Detecting multi-way epistasis in family-based association studies.

The era of genome-wide association studies (GWAS) has led to the discovery of numerous genetic variants associated with disease. Better understanding of whether these or other variants interact leading to differential risk compared with individual marker effects will increase our understanding of the genetic architecture of disease, which may be investigated using the family-based study design. We present M-TDT (the multi-locus transmission disequilibrium test), a tool for detecting family-based multi-locus multi-allelic effects for qualitative or quantitative traits, extended from the original transmission disequilibrium test (TDT). Tests to handle the comparison between additive and epistatic models, lack of independence between markers and multiple offspring are described. Performance of M-TDT is compared with a multifactor dimensionality reduction (MDR) approach designed for investigating families in the hypothesis-free genome-wide setting (the multifactor dimensionality reduction pedigree disequilibrium test, MDR-PDT). Other methods derived from the TDT or MDR to investigate genetic interaction in the family-based design are also discussed. The case of three independent biallelic loci is illustrated using simulations for one- to three-locus alternative hypotheses. M-TDT identified joint-locus effects and distinguished effectively between additive and epistatic models. We showed a practical example of M-TDT based on three genes already known to be implicated in malaria susceptibility. Our findings demonstrate the value of M-TDT in a hypothesis-driven context to test for multi-way epistasis underlying common disease etiology, whereas MDR-PDT-based methods are more appropriate in a hypothesis-free genome-wide setting.

Characterization of the major bacterial-fungal populations colonizing dandruff scalps in Shanghai, China, shows microbial disequilibrium.

Dandruff is a scalp disorder characterized by the formation of flaky white-yellowish scales due to an altered proliferation and differentiation status; a disrupted barrier function; a decrease in the level of hydration and of natural moisturizing factors (NMF) in the scalp, with a persistent and relapsing inflammatory condition. It was recently reported that an imbalance between bacterial and fungal species colonizing the scalp of French volunteers was associated with dandruff condition. The purpose of the present study was to analyze the major bacterial and fungal species present on the scalp surface of Chinese volunteers and to investigate possible region-related variation in the microbiota linked to dandruff condition. The data obtained from the Chinese populations were highly similar to those obtained in France, confirming that dandruff scalps are associated with a higher incidence of Malassezia restricta and Staphylococcal sp. The ratios of Malassezia to Propionibacterium and Propionibacterium to Staphylococcus were also significantly higher in the dandruff volunteers as compared to normal volunteers, suggesting that equilibrium between the major bacterial and fungal taxa found on the normal scalps is perturbed in the dandruff scalps. The main difference between the French and Shanghai subjects was in their Staphylococcal biota. The results obtained in China and in France suggest that targeting one particular Malassezia sp. by antifungals instead of using large spectrum antifungals and rebalancing the dandruff scalp microbiota could be common approach to improve dandruff condition in the two countries.

Drug sales data analysis for outbreak detection of infectious diseases: a systematic literature review.

BACKGROUND: This systematic literature review aimed to summarize evidence for the added value of drug sales data analysis for the surveillance of infectious diseases. METHODS: A search for relevant publications was conducted in Pubmed, Embase, Scopus, Cochrane Library, African Index Medicus and Lilacs databases. Retrieved studies were evaluated in terms of objectives, diseases studied, data sources, methodologies and performance for real-time surveillance. Most studies compared drug sales data to reference surveillance data using correlation measurements or indicators of outbreak detection performance (sensitivity, specificity, timeliness of the detection). RESULTS: We screened 3266 articles and included 27 in the review. Most studies focused on acute respiratory and gastroenteritis infections. Nineteen studies retrospectively compared drug sales data to reference clinical data, and significant correlations were observed in 17 of them. Four studies found that over-the-counter drug sales preceded clinical data in terms of incidence increase. Five studies developed and evaluated statistical algorithms for selecting drug groups to monitor specific diseases. Another three studies developed models to predict incidence increase from drug sales. CONCLUSIONS: Drug sales data analyses appear to be a useful tool for surveillance of gastrointestinal and respiratory disease, and OTC drugs have the potential for early outbreak detection. Their utility remains to be investigated for other diseases, in particular those poorly surveyed.

