Association of HLA-DR/DQ Polymorphism With Alzheimer’s Disease

Dissecting the immune response of CD4+ T cells in Alzheimer's disease

The formation of amyloid-β (Aβ) plaques is a neuropathological hallmark of Alzheimer's disease (AD), however, these pathological aggregates can also be found in the brains of cognitively unimpaired elderly population. In that context, individual variations in the Aβ-specific immune response could be key factors that determine the level of Aβ-induced neuroinflammation and thus the propensity to develop AD. CD4+ T cells are the cornerstone of the immune response that coordinate the effector functions of both adaptive and innate immunity. However, despite intensive research efforts, the precise role of these cells during AD pathogenesis is still not fully elucidated. Both pathogenic and beneficial effects have been observed in various animal models of AD, as well as in humans with AD. Although this functional duality of CD4+ T cells in AD can be simply attributed to the vast phenotype heterogeneity of this cell lineage, disease stage-specific effect have also been proposed. Therefore, in this review, we summarized the current understanding of the role of CD4+ T cells in the pathophysiology of AD, from the aspect of their antigen specificity, activation, and phenotype characteristics. Such knowledge is of practical importance as it paves the way for immunomodulation as a therapeutic option for AD treatment, given that currently available therapies have not yielded satisfactory results.

Human Leukocyte Antigen and microRNAs as Key Orchestrators of Mild Cognitive Impairment and Alzheimer's Disease: A Systematic Review

The expression of inflamma-miRs and human leukocyte antigen (HLA) haplotypes could indicate mild cognitive impairment (MCI) and Alzheimer's disease (AD). We used international databases to conduct a systematic review of studies on HLA variants and a meta-analysis of research on microRNAs (miRNAs). We aimed to analyze the discriminative value of HLA variants and miRNAs in MCI, AD and controls to evaluate the protective or causative effect of HLA in cognitive decline, establish the role of miRNAs as biomarkers for the early detection of AD, and find a possible link between miRNAs and HLA. Statistical analysis was conducted using Comprehensive Meta-analysis software, version 2.2.050 (Biostat Inc., Englewood, NJ, USA). The effect sizes were estimated by the logarithm base 2 of the fold change. The systematic review revealed that some HLA variants, such as HLA-B*4402, HLA-A*33:01, HLA-A*33:01, HLA-DPB1, HLA-DR15, HLA-DQB1*03:03, HLA-DQB1*06:01, HLA-DQB1*03:01, SNPs on HLA-DRB1/DQB1, and HLA-DQA1, predisposed to cognitive decline before the occurrence of AD, while HLA-A1*01, HLA-DRB1∗13:02, HLA-DRB1*04:04, and HLA-DRB1*04:01 demonstrated a protective role. The meta-analysis identified let-7 and miR-15/16 as biomarkers for the early detection of AD. The association between these two miRNA families and the HLA variants that predispose to AD could be used for the early screening and prevention of MCI.

The HLA-DRB1*09:01-DQB1*03:03 haplotype is associated with the risk for late-onset Alzheimer's disease in APOE [Formula: see text]4-negative Japanese adults

Late-onset Alzheimer's disease (LOAD) is the most common cause of dementia among those older than 65 years. The onset of LOAD is influenced by neuroinflammation. The human leukocyte antigen (HLA) system is involved in regulating inflammatory responses. Numerous HLA alleles and their haplotypes have shown varying associations with LOAD in diverse populations, yet their impact on the Japanese population remains to be elucidated. Here, we conducted a comprehensive investigation into the associations between LOAD and HLA alleles within the Japanese population. Using whole-genome sequencing (WGS) data from 303 LOAD patients and 1717 cognitively normal (CN) controls, we identified four-digit HLA class I alleles (A, B, and C) and class II alleles (DRB1, DQB1, and DPB1). We found a significant association between the HLA-DRB1*09:01-DQB1*03:03 haplotype and LOAD risk in APOE [Formula: see text]4-negative samples (odds ratio = 1.81, 95% confidence interval = 1.38-2.38, P = 2.03[Formula: see text]). These alleles not only showed distinctive frequencies specific to East Asians but demonstrated a high degree of linkage disequilibrium in APOE [Formula: see text]4-negative samples (r2 = 0.88). Because HLA class II molecules interact with T-cell receptors (TCRs), we explored potential disparities in the diversities of TCR α chain (TRA) and β chain (TRB) repertoires between APOE [Formula: see text]4-negative LOAD and CN samples. Lower diversity of TRA repertoires was associated with LOAD in APOE [Formula: see text]4-negative samples, irrespective of the HLA DRB1*09:01-DQB1*03:03 haplotype. Our study enhances the understanding of the etiology of LOAD in the Japanese population and provides new insights into the underlying mechanisms of its pathogenesis.

