panel, and filtered for quality and frequency. Temporal cortex levels of five AD-related proteins from three fractions, buffer-soluble (TBS), detergent-soluble (Triton-X = TX), and insoluble (Formic acid = FA), were available for these same individuals. Variants were tested for association with each quantitative biochemical measure using linear regression, and GSA-SNP2 was used to identify enriched Gene Ontology (GO) terms. Implicated variants and genes were further assessed for association with other relevant variables.

RESULTS

We identified genome-wide significant associations at seven novel loci and the APOE locus. Genes and variants at these loci also associate with multiple AD-related measures, regulate gene expression, have cell-type specific enrichment, and roles in brain health and other neuropsychiatric diseases. Pathway analysis identified significant enrichment of shared and distinct biological pathways.

CONCLUSIONS

Although all biochemical measures tested reflect proteins core to AD pathology, our results strongly suggest that each have unique genetic architecture and biological pathways that influence their specific biochemical states in the brain. Our novel approach of deep brain biochemical endophenotype GWAS has implications for pathophysiology of proteostasis in AD that can guide therapeutic discovery efforts focused on these proteins.

MED13 and glycolysis are conserved modifiers of α-synuclein-associated neurodegeneration

α-Synuclein (α-syn) is important in synucleinopathies such as Parkinson's disease (PD). While genome-wide association studies (GWASs) of synucleinopathies have identified many risk loci, the underlying genes have not been shown for most loci. Using Drosophila, we screened 3,471 mutant chromosomes for genetic modifiers of α-synuclein and identified 12 genes. Eleven modifiers have human orthologs associated with diseases, including MED13 and CDC27, which lie within PD GWAS loci. Drosophila Skd/Med13 and glycolytic enzymes are co-upregulated by α-syn-associated neurodegeneration. While elevated α-syn compromises mitochondrial function, co-expressing skd/Med13 RNAi and α-syn synergistically increase the ratio of oxidized-to-reduced glutathione. The resulting neurodegeneration can be suppressed by overexpressing a glycolytic enzyme or treatment with deferoxamine, suggesting that compensatory glycolysis is neuroprotective. In addition, the functional relationship between α-synuclein, MED13, and glycolytic enzymes is conserved between flies and mice. We propose that hypoxia-inducible factor and MED13 are part of a druggable pathway for PD.

The road to precision medicine: Eliminating the "One Size Fits All" approach in Alzheimer's disease

The expeditious advancement of Alzheimer's Disease (AD) is a threat to the global healthcare system, that is further supplemented by therapeutic failure. The prevalence of this disorder has been expected to quadrupole by 2050, thereby exerting a tremendous economic pressure on medical sector, worldwide. Thus, there is a dire need of a change in conventional approaches and adopt a novel methodology of disease prevention, treatment and diagnosis. Precision medicine offers a personalized approach to disease management, It is dependent upon genetic, environmental and lifestyle factors associated with the individual, aiding to develop tailored therapeutics. Precision Medicine Initiatives are launched, worldwide, to facilitate the integration of personalized models and clinical medicine. The review aims to provide a comprehensive understanding of the neuroinflammatory processes causing AD, giving a brief overview of the disease interventions. This is further followed by the role of precision medicine in AD, constituting the genetic perspectives, operation of personalized form of medicine and optimization of clinical trials with the 3 R's, showcasing an in-depth understanding of this novel approach in varying aspects of the healthcare industry, to provide an opportunity to the global AD researchers to elucidate suitable therapeutic regimens in clinically and pathologically complex diseases, like AD.

