Gene expression levels as endophenotypes in genome-wide association studies of Alzheimer disease

Ide Copy Number Variant Does Not Influence Stroke Severity in 2 C57BL/6J Mouse Models nor in Humans: An Exploratory Study

BACKGROUND

Contrary to the common belief, the most commonly used laboratory C57BL/6J mouse inbred strain presents a distinctive genetic and phenotypic variability, and for several traits, the genotype-phenotype link remains still unknown. Recently, we characterized the most important stroke survival factor such as brain collateral plasticity in 2 brain ischemia C57BL/6J mouse models (bilateral common carotid artery stenosis and middle cerebral artery occlusion) and observed a Mendelian-like fashion of inheritance of the posterior communicating artery (PcomA) patency. Interestingly, a copy number variant (CNV) spanning Ide locus was reported to segregate in an analogous Mendelian-like pattern in the C57BL/6J colonies of the Jackson Laboratory. Given IDE critical role in vascular plasticity, we hypothesized Ide CNV may have explained PcomA variability in C57BL/6J inbred mice.

METHODS

We applied a combination of techniques (T2-weighted magnetic resonance imaging, time-of-flight angiography, cerebral blood flow imaging, and histology) to characterize the collaterome in 77 C57BL/6J bilateral common carotid artery stenosis, middle cerebral artery occlusion, naive, and sham mice and performed on these Taqman genotyping, exome sequencing, and RNA sequencing. We then investigated the hypothesis that IDE structural variants (CNVs, gain/loss of function mutations) may have influenced the cerebrovascular phenotype in a large cohort of 454 040 cases and controls (UK Biobank, Genomics England).

RESULTS

We detected an Ide CNV in a bilateral common carotid artery stenosis mouse with 2 patent PcomAs (minor allele frequency, 1.3%), not segregating with the PcomA patency phenotype. In addition, 2 heterozygous IDE CNVs, resulting in loss of function were found in 1 patient with hereditary ataxia, a patient with hereditary congenital heart disease, and 2 healthy individuals (minor allele frequency 9×10-6). Moreover, we report 4 IDE loss of function point mutations (p.Leu5X, p.Met394ValfsX29, p.Pro14SerfsX26, p.Leu889X, minor allele frequency 0.02%) present also in controls or inherited from healthy parents.

CONCLUSIONS

Ide CNV and loss of function variants are rare, do not crucially influence PcomA variability in C57BL/6J inbred mice, and do not cause a vascular phenotype in humans.

Inhibition of Insulin Degrading Enzyme to Control Diabetes Mellitus and its Applications on some Other Chronic Disease: a Critical Review

PURPOSE

This review aims to provide a precise perceptive of the insulin-degrading enzyme (IDE) and its relationship to type 2 diabetes (T2D), Alzheimer's disease (AD), obesity, and cardiovascular diseases. The purpose of the current study was to provide clear idea of treating prevalent diseases such as T2D, and AD by molecular pharmacological therapeutics rather than conventional medicinal therapy.

METHODS

To achieve the aims, molecular docking was performed using several softwares such as LIGPLOT+, Python, and Protein-Ligand Interaction Profiler with corresponding tools.

RESULTS

The IDE is a large zinc-metalloprotease that breakdown numerous pathophysiologically important extracellular substrates, comprising amyloid β-protein (Aβ) and insulin. Recent studies demonstrated that dysregulation of IDE leads to develop AD and T2D. Specifically, IDE regulates circulating insulin in a variety of organs via a degradation-dependent clearance mechanism. IDE is unique because it was subjected to allosteric activation and mediated via an oligomer structure.

CONCLUSION

In this review, we summarised the factors that modulate insulin reformation by IDE and interaction of IDE and some recent reports on IDE inhibitors against AD and T2D. We also highlighted the latest signs of progress of the function of IDE and challenges in advancing IDE- targetted therapies against T2D and AD.

