A weight-loss model based on baseline microbiota and genetic scores for selection of dietary treatments in overweight and obese population.

BACKGROUND & AIMS: The response to weight loss depends on the interindividual variability of determinants such as gut microbiota and genetics. The aim of this investigation was to develop an integrative model using microbiota and genetic information to prescribe the most suitable diet for a successful weight loss in individuals with excess of body weight. METHODS: A total of 190 Spanish overweight and obese participants were randomly assigned to two hypocaloric diets for 4 months: 61 women and 29 men followed a moderately high protein (MHP) diet, and 72 women and 28 men followed a low fat (LF) diet. Baseline fecal DNA was sequenced and used for the construction of four microbiota subscores associated with the percentage of BMI loss for each diet (MHP and LF) and for each sex. Bootstrapping techniques and multiple linear regression models were used for the selection of families, genera and species included in the subscores. Finally, two total microbiota scores were generated for each sex. Two genetic subscores previously reported to weight loss were used to generate a total genetic score. In an attempt to personalize the weight loss prescription, several linear mixed models that included interaction with diet between microbiota scores and genetic scores for both, men and women, were studied. RESULTS: The microbiota subscore for the women who followed the MHP-diet included Coprococcus, Dorea, Flavonifractor, Ruminococcus albus and Clostridium bolteaea. For LF-diet women, Cytophagaceae, Catabacteriaceae, Flammeovirgaceae, Rhodobacteriaceae, Clostridium-x1vb, Bacteriodes nordiiay, Alistipes senegalensis, Blautia wexlerae and Psedoflavonifractor phocaeensis. For MHP-diet men, Cytophagaceae, Acidaminococcaceae, Marinilabiliaceae, Bacteroidaceae, Fusicatenibacter, Odoribacter and Ruminococcus faecis; and for LF-men, Porphyromanadaceae, Intestinimonas, Bacteroides finegoldii and Clostridium bartlettii. The mixed models with microbiota scores facilitated the selection of diet in 72% of women and in 84% of men. The model including genetic information allows to select the type of diet in 84% and 73%, respectively. CONCLUSIONS: Decision algorithm models can help to select the most adequate type of weight loss diet according to microbiota and genetic information. CLINICAL TRIAL REGISTRY NUMBER: This trial was registered at www. CLINICALTRIALS: gov as NCT02737267 (https://clinicaltrials.gov/ct2/show/NCT02737267?term=NCT02737267&cond=obekit&draw=2&rank=1).

Midbrain microglia mediate a specific immunosuppressive response under inflammatory conditions.

BACKGROUND: Inflammation is a critical process for the progression of neuronal death in neurodegenerative disorders. Microglia play a central role in neuroinflammation and may affect neuron vulnerability. Next generation sequencing has shown the molecular heterogeneity of microglial cells; however, the variability in their response to pathological inputs remains unknown. METHODS: To determine the effect of an inflammatory stimulus on microglial cells, lipopolysaccharide (LPS) was administered peripherally to mice and the inflammatory status of the cortex, hippocampus, midbrain, and striatum was assessed. Microglial activation and interaction with the immune system were analyzed in single cell suspensions obtained from the different brain regions by fluorescence-activated cell sorting, next generation RNA sequencing, real-time PCR, and immunohistochemical techniques. Antigen-presenting properties of microglia were evaluated by the ability of isolated cells to induce a clonal expansion of CD4+ T cells purified from OT-II transgenic mice. RESULTS: Under steady-state conditions, the midbrain presented a high immune-alert state characterized by the presence of two unique microglial subpopulations, one expressing the major histocompatibility complex class II (MHC-II) and acting as antigen-presenting cells and another expressing the toll-like receptor 4 (TLR4), and by the presence of a higher proportion of infiltrating CD4+ T cells. This state was not detected in the cortex, hippocampus, or striatum. Systemic LPS administration induced a general increase in classic pro-inflammatory cytokines, in co-inhibitory programmed death ligand 1 (PD-L1), and in cytotoxic T lymphocyte antigen 4 (CTLA-4) receptors, as well as a decrease in infiltrating effector T cells in all brain regions. Interestingly, a specific immune-suppressive response was observed in the midbrain which was characterized by the downregulation of MHC-II microglial expression, the upregulation of the anti-inflammatory cytokines IL10 and TGFß, and the increase in infiltrating regulatory T cells. CONCLUSIONS: These data show that the midbrain presents a high immune-alert state under steady-state conditions that elicits a specific immune-suppressive response when exposed to an inflammatory stimulus. This specific inflammatory tone and response may have an impact in neuronal viability.

