PubMed Health⌕ Search

Biomedical subjects

Roger Higdon

Publications and source records attributed to Roger Higdon.

13 recordsLinked to original sources

A predictive model for identifying proteins by a single peptide match.

MOTIVATION: Tandem mass-spectrometry of trypsin digests, followed by database searching, is one of the most popular approaches in high-throughput proteomics studies. Peptides are considered identified if they pass certain scoring thresholds. To avoid false positive protein identification, > or = 2 unique peptides identified within a single protein are generally recommended. Still, in a typical high-throughput experiment, hundreds of proteins are identified only by a single peptide. We introduce here a method for distinguishing between true and false identifications among single-hit proteins. The approach is based on randomized database searching and usage of logistic regression models with cross-validation. This approach is implemented to analyze three bacterial samples enabling recovery 68-98% of the correct single-hit proteins with an error rate of < 2%. This results in a 22-65% increase in number of identified proteins. Identifying true single-hit proteins will lead to discovering many crucial regulators, biomarkers and other low abundance proteins. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Algorithms↗

Protein identification and expression analysis using mass spectrometry.

The identification and quantification of the proteins that a whole organism expresses under certain conditions is a main focus of high-throughput proteomics. Advanced proteomics approaches generate new biologically relevant data and potent hypotheses. A practical report of what proteome studies can and cannot accomplish in common laboratory settings is presented here. The review discusses the most popular tandem mass-spectrometry-based methods and focuses on how to produce reliable results. A step-by-step description of proteome experiments is given, including sample preparation, digestion, labeling, liquid chromatography, data processing, database searching and statistical analysis. The difficulties and bottlenecks of proteome analysis are addressed and the requirements for further improvements are discussed. Several diverse high-throughput proteomics-based studies of microorganisms are described.

Amino Acid Sequence↗

Experimental standards for high-throughput proteomics.

Proteome analysis, utilizing high-throughput proteomics approaches, involves studying proteins that a whole organism (or specific tissue or cellular compartment) expresses under certain conditions. Intrinsic difficulties of these studies, as well as the enormous volumes of data they typically produce, make the proteome analysis and interpretation very difficult. As with any high-throughput approach, proteomics experiments should be carefully designed, analyzed, and verified. In addition to computational standards,experimental standards--simple and complex mixtures of known proteins--for high-throughput proteomics have to be developed and utilized. This article discusses such experimental standards and their implementations.

Animals↗

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.

Aged, 80 and over↗

Global profiling of Shewanella oneidensis MR-1: expression of hypothetical genes and improved functional annotations.

The gamma-proteobacterium Shewanella oneidensis strain MR-1 is a metabolically versatile organism that can reduce a wide range of organic compounds, metal ions, and radionuclides. Similar to most other sequenced organisms, approximately 40% of the predicted ORFs in the S. oneidensis genome were annotated as uncharacterized "hypothetical" genes. We implemented an integrative approach by using experimental and computational analyses to provide more detailed insight into gene function. Global expression profiles were determined for cells after UV irradiation and under aerobic and suboxic growth conditions. Transcriptomic and proteomic analyses confidently identified 538 hypothetical genes as expressed in S. oneidensis cells both as mRNAs and proteins (33% of all predicted hypothetical proteins). Publicly available analysis tools and databases and the expression data were applied to improve the annotation of these genes. The annotation results were scored by using a seven-category schema that ranked both confidence and precision of the functional assignment. We were able to identify homologs for nearly all of these hypothetical proteins (97%), but could confidently assign exact biochemical functions for only 16 proteins (category 1; 3%). Altogether, computational and experimental evidence provided functional assignments or insights for 240 more genes (categories 2-5; 45%). These functional annotations advance our understanding of genes involved in vital cellular processes, including energy conversion, ion transport, secondary metabolism, and signal transduction. We propose that this integrative approach offers a valuable means to undertake the enormous challenge of characterizing the rapidly growing number of hypothetical proteins with each newly sequenced genome.

