Academic highlights: emerging therapeutic strategies in Alzheimer's disease.
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Alzheimer Disease↗
Biomedical subjects
Gary W Small
Publications and source records attributed to Gary W Small.
Multivariate calibration standardization across instruments for the determination of glucose by Fourier transform near-infrared spectrometry.
The transfer of multivariate calibration models is investigated between a primary (A) and two secondary Fourier transform near-infrared (near-IR) spectrometers (B, C). The application studied in this work is the use of bands in the near-IR combination region of 5000-4000 cm(-)(1) to determine physiological levels of glucose in a buffered aqueous matrix containing varying levels of alanine, ascorbate, lactate, triacetin, and urea. The three spectrometers are used to measure 80 samples produced through a randomized experimental design that minimizes correlations between the component concentrations and between the concentrations of glucose and water. Direct standardization (DS), piecewise direct standardization (PDS), and guided model reoptimization (GMR) are evaluated for use in transferring partial least-squares calibration models developed with the spectra of 64 samples from the primary instrument to the prediction of glucose concentrations in 16 prediction samples measured with each secondary spectrometer. The three algorithms are evaluated as a function of the number of standardization samples used in transferring the calibration models. Performance criteria for judging the success of the calibration transfer are established as the standard error of prediction (SEP) for internal calibration models built with the spectra of the 64 calibration samples collected with each secondary spectrometer. These SEP values are 1.51 and 1.14 mM for spectrometers B and C, respectively. When calibration standardization is applied, the GMR algorithm is observed to outperform DS and PDS. With spectrometer C, the calibration transfer is highly successful, producing an SEP value of 1.07 mM. However, an SEP of 2.96 mM indicates unsuccessful calibration standardization with spectrometer B. This failure is attributed to differences in the variance structure of the spectra collected with spectrometers A and B. Diagnostic procedures are presented for use with the GMR algorithm that forecasts the successful calibration transfer with spectrometer C and the unsatisfactory results with spectrometer B.
Algorithms↗
Glutathione S-transferase omega-1 modifies age-at-onset of Alzheimer disease and Parkinson disease.
We previously reported genetic linkage of loci controlling age-at-onset in Alzheimer disease (AD) and Parkinson's disease (PD) to a 15 cM region on chromosome 10q. Given the large number of genes in this initial starting region, we applied the process of 'genomic convergence' to prioritize and reduce the number of candidate genes for further analysis. As our second convergence factor we performed gene expression studies on hippocampus obtained from AD patients and controls. Analysis revealed that four of the genes [stearoyl-CoA desaturase; NADH-ubiquinone oxidoreductase 1 beta subcomplex 8; protease, serine 11; and glutathione S-transferase, omega-1 (GSTO1)] were significantly different in their expression between AD and controls and mapped to the 10q age-at-onset linkage region, the first convergence factor. Using 2814 samples from our AD dataset (1773 AD patients) and 1362 samples from our PD dataset (635 PD patients), allelic association studies for age-at-onset effects in AD and PD revealed no association for three of the candidates, but a significant association was found for GSTO1 (P=0.007) and a second transcribed member of the GST omega class, GSTO2 (P=0.005), located next to GSTO1. The functions of GSTO1 and GSTO2 are not well understood, but recent data suggest that GSTO1 maybe involved in the post-translational modification of the inflammatory cytokine interleukin-1beta. This is provocative given reports of the possible role of inflammation in these two neurodegenerative disorders.
Age of Onset↗
Ordered-subsets linkage analysis detects novel Alzheimer disease loci on chromosomes 2q34 and 15q22.
Alzheimer disease (AD) is a complex disorder characterized by a wide range, within and between families, of ages at onset of symptoms. Consideration of age at onset as a covariate in genetic-linkage studies may reduce genetic heterogeneity and increase statistical power. Ordered-subsets analysis includes continuous covariates in linkage analysis by rank ordering families by a covariate and summing LOD scores to find a subset giving a significantly increased LOD score relative to the overall sample. We have analyzed data from 336 markers in 437 multiplex (>/=2 sampled individuals with AD) families included in a recent genomic screen for AD loci. To identify genetic heterogeneity by age at onset, families were ordered by increasing and decreasing mean and minimum ages at onset. Chromosomewide significance of increases in the LOD score in subsets relative to the overall sample was assessed by permutation. A statistically significant increase in the nonparametric multipoint LOD score was observed on chromosome 2q34, with a peak LOD score of 3.2 at D2S2944 (P=.008) in 31 families with a minimum age at onset between 50 and 60 years. The LOD score in the chromosome 9p region previously linked to AD increased to 4.6 at D9S741 (P=.01) in 334 families with minimum age at onset between 60 and 75 years. LOD scores were also significantly increased on chromosome 15q22: a peak LOD score of 2.8 (P=.0004) was detected at D15S1507 (60 cM) in 38 families with minimum age at onset >/=79 years, and a peak LOD score of 3.1 (P=.0006) was obtained at D15S153 (62 cM) in 43 families with mean age at onset >80 years. Thirty-one families were contained in both 15q22 subsets, indicating that these results are likely detecting the same locus. There is little overlap in these subsets, underscoring the utility of age at onset as a marker of genetic heterogeneity. These results indicate that linkage to chromosome 9p is strongest in late-onset AD and that regions on chromosome 2q34 and 15q22 are linked to early-onset AD and very-late-onset AD, respectively.
