Gene expression endophenotypes: a novel approach for gene discovery in Alzheimer's disease

Uncovering the underlying genetic component of any disease is key to the understanding of its pathophysiology and may open new avenues for development of therapeutic strategies and biomarkers. In the past several years, there has been an explosion of genome-wide association studies (GWAS) resulting in the discovery of novel candidate genes conferring risk for complex diseases, including neurodegenerative diseases. Despite this success, there still remains a substantial genetic component for many complex traits and conditions that is unexplained by the GWAS findings. Additionally, in many cases, the mechanism of action of the newly discovered disease risk variants is not inherently obvious. Furthermore, a genetic region with multiple genes may be identified via GWAS, making it difficult to discern the true disease risk gene. Several alternative approaches are proposed to overcome these potential shortcomings of GWAS, including the use of quantitative, biologically relevant phenotypes. Gene expression levels represent an important class of endophenotypes. Genetic linkage and association studies that utilize gene expression levels as endophenotypes determined that the expression levels of many genes are under genetic influence. This led to the postulate that there may exist many genetic variants that confer disease risk via modifying gene expression levels. Results from the handful of genetic studies which assess gene expression level endophenotypes in conjunction with disease risk suggest that this combined phenotype approach may both increase the power for gene discovery and lead to an enhanced understanding of their mode of action. This review summarizes the evidence in support of gene expression levels as promising endophenotypes in the discovery and characterization of novel candidate genes for complex diseases, which may also represent a novel approach in the genetic studies of Alzheimer's and other neurodegenerative diseases

Genetics of Alzheimer disease in the pre- and post-GWAS era

Since the 1990s, the genetics of Alzheimer disease (AD) has been an active area of research. The identification of deterministic mutations in the APP, PSEN1, and PSEN2 genes responsible for early-onset autosomal dominant familial forms of AD led to a better understanding of the pathophysiology of this disease. In the past decade, the plethora of candidate genes and regions emerging from genetic linkage and smaller-scale association studies yielded intriguing 'hits' that have often proven difficult to replicate consistently. In the last two years, 11 published genome-wide association studies (GWASs) in AD confirmed the universally accepted role of APOE as a genetic risk factor for late-onset AD as well as generating additional candidate genes that require confirmation. It is unclear whether GWASs, though a promising novel approach in the genetics of complex diseases, can help explain most of the underlying genetic risk for AD. This review provides a brief summary of the genetic studies in AD preceding the GWAS era, with the main focus on the findings from recent GWASs. Potential approaches that could provide further insight into the genetics of AD in the post-GWAS era are also discussed

Gene-based GWAS and -biological pathway analysis of the resilience of executive functioning

Resilience in executive functioning (EF) is characterized by high EF measured by neuropsychological test performance despite structural brain damage from neurodegenerative conditions. We previously reported single nucleotide polymorphism (SNP) genome-wide association study (GWAS) results for EF resilience. Here, we report gene- and pathway-based analyses of the same resilience phenotype, using an optimal SNP-set (Sequence) Kernel Association Test (SKAT) for gene-based analyses (conservative threshold for genome-wide significance = 0.05/18,123=2.8×10−6) and the gene-set enrichment package GSA-SNP for biological pathway analyses (False discovery rate (FDR) < 0.05). Gene-based analyses found a genome-wide significant association between RNASE13 and EF resilience (p=1.33×10−7). Genetic pathways involved with dendritic/neuron spine, presynaptic membrane, postsynaptic density etc. were enriched with association to EF resilience. Although replication of these results is necessary, our findings indicate the potential value of gene- and pathway-based analyses in research on determinants of cognitive resilience

Molecular estimation of neurodegeneration pseudotime in older brains.

