An ontology to standardize research output of nutritional epidemiology : from paper-based standards to linked content

Background: The use of linked data in the Semantic Web is a promising approach to add value to nutrition research. An ontology, which defines the logical relationships between well-defined taxonomic terms, enables linking and harmonizing research output. To enable the description of domain-specific output in nutritional epidemiology, we propose the Ontology for Nutritional Epidemiology (ONE) according to authoritative guidance for nutritional epidemiology. Methods: Firstly, a scoping review was conducted to identify existing ontology terms for reuse in ONE. Secondly, existing data standards and reporting guidelines for nutritional epidemiology were converted into an ontology. The terms used in the standards were summarized and listed separately in a taxonomic hierarchy. Thirdly, the ontologies of the nutritional epidemiologic standards, reporting guidelines, and the core concepts were gathered in ONE. Three case studies were included to illustrate potential applications: (i) annotation of existing manuscripts and data, (ii) ontology-based inference, and (iii) estimation of reporting completeness in a sample of nine manuscripts. Results: Ontologies for food and nutrition (n = 37), disease and specific population (n = 100), data description (n = 21), research description (n = 35), and supplementary (meta) data description (n = 44) were reviewed and listed. ONE consists of 339 classes: 79 new classes to describe data and 24 new classes to describe the content of manuscripts. Conclusion: ONE is a resource to automate data integration, searching, and browsing, and can be used to assess reporting completeness in nutritional epidemiology

Leveraging Epidemiology to Improve Risk Assessment.

The field of environmental public health is at an important crossroad. Our current biomonitoring efforts document widespread exposure to a host of chemicals for which toxicity information is lacking. At the same time, advances in the fields of genomics, proteomics, metabolomics, genetics and epigenetics are yielding volumes of data at a rapid pace. Our ability to detect chemicals in biological and environmental media has far outpaced our ability to interpret their health relevance, and as a result, the environmental risk paradigm, in its current state, is antiquated and ill-equipped to make the best use of these new data. In light of new scientific developments and the pressing need to characterize the public health burdens of chemicals, it is imperative to reinvigorate the use of environmental epidemiology in chemical risk assessment. Two case studies of chemical assessments from the Environmental Protection Agency Integrated Risk Information System database are presented to illustrate opportunities where epidemiologic data could have been used in place of experimental animal data in dose-response assessment, or where different approaches, techniques, or studies could have been employed to better utilize existing epidemiologic evidence. Based on the case studies and what can be learned from recent scientific advances and improved approaches to utilizing human data for dose-response estimation, recommendations are provided for the disciplines of epidemiology and risk assessment for enhancing the role of epidemiologic data in hazard identification and dose-response assessment

Development of Multi-Locus Variable Number Tandem Repeat Analysis for Outbreak Detection of Neisseria meningitidis

Neisseria meningitidis is a major cause of septicemia and meningitis worldwide. Traditional typing methods like pulsed-field gel electrophoresis (PFGE) for identifying outbreaks are subjective and time consuming. Multi-locus variable number tandem repeats analysis (MLVA) is an objective typing method amenable to automation that has been used to type other bacterial pathogens. This report describes the development of MLVA for outbreak detection of N. meningitidis. Tandem Repeats Finder software was used to identify variable number tandem repeats (VNTRs) from 3 sequenced N. meningitidis genomes. PCR amplification of identified VNTRs was performed on DNA from 7 serogroup representative isolates. PCR products were sequenced and repeats were manually counted. VNTR loci identified by this screen were evaluated on a collection of 46 outbreak and sporadic serogroup C isolates. Alleles at each locus were concatenated to define the MLVA type for each isolate. Minimum spanning tree (MST) analysis was performed to determine the genetic relationships among the isolates. The genetic distance was defined as the summed tandem repeat difference (STRD) between isolates MLVA types. Outbreak clusters were defined by a STRD less than or equal to 3. These data was compared to PFGE data to determine the utility of MLVA for outbreak detection. Twenty-one VNTR loci with variable copy numbers among the sequenced genomes were identified that met the established criteria of short repeat length and consensus sequence > 85%. Seven VNTR loci were reliably amplified among the 7 serogroups tested. These loci had repeat lengths between 4 and 20 nucleotides and exhibited between 10 and 26 alleles among 61 isolates belonging to 7 different serogroups. MST analysis with 7 loci differentiated serogroups, discriminated sporadic isolates and identified 7 out of 8 serogroup C outbreaks. In summary, MLVA with 5 VNTR loci distinguished N. meningitidis isolates from 7 different serogroups and sporadic isolates within each serogroup. In addition, MLVA identified 88% of PFGE-defined serogroup C outbreaks. Further investigation of these and other outbreak-associated isolates is necessary to define the optimal combination of VNTR loci and to evaluate MST analysis criteria in order to determine the utility of MLVA for N. meningitidis outbreak detection

A new robust diagnostic polymerase chain reaction for determining the mating status of female Anopheles gambiae mosquitoes.