Age of Onset↗
The Q7R Saitohin gene polymorphism is not associated with Alzheimer disease.
Previous studies have reported conflicting results regarding the association of the Q7R polymorphism in the Saitohin gene with late-onset Alzheimer disease (AD). Given that AD is a tauopathy but no mutations or polymorphisms in Tau have been consistently associated with AD, and that Saitohin is nested in intron 9 of Tau and shares a similar expression pattern, we tested this association in 690 multiplex AD families and in a case-control sample (903 patients and 320 controls). We found no evidence of significant association of this polymorphism with risk of AD using family-based and case-control tests of association.
Alzheimer Disease↗
Robust classifier for the automated detection of ammonia in heated plumes by passive fourier transform infrared spectrometry.
An automated classification algorithm is implemented for the detection of ammonia vapor in heated plumes by passive Fourier transform infrared (FT-IR) spectrometry. This classification methodology allows the real-time detection of chemical signatures in gaseous effluents such as those generated from industrial processes. The characteristics of real-time implementation and excellent robustness are achieved by an analysis strategy based on the application of band-pass digital filters to short segments of the interferogram data collected by the FT-IR spectrometer, followed by the use of piecewise linear discriminant analysis to obtain a yes/no classification regarding the presence of the analyte signature in the filtered data. The optimal classifier developed through this work is based on only 110 interferogram points and employs a single band-pass filter centered at 945 cm(-)(1) with a pass-band full width at half-maximum of 93 cm(-)(1). The average stop-band attenuation of the optimal filter is 42.1 dB. The robustness of the algorithm is tested by exposing it to chemical releases of sulfur hexafluoride, ethanol, methanol, sulfur dioxide, and hydrogen chloride that were not included in the development of the classifier. Excellent classification performance is demonstrated, with missed ammonia detections occurring at a rate of approximately 1%. The occurrence of false detections is less than 0.1% for SF(6) and less than 0.02% for the other interferences tested.
Air Pollutants, Occupational↗
Mitochondrial polymorphisms significantly reduce the risk of Parkinson disease.
Mitochondrial (mt) impairment, particularly within complex I of the electron transport system, has been implicated in the pathogenesis of Parkinson disease (PD). More than half of mitochondrially encoded polypeptides form part of the reduced nicotinamide adenine dinucleotide dehydrogenase (NADH) complex I enzyme. To test the hypothesis that mtDNA variation contributes to PD expression, we genotyped 10 single-nucleotide polymorphisms (SNPs) that define the European mtDNA haplogroups in 609 white patients with PD and 340 unaffected white control subjects. Overall, individuals classified as haplogroup J (odds ratio [OR] 0.55; 95% confidence interval [CI] 0.34-0.91; P=.02) or K (OR 0.52; 95% CI 0.30-0.90; P=.02) demonstrated a significant decrease in risk of PD versus individuals carrying the most common haplogroup, H. Furthermore, a specific SNP that defines these two haplogroups, 10398G, is strongly associated with this protective effect (OR 0.53; 95% CI 0.39-0.73; P=.0001). SNP 10398G causes a nonconservative amino acid change from threonine to alanine within the NADH dehydrogenase 3 (ND3) of complex I. After stratification by sex, this decrease in risk appeared stronger in women than in men (OR 0.43; 95% CI 0.27-0.71; P=.0009). In addition, SNP 9055A of ATP6 demonstrated a protective effect for women (OR 0.45; 95% CI 0.22-0.93; P=.03). Our results suggest that ND3 is an important factor in PD susceptibility among white individuals and could help explain the role of complex I in PD expression.
DNA, Mitochondrial↗
Association study of Parkin gene polymorphisms with idiopathic Parkinson disease.
