Genomic characterization of the inflammatory response initiated by surgical intervention and the effect of perioperative cyclooxygenase 2 blockade.

OBJECTIVE: There are potentially deleterious sequelae of the physiologic response to surgical intervention. Some inflammatory cytokines can act as tumor growth factors, angiogenic and metastatic promoters, or both. Modulation of negative effects could improve outcomes from surgical intervention. The effects of surgical intervention on gene expression have not been fully elucidated. We assayed gene expression changes in an animal model of thoracotomy versus a sham operation and evaluated the ability of a cyclooxygenase inhibitor, celecoxib, to mediate these changes. METHODS: Sixty adult male BALB/c mice were randomized into one of 3 experimental groups: sham operation with anesthesia only, thoracotomy incision, and thoracotomy incision with perioperative celecoxib administration. Six hours after surgical intervention, the animals were killed, and blood was collected. RNA pools from each group were labeled and hybridized to Mouse Whole Genome Microarrays. Gene expression profiles were analyzed to determine the effect of both surgical intervention and celecoxib treatment. RESULTS: Surgical intervention initiated a robust gene expression response. We identified 867 transcripts that were found to be statistically significant (corrected P < .05) and differentially expressed at least 2-fold in response to surgical intervention. Celecoxib had a profound effect on this response, preserving close to baseline levels of expression for most of those genes. CONCLUSIONS: Surgical intervention has a dramatic effect on the expression of genes related to the inflammatory response. Perioperative treatment with a cyclooxygenase 2 inhibitor abated many of these changes and might counteract many of the negative effects of the response to surgical intervention.

Whole genome association analysis shows that ACE is a risk factor for Alzheimer's disease and fails to replicate most candidates from Meta-analysis.

For late onset Alzheimer's disease (LOAD), the only confirmed, genetic association is with the apolipoprotein E (APOE) locus on chromosome 19. Meta-analysis is often employed to sort the true associations from the false positives. LOAD research has the advantage of a continuously updated meta-analysis of candidate gene association studies in the web-based AlzGene database. The top 30 AlzGene loci on May 1(st), 2007 were investigated in our whole genome association data set consisting of 1411 LOAD cases and neuropathoiogicaiiy verified controls genotyped at 312,316 SNPs using the Affymetrix 500K Mapping Platform. Of the 30 "top AlzGenes", 32 SNPs in 24 genes had odds ratios (OR) whose 95% confidence intervals that did not include 1. Of these 32 SNPs, six were part of the Affymetrix 500K Mapping panel and another ten had proxies on the Affymetrix array that had >80% power to detect an association with α=0.001. Two of these 16 SNPs showed significant association with LOAD in our sample series. One was rs4420638 at the APOE locus (uncorrected p-value=4.58E-37) and the other was rs4293, located in the angiotensin converting enzyme (ACE) locus (uncorrected p-value=0.014). Since this result was nominally significant, but did not survive multiple testing correction for 16 independent tests, this association at rs4293 was verified in a geographically distinct German cohort (p-value=0.03). We present the results of our ACE replication aiongwith a discussion of the statistical limitations of multiple test corrections in whole genome studies.

Evidence for an association between KIBRA and late-onset Alzheimer's disease.

We recently reported evidence for an association between the individual variation in normal human episodic memory and a common variant of the KIBRA gene, KIBRA rs17070145 (T-allele). Since memory impairment is a cardinal clinical feature of Alzheimer's disease (AD), we investigated the possibility of an association between the KIBRA gene and AD using data from neuronal gene expression, brain imaging studies, and genetic association tests. KIBRA was significantly over-expressed and three of its four known binding partners under-expressed in AD-affected hippocampal, posterior cingulate and temporal cortex regions (P<0.010, corrected) in a study of laser-capture microdissected neurons. Using positron emission tomography in a cohort of cognitively normal, late-middle-aged persons genotyped for KIBRA rs17070145, KIBRA T non-carriers exhibited lower glucose metabolism than did carriers in posterior cingulate and precuneus brain regions (P<0.001, uncorrected). Lastly, non-carriers of the KIBRA rs17070145 T-allele had increased risk of late-onset AD in an association study of 702 neuropathologically verified expired subjects (P=0.034; OR=1.29) and in a combined analysis of 1026 additional living and expired subjects (P=0.039; OR=1.26). Our findings suggest that KIBRA is associated with both individual variation in normal episodic memory and predisposition to AD.

Genetic control of human brain transcript expression in Alzheimer disease.

