Rare and common genetic determinants of metabolic individuality and their effects on human health

Garrod’s concept of ‘chemical individuality’ has contributed to comprehension of the molecular origins of human diseases. Untargeted high-throughput metabolomic technologies provide an in-depth snapshot of human metabolism at scale. We studied the genetic architecture of the human plasma metabolome using 913 metabolites assayed in 19,994 individuals and identified 2,599 variant–metabolite associations (P < 1.25 × 10−11) within 330 genomic regions, with rare variants (minor allele frequency ≤ 1%) explaining 9.4% of associations. Jointly modeling metabolites in each region, we identified 423 regional, co-regulated, variant–metabolite clusters called genetically influenced metabotypes. We assigned causal genes for 62.4% of these genetically influenced metabotypes, providing new insights into fundamental metabolite physiology and clinical relevance, including metabolite-guided discovery of potential adverse drug effects (DPYD and SRD5A2). We show strong enrichment of inborn errors of metabolism-causing genes, with examples of metabolite associations and clinical phenotypes of non-pathogenic variant carriers matching characteristics of the inborn errors of metabolism. Systematic, phenotypic follow-up of metabolite-specific genetic scores revealed multiple potential etiological relationships

To hit or not to hit, that is the question -genome-wide structure-based druggability predictions for <i>pseudomonas aeruginosa </i>proteins

Pseudomonas aeruginosa is a Gram-negative bacterium known to cause opportunistic infections in immune-compromised or immunosuppressed individuals that often prove fatal. New drugs to combat this organism are therefore sought after. To this end, we subjected the gene products of predicted perturbative genes to structure-based druggability predictions using DrugPred. Making this approach suitable for large-scale predictions required the introduction of new methods for calculation of descriptors, development of a workflow to identify suitable pockets in homologous proteins and establishment of criteria to obtain valid druggability predictions based on homologs. We were able to identify 29 perturbative proteins of P. aeruginosa that may contain druggable pockets, including some of them with no or no drug-like inhibitors deposited in ChEMBL. These proteins form promising novel targets for drug discovery against P. aeruginosa

An evaluation of prescribing practices for community-acquired pneumonia (CAP) in Mongolia

BACKGROUND: Community-acquired pneumonia (CAP) is a significant cause of morbidity and mortality in all age groups worldwide. It may be classified as mild/moderate or severe, the latter usually requiring hospitalisation. Although, there are many studies reported in relation to CAP, there is relatively little known about the treatment of CAP and its antibiotic use in Mongolia. The study aim was to evaluate prescribing practices for the treatment of mild/moderate CAP in Mongolia with respect to national prescribing guidelines. METHODS: Written prescriptions with a written diagnosis of CAP included were collected prospectively and sequentially for ten weeks from a purposefully selected sample of community pharmacies in rural and urban areas of Mongolia. The data collected included the patient's age, gender, medication details, frequency and number of doses prescribed. Evaluation was with respect to the Mongolian Standard Treatment Guidelines (2005, 2008). Statistical differences between groups were tested using the Chi-squared and Fisher's exact tests.RESULTS: Prescriptions were collected from 22 pharmacies and represented the prescribing practices of 118 doctors. The study enrolled 394 (193 adults and 201 children) patients, with a median age for children of 2.0 years (range: 0.03-12) and adults of 33.0 years (range: 13--92).The most commonly prescribed drugs were amino penicillins, vitamins, and mucolytics, with the median number of drugs being three per prescription. Inappropriate drug selection was similar for adults (57.7%) and children (56.6%), and the major reason for an overall frequency of inappropriate prescribing for adults were 89.0% and for children 78.0%. Doctors in urban areas prescribed more inappropriate drugs than those in rural areas for both children and adults, p = .0014. The proportion of prescribed injections was 28.4% for adults and 9.0% for children, and for adults was significantly higher in urban areas. The prescribing standard for non-hospitalized patients in Mongolia states that injections should not be prescribed. CONCLUSIONS: The high level of inappropriate prescribing for mild/moderate CAP highlights the need to develop comprehensive and reliable procedures nationwide to improve prescribing practices in Mongolia

Rare and common genetic determinants of metabolic individuality and their effects on human health

Garrod’s concept of ‘chemical individuality’ has contributed to comprehension of the molecular origins of human diseases. Untargeted high-throughput metabolomic technologies provide an in-depth snapshot of human metabolism at scale. We studied the genetic architecture of the human plasma metabolome using 913 metabolites assayed in 19,994 individuals and identified 2,599 variant–metabolite associations (P < 1.25 × 10−11) within 330 genomic regions, with rare variants (minor allele frequency ≤ 1%) explaining 9.4% of associations. Jointly modeling metabolites in each region, we identified 423 regional, co-regulated, variant–metabolite clusters called genetically influenced metabotypes. We assigned causal genes for 62.4% of these genetically influenced metabotypes, providing new insights into fundamental metabolite physiology and clinical relevance, including metabolite-guided discovery of potential adverse drug effects (DPYD and SRD5A2). We show strong enrichment of inborn errors of metabolism-causing genes, with examples of metabolite associations and clinical phenotypes of non-pathogenic variant carriers matching characteristics of the inborn errors of metabolism. Systematic, phenotypic follow-up of metabolite-specific genetic scores revealed multiple potential etiological relationships

A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes

dentification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 x 10(-8)) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk variant discovery for DKD.Peer reviewe