Cell-type-specific expression quantitative trait loci associated with Alzheimer disease in blood and brain tissue

Because regulation of gene expression is heritable and context-dependent, we investigated AD-related gene expression patterns in cell types in blood and brain. Cis-expression quantitative trait locus (eQTL) mapping was performed genome-wide in blood from 5257 Framingham Heart Study (FHS) participants and in brain donated by 475 Religious Orders Study/Memory & Aging Project (ROSMAP) participants. The association of gene expression with genotypes for all cis SNPs within 1 Mb of genes was evaluated using linear regression models for unrelated subjects and linear-mixed models for related subjects. Cell-type-specific eQTL (ct-eQTL) models included an interaction term for the expression of "proxy" genes that discriminate particular cell type. Ct-eQTL analysis identified 11,649 and 2533 additional significant gene-SNP eQTL pairs in brain and blood, respectively, that were not detected in generic eQTL analysis. Of note, 386 unique target eGenes of significant eQTLs shared between blood and brain were enriched in apoptosis and Wnt signaling pathways. Five of these shared genes are established AD loci. The potential importance and relevance to AD of significant results in myeloid cell types is supported by the observation that a large portion of GWS ct-eQTLs map within 1 Mb of established AD loci and 58% (23/40) of the most significant eGenes in these eQTLs have previously been implicated in AD. This study identified cell-type-specific expression patterns for established and potentially novel AD genes, found additional evidence for the role of myeloid cells in AD risk, and discovered potential novel blood and brain AD biomarkers that highlight the importance of cell-type-specific analysis.

Set-Based Rare Variant Expression Quantitative Trait Loci in Blood and Brain from Alzheimer Disease Study Participants

Because studies of rare variant effects on gene expression have limited power, we investigated set-based methods to identify rare expression quantitative trait loci (eQTL) related to Alzheimer disease (AD). Gene-level and pathway-level cis rare-eQTL mapping was performed genome-wide using gene expression data derived from blood donated by 713 Alzheimer's Disease Neuroimaging Initiative participants and from brain tissues donated by 475 Religious Orders Study/Memory and Aging Project participants. The association of gene or pathway expression with a set of all cis potentially regulatory low-frequency and rare variants within 1 Mb of genes was evaluated using SKAT-O. A total of 65 genes expressed in the brain were significant targets for rare expression single nucleotide polymorphisms (eSNPs) among which 17% (11/65) included established AD genes HLA-DRB1 and HLA-DRB5. In the blood, 307 genes were significant targets for rare eSNPs. In the blood and the brain, GNMT, LDHC, RBPMS2, DUS2, and HP were targets for significant eSNPs. Pathway enrichment analysis revealed significant pathways in the brain (n = 9) and blood (n = 16). Pathways for apoptosis signaling, cholecystokinin receptor (CCKR) signaling, and inflammation mediated by chemokine and cytokine signaling were common to both tissues. Significant rare eQTLs in inflammation pathways included five genes in the blood (ALOX5AP, CXCR2, FPR2, GRB2, IFNAR1) that were previously linked to AD. This study identified several significant gene- and pathway-level rare eQTLs, which further confirmed the importance of the immune system and inflammation in AD and highlighted the advantages of using a set-based eQTL approach for evaluating the effect of low-frequency and rare variants on gene expression.

An APOE-independent cis-eSNP on chromosome 19q13.32 influences tau levels and late-onset Alzheimer's disease risk

Although multiple susceptibility loci for late-onset Alzheimer's disease (LOAD) have been identified, a large portion of the genetic risk for this disease remains unexplained. LOAD risk may be associated with single-nucleotide polymorphisms responsible for changes in gene expression (eSNPs). To detect eSNPs associated with LOAD, we integrated data from LOAD genome-wide association studies and expression quantitative trait loci using Sherlock (a Bayesian statistical method). We identified a cis-regulatory eSNP (rs2927438) located on chromosome 19q13.32, for which subsequent analyses confirmed the association with both LOAD risk and the expression level of several nearby genes. Importantly, rs2927438 may represent an APOE-independent LOAD eSNP according to the weak linkage disequilibrium of rs2927438 with the 2 polymorphisms (rs7412 and rs429358) defining the APOE-ε2, -ε3, and -ε4 alleles. Furthermore, rs2927438 does not influence chromatin interaction events at the APOE locus or cis-regulation of APOE expression. Further exploratory analysis revealed that rs2927438 is significantly associated with tau levels in the cerebrospinal fluid. Our findings suggest that rs2927438 may confer APOE-independent risk for LOAD.

