Alexithymia, a personality trait characterized by difficulties in emotional processing, has been associated with unhealthy behaviors and chronic medical conditions. This study aimed to further develop our understanding of this complex relationship by investigating whether alexithymia increases the risk of metabolic syndrome (MetS) in participants with obesity or overweight through the mediating role of binge eating (BE).A consecutive sample of 238 treatment-seeking patients with obesity or overweight were recruited. Alexithymia (TAS-20), binge eating symptoms (BES), body mass index (BMI), and depression and anxiety symptoms (HADS) were concurrently assessed.p < 0.01). Individual with MetS also had higher HADS, BES, and TAS-20 scores, particularly difficulty identifying and describing feelings. The structural equation modeling (SEM) analysis revealed that BES levels exerted a significant direct effect on MetS (p < 0.01), and that TAS-20 levels exerted a significant direct effect on BES (p < 0.01), anxiety (p < 0.001) and depression (p < 0.001). Moreover, psychological distress  indirectly affected MetS through the mediating effect of BES, and TAS-20 (p = 0.01) indirectly affected MetS through the mediating effect of HADS and BES. Finally, age had a significant direct effect on MetS (p < 0.001).Almost half of the participants met the criteria for MetS (44.12%). Compared to patients without MetS, those with MetS were older, had a longer duration of overweight, and had a higher BMI (Our findings indicate that alexithymia is a concurrent causative factor to the development of MetS through the mediating role of BE and psychological distress.Level III, case–control analytic study. Globally, both obesity and metabolic syndrome (MetS) are growing public health problems . The preMetS is a combination of clinical criteria including abdominal obesity, metabolic abnormalities (high levels of glycaemia and blood pressure), and altered lipid metabolism (high levels of triglycerides and cholesterol) (see Methods 2.2.2 below), and is considered a major risk factor for cardiovascular disease . MetS isBinge eating (BE) is one behavior that has been identified as clinically relevant for the development of combined obesity and MetS –13. BE iAlexithymia is a personality dimension that has been associated with an increased incidence of numerous physical illnesses. The association between alexithymia and physical ill health is complex, alexithymia may modulate illness severity, pre-dispose an individual, be a consequence of the illness, or may involve a complex combination of all of these roles . It is aPreviously published studies mainly focused on the association of alexithymic features with single risk factors or components of MetS. The severity of alexithymia may contribute indirectly to MetS by influencing some of its components, such as T2D and cardiovascular risk , 30. GivA sample of 297 treatment-seeking outpatients with obesity or overweight were consecutively enrolled at their first visit at the Obesity Centre at the University Clinical Hospital of Chieti . At intake subjects were first screened for medical conditions and their motivation to participate in the weight loss program. The weight loss program was characterized as an integrated approach including daily food intake monitoring, the promotion of a healthy lifestyle, behavioral modification of risk factors associated with eating behavior, and psychological counseling aimed at individual and interpersonal distress. To maximize the ecological validity of the sample, all adult outpatients from 18 to 70 years old with a Body Mass Index (BMI) ≥ 25 were invited to take part. Individuals were excluded if they self-reported a psychiatric or neurological disorder or the use of psychoactive substances in the past 10 years, were pregnant, were unable to complete the self-rating scales, or had documented or self-reported type 1 diabetes or any other endocrinological problem other than MetS.All subjects provided written informed consent to take part in the study. The study was reviewed and approved by the Ethics Committee of University G.d'Annunzio—Chieti-Pescara and carried out in accordance with the World Medical Association Declaration of Helsinki and its subsequent revisions .An ad hoc semi-structured interview was used to gather information on socio-demographic and clinical characteristics, such as age, gender, BMI, education level, marital status, and duration of overweight (years from the first dietary treatment), past and/or current psychopathological and neurologic symptoms, use of psychiatric medication, and experiences with psychotherapy. A BMI ≥ 30 was used as the cut-off for determining obesity and was analyzed as the ratio of weight in kilograms to the square of height in meters (kg/m2).In the present study, MetS was clinically defined using the NCEP–ATP III diagnostic criteria .According to the polythetic NCEP–ATP III criteria , MetS isThe Binge Eating Scale (BES) was used to assess the severity of BE behaviors . The BESThe self-report 20-item Toronto Alexithymia Scale (TAS-20) was used to measure Alexithymia . Each itDepressive and anxiety symptoms were measured using the Hospital Anxiety and Depression Scale (HADS) . The HADA 2-step strategy was used for data analysis.t test or chi-square test (χ2) and an analysis of variance (ANOVA) were used to compare between-group differences in socio-demographic and clinical variables for patients with or without MetS and BE. The standardized mean difference was used as a measure of effect size. A standardized effect size (Cohen’s d) of 0.20–0.50 is considered small, 0.50–0.80 moderate, and > 0.80 large [η2), a measure of effect size for ANOVA, was also used. A standardized effect size (η2) of 0.01–0.05 is considered small, 0.06–0.14 moderate, and > 0.14 large. Pearson’s correlation coefficient was used for the associations between socio-demographic, clinical and psychological variables.First, Student’s 80 large . The EtaSecond, Structural Equation Modeling (SEM) was used to evaluate the direct, indirect and total effects of alexithymia on MetS through the mediating role of BE, depression and anxiety symptoms. SEM is a set of statistical techniques used to measure and analyze the relationships of observed and latent variables. It examines linear causal relationships among variables, while simultaneously accounting for measurement error. Latent variables or factors are considered to represent theoretical constructs that can be interpreted as latent traits or “true” variables underlying the measured items. Observable variables or factors are variables that can be observed and directly measured .