We recently surveyed the relationship between the human brain transcriptome and genome in a series of neuropathologically normal postmortem samples. We have now analyzed additional samples with a confirmed pathologic diagnosis of late-onset Alzheimer disease (LOAD; final n = 188 controls, 176 cases). Nine percent of the cortical transcripts that we analyzed had expression profiles correlated with their genotypes in the combined cohort, and approximately 5% of transcripts had SNP-transcript relationships that could distinguish LOAD samples. Two of these transcripts have been previously implicated in LOAD candidate-gene SNP-expression screens. This study shows how the relationship between common inherited genetic variants and brain transcript expression can be used in the study of human brain disorders. We suggest that studying the transcriptome as a quantitative endo-phenotype has greater power for discovering risk SNPs influencing expression than the use of discrete diagnostic categories such as presence or absence of disease.

Expression of LKB1 tumor suppressor in non-small cell lung cancer determines sensitivity to 2-deoxyglucose.

OBJECTIVE: Targeted therapy promises to improve patient outcome in non-small cell lung cancer. Biomarkers can direct targeted therapy toward patients who are most likely to respond, thus optimizing benefit. A novel agent with antineoplastic potential is the glucose analog, 2-deoxyglucose. 2-Deoxyglucose targets tumor cells, owing to their increased glucose uptake, inhibiting cellular metabolism and inducing energetic stress, resulting in decreased cellular viability. The tumor suppressor LKB1 is activated by energetic stress, and cells that lack LKB1 fail to respond and undergo cell death, suggesting that LKB1-null non-small cell lung cancer may have an increased susceptibility to 2-deoxyglucose. Inasmuch as somatic loss of LKB1 is a frequent event in non-small cell lung cancer, LKB1 expression could be used as a biomarker for directing 2-deoxyglucose therapy in patients with this type of cancer. METHODS: LKB1-positive and LKB1-negative non-small cell lung cancer cell lines were evaluated for cell viability, markers of apoptosis, and gene expression after 2-deoxyglucose treatment and compared with vehicle control. RESULTS: LKB1-negative cells treated with 2-deoxyglucose displayed a significant decrease in cell viability compared with LKB1-positive cells. Gene expression profiles of 2-deoxyglucose treated cells revealed changes in apoptotic markers in LKB1-negative cells, correlating with activation of apoptosis. Re-expression of LKB1 prevented 2-deoxyglucose mediated apoptosis, demonstrating the critical role of LKB1 in mediating 2-deoxyglucose toxicity. CONCLUSIONS: LKB1 loss increases susceptibility to 2-deoxyglucose treatment in non-small cell lung cancer lines, even at low doses. Thus, determination of LKB1 status may help direct therapy to those patients most likely to benefit from this novel approach, making it useful in the treatment of patients with non-small cell lung cancer.

Sorl1 as an Alzheimer's disease predisposition gene?

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressively disabling impairments in memory, cognition, and non-cognitive behavioural symptoms. Sporadic AD is multifactorial and genetically complex. While several monogenic mutations cause early-onset AD and gene alleles have been suggested as AD susceptibility factors, the only extensively validated susceptibility gene for late-onset AD is the apolipoprotein E (APOE) epsilon4 allele. Alleles of the APOE gene do not account for all of the genetic load calculated to be responsible for AD predisposition. Recently, polymorphisms across the neuronal sortilin-related receptor (SORL1) gene were shown to be significantly associated with AD in several cohorts. Here we present the results of our large case-control whole-genome scan at over 500,000 polymorphisms which presents weak evidence for association and potentially narrows the association interval.

A survey of genetic human cortical gene expression.

It is widely assumed that genetic differences in gene expression underpin much of the difference among individuals and many of the quantitative traits of interest to geneticists. Despite this, there has been little work on genetic variability in human gene expression and almost none in the human brain, because tools for assessing this genetic variability have not been available. Now, with whole-genome SNP genotyping arrays and whole-transcriptome expression arrays, such experiments have become feasible. We have carried out whole-genome genotyping and expression analysis on a series of 193 neuropathologically normal human brain samples using the Affymetrix GeneChip Human Mapping 500K Array Set and Illumina HumanRefseq-8 Expression BeadChip platforms. Here we present data showing that 58% of the transcriptome is cortically expressed in at least 5% of our samples and that of these cortically expressed transcripts, 21% have expression profiles that correlate with their genotype. These genetic-expression effects should be useful in determining the underlying biology of associations with common diseases of the human brain and in guiding the analysis of the genomic regions involved in the control of normal gene expression.