Altered gene expression in late-onset Alzheimer's disease due to SNPs within 3'UTR microRNA response elements

Late-onset Alzheimer's disease (LOAD) is a progressive and fatal neurodegenerative disease found in people older than 65years of age. Disease etiology is complex, as susceptibility has been linked to multiple gene variants conferred by single nucleotide polymorphisms (SNPs). However, the molecular mechanisms by which SNPs contribute to LOAD pathogenesis have not been extensively studied, particularly for SNPs within the 3' untranslated regions (3'UTRs), the hubs for microRNA binding. Therefore, we screened for SNPs within the 3'UTRs of LOAD-associated genes that may create or destroy microRNA response elements (MREs) and thus alter gene expression. This investigation adopted an in-silico approach that integrated structural and thermodynamic features of miRNA target binding with screening using CLIP-seq data, followed by network analysis. This strategy identified three 3'UTR SNPs, rs10876135, rs5848, and rs5786996 that may alter the respective binding sites for the miRNAs hsa-miR-197-5p, hsa-miR-185-5p, and hsa-miR-34a-5p, all of which are upregulated in LOAD. The functional significance of these MRE-SNPs was assessed by potential regulation of biological networks known to be associated with LOAD. This is the first study to demonstrate a possible role for above 3'UTR MRE-SNPs in aberrant expression of target genes with functional consequences for LOAD.

Human whole genome genotype and transcriptome data for Alzheimer's and other neurodegenerative diseases

Previous genome-wide association studies (GWAS), conducted by our group and others, have identified loci that harbor risk variants for neurodegenerative diseases, including Alzheimer's disease (AD). Human disease variants are enriched for polymorphisms that affect gene expression, including some that are known to associate with expression changes in the brain. Postulating that many variants confer risk to neurodegenerative disease via transcriptional regulatory mechanisms, we have analyzed gene expression levels in the brain tissue of subjects with AD and related diseases. Herein, we describe our collective datasets comprised of GWAS data from 2,099 subjects; microarray gene expression data from 773 brain samples, 186 of which also have RNAseq; and an independent cohort of 556 brain samples with RNAseq. We expect that these datasets, which are available to all qualified researchers, will enable investigators to explore and identify transcriptional mechanisms contributing to neurodegenerative diseases.

Arguments for the sake of endophenotypes: examining common misconceptions about the use of endophenotypes in psychiatric genetics

Endophenotypes are measurable biomarkers that are correlated with an illness, at least in part, because of shared underlying genetic influences. Endophenotypes may improve our power to detect genes influencing risk of illness by being genetically simpler, closer to the level of gene action, and with larger genetic effect sizes or by providing added statistical power through their ability to quantitatively rank people within diagnostic categories. Furthermore, they also provide insight into the mechanisms underlying illness and will be valuable in developing biologically-based nosologies, through efforts such as RDoC, that seek to explain both the heterogeneity within current diagnostic categories and the overlapping clinical features between them. While neuroimaging, electrophysiological, and cognitive measures are currently most used in psychiatric genetic studies, researchers currently are attempting to identify candidate endophenotypes that are less genetically complex and potentially closer to the level of gene action, such as transcriptomic and proteomic phenotypes. Sifting through tens of thousands of such measures requires automated, high-throughput ways of assessing, and ranking potential endophenotypes, such as the Endophenotype Ranking Value. However, despite the potential utility of endophenotypes for gene characterization and discovery, there is considerable resistance to endophenotypic approaches in psychiatry. In this review, we address and clarify some of the common issues associated with the usage of endophenotypes in the psychiatric genetics community.

Functional CLOCK gene rs1554483 G/C polymorphism is associated with susceptibility to Alzheimer's disease in the Chinese population

OBJECTIVE

To examine the association between the circadian locomotor output cycles kaput (CLOCK) gene rs1554483 G/C polymorphism and susceptibility to Alzheimer's disease in Chinese people.

METHODS

This case-control study determined apolipoprotein E (APOE) and CLOCK rs1554483 G/C genotypes using polymerase chain reaction restriction fragment length polymorphism.

RESULTS

Unrelated patients with Alzheimer's disease (n = 130) and healthy controls (n = 188) were analysed for an association between the CLOCK gene rs1554483 G/C polymorphism and susceptibility to Alzheimer's disease. In the whole sample and in APOE ε4 isoform noncarriers, the prevalence of CLOCK gene rs1554483 G allele carriers was significantly higher in patients with Alzheimer's disease than in controls. Among APOE ε4 carriers, the prevalence of CLOCK rs1554483 G allele carriers was not significantly different between patients with Alzheimer's disease and controls.

