Exome-wide association study identifies genetic polymorphisms of C12orf51, MYL2, and ALDH2 associated with blood lead levels in the general Korean population

Evidence of micro-evolution in Crocidura russula from two abandoned heavy metal mines: potential use of Cytb, CYP1A1, and p53 as gene biomarkers

Heavy metals accumulated in the environment due to the mining industry may impact on the health of exposed wild animals with consequences at the population level via survival and selection of the most resistant individuals. The detection and quantification of shifts in gene frequencies or in the genetic structure in populations inhabiting polluted sites may be used as early indicators of environmental stress and reveal potential 'candidate gene biomarkers' for environmental health assessment. We had previously observed that specimens of the Greater white-toothed shrew (Crocidura russula) from two heavy metal mines in Southern Portugal (the Aljustrel and the Preguiça mines) carried physiological alterations compared to shrews from an unpolluted site. Here, we further investigated whether these populations showed genetic differences in genes relevant for physiological homeostasis and/or that are associated with pathways altered in animals living under chronic exposure to pollution, and which could be used as biomarkers. We analysed the mitochondrial cytochrome b (Cytb) gene and intronic and/or exonic regions of four nuclear genes: CYP1A1, LCAT, PRPF31, and p53. We observed (1) population differences in allele frequencies, types of variation, and diversity parameters in the Cytb, CYP1A1, and p53 genes; (2) purifying selection of Cytb in the mine populations; (3) genetic differentiation of the two mine populations from the reference by the p53 gene. Adding to our previous observations with Mus spretus, we provide unequivocal evidence of a population effect exerted by the contaminated environment of the mines on the local species of small mammals.

Blood lead concentration and exposure related factors in Korea from the National Environmental Health Survey (KoNEHS) II (2012-2014)

This study evaluated lead concentrations in blood and related factors among the South Korean population based on data from the Korea National Environmental Health Survey (KoNEHS) II (2012-2014) conducted by the National Institute of Environmental Research and the Ministry of Environment. Personal data were obtained from non-institutionalized civilian Korean individuals in an interview with trained community surveyors using a structured questionnaire (n = 6,455, aged 19 or older, mean age 49.7 years). The lead concentrations in whole blood were analyzed by atomic absorption spectrophotometry (AAS) with a Zeeman-effect-based background corrector. The precision and accuracy of the analytical methods were verified by internal and external quality controls (G-EQUAS, Germany). Statistical analysis was performed using weighted KoNEHS II data separated by sex, and the lead concentration was expressed as a geometric mean (GM). Multiple linear regression was performed using the SPSS 23.0 software package (SPSS Inc., Chicago, IL, USA). The total GM of lead concentrations was 19.5 µg/L. Lead concentrations increased with age and were higher in males (22.8 µg/L) than in females (16.6 µg/L). Smokers and drinkers had higher concentrations than non-smokers and non-drinkers of both sexes. People who used herbal medications had higher concentrations than those who did not among females. People of both sexes living in rural areas had higher lead concentrations than those in urban areas. Lead concentrations also varied with educational level, total family income, the type of water regularly consumed, and occupation. The average lead concentration of the general adult population in Korea has rapidly decreased over time from 45.8 µg/L (1999) to 19.45 µg/L (2012-2014); however, it remains higher than that of the United States, Germany, and Canada. The factors significantly related to lead concentration in South Korea were age, sex, smoking and alcohol drinking status, herbal medication usage by females, residential area, drinking water at home, and occupation. These factors could be used to improve occupational and environmental hygiene among the Korean population.

Large-Scale Analysis of Genetic and Clinical Patient Data

Biomedical data science has experienced an explosion of new data over the past decade. Abundant genetic and genomic data are increasingly available in large, diverse data sets due to the maturation of modern molecular technologies. Along with these molecular data, dense, rich phenotypic data are also available on comprehensive clinical data sets from health care provider organizations, clinical trials, population health registries, and epidemiologic studies. The methods and approaches for interrogating these large genetic/genomic and clinical data sets continue to evolve rapidly, as our understanding of the questions and challenges continue to emerge. In this review, the state-of-the-art methodologies for genetic/genomic analysis along with complex phenomics will be discussed. This field is changing and adapting to the novel data types made available, as well as technological advances in computation and machine learning. Thus, I will also discuss the future challenges in this exciting and innovative space. The promises of precision medicine rely heavily on the ability to marry complex genetic/genomic data with clinical phenotypes in meaningful ways.