Genome-Wide Association Analysis across Endophenotypes in Alzheimer's Disease: Main Effects and Disease Stage-Specific Interactions

The underlying genetic susceptibility for Alzheimer's disease (AD) is not yet fully understood. The heterogeneous nature of the disease challenges genetic association studies. Endophenotype approaches can help to address this challenge by more direct interrogation of biological traits related to the disease. AD endophenotypes based on amyloid-β, tau, and neurodegeneration (A/T/N) biomarkers and cognitive performance were selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort (N = 1565). A genome-wide association study (GWAS) of quantitative phenotypes was performed using an SNP main effect and an SNP by Diagnosis interaction (SNP × DX) model to identify disease stage-specific genetic effects. Nine loci were identified as study-wide significant with one or more A/T/N endophenotypes in the main effect model, as well as additional findings significantly associated with cognitive measures. These nine loci include SNPs in or near the genes APOE, SRSF10, HLA-DQB1, XKR3, and KIAA1671. The SNP × DX model identified three study-wide significant genetic loci (BACH2, EP300, and PACRG-AS1) with a neuroprotective effect in later AD stage endophenotypes. An endophenotype approach identified novel genetic associations and provided insight into the molecular mechanisms underlying the genetic associations that may otherwise be missed using conventional case-control study designs.

Identification of highly reliable risk genes for Alzheimer's disease through joint-tissue integrative analysis

Numerous genetic variants associated with Alzheimer's disease (AD) have been identified through genome-wide association studies (GWAS), but their interpretation is hindered by the strong linkage disequilibrium (LD) among the variants, making it difficult to identify the causal variants directly. To address this issue, the transcriptome-wide association study (TWAS) was employed to infer the association between gene expression and a trait at the genetic level using expression quantitative trait locus (eQTL) cohorts. In this study, we applied the TWAS theory and utilized the improved Joint-Tissue Imputation (JTI) approach and Mendelian Randomization (MR) framework (MR-JTI) to identify potential AD-associated genes. By integrating LD score, GTEx eQTL data, and GWAS summary statistic data from a large cohort using MR-JTI, a total of 415 AD-associated genes were identified. Then, 2873 differentially expressed genes from 11 AD-related datasets were used for the Fisher test of these AD-associated genes. We finally obtained 36 highly reliable AD-associated genes, including APOC1, CR1, ERBB2, and RIN3. Moreover, the GO and KEGG enrichment analysis revealed that these genes are primarily involved in antigen processing and presentation, amyloid-beta formation, tau protein binding, and response to oxidative stress. The identification of these potential AD-associated genes not only provides insights into the pathogenesis of AD but also offers biomarkers for early diagnosis of the disease.

Statistical power of transcriptome-wide association studies

Transcriptome-Wide Association Studies (TWASs) have become increasingly popular in identifying genes (or other endophenotypes or exposures) associated with complex traits. In TWAS, one first builds a predictive model for gene expressions using an expression quantitative trait loci (eQTL) data set in stage 1, then tests the association between the predicted gene expression and a trait based on a large, independent genome-wide association study (GWAS) data set in stage 2. However, since the sample size of the eQTL data set is usually small and the coefficient of multiple determination (i.e.,R 2 ${R}^{2}$ ) of the model for many genes is also small, a question of interest is to what extent these factors affect the statistical power of TWAS. In addition, in contrast to a standard (univariate) TWAS (UV-TWAS) considering only a single gene at a time, multivariate TWAS (MV-TWAS) methods have recently emerged to account for the effects of multiple genes, or a gene's nonlinear effects, simultaneously. With the absence of the power analysis for these MV-TWAS methods, it would be of interest to investigate whether one can gain or lose power by using the newly proposed MV-TWAS instead of UV-TWAS. In this paper, we first outline a general method for sample size/power calculations for two-sample TWAS, then use real data-the Alzheimer's Disease Neuroimaging Initiative (ADNI) expression quantitative trait loci (eQTL) data and the Genotype-Tissue Expression (GTEx) eQTL data for stage 1, the International Genomics of Alzheimer's Project Alzheimer's disease (AD) GWAS summary data and UK Biobank (UKB) individual-level data for stage 2-to empirically address these questions. Our most important conclusions are the following. First, a sample size of a few thousands (~8000) would suffice in stage 1, where the power of TWAS would be more determined by cis-heritability of gene expression. Second, as in the general case of simple regression versus multiple regression, the power of MV-TWAS may be higher or lower than that of UV-TWAS, depending on the specific relationships among the GWAS trait and multiple genes (or linear and nonlinear terms of the same gene's expression levels), such as their correlations and effect sizes. Interestingly, several top genes with large power gains in MV-TWAS (over that in UV-TWAS) were known to be (and in our data more significantly) associated with AD. We also reached similar conclusions in an application to the GTEx whole blood gene expression data and UKB GWAS data of high-density lipoprotein cholesterol. The proposed method and the conclusions are expected to be useful in planning and designing future TWAS and other related studies (e.g., Proteome- or Metabolome-Wide Association Studies) when determining the sample sizes for the two stages.

