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PubMed2006

Investigation of the ability of haplotype association and logistic regression to identify associated susceptibility loci.

While finely spaced markers are increasingly being used in case-control association studies in attempts to identify susceptibility loci, not enough is yet known as to the optimal spacing of such markers, their likely power to detect association, the relative merits of single marker versus multimarker analysis, or which methods of analysis may be optimal. Some investigations of these issues have used markers simulated under different theoretical models of population evolution. However the HapMap project and other sources provide real datasets which can be used to obtain a more realistic view of the performance of these approaches. SNPs around APOE and from two HapMap regions were used to obtain information regarding linkage disequilibrium (LD) relationships between polymorphisms, and these real patterns of LD were used to simulate datasets such as would be obtained in case-control studies were these SNPs to influence susceptibility to disease. The datasets obtained were analysed using tests for heterogeneity of estimated haplotype frequencies and using logistic regression analyses in which only main effects from each marker were considered. All markers surrounding the putative susceptibility locus were analysed, using sets of either 1, 2, 3 or 4 markers at a time. Some markers within 150 kb of the susceptibility locus were able to detect association. At distances less than 100 kb there was no correlation between the distance from the susceptibility locus and the strength of evidence for association. When the average inter-locus spacing is 25 kb many loci would not be detected, while when the spacing is as low as 2 kb one can be fairly confident that at least one marker will be in strong enough LD with the susceptibility locus to enable association to be detected, if the susceptibility locus has a strong enough effect relative to the sample size. With an inter-locus spacing of 4 kb some susceptibility loci did not have a marker locus in strong LD, potentially undermining the ability to detect association. There was little difference in the performance of haplotype-based analysis compared with logistic regression considering effects of each marker as separate. Multimarker analysis on occasion produced results which were much more highly significant than single marker analysis, but only very rarely. Our results support the view that if markers are randomly selected then a spacing as low as 2 kb is desirable. Multimarker analysis can sometimes be more powerful than single marker analysis so both should be performed. However, because it is rare for multimarker analysis to be much more highly significant than single marker analysis one should strongly suspect that when such results occur they may be due to mistakes in genotyping or through some other artefact. Haplotype analysis may be more prone to such problems than logistic regression, suggesting that the latter method might be preferred.

Apolipoproteins E↗

PubMed2006

Extreme patterns of variance in small populations: placing limits on human Y-chromosome diversity through time in the Vanuatu Archipelago.

Small populations are dominated by unique patterns of variance, largely characterized by rapid drift of allele frequencies. Although the variance components of genetic datasets have long been recognized, most population genetic studies still treat all sampling locations equally despite differences in sampling and effective population sizes. Because excluding the effects of variance can lead to significant biases in historical reconstruction, variance components should be incorporated explicitly into population genetic analyses. The possible magnitude of variance effects in small populations is illustrated here via a case study of Y-chromosome haplogroup diversity in the Vanuatu Archipelago. Deme-based modelling is used to simulate allele frequencies through time, and conservative confidence bounds are placed on the accumulation of stochastic variance effects, including diachronic genetic drift and contemporary sampling error. When the information content of the dataset has been ascertained, demographic models with parameters falling outside the confidence bounds of the variance components can then be accepted with some statistical confidence. Here I emphasize how aspects of the demographic history of a population can be disentangled from stochastic variance effects, and I illustrate the extreme roles of genetic drift and sampling error for many small human population datasets.

Alleles↗

PubMed2006

A test of the generality of leaf trait relationships on the Tibetan Plateau.

Leaf mass per area (LMA), nitrogen concentration (on mass and area bases, N(mass) and N(area), respectively), photosynthetic capacity (A(mass) and A(area)) and photosynthetic nitrogen use efficiency (PNUE) are key foliar traits, but few data are available from cold, high-altitude environments. Here, we systematically measured these leaf traits in 74 species at 49 research sites on the Tibetan Plateau to examine how these traits, measured near the extremes of plant tolerance, compare with global patterns. Overall, Tibetan species had higher leaf nitrogen concentrations and photosynthetic capacities compared with a global dataset, but they had a slightly lower A(mass) at a given N(mass). These leaf trait relationships were consistent with those reported from the global dataset, with slopes of the standardized major axes A(mass)-LMA, N(mass)-LMA and A(mass)-N(mass) identical to those from the global dataset. Climate only weakly modulated leaf traits. Our data indicate that covarying sets of leaf traits are consistent across environments and biogeographic regions. Our results demonstrate functional convergence of leaf trait relationships in an extreme environment.