CONCLUSION

Among APOE ε4 noncarriers, but not APOE ε4 carriers, the CLOCK rs1554483 G allele was associated with increased susceptibility to Alzheimer's disease.

Association of loblolly pine xylem development gene expression with single-nucleotide polymorphisms

Variation in the expression of genes with putative roles in wood development was associated with single-nucleotide polymorphisms (SNPs) using a population of loblolly pine (Pinus taeda L.) that included individuals from much of the native range. Association studies were performed using 3938 SNPs and expression data obtained using quantitative real-time polymerase chain reaction (PCR) (qRT-PCR) for 106 xylem development genes in 400 clonally replicated loblolly pine individuals. A general linear model (GLM) approach, which takes the underlying population structure into consideration, was used to discover significant associations. After adjustment for multiple testing using a false discovery rate correction, 88 statistically significant associations (Q<0.05) were observed for 80 SNPs with the expression data of 33 xylem development genes. Thirty SNPs caused nonsynonymous mutations, 18 resulted in synonymous mutations, 11 were in 3' untranslated regions (UTRs), 1 was in a 5' UTR and 20 were in introns. Using AraNet, we found that Arabidopsis genes with high similarity to the loblolly pine genes involved in 21 of the 88 statistically significant associations are connected in functional gene networks. Comparisons of gene expression values revealed that in most cases the average expression in plants homozygous for the rare SNP allele was lower than that of plants that were heterozygous or homozygous for the abundant allele. Although there are association studies of SNPs and expression profiles for humans, Arabidopsis and white spruce, to the best of our knowledge, this is the first example of such an association genetic study in pines. Functional validation of these associations will lead to a deeper understanding of the molecular basis of phenotypic differences in wood development among individuals in conifer populations.

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.

Linking protective GAB2 variants, increased cortical GAB2 expression and decreased Alzheimer's disease pathology

GRB-associated binding protein 2 (GAB2) represents a compelling genome-wide association signal for late-onset Alzheimer's disease (LOAD) with reported odds ratios (ORs) ranging from 0.75-0.85. We tested eight GAB2 variants in four North American Caucasian case-control series (2,316 LOAD, 2,538 controls) for association with LOAD. Meta-analyses revealed ORs ranging from (0.61-1.20) with no significant association (all p>0.32). Four variants were hetergeneous across the populations (all p<0.02) due to a potentially inflated effect size (OR = 0.61-0.66) only observed in the smallest series (702 LOAD, 209 controls). Despite the lack of association in our series, the previously reported protective association for GAB2 remained after meta-analyses of our data with all available previously published series (11,952-22,253 samples; OR = 0.82-0.88; all p<0.04). Using a freely available database of lymphoblastoid cell lines we found that protective GAB2 variants were associated with increased GAB2 expression (p = 9.5×10(-7)-9.3×10(-6)). We next measured GAB2 mRNA levels in 249 brains and found that decreased neurofibrillary tangle (r = -0.34, p = 0.0006) and senile plaque counts (r = -0.32, p = 0.001) were both good predictors of increased GAB2 mRNA levels albeit that sex (r = -0.28, p = 0.005) may have been a contributing factor. In summary, we hypothesise that GAB2 variants that are protective against LOAD in some populations may act functionally to increase GAB2 mRNA levels (in lymphoblastoid cells) and that increased GAB2 mRNA levels are associated with significantly decreased LOAD pathology. These findings support the hypothesis that Gab2 may protect neurons against LOAD but due to significant population heterogeneity, it is still unclear whether this protection is detectable at the genetic level.

Allele-specific behavior of molecular networks: understanding small-molecule drug response in yeast

The study of systems genetics is changing the way the genetic and molecular basis of phenotypic variation, such as disease susceptibility and drug response, is being analyzed. Moreover, systems genetics aids in the translation of insights from systems biology into genetics. The use of systems genetics enables greater attention to be focused on the potential impact of genetic perturbations on the molecular states of networks that in turn affects complex traits. In this study, we developed models to detect allele-specific perturbations on interactions, in which a genetic locus with alternative alleles exerted a differing influence on an interaction. We utilized the models to investigate the dynamic behavior of an integrated molecular network undergoing genetic perturbations in yeast. Our results revealed the complexity of regulatory relationships between genetic loci and networks, in which different genetic loci perturb specific network modules. In addition, significant within-module functional coherence was found. We then used the network perturbation model to elucidate the underlying molecular mechanisms of individual differences in response to 100 diverse small molecule drugs. As a result, we identified sub-networks in the integrated network that responded to variations in DNA associated with response to diverse compounds and were significantly enriched for known drug targets. Literature mining results provided strong independent evidence for the effectiveness of these genetic perturbing networks in the elucidation of small-molecule responses in yeast.