Accounting for nonlinear effects of gene expression identifies additional associated genes in transcriptome-wide association studies

Transcriptome-wide association studies (TWAS) integrate genome-wide association study (GWAS) data with gene expression (GE) data to identify (putative) causal genes for complex traits. There are two stages in TWAS: in Stage 1, a model is built to impute gene expression from genotypes, and in Stage 2, gene-trait association is tested using imputed gene expression. Despite many successes with TWAS, in the current practice, one only assumes a linear relationship between GE and the trait, which however may not hold, leading to loss of power. In this study, we extend the standard TWAS by considering a quadratic effect of GE, in addition to the usual linear effect. We train imputation models for both linear and quadratic gene expression levels in Stage 1, then include both the imputed linear and quadratic expression levels in Stage 2. We applied both the standard TWAS and our approach first to the ADNI gene expression data and the IGAP Alzheimer's disease GWAS summary data, then to the GTEx (V8) gene expression data and the UK Biobank individual-level GWAS data for lipids, followed by validation with different GWAS data, suitable model checking and more robust TWAS methods. In all these applications, the new TWAS approach was able to identify additional genes associated with Alzheimer's disease, LDL and HDL cholesterol levels, suggesting its likely power gains and thus the need to account for potentially nonlinear effects of gene expression on complex traits.

Untangling huge literature to disinter genetic underpinnings of Alzheimer's Disease: A systematic review and meta-analysis

Drug discovery for Alzheimer's Disease (AD) is channeled towards unravelling key disease specific drug targets/genes to predict promising therapeutic candidates. Though enormous literature on AD genetics is available, there exists dearth in data pertinent to drug targets and crucial pathological pathways intertwined in disease progression. Further, the research findings revealing genetic associations failed to demonstrate consistency across different studies. This scenario prompted us to initiate a systematic review and meta-analysis with an aim of unearthing significant genetic hallmarks of AD. Initially, a Boolean search strategy was developed to retrieve case-control studies from PubMed, Cochrane, ProQuest, Europe PMC, grey literature and HuGE navigator. Subsequently, certain inclusion and exclusion criteria were framed to shortlist the relevant studies. These studies were later critically appraised using New Castle Ottawa Scale and Q-Genie followed by data extraction. Later, meta-analysis was performed only for those Single Nucleotide Polymorphisms (SNPs) which were evaluated in at least two different ethnicities from two different reports. Among, 204,351 studies retrieved, 820 met our eligibility criteria and 117 were processed for systematic review after critical appraisal. Ultimately, meta-analysis was performed for 23 SNPs associated with 15 genes which revealed significant associations of rs3865444 (CD33), rs7561528 (BIN1) and rs1801133 (MTHFR) with AD risk.

Pharmacogenetic and Association Studies on the Influence of HLA Alleles and Rivastigmine on the Iranian Patients with Late-Onset Alzheimer's Disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting cognitive function. A number of allelic genes from HLA complex have shown variable associations with AD in different populations. In this study, we investigated the association of DQB1*06:00/x, DRB1*04:00/x, DRB1*15:00/x, and B*07:00/x genotypes with AD and their relevance to the efficacy of rivastigmine treatment in the Iranian population. Our findings suggest that DQB1*06:00/x genotype offers strong protection against AD (P = 0.0074), while B*07:00/x genotype imposes a significant susceptibility for sporadic Alzheimer's disease (SAD) (P = 0.009). Interestingly, B*07:00/x genotype does not show any apparent associations with familial Alzheimer's disease (FAD). Our studies also suggest a pharmacogenetic relationship between drug treatment and presence of a particular genotype in the Iranian LOAD patient population. The Clinical Dementia Rating analysis showed that LOAD patients carrying DRB1*04:00/x genotype tend to display a downward trend in the disease severity and symptoms after 2-year follow-up with rivastigmine treatment. Moreover, in our total patient population, the carriers of DQB1*06:00/x and B*07:00/x alleles have better and worse responses to rivastigmine respectively. We also measured the clinical relevance of the testing for these genotypes employing prevalence-corrected positive predictive value (PcPPV) formula. The PcPPV of testing for DQB1*06:00/x in the Iranian LOAD patients was 1.17% which means that people carrying this genotype have half of the probability of the absolute risk for developing LOAD, whereas the PcPPV of testing for B*07:00/x was 4.45% for SAD, which can be interpreted as a doubling chance for developing LOAD among the Iranian population carrying this genotype. These results also suggest that DQβ1 peptide containing positively charged AAs histidine³⁰ and arginine⁵⁵ and HLA class I β chain containing negatively charges aspartic acid¹¹⁴ and glutamic acid^45,152 in their binding groove plays important roles in protection against and susceptibility for LOAD respectively.