Simplify enrichment: A bioconductor package for clustering and visualizing functional enrichment results

Functional enrichment analysis or gene set enrichment analysis is a basic bioinformatics method that evaluates the biological importance of a list of genes of interest. However, it may produce a long list of significant terms with highly redundant information that is difficult to summarize. Current tools to simplify enrichment results by clustering them into groups either still produce redundancy between clusters or do not retain consistent term similarities within clusters. We propose a new method named binary cut for clustering similarity matrices of functional terms. Through comprehensive benchmarks on both simulated and real-world datasets, we demonstrated that binary cut could efficiently cluster functional terms into groups where terms showed consistent similarities within groups and were mutually exclusive between groups. We compared binary cut clustering on the similarity matrices obtained from different similarity measures and found that semantic similarity worked well with binary cut, while similarity matrices based on gene overlap showed less consistent patterns. We implemented the binary cut algorithm in the R package simplifyEnrichment, which additionally provides functionalities for visualizing, summarizing, and comparing the clustering. The simplifyEnrichment package and the documentation are available at https://bioconductor.org/packages/simplifyEnrichment/.

Inflammation and Brain Structure in Schizophrenia and Other Neuropsychiatric Disorders: A Mendelian Randomization Study

Importance

Previous in vitro and postmortem research suggests that inflammation may lead to structural brain changes via activation of microglia and/or astrocytic dysfunction in a range of neuropsychiatric disorders.

Objective

To investigate the relationship between inflammation and changes in brain structures in vivo and to explore a transcriptome-driven functional basis with relevance to mental illness.

Design, Setting, and Participants

This study used multistage linked analyses, including mendelian randomization (MR), gene expression correlation, and connectivity analyses. A total of 20 688 participants in the UK Biobank, which includes clinical, genomic, and neuroimaging data, and 6 postmortem brains from neurotypical individuals in the Allen Human Brain Atlas (AHBA), including RNA microarray data. Data were extracted in February 2021 and analyzed between March and October 2021.

Exposures

Genetic variants regulating levels and activity of circulating interleukin 1 (IL-1), IL-2, IL-6, C-reactive protein (CRP), and brain-derived neurotrophic factor (BDNF) were used as exposures in MR analyses.

Main Outcomes and Measures

Brain imaging measures, including gray matter volume (GMV) and cortical thickness (CT), were used as outcomes. Associations were considered significant at a multiple testing-corrected threshold of P < 1.1 × 10-4. Differential gene expression in AHBA data was modeled in brain regions mapped to areas significant in MR analyses; genes were tested for biological and disease overrepresentation in annotation databases and for connectivity in protein-protein interaction networks.

Results

Of 20 688 participants in the UK Biobank sample, 10 828 (52.3%) were female, and the mean (SD) age was 55.5 (7.5) years. In the UK Biobank sample, genetically predicted levels of IL-6 were associated with GMV in the middle temporal cortex (z score, 5.76; P = 8.39 × 10-9), inferior temporal (z score, 3.38; P = 7.20 × 10-5), fusiform (z score, 4.70; P = 2.60 × 10-7), and frontal (z score, -3.59; P = 3.30 × 10-5) cortex together with CT in the superior frontal region (z score, -5.11; P = 3.22 × 10-7). No significant associations were found for IL-1, IL-2, CRP, or BDNF after correction for multiple comparison. In the AHBA sample, 5 of 6 participants (83%) were male, and the mean (SD) age was 42.5 (13.4) years. Brain-wide coexpression analysis showed a highly interconnected network of genes preferentially expressed in the middle temporal gyrus (MTG), which further formed a highly connected protein-protein interaction network with IL-6 (enrichment test of expected vs observed network given the prevalence and degree of interactions in the STRING database: 43 nodes/30 edges observed vs 8 edges expected; mean node degree, 1.4; genome-wide significance, P = 4.54 × 10-9). MTG differentially expressed genes that were functionally enriched for biological processes in schizophrenia, autism spectrum disorder, and epilepsy.

Conclusions and Relevance

In this study, genetically determined IL-6 was associated with brain structure and potentially affects areas implicated in developmental neuropsychiatric disorders, including schizophrenia and autism.

Genome- and epigenome-wide studies of plasma protein biomarkers for Alzheimer's disease implicate TBCA and TREM2 in disease risk

Introduction

The levels of many blood proteins are associated with Alzheimer's disease (AD) or its pathological hallmarks. Elucidating the molecular factors that control circulating levels of these proteins may help to identify proteins associated with disease risk mechanisms.