GAB2 alleles modify Alzheimer's risk in APOE epsilon4 carriers.

The apolipoprotein E (APOE) epsilon4 allele is the best established genetic risk factor for late-onset Alzheimer's disease (LOAD). We conducted genome-wide surveys of 502,627 single-nucleotide polymorphisms (SNPs) to characterize and confirm other LOAD susceptibility genes. In epsilon4 carriers from neuropathologically verified discovery, neuropathologically verified replication, and clinically characterized replication cohorts of 1411 cases and controls, LOAD was associated with six SNPs from the GRB-associated binding protein 2 (GAB2) gene and a common haplotype encompassing the entire GAB2 gene. SNP rs2373115 (p = 9 x 10(-11)) was associated with an odds ratio of 4.06 (confidence interval 2.81-14.69), which interacts with APOE epsilon4 to further modify risk. GAB2 was overexpressed in pathologically vulnerable neurons; the Gab2 protein was detected in neurons, tangle-bearing neurons, and dystrophic neuritis; and interference with GAB2 gene expression increased tau phosphorylation. Our findings suggest that GAB2 modifies LOAD risk in APOE epsilon4 carriers and influences Alzheimer's neuropathology.

A high-density whole-genome association study reveals that APOE is the major susceptibility gene for sporadic late-onset Alzheimer's disease.

OBJECTIVE: While the apolipoprotein E (APOE) epsilon allele is a well-established risk factor for late-onset Alzheimer's disease (AD), initial genome scans using microsatellite markers in late-onset AD failed to identify this locus on chromosome 19. Recently developed methods for the simultaneous assessment of hundreds of thousands of single nucleotide polymorphisms (SNPs) promise to help more precisely identify loci that contribute to the risk of AD and other common multigenic conditions. We sought here to demonstrate that more precise identification of loci that are associated with complex, multi-genic genetic disorders can be achieved using ultra-high-density whole-genome associations by demonstrating their ability to identify the APOE locus as a major susceptibility gene for late-onset AD, despite the absence of SNPs within the APOE locus itself, as well as to refine odds ratios (ORs) based on gold-standard phenotyping of the study population. METHOD: An individualized genome-wide association study using 502,627 SNPs was performed in 1086 his-topathologically verified AD cases and controls to determine the OR associated with genes predisposing to Alzheimer's disease. RESULTS: As predicted, ultra-high-density SNP genotyping, in contrast to traditional microsatellite-based genome screening approaches, precisely identified the APOE locus as having a significant association with late-onset AD. SNP rs4420638 on chromosome 19, located 14 kilobase pairs distal to the APOE epsilon variant, significantly distinguished between AD cases and controls (Bonferroni corrected p value = 5.30 x 10(-34), OR = 4.01) and was far more strongly associated with the risk of AD than any other SNP of the 502,627 tested. CONCLUSION: This study provides empirical support for the suggestion that the APOE locus is the major susceptibility gene for late-onset AD in the human genome, with an OR significantly greater than any other locus in the human genome. It also supports the feasibility of the ultra-high-density whole-genome association approach to the study of AD and other heritable phenotypes. These whole-genome association studies show great promise to identify additional genes that contribute to the risk of AD.

Identification of a novel risk locus for progressive supranuclear palsy by a pooled genomewide scan of 500,288 single-nucleotide polymorphisms.

To date, only the H1 MAPT haplotype has been consistently associated with risk of developing the neurodegenerative disease progressive supranuclear palsy (PSP). We hypothesized that additional genetic loci may be involved in conferring risk of PSP that could be identified through a pooling-based genomewide association study of >500,000 SNPs. Candidate SNPs with large differences in allelic frequency were identified by ranking all SNPs by their probe-intensity difference between cohorts. The MAPT H1 haplotype was strongly detected by this methodology, as was a second major locus on chromosome 11p12-p11 that showed evidence of association at allelic (P<.001), genotypic (P<.001), and haplotypic (P<.001) levels and was narrowed to a single haplotype block containing the DNA damage-binding protein 2 (DDB2) and lysosomal acid phosphatase 2 (ACP2) genes. Since DNA damage and lysosomal dysfunction have been implicated in aging and neurodegenerative processes, both genes are viable candidates for conferring risk of disease.

A generic research paradigm for identification and validation of early molecular diagnostics and new therapeutics in common disorders.