χ2) (p > 0.05), Root Mean Square Error of Approximation (RMSEA) close to 0.06 or less for a well-fitted model, Comparative Fit Index (CFI) near 0.90 or greater and Tucker–Lewis Index (TLI) near 0.90 or greater [SEM, with a maximum likelihood estimation method, was used to evaluate the fit of the hypothesized model based on the following criteria: chi-squared  were enrolled. The main reason for not participating was a lack of time. Included patients were mostly females (69.33%) and with a median age of 48 years. Most of the participants had graduated from high or secondary school (73.95%) and were married (74.14%). According to the polythetic NCEP–ATPIII criteria (see Methods 2.2.2), MetS was present in 44.12% of the sample.d = 0.39), duration of overweight (d = 0.68), and older age (d = 0.74). No other sociodemographic differences were found between the two groups. BE behaviors, alexithymia, and psychological distress showed significant between-group differences, with effect sizes in the small range. In particular, patients with MetS reported significantly higher BES (d = 0.26), TAS-20 (d = 0.43), DIF (d = 0.39), and DDF (d = 0.34) scores than patients without MetS. Moreover, patients with MetS showed significantly higher depression and anxiety symptoms (d = 0.28) than patients without MetS  than the other 3 groups and had a higher BMI (η2 = 0.04) and a longer duration of overweight (η2 = 0.13) than patients without MetS and BE. Patients without MetS and BE exhibited significantly lower TAS-20 scores than the other groups (η2 = 0.09), particularly lower DIF (η2 = 0.09). Patients with both MetS and BE had significantly higher TAS-20 (0.09) and DIF (0.09) scores than patients without MetS and BE, had significantly higher depression score (η2 = 0.07) than groups without BE, and significantly higher anxiety score (η2 = 0.07) than patients without MetS and without BE. Patients without MetS and with BE had a significantly higher TAS-20 (η2 = 0.09), DIF (η2 = 0.09), DDF (η2 = 0.06), and anxiety (η2 = 0.07) than patients without MetS and without BE  were found among variables. Alexithymia was significantly associated with psychological distress and BE. In particular, the TAS-20 total and the DIF subscale correlated higher with HADS-D  and at a lower level with HADS-A and BES scores (r = 0.30–0.35). The DDF subscale and BES also showed significant correlations with psychological distress within the same correlation range. The highest correlation coefficient occurred between age and the duration of overweight (r = 0.83) (see Table Multiple significant correlations in the moderate range r = 0.0–0.50 weβ = 0.15), whereas there were no significant direct effects of HADS-A and HADS-D . A significant direct effect of alexithymia was found on BE (β = 0.17), and depression (β = 0.50) and anxiety symptoms (β = 0.39). In addition, a significant direct effect of depression and anxiety symptoms  was found on BE. Finally, a significant direct effect of age as a covariate on MetS (β = 0.38), and a significant positive correlation between HADS-A and HADS-D were found . Put in more clinically bound words, results of SEM indicate that: (a) the higher the alexithymia level, the greater the increase of BE behaviors and psychological distress; (b) the higher the increase of psychological distress, the greater the increase of BE behaviors; and (c) the higher the BE behaviors, the greater the increase in MetS.Figure βindirect = 0.10, p = 0.01) on MetS through the mediation of BE behaviors and depression and anxiety symptoms. In addition, a positive and indirect effect of depression  and anxiety symptoms  was found on MetS through the mediation of BE behaviors , BE , and age  on MetS was significant, but there were no significant total effects of psychological distress on MetS. The values of multiple fit indices indicated that the proposed model provided a good fit of the data, χ2(183) = 314.227, p < 0.001, TLI = 0.90, CFI = 0.91, CD = 0.90, and RMSEA = 0.05.SEM showed positive and indirect effects of alexithymia , reported more behavioral patterns of BE, and were more psychologically distressed than those without MetS. These results are consistent with findings from previously published prospective studies on psychological factors and their co-occurrence with MetS and its components , 49. ForConsistent with the literature, our patients showed a close link between alexithymia and psychological symptoms . A substantial body of evidence indicates that alexithymia and affective symptoms largely overlap, and that it is difficult to disentangle the causative role played by either one of these overlapping factors . A numbeIn our third hypothesis, alexithymia was expected to indirectly affect MetS through the mediating role of BE behaviors and psychological distress. As expected, SEM analysis revealed that alexithymia affected MetS through the mediating role of BE, and depression and anxiety symptoms. This finding is in line with the results of our previous study that have emphasized the effect of alexithymic features on the severity of BE behaviors in patients with obesity . The preThere are several methodological limitations that require consideration when interpreting the findings of this study. First and foremost, a consecutive non‐probabilistic sampling method was used. Non-probabilistic recruitment can result in a biased sample that is not fully