BACKGROUND: Previously, we detected linkage of idiopathic Parkinson disease (PD) to the region on chromosome 6 that contains the Parkin gene (D6S305; logarithm of odds score, 5.47) in families with at least one individual with age at onset younger than 40 years (families with early-onset disease). Further study demonstrated the presence of Parkin mutations in this data set. However, previous case-control studies have reported conflicting results regarding the role of more common Parkin polymorphisms as susceptibility alleles for idiopathic PD. OBJECTIVE: To investigate the association of 7 previously studied Parkin single-nucleotide polymorphisms (SNPs) throughout the promoter and most of the open reading frame with PD in a large cohort of patients with primarily late-onset PD. METHODS: One promoter, 3 intronic, and 3 exonic Parkin SNPs were genotyped in 1580 individuals belonging to 397 families, and their association with PD was evaluated using family-based association tests. RESULTS: No significant association (P>.05) between PD and any Parkin SNP allele or genotype was detected. Haplotype analysis and stratification by age at onset or family history also failed to produce significant results. CONCLUSIONS: These results suggest that these common variants of Parkin are not associated with PD in white patients, although Parkin mutations are known to cause early- and late-onset PD.
Adolescent↗
Parkin mutations and susceptibility alleles in late-onset Parkinson's disease.
Parkin, an E2-dependent ubiquitin protein ligase, carries pathogenic mutations in patients with autosomal recessive juvenile parkinsonism, but its role in the late-onset form of Parkinson's disease (PD) is not firmly established. Previously, we detected linkage of idiopathic PD to the region on chromosome 6 containing the Parkin gene (D6S305, logarithm of odds score, 5.47) in families with at least one subject with age at onset (AAO) younger than 40 years. Mutation analysis of the Parkin gene in the 174 multiplex families from the genomic screen and 133 additional PD families identified mutations in 18% of early-onset and 2% of late-onset families (5% of total families screened). The AAO of patients with Parkin mutations ranged from 12 to 71 years. Excluding exon 7 mutations, the mean AAO of patients with Parkin mutations was 31.5 years. However, mutations in exon 7, the first RING finger (Cys253Trp, Arg256Cys, Arg275Trp, and Asp280Asn) were observed primarily in heterozygous PD patients with a much later AAO (mean AAO, 49.2 years) but were not found in controls in this study or several previous reports (920 chromosomes). These findings suggest that mutations in Parkin contribute to the common form of PD and that heterozygous mutations, especially those lying in exon 7, act as susceptibility alleles for late-onset form of Parkinson disease.
Adolescent↗
An open-label extension trial of galantamine in patients with probable vascular dementia and mixed dementia.
BACKGROUND: Alzheimer's disease (AD) and vascular dementia (VaD) are the most common types of dementia worldwide. Galantamine, an acetylcholinesterase inhibitor and allosteric nicotinic modulator, has shown broad clinical benefits in patients with mild to moderate dementia due to AD, probable VaD, or AD with cerebrovascular disease (CVD)-so-called mixed dementia. OBJECTIVE: The purpose of this study was to evaluate the efficacy and safety profiles of galantamine 24 mg/d in patients with VaD or AD with CVD over the longer term (>6 months). METHODS: This was an open-label extension of a 6-month double-blind study of galantamine. Patients who had been randomized to receive galantamine 24 mg/d or placebo in the double-blind phase were eligible to continue open-label treatment with galantamine 24 mg/d for 6 months. The primary efficacy end point was change in cognition, based on scores on the 11-item Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-cog/11). Secondary measures included changes in functional ability (as measured on the Disability Assessment for Dementia [DAD]) and behavior (as measured on the Neuropsychiatric Inventory [NPI]). Safety and tolerability were also monitored. RESULTS: Four hundred fifty-nine patients (240 men, 219 women; mean [SE] age, 75.2 [0.33] years) entered the open-label phase. Of these patients, 195 (42.5%) had a diagnosis of probable VaD, and 238 (51.9%) had a diagnosis of AD with CVD; the remainder had an inconclusive diagnosis. At month 12 of the study, improvements from baseline (the start of the double-blind phase) in ADAS-cog/11 scores were observed in both the group that received placebo during the double-blind phase (placebo/galantamine group: -0.3 point; 95% CI, -1.64 to 1.06) and the group that received galantamine during the double-blind phase (galantamine/galantamine group: -0.9 point; 95% CI, -1.73 to 0.03). Improvement in functional ability was demonstrated by statistically significant mean (SE) changes from baseline in DAD score in both the placebo/galantamine group (-7.4 [1.68]; P < or = 0.001) and the galantamine/galantamine group (-3.6 [1.33]; P < or = 0.01). There was no significant change in mean (SE) NPI scores in either group (0.2 [0.98] and 0.1 [0.70], respectively). Galantamine treatment was well tolerated. CONCLUSIONS: In these patients with VaD and AD with CVD, galantamine treatment produced similar sustained benefits in terms of maintenance of or improvement in cognition (ADAS-cog/11), functional ability (DAD), and behavior (NPI) after 12 months.