Genetically complex disorders continue to confound investigators because of their many underlying factors, both genetic and environmental. In order to tease apart the heritable from the non-heritable contributions to disease, clinicians are relying on researchers in the rapidly expanding fields of high-throughput genomics to identify surrogate clinical endpoints, called biomarkers, that provide a measure of the probability that an individual will succumb to the disease in question. The goals of current biomedical research into complex disorders are to identify and utilize these biomarkers, not only for early detection, but also for personalized treatment with knowledge-guided therapeutics. As the identification of these biomarkers is basically a problem of discovery, we discuss new insights into biomarker detection utilizing the most current genomic technologies available. Additionally, we present here a generic paradigm for the validation of such molecular diagnostics as well as new treatment modalities for complex and increasingly common diseases. Lastly, we delve into the ways genomic biomarkers might be implemented in a clinical setting to allow the subsequent application of targeted therapeutics, which can help the ever expanding groups of individuals experiencing these insidious diseases.

Identification of the genetic basis for complex disorders by use of pooling-based genomewide single-nucleotide-polymorphism association studies.

We report the development and validation of experimental methods, study designs, and analysis software for pooling-based genomewide association (GWA) studies that use high-throughput single-nucleotide-polymorphism (SNP) genotyping microarrays. We first describe a theoretical framework for establishing the effectiveness of pooling genomic DNA as a low-cost alternative to individually genotyping thousands of samples on high-density SNP microarrays. Next, we describe software called "GenePool," which directly analyzes SNP microarray probe intensity data and ranks SNPs by increased likelihood of being genetically associated with a trait or disorder. Finally, we apply these methods to experimental case-control data and demonstrate successful identification of published genetic susceptibility loci for a rare monogenic disease (sudden infant death with dysgenesis of the testes syndrome), a rare complex disease (progressive supranuclear palsy), and a common complex disease (Alzheimer disease) across multiple SNP genotyping platforms. On the basis of these theoretical calculations and their experimental validation, our results suggest that pooling-based GWA studies are a logical first step for determining whether major genetic associations exist in diseases with high heritability.

Impaired platelet mitochondrial activity in Alzheimer's disease and mild cognitive impairment.

Mitochondrial abnormalities are found in Alzheimer's disease (AD), but previous reports have not examined at-risk groups. In subjects with AD, mild cognitive impairment (MCI), and non-demented aged controls, platelet and lymphocyte mitochondria were isolated and analyzed for Complexes I, III, and IV of the electron transport chain. Western blots were used to control for differential enrichment of samples. Results demonstrated significant declines in Complexes III and IV in AD, and a significant decline in Complex IV in MCI. This report confirms mitochondrial deficiencies in AD, extends them to MCI, and suggests they are present at the earliest symptomatic stages of disease.

Preliminary demonstration of an allelic association of the IREB2 gene with Alzheimer's disease.

The role of iron metabolism in Alzheimer's disease (AD) is well documented. Regulation of the proteins that maintain cellular iron metabolism is mediated by two cytoplasmic RNA-binding proteins, the Iron Regulatory Proteins (IRP1 and IRP2), that function through post-transcriptional interactions with RNA stem loop structures called iron-responsive elements. As the primary mediator of iron homeostasis in neuronal cells, IRP2 is a strong candidate for polymorphisms that could impact AD pathogenesis. Thus, we performed a pilot study to assess polymorphisms in the gene encoding IRP2 (IREB2) on clinically well-characterized, post-mortem samples (50 AD and 50 controls). DNA sequence analysis of the IREB2 gene region revealed 14 polymorphisms. Two (rs2656070 and rs13180) showed statistically significant skewing of allelic and genotypic distributions between AD patients and controls. In silico analyses revealed that rs2656070 lies within a probable promoter and disrupts the binding sites of at least two known transcription factors. Though silent and likely not functionally relevant, rs13180 is in complete LD with rs2656070 (D' > 0.999), creating an IREB2-haplotype that is significantly associated with AD. Confirmation of this association in a larger cohort of cases and controls would further support the role of iron regulation in the pathogenesis of this catastrophic and increasingly common neurodegenerative disorder.

Quantitation of heteroplasmy of mtDNA sequence variants identified in a population of AD patients and controls by array-based resequencing.