HLA in Alzheimer's Disease: Genetic Association and Possible Pathogenic Roles

Alzheimer's disease (AD) is commonly considered as the most prominent dementing disorder globally and is characterized by the deposition of misfolded amyloid-β (Aβ) peptide and the aggregation of neurofibrillary tangles. Immunological disturbances and neuroinflammation, which result from abnormal immunological reactivations, are believed to be the primary stimulating factors triggering AD-like neuropathy. It has been suggested by multiple previous studies that a bunch of AD key influencing factors might be attributed to genes encoding human leukocyte antigen (HLA), whose variety is an essential part of human adaptive immunity. A wide range of activities involved in immune responses may be determined by HLA genes, including inflammation mediated by the immune response, T-cell transendothelial migration, infection, brain development and plasticity in AD pathogenesis, and so on. The goal of this article is to review the recent epidemiological findings of HLA (mainly HLA class I and II) associated with AD and investigate to what extent the genetic variations of HLA were clinically significant as pathogenic factors for AD. Depending on the degree of contribution of HLA in AD pathogenesis, targeted research towards HLA may propel AD therapeutic strategies into a new era of development.

Insights into the polymorphism in HLA-DRA and its evolutionary relationship with HLA haplotypes

HLA-DRA encodes the alpha chain of the HLA-DR protein, one of the classical HLA class II molecules. Reported polymorphism within HLA-DRA is currently limited compared with other HLA genes, as only a single polymorphism encodes an amino acid difference in the translated protein. Since this SNP (rs7192, HLA00662.1:g.4276G>T p.Val217Leu) lies within exon 4, in the region encoding the cytoplasmic tail, the resulting protein is effectively monomorphic. For this reason, in-depth studies on HLA-DRA and its function have been limited. However, analysis of sequences from the 1000 Genomes Project and preliminary data from our lab reveals unrepresented polymorphism within HLA-DRA, suggesting a more complex role within the MHC than previously assumed. This study focuses on elucidating the extent of HLA-DRA polymorphism, and extending our understanding of the gene's role in HLA-DR~HLA-DQ haplotypes. Ninety-eight samples were sequenced for full-length HLA-DRA, and from this analysis, we identified 20 novel SNP positions in the intronic sequences within the 5711 bp region represented in IPD-IMGT/HLA. This polymorphism gives rise to at least 22 novel HLA-DRA alleles, and the patterns of intronic and 3' UTR polymorphism correspond to HLA-DRA~HLA-DRB345~HLA-DRB1~HLA-DQB1 haplotypes. The current understanding of the organization of the genes within the HLA-DR region assumes a single lineage for the HLA-DRA gene, as opposed to multiple gene lineages, such as in HLA-DRB. This study suggests that the intron and 3' UTR polymorphism of HLA-DRA indicates different lineages, and represents the HLA-DRA~HLA-DRB345~HLA-DRB1~HLA-DQB1 haplotypes.

Study on the association of the polymorphism of HLA-II gene with leukemia

We explored the association between the HLA-II gene polymorphisms and the occurrence of leukemia. For this study, we selected 53 patients with leukemia treated at Zhongnan Hospital of Wuhan University from February 2014 to September 2015 and 46 healthy patients as the control group. We used polymerase chain reaction with sequence specific primers for DNA typing which was carried out to analyze the patients HLA-A/B gene polymorphism. We also used enzyme-linked immunosorbent assay and western blotting method to measure the protein expression of different genotypes and activity. Compared to the control group, HLA-A04, B08 gene frequencies were significantly lower than those of HLA-A04, B08 gene frequencies of the observation group; results were statistically significant (χ²=16.28, P<0.05; χ²=16.47, P<0.05). However, in the control group, the frequency of HLA-A09 gene was significantly higher than that of the observation group; there was a significant difference between the two groups (χ²=15.28, P<0.05). Through the measurement of the protein expression levels of the different genotypes in the control group and the observation group, it was found that in the observation group, HLA-A04, B08 protein contents (4.6 and 3.2 µg/l) were significantly higher than those of the control group (0.13 and 0.1 µg/l). While the control group HLA-A09 genotype protein content (3.7 µg/l) was significantly higher than that of the observation group (0.2 µg/l); there were significant differences between both (P<0.05). Therefore, there is a significant correlation between HLA-II gene polymorphism and leukemia that is higher than HLA-A04 and B08 gene frequency and can help promote the occurrence of leukemia. The higher frequency of HLA-A09 gene can help to suppress the occurrence of leukemia.