Interaction Among Sex, Aging, and Epigenetic Processes Concerning Visceral Fat, Insulin Resistance, and Dyslipidaemia.

The distribution of adipose tissue is influenced by gender and by age, shifting from subcutaneous to visceral depots with longevity, increasing the development of several aging-related diseases and manifestations such as obesity, metabolic syndrome, and insulin resistance. Epigenetics might have an important role in aging processes. The aim of this research was to investigate the interactions between aging and epigenetic processes and the role of visceral adipose tissue, insulin resistance, and dyslipidaemia. Two different study samples of 366 and 269 adult participants were analyzed. Anthropometric, biochemical (including the triglycerides-glucose (TyG) index), and blood pressure measurements were assessed following standardized methods. Body composition measurements by Dual-energy X-ray absorptiometry (DXA) were also performed for the second sample. Methylation data were assessed by Infinium Human Methylation BeadChip (Illumina) in peripheral white blood cells. Epigenetic age acceleration was calculated using the methods DNAmAge (AgeAcc) and GrimAge (AgeAccGrim). Age acceleration (AgeAccGrim) showed better correlations than AgeAcc with most of the measured variables (waist circumference, glucose, HOMA-IR, HDL-cholesterol, triglycerides, and TyG index) for the first sample. In the second sample, all the previous correlations were confirmed, except for HOMA-IR. In addition, many of the anthropometrical measurements assessed by DXA and C-reactive protein (CRP) were also statistically associated with AgeAccGrim. Associations separated by sex showed statistically significant correlations between AgeAccGrim and HDL-cholesterol or CRP in women, whereas, in men, the association was with visceral adipose tissue mass DXA, triglycerides and TyG index. Linear regression models (model 1 included visceral adipose tissue mass DXA and TyG index and model 2 included HDL-cholesterol and CRP) showed a significant association for men concerning visceral adipose tissue mass DXA and TyG index, while HDL-cholesterol and CRP were associated in women. Moreover, structural equation modeling showed that the TyG index was mediating the majority of the visceral adipose tissue mass action on age acceleration. Collectively, these findings showed that there are different mechanisms affecting epigenetic age acceleration depending on sex. The identified relationships between epigenetic age acceleration and disease markers will contribute to the understanding of the development of age-related diseases.

Evaluation of RETICs Glaucoma Diagnostic Calculators in Preperimetric Glaucoma.

PURPOSE: To evaluate two glaucoma diagnostic calculators (GDC) in a group of eyes with preperimetric glaucoma (PPG). METHODS: All eyes (n = 265) included in this study had ocular hypertension with normal visual fields (VFs) on repeated VF tests. PPG was defined as progression in the Guided Progression Analysis software from Cirrus-optical coherence tomography (GPA-OCT). Three PPG types were defined according to the GPA-OCT software as follows: (1) GPA-OCT with one or more red boxes in two or more columns; (2) GPA-OCT with two or more red boxes in two or more columns; and (3) GPA-OCT with two or more red boxes in two or more columns (definition 2), and in the last scan one or more red box in the RNFL average or quadrants. Nonparametric tests, areas under the receiver operating characteristic curve (AUC), and Bland-Altman tests were assessed. RESULTS: Definitions one, two, and three were met by 44 (16.6%), 29 (10.9%), and 11 (4.2%) eyes, respectively. The GDC indices (means ± standard deviations) were, respectively, 14.49 ± 21.55% and 26.06 ± 22.50% using the combined and quantitative GDC (P < 0.001) in all eyes. Both GDC showed higher glaucoma probability in the PPG group (P < 0.04; combined GDC AUCs, 0.720-0.833; quantitative GDC AUCs, 0.700-0.839). GDC values were higher (P < 0.01) with greater GPA progression. CONCLUSIONS: The values of both GDC were higher in the PPG group than the ocular hypertension group. The GDC were higher when more columns in the GPA software indicated progression. Both GDC showed a similar ability to detect PPG. TRANSLATIONAL RELEVANCE: These calculators facilitate diagnosis of PPG in ocular hypertensive eyes.