The principal malaria vector in Africa, Anopheles gambiae, contains two pairs of autosomes and one pair of sex chromosomes. The Y chromosome is only associated with males and other Y chromosome-specific DNA sequences, which are transferred to women during mating. A reliable tool to determine the mating status of dried wild An. gambiae females is currently lacking. DNA was extracted from dried virgin and mated females and used to test whether Y chromosome-specific polymerase chain reaction (PCR) markers can be successfully amplified and used as a predictor of mating. Here we report a new PCR-based method to determine the mating status among successfully inseminated and virgin wild An. gambiae females, using three male-specific primers. This dissection-free method has the potential to facilitate studies of both population demographics and gene flow from dried mosquito samples routinely collected in epidemiologic monitoring and aid existing and new malaria-vector control approaches

Exposure to benzene at work and the risk of leukemia: a systematic review and meta-analysis

Background A substantial number of epidemiologic studies have provided estimates of the relation between exposure to benzene at work and the risk of leukemia, but the results have been heterogeneous. To bridge this gap in knowledge, we synthesized the existing epidemiologic evidence on the relation between occupational exposure to benzene and the risk of leukemia, including all types combined and the four main subgroups acute myeloid leukemia (AML), acute lymphocytic leukemia (ALL), chronic lymphocytic leukemia (CLL), and chronic myeloid leukemia (CML). Methods A systematic literature review was carried out using two databases 'Medline' and 'Embase' from 1950 through to July 2009. We selected articles which provided information that can be used to estimate the relation between benzene exposure and cancer risk (effect size). Results In total 15 studies were identified in the search, providing 16 effect estimates for the main analysis. The summary effect size for any leukemia from the fixed-effects model was 1.40 (95% CI, 1.23-1.57), but the study-specific estimates were strongly heterogeneous (I2 = 56.5%, Q stat = 34.47, p = 0.003). The random-effects model yielded a summary- effect size estimate of 1.72 (95% CI, 1.37-2.17). Effect estimates from 9 studies were based on cumulative exposures. In these studies the risk of leukemia increased with a dose-response pattern with a summary-effect estimate of 1.64 (95% CI, 1.13-2.39) for low (< 40 ppm-years), 1.90 (95% CI, 1.26-2.89) for medium (40-99.9 ppm-years), and 2.62 (95% CI, 1.57-4.39) for high exposure category (> 100 ppm-years). In a meta-regression, the trend was statistically significant (P = 0.015). Use of cumulative exposure eliminated heterogeneity. The risk of AML also increased from low (1.94, 95% CI, 0.95-3.95), medium (2.32, 95% CI, 0.91-5.94) to high exposure category (3.20, 95% CI, 1.09-9.45), but the trend was not statistically significant. Conclusions Our study provides consistent evidence that exposure to benzene at work increases the risk of leukemia with a dose-response pattern. There was some evidence of an increased risk of AML and CLL. The meta-analysis indicated a lack of association between benzene exposure and the risk of CML

Differential trends in the compression of mortality: Assessing the antecedents to current gaps in health expectancy in New Zealand

Health Expectancies (HEs) for New Zealand show significant differentials between Maori and non-Maori, but also by gender and period. These differentials correlate with findings from both generation and synthetic life-tables relating to New Zealand’s epidemiologic transition. At the beginning of that transition quartile 1 (Q(1)), and Median (Med) d(x) values were close and centred at young ages; during the transition the gap became very wide; at the transition’s end the gap again narrowed. Cohort and synthetic trends in d(x), l(x), M, Qs and Meds are reviewed and linked to recent HEs. Data point to epidemic polarisation. Cohort analysis allows the evaluation of the role of past experiences on the recent HEs, and thus point to possible strategies for reducing gaps in both d(x), and HEs

A 10-year Study of Factors Associated with Alcohol Treatment Use and Non-use in a U.S. Population Sample

Background This study seeks to identify changes in perceived barriers to alcohol treatment and predictors of treatment use between 1991–92 and 2001–02, to potentially help understand reported reductions in treatment use at this time. Social, economic, and health trends during these 10 years provide a context for the study. Methods Subjects were Whites, Blacks, and Hispanics. The data were from the National Longitudinal Alcohol Epidemiologic Survey (NLAES) and the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). We conducted two analyses that compared the surveys on: 1) perceived treatment barriers for subjects who thought they should get help for their drinking, and 2) variables predicting past-year treatment use in an alcohol use disorder subsample using a multi-group multivariate regression model. Results In the first analysis, those barriers that reflected negative beliefs and fears about seeking treatment as well as perceptions about the lack of need for treatment were more prevalent in 2001–02. The second analysis showed that survey year moderated the relationship between public insurance coverage and treatment use. This relationship was not statistically significant in 1991–92 but was significant and positive in 2001–02, although the effect of this change on treatment use was small. Conclusions Use of alcohol treatment in the U.S. may be affected by a number of factors, such as trends in public knowledge about treatment, social pressures to reduce drinking, and changes in the public financing of treatment

Discriminatory ability of hypervariable variable number tandem repeat loci in population-based analysis of Mycobacterium tuberculosis strains, London, UK

To address conflicting results about the stability of variable number tandem repeat (VNTR) loci and their value in prospective molecular epidemiology of Mycobacterium tuberculosis, we conducted a large prospective population-based analysis of all M. tuberculosis strains in a metropolitan setting. Optimal and reproducible conditions for reliable PCR and fragment analysis, comprising enzymes, denaturing conditions, and capillary temperature, were identified for a panel of hypervariable loci, including 3232, 2163a, 1982, and 4052. A total of 2,261 individual M. tuberculosis isolates and 265 sets of serial isolates were analyzed by using a standardized 15-loci VNTR panel, then an optimized hypervariable loci panel. The discriminative ability of loci varied substantially; locus VNTR 3232 varied the most, with 19 allelic variants and Hunter-Gaston index value of 0.909 . Hypervariable loci should be included in standardized panels because they can provide consistent comparable results at multiple settings, provided the proposed conditions are adhered to