representative of the wider population. A probabilistic sampling procedure should, therefore, be utilized in future studies. Second, the cross‐sectional nature of the current study does not enable us to explore causal relationships between MetS, BE, and alexithymia. Prospective longitudinal studies should be used in the future to explore the timing and sequence of BE onset and various metabolic disruptions across the lifespan to tease apart these complex relationships. Third, alexithymia, psychological distress, and BE were only assessed using self-report scales. Self-reported scales require a considerable amount of personal insight and may be influenced by subjective biases and social desirability effects. Nonetheless, evidence indicates that the self-report TAS-20 is a valid and sound measure of alexithymia . The intWith these limitations in mind, the present findings indicate that alexithymia, particularly the facets of difficulty identifying and describing feelings, and BE have a relevant role in explaining the development of MetS in individuals with obesity or overweight, which may have important clinical implications. Clinicians should consider binge eating behavioral patterns and alexithymic characteristics in the clinical management of patients with MetS because these psychological aspects may influence the clinical presentation of the overall syndrome or its separate components. In addition, both alexithymia and BE can be modified through specific psychological interventions as well as integrated multicomponent treatment programs . ScreeniIn conclusion, we aimed to further explore the complex association between alexithymia and MetS by evaluating the mediating role of binge eating behavior and psychological distress. Our findings suggest that MetS is associated with distinct emotional and behavioral characteristics that require appropriate attention in the clinical management of patients.Overweight, obesity, and metabolic syndrome are an increasing global health challenge. Alexithymia has previously been associated with unhealthy behaviors and chronic medical conditions. Binge eating has not been considered as a co-variable in previous studies exploring the relationship of alexithymia with MetS. In this study, we aimed to explore the association between alexithymia and MetS by including maladaptive eating behavior and psychological distress as mediating factors.Binge eating and psychological distress mediate the relationship between alexithymia and MetS. Our findings suggest that MetS is associated with distinct emotional and behavioral characteristics that require appropriate attention in the clinical management of patients.


Apodemus flavicollis).Mammalian mandible and cranium are well-established model systems for studying canalization and developmental stability (DS) as two elements of developmental homeostasis. Nematode infections are usually acquired in early life and increase in intensity with age, while canalization and DS of rodent skulls could vary through late postnatal ontogeny. We aimed to estimate magnitudes and describe patterns of mandibular and cranial canalization and DS related to age and parasite intensity (diversity) in adult yellow-necked mice  decreased with age. We detected mandibular and cranial shape changes during postnatal ontogeny, but revealed no age-related dynamics of their covariance structure among and within individuals. Categories regarding parasitism differed in the level of canalization for cranial size and the level of DS for cranial shape. We observed differences in age-related dynamics of the level of canalization between non-parasitized and parasitized animals, as well as between yellow-necked mice parasitized by different number of nematode species. Likewise, individual measures of mandibular and cranial shape FA decreased with age for the mandible in the less parasitized category and increased for the cranium in the most parasitized category.Our age-related results partly agree with previous findings. However, no rodent study so far has explored age-related changes in the magnitude of FA for mandibular size or mandibular and cranial FA covariance structure. This is the first study dealing with the nematode parasitism-related canalization and DS in rodents. We showed that nematode parasitism does not affect mandibular and cranial shape variation and covariance structure among and within individuals. However, parasite intensity (diversity) is related to ontogenetic dynamics of the levels of canalization and DS. Overall, additional studies on animals from natural populations are required before drawing some general conclusions.The online version contains supplementary material available at 10.1186/s12983-021-00439-4. Developmentally and functionally complex morphological structures, such as mammalian mandible and cranium, are well-established model systems for studying canalization, developmental stability (DS), and morphological integration, recognized by Hallgrímsson et al.  as threeSymmetric traits in different individuals develop under different genetic and environmental conditions, whereas in the same individuals they share the same genome and experience the same environmental conditions , 9. TherThe factors that may disturb developmental homeostasis can be of environmental or genetic origin . TraditiMus musculus domesticus; Calomys expulsus) and rats , as well as rodents from wild populations. Laboratory-based studies delivered important knowledge regarding relations between magnitude/pattern of variation among and within individuals and environmental [Within rodents, canalization and DS of skull traits were explored using laboratory-bred mice  [Although numerous studies have reported a relationship between DS and parasite infections, reflected in increased levels of FA in host individuals , 17, 52,arandus) . Second,arandus) , 55. Thiarandus) , 56–58.Apodemus flavicollis Melchior, 1834), common in the Western Palearctic region, is abundantly distributed throughout the territory of Serbia. The