Phenotype and genotype predictors of BMI variability among European adults.

BACKGROUND/OBJECTIVE: Obesity is a complex and multifactorial disease resulting from the interactions among genetics, metabolic, behavioral, sociocultural and environmental factors. In this sense, the aim of the present study was to identify phenotype and genotype variables that could be relevant determinants of body mass index (BMI) variability. SUBJECTS/METHODS: In the present study, a total of 1050 subjects (798 females; 76%) were included. Least angle regression (LARS) analysis was used as regression model selection technique, where the dependent variable was BMI and the independent variables were age, sex, energy intake, physical activity level, and 16 polymorphisms previously related to obesity and lipid metabolism. RESULTS: The LARS analysis obtained the following formula for BMI explanation: (64.7 + 0.10 × age [years] + 0.42 × gender [0, men; 1, women] + -40.6 × physical activity [physical activity level] + 0.004 × energy intake [kcal] + 0.74 × rs9939609 [0 or 1-2 risk alleles] + -0.72 × rs1800206 [0 or 1-2 risk alleles] + -0.86 × rs1801282 [0 or 1-2 risk alleles] + 0.87 × rs429358 [0 or 1-2 risk alleles]. The multivariable regression model accounted for 21% of the phenotypic variance in BMI. The regression model was internally validated by the bootstrap method (r2 original data set = 0.208, mean r2 bootstrap data sets = 0.210). CONCLUSION: In conclusion, age, physical activity, energy intake and polymorphisms in FTO, APOE, PPARG and PPARA genes are significant predictors of the BMI trait.

Intraobserver and Interobserver Agreement of Structural and Functional Software Programs for Measuring Glaucoma Progression.

IMPORTANCE: It is important to evaluate intraobserver and interobserver agreement using visual field (VF) testing and optical coherence tomography (OCT) software in order to understand whether the use of this software is sufficient to detect glaucoma progression and to make decisions regarding its treatment. OBJECTIVE: To evaluate agreement in VF and OCT software among 5 glaucoma specialists. DESIGN, SETTING AND PARTICIPANTS: The printout pages from VF progression software and OCT progression software from 100 patients were randomized, and the 5 glaucoma specialists subjectively and independently evaluated them for glaucoma. Each image was classified as having no progression, questionable progression, or progression. The principal investigator classified the patients previously as without variability (normal) or with high variability among tests (difficult). Using both software, the specialists also evaluated whether the glaucoma damage had progressed and if treatment change was needed. One month later, the same observers reevaluated the patients in a different order to determine intraobserver reproducibility. MAIN OUTCOMES AND MEASURES: Intraobserver and interobserver agreement was estimated using κ statistics and Gwet second-order agreement coefficient. The agreement was compared with other factors. RESULTS: Of the 100 observed patients, half were male and all were white; the mean (SD) age was 69.7 (14.1) years. Intraobserver agreement was substantial to almost perfect for VF software (overall κ [95% CI], 0.59 [0.46-0.72] to 0.87 [0.79-0.96]) and similar for OCT software (overall κ [95% CI], 0.59 [0.46-0.71] to 0.85 [0.76-0.94]). Interobserver agreement among the 5 glaucoma specialists with the VF progression software was moderate (κ, 0.48; 95% CI, 0.41-0.55) and similar to OCT progression software (κ, 0.52; 95% CI, 0.44-0.59). Interobserver agreement was substantial in images classified as having no progression but only fair in those classified as having questionable glaucoma progression or glaucoma progression. Interobserver agreement was fair regarding questions about glaucoma progression (κ, 0.39; 95% CI, 0.32-0.48) and consideration about treatment changes (κ, 0.39; 95% CI, 0.32-0.48). The factors associated with agreement were the glaucoma stage and case difficulty. CONCLUSIONS AND RELEVANCE: There was substantial intraobserver agreement but moderate interobserver agreement among glaucoma specialists using 2 glaucoma progression software packages. These data suggest that these glaucoma progression software packages are insufficient to obtain high interobserver agreement in both devices except in patients with no progression. The low agreement regarding progression or treatment changes suggests that both software programs used in isolation are insufficient for decision making.