Methods

Genome-wide and epigenome-wide studies (nindividuals ≤1064) were performed on plasma levels of 282 AD-associated proteins, identified by a structured literature review. Bayesian penalized regression estimated contributions of genetic and epigenetic variation toward inter-individual differences in plasma protein levels. Mendelian randomization (MR) and co-localization tested associations between proteins and disease-related phenotypes.

Results

Sixty-four independent genetic and 26 epigenetic loci were associated with 45 proteins. Novel findings included an association between plasma triggering receptor expressed on myeloid cells 2 (TREM2) levels and a polymorphism and cytosine-phosphate-guanine (CpG) site within the MS4A4A locus. Higher plasma tubulin-specific chaperone A (TBCA) and TREM2 levels were significantly associated with lower AD risk.

Discussion

Our data inform the regulation of biomarker levels and their relationships with AD.

CSF sTREM2 in neurological diseases: a two-sample Mendelian randomization study

Background

Soluble triggering receptor expressed on myeloid cells 2 (sTREM2) in cerebrospinal fluid (CSF) has been described as a biomarker for microglial activation, which were observed increased in a variety of neurological disorders.

Objective

Our objective was to explore whether genetically determined CSF sTREM2 levels are causally associated with different neurological diseases by conducting a two-sample Mendelian randomization (MR) study.

Methods

Single nucleotide polymorphisms significantly associated with CSF sTREM2 levels were selected as instrumental variables to estimate the causal effects on clinically common neurological diseases, including stroke, Alzheimer’s diseases, Parkinson’s diseases, amyotrophic lateral sclerosis, multiple sclerosis, and epilepsy and their subtypes. Summary-level statistics of both exposure and outcomes were applied in an MR framework.

Results

Genetically predicted per 1 pg/dL increase of CSF sTREM2 levels was associated with higher risk of multiple sclerosis (OR = 1.038, 95%CI = 1.014–1.064, p = 0.002). Null association was found in risk of other included neurological disorders.

Conclusions

These findings provide support for a potential causal relationship between elevated CSF sTREM2 levels and higher risk of multiple sclerosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02443-9.

Diagnostic Accuracy of Blood-Based Biomarker Panels: A Systematic Review

Background

Because of high prevalence of Alzheimer's disease (AD) in low- and middle-income countries (LMICs), there is an urgent need for inexpensive and minimally invasive diagnostic tests to detect biomarkers in the earliest and asymptomatic stages of the disease. Blood-based biomarkers are predicted to have the most impact for use as a screening tool and predict the onset of AD, especially in LMICs. Furthermore, it has been suggested that panels of markers may perform better than single protein candidates.

Methods

Medline/Pubmed was searched to identify current relevant studies published from January 2016 to December 2020. We included all full-text articles examining blood-based biomarkers as a set of protein markers or panels to aid in AD's early diagnosis, prognosis, and characterization.

Results

Seventy-six articles met the inclusion criteria for systematic review. Majority of the studies reported plasma and serum as the main source for biomarker determination in blood. Protein-based biomarker panels were reported to aid in AD diagnosis and prognosis with better accuracy than individual biomarkers. Conventional (amyloid-beta and tau) and neuroinflammatory biomarkers, such as amyloid beta-42, amyloid beta-40, total tau, phosphorylated tau-181, and other tau isoforms, were the most represented. We found the combination of amyloid beta-42/amyloid beta-40 ratio and APOEε4 status to be most represented with high accuracy for predicting amyloid beta-positron emission tomography status.

Conclusion

Assessment of Alzheimer's disease biomarkers in blood as a non-invasive and cost-effective alternative will potentially contribute to early diagnosis and improvement of therapeutic interventions. Given the heterogeneous nature of AD, combination of markers seems to perform better in the diagnosis and prognosis of the disease than individual biomarkers.

