Clinical Pharmacy in the Genomic Era

Over a century ago Gregor Mendel investigated quantitatively how physical traits of plants were passed on from one generation to the next. Soon after, William Bateson and Archibald Garrod showed the relevance of Mendel’s findings to human disease. Pharmacists have throughout history marketed themselves as experts who could treat disease with specific medicines. Their claims were however poorly validated until Louis Pasteur and Robert Koch established the microbial aetiology of many diseases. Effective antimicrobial agents and immunotherapies soon became available for an expanding range of infections, and personalisation of treatment became possible through sensitivity testing. Later, a greater understanding of the molecular pathogenesis of non-microbial diseases led to the development of effective drugs, such as antihypertensives and anticoagulants. As a result, current pharmacopoeias bear no resemblance to their predecessors cluttered with predominantly useless drugs. With the unravelling of the double helical structure of DNA and greater understanding of its implications for health and disease, pharmacopoeias are being rewritten again. The new drugs enable an unprecedented level of individualisation of therapy. To optimise the promise of these drugs, input from a new generation of well-informed clinical pharmacists is needed. In this presentation, we identify some of these developments, and where input from pharmacists is most likely to be required. Will clinical pharmacists deliver

Bacteremic pneumonia caused by extended-spectrum beta-lactamase-producing Escherichia coli and Klebsiella pneumoniae: Appropriateness of empirical treatment matters

BackgroundClinical information about bacteremic pneumonia caused by extended-spectrum beta-lactamase (ESBL)-producing organism is limited.MethodsA retrospective study was conducted at two medical centers in Taiwan. From May 2002 to August 2010, clinical information and outcome of adults with bacteremic pneumonia caused by ESBL-producing Escherichia coli and Klebsiella pneumoniae were analyzed. The primary outcome is the 30-day mortality.ResultsA total of 111 patients with bacteremic pneumonia caused by E. coli (37 patients, 33.3%) and K. pneumoniae (74, 66.7%) were identified. Their mean age was 69.2 years and 51.4% were male patients. Fifty-seven (51.3%) episodes were classified as hospital-acquired infections, 19 (17.1%) as health-care-associated infections, and four (3.6%) as community-acquired infections. Fifty-one (45.9%) patients received appropriate empiric antimicrobial therapy. The 30-day mortality rate was 40.5% (45 patients). In the multivariate analysis, several independent risk factors, including rapidly fatal underlying disease [odds ratio (OR), 5.75; 95% confidence interval (CI), 1.54–21.48; p = 0.009], severe sepsis (OR, 4.84; 95% CI, 1.55–15.14; p = 0.007), critical illness (OR, 4.28; 95% CI, 1.35–13.57; p = 0.013), and receipt of appropriate empirical therapy (OR, 0.19; 95% CI, 0.07–0.55; p = 0.002), were associated with 30-day mortality. The survival analysis consistently found that individuals with appropriate empiric therapy had a higher survival rate (log-rank test, p < 0.001).ConclusionESBL-producing bacteremic pneumonia, especially health-care-associated infections, often occurred in adults with comorbidities. Appropriate empirical therapy was associated with a favorable outcome

Genome-Wide Gene-Environment Interaction Analysis Using Set-Based Association Tests

The identification of gene-environment interactions (G × E) may eventually guide health-related choices and medical interventions for complex diseases. More powerful methods must be developed to identify G × E. The “adaptive combination of Bayes factors method” (ADABF) has been proposed as a powerful genome-wide polygenic approach to detect G × E. In this work, we evaluate its performance when serving as a gene-based G × E test. We compare ADABF with six tests including the “Set-Based gene-EnviRonment InterAction test” (SBERIA), “gene-environment set association test” (GESAT), etc. With extensive simulations, SBERIA and ADABF are found to be more powerful than other G × E tests. However, SBERIA suffers from a power loss when 50% SNP main effects are in the same direction with the SNP × E interaction effects while 50% are in the opposite direction. We further applied these seven G × E methods to the Taiwan Biobank data to explore gene× alcohol interactions on blood pressure levels. The ADAMTS7P1 gene at chromosome 15q25.2 was detected to interact with alcohol consumption on diastolic blood pressure (p = 9.5 × 10−7, according to the GESAT test). At this gene, the P-values provided by other six tests all reached the suggestive significance level (p &lt; 5 × 10−5). Regarding the computation time required for a genome-wide G × E analysis, SBERIA is the fastest method, followed by ADABF. Considering the validity, power performance, robustness, and computation time, ADABF is recommended for genome-wide G × E analyses