The temporal molecular changes that lead to disease onset and progression in Alzheimer\u27s disease (AD) are still unknown. Here we develop a temporal model for these unobserved molecular changes with a manifold learning method applied to RNA-Seq data collected from human postmortem brain samples collected within the ROS/MAP and Mayo Clinic RNA-Seq studies. We define an ordering across samples based on their similarity in gene expression and use this ordering to estimate the molecular disease stage-or disease pseudotime-for each sample. Disease pseudotime is strongly concordant with the burden of tau (Braak score, P = 1.0 × 10-5), Aβ (CERAD score, P = 1.8 × 10-5), and cognitive diagnosis (P = 3.5 × 10-7) of late-onset (LO) AD. Early stage disease pseudotime samples are enriched for controls and show changes in basic cellular functions. Late stage disease pseudotime samples are enriched for late stage AD cases and show changes in neuroinflammation and amyloid pathologic processes. We also identify a set of late stage pseudotime samples that are controls and show changes in genes enriched for protein trafficking, splicing, regulation of apoptosis, and prevention of amyloid cleavage pathways. In summary, we present a method for ordering patients along a trajectory of LOAD disease progression from brain transcriptomic data

Genome-wide pleiotropy analysis of neuropathological traits related to Alzheimer’s disease

Background Simultaneous consideration of two neuropathological traits related to Alzheimer’s disease (AD) has not been attempted in a genome-wide association study. Methods We conducted genome-wide pleiotropy analyses using association summary statistics from the Beecham et al. study (PLoS Genet 10:e1004606, 2014) for AD-related neuropathological traits, including neuritic plaque (NP), neurofibrillary tangle (NFT), and cerebral amyloid angiopathy (CAA). Significant findings were further examined by expression quantitative trait locus and differentially expressed gene analyses in AD vs. control brains using gene expression data. Results Genome-wide significant pleiotropic associations were observed for the joint model of NP and NFT (NP + NFT) with the single-nucleotide polymorphism (SNP) rs34487851 upstream of C2orf40 (alias ECRG4, P = 2.4 × 10−8) and for the joint model of NFT and CAA (NFT + CAA) with the HDAC9 SNP rs79524815 (P = 1.1 × 10−8). Gene-based testing revealed study-wide significant associations (P ≤ 2.0 × 10−6) for the NFT + CAA outcome with adjacent genes TRAPPC12, TRAPPC12-AS1, and ADI1. Risk alleles of proxy SNPs for rs79524815 were associated with significantly lower expression of HDAC9 in the brain (P = 3.0 × 10−3), and HDAC9 was significantly downregulated in subjects with AD compared with control subjects in the prefrontal (P = 7.9 × 10−3) and visual (P = 5.6 × 10−4) cortices. Conclusions Our findings suggest that pleiotropy analysis is a useful approach to identifying novel genetic associations with complex diseases and their endophenotypes. Functional studies are needed to determine whether ECRG4 or HDAC9 is plausible as a therapeutic target

LRRTM3 Interacts with APP and BACE1 and Has Variants Associating with Late-Onset Alzheimer's Disease (LOAD)

Leucine rich repeat transmembrane protein 3 (LRRTM3) is member of a synaptic protein family. LRRTM3 is a nested gene within α-T catenin (CTNNA3) and resides at the linkage peak for late-onset Alzheimer’s disease (LOAD) risk and plasma amyloid β (Aβ) levels. In-vitro knock-down of LRRTM3 was previously shown to decrease secreted Aβ, although the mechanism of this is unclear. In SH-SY5Y cells overexpressing APP and transiently transfected with LRRTM3 alone or with BACE1, we showed that LRRTM3 co-localizes with both APP and BACE1 in early endosomes, where BACE1 processing of APP occurs. Additionally, LRRTM3 co-localizes with APP in primary neuronal cultures from Tg2576 mice transduced with LRRTM3-expressing adeno-associated virus. Moreover, LRRTM3 co-immunoprecipitates with both endogenous APP and overexpressed BACE1, in HEK293T cells transfected with LRRTM3. SH-SY5Y cells with knock-down of LRRTM3 had lower BACE1 and higher CTNNA3 mRNA levels, but no change in APP. Brain mRNA levels of LRRTM3 showed significant correlations with BACE1, CTNNA3 and APP in ∼400 humans, but not in LRRTM3 knock-out mice. Finally, we assessed 69 single nucleotide polymorphisms (SNPs) within and flanking LRRTM3 in 1,567 LOADs and 2,082 controls and identified 8 SNPs within a linkage disequilibrium block encompassing 5′UTR-Intron 1 of LRRTM3 that formed multilocus genotypes (MLG) with suggestive global association with LOAD risk (p = 0.06), and significant individual MLGs. These 8 SNPs were genotyped in an independent series (1,258 LOADs and 718 controls) and had significant global and individual MLG associations in the combined dataset (p = 0.02–0.05). Collectively, these results suggest that protein interactions between LRRTM3, APP and BACE1, as well as complex associations between mRNA levels of LRRTM3, CTNNA3, APP and BACE1 in humans might influence APP metabolism and ultimately risk of AD.© 2013 Lincoln et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Two novel loci, COBL and SLC10A2, for Alzheimer's disease in African Americans