Gene Expression Profiling↗

Earlier onset of Alzheimer disease symptoms in latino individuals compared with anglo individuals.

BACKGROUND: Latino individuals are the largest minority group and the fastest growing population group in the United States, yet there are few studies comparing the clinical features of Alzheimer disease (AD) in this population with those found in Anglo (white non-Latino) patients. OBJECTIVE: To compare the age at AD symptom onset in Latino and Anglo individuals. DESIGN: Cross-sectional assessment using standardized methods to collect and compare age at AD symptom onset, demographic variables, and medical variables. SETTING: Five National Institute on Aging-sponsored Alzheimer's Disease Centers with experience evaluating Spanish-speaking individuals. PATIENTS: We evaluated 119 Latino and 55 Anglo patients who had a diagnosis of AD. MAIN OUTCOME MEASURE: Age at symptom onset. RESULTS: After adjusting for center, sex, and years of education, Latino patients had a mean age at symptom onset 6.8 years earlier (95% confidence interval, 3.5-10.3 years earlier) than Anglo patients. CONCLUSIONS: An earlier age at symptom onset suggests that US mainland Latino individuals may experience an increased burden of AD compared with Anglo individuals. The basis for the younger age at symptom onset remains obscure.

Age of Onset↗

Charge state estimation for tandem mass spectrometry proteomics.

High-throughput protein analysis by tandem mass spectrometry produces anywhere from thousands to millions of spectra that are being used for peptide and protein identifications. Though each spectrum corresponds only to one charged peptide (ion) state, repetitive database searches of multiple charge states are typically conducted since the resolution of many common mass spectrometers is not sufficient to determine the charge state. The resulting database searches are both error-prone and time-consuming. We describe a straightforward, accurate approach on charge state estimation (CHASTE). CHASTE relies on fragment ion peak distributions, and by using reliable logistic regression models, combines different measurements to improve its accuracy. CHASTE's performance has been validated on data sets, comprised of known peptide dissociation spectra, obtained by replicate analyses of our earlier developed protein standard mixture using ion trap mass spectrometers at different laboratories. CHASTE was able to reduce number of needed database searches by at least 60% and the number of redundant searches by at least 90% virtually without any informational loss. This greatly alleviates one of the major bottlenecks in high throughput peptide and protein identifications. Thresholds and parameter estimates can be tailored to specific analysis situations, pipelines, and instrumentations. CHASTE was implemented in Java GUI-based and command-line-based interfaces.

Computer Graphics↗

Randomized sequence databases for tandem mass spectrometry peptide and protein identification.

Tandem mass spectrometry (MS/MS) combined with database searching is currently the most widely used method for high-throughput peptide and protein identification. Many different algorithms, scoring criteria, and statistical models have been used to identify peptides and proteins in complex biological samples, and many studies, including our own, describe the accuracy of these identifications, using at best generic terms such as "high confidence." False positive identification rates for these criteria can vary substantially with changing organisms under study, growth conditions, sequence databases, experimental protocols, and instrumentation; therefore, study-specific methods are needed to estimate the accuracy (false positive rates) of these peptide and protein identifications. We present and evaluate methods for estimating false positive identification rates based on searches of randomized databases (reversed and reshuffled). We examine the use of separate searches of a forward then a randomized database and combined searches of a randomized database appended to a forward sequence database. Estimated error rates from randomized database searches are first compared against actual error rates from MS/MS runs of known protein standards. These methods are then applied to biological samples of the model microorganism Shewanella oneidensis strain MR-1. Based on the results obtained in this study, we recommend the use of use of combined searches of a reshuffled database appended to a forward sequence database as a means providing quantitative estimates of false positive identification rates of peptides and proteins. This will allow researchers to set criteria and thresholds to achieve a desired error rate and provide the scientific community with direct and quantifiable measures of peptide and protein identification accuracy as opposed to vague assessments such as "high confidence."