Climate↗

PubMed1988

Interspecific scaling of toxicity data.

This paper reexamines the scaling approaches used in cancer risk assessment and proposes a more precise body weight scaling factor. Two approaches are conventionally used in scaling exposure and dose from experimental animals to man: body weight scaling (used by FDA) and surface area scaling (BW0.67--used by EPA). This paper reanalyzes the Freireich et al. (1966) study of the maximum tolerated dose (MTD) of 14 anticancer agents in mice, rats, dogs, monkeys, and humans, the dataset most commonly cited as justification for surface area extrapolation. This examination was augmented with an analysis of a similar dataset by Schein et al. (1970) of the MTD of 13 additional chemotherapy agents. The reanalysis shows that BW0.75 is a more appropriate scaling factor for the 27 direct-acting compounds in this dataset.

Animals↗

PubMed1999

"Optimum" formulae for heart rate correction of the QT interval.

The study investigated the performance of several generic QT/RR regression models in a dataset of QT and RR intervals obtained from resting electrocardiograms of 1,100 healthy subjects (913 male, mean age 33+/-12 years). All the investigated models have three degrees of freedom and included the hyperparabolic and hyper-hyperbolic models, algorithmic models, negative exponential models, and models involving inverse tangent, hyperbolic tangent, and inverse hyperbolic sign functions. For each generic model, the combination of parameters leading to the lowest regression residuum was found. The results of the study show that the goodness of the optimum fit is practically independent of the generic form of the regression model and that different datasets lead to different combinations of the numerical values of parameters of the corresponding regression models. The study concludes that the search for a universally applicable QT/RR regression model that would provide the best fit in all circumstances is most likely fruitless. Rather, individual studies such as those investigating drug related QT prolongation might benefit from establishing a best-fit regression that would provide the optimum model for each particular dataset.

Adolescent↗

PubMed2001

Bias of QT dispersion.

BACKGROUND: Prolonged QT dispersion (QTD) is associated with an increased risk of arrhythmic death but its accuracy varies substantially between otherwise similar studies. This study describes a new type of bias that can explain some of these differences. MATERIAL: One dataset (DiaSet) consisted of 356 subjects: 169 with diabetes, 187 nondiabetic control persons. Another dataset (ArrSet) consisted of 110 subjects with remote myocardial infarction: 55 with no history of arrhythmia and 55 with a recent history of ventricular tachycardia or fibrillation. METHODS: 12-lead surface ECGs were recorded with an amplification of 10 mm/mV at a paper speed of 50 mm/s. The QT interval was measured manually by the tangent-method. The bias depends on the magnitude of the measurement errors and the measurable part of the bias increases with the number of the repeated measurements of QT. RESULTS: The measurable bias was significant for both datasets and decreased for increasing QTD in the DiaSet (P < 0.001) and in the ArrSet (P = 0.11). The bias was 2.5 ms and 1.9 ms at QTD = 38 ms and 68 ms, respectively, in the ArrSet, and 7.5 ms and 2.8 ms at QTD = 19 ms and 55 ms, respectively, in the DiaSet. CONCLUSIONS: This study shows that random measurement errors of QT introduces a type of bias in QTD that decreases as the dispersion increases, thus reducing the separation between patients with low versus high dispersion. The bias can also explain some of the differences in the mean QTD between studies of healthy populations. Averaging QT over three successive beats reduces the bias efficiently.

Aged↗

PubMed2006

Subcellular localization of mammalian type II membrane proteins.

Application of a computational membrane organization prediction pipeline, MemO, identified putative type II membrane proteins as proteins predicted to encode a single alpha-helical transmembrane domain (TMD) and no signal peptides. MemO was applied to RIKEN's mouse isoform protein set to identify 1436 non-overlapping genomic regions or transcriptional units (TUs), which encode exclusively type II membrane proteins. Proteins with overlapping predicted InterPro and TMDs were reviewed to discard false positive predictions resulting in a dataset comprised of 1831 transcripts in 1408 TUs. This dataset was used to develop a systematic protocol to document subcellular localization of type II membrane proteins. This approach combines mining of published literature to identify subcellular localization data and a high-throughput, polymerase chain reaction (PCR)-based approach to experimentally characterize subcellular localization. These approaches have provided localization data for 244 and 169 proteins. Type II membrane proteins are localized to all major organelle compartments; however, some biases were observed towards the early secretory pathway and punctate structures. Collectively, this study reports the subcellular localization of 26% of the defined dataset. All reported localization data are presented in the LOCATE database (http://www.locate.imb.uq.edu.au).