The role of mitochondrial dysfunction in the pathogenesis of Alzheimer's disease (AD) has been well documented. Though evidence for the role of mitochondria in AD seems incontrovertible, the impact of mitochondrial DNA (mtDNA) mutations in AD etiology remains controversial. Though mutations in mitochondrially encoded genes have repeatedly been implicated in the pathogenesis of AD, many of these studies have been plagued by lack of replication as well as potential contamination of nuclear-encoded mitochondrial pseudogenes. To assess the role of mtDNA mutations in the pathogenesis of AD, while avoiding the pitfalls of nuclear-encoded mitochondrial pseudogenes encountered in previous investigations and showcasing the benefits of a novel resequencing technology, we sequenced the entire coding region (15,452 bp) of mtDNA from 19 extremely well-characterized AD patients and 18 age-matched, unaffected controls utilizing a new, reliable, high-throughput array-based resequencing technique, the Human MitoChip. High-throughput, array-based DNA resequencing of the entire mtDNA coding region from platelets of 37 subjects revealed the presence of 208 loci displaying a total of 917 sequence variants. There were no statistically significant differences in overall mutational burden between cases and controls, however, 265 independent sites of statistically significant change between cases and controls were identified. Changed sites were found in genes associated with complexes I (30.2%), III (3.0%), IV (33.2%), and V (9.1%) as well as tRNA (10.6%) and rRNA (14.0%). Despite their statistical significance, the subtle nature of the observed changes makes it difficult to determine whether they represent true functional variants involved in AD etiology or merely naturally occurring dissimilarity. Regardless, this study demonstrates the tremendous value of this novel mtDNA resequencing platform, which avoids the pitfalls of erroneously amplifying nuclear-encoded mtDNA pseudogenes, and our proposed analysis paradigm, which utilizes the availability of raw signal intensity values for each of the four potential alleles to facilitate quantitative estimates of mtDNA heteroplasmy. This information provides a potential new target for burgeoning diagnostics and therapeutics that could truly assist those suffering from this devastating disorder.

Gene expression correlates of neurofibrillary tangles in Alzheimer's disease.

Neurofibrillary tangles (NFT) constitute one of the cardinal histopathological features of Alzheimer's disease (AD). To explore in vivo molecular processes involved in the development of NFTs, we compared gene expression profiles of NFT-bearing entorhinal cortex neurons from 19 AD patients, adjacent non-NFT-bearing entorhinal cortex neurons from the same patients, and non-NFT-bearing entorhinal cortex neurons from 14 non-demented, histopathologically normal controls (ND). Of the differentially expressed genes, 225 showed progressively increased expression (AD NFT neurons > AD non-NFT neurons > ND non-NFT neurons) or progressively decreased expression (AD NFT neurons < AD non-NFT neurons < ND non-NFT neurons), raising the possibility that they may be related to the early stages of NFT formation. Immunohistochemical studies confirmed that many of the implicated proteins are dysregulated and preferentially localized to NFTs, including apolipoprotein J, interleukin-1 receptor-associated kinase 1, tissue inhibitor of metalloproteinase 3, and casein kinase 2, beta. Functional validation studies are underway to determine which candidate genes may be causally related to NFT neuropathology, thus providing therapeutic targets for the treatment of AD.

Discovery and development of biomarkers of neurological disease.

The identification of clinically relevant biomarkers for neurological diseases poses unique challenges. These include an historical lack of availability of relevant tissues from the site of pathology, relatively poorly matured techniques for disease diagnosis, the complexity and cellular heterogeneity of the brain, and a clear deficiency of models for functional validation of candidate biomarkers. Here, the unique challenges that neurological disorders introduce to biomarker discovery are described and how modern technological advances in genomics, proteomics and metabolomics are overcoming these obstacles and are driving the discovery of novel biomarkers to improve early diagnosis and therapeutic treatment is discussed.

Biomarker identification in neurologic diseases: improving diagnostics and therapeutics.

Identification of biomarkers in neurological disease remains impeded by many obstacles. Among them are the availability of tissue at the site of pathology, poor clinical diagnostics, the complexity of the brain and a general dearth of functional end points and models for validation. However, advances in technology have helped to overcome these challenges. Some of these advances include standardization and increased efficiency in brain banking, novel techniques for brain imaging, improved methods for reducing tissue heterogeneity including laser capture microdissection, high-throughput genomics, new functional validation techniques such as RNA interference, and the development of new animal models of neurologic disease. In order to efficiently handle the wealth of information that will be gleaned from these new technologies, new integrated databasing protocols will be necessary. Access to these databases by researchers and clinicians is critical to the continued progress being made in biomarker identification in neurological disease. These challenges and ways to overcome them are presented here in the context of a disease known to be a robust model for biomarker identification, Alzheimer's disease.