Databases, Protein↗

A comparison of classification methods for differentiating fronto-temporal dementia from Alzheimer's disease using FDG-PET imaging.

Flurodeoxyglucose positron emission tomography (FDG-PET) is being explored to determine its ability to differentiate between a diagnosis of Alzheimer's disease (AD) and fronto-temporal dementia (FTD). We have examined statistical discrimination procedures to help achieve this purpose and compared the results to visual ratings of FDG-PET images. The methods are applied to a data set of 48 subjects with autopsy confirmed diagnoses of AD or FTD (these subjects come from a multi-centre collaborative study funded by the National Alzheimer's Coordinating Center). FDG-PET images are composed of thousands of voxels (volume elements) so one is left with a situation where there are vastly more variables than subjects. Therefore, it is necessary to perform a data reduction before a statistical procedure can be applied. Approaches using both the entire image and summary statistics calculated on a number of volumes of interest (VOI) are examined. We performed the data reduction techniques of principal components analysis (PCA) and partial least-squares (PLS) on the entire image and then used linear discriminant analysis (LDA), quadratic (QDA) or logistic regression (LR) to classify subjects as having AD or FTD. Some of these methods achieve diagnostic accuracy (as assessed by leave-one-out cross-validation) that is similar to visual ratings by expert raters. Methods using PLS appear to be more successful. Averaging or using VOI data may also be helpful.

Alzheimer Disease↗

LIP index for peptide classification using MS/MS and SEQUEST search via logistic regression.

This study addresses the issue of peptide identification resulting from tandem mass spectrometry proteomics analysis followed by database search. This work shows that the Logistic Identification of Peptides (LIP) Index achieves high sensitivity and specificity for peptide classification relative to a manually verified "gold" standard and also accurately estimates the probability of a correct peptide match. The LIP Index is a weighted average of SEQUEST output variables based on logistic regression models and is a transparent, easy to use, inclusive, extendable, and statistically sound approach to classify correct peptide identifications. Modifications, such as normalizing cross-correlations (Xcorr) for peptide length, adjusting for charge state, and the number of tryptic termini, significantly improve the fit the logistic regression models, as well as increase sensitivity and specificity. The LIP Index also incorporates earlier developed statistical models on spectral quality assessment and peptide identification, which further improves sensitivity and specificity.

Algorithms↗

Dementia and Alzheimer disease incidence: a prospective cohort study.

CONTEXT: Age-specific incidence rates for dementia and Alzheimer disease (AD) are important for research and clinical practice. Incidence estimates for the United States are few and vary with the population sampled and study design; we present data that will contribute to a consensus of these rates. OBJECTIVES: To provide age-specific incidence estimates for dementia and AD and to estimate the association of sex, educational level, and apolipoprotein E genotype with onset. DESIGN: Prospective cohort study; begun in 1994 with follow-up interviews every 2 years. SETTING: Members of community-based, large health maintenance organization with demographics consistent with the surrounding base population; diagnostic evaluation by university-based study clinicians. SUBJECTS: Random sample of subjects aged 65 years or older from the base population; dementia free, nonnursing home residents. Of 5422 who were eligible, 2581 were enrolled, and 2356 had at least 1 follow-up evaluation (10 591 person-years of observation). MAIN OUTCOME MEASURE: Dementia and Alzheimer disease diagnoses were based on standard criteria. Age-specific incidence rates were calculated using a person-years approach with Poisson distribution confidence intervals. Cox proportional hazards model analysis was used to examine other factors. RESULTS: Two hundred fifteen cases of dementia and 151 cases of AD were diagnosed. Incidence rates for dementia and AD increase across the 5-year age groups; AD rates rise from 2.8 per 1000 person-years (age group, 65-69 years) to 56.1 per 1000 person-years in the older than 90-year age group. The rates nearly triple from the 75-to-79-year and 80-to-84-year age groups, but the relative increase is much less thereafter. Sex was not associated with AD onset. Educational level (>15 years vs <12 years) was associated with a decreased risk of AD; however, the association was also dependent on the baseline cognitive screening test score. CONCLUSIONS: Our dementia and AD incidence rates are consistent with recent US and European cohort studies, providing clinicians and researchers new information concerning the reproducibility of incidence estimates across settings. Increased risk was associated with age and the apolipoprotein E genotype; also with a low baseline cognitive screening test score. Educational level was inversely associated with the risk of dementia and positively associated with the baseline cognitive test score; thus, detection of AD by the screening test could also be influenced by educational level.