Dissection of the polygenic architecture of neuronal Aβ production using a large sample of individual iPSC lines derived from Alzheimer's disease patients

Genome-wide association studies have demonstrated that polygenic risks shape Alzheimer's disease (AD). To elucidate the polygenic architecture of AD phenotypes at a cellular level, we established induced pluripotent stem cells from 102 patients with AD, differentiated them into cortical neurons and conducted a genome-wide analysis of the neuronal production of amyloid β (Aβ). Using such a cellular dissection of polygenicity (CDiP) approach, we identified 24 significant genome-wide loci associated with alterations in Aβ production, including some loci not previously associated with AD, and confirmed the influence of some of the corresponding genes on Aβ levels by the use of small interfering RNA. CDiP genotype sets improved the predictions of amyloid positivity in the brains and cerebrospinal fluid of patients in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Secondary analyses of exome sequencing data from the Japanese ADNI and the ADNI cohorts focused on the 24 CDiP-derived loci associated with alterations in Aβ led to the identification of rare AD variants in KCNMA1.

Neuroimmune contributions to Alzheimer's disease: a focus on human data

The past decade has seen the convergence of a series of new insights that arose from genetic and systems analyses of Alzheimer's disease (AD) with a wealth of epidemiological data from a variety of fields; this resulted in renewed interest in immune responses as important, potentially causal components of AD. Here, we focus primarily on a review of human data which has recently yielded a set of robust, reproducible results that exist in a much larger universe of conflicting reports stemming from small studies with important limitations in their study design. Thus, we are at an important crossroads in efforts to first understand at which step of the long, multiphasic course of AD a given immune response may play a causal role and then modulate this response to slow or block the pathophysiology of AD. We have a wealth of new experimental tools, analysis methods, and capacity to sample human participants at large scale longitudinally; these resources, when coupled to a foundation of reproducible results and novel study designs, will enable us to monitor human immune function in the CNS at the level of complexity that is required while simultaneously capturing the state of the peripheral immune system. This integration of peripheral and central perturbations in immune responses results in pathologic responses in the central nervous system parenchyma where specialized cellular microenvironments composed of multiple cell subtypes respond to these immune perturbations as well as to environmental exposures, comorbidities and the impact of the advancing life course. Here, we offer an overview that seeks to illustrate the large number of interconnecting factors that ultimately yield the neuroimmune component of AD.

An integrated brain-specific network identifies genes associated with neuropathologic and clinical traits of Alzheimer’s disease

Alzheimer’s disease (AD) has a strong genetic predisposition. However, its risk genes remain incompletely identified. We developed an Alzheimer’s brain gene network-based approach to predict AD-associated genes by leveraging the functional pattern of known AD-associated genes. Our constructed network outperformed existing networks in predicting AD genes. We then systematically validated the predictions using independent genetic, transcriptomic, proteomic data, neuropathological and clinical data. First, top-ranked genes were enriched in AD-associated pathways. Second, using external gene expression data from the Mount Sinai Brain Bank study, we found that the top-ranked genes were significantly associated with neuropathological and clinical traits, including the Consortium to Establish a Registry for Alzheimer’s Disease score, Braak stage score and clinical dementia rating. The analysis of Alzheimer’s brain single-cell RNA-seq data revealed cell-type-specific association of predicted genes with early pathology of AD. Third, by interrogating proteomic data in the Religious Orders Study and Memory and Aging Project and Baltimore Longitudinal Study of Aging studies, we observed a significant association of protein expression level with cognitive function and AD clinical severity. The network, method and predictions could become a valuable resource to advance the identification of risk genes for AD.

Alternative Splicing Regulation of Low-Frequency Genetic Variants in Exon 2 of TREM2 in Alzheimer's Disease by Splicing-Based Aggregation