nematode fauna of A. flavicollis is well documented in several European countries [A. flavicollis has been used as a model organism for various surveys of Bs in mammals [A. flavicollis found that Bs do not disturb developmental homeostasis in their carriers [A. flavicollis, Adnađević et al. [The yellow-necked mouse  and pattern (for shape) of variation among and within individuals were explored, and compared, separately across age categories and categories regarding parasitism.Our initial aim in the present study was to inspect canalization and DS of the mandible and cranium in relation to intestinal nematode parasitism in adult specimens of with age , 78, whiwith age , 35–37. With regards to the age-related dynamics of canalization and DS, and in line with previous findings in laboratory-reared rodents, we tested the following hypotheses: (1) Variance among individuals  will decrease with age, i.e. the highest levels of canalization for mandibular and cranial size and shape will be in the oldest yellow-necked mice; (2) There will be no change in the magnitude of shape variation within individuals through late ontogeny, i.e. we assume the absence of age-related dynamics of the levels of DS for mandibular and cranial shape; (3) Mandibular and cranial shape will differ across ontogenetic stages, as well as mandibular and cranial covariance structure among individuals. To the best of our knowledge, no rodent study has explored either changes in the magnitude of mandibular size variation within individuals through late ontogeny, or ontogenetic dynamics of mandibular and cranial FA covariance structure, so we could not make any predictions.A. flavicollis. Thus, we expect that parasitized animals possess lower levels of canalization  and DS  compared to non-parasitized yellow-necked mice; and (2) Infections by intestinal nematodes may be linked with the shape variation among individuals and the patterns of variation among and within individuals of A. flavicollis. Accordingly, we expect differences in the mandibular and cranial shape variation among individuals, as well as differences in mandibular and cranial patterns of canalization and DS, between different categories of parasitized animals.Regarding the relationship of nematode parasitism with canalization and DS, with no assumption of any of the three reasons proposed by Møller , we testApodemus flavicollis) were collected between 2011 and 2015 from 21 localities in Serbia  were identified using keys by Ryzhikov et al. [Yellow-necked mice  of left and right mandibles in the labial view and images (2272 × 1520 pixels resolution) of crania in the ventral view, supported by modeling clay with the palate positioned parallel to the photographic plane, were taken with a NIKON Coolpix 4500 digital camera by the same person (VJ). Mandibles are more fragile than crania and during cleaning and imaging some of them were damaged, particularly in the region of the coronoid process. As studies of mandibular fluctuating asymmetry (FA) require both intact mandibles (left and right), their sample size was smaller than sample size of crania. Using TpsDig software , 85, thePrior to digitizing 2D landmarks on mandibles, all images of left mandibles were reflected to right side to avoid a bias when locating landmarks on images of the left and right sides of biological structures . To asseA. flavicollis, Jovanović et al. [A. flavicollis, i.e. animals whose dry eye lens mass in mg was: ≤ 15 mg (A1 category), 15–25 mg (A2 category), and > 25 mg (A3 category) , we were in a rather difficult situation to separate effects of parasitism from the effects of aging on canalization and DS. Consequently, all the following analyses were performed separately for age categories and categories regarding parasitism.In an earlier study concerning sex ratio variation of intestinal nematode infrapopulations in ć et al.  distingus = 0.413; P < 0.05) and cranium  samples, indicating that parasite infection (parasite diversity) is higher in older animals. Additionally, we calculated body condition indices (BCI) as the residuals of linear regression of total body mass on standard length [3, 316 = 1.70, P = 0.1672), indicating that parasite diversity does not affect the body condition of animals.Spearman’s rank correlation coefficient revealed statistically significant relationship between categories regarding parasitism and age categories in both mandible  –91 to exSymmCS), while cranial among-individual size variance was calculated as the variance of CS (VarCS). To estimate the significance of differences in size variance among categories, Levene’s test was performed on absolute size differences .For mandibular and cranial size, the level of canalization was assessed by among-individual size variance , 23, 25.For mandibular size, the level of developmental stability (DS) was estimated by the level of size FA using FA10a index , 30. To In addition, to determine the association of individual measures of mandibular and cranial size variance and mandibular size FA with age, absolute size differences and asymmetric CS were regressed on dry eye lens mass (age) within the whole sample for age categories, as well as within each category regarding parasitism.Within each category, to eliminate the influence of allometry, all individuals were standardized to the mean CS for corresponding category using the Standard6b program . Subsequshape) was calculated for Procrustes distances (Pds), computed from the symmetric component of shape variation, based on the standard metric for variance. To assess the significance of the differences in shape variance among categories, Levene’s test was performed on these Pds.For mandibular and cranial shape, the level of canalization was estimated by among-individual shape variance , 23, 25.For mandibular and cranial shape, the level of DS was estimated by the level of shape FA using FA10a index of Palmer & Strobeck . To asseIn addition, to determine the association of individual measures of mandibular and cranial