Taxon influence index: assessing taxon-induced incongruities in phylogenetic inference.

Understanding the evolutionary history of species is at the core of molecular evolution and is done using several inference methods. The critical issue is to quantify the uncertainty of the inference. The posterior probabilities in Bayesian phylogenetic inference and the bootstrap values in frequentist approaches measure the variability of the estimates due to the sampling of sites from genes and the sampling of genes from genomes. However, they do not measure the uncertainty due to taxon sampling. Taxa that experienced molecular homoplasy, recent selection, a spur of evolution, and so forth may disrupt the inference and cause incongruences in the estimated phylogeny. We define a taxon influence index to assess the influence of each taxon on the phylogeny. We found that although most taxa have a weak influence on the phylogeny, a small fraction of influential taxa strongly alter it even in clades only loosely related to them. We conclude that highly influential taxa should be given special attention and sampling them more thoroughly can lead to more dependable phylogenies.

High-spatial resolution epidemic surveillance of bacterial meningitis in the African meningitis belt in Burkina Faso.

Despite improved surveillance capacities and WHO recommendations for subdistrict analysis, routine epidemic surveillance of acute bacterial meningitis in the African meningitis belt remains largely limited to the district level. We evaluated the appropriateness and performance of analyses at higher spatial resolution. We used suspected meningitis surveillance data at health centre (HC) resolution from Burkina Faso from 14 health districts spanning years 2004-2014 and analysed them using spatio-temporal statistics and generative models. An operational analysis compared epidemic signals at district and HC-level using weekly incidence thresholds. Eighty-four percent (N = 98/116) of epidemic clusters spanned only one HC-week. Spatial propagation of epidemic clusters was mostly limited to 10-30 km. During the 2004-2009 (with serogroup A meningitis) and 2010-2014 (after serogroup A elimination) period, using weekly HC-level incidence thresholds of 100 and 50 per 100,000 respectively, we found a gain in epidemic detection and timeliness in 9 (41% of total) and 10 (67%), respectively, district years with at least one HC signal. Individual meningitis epidemics expanded little in space, suggesting that a health centre level analysis is most appropriate for epidemic surveillance. Epidemic surveillance could gain in precision and timeliness by higher spatial resolution. The optimal threshold should be defined depending on the current background incidence of bacterial meningitis.

Sex influence on muscle synergies in a ballistic force-velocity test during the delayed recovery phase after a graded endurance run.

The acute and delayed phases of the functional recovery pattern after running exercise have been studied mainly in men. However, it seems that women are less fatigable and/or recover faster than men, at least when tested in isometric condition. After a 20 km graded running race, the influence of sex on the delayed phase of recovery at 2-4 days was studied using a horizontal ballistic force-velocity test. Nine female and height male recreational runners performed maximal concentric push-offs at four load levels a week before the race (PRE), 2 and 4 days (D2 and D4) later. Ground reaction forces and surface electromyographic (EMG) activity from 8 major lower limb muscles were recorded. For each session, the mechanical force-velocity-power profile (i.e. theoretical maximal values of force ( F ¯ 0), velocity ( V ¯ 0), and power ( P ¯ max)) was computed. Mean EMG activity of each recorded muscle and muscle synergies (three for both men and women) were extracted. Independently of the testing sessions, men and women differed regarding the solicitation of the bi-articular thigh muscles (medial hamstring muscles and rectus femoris). At mid-push-off, female made use of more evenly distributed lower limb muscle activities than men. No fatigue effect was found for both sexes when looking at the mean ground reaction forces. However, the force-velocity profile varied by sex throughout the recovery: only men showed a decrease of both V ¯ 0 (p < 0.05) and P ¯ max (p < 0.01) at D2 compared to PRE. Vastus medialis activity was reduced for both men and women up to D4, but only male synergies were impacted at D2: the center of activity of the first and second synergies was reached later. This study suggests that women could recover earlier in a dynamic multi-joint task and that sex-specific organization of muscle synergies may have contributed to their different recovery times after such a race.

