A Bayesian Hierarchical Model to Derive Novel Gene Networks from Gene Ontology Fingerprints

We developed a Bayesian hierarchical model to identify gene networks based on the similarity score generated from comparing the gene ontology fingerprints of gene pairs. Genes in this network were assumed to have similar biological functions that can be indicated by their ontology fingerprints. Our results indicate that different pathways show consistent score threshold that allow us to distinguish biological relevant gene—gene connections in the network

Using Ontology Fingerprints to evaluate genome-wide association study results

We describe an approach to characterize genes or phenotypes via ontology fingerprints which are composed of Gene Ontology (GO) terms overrepresented among those PubMed abstracts linked to the genes or phenotypes. We then quantify the biological relevance between genes and phenotypes by comparing their ontology fingerprints to calculate a similarity score. We validated this approach by correctly identifying genes belong to their biological pathways with high accuracy, and applied this approach to evaluate GWA study by ranking genes associated with the lipid concentrations in plasma as well as to prioritize genes within linkage disequilibrium (LD) block. We found that the genes with highest scores were: ABCA1, LPL, and CETP for HDL; LDLR, APOE and APOB for LDL; and LPL, APOA1 and APOB for triglyceride. In addition, we identified some top ranked genes linking to lipid metabolism from the literature even in cases where such knowledge was not reflected in current annotation of these genes. These results demonstrate that ontology fingerprints can be used effectively to prioritize genes from GWA studies for experimental validation

Evaluation of the learning outcomes of a year-long postgraduate training course in community geriatrics for primary care doctors

There are increasing expectations on primary care doctors to shoulder a bigger share of care for patients with common geriatric problems in the community. This study aims to examine the outcomes of a postgraduate training course in geriatrics for primary care doctors. A questionnaire developed by the research team was sent to the course graduates (years 2001-2007). Ninety-eight replies were received with a response rate of 52.4% (98/187). Difference in the ratings by the respondents before and after taking the course was analyzed using the nonparametric Wilcoxon signed rank test. Most respondents felt more rewarding and had participated more in geriatric care, and the majority had improvement in their communication skills with elderly patients after taking the course. Moreover, the graduates are more confident in diagnosing and managing common geriatric problems, and deciding to which specialty to refer the elderly patients. Of the referrals, there was a significant increase to private geriatricians and a significant reduction to other specialists. The average number of elderly patients seen per day had also increased. However, little change was observed about making nursing home visits, the frequency of which remained low. Many graduates expressed difficulties in conducting nursing home visits. © 2010 Elsevier Ireland Ltd.postprin

Drawing-Based Automatic Dementia Screening Using Gaussian Process Markov Chains

Screening tests play an important role for early detection of dementia. Among those widely used screening tests, drawing tests have gained much attention in clinical psychology. Traditional evaluation of drawing tests totally relies on the appearance of drawn picture, but does not consider any time-dependent behaviour. We demonstrated that the processing speed and direction can reflect the decline of cognitive function, and thus may be useful for disease screening. We proposed a model of Gaussian process Markov chains (GPMC) to study the complex associations within the drawing data. Specifically, we modeled the process of drawing in a state-space form, where a drawing state is composed of drawing direction and velocity with consideration of the processing time. For temporal modeling, our scope focused more on discrete-time Markov chains on continuous state space. Because of the short processing time of picture drawing, we applied higher-order of Markov chains to model long-term temporal correlation across drawing states. Gaussian process regression was used for universal function approximation to flexibly infer the state transition function. With Gaussian process prior to the distribution of function space, we could encode high-level function properties such as noisiness, smoothness and periodicity. We also derived an efficient training mechanism for complex Gaussian process regression on bivariate Markov chains. With GPMC, we present an optimal decision rule based on Bayesian decision theory. We applied our proposed method to a drawing test for dementia screening, i.e. interlocking pentagon-drawing test. We tested our models with 256 subjects who are aged from 65 to 95. Finally, comparing to the traditional methods, our models showed remarkable improvement in drawing test for dementia screening

Consistent Differential Expression Pattern (CDEP) on microarray to identify genes related to metastatic behavior