Age Factors↗

Older adults and functional decline: a cross-cultural comparison.

BACKGROUND: The study was conducted to examine the relationships between functional decline, health risk factors, lifestyle practices, and demographic variables in two culturally diverse, community-based samples of White and Japanese American older adults. DESIGN: The study was an analysis of data from two ongoing studies of aging and dementia in King County, Washington. Functional status at baseline was evaluated, and factors associated with functional decline over a 4-year follow-up period were identified. The sample included 1,083 Japanese American and 1,011 White cognitively intact, community-dwelling adults aged 65 and older, who had no functional limitations at baseline and participated in at least one follow-up examination. RESULTS: In 4 years of follow-up, 70% of the subjects reported no increase in functional limitation, and fewer than 5% of subjects declined in five or more activities. Risk factors associated with functional decline included increased age, female gender, medical comorbidity (particularly cerebrovascular disease, arthritis, and hypertension), elevated body mass index, poorer self-perceived health, and smoking. Depression and diabetes were also significant for persons with the greatest functional decline over the 4-year follow-up. Japanese speakers were significantly less likely to decline over the follow-up period than White or English-speaking Japanese American subjects. However, Japanese speakers were more likely to discontinue participation during the follow-up period, and may also have been more likely to underreport symptoms of functional decline. CONCLUSIONS: The present study provides further support that healthy lifestyle practices and prevention of chronic disease are important for maintaining functional independence in older adults. Japanese-speaking subjects were less likely to decline over time, although this could be due in part to differential dropout and reporting bias. These findings have important implications for the design and interpretation of longitudinal studies of older adults. Researchers interested in the effects of ethnicity on health and aging should be cognizant of differences in recruitment and enrollment strategies among studies, and the ways in which these affect study findings. This study also demonstrates the importance of devoting adequate resources to minimize dropouts, and of including measures of health and functioning that are culturally equivalent and less reliant on self-report data.

Aged↗

BCL2 antisense reduces prostate cancer cell survival following irradiation.

Irradiation of the prostate, delivered as external beam radiation therapy (EBRT), is currently one of the few treatment options for localized prostate cancer. While it is relatively effective, the failure rate still remains unacceptably high with a 5-year biochemical failure rate of 10-40%. Utilizing genetically engineered LNCaP prostate cancer sublines that either overexpress Bcl2 (LNCaP/S22-d) or have down-regulated Bcl2 (LNCaP/AS17-f) we investigated the influence of this antiapoptotic protein on clonogenic survival following radiation. The radiation dose response curves (2-8 Gy) for the sublines differed significantly from the parental LNCaP (LNCaP/S22d: p < 0.001 and LNCaP/AS17-f: p = 0.008). The relative survival of the sublines revealed increased survival in the Bcl2 overexpressing cells, and decreased survival in the Bcl2 down-regulated cells. These data suggest a potentially important therapeutic approach for enhancing radiosensitivity in prostate tumors via antisense oligonucleotide or other drug therapies that down-regulate Bcl2. Strategies such as these likely hold the promise of enhancing the efficacy of EBRT by decreasing tumor cell survival, reducing the incidence of tumor recurrence and improving patient outcome.

Cell Survival↗