A real-world implementation of a nationwide, long-term monitoring program to assess the impact of agrochemicals and agricultural practices on biodiversity.

Biodiversity has undergone a major decline throughout recent decades, particularly in farmland. Agricultural practices are recognized to be an important pressure on farmland biodiversity, and pesticides are suspected to be one of the main causes of this decline in biodiversity. As part of the national plan for reduction of pesticides use (Ecophyto), the French ministry of agriculture launched the 500 ENI (nonintended effects) monitoring program in 2012 in order to assess the unintended effects of agricultural practices, including pesticide use, on biodiversity represented by several taxonomic groups of interest for farmers. This long-term program monitors the biodiversity of nontargeted species (earthworms, plants, coleoptera, and birds), together with a wide range of annual data on agricultural practices (crop rotation, soil tillage, weed control, fertilizers, chemical treatments, etc.). Other parameters (e.g., landscape and climatic characteristics) are also integrated as covariates during the analyses. This monitoring program is expected to improve our understanding of the relative contribution of the different drivers of population and community trends. Here, we present the experience of setting up the 500 ENI network for this ambitious and highly complex monitoring program, as well as the type of data it collects. The issue of data quality control and some first results are discussed. With the aim of being useful to readers who would like to set up similar monitoring schemes, we also address some questions that have arisen following the first five years of the implementation phase of the program.

Influence function for robust phylogenetic reconstructions.

Based on the computation of the influence function, a tool to measure the impact of each piece of sampled data on the statistical inference of a parameter, we propose to analyze the support of the maximum-likelihood (ML) tree for each site. We provide a new tool for filtering data sets (nucleotides, amino acids, and others) in the context of ML phylogenetic reconstructions. Because different sites support different phylogenic topologies in different ways, outlier sites, that is, sites with a very negative influence value, are important: they can drastically change the topology resulting from the statistical inference. Therefore, these outlier sites must be clearly identified and their effects accounted for before drawing biological conclusions from the inferred tree. A matrix containing 158 fungal terminals all belonging to Chytridiomycota, Zygomycota, and Glomeromycota is analyzed. We show that removing the strongest outlier from the analysis strikingly modifies the ML topology, with a loss of as many as 20% of the internal nodes. As a result, estimating the topology on the filtered data set results in a topology with enhanced bootstrap support. From this analysis, the polyphyletic status of the fungal phyla Chytridiomycota and Zygomycota is reinforced, suggesting the necessity of revisiting the systematics of these fungal groups. We show the ability of influence function to produce new evolution hypotheses.

Comparison of 3 methods of automated internal carotid segmentation in human brain PET studies: application to the estimation of arterial input function.

UNLABELLED: Quantitative brain (18)F-FDG PET studies often require the plasma time-activity curve (input function) for estimation of the cerebral metabolic rate of glucose (CMRglc). The gold standard for input function measurement is arterial blood sampling, which is invasive and time-consuming. Alternatively, input function can be estimated from dynamic images. This estimation often implies the use of manually placed regions of interest (ROIs) over cerebral vasculature, which is an operator-dependent and time-consuming task. The aim of our study was to compare 3 algorithms of image segmentation (local means analysis [LMA], soft-decision similar component analysis [SCA], and k-means) to automatically segment internal carotid arteries from dynamic (18)F-FDG brain studies. METHODS: The accuracy of automatic carotid segmentation algorithms was first tested using numeric phantoms of the human brain, by quantitatively assessing the overlap between the segmented carotids and the reference regions in the phantom. Then, the algorithm that yielded the best results was applied to data from 4 healthy volunteers, who underwent an (18)F-FDG dynamic 3-dimensional PET brain study. Concordance between manual and automatic ROIs, both uncorrected and after partial-volume effect and spillover correction, was first assessed. Linear regression was then used to compare manual versus automatic CMRglc values obtained using Patlak analysis. CMRglc values obtained by arterial sampling were used as a reference. RESULTS: In phantom studies, LMA was shown to be superior to the other segmentation algorithms. By visual inspection, volunteers' internal carotids segmented by LMA were anatomically relevant. No significant difference was found between ROI values obtained by manual and automatic segmentation, either uncorrected or corrected for partial-volume effect. Linear regression demonstrated excellent agreement between the manual and automatic image-derived CMRglc values (P < 0.0001), and both correlated well with the reference values obtained by plasma samples. CONCLUSION: The LMA segmentation algorithm allows accurate automatic delineation of internal carotids from dynamic PET brain studies. After correction for partial-volume effect, the main application would be the estimation of an image-derived input function.