Animals↗

PubMed2025

ESMpHLA: Evolutionary Scale Model-Based Deep Learning Prediction of HLA Class I Binding Peptides.

The recognition of endogenous peptides by HLA class I plays a crucial role in CD8+ T cell immune responses and human adaptive cell immune. Thus, the prediction of HLA class I-peptide binding affinities is always the core issue for the research of immune recognition and vaccine development. In this study, an evolutionary scale model (ESM) combined with parallel CNN blocks and a cross attention mechanism was used to construct a novel ESMpHLA model for predicting HLA class I binding peptides. Based on the 91,560 binding peptides of 41 HLA-A alleles, 56,731 of 50 HLA-B alleles and 2444 of 10 HLA-C alleles, the ESMpHLA model was successfully established and achieved satisfying prediction performances with the overall accuracy and AUC values of 0.874 and 0.938 for the test dataset. The results indicate that the ESMpHLA model performs well in dealing with different HLA class I 2-field alleles as well as the peptides with different lengths. Then, the generalisation ability of the ESMpHLA model was validated by an independent test dataset compiled from recent IEDB weekly benchmark datasets. The results showed that the ESMpHLA model achieved the highest ROC-AUC and PR-AUC values when compared with the latest BVMHC, CapsNet-MHC, STMHCpan and BVLSTM models. In addition, two ensemble models were also established by integrating the above 5 deep learning models using soft-voting and hard-voting strategies.

Humans↗

PubMed2026

MAdLandExpression: integrating sexual reproduction into the Physcomitrium patens expression atlas.

Physcomitrium patens is a bryophyte model system particularly valuable for evolutionary developmental and comparative genomics studies. Sexual reproduction in bryophytes offers unique insights into the evolution of land plant reproduction. Unlike seed plants, bryophytes have a dominant gametophyte phase and provide significant advantages for studying sexual reproduction, such as the possibility to maintain embryo-lethal mutants through vegetative propagation or the presence of motile male gametes. More than 25 years after the first publications of transcriptomic data for P. patens, expression data of most developmental stages of P. patens as well as its responses to various biotic and abiotic perturbations have been represented by microarrays or RNA-seq datasets. To facilitate the use of such data, we introduce the MAdLandExpression atlas as a successor of PEATmoss (Physcomitrium Expression Atlas Tool), integrating its 109 P. patens expression experiments and expanding it with 20 recently published RNA-seq samples of sexual reproduction stages, thus completing the coverage of the P. patens life cycle. The MAdLandExpression atlas also introduces new features for data visualization and analysis, such as the comparison of samples from multiple datasets and gene set normalization. Using this tool, the sexual reproduction dataset was analyzed, identifying genes potentially important for egg and sperm cell development, and confirming the behavior of known key genes in sexual development observed in previous studies.

Bryopsida↗

PubMed2004

Monte Carlo dosimetric study of best industries and Alpha Omega Ir-192 brachytherapy seeds.

Ir-192 seeds are widely used in the USA for low dose rate interstitial brachytherapy. There are two commercially available models: those manufactured by Best Industries filtered with stainless steel, and those manufactured by Alpha-Omega seeds filtered with Pt. Newly developed 3D correction algorithms for brachytherapy are based on dosimetry data obtained on unbounded phantom size, allowing corrections for heterogeneities and actual tissue boundaries. Published dosimetric datasets for both seeds have been obtained under bounded conditions. The aim of the present study is to obtain dosimetric datasets for these seeds under full scatter conditions. The Monte Carlo GEANT4 code has been used to estimate air-kerma strength and dose rate in water around the Ir-192 seeds. Functions and parameters following the TG43 formalism are obtained and presented in tabular forms: the dose rate constant, the radial dose function, and the anisotropy function. Tables for the anisotropy factor have been obtained in order to apply punctual approximation. Differences between dose rate distributions for both seeds show that specific dataset must be used for each type of seed in clinical dosimetry. The data in the present study improve on published data in the following aspects: (i) dosimetric data were obtained under full scatter conditions, which affect dose values at distances greater than 4-5 cm from the source; (ii) the dose rate tables are given at greater distances from the source; and (iii) the spatial resolution in high dose gradient areas, such as those near the longitudinal source axis, has been improved.