Aged↗
Prognostic value of regional cerebral metabolism in patients undergoing dementia evaluation: comparison to a quantifying parameter of subsequent cognitive performance and to prognostic assessment without PET.
It is difficult to accurately forecast the clinical course of many patients presenting with mild cognitive problems. The utility in prognostic evaluation of various parameters of brain structure and function that can now be noninvasively measured remains to be clearly defined. The present work examined the value of regional cerebral metabolism, assessed with positron emission tomography (PET) and [(18)F]fluoro-2-deoxyglucose, in this context. PET scans of 167 patients (mean Mini-Mental State Examination (MMSE)=24 of 30 possible points) were classified as being positive or negative for evidence of progressive dementia. Results of scans were compared to patients' subsequent clinical course in general and in particular, to their changes in MMSE scores, for up to 10 years following PET. Data were further stratified according to the predictions of referring physicians based upon clinical assessments that had been performed up until the time of PET. Among those patients for whom a progressive dementing course had been predicted by PET criteria (but not those who were predicted by PET criteria to remain stable) a significant decline in general cognitive performance and MMSE scores occurred in the period following PET. Among those patients predicted by clinical criteria to have a progressive dementing illness, 94% of those with positive PET scans did suffer a progressive decline, while only 25% of those with negative scans progressed (relative risk 3.8). Similarly, among those patients who had been predicted by clinical criteria to remain cognitively stable, 74% of those with positive PET scans nevertheless suffered progressive decline, compared with 4% of those with negative PET scans (relative risk 18.4). These data indicate that evaluation of brain metabolism by PET in appropriately selected patients may improve the accuracy of clinical prognostic assessment.
Aged↗
MMSE items predict cognitive decline in persons with genetic risk for Alzheimer's disease.
Performance on individual Mini-Mental State Examination (MMSE) items can predict incident Alzheimer's disease (AD). The purpose of the current study is to determine whether, in nondemented persons with and without the apolipoprotein E-4 (APOE-4) genetic risk for AD, a subset of MMSE items predict cognitive decline. Fifty-four nondemented subjects, 23 with at least one copy of the APOE-4 allele and 31 without APOE-4, were given the MMSE and cognitive tests at baseline and 2-year follow-up. MMSE total score and a subset of MMSE items including delayed recall, serial 7s, pentagon, and orientation to time and place were used to predict change on cognitive tests. The subset of MMSE items significantly predicted decline in visuo-spatial construction and naming in APOE-4 carriers but not in noncarriers. Performance on a subset of MMSE items, combined with APOE-4 genotype, may aid in identifying high-risk persons for research or follow-up.
Aged↗
Classification of Fourier transform infrared microscopic imaging data of human breast cells by cluster analysis and artificial neural networks.
Cluster analysis and artificial neural networks (ANNs) are applied to the automated assessment of disease state in Fourier transform infrared microscopic imaging measurements of normal and carcinomatous immortalized human breast cell lines. K-means clustering is used to implement an automated algorithm for the assignment of pixels in the image to cell and non-cell categories. Cell pixels are subsequently classified into carcinoma and normal categories through the use of a feed-forward ANN computed with the Broyden-Fletcher-Goldfarb-Shanno training algorithm. Inputs to the ANN consist of principal component scores computed from Fourier filtered absorbance data. A grid search optimization procedure is used to identify the optimal network architecture and filter frequency response. Data from three images corresponding to normal cells, carcinoma cells, and a mixture of normal and carcinoma cells are used to build and test the classification methodology. A successful classifier is developed through this work, although differences in the spectral backgrounds between the three images are observed to complicate the classification problem. The robustness of the final classifier is improved through the use of a rejection threshold procedure to prevent classification of outlying pixels.
Algorithms↗
Remote detection of heated ethanol plumes by airborne passive Fourier transform infrared spectrometry.