Noninjection Synthesis of CdS and Alloyed CdSxSe1−xNanocrystals Without Nucleation Initiators

CdS and alloyed CdSxSe1−x nanocrystals were prepared by a simple noninjection method without nucleation initiators. Oleic acid (OA) was used to stabilize the growth of the CdS nanocrystals. The size of the CdS nanocrystals can be tuned by changing the OA/Cd molar ratios. On the basis of the successful synthesis of CdS nanocrystals, alloyed CdSxSe1−x nanocrystals can also be prepared by simply replacing certain amount of S precursor with equal amount of Se precursor, verified by TEM, XRD, EDX as well as UV–Vis absorption analysis. The optical properties of the alloyed CdSxSe1−x nanocrystals can be tuned by adjusting the S/Se feed molar ratios. This synthetic approach developed is highly reproducible and can be readily scaled up for potential industrial production

Electrospun ZnO Nanowires as Gas Sensors for Ethanol Detection

ZnO nanowires were produced using an electrospinning method and used in gas sensors for the detection of ethanol at 220 °C. This electrospinning technique allows the direct placement of ZnO nanowires during their synthesis to bridge the sensor electrodes. An excellent sensitivity of nearly 90% was obtained at a low ethanol concentration of 10 ppm, and the rest obtained at higher ethanol concentrations, up to 600 ppm, all equal to or greater than 90%

Dietary Exposure to the Environmental Chemical, PFOS on the Diversity of Gut Microbiota, Associated With the Development of Metabolic Syndrome

The gut microbiome is a dynamic ecosystem formed by thousands of diverse bacterial species. This bacterial diversity is acquired early in life and shaped over time by a combination of multiple factors, including dietary exposure to distinct nutrients and xenobiotics. Alterations of the gut microbiota composition and associated metabolic activities in the gut are linked to various immune and metabolic diseases. The microbiota could potentially interact with xenobiotics in the gut environment as a result of their board enzymatic capacities and thereby affect the bioavailability and toxicity of the xenobiotics in enterohepatic circulation. Consequently, microbiome-xenobiotic interactions might affect host health. Here, we aimed to investigate the effects of dietary perfluorooctane sulfonic acid (PFOS) exposure on gut microbiota in adult mice and examine the induced changes in animal metabolic functions. In mice exposed to dietary PFOS for 7 weeks, body PFOS and lipid contents were measured, and to elucidate the effects of PFOS exposure, the metabolic functions of the animals were assessed using oral glucose-tolerance test and intraperitoneal insulin-tolerance and pyruvate-tolerance tests; moreover, on Day 50, cecal bacterial DNA was isolated and subject to 16S rDNA sequencing. Our results demonstrated that PFOS exposure caused metabolic disturbances in the animals, particularly in lipid and glucose metabolism, but did not substantially affect the diversity of gut bacterial species. However, marked modulations were detected in the abundance of metabolism-associated bacteria belonging to the phyla Firmicutes, Bacteroidetes, Proteobacteria, and Cyanobacteria, including, at different taxonomic levels, Turicibacteraceae, Turicibacterales, Turicibacter, Dehalobacteriaceae, Dehalobacterium, Allobaculum, Bacteroides acidifaciens, Alphaproteobacteria, and 4Cod-2/YS2. The results of PICRUSt analysis further indicated that PFOS exposure perturbed gut metabolism, inducing notable changes in the metabolism of amino acids (arginine, proline, lysine), methane, and a short-chain fatty acid (butanoate), all of which are metabolites widely recognized to be associated with inflammation and metabolic functions. Collectively, our study findings provide key information regarding the biological relevance of microbiome–xenobiotic interactions associated with the ecology of gut microbiota and animal energy metabolism