ABSTRACT
BACKGROUND: Fatigue is a common and debilitating phenomenon experienced by individuals with traumatic brain injury (TBI) that can negatively influence rate and extent of functional recovery by reducing participation in brain injury rehabilitation services and increasing maladaptive lifestyle practices. The underlying mechanisms of TBI-related fatigue are not entirely understood and focused research on symptom reduction or prevention is limited. REVIEW: The current review of the literature suggests that the aetiology of TBI-related fatigue can be viewed as a multifactorial and complex model impacting physiological systems (i.e. endocrine, skeletal muscle and cardiorespiratory) that can be directly or indirectly influenced by neuropsychological correlates including cognitive and psychological impairment. Distinguishing central from peripheral fatigue is helpful in this regard. Potential therapeutic strategies and pharmacological agents to help alleviate fatigue in this patient population are discussed.
Subject(s)
Adaptation, Physiological , Brain Injuries/physiopathology , Fatigue/physiopathology , Recovery of Function , Sleep Wake Disorders/physiopathology , Activities of Daily Living , Brain Injuries/complications , Exercise , Fatigue/etiology , Female , Humans , Male , Neuropsychological Tests , Prognosis , Quality of Life , Regional Blood Flow , Sickness Impact Profile , Sleep , Sleep Wake Disorders/etiologyABSTRACT
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.
Subject(s)
Alzheimer Disease/genetics , Alzheimer Disease/pathology , Brain/pathology , Genetic Predisposition to Disease , Proteins/genetics , Aged , Aged, 80 and over , Alzheimer Disease/complications , Alzheimer Disease/diagnostic imaging , Apolipoproteins E/genetics , Brain/diagnostic imaging , Brain/enzymology , Brain Mapping , Cognition Disorders/etiology , Cognition Disorders/genetics , Female , Gene Expression Profiling/methods , Genome-Wide Association Study/methods , Genotype , Glial Fibrillary Acidic Protein/metabolism , Humans , Intracellular Signaling Peptides and Proteins , Male , Neurons/metabolism , Neurons/pathology , Neuropsychological Tests , Oligonucleotide Array Sequence Analysis/methods , Phosphoproteins , Polymorphism, Single Nucleotide/genetics , Positron-Emission Tomography/methodsABSTRACT
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.
ABSTRACT
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.
Subject(s)
Alzheimer Disease/genetics , Alzheimer Disease/metabolism , Brain/metabolism , Age of Onset , Aged , Case-Control Studies , Female , Gene Expression Profiling , Gene Regulatory Networks , Genome-Wide Association Study , Humans , Male , Oligonucleotide Array Sequence Analysis , Polymorphism, Single Nucleotide , Quantitative Trait Loci , Transcription Initiation Site , Transcription, GeneticABSTRACT
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.
Subject(s)
Alzheimer Disease/genetics , Genetic Predisposition to Disease/genetics , LDL-Receptor Related Proteins/genetics , Membrane Transport Proteins/genetics , Aged , Aged, 80 and over , Case-Control Studies , Female , Genetic Markers/genetics , Humans , Male , Polymorphism, Genetic/geneticsABSTRACT
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.
Subject(s)
Cerebral Cortex/metabolism , Gene Expression Profiling , Genetic Variation , Polymorphism, Single Nucleotide , Aged , Aged, 80 and over , Humans , Oligonucleotide Array Sequence AnalysisABSTRACT
BACKGROUND: Approximately 90% of persons with amyotrophic lateral sclerosis (ALS) have the sporadic form, which may be caused by the interaction of multiple environmental factors and previously unknown genes. METHODS: We performed a genomewide association analysis using 766,955 single-nucleotide polymorphisms (SNPs) found in 386 white patients with sporadic ALS and 542 neurologically normal white controls (the discovery series). Associations of SNPs with sporadic ALS were confirmed in two independent replication populations: replication series 1, with 766 case patients with the disease and 750 neurologically normal controls, and replication series 2, with 135 case patients and 275 controls. RESULTS: We identified 10 genetic loci that are significantly associated (P<0.05) with sporadic ALS in three independent series of case patients and controls and an additional 41 loci that had significant associations in two of the three series. The most significant association with disease in white case patients as compared with controls was found for a SNP near an uncharacterized gene known as FLJ10986 (P=3.0x10(-4); odds ratio for having the genotype in patients vs. controls, 1.35; 95% confidence interval, 1.13 to 1.62). The FLJ10986 protein was found to be expressed in the spinal cord and cerebrospinal fluid of patients and of controls. Specific SNPs seem to be associated with sex, age at onset, and site of onset of sporadic ALS. CONCLUSIONS: Variants of FLJ10986 may confer susceptibility to sporadic ALS. FLJ10986 and 50 other candidate loci warrant further investigation for their potential role in conferring susceptibility to the disease.
Subject(s)
Amyotrophic Lateral Sclerosis/genetics , Cerebrospinal Fluid Proteins/genetics , Genetic Predisposition to Disease , Polymorphism, Single Nucleotide , Age of Onset , Case-Control Studies , Female , Genome, Human , Genotype , Humans , Immunoblotting , Male , Mutation , Odds Ratio , Risk Factors , Sequence Analysis, DNAABSTRACT
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.
Subject(s)
Adaptor Proteins, Signal Transducing/genetics , Alzheimer Disease/genetics , Alzheimer Disease/metabolism , Apolipoprotein E4/genetics , Genetic Predisposition to Disease/genetics , Polymorphism, Single Nucleotide/genetics , Brain/metabolism , Brain/pathology , Brain/physiopathology , Brain Chemistry/genetics , Cell Line, Tumor , DNA Mutational Analysis , Gene Expression Regulation/genetics , Gene Frequency , Genetic Markers/genetics , Genetic Testing , Haplotypes/genetics , Humans , Mutation , Neurofibrillary Tangles/genetics , Neurofibrillary Tangles/metabolism , Neurofibrillary Tangles/pathology , Phosphorylation , Risk Factors , tau Proteins/metabolismABSTRACT
MOTIVATION: The technology to genotype single nucleotide polymorphisms (SNPs) at extremely high densities provides for hypothesis-free genome-wide scans for common polymorphisms associated with complex disease. However, we find that some errors introduced by commonly employed genotyping algorithms may lead to inflation of false associations between markers and phenotype. RESULTS: We have developed a novel SNP genotype calling program, SNiPer-High Density (SNiPer-HD), for highly accurate genotype calling across hundreds of thousands of SNPs. The program employs an expectation-maximization (EM) algorithm with parameters based on a training sample set. The algorithm choice allows for highly accurate genotyping for most SNPs. Also, we introduce a quality control metric for each assayed SNP, such that poor-behaving SNPs can be filtered using a metric correlating to genotype class separation in the calling algorithm. SNiPer-HD is superior to the standard dynamic modeling algorithm and is complementary and non-redundant to other algorithms, such as BRLMM. Implementing multiple algorithms together may provide highly accurate genotyping calls, without inflation of false positives due to systematically miss-called SNPs. A reliable and accurate set of SNP genotypes for increasingly dense panels will eliminate some false association signals and false negative signals, allowing for rapid identification of disease susceptibility loci for complex traits. AVAILABILITY: SNiPer-HD is available at TGen's website: http://www.tgen.org/neurogenomics/data.