shape variance and FA with age, Pds and shape FA scores were regressed on dry eye lens mass (age) within the whole sample for age categories, as well as within each category regarding parasitism.Previously size-standardized datasets were combined in a single dataset and averaged by individual. To quantify the mean shape differences between categories in the symmetric component of shape variation , Pds were computed. To assess their statistical significance we used a permutation test (with 10 000 permutation runs) under the null hypothesis of equal category means, followed by Bonferroni adjustment. Afterward, principal component analysis (PCA) was performed on the covariance matrix of symmetric component of shape variation and displayed as a scatterplot of the first two principal components (PC1 and PC2) . TPS defTo test whether categories differ in the pattern of symmetric (Ind) and asymmetric (FA) shape variation, we compared the respective covariance matrices by matrix correlation. The significance of matrix correlation was obtained using the matrix permutation test with 10 000 iterations against the null hypothesis of complete dissimilarity between the respective covariance matrices , by permSpearman’s rank correlation, Kolmogorov–Smirnov and Levene’s tests, as well as ANOVA and regressions, were performed using Statistica v. 5.1 . All othParametric F-tests in ANOVAs of centroid size (CS) reveal that mandibular and cranial size variation among individuals, as well as directional asymmetry (DA) and fluctuating asymmetry (FA) for the mandible, are all highly significant in all age categories  for mandibular size and variance of CS (VarCS) for cranial size are the highest in A2 category, followed by A3 and A1 for the mandible and A1 and A3 for the cranium (Table j—SymmCSmean for the mandible and CSj—CSmean for the cranium) reveal no significant differences in size variance among age categories . Besides, regressions of absolute size differences on dry eye lens mass show no age-related changes in mandibular and cranial size variance .Both variance of symmetric CS . Moreover, regression of asymmetric CS versus dry eye lens mass indicates the absence of the association of individual measures of size FA with age .For mandibular size the level of FA (SizeFA10a index) is the highest in A3 and the lowest in A2 category  is the lowest in A1 and the highest in A3 category . However, regressions of Pds on dry eye lens mass are statistically significant  indicating their increase with age.For both mandible and cranium, among-individual shape variance . However, regression of mandibular Procrustes FA scores versus age is statistically significant  indicating their decline with age, while regression of cranial Procrustes FA scores versus age is not statistically significant .For mandibular shape the level of FA (ShapeFA10a index) is the highest in A1 and the lowest in A3 category, whereas for cranial shape the level of FA (ShapeFA10a index) is the highest in A3 and the lowest in A2 category  = 0.0362, P < 0.0001; Pd (A2 vs. A3) = 0.0109, P < 0.0001; cranium: Pd (A1 vs. A2) = 0.0206, P < 0.0001; Pd (A1 vs. A3) = 0.0309, P < 0.0001; Pd (A2 vs. A3) = 0.0109, P < 0.0001). As illustrated by scatterplots of the first two principal components (PC1 and PC2) for symmetric shape variation, age categories separate from each other along PC1 axis, although there is a larger overlap between A2 and A3 categories for the mandible than for the cranium  = 0.0280,  A1 vs. A = 0.0362For both mandible and cranium the patterns of symmetric (Ind) and asymmetric (FA) shape variation is similar between all age categories Table .Table 3CP = 0.0310. Additional effect of sex is significant in P3 category for the mandible and in P1 and P3 categories for the cranium. Effect of presence of B chromosomes (Bs) is significant only for the mandible within P1 category at P = 0.0353. Although significant, DA accounts for a fairly small percentage of the total mandibular size variation . Kolmogorov–Smirnov tests show that CS asymmetry is normally distributed, indicating the absence of antisymmetry in mandibular size within each category regarding parasitism.According to parametric F-tests in ANOVAs of centroid size (CS)  for mandibular size and variance of CS (VarCS) for cranial size are the highest in P1 category, followed by P2 and P0 categories, whereas the lowest values are observed in P3 category , Levene’s test performed on absolute size differences reveals statistically significant differences in cranial size variance . Besides, regressions of absolute size differences on dry eye lens mass show the absence of age-related changes in mandibular and cranial size variance in each category regarding parasitism, except in P0 category  where both mandibular and cranial size variance increased with age . Likewise, regressions of asymmetric CS versus age indicate the absence of the association of individual measures of size FA with age within each category regarding parasitism .For mandibular size the level of FA (SizeFA10a index) is the highest in P3 category, followed by P1 and P0 categories, while the lowest value of SizeFA10a index is observed in P2 category Table . Levene’As presented by parametric F-tests in Procrustes ANOVAs of shape  is the highest in P3 category, followed by P1 and P2 categories, whereas the lowest value is observed in P0 category . Regressions of Pds on dry eye lens mass show the absence of age-related changes in mandibular shape variance in each category regarding parasitism, except in P0 category  where mandibular shape variance increased with age  is the highest in P2 category, followed by the same values observed in P1 and P3 categories, whereas the lowest value is observed in P0 category . Regressions of Pds on dry eye lens mass show the absence of age-related changes in cranial shape variance in P0 and P3 categories, but its presence in P1  and P2  categories where cranial shape variance increased with age . Regressions of mandibular Procrustes FA scores versus age are