Relating human genetic variation to variation in drug responses

Although sequencing a single human genome was a monumental effort a decade ago, more than 1000 genomes have now been sequenced. The task ahead lies in transforming this information into personalized treatment strategies that are tailored to the unique genetics of each individual. One important aspect of personalized medicine is patient-to-patient variation in drug response. Pharmacogenomics addresses this issue by seeking to identify genetic contributors to human variation in drug efficacy and toxicity. Here, we present a summary of the current status of this field, which has evolved from studies of single candidate genes to comprehensive genome-wide analyses. Additionally, we discuss the major challenges in translating this knowledge into a systems-level understanding of drug physiology, with the ultimate goal of developing more effective personalized clinical treatment strategies.

Constructing endophenotypes of complex diseases using non-negative matrix factorization and adjusted rand index

Complex diseases are typically caused by combinations of molecular disturbances that vary widely among different patients. Endophenotypes, a combination of genetic factors associated with a disease, offer a simplified approach to dissect complex trait by reducing genetic heterogeneity. Because molecular dissimilarities often exist between patients with indistinguishable disease symptoms, these unique molecular features may reflect pathogenic heterogeneity. To detect molecular dissimilarities among patients and reduce the complexity of high-dimension data, we have explored an endophenotype-identification analytical procedure that combines non-negative matrix factorization (NMF) and adjusted rand index (ARI), a measure of the similarity of two clusterings of a data set. To evaluate this procedure, we compared it with a commonly used method, principal component analysis with k-means clustering (PCA-K). A simulation study with gene expression dataset and genotype information was conducted to examine the performance of our procedure and PCA-K. The results showed that NMF mostly outperformed PCA-K. Additionally, we applied our endophenotype-identification analytical procedure to a publicly available dataset containing data derived from patients with late-onset Alzheimer's disease (LOAD). NMF distilled information associated with 1,116 transcripts into three metagenes and three molecular subtypes (MS) for patients in the LOAD dataset: MS1 (n1=80), MS2 (n2=73), and MS3 (n3=23). ARI was then used to determine the most representative transcripts for each metagene; 123, 89, and 71 metagene-specific transcripts were identified for MS1, MS2, and MS3, respectively. These metagene-specific transcripts were identified as the endophenotypes. Our results showed that 14, 38, 0, and 28 candidate susceptibility genes listed in AlzGene database were found by all patients, MS1, MS2, and MS3, respectively. Moreover, we found that MS2 might be a normal-like subtype. Our proposed procedure provides an alternative approach to investigate the pathogenic mechanism of disease and better understand the relationship between phenotype and genotype.

Novel late-onset Alzheimer disease loci variants associate with brain gene expression

OBJECTIVE

Recent genome-wide association studies (GWAS) of late-onset Alzheimer disease (LOAD) identified 9 novel risk loci. Discovery of functional variants within genes at these loci is required to confirm their role in Alzheimer disease (AD). Single nucleotide polymorphisms that influence gene expression (eSNPs) constitute an important class of functional variants. We therefore investigated the influence of the novel LOAD risk loci on human brain gene expression.

METHODS

We measured gene expression levels in the cerebellum and temporal cortex of autopsied AD subjects and those with other brain pathologies (∼400 total subjects). To determine whether any of the novel LOAD risk variants are eSNPs, we tested their cis-association with expression of 6 nearby LOAD candidate genes detectable in human brain (ABCA7, BIN1, CLU, MS4A4A, MS4A6A, PICALM) and an additional 13 genes ±100 kb of these SNPs. To identify additional eSNPs that influence brain gene expression levels of the novel candidate LOAD genes, we identified SNPs ±100 kb of their location and tested for cis-associations.