Fine-mapping of the human leukocyte antigen locus as a risk factor for Alzheimer disease: A case-control study

BACKGROUND

Alzheimer disease (AD) is a progressive disorder that affects cognitive function. There is increasing support for the role of neuroinflammation and aberrant immune regulation in the pathophysiology of AD. The immunoregulatory human leukocyte antigen (HLA) complex has been linked to susceptibility for a number of neurodegenerative diseases, including AD; however, studies to date have failed to consistently identify a risk HLA haplotype for AD. Contributing to this difficulty are the complex genetic organization of the HLA region, differences in sequencing and allelic imputation methods, and diversity across ethnic populations.

METHODS AND FINDINGS

Building on prior work linking the HLA to AD, we used a robust imputation method on two separate case-control cohorts to examine the relationship between HLA haplotypes and AD risk in 309 individuals (191 AD, 118 cognitively normal [CN] controls) from the San Francisco-based University of California, San Francisco (UCSF) Memory and Aging Center (collected between 1999-2015) and 11,381 individuals (5,728 AD, 5,653 CN controls) from the Alzheimer's Disease Genetics Consortium (ADGC), a National Institute on Aging (NIA)-funded national data repository (reflecting samples collected between 1984-2012). We also examined cerebrospinal fluid (CSF) biomarker measures for patients seen between 2005-2007 and longitudinal cognitive data from the Alzheimer's Disease Neuroimaging Initiative (n = 346, mean follow-up 3.15 ± 2.04 y in AD individuals) to assess the clinical relevance of identified risk haplotypes. The strongest association with AD risk occurred with major histocompatibility complex (MHC) haplotype A*03:01~B*07:02~DRB1*15:01~DQA1*01:02~DQB1*06:02 (p = 9.6 x 10-4, odds ratio [OR] [95% confidence interval] = 1.21 [1.08-1.37]) in the combined UCSF + ADGC cohort. Secondary analysis suggested that this effect may be driven primarily by individuals who are negative for the established AD genetic risk factor, apolipoprotein E (APOE) ɛ4. Separate analyses of class I and II haplotypes further supported the role of class I haplotype A*03:01~B*07:02 (p = 0.03, OR = 1.11 [1.01-1.23]) and class II haplotype DRB1*15:01- DQA1*01:02- DQB1*06:02 (DR15) (p = 0.03, OR = 1.08 [1.01-1.15]) as risk factors for AD. We followed up these findings in the clinical dataset representing the spectrum of cognitively normal controls, individuals with mild cognitive impairment, and individuals with AD to assess their relevance to disease. Carrying A*03:01~B*07:02 was associated with higher CSF amyloid levels (p = 0.03, β ± standard error = 47.19 ± 21.78). We also found a dose-dependent association between the DR15 haplotype and greater rates of cognitive decline (greater impairment on the 11-item Alzheimer's Disease Assessment Scale cognitive subscale [ADAS11] over time [p = 0.03, β ± standard error = 0.7 ± 0.3]; worse forgetting score on the Rey Auditory Verbal Learning Test (RAVLT) over time [p = 0.02, β ± standard error = -0.2 ± 0.06]). In a subset of the same cohort, dose of DR15 was also associated with higher baseline levels of chemokine CC-4, a biomarker of inflammation (p = 0.005, β ± standard error = 0.08 ± 0.03). The main study limitations are that the results represent only individuals of European-ancestry and clinically diagnosed individuals, and that our study used imputed genotypes for a subset of HLA genes.

CONCLUSIONS

We provide evidence that variation in the HLA locus-including risk haplotype DR15-contributes to AD risk. DR15 has also been associated with multiple sclerosis, and its component alleles have been implicated in Parkinson disease and narcolepsy. Our findings thus raise the possibility that DR15-associated mechanisms may contribute to pan-neuronal disease vulnerability.

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.