TREM2 is among the most well-known Alzheimer’s disease (AD) risk genes; however, the functional roles of its AD-associated variants remain to be elucidated, and most known risk alleles are low-frequency variants whose investigation is challenging. Here, we utilized a splicing-guided aggregation method in which multiple low-frequency TREM2 variants were bundled together to investigate the functional impact of those variants on alternative splicing in AD. We analyzed whole genome sequencing (WGS) and RNA-seq data generated from cognitively normal elderly controls (CN) and AD patients in two independent cohorts, representing three regions in the frontal lobe of the human brain: the dorsolateral prefrontal cortex (CN = 213 and AD = 376), frontal pole (CN = 72 and AD = 175), and inferior frontal (CN = 63 and AD = 157). We observed an exon skipping event in the second exon of TREM2, with that exon tending to be more frequently skipped (p = 0.0012) in individuals having at least one low-frequency variant that caused loss-of-function for a splicing regulatory element. In addition, genes differentially expressed between AD patients with high vs. low skipping of the second exon (i.e., loss of a TREM2 functional domain) were significantly enriched in immune-related pathways. Our splicing-guided aggregation method thus provides new insight into the regulation of alternative splicing of the second exon of TREM2 by low-frequency variants and could be a useful tool for further exploring the potential molecular mechanisms of multiple, disease-associated, low-frequency variants.

Microglial Hyperreactivity Evolved to Immunosuppression in the Hippocampus of a Mouse Model of Accelerated Aging and Alzheimer's Disease Traits

Neuroinflammation is a risk factor for Alzheimer's disease (AD). We sought to study the glial derangement in AD using diverse experimental models and human brain tissue. Besides classical pro-inflammatory cytokines, we analyzed chitinase 3 like 1 (CHI3L1 or YKL40) and triggering receptor expressed on myeloid cells 2 (TREM2) that are increasingly being associated with astrogliosis and microgliosis in AD, respectively. The SAMP8 mouse model of accelerated aging and AD traits showed elevated pro-inflammatory cytokines and activated microglia phenotype. Furthermore, 6-month-old SAMP8 showed an exacerbated inflammatory response to peripheral lipopolysaccharide in the hippocampus and null responsiveness at the advanced age (for this strain) of 12 months. Gene expression of TREM2 was increased in the hippocampus of transgenic 5XFAD mice and in the cingulate cortex of autosomal dominant AD patients, and to a lesser extent in aged SAMP8 mice and sporadic early-onset AD patients. However, gene expression of CHI3L1 was increased in mice but not in human AD brain samples. The results support the relevance of microglia activation in the pathways leading to neurodegeneration and suggest diverse neuroinflammatory responses according to the AD process. Therefore, the SAMP8 mouse model with marked alterations in the dynamics of microglia activation and senescence may provide a complementary approach to transgenic mouse models for the study of the neuroinflammatory mechanisms underlying AD risk and progression.

Shifting paradigms: The central role of microglia in Alzheimer's disease

Recent human genetic studies have challenged long standing hypotheses about the chain of events in Alzheimer's disease (AD), as the identification of genetic risk factors in microglial genes supports a causative role for microglia in the disease. Parallel transcriptome and histology studies at the single-cell level revealed a rich palette of microglial states affected by disease status and genetic risk factors. Taken together, those findings support microglia dysfunction as a central mechanism in AD etiology and thus the therapeutic potential of modulating microglial activity for AD treatment. Here we review how human genetic studies discovered microglial AD risk genes, such as TREM2, CD33, MS4A and APOE, and how experimental studies are beginning to decipher the cellular functions of some of these genes. Our review also focuses on recent transcriptomic studies of human microglia from postmortem tissue to critically assess areas of similarity and dissimilarity between human and mouse models currently in use in order to better understand the biology of innate immunity in AD.

The Genetics of Alzheimer's Disease in the Chinese Population

Alzheimer’s disease (AD) is a neurodegenerative disease characterized by progressive cognitive dysfunction and behavioral impairment. In China, the number of AD patients is growing rapidly, which poses a considerable burden on society and families. In recent years, through the advancement of genome-wide association studies, second-generation gene sequencing technology, and their application in AD genetic research, more genetic loci associated with the risk for AD have been discovered, including KCNJ15, TREM2, and GCH1, which provides new ideas for the etiology and treatment of AD. This review summarizes three early-onset AD causative genes (APP, PSEN1, and PSEN2) and some late-onset AD susceptibility genes and their mutation sites newly discovered in China, and briefly introduces the potential mechanisms of these genetic susceptibilities in the pathogenesis of AD, which would help in understanding the genetic mechanisms underlying this devastating disease.