Body Burden↗

PubMed2006

Modeling distortion product otoacoustic emission input/output functions using segmented regression.

Distortion product otoacoustic emissions (DPOAEs) are low-level acoustic signals, the detection of which involves extraction from a background of noise. Boege and Janssen [J. Acoust. Soc. Am. 111, 1810-1818 (2002)] described a method for modeling the presence and growth of these responses. While improving growth function parameter estimation, this technique excludes a significant fraction of the data (especially low-level responses), and relies on ad hoc model fit acceptance criteria. The statistical difficulties associated with these limitations are described, and a weighted segmented linear regression model that avoids them is proposed. A simple test is presented for the presence of DPOAE growth. This technique is compared to that of Boege and Janssen in a dataset of 9 556 input/output (I/O) functions collected over 4 years on 866 ears from 379 construction apprentices and 63 age-matched controls. Comparisons are made on the entire dataset and within audiometric hearing loss categories. Segmented regression avoids the statistical pitfalls of the previous method, allows estimation of the threshold and slope of auditory response on a far greater number of I/O functions, and improves estimation of these parameters in this dataset. The potential for this method to yield more sensitive metrics of hearing function and compromise is discussed.

Acoustic Impedance Tests↗

PubMed2007

Zonal gene expression in mouse liver resembles expression patterns of Ha-ras and beta-catenin mutated hepatomas.

Hepatocytes of the periportal and perivenous zones of the liver lobule differ in their levels and activities of various enzymes and other proteins. We have recently suggested that beta-catenin- and Ras-dependent signaling pathways play an important role in the regulation of perivenous and periportal gene expression profiles. This hypothesis was primarily based on similarities in zonal differences in gene expression of hepatocytes from normal liver with gene expression patterns of liver tumors: several proteins and mRNAs preferentially expressed in periportal hepatocytes were often overexpressed in Ha-ras mutated mouse liver tumors, whereas perivenous markers were overexpressed in Ctnnb1 (encoding beta-catenin) mutated tumors. We have now extended this work by use of data from two previously conducted microarray analyses aimed to analyze 1) global gene expression patterns of Ha-ras and Ctnnb1 mutated mouse liver tumors and 2) transcriptome differences between periportal and perivenous mouse hepatocytes. By comparison of the datasets, 134 genes or expressed sequences were identified that were present in both datasets. Gene expression patterns in perivenous hepatocytes and Ctnnb1 mutated hepatoma cells were strongly correlated: 96.5% of the genes present in both datasets were regulated in the same direction. In analogy, expression of 74.1% of the genes deregulated in Ha-ras mutated tumors was correlated with the respective expression patterns in periportal hepatocytes. These findings favor the hypothesis that gene expression patterns in periportal and perivenous hepatocytes are regulated, at least in part, by Ras- and beta-catenin-dependent signaling pathways.

Animals↗

PubMed1992

Computer system for assisting with clinical interpretation of tumour marker data.

OBJECTIVE: To design and evaluate a computer advisory system for the treatment of gestational trophoblastic tumour. DESIGN: A comparison of clinicians' treatment decisions with those of the computer system. Two datasets were used: one to calibrate the system and one to independently evaluate it. SETTING: Department of medical oncology. PATIENTS: Computerised records of 290 patients with low risk gestational trophoblastic tumour for whom the advisory system could predict the adequacy of treatment. The calibration set comprised patients admitted during 1979-86(227) and the test set patients during 1986-89(63). MAIN OUTCOME MEASURES: The system's accuracy in predicting need to change treatment compared with clinicians' actions. The mean time faster that the system was in predicting the need to change treatment. RESULTS: On the calibration dataset the system was 94% (164/174) accurate in predicting patients whose treatment was adequate, recommending change when none occurred in only 10 (6%) patients. In patients whose treatment was changed the system recommended change earlier than clinicians in 39/53 cases (74%), with a mean time advantage of 14.9 (SE 2.02) days. On the test dataset the system had an accuracy of 91% (31/34) in predicting treatment adequacy and a false positive rate of 9% (3/34). The system recommended change earlier than clinicians in 22/29 cases (76%), with a mean time advantage of 12.5 (2.22) days. CONCLUSIONS: The computer advisory system could improve patient management by reducing the time spent receiving ineffective treatment. This has implications for both patient time and clinical costs.