A Diagnostic Calculator for Detecting Glaucoma on the Basis of Retinal Nerve Fiber Layer, Optic Disc, and Retinal Ganglion Cell Analysis by Optical Coherence Tomography.

PURPOSE: The purpose of this study was to develop and validate a multivariate predictive model to detect glaucoma by using a combination of retinal nerve fiber layer (RNFL), retinal ganglion cell-inner plexiform (GCIPL), and optic disc parameters measured using spectral-domain optical coherence tomography (OCT). METHODS: Five hundred eyes from 500 participants and 187 eyes of another 187 participants were included in the study and validation groups, respectively. Patients with glaucoma were classified in five groups based on visual field damage. Sensitivity and specificity of all glaucoma OCT parameters were analyzed. Receiver operating characteristic curves (ROC) and areas under the ROC (AUC) were compared. Three predictive multivariate models (quantitative, qualitative, and combined) that used a combination of the best OCT parameters were constructed. A diagnostic calculator was created using the combined multivariate model. RESULTS: The best AUC parameters were: inferior RNFL, average RNFL, vertical cup/disc ratio, minimal GCIPL, and inferior-temporal GCIPL. Comparisons among the parameters did not show that the GCIPL parameters were better than those of the RNFL in early and advanced glaucoma. The highest AUC was in the combined predictive model (0.937; 95% confidence interval, 0.911-0.957) and was significantly (P = 0.0001) higher than the other isolated parameters considered in early and advanced glaucoma. The validation group displayed similar results to those of the study group. CONCLUSIONS: Best GCIPL, RNFL, and optic disc parameters showed a similar ability to detect glaucoma. The combined predictive formula improved the glaucoma detection compared to the best isolated parameters evaluated. The diagnostic calculator obtained good classification from participants in both the study and validation groups.

Lung cancer in patients with chronic obstructive pulmonary disease. Development and validation of the COPD Lung Cancer Screening Score.

RATIONALE: Patients with chronic obstructive pulmonary disease (COPD) are at high risk for lung cancer (LC) and represent a potential target to improve the diagnostic yield of screening programs. OBJECTIVES: To develop a predictive score for LC risk for patients with COPD. METHODS: The Pamplona International Early Lung Cancer Detection Program (P-IELCAP) and the Pittsburgh Lung Screening Study (PLuSS) databases were analyzed. Only patients with COPD on spirometry were included. By logistic regression we determined which factors were independently associated with LC in PLuSS and developed a COPD LC screening score (COPD-LUCSS) to be validated in P-IELCAP. MEASUREMENTS AND MAIN RESULTS: By regression analysis, age greater than 60, body mass index less than 25 kg/m(2), pack-years history greater than 60, and emphysema presence were independently associated with LC diagnosis and integrated into the COPD-LUCSS, which ranges from 0 to 10 points. Two COPD-LUCSS risk categories were proposed: low risk (scores 0-6) and high risk (scores 7-10). In comparison with low-risk patients, in both cohorts LC risk increased 3.5-fold in the high-risk category. CONCLUSIONS: The COPD-LUCSS is a good predictor of LC risk in patients with COPD participating in LC screening programs. Validation in two different populations adds strength to the findings.