Hierarchizing Determinants of Sick Leave: Insights From a Survey on Health and Well-being at the Workplace.

OBJECTIVE: We hierarchized a range of individual and occupational factors impacting the occurrence of very short (1-3 days), short (4 days to 1 month), or long-term (more than a month) sick leave spells. METHODS: Data were collected from a repeated cross-sectional survey conducted in the French private sector over the period 2011 to 2017. Fifty one sick leave determinants were ranked using a conditional random forest approach. RESULTS: The main determinants of long-term sick leaves were mainly health-related characteristics, such as perceived health, but also work-related covariates such as supervisor acknowledgment. On the contrary, very short-term spells were mainly defined by sociodemographic covariates. CONCLUSION: These results could be useful for devising appropriate actions to prevent against sick leave at the workplace, particularly long-term spells. Random forest approach is a promising approach for ranking correlated covariates from large datasets.

An integrative modeling approach to the age-performance relationship in mammals at the cellular scale.

Physical and cognitive performances change across lifespan. Studying cohorts of individuals in specific age ranges and athletic abilities remains essential in assessing the underlying physiological mechanisms that result in such a drop in performance. This decline is now viewed as a unique phenotypic biomarker and a hallmark of the aging process. The rates of decline are well documented for sets of traits such as running or swimming but only a limited number of studies have examined the developmental and senescent phases together. Moreover, the few attempts to do so are merely descriptive and do not include any meaningful biological features. Here we propose an averaged and deterministic model, based on cell population dynamics, replicative senescence and functionality loss. It describes the age-related change of performance in 17 time-series phenotypic traits, including human physical and cognitive skills, mouse lemur strength, greyhound and thoroughbred speed, and mouse activity. We demonstrate that the estimated age of peak performance occurs in the early part of life (20.5% ± 6.6% of the estimated lifespan) thus emphasizing the asymmetrical nature of the relationship. This model is an initial attempt to relate performance dynamics to cellular dynamics and will lead to more sophisticated models in the future.

Normalization for triple-target microarray experiments.

BACKGROUND: Most microarray studies are made using labelling with one or two dyes which allows the hybridization of one or two samples on the same slide. In such experiments, the most frequently used dyes are Cy3 and Cy5. Recent improvements in the technology (dye-labelling, scanner and, image analysis) allow hybridization up to four samples simultaneously. The two additional dyes are Alexa488 and Alexa494. The triple-target or four-target technology is very promising, since it allows more flexibility in the design of experiments, an increase in the statistical power when comparing gene expressions induced by different conditions and a scaled down number of slides. However, there have been few methods proposed for statistical analysis of such data. Moreover the lowess correction of the global dye effect is available for only two-color experiments, and even if its application can be derived, it does not allow simultaneous correction of the raw data. RESULTS: We propose a two-step normalization procedure for triple-target experiments. First the dye bleeding is evaluated and corrected if necessary. Then the signal in each channel is normalized using a generalized lowess procedure to correct a global dye bias. The normalization procedure is validated using triple-self experiments and by comparing the results of triple-target and two-color experiments. Although the focus is on triple-target microarrays, the proposed method can be used to normalize p differently labelled targets co-hybridized on a same array, for any value of p greater than 2. CONCLUSION: The proposed normalization procedure is effective: the technical biases are reduced, the number of false positives is under control in the analysis of differentially expressed genes, and the triple-target experiments are more powerful than the corresponding two-color experiments. There is room for improving the microarray experiments by simultaneously hybridizing more than two samples.

