Metabolic and cardiovascular traits: an abundance of recently identified common genetic variants

Genome-wide association studies are providing new insights into the genetic basis of metabolic and cardiovascular traits. In the past 3 years, common variants in ∼50 loci have been strongly associated with metabolic and cardiovascular traits. Several of these loci have implicated genes without a previously known connection with metabolism. Further studies will be required to characterize the full impact of these loci on metabolism. Many of the identified loci include multiple independent variants that influence the same metabolic or cardiovascular trait and a few loci harbor independent variants that each influence distinct traits. The total proportion of trait heritability explained by variants identified so far is still modest (typically <10%). Future studies will build on these successes by identifying additional common and rare variants and by determining the functional impact of the underlying alleles and genes

A meeting report: OECD-GESIS Seminar on Translating and Adapting Instruments in Large-Scale Assessments (2018)

This report summarizes the main themes and conclusions from the OECD-GESIS Seminar on Translating and Adapting Instruments in Large-Scale Assessments, which took place at the Organization for Economic Co-operation and Development (OECD), Paris, in June 2018. The five sessions covered the topics (1) etic (universal) vs. emic (culture-specific) measurement instruments, (2) language- and culture-sensitive development of measurement instruments, (3) international guidelines vs. implementation in countries and by translators, (4) tools and technological developments, and (5) quality control of translations. Key players in the field presented on best practice, lessons learned, and innovations and also made suggestions for moving the field forward

An assessment of drinking water contamination with Helicobacter pylori in Lima, Peru

BackgroundHelicobacter pylori is a gut bacterium that is the primary cause of gastric cancer. H. pylori infection has been consistently associated with lack of access to sanitation and clean drinking water. In this study, we conducted time‐series sampling of drinking water in Lima, Peru, to examine trends of H. pylori contamination and other water characteristics.Materials and methodsDrinking water samples were collected from a single faucet in Lima’s Lince district 5 days per week from June 2015 to May 2016, and pH, temperature, free available chlorine, and conductivity were measured. Quantities of H. pylori in all water samples were measured using quantitative polymerase chain reaction. Relationships between the presence/absence and quantity of H. pylori and water characteristics in the 2015‐2016 period were examined using regression methods accounting for the time‐series design.ResultsForty‐nine of 241 (20.3%) of drinking water samples were contaminated with H. pylori. Statistical analyses identified no associations between sampling date and the likelihood of contamination with H. pylori. Statistically significant relationships were found between lower temperatures and a lower likelihood of the presence of H. pylori (P < .05), as well as between higher pH and higher quantities of H. pylori (P < .05).ConclusionsThis study has provided evidence of the presence of H. pylori DNA in the drinking water of a single drinking water faucet in the Lince district of Lima. However, no seasonal trends were observed. Further studies are needed to determine the presence of H. pylori in other drinking water sources in other districts in Lima, as well as to determine the viability of H. pylori in these water sources. Such studies would potentially allow for better understanding and estimates of the risk of infection due to exposure to H. pylori in drinking water.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142894/1/hel12462.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142894/2/hel12462_am.pd

EFBAT: exact family-based association tests

Background: Family-based association tests are important tools for investigating genetic risk factors of complex diseases. These tests are especially valuable for being robust to population structure. We introduce a tool, EFBAT, which performs exact family-based tests of association for X-chromosome and autosomal biallelic markers. Results: The program EFBAT extends a network algorithm previously applied to autosomal markers to include the X-chromosome and to perform tests of association under the null hypotheses "no association, no linkage" and "no association in the presence of linkage" under additive, dominant and recessive genetic models. These tests are valid regardless of patterns of missing familial data. Conclusion: The general framework for performing exact family-based association tests has been usefully extended to the X-chromosome, particularly for the hypothesis of "no association in the presence of linkage" and for different genetic models