Sequence variants associating with urinary biomarkers

Urine dipstick tests are widely used in routine medical care to diagnose kidney and urinary tract and metabolic diseases. Several environmental factors are known to affect the test results, whereas the effects of genetic diversity are largely unknown. We tested 32.5 million sequence variants for association with urinary biomarkers in a set of 150 274 Icelanders with urine dipstick measurements. We detected 20 association signals, of which 14 are novel, associating with at least one of five clinical entities defined by the urine dipstick: glucosuria, ketonuria, proteinuria, hematuria and urine pH. These include three independent glucosuria variants at SLC5A2, the gene encoding the sodium-dependent glucose transporter (SGLT2), a protein targeted pharmacologically to increase urinary glucose excretion in the treatment of diabetes. Two variants associating with proteinuria are in LRP2 and CUBN, encoding the co-transporters megalin and cubilin, respectively, that mediate proximal tubule protein uptake. One of the hematuria-associated variants is a rare, previously unreported 2.5 kb exonic deletion in COL4A3. Of the four signals associated with urine pH, we note that the pH-increasing alleles of two variants (POU2AF1, WDR72) associate significantly with increased risk of kidney stones. Our results reveal that genetic factors affect variability in urinary biomarkers, in both a disease dependent and independent context

A framework for evolutionary systems biology

<p>Abstract</p> <p>Background</p> <p>Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.</p> <p>Results</p> <p>Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions <it>in silico</it>. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism.</p> <p>Conclusion</p> <p>EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.</p

Negative Impact of Disorders of Gut-Brain Interaction on Health-related Quality of Life: Results from the Rome Foundation Global Epidemiology Survey.

Background & aims This study, using the database from the Rome Foundation Global Epidemiology Survey, aimed to assess the differences in quality of life overall, and by age and sex, across individual disorders of gut-brain interaction (DGBI), gastrointestinal anatomical region(s), and number of overlapping DGBI. Methods Data were collected via the internet in 26 countries, using the Rome IV diagnostic questionnaire and a supplemental questionnaire including the Patient-Reported Outcomes Measurement Information Systems Global-10 quality of life measure. Factorial ANOVAs were used to explore physical and mental quality of life, adjusting for multiple comparisons. Results Among the 54,127 respondents, quality of life deteriorated significantly with increasing number of overlapping DGBI, with respondents reporting two or more DGBI having significantly poorer quality of life than those with only one DGBI or those without any DGBI. Males with DGBI reported better quality of life than females, and those aged ≥65 years old reported better quality of life than those <65 years. Age, sex, number of overlapping DGBI, somatization, anxiety, depression, and functional experiences (concern, embarrassment, or stress associated with bowel functioning) relating to DGBI, were significant predictors of poorer physical and mental quality of life. Conclusions This study is the most comprehensive assessment of quality of life to date in adults living with a DGBI. It provides a representative picture of DGBI impact on adults in the global adult population, and highlights the significant detrimental impact of living with a DGBI on quality of life