RESULTS

CLU rs11136000 (p = 7.81 × 10(-4)) and MS4A4A rs2304933/rs2304935 (p = 1.48 × 10(-4)-1.86 × 10(-4)) significantly influence temporal cortex expression levels of these genes. The LOAD-protective CLU and risky MS4A4A locus alleles associate with higher brain levels of these genes. There are other cis-variants that significantly influence brain expression of CLU and ABCA7 (p = 4.01 × 10(-5)-9.09 × 10(-9)), some of which also associate with AD risk (p = 2.64 × 10(-2)-6.25 × 10(-5)).

CONCLUSIONS

CLU and MS4A4A eSNPs may at least partly explain the LOAD risk association at these loci. CLU and ABCA7 may harbor additional strong eSNPs. These results have implications in the search for functional variants at the novel LOAD risk loci.

Glutathione S-transferase omega genes in Alzheimer and Parkinson disease risk, age-at-diagnosis and brain gene expression: an association study with mechanistic implications

BACKGROUND

Glutathione S-transferase omega-1 and 2 genes (GSTO1, GSTO2), residing within an Alzheimer and Parkinson disease (AD and PD) linkage region, have diverse functions including mitigation of oxidative stress and may underlie the pathophysiology of both diseases. GSTO polymorphisms were previously reported to associate with risk and age-at-onset of these diseases, although inconsistent follow-up study designs make interpretation of results difficult. We assessed two previously reported SNPs, GSTO1 rs4925 and GSTO2 rs156697, in AD (3,493 ADs vs. 4,617 controls) and PD (678 PDs vs. 712 controls) for association with disease risk (case-controls), age-at-diagnosis (cases) and brain gene expression levels (autopsied subjects).

RESULTS

We found that rs156697 minor allele associates with significantly increased risk (odds ratio = 1.14, p = 0.038) in the older ADs with age-at-diagnosis > 80 years. The minor allele of GSTO1 rs4925 associates with decreased risk in familial PD (odds ratio = 0.78, p = 0.034). There was no other association with disease risk or age-at-diagnosis. The minor alleles of both GSTO SNPs associate with lower brain levels of GSTO2 (p = 4.7 × 10-11-1.9 × 10-27), but not GSTO1. Pathway analysis of significant genes in our brain expression GWAS, identified significant enrichment for glutathione metabolism genes (p = 0.003).

CONCLUSION

These results suggest that GSTO locus variants may lower brain GSTO2 levels and consequently confer AD risk in older age. Other glutathione metabolism genes should be assessed for their effects on AD and other chronic, neurologic diseases.

Association between variants in IDE-KIF11-HHEX and plasma amyloid β levels

Genetic linkage and association studies in late-onset Alzheimer's disease (LOAD) or its endophenotypes have pointed to several regions on chromosome 10q, among these the ∼ 250 kb linkage disequilibrium (LD) block harboring the genes IDE, KIF1, and HHEX. We explored the association between variants in the genomic region harboring the IDE-KIF11-HHEX complex with plasma Aβ40 and Aβ42 levels in a case-control cohort of Caribbean Hispanics. First, we performed single marker linear regression analysis relating the individual single nucleotide polymorphisms (SNPs) with plasma Aβ40 and Aβ42 levels. Then we performed 3-SNP sliding window haplotype analyses, correcting all analyses for multiple testing. Out of 32 SNPs in this region, 3 SNPs in IDE (rs2421943, rs12264682, rs11187060) were associated with plasma Aβ40 or Aβ42 levels in single marker and haplotype analyses after correction for multiple testing. All these SNPs lie within the same LD block, and are in LD with the previously reported haplotypes. Our findings provide support for an association in the IDE region on chromosome 10q with Aβ40 and 42 levels.

Are amyloid-degrading enzymes viable therapeutic targets in Alzheimer's disease?