statistically insignificant within each category regarding parasitism, except in P1 category  where shape FA scores decreased with age . Regressions of cranial Procrustes FA scores versus age are statistically insignificant within each category regarding parasitism, except in P3 category  where shape FA scores increased with age  is the highest in P0 category, followed by P1 and P3 categories, whereas the lowest value is observed in P2 category Table . Levene’age Fig. . Levene’P = 0.0123; non-significant after Bonferroni correction) and P2 vs. P3  for the mandible and P1 vs. P2 for the cranium , show statistically significant mean shape differences in symmetric component of shape variation (mandible: Pd (P0 vs. P1) = 0.0131, P < 0.0001; Pd (P0 vs. P2) = 0.0175, P < 0.0001; Pd (P0 vs. P3) = 0.0221, P < 0.0001; Pd (P1 vs. P3) = 0.0122, P = 0.0001; cranium: Pd (P0 vs. P1) = 0.0119, P < 0.0001; Pd (P0 vs. P2) = 0.0136, P < 0.0001; Pd (P0 vs. P3) = 0.0199, P < 0.0001; Pd (P1 vs. P3) = 0.0086 P < 0.0001; Pd (P2 vs. P3) = 0.0069, P < 0.0001). Scatterplots of the first two principal components (PC1 and PC2) for symmetric shape variation, demonstrate that for the mandible there is a complete overlap of specimens belonging to four categories regarding parasitism  and asymmetric (FA) shape variation is similar between all categories regarding parasitism Table .Table 5CApodemus flavicollis individuals does not decrease with age, indicating the absence of age-related changes in the level of canalization for mandibular and cranial size. This discrepancy from the previous examinations of laboratory-reared [In contrast to our prediction, mandibular and cranial size variance among y-reared , 25, 35,y-reared , that doA. flavicollis individuals with age, i.e. age-related decline of the level of canalization for mandibular and cranial shape. This result contradicts our prediction, as well as earlier findings of statistically significant reduction in skull shape variance among individuals in older groups of specimens in laboratory-raised rodents [A. flavicollis individuals observed in the oldest group, i.e. the reduction in the level of canalization for mandibular and cranial shape with age, could be explained by the fact that animals from natural populations, in contrast to those from laboratories, would be exposed to heterogeneous environmental conditions, and their diet would probably differ greatly from that of lab animals, as suggested by Willmore et al. [We detected statistically significant increase of both mandibular and cranial shape variance among  rodents , 36, 37. rodents . Inspect rodents  surveyede et al. . AccordiA. flavicollis intraindividual mandibular size variation (FA) is not statistically significant. Once again, the absence of differences in the level of DS for mandibular size among age categories may be a consequence of the absence of juveniles in the study sample. However, for mandibular shape, the level of DS increases with age, whereas for cranial shape there are no age-related changes in the level of DS. DS was found to decrease with age postnatally in both macaque and human crania [Age-related dynamics of the magnitude of n crania . Neverthn crania  documentn crania  reportedA. flavicollis point to the largest differences in the mean shape between A1 and A3, followed by A1 and A2, and the smallest ones between A2 and A3 categories. As evident from the PCA scatterplots of the first two principal components (PC1 and PC2) for symmetric shape variation, PC1 axis separates age categories. As expected, mandibular and cranial shape changes are most visible between the youngest and the oldest age groups, supporting the earlier findings in rodents [A. flavicollis specimens, are concordant with the ontogenetic mandibular shape variation in eight rodent species observed by Zelditch et al. [Sigmodon fulviventer) and house mouse (Mus musculus domesticus). Cranial shape changes between the youngest and the oldest groups, i.e. reduced basicranial region, but longer and narrower facial region in older A. flavicollis specimens, are in agreement with the common postnatal ontogenetic cranial shape changes in tetrapods [A. flavicollis are consistent with findings of postnatal ontogenetic cranial shape variation in the yellow-bellied marmot Marmota flaviventris [Dinaromys bogdanovi [Investigations of laboratory-reared mice and rats , 37, 100 rodents . Concernh et al. . These aetrapods , while civentris  and Martogdanovi .A. flavicollis individuals. Likewise, we detected no ontogenetic dynamics of covariance pattern within A. flavicollis individuals. Analyzing covariance structures from age to age in two rodent species, cotton rats (S. fulviventer) and house mice (M. m. domesticus), Zelditch et al. [A. flavicollis individuals.Contrary to our prediction, there is no age-related dynamics of covariance structure among h et al.  also assh et al.  found thA. flavicollis, we predicted the highest level of canalization in non-parasitized animals (P0 category). Disagreeing with our prediction, the most parasitized category (P3) was characterized by the highest level of canalization observed for mandibular and cranial size. Even though in P0 category the level of canalization for both mandibular and cranial shape is the highest as we expected, we observed no statistically significant differences in mandibular and cranial shape variance among analyzed categories regarding parasitism. In P0 category we detected statistically significant increase of mandibular size and shape variance and cranial size variance with age, indicating age-related decline of the level of canalization in non-parasitized animals. Age-related reduction in the level of canalization for cranial shape is detected in P1 and P2 categories. As concluded previously, age-related reduction in the level of canalization in wild compared to laboratory-reared animals could be explained by differences in environments animals from natural and captive habitats experience. Heterogeneous environmental conditions, particularly