Antonio Miñarro

Soluble extracts from a lymphoblastoid cell line modulate simian immunodeficiency syndrome (SAIDS) evolution

Nineteen Macaca fascicularis monkeys were injected with SIV. They were subsequently divided into 5 groups. Four groups of 4 animals were injected with dialysable extracts (DLE) from a lymphoblastoid cell line which had been previously induced with DLE obtained either from the total lymphocyte population, or from the CD4 or CD8 subpopulations of mice immunized with SIV virus. The other three animals which constituted the control group received saline injections. The animals were kept under observation for a 108-day period, and the values of several biological parameters were compared in a multivariant statistical analysis. On the 108th day, the control group was significantly different from the other groups in the multivariant analysis. Furthermore, the CD4/CD8 ratio and the platelets and CD4 cell counts varied significantly between the groups in the univariant analysis. It is thus surmised that DLE obtained from CD8 cells or the total lymphocyte population of immunized animals may exert a modulating effect on the evolution of SAIDS.

A two-question tool to assess the risk of repeated falls in the elderly

Introduction Older adults’ perception of their own risk of fall has never been included into screening tools. The goal of this study was to evaluate the predictive validity of questions on subjects’ self-perception of their own risk of fall. Methods This prospective study was conducted on a probabilistic sample of 772 Spanish community-dwelling older adults, who were followed-up for a one year period. At a baseline visit, subjects were asked about their recent history of falls (question 1: “Have you fallen in the last 6 months?”), as well as on their perception of their own risk of fall by using two questions (question 2: “Do you think you may fall in the next few months?” possible answers: yes/no; question 3: “What is the probability that you fall in the next few months?” possible answers: low/intermediate/high). The follow-up consisted of quarterly telephone calls, where the number of falls occurred in that period was recorded. Results A short questionnaire built with questions 1 and 3 showed 70% sensitivity (95% CI: 56%-84%), 72% specificity (95% CI: 68%-76%) and 0.74 area under the ROC curve (95% CI: 0.66–0.82) for prediction of repeated falls in the subsequent year. Conclusions The estimation of one’s own risk of fall has predictive validity for the occurrence of repeated falls in older adults. A short questionnaire including a question on perception of one’s own risk of fall and a question on the recent history of falls had good predictive validity.

Searching for differential expression: a non-parametric approach

Microarray experiments are being widely used in medical and biological research. The main features of these studies are the large number of variables (genes) involved and the low number of replicates (arrays). It seems clear that the most appropriate models, when looking for detecting differences in gene expression are those that exploit the most useful information to compensate for the lack of replicates. On the other hand, the control of the error in the decision process plays an important role for the high number of simultaneous statistical tests (one for each gene), so that concepts such as the false discovery rate (FDR) take a special importance. One of the alternatives for the analysis of the data in these experiments is based on the calculation of statistics derived from modifications of the classical methods used in this type of problems (moderated-t, B-statistic). Nonparametric techniques have been also proposed [B. Efron, R. Tibshirani, J.D. Storey, and V. Tusher, Empirical Bayes analysis of a microarray experiment, J. Amer. Stat. Assoc. 96 (2001), pp. 1151–1160; W. Pan, J. Lin, and C.T. Le, A mixture model approach to detecting differentially expressed genes with microarray data, Funct. Integr. Genomics 3 (2003), pp. 117–124], allowing the analysis without assuming any prior condition about the distribution of the data, which make them especially suitable in such situations. This paper presents a new method to detect differentially expressed genes based on non-parametric density estimation by a class of functions that allow us to define a distance between individuals in the sample (characterized by the coordinates of the individual (gene) in the dual space tangent to the manifold of parameters) [A. Miñarro and J.M. Oller, Some remarks on the individuals-score distance and its applications to statistical inference, Qüestiió, 16 (1992), pp. 43–57]. From these distances, we designed the test to determine the rejection region based on the control of FDR.

Normal limits of home measured spatial gait parameters of the elderly population and their association with health variables

Gait studies in the elderly population have been always conducted in gait labs or spacious clinical facilities, which influence gait parameters, and also implies that the participants have to be able to move to these facilities. Indoors gait characteristics of the elderly population have been very little studied. In this study, we aim to define the normal limits of the spatial gait parameters of the elderly, when walking at home, and to analyze relationship existing between the spatial gait parameters to other health variables. For such purpose, we conducted a transversal study on a probabilistic sample of 431 Spanish community-dwelling older, in which the spatial gait parameters were recorded by using an ink footprints method. We found that the mean stride length indoors was 88.47 cm (SD:26.05 cm; mean CI95%:85.52–91.41 cm), and the mean step width was 10.34 cm (SD:4.37 cm; mean CI95%:9.84–10.83 cm). Stride length was shorter in women and the oldest group, and was significantly influenced by the strength, balance, and physical activity. Stride width was larger in the oldest group and mainly affected by balance. A composite parameter including width and normalized stride length was independent from sex, and strongly differentiated between age groups. This parameter was affected by strength.