: The amyloid cascade hypothesis of Alzheimer's disease envisages that the initial elevation of amyloid β-peptide (Aβ) levels, especially of Aβ(1-42) , is the primary trigger for the neuronal cell death specific to onset of Alzheimer's disease. There is now substantial evidence that brain amyloid levels are manipulable because of a dynamic equilibrium between their synthesis from the amyloid precursor protein and their removal by amyloid-degrading enzymes (ADEs) providing a potential therapeutic strategy. Since the initial reports over a decade ago that two zinc metallopeptidases, insulin-degrading enzyme and neprilysin (NEP), contributed to amyloid degradation in the brain, there is now an embarras de richesses in relation to this category of enzymes, which currently number almost 20. These now include serine and cysteine proteinases, as well as numerous zinc peptidases. The experimental validation for each of these enzymes, and which to target, varies enormously but up-regulation of several of them individually in mouse models of Alzheimer's disease has proved effective in amyloid and plaque clearance, as well as cognitive enhancement. The relative status of each of these enzymes will be critically evaluated. NEP and its homologues, as well as insulin-degrading enzyme, remain as principal ADEs and recently discovered mechanisms of epigenetic regulation of NEP expression potentially open new avenues in manipulation of AD-related genes, including ADEs.

A computational method based on the integration of heterogeneous networks for predicting disease-gene associations

The identification of disease-causing genes is a fundamental challenge in human health and of great importance in improving medical care, and provides a better understanding of gene functions. Recent computational approaches based on the interactions among human proteins and disease similarities have shown their power in tackling the issue. In this paper, a novel systematic and global method that integrates two heterogeneous networks for prioritizing candidate disease-causing genes is provided, based on the observation that genes causing the same or similar diseases tend to lie close to one another in a network of protein-protein interactions. In this method, the association score function between a query disease and a candidate gene is defined as the weighted sum of all the association scores between similar diseases and neighbouring genes. Moreover, the topological correlation of these two heterogeneous networks can be incorporated into the definition of the score function, and finally an iterative algorithm is designed for this issue. This method was tested with 10-fold cross-validation on all 1,126 diseases that have at least a known causal gene, and it ranked the correct gene as one of the top ten in 622 of all the 1,428 cases, significantly outperforming a state-of-the-art method called PRINCE. The results brought about by this method were applied to study three multi-factorial disorders: breast cancer, Alzheimer disease and diabetes mellitus type 2, and some suggestions of novel causal genes and candidate disease-causing subnetworks were provided for further investigation.

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.

Association of common KIBRA variants with episodic memory and AD risk

KIBRA single nucleotide polymorphism (SNP) rs17070145 was identified in a genome-wide association study (GWAS) of memory performance, with some but not all follow-up studies confirming association of its T allele with enhanced memory. This allele was associated with reduced Alzheimer's disease (AD) risk in 1 study, which also found overexpression of KIBRA in memory-related brain regions of AD. We genotyped rs17070145 and 14 additional SNPs in 2571 late onset Alzheimer's disease (LOAD) patients vs. 2842 controls, including African-Americans. We found significantly reduced risk for rs17070145 T allele in the older African-American subjects (p = 0.007) and a suggestive effect in the older Caucasian series. Meta-analysis of this allele in > 8000 subjects from our and published series showed a suggestive protective effect (p = 0.07). Analysis of episodic memory in control subjects did not identify associations with rs17070145, though other SNPs showed significant associations in 1 series. KIBRA showed evidence of overexpression in the AD temporal cortex (p = 0.06) but not cerebellum. These results suggest a modest role for KIBRA as a cognition and AD risk gene, and also highlight the multifactorial complexity of its genetic associations.

Exploration of 16 candidate genes identifies the association of IDE with Alzheimer's disease in Han Chinese

Alzheimer's disease (AD) has a complex pattern of inheritance and many genes have recently been reported to contribute to the disease susceptibility. We selected 106 SNPs within 16 candidate genes and performed a multistage association study using 4 sample sets consisting of 731 AD patients and 738 control subjects to identify genetic factors for AD in Han Chinese. A single nucleotide polymorphism (SNP) in the insulin degrading enzyme gene (IDE), rs3781239, showed a significant association with AD. The C allele increased the risk of AD 1.72-fold than the G allele (odds ratio [OR] = 1.72, 95% confidence interval [CI] = 1.17-2.53, p = 0.006) and CC carriers had a 4.89-fold higher risk for AD than that of the carriers with CG and GG genotypes (odds ratio = 4.89, 95% CI = 1.85-12.91, p = 0.001). Moreover, the CC genotype was significantly associated with earlier age at onset (p = 0.001, hazard ratio [HR] = 2.09, 95% CI = 1.38-3.18). Our data suggest that the polymorphism of IDE is associated with susceptibility to Alzheimer's disease in Han Chinese.