Methodology is developed for the automated detection of heated plumes of ethanol vapor with airborne passive Fourier transform infrared spectrometry. Positioned in a fixed-wing aircraft in a downward-looking mode, the spectrometer is used to detect ground sources of ethanol vapor from an altitude of 2000-3000 ft. Challenges to the use of this approach for the routine detection of chemical plumes include (1) the presence of a constantly changing background radiance as the aircraft flies, (2) the cost and complexity of collecting the data needed to train the classification algorithms used in implementing the plume detection, and (3) the need for rapid interferogram scans to minimize the ground area viewed per scan. To address these challenges, this work couples a novel ground-based data collection and training protocol with the use of signal processing and pattern recognition methods based on short sections of the interferogram data collected by the spectrometer. In the data collection, heated plumes of ethanol vapor are released from a portable emission stack and viewed by the spectrometer from ground level against a synthetic background designed to simulate a terrestrial radiance source. Classifiers trained with these data are subsequently tested with airborne data collected over a period of 2.5 years. Two classifier architectures are compared in this work: support vector machines (SVM) and piecewise linear discriminant analysis (PLDA). When applied to the airborne test data, the SVM classifiers perform best, failing to detect ethanol in only 8% of the cases in which it is present. False detections occur at a rate of less than 0.5%. The classifier performs well in spite of differences between the backgrounds associated with the ground-based and airborne data collections and the instrumental drift arising from the long time span of the data collection. Further improvements in classification performance are judged to require increased sophistication in the ground-based data collection in order to provide a better match to the infrared backgrounds observed from the air.
Air Pollutants↗
Use of neuroimaging to detect early brain changes in people at genetic risk for Alzheimer's disease.
The neuropathological and cognitive changes preceding Alzheimer's disease appear to begin subtly decades before symptoms of the disease make the clinical diagnosis obvious. Clinical trials have begun to focus on preventive treatments designed to slow age-related cognitive decline and delay the onset of Alzheimer's disease in people with only mild memory complaints. Because people with few cognitive deficits represent a heterogeneous population, prevention studies require large samples in order to detect active drug effects. To address such challenges, recent neuroimaging studies have focused on middle-aged and older adults with only mild memory complaints and evaluated results according to the major known genetic risk for Alzheimer's disease, the apolipoprotein E-4 (APOE-4) allele. In studies using positron emission tomography during mental rest and functional magnetic resonance imaging during memory task performance, brain patterns differ according to genetic risk and are useful in predicting future decline measures and following disease progression in clinical trials.
Alzheimer Disease↗
Calibration standardization algorithm for partial least-squares regression: application to the determination of physiological levels of glucose by near-infrared spectroscopy.
Calibration standardization methodology for near-infrared (near-IR) spectroscopy is described for updating a partial least-squares calibration model to take into account changes in instrumental response. The guided model reoptimization (GMR) algorithm uses a transfer set of eight samples to characterize the new response and a database of previously acquired spectra used to develop the original calibration model. The samples in the transfer set need not have been measured under the old instrumental conditions, making the algorithm compatible with samples that change over time. The spectra comprising the transfer set are used to guide an iterative optimization procedure that (1) finds an optimal subset of samples from the original database to use in computing the updated model and (2) finds an optimal set of weights to apply to the spectral resolution elements in order to minimize the effects of instrumental changes on the computed model. The optimization relies on an alternating grid search and stepwise addition/deletion steps. The algorithm is evaluated through the use of combination region near-IR spectra to determine physiological levels of glucose in a synthetic biological matrix containing bovine serum albumin and triacetin in phosphate buffer. The ability to update a calibration to account for changes in the response of a Fourier transform spectrometer over four to six years is examined in this study. Separate spectral databases collected in 1994 and 1996 are used with a transfer set and separate test set of spectra collected in 2000. With the 1994 database, the standardization algorithm achieves a standard error of prediction (SEP) of 0.69 mM for the 2000 test set. This compares favorably to SEP values > 2 mM when the original 1994 calibration model is used without standardization. A similar improvement in the prediction performance of the 2000 test set is obtained after standardization with the 1996 database (SEP = 0.70 mM).
Algorithms↗
What we need to know about age related memory loss.
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Age Factors↗
Age at onset in two common neurodegenerative diseases is genetically controlled.
To identify genes influencing age at onset (AAO) in two common neurodegenerative diseases, a genomic screen was performed for AAO in families with Alzheimer disease (AD; n=449) and Parkinson disease (PD; n=174). Heritabilities between 40%--60% were found in both the AD and PD data sets. For PD, significant evidence for linkage to AAO was found on chromosome 1p (LOD = 3.41). For AD, the AAO effect of APOE (LOD = 3.28) was confirmed. In addition, evidence for AAO linkage on chromosomes 6 and 10 was identified independently in both the AD and PD data sets. Subsequent unified analyses of these regions identified a single peak on chromosome 10q between D10S1239 and D10S1237, with a maximum LOD score of 2.62. These data suggest that a common gene affects AAO in these two common complex neurodegenerative diseases.
Age of Onset↗