<p>Abstract</p> <p>Background</p> <p>To utilize the large volume of gene expression information generated from different microarray experiments, several meta-analysis techniques have been developed. Despite these efforts, there remain significant challenges to effectively increasing the statistical power and decreasing the Type I error rate while pooling the heterogeneous datasets from public resources. The objective of this study is to develop a novel meta-analysis approach, Consistent Differential Expression Pattern (CDEP), to identify genes with common differential expression patterns across different datasets.</p> <p>Results</p> <p>We combined False Discovery Rate (FDR) estimation and the non-parametric RankProd approach to estimate the Type I error rate in each microarray dataset of the meta-analysis. These Type I error rates from all datasets were then used to identify genes with common differential expression patterns. Our simulation study showed that CDEP achieved higher statistical power and maintained low Type I error rate when compared with two recently proposed meta-analysis approaches. We applied CDEP to analyze microarray data from different laboratories that compared transcription profiles between metastatic and primary cancer of different types. Many genes identified as differentially expressed consistently across different cancer types are in pathways related to metastatic behavior, such as ECM-receptor interaction, focal adhesion, and blood vessel development. We also identified novel genes such as <it>AMIGO2</it>, <it>Gem</it>, and <it>CXCL11 </it>that have not been shown to associate with, but may play roles in, metastasis.</p> <p>Conclusions</p> <p>CDEP is a flexible approach that borrows information from each dataset in a meta-analysis in order to identify genes being differentially expressed consistently. We have shown that CDEP can gain higher statistical power than other existing approaches under a variety of settings considered in the simulation study, suggesting its robustness and insensitivity to data variation commonly associated with microarray experiments.</p> <p><b>Availability</b>: CDEP is implemented in R and freely available at: <url>http://genomebioinfo.musc.edu/CDEP/</url></p> <p><b>Contact</b>: [email protected]</p

A partitioned 88-loci psoriasis genetic risk score reveals HLA and non-HLA contributions to clinical phenotypes in a Newfoundland psoriasis cohort

Psoriasis is an immune-mediated inflammatory skin disease typically characterized by erythematous and scaly plaques. It affects 3% of the Newfoundland population while only affecting 1.7% of the general Canadian population. Recent genome-wide association studies (GWAS) in psoriasis have identified more than 63 genetic susceptibility loci that individually have modest effects. Prior studies have shown that a genetic risk score (GRS) combining multiple loci can improve psoriasis disease prediction. However, these prior GRS studies have not fully explored the association of GRS with patient clinical characteristics. In this study, we calculated three types of GRS: one using all known GWAS SNPs (GRS-ALL), one using a subset of SNPs from the HLA region (GRS-HLA), and the last using non-HLA SNPs (GRS-noHLA). We examined the relationship between these GRS and a number of psoriasis features within a well characterized Newfoundland psoriasis cohort. We found that both GRS-ALL and GRS-HLA were significantly associated with early age of psoriasis onset, psoriasis severity, first presentation of psoriasis at the elbow or knee, and the total number of body locations affected, while only GRS-ALL was associated with a positive family history of psoriasis. GRS-noHLA was uniquely associated with genital psoriasis. These findings clarify the relationship of the HLA and non-HLA components of GRS with important clinical features of psoriasis

Signaling network prediction by the Ontology Fingerprint enhanced Bayesian network

Abstract Background Despite large amounts of available genomic and proteomic data, predicting the structure and response of signaling networks is still a significant challenge. While statistical method such as Bayesian network has been explored to meet this challenge, employing existing biological knowledge for network prediction is difficult. The objective of this study is to develop a novel approach that integrates prior biological knowledge in the form of the Ontology Fingerprint to infer cell-type-specific signaling networks via data-driven Bayesian network learning; and to further use the trained model to predict cellular responses. Results We applied our novel approach to address the Predictive Signaling Network Modeling challenge of the fourth (2009) Dialog for Reverse Engineering Assessment's and Methods (DREAM4) competition. The challenge results showed that our method accurately captured signal transduction of a network of protein kinases and phosphoproteins in that the predicted protein phosphorylation levels under all experimental conditions were highly correlated (R2 = 0.93) with the observed results. Based on the evaluation of the DREAM4 organizer, our team was ranked as one of the top five best performers in predicting network structure and protein phosphorylation activity under test conditions. Conclusions Bayesian network can be used to simulate the propagation of signals in cellular systems. Incorporating the Ontology Fingerprint as prior biological knowledge allows us to efficiently infer concise signaling network structure and to accurately predict cellular responses.http://deepblue.lib.umich.edu/bitstream/2027.42/109490/1/12918_2012_Article_989.pd