Biases induced by pooling samples in microarray experiments.

MOTIVATION: If there is insufficient RNA from the tissues under investigation from one organism, then it is common practice to pool RNA. An important question is to determine whether pooling introduces biases, which can lead to inaccurate results. In this article, we describe two biases related to pooling, from a theoretical as well as a practical point of view. RESULTS: We model and quantify the respective parts of the pooling bias due to the log transform as well as the bias due to biological averaging of the samples. We also evaluate the impact of the bias on the statistical differential analysis of Affymetrix data.

A novel method for measuring patients' adherence to insulin dosing guidelines: introducing indicators of adherence.

BACKGROUND: Diabetic type 1 patients are often advised to use dose adjustment guidelines to calculate their doses of insulin. Conventional methods of measuring patients' adherence are not applicable to these cases, because insulin doses are not determined in advance. We propose a method and a number of indicators to measure patients' conformance to these insulin dosing guidelines. METHODS: We used a database of logbooks of type 1 diabetic patients who participated in a summer camp. Patients used a guideline to calculate the doses of insulin lispro and glargine four times a day, and registered their injected doses in the database. We implemented the guideline in a computer system to calculate recommended doses. We then compared injected and recommended doses by using five indicators that we designed for this purpose: absolute agreement (AA): the two doses are the same; relative agreement (RA): there is a slight difference between them; extreme disagreement (ED): the administered and recommended doses are merely opposite; Under-treatment (UT) and over-treatment (OT): the injected dose is not enough or too high, respectively. We used weighted linear regression model to study the evolution of these indicators over time. RESULTS: We analyzed 1656 insulin doses injected by 28 patients during a three weeks camp. Overall indicator rates were AA = 45%, RA = 30%, ED = 2%, UT = 26% and OT = 30%. The highest rate of absolute agreement is obtained for insulin glargine (AA = 70%). One patient with alarming behavior (AA = 29%, RA = 24% and ED = 8%) was detected. The monitoring of these indicators over time revealed a crescendo curve of adherence rate which fitted well in a weighted linear model (slope = 0.85, significance = 0.002). This shows an improvement in the quality of therapeutic decision-making of patients during the camp. CONCLUSION: Our method allowed the measurement of patients' adherence to their insulin adjustment guidelines. The indicators that we introduced were capable of providing quantitative data on the quality of patients' decision-making for the studied population as a whole, for each individual patient, for all injections, and for each time of injection separately. They can be implemented in monitoring systems to detect non-adherent patients.

Design of a graphical and interactive interface for facilitating access to drug contraindications, cautions for use, interactions and adverse effects.

BACKGROUND: Drug iatrogeny is important but could be decreased if contraindications, cautions for use, drug interactions and adverse effects of drugs described in drug monographs were taken into account. However, the physician's time is limited during consultations, and this information is often not consulted. We describe here the design of "Mister VCM", a graphical interface based on the VCM graphical language, facilitating access to drug monographs. We also provide an assessment of the usability of this interface. METHODS: The "Mister VCM" interface was designed by dividing the screen into two parts: a graphical interactive one including VCM icons and synthetizing drug properties, a textual one presenting on demand drug monograph excerpts. The interface was evaluated over 11 volunteer general practitioners, trained in the use of "Mister VCM". They were asked to answer clinical questions related to fictitious randomly generated drug monographs, using a textual interface or "Mister VCM". When answering the questions, correctness of the responses and response time were recorded. RESULTS: "Mister VCM" is an interactive interface that displays VCM icons organized around an anatomical diagram of the human body with additional mental, etiological and physiological areas. Textual excerpts of the drug monograph can be displayed by clicking on the VCM icons. The interface can explicitly represent information implicit in the drug monograph, such as the absence of a given contraindication. Physicians made fewer errors with "Mister VCM" than with text (factor of 1.7; p = 0.034) and responded to questions 2.2 times faster (p < 0.001). The time gain with "Mister VCM" was greater for long monographs and questions with implicit replies. CONCLUSION: "Mister VCM" seems to be a promising interface for accessing drug monographs. Similar interfaces could be developed for other medical domains, such as electronic patient records.