diverse diet, would result in increased phenotypic variation through late postnatal ontogeny in wild animals. As infections by parasites may be associated with host diet choice [Regarding the relationship of nematode parasitism with canalization for mandibular and cranial size and shape in t choice , differeA. flavicollis individuals (FA), inconsistent with our prediction, the level of DS for both mandibular size and shape is the highest in P2 category, while the level of DS for mandibular shape is the lowest in P0 category. These differences in the level of mandibular size and shape FA among categories regarding parasitism are not statistically significant. We found statistically significant differences in the level of FA for cranial shape among analyzed categories regarding parasitism. However, contradictory to our prediction, the level of DS for cranial shape is the highest in P2, followed by P0 and P3 category, and the lowest in P1 category. We detected statistically significant association of individual measures of mandibular and cranial shape FA with age. Namely, individual measures of mandibular and cranial shape FA significantly decreased with age for the mandible in the less parasitized category (P1) and increased for the cranium in the most parasitized category (P3). Observed ontogenetic trend in mandibular shape FA in P1 category correspond to that identified within the whole sample for age categories, i.e. the level of DS for mandibular shape increases with age. If parasites directly act on the developmental stability of their hosts by imposing on them a metabolic cost during their ontogeny [A. flavicollis is caused by parasitic disruption of host development and their direct effect on host DS, i.e. by the third reason proposed by Møller [Considering the magnitude of mandibular size and shape variation within ontogeny , 56, it ontogeny , 56–58. y Møller . It is ay Møller , 54, 55 y Møller –54. Bodyy Møller  and is iy Møller . Due to y Møller . Since py Møller , it wouly Møller .Discrepancy of the results related to the model systems (mandible/cranium) could be explained by possible trait-specific effects of environmental perturbations and developmental noise acting upon the level of canalization and DS, respectively. Different traits might be affected differently by the same conditions owing to different growth curves or different functions of the traits . MoreoveA. flavicollis individuals. Likewise, we reported the absence of statistically significant differences in the pattern of symmetric and asymmetric shape variation between non-parasitized and parasitized A. flavicollis specimens, as well as between yellow-necked mice parasitized by different number of nematode species, for both mandible and cranium. However, as we previously concluded, besides biological, methodological issues cannot be omitted as a possible reason for the failure to detect differences in covariance structures.Contradicting our prediction, infections by intestinal nematodes are not associated with mandibular and cranial shape variation among On a final note, advantages of laboratory-based studies over those that include animals from wild populations are obvious. Studies of experimental developmental biology use animals characterized by low levels of genetic variation, such as inbred mice and rats, and control environmental factors, whereas in natural populations multiple genetic and environmental determinants act on magnitude and pattern of morphological variation. On the other hand, development of a population developmental biology approach based on developmental stability study in natural populations is recognized by Zakharov et al.  as partiOur age-related results partly agree with previous findings in rodents. We observed the absence of age-related changes in the levels of canalization for mandibular and cranial size, but found age-related decline of the level of canalization for mandibular and cranial shape and age-related increase of the level of DS for mandibular shape. We detected mandibular and cranial shape changes during postnatal ontogeny, but revealed no age-related dynamics of mandibular and cranial covariance structure among individuals. However, no rodent study so far has explored age-related changes in the magnitude of FA for mandibular size or mandibular and cranial FA covariance structure. We found the absence of age-related changes in the level of DS for mandibular size. Likewise, we detected no age-related dynamics of mandibular and cranial FA covariance structure.A. flavicollis may be caused by parasitic disruption of host development and their direct effect on host DS or the most parasitized animals may be more susceptible to parasitism. Discrepancy of the results related to the model systems (mandible/cranium) could be explained by trait-specific effects of environmental perturbations and developmental noise acting upon the level of canalization and DS, respectively. Mandibular and cranial shape variation and covariance structure among and within individuals are not affected by the nematode parasitism.This is the first study dealing with the nematode parasitism-related canalization and DS in rodents. We found that categories regarding parasitism differ in the level of canalization for cranial size and the level of DS for cranial shape. We observed differences in age-related dynamics of the level of canalization between non-parasitized and parasitized animals, as well as between yellow-necked mice parasitized by different number of nematode species. As infections by parasites may be associated with host diet choice, these differences between categories regarding parasitism may be related to potential diet differences between them. Individual measures of mandibular and cranial shape FA decreased with age for the mandible in the less parasitized category and increased for the cranium in the most parasitized category. Detected relationship between cranial shape DS and nematode infections in Overall, additional studies concerning