Biomarkers, Tumor↗

PubMed1995

Specific therapeutic group age-sex related prescribing units (STAR-PUs): weightings for analysing general practices' prescribing in England.

OBJECTIVES: To derive cost comparators for prescribing by English general practitioners in eight specific therapeutic groups, based on age-sex related weightings, and to confirm, from a new dataset, earlier age-sex weightings for overall prescribing (ASTRO-PUs). DESIGN: Calculations based on one year's prescribing data from selected practices using AAH Meditel software, held on MediPlus by Intercontinental Medical Statistics (IMS, UK and Ireland), and research practices using VAMP software, held on the General Practice Research Database. SETTING: 112 English practices with 739,672 patients and 510 British practices with 3,126,570 patients. MAIN OUTCOME MEASURES: Cost based weightings for 18 age-sex groups and for temporary residents for eight leading specific therapeutic groups and for prescribing overall. RESULTS: The two datasets were similar in age distribution and in the way that prescription numbers were distributed by age-sex band in each therapeutic group. The cost based weightings for specific therapeutic groups showed great variation in the use of these groups for patients in different age-sex groups. When these weightings were applied to the prescribing of practices in two family health services authorities they differed in their power to predict prescribing costs: for cardiovascular and gastrointestinal drugs predictive power was particularly high; for drugs for infections it was particularly low, since these are widely used at all ages and for both sexes. Cost based weightings for overall prescribing derived from the IMS data were similar to those of the ASTRO-PU system even though they were derived by different methods from different datasets. CONCLUSIONS: The weightings (STAR-PUs) offer a sound basis for cost comparisons at the therapeutic group level. Cost-based weightings for overall prescribing derived from the IMS data were reassuringly similar to those of the existing ASTRO-PU system.

Adolescent↗

PubMed2004

Timing of birth and risk of multiple sclerosis: population based study.

OBJECTIVES: To determine if risk of multiple sclerosis (MS) is associated with month of birth in countries in the northern hemisphere and if factors related to month of birth interact with genetic risk. DESIGN: Population based study with population and family based controls and a retrospective cohort identified from death certificates. A post hoc pooled analysis was carried out for large northern datasets including Sweden and Denmark. SETTING: 19 MS clinics in major cities across Canada (Canadian collaborative project on the genetic susceptibility to multiple sclerosis); incident cases of MS from a population based study in the Lothian and Border regions of Scotland; and death records from the UK Registrar General. POPULATIONS: 17,874 Canadian patients and 11,502 British patients with multiple sclerosis. MAIN OUTCOME MEASURE: Diagnosis of multiple sclerosis. RESULTS: In Canada (n = 17,874) significantly fewer patients with MS were born in November compared with controls from the population census and unaffected siblings. These observations were confirmed in a dataset of British patients (n = 11, 502), in which there was also an increase in the number of births in May. A pooled analysis of datasets from Canada, Great Britain, Denmark, and Sweden (n = 42,045) showed that significantly fewer (8.5%) people with MS were born in November and significantly more (9.1%) were born in May. For recent incident data, the effect of month of birth was most evident in Scotland, where MS prevalence is the highest. CONCLUSIONS: Month of birth and risk of MS are associated, more so in familial cases, implying interactions between genes and environment that are related to climate. Such interactions may act during gestation or shortly after birth in individuals born in the northern countries studied.

Canada↗

PubMed1997

Secular trends in proximal femoral fracture, Oxford record linkage study area and England 1968-86.