INTRODUCTION: African Americans' (AAs) late-onset Alzheimer's disease (LOAD) genetic risk profile is incompletely understood. Including clinical covariates in genetic analyses using informed conditioning might improve study power. METHODS: We conducted a genome-wide association study (GWAS) in AAs employing informed conditioning in 1825 LOAD cases and 3784 cognitively normal controls. We derived a posterior liability conditioned on age, sex, diabetes status, current smoking status, educational attainment, and affection status, with parameters informed by external prevalence information. We assessed association between the posterior liability and a genome-wide set of single-nucleotide polymorphisms (SNPs), controlling for APOE and ABCA7, identified previously in a LOAD GWAS of AAs. RESULTS: Two SNPs at novel loci, rs112404845 (P = 3.8 × 10-8), upstream of COBL, and rs16961023 (P = 4.6 × 10-8), downstream of SLC10A2, obtained genome-wide significant evidence of association with the posterior liability. DISCUSSION: An informed conditioning approach can detect LOAD genetic associations in AAs not identified by traditional GWAS

Evaluating the role of pathogenic dementia variants in posterior cortical atrophy

Posterior cortical atrophy (PCA) is an understudied visual impairment syndrome most often due to “posterior Alzheimer's disease (AD)” pathology. Case studies detected mutations in PSEN1, PSEN2, GRN, MAPT, and PRNP in subjects with clinical PCA. To detect the frequency and spectrum of mutations in known dementia genes in PCA, we screened 124 European-American subjects with clinical PCA (n = 67) or posterior AD neuropathology (n = 57) for variants in genes implicated in AD, frontotemporal dementia, and prion disease using NeuroX, a customized exome array. Frequencies in PCA of the variants annotated as pathogenic or potentially pathogenic were compared against ∼4300 European-American population controls from the NHLBI Exome Sequencing Project. We identified 2 rare variants not previously reported in PCA, TREM2 Arg47His, and PSEN2 Ser130Leu. No other pathogenic or potentially pathogenic variants were detected in the screened dementia genes. In this first systematic variant screen of a PCA cohort, we report 2 rare mutations in TREM2 and PSEN2, validate our previously reported APOE ε4 association, and demonstrate the utility of NeuroX

A candidate regulatory variant at the TREM gene cluster associates with decreased Alzheimer's disease risk and increased TREML1 and TREM2 brain gene expression

Introduction: We hypothesized that common Alzheimer's disease (AD)-associated variants within the triggering receptor expressed on myeloid (TREM) gene cluster influence disease through gene expression. Methods: Expression microarrays on temporal cortex and cerebellum from ∼400 neuropathologically diagnosed subjects and two independent RNAseq replication cohorts were used for expression quantitative trait locus analysis. Results: A variant within a DNase hypersensitive site 5′ of TREM2, rs9357347-C, associates with reduced AD risk and increased TREML1 and TREM2 levels (uncorrected P = 6.3 × 10−3 and 4.6 × 10−2, respectively). Meta-analysis on expression quantitative trait locus results from three independent data sets (n = 1006) confirmed these associations (uncorrected P = 3.4 × 10−2 and 3.5 × 10−3, Bonferroni-corrected P = 6.7 × 10−2 and 7.1 × 10−3, respectively). Discussion: Our findings point to rs9357347 as a functional regulatory variant that contributes to a protective effect observed at the TREM locus in the International Genomics of Alzheimer's Project genome-wide association study meta-analysis and suggest concomitant increase in TREML1 and TREM2 brain levels as a potential mechanism for protection from AD