Influence of examiner experience on the reproducibility of retinal nerve fiber thickness values using Cirrus and Stratus OCTs.

PURPOSE: The purpose of the study was to evaluate the influence of the examiner's experience on the reproducibility of retinal nerve fiber layer (RNFL) measurements obtained with Cirrus optical coherence tomography (OCT) and Stratus. METHODS: Fifty-one normal and glaucomatous eyes of 51 participants were included. Two examiners (1 novice, 1 experienced) obtained 2 scans using both OCTs. For quantitative measurements, Bland and Altman limits of agreement were evaluated. For qualitative classifications, κ coefficients were calculated. RESULTS: Signal strength was higher with Cirrus than with Stratus (P<0.05). Signal strength was higher in scans performed by the experienced examiner than in those carried out by the inexperienced examiner in Stratus but not in Cirrus. RNFL measurement differences between Cirrus and Stratus were influenced by the examiner for the inferior (P=0.02), superior (P<0.001), and temporal quadrants (P=0.009). The RNFL quantitative agreement of examiners was higher in Cirrus than in Stratus. The qualitative agreement (κ coefficients) of both examiners in the RNFL classification were almost perfect with Cirrus (in the average, superior, and inferior quadrants), and moderate with Stratus (only in average and inferior quadrant). CONCLUSIONS: The signal strength is independent of the examiner's experience in Cirrus but not in Stratus. RNFL measurements obtained by both examiners were more reproducible with Cirrus than with Stratus. The differences in RNFL measurements between both OCTs were related to the examiner's experience in all 3 quadrants. Agreement between operators in the RNFL classification was higher with Cirrus than Stratus.

Risks factors and regression model for risk calculation of anesthesiologic intervention in topical and intracameral cataract surgery.

PURPOSE: To determine risk factors for anesthesiologist intervention during routine cataract surgery performed with topical and intracameral anesthesia and establish a regression model to identify high-risk patients. SETTING: Department of Ophthalmology, Clínica Universidad de Navarra, Pamplona, Spain. DESIGN: Prospective case series. METHODS: After cataract surgery at an ambulatory surgical center, anesthesia personnel completed a questionnaire to determine adverse medical events and risk factors related to anesthesiologist intervention. A Poisson regression model was used to calculate the interventional risks. Bootstrapping was performed for internal model validation. RESULTS: Of the 1010 cases, 50 (4.95%) required anesthesiologist intervention. Univariate analysis identified an association between anesthesiologist intervention and hypertension (P<.001), psychiatric history (P=.002), initial systolic blood pressure (P<.001), surgical duration (P=.001), and diabetes (P=.018). Scores were obtained using the following proposed regression model equation: (-8.68 + 0.33 × sex [men, 0; women, 1] + -0.02 × age [years] + 0.68 × hypertensive history [no, 0; yes, 1] + 1.18 × psychiatric background [no, 0; yes, 1] + 0.04 × initial systolic blood pressure [mm Hg]). The area under the receiver-operating curve was 0.803 (95% confidence interval [CI], 0.721-0.886). The area under the curve found in the validation method was 0.813 (95% CI, 0.727-0.887). CONCLUSION: Hypertension was the main risk factor for anesthesiologist intervention. The regression model discriminated between patients at lower and higher risk for intraoperative intervention for monitored anesthesia care. The probability of anesthesiologist intervention was 11.7 times higher when the model obtained a high score. FINANCIAL DISCLOSURE: No author has a financial or proprietary interest in any material or method mentioned.

Misalignments in the retinal nerve fiber layer evaluation using cirrus high-definition optical coherence tomography.