An iconic language for the graphical representation of medical concepts.

BACKGROUND: Many medication errors are encountered in drug prescriptions, which would not occur if practitioners could remember the drug properties. They can refer to drug monographs to find these properties, however drug monographs are long and tedious to read during consultation. We propose a two-step approach for facilitating access to drug monographs. The first step, presented here, is the design of a graphical language, called VCM. METHODS: The VCM graphical language was designed using a small number of graphical primitives and combinatory rules. VCM was evaluated over 11 volunteer general practitioners to assess if the language is easy to learn, to understand and to use. Evaluators were asked to register their VCM training time, to indicate the meaning of VCM icons and sentences, and to answer clinical questions related to randomly generated drug monograph-like documents, supplied in text or VCM format. RESULTS: VCM can represent the various signs, diseases, physiological states, life habits, drugs and tests described in drug monographs. Grammatical rules make it possible to generate many icons by combining a small number of primitives and reusing simple icons to build more complex ones. Icons can be organized into simple sentences to express drug recommendations. Evaluation showed that VCM was learnt in 2 to 7 hours, that physicians understood 89% of the tested VCM icons, and that they answered correctly to 94% of questions using VCM (versus 88% using text, p = 0.003) and 1.8 times faster (p < 0.001). CONCLUSION: VCM can be learnt in a few hours and appears to be easy to read. It can now be used in a second step: the design of graphical interfaces facilitating access to drug monographs. It could also be used for broader applications, including the design of interfaces for consulting other types of medical document or medical data, or, very simply, to enrich medical texts.

Atmospheric Dust, Early Cases, and Localized Meningitis Epidemics in the African Meningitis Belt: An Analysis Using High Spatial Resolution Data.

BACKGROUND: Bacterial meningitis causes a high burden of disease in the African meningitis belt, with regular seasonal hyperendemicity and sporadic short, but intense, localized epidemics during the late dry season occurring at a small spatial scale [i.e., below the district level, in individual health centers (HCs)]. In addition, epidemic waves with larger geographic extent occur every 7-10 y. Although atmospheric dust load is thought to be an essential factor for hyperendemicity, its role for localized epidemics remains hypothetic. OBJECTIVES: Our goal was to evaluate the association of localized meningitis epidemics in HC catchment areas with the dust load and the occurrence of cases in the same population early in the dry season. METHODS: We compiled weekly reported cases of suspected bacterial meningitis at the HC resolution for 14 districts of Burkina Faso for the period 2004-2014. Using logistic regression, we evaluated the association of epidemic HC-weeks with atmospheric dust [approximated by the aerosol optical thickness (AOT) satellite product] and with the observation of early meningitis cases during October-December. RESULTS: Although AOT was strongly associated with epidemic HC-weeks in crude analyses across all HC-weeks during the meningitis season [odds ratio (OR) [Formula: see text]; 95% CI: 4.90, 9.50], the association was no longer apparent when controlling for calendar week (OR [Formula: see text]; 95% CI: 0.60, 1.50). The number of early meningitis cases reported during October-December was associated with epidemic HC-weeks in the same HC catchment area during January-May of the following year (OR for each additional early case [Formula: see text]; 95% CI: 1.06, 1.21). CONCLUSIONS: Spatial variations of atmospheric dust load do not seem to be a factor in the occurrence of localized meningitis epidemics, and the factor triggering them remains to be identified. The pathophysiological mechanism linking early cases to localized epidemics is not understood, but their occurrence and number of early cases could be an indicator for epidemic risk. https://doi.org/10.1289/EHP2752.

A constrained polynomial regression procedure for estimating the local False Discovery Rate.