Hong Kong domestic health spending: financial years 1989/90 to 2005/06

This report presents the latest estimates of Hong Kong domestic health spending between fiscal years 1989/90 and 2005/06, cross-stratified and categorised by financing source, provider, and function on an annual basis. In fiscal year 2005/06, total health expenditure was HK$71 557 million. In real terms, it grew 6.5$71 557 million total health expenditure in 2005/06, HK$68 810 million (96.2$2746 million (3.8%) on capital expenses (ie investment in medical facilities). Services of curative care accounted for the largest share (67.3%) and were made up of ambulatory services (35.7%), in-patient services (27.7%), day patient hospital services (3.4%), and home care (0.6%). The second largest share was spending on medical goods outside the patient care setting (10.8%). In terms of health care providers, hospitals (44.0%) accounted for the largest share of total health expenditure in 2005/06, followed by providers of ambulatory health care (31.4%). We observed a system-wide trend towards service consolidation at institutions (as opposed to free-standing ambulatory clinics, most of which are staffed by solo practitioners). Not taking capital expenses (ie investment in medical facilities) into account, public current expenditure on health amounted to HK$34 849 million (50.6$33 961 million) was mostly incurred at providers of ambulatory health care (55.8%). This reflects the mixed health care economy of Hong Kong, where public hospitals generally account for about 90% of total bed-days and private doctors (including western and Chinese medicine practitioners) provide about 70% of out-patient care. Although both public and private spending were mostly expended on personal health care services and goods (93.0%), the patterns of distribution among functional categories differed. Public expenditure was targeted at in-patient care (53.7%) and substantially less on out-patient care (24.6%), especially low-intensity first-contact care. In comparison, private spending was concentrated on out-patient care (49.9%), followed by medical goods outside the patient care setting (22.0%) and in-patient care (19.0%). Compared to countries of the Organisation for Economic Co-operation and Development, Hong Kong has devoted a relatively low percentage of gross domestic product on health services in the last decade. As a share of total spending, public funding (either general government revenue or social security funds) was also lower than in most comparably developed economies, although commensurate with its public revenue collection base.published_or_final_versio

Management and outcome of antenatally diagnosed congenital cystic adenomatoid malformation of the lung

Objective: To review the management and outcome of babies with antenatally diagnosed congenital cystic adenomatoid malformation. Design: Retrospective cohort review. Setting: Tertiary neonatal care unit at Queen Mary Hospital and antenatal diagnostic centre at Tsan Yuk Hospital. Patients: Consecutive patients with antenatally suspected congenital cystic adenomatoid malformation in their concepti among antenatal patients attending Tsan Yuk Hospital from 1994 to 2002. Twenty-four of 33 cases were referred to Queen Mary Hospital for postnatal management and for whom comprehensive records were available for analysis in 23. Interventions: Postnatal interventions in their babies included investigational imaging for congenital cystic adenomatoid malformation and surgery. Main outcome measures: Antenatal and postnatal outcome, as well as pathology of the excised lesions. Results: Antenatal outcome: termination of pregnancy in two cases and spontaneous abortion in one; in-utero regression was documented in nine cases and in one hydropic change was apparent. Postnatal outcome: only eight of 20 babies born alive had symptoms in neonatal period. Two developed serious infective complications in infancy, one with documented in-utero regression. Pulmonary parenchymal abnormalities were detected on computed tomography of the thorax in six of seven cases with normal or non-specific chest radiograph findings. Among nine cases with in-utero regression, congenital cystic adenomatoid malformation was confirmed by operative histology in five and abnormal computed tomography findings in three. Fifteen babies underwent surgical excision, one of whom died because of severe pre-existing pulmonary hypoplasia and nine endured minor postoperative complications. A favourable outcome was documented at a mean follow-up of 22 months (range, 2 months-7 years). Conclusions: In-utero regression of congenital cystic adenomatoid malformation on antenatal ultrasound may not represent genuine resolution. Computed tomographic thorax should be considered in all newborns with antenatally diagnosed congenital cystic adenomatoid malformation, and if confirmed early operation before first hospital discharge is recommended.published_or_final_versio

Hong Kong domestic health spending: Financial years 1989/90 to 2008/09

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