PURPOSE: To evaluate the frequency and characteristics of misalignments (MAs) in the retinal nerve fiber layer (RNFL) analysis protocol of spectral-domain optical coherence tomography (Cirrus) and determine factors associated with MAs. METHODS: Three hundred eyes (162 normal and 138 glaucomatous eyes) were included in this cross-sectional study. The MAs were considered limited when they affected only part of the scan line, and complete (CMA) when they were observed in the entire scan line. A subgroup (153 cases) with repeated scans was analyzed to compare the RNFL thicknesses in the scans with and without CMAs. RESULTS: Two hundred ninety-nine limited MAs were found in 140 eyes (46.7%) and 151 CMAs were found in 91 eyes (30.3%). The frequency and number of CMAs were significantly related to age (P<0.05). Seventy-two CMAs were in the measurement ring in 48 eyes, more frequently in the 3 and 9-o'clock positions (P=0.001) and the horizontal quadrants (P=0.001). Among the repeated scans, the number of cases with CMAs was similar to the first scan (P=0.32). No significant differences were found in global or quadrant RNFL thickness between scans with and without CMAs. CONCLUSIONS: CMAs were present in the first or second scans in about 30% of cases and were related to older age. CMAs were more frequently in horizontal meridians and quadrants. No differences in RNFL thickness were found between scans with and without CMAs in the same patients. Scans with CMAs in the measurement ring can be considered in the RNFL evaluation.

Cytogenetic aberrations and their prognostic value in a series of 330 splenic marginal zone B-cell lymphomas: a multicenter study of the Splenic B-Cell Lymphoma Group.

We conducted a retrospective collaborative study to cytogenetically characterize splenic marginal zone lymphoma (SMZL) and ascertain the prognostic value of chromosomal aberrations. Of 330 cases, 72% displayed an aberrant karyotype, 53% were complex, and 29% had a single aberration. The predominant aberrations were gains of 3/3q and 12q, deletions of 7q and 6q and translocations involving 8q/1q/14q. CD5 expression was detected in 39 of 158 cases (25%). The cytogenetic makeup of the CD5(+) group differed significantly from that of the CD5(-) group. Cases with unmutated IGHV were significantly associated with deletions of 7q and TP53. A strong association was noted between usage of the IGVH1-2 and deletion 7q, 14q alterations, and abnormal karyotype. On univariate analysis, patients with more than or equal to 2 aberrations, 14q alterations, and TP53 deletions had the shortest survival; 7q deletion did not affect survival. On multivariate analysis, cytogenetic aberrations did not retain prognostic significance; the parameters negatively affecting survival were hemoglobin and age. In conclusion, the cytogenetic profile of SMZL is distinct from other B-cell lymphomas. Complexity of the karyotype, 14q aberrations, and TP53 deletions are poor prognostic indicators and may be considered together with other clinicobiologic parameters to ascertain the prognosis of SMZL.

Identification of peptide inhibitors of transforming growth factor beta 1 using a phage-displayed peptide library.

Pathologies such as liver fibrosis and scleroderma are characterized by harmful levels of transforming growth factor beta 1 (TGFbeta1). These levels could be neutralized if inhibitors of this cytokine were available. With this aim we searched for peptides with binding affinity for TGFbeta1 using a phage-displayed random 15-mer peptide library. Some peptides thus identified blocked activity of TGFbeta1 in vitro, as measured by their capacity to restore growth of Mv-1-Lu cells in presence of added TGFbeta1. Also, they inhibited TGFbeta1-dependent expression of collagen type I mRNA in liver of mice orally insulted with CCl(4). Intraperitoneal administration of 50 microg of peptide P17 (the most active 15-mer peptide, also referred to as P17(1-15)) inhibited expression of collagen type I mRNA by almost 100%. Interestingly, titration experiments showed that P17(1-12) (a peptide encompassing the first 12 amino acids of P17) was approximately four times more active than P17. These results suggest that both peptides, as well as others reported here, may be of therapeutic interest in processes requiring control of undesired high levels of TGFbeta1.