BACKGROUND: In the context of genomic association studies, for which a large number of statistical tests are performed simultaneously, the local False Discovery Rate (lFDR), which quantifies the evidence of a specific gene association with a clinical or biological variable of interest, is a relevant criterion for taking into account the multiple testing problem. The lFDR not only allows an inference to be made for each gene through its specific value, but also an estimate of Benjamini-Hochberg's False Discovery Rate (FDR) for subsets of genes. RESULTS: In the framework of estimating procedures without any distributional assumption under the alternative hypothesis, a new and efficient procedure for estimating the lFDR is described. The results of a simulation study indicated good performances for the proposed estimator in comparison to four published ones. The five different procedures were applied to real datasets. CONCLUSION: A novel and efficient procedure for estimating lFDR was developed and evaluated.

Profiling at mRNA, protein, and metabolite levels reveals alterations in renal amino acid handling and glutathione metabolism in kidney tissue of Pept2-/- mice.

PEPT2 is an integral membrane protein in the apical membrane of renal epithelial cells that operates as a rheogenic transporter for di- and tripeptides and structurally related drugs. Its prime role is thought to be the reabsorption of filtered di- and tripeptides contributing to amino acid homeostasis. To elucidate the role of PEPT2 in renal amino acid metabolism we submitted kidney tissues of wild-type and a Pept2(-/-) mouse line to a comprehensive transcriptome, proteome and metabolome profiling and analyzed urinary amino acids and dipeptides. cDNA microarray analysis identified 147 differentially expressed transcripts in transporter-deficient animals, and proteome analysis by 2D-PAGE and MALDI-TOF-MS identified 37 differentially expressed proteins. Metabolite profiling by GC-MS revealed predominantly altered concentrations of amino acids and derivatives. Urinary excretion of amino acids demonstrated increased glycine and cysteine/cystine concentrations and dipeptides in urine were assessed by amino acid analysis of urine samples before and after in vitro dipeptidase digestion. Dipeptides constituted a noticeable fraction of urinary amino acids in Pept2(-/-) animals, only, and dipeptide-bound glycine and cystine were selectively increased in Pept2(-/-) urine samples. These findings were confirmed by a drastically increased excretion of cysteinyl-glycine (cys-gly). Urinary loss of cys-gly together with lower concentrations of cysteine, glycine, and oxoproline in kidney tissue and altered expression of mRNA and proteins involved in glutathione (GSH) metabolism suggests that PEPT2 is predominantly a system for reabsorption of cys-gly originating from GSH break-down, thus contributing to resynthesis of GSH.

Increased infiltration of macrophages in omental adipose tissue is associated with marked hepatic lesions in morbid human obesity.

In human obesity, white adipose tissue (WAT) is enriched in macrophages. How macrophage infiltration in WAT contributes to the complications of obesity is unknown. This study tested the hypothesis that recruitment of macrophages in omental WAT is associated with hepatic damage in obese patients. Paired biopsies of subcutaneous and omental WAT and a liver biopsy were collected during gastric surgery in 46 obese women and 9 obese men (BMI 47.9 +/- 0.93 kg/m(2)). The number of HAM56+ macrophages in WAT was quantified microscopically, and correlations with clinical and biological parameters and histological liver pathology were investigated. There were twice as many macrophages in omental as in subcutaneous WAT (P<0.0001). After adjustment for age, omental WAT macrophage infiltration was correlated to fasting glucose and insulin, quantitative insulin sensitivity check index, triglycerides, aspartate aminotransferase (AST), and gamma-glutamyltranspeptidase. We propose an easy equation to estimate the amount of macrophages in omental WAT. Increased macrophage accumulation specifically in omental WAT was associated with hepatic fibroinflammatory lesions (P=0.01). The best predictive model for the severity of hepatic damage includes adiponectinemia, AST, and omental WAT macrophages. These data suggest that the presence of macrophages in omental WAT participates in the cellular mechanisms favoring hepatic fibroinflammatory lesions in obese patients.