OBJECTIVE: To study hospital admission rates for fractures of the proximal femur over a period when incidence is reported to have increased, compensating for known lack of precision in coding, excluding nonemergency admissions and transfers, and modelling for age, period, and cohort effects. DESIGN: Validation of coding of a sample of hospital admissions followed by study of two sets of routinely collected statistical abstracts of hospital records; graphical analysis and statistical modelling were used to search for period and cohort effects. SETTING: Oxfordshire and west Berkshire in 1968-86, covered by the Oxford record linkage study (ORLS), and ENGLAND in 1968-85, covered by the hospital inpatient enquiry (HIPE). The ORLS and HIPE datasets are almost independent (ORLS contributed about 1.8% of the HIPE data). SUBJECTS: Records of patients aged 65 and over. OUTCOME MEASURES: Admission rates for fractured neck of femur and fracture of other and unspecified parts of femur (N820 and N821), and evidence of period and cohort effects. RESULTS: The validation study indicated that it was important to combine the codes 820 and 821 in this age group. Admission rates increased over the period studied in both HIPE and ORLS datasets. In HIPE the pattern was of two plateaux separated by a period of rapid rise in the late 1970s. In the ORLS data there was a more steady rise. Statistical analysis showed significant period and cohort effects but much of this was attributable to the component of the model common to both period and cohort effects (termed "drift"). CONCLUSIONS: The finding that admission rates increased in both datasets, combining relevant codings and restricting analysis to emergency admissions, strongly suggests that the rise was real. At least part of the period effect in the HIPE data, however, might be attributable to a sampling artefact. The cohort effect in incidence rates of femoral fracture has not been previously shown and would be compatible with a number of aetiological hypotheses.

Aged↗

PubMed2000

Validity of rapid estimates of household wealth and income for health surveys in rural Africa.

STUDY OBJECTIVE: To test the validity of proxy measures of household wealth and income that can be readily implemented in health surveys in rural Africa. DESIGN: Data are drawn from four different integrated household surveys. The assumptions underlying the choice of wealth proxy are described, and correlations with the true value are assessed in two different settings. The expenditure proxy is developed and then tested for replicability in two independent datasets representing the same population. SETTING: Rural areas of Mali, Malawi, and Côte d'Ivoire (two national surveys). PARTICIPANTS: Random sample of rural households in each setting (n=275, 707, 910, and 856, respectively). MAIN RESULTS: In both Mali and Malawi, the wealth proxy correlated highly (r>/=0.74) with the more complex monetary value method. For rural areas of Côte d'Ivoire, it was possible to generate a list of just 10 expenditure items, the values of which when summed correlated highly with expenditures on all items combined (r=0.74, development dataset, r=0. 72, validation dataset). Total household expenditure is an accepted alternative to household income in developing country settings. CONCLUSIONS: It is feasible to approximate both household wealth and expenditures in rural African settings without dramatically lengthening questionnaires that have a primary focus on health outcomes.

Africa↗

PubMed2001

Prognostic factors in women with breast cancer: distribution by socioeconomic status and effect on differences in survival.

STUDY OBJECTIVE: To quantify and investigate differences in survival from breast cancer between women resident in affluent and deprived areas and define the contribution of underlying factors to this variation. DESIGN: Analysis of two datasets relating to breast cancer patients in Scotland: (1) population-based cancer registry data; (2) a subset of cancer registration records supplemented by abstraction of prognostic variables (stage, node status, tumour size, oestrogen receptor (ER) status, type of surgery, use of radiotherapy and use of adjuvant systemic therapy) from medical records. SETTING: Scotland. PATIENTS: (1) Cancer registration data on 21,751 women aged under 85 years diagnosed with primary breast cancer between 1978 and 1987; (2) national clinical audit data on 2035 women aged under 85 years diagnosed with primary breast cancer during 1987 for whom adequate medical records were available. MAIN RESULTS: Survival differences of 10% between affluent and deprived women were observed in both datasets, across all age groups. In the audit dataset, the distribution of ER status varied by deprivation group (65% ER positive in affluent group v 48% ER positive in deprived group; under 65 age group). Women aged under 65 with non-metastatic disease were more likely to have breast conservation than a mastectomy if they were affluent (45%) than deprived (32%); the affluent were more likely to receive endocrine therapy (65%) than the deprived (50%). However, these factors accounted for about 20% of the observed difference in survival between women resident in affluent and deprived areas. CONCLUSIONS: Deprived women with breast cancer have poorer outcomes than affluent women. This can only partly be explained by deprived women having more ER negative tumours than affluent women. Further research is required to identify other reasons for poorer outcomes in deprived women, with a view to reducing these survival differences.

Adult↗