Metabotypes of response to bariatric surgery independent of the magnitude of weight loss

Objective Bariatric surgery is considered the most efficient treatment for morbid obesity and its related diseases. However, its role as a metabolic modifier is not well understood. We aimed to determine biosignatures of response to bariatric surgery and elucidate short-term metabolic adaptations. Methods We used a LC- and FIA-ESI-MS/MS approach to quantify acylcarnitines, (lyso)phosphatidylcholines, sphingomyelins, amino acids, biogenic amines and hexoses in serum samples of subjects with morbid obesity (n = 39) before and 1, 3 and 6 months after bariatric surgery. K-means cluster analysis allowed to distinguish metabotypes of response to bariatric surgery. Results For the first time, global metabolic changes following bariatric surgery independent of the baseline health status of the subjects have been revealed. We identify two metabolic phenotypes (metabotypes) at the interval 6 months-baseline after surgery, which presented differences in the levels of compounds of urea metabolism, gluconeogenic precursors and (lyso)phospholipid particles. Clinically, metabotypes were different in terms of the degree of improvement in insulin resistance, cholesterol, low-density lipoproteins and uric acid independent of the magnitude of weight loss. Conclusions This study opens new perspectives and new hypotheses on the metabolic benefits of bariatric surgery and understanding of the biology of obesity and its associated diseases.

Untargeted Profiling of Concordant/Discordant Phenotypes of High Insulin Resistance and Obesity To Predict the Risk of Developing Diabetes

This study explores the metabolic profiles of concordant/discordant phenotypes of high insulin resistance (IR) and obesity. Through untargeted metabolomics (LC-ESI-QTOF-MS), we analyzed the fasting serum of subjects with high IR and/or obesity ( n = 64). An partial least-squares discriminant analysis with orthogonal signal correction followed by univariate statistics and enrichment analysis allowed exploration of these metabolic profiles. A multivariate regression method (LASSO) was used for variable selection and a predictive biomarker model to identify subjects with high IR regardless of obesity was built. Adrenic acid and a dyglyceride (DG) were shared by high IR and obesity. Uric and margaric acids, 14 DGs, ketocholesterol, and hydroxycorticosterone were unique to high IR, while arachidonic, hydroxyeicosatetraenoic (HETE), palmitoleic, triHETE, and glycocholic acids, HETE lactone, leukotriene B4, and two glutamyl-peptides to obesity. DGs and adrenic acid differed in concordant/discordant phenotypes, thereby revealing protective mechanisms against high IR also in obesity. A biomarker model formed by DGs, uric and adrenic acids presented a high predictive power to identify subjects with high IR [AUC 80.1% (68.9-91.4)]. These findings could become relevant for diabetes risk detection and unveil new potential targets in therapeutic treatments of IR, diabetes, and obesity. An independent validated cohort is needed to confirm these results.

Seasonal variations of changes in lipid and glucidic variables after bariatric surgery

ABSTRACT Seasonality is a phenomenon that is characterized by changes over the year in sleep, mood, behaviour, appetite and body weight. In humans, seasonal variations have been found in certain variables, such as lipid variables and body mass index. We hypothesize that this rhythm could influence the expected variation of the levels of biochemical variables in cases of body weight loss. Thus, the goal of this study was to observe whether the time of year in which bariatric surgery (BS) took place modulated the changes in several variables related to glucidic and lipid metabolism. Blood samples were obtained from 24 women and 10 men before BS and 1 and 3 months after BS. We calculated the percentage of variation that occurred for each individual and for each variable as a function of the time of the year. Data were adjusted to a 12-month period sinusoidal curve, with significance being set at p < 0.05. The results showed that almost all of the studied variables changed due to the BS according to a seasonal rhythm. Most of the variables showed a decrease that was most prominent in winter. In the cases of body mass index (BMI), adrenocorticotropin hormone (ACTH), and cortisol, the highest variation occurred in winter. Insulin and cholesterol in high-density lipoproteins (cHLD) variations were higher in springtime. Glucose variation showed a decrease after surgery with acrophase in summer-fall and plasminogen activator inhibitor-1 (PAI-1) and homeostatic model assessment-insulin resistance (HOMA-IR) in spring-summer. Ghrelin levels showed increases with a rhythm of variation with an acrophase in summer-fall. The seasonal rhythm found in this study fits nearly with the inverse of the endogenous circannual rhythm of the variables studied. The time of the year when the highest variation takes place is related to the circannual rhythm of the variable. The results agree with the manifestation of seasonal rhythm in human biochemical variables, which are reflected in the responses to weight loss after BS.