both age- and nematode parasitism-related canalization and DS of rodent skulls, particularly those from natural populations, are required before drawing some general conclusions.Additional file 1. Table S1 Anatomical definitions of landmarks recorded on the labial view of the mandible and the ventral surface of the cranium of the yellow-necked field mouse (Apodemus flavicollis)Additional file 2. Table S2 ANOVAs of centroid size (CS). % total—percentage of the total size variation. Age categories: A1—first age category, A2—second age category, A3—third age categoryAdditional file 3. Table S3 Procrustes ANOVAs of shape. % total—percentage of the total shape variation. Age categories: A1—first age category, A2—second age category, A3—third age categoryAdditional file 4. Table S4 ANOVAs of centroid size (CS). % total—percentage of the total size variation. Categories regarding parasitism: P0—non-parasitized animals, P1—animals parasitized by one nematode species, P2—animals parasitized by two nematode species, P3—animals parasitized by three to five nematode speciesAdditional file 5. Table S5 Procrustes ANOVAs of shape. % total—percentage of the total shape variation. Categories regarding parasitism: P0—non-parasitized animals, P1—animals parasitized by one nematode species, P2—animals parasitized by two nematode species, P3—animals parasitized by three to five nematode species


In Tibet, the two most important breeds are Tibetan chicken and Lhasa white chicken, and the duo exhibit specific adaptations to the high altitude thereby supplying proteins for humans living in the plateau. These breeds are partly included in the conservation plans because they represent important chicken genetic resources. However, the genetic diversity of these chickens is rarely investigated. Based on whole-genome sequencing data of 113 chickens from 4 populations of Tibetan chicken including Shigatse (SH), Nyemo (NM), Dagze (DZ) and Nyingchi (LZ), as well as Lhasa white (LW) chicken breed, we investigated the genetic diversity of these chicken breeds by genetic differentiation, run of homozygosity (ROH), genomic inbreeding and selection signature analyses.ROH) of 0.11 was observed in LZ. In other populations, the FROH ranged from 0.04 to 0.06. In total, 74, 111, 62, 42 and 54 ROH islands containing SNPs ranked top 1% for concurrency were identified in SH, NM, DZ, LZ and LW, respectively. Genes common to the ROH islands in the five populations included BDNF, CCDC34, LGR4, LIN7C, GLS, LOC101747789, MYO1B, STAT1 and STAT4. This suggested their essential roles in adaptation of the chickens. We also identified a common candidate genomic region harboring AMY2A, NTNG1 and VAV3 genes in all populations. These genes had been implicated in digestion, neurite growth and high-altitude adaptation.Our results revealed high genetic diversity across the five chicken populations. The linkage disequilibrium decay was highest in LZ, while subtle genetic differentiation was found between LZ and other populations (Fst ranging from 0.05 to 0.10). Furthermore, the highest ROH-based inbreeding estimate (FHigh genetic diversity is observed in Tibetan native chickens. Inbreeding is more intense in the Nyingchi population which is also genetically distant from other chicken populations. Candidate genes in ROH islands are likely to be the drivers of adaptation to high altitude exhibited by the five Tibetan native chicken populations. Our findings contribute to the understanding of genetic diversity offer valuable insights for the genetic mechanism of adaptation, and provide veritable tools that can help in the design and implementation of breeding and conservation strategies for Tibetan native chickens.The online version contains supplementary material available at 10.1186/s12864-021-08280-z. The Tibetan plateau is the largest high-altitude area on earth with an average altitude exceeding 4000 m, representing 25% of the landmass of China. This high-altitude environment becomes a habitat for many unique animal genetic resources. Tibetan chicken is one of the chicken breeds found in this area dating back to the seventh century A.C . The chiThe availability of high-throughput affordable sequencing techniques has allowed genome-wide analysis of the genetic structure and relationships in animal populations. Large scale omics data have opened new perspectives for a more accurate animal genetic analysis. In addition to SNP and gene expression data, runs of homozygosity (ROH) has joined the assembly of omics data available in biological databases for livestock gene discovery and diversity assessment. ROH is a kind of long continuous homozygous stretches in the genome that are formed by the combination of two identical haplotypes in an individual . These rIn chickens, analysis of ROH has been deployed to assess the genome-wide diversity in local and imported genetic resources. Results from such analysis help in the design and review of effective conservation program for endangered populations –13. The Within-breed diversity and the population structure analyses in livestock species are fundamental for understanding environmental adaptation, implementing conservation programs and designing selection plans , 17, 18.2 values were 0.08, 0.07, 0.08, 0.20 and 0.09 for SH, NM, DZ, LZ and LW populations, respectively. This indicated a stronger LD between SNPs and a clear difference in LZ compared to the other four chicken populations. Furthermore, the analysis of population relatedness (Table SThe genetic diversity for Shigatse (SH), Neymo (NM), Dagze (DZ), Nyingchi (LZ) and Lhasa white (LW) chicken populations was evaluated by observed heterozygosity (Ho), expected heterozygosity (He) and multiple-locus heterozygosity (MLH) using eligible SNPs under Hardy–Weinberg equilibrium. Ignoring the minor allele frequency (MAF) of SNPs, the Ho ranged from 0.15 to 0.18. Using filtered SNPs with MAF ≥ 5%, Ho increased ranging from 0.27 to 0.31. The estimates of He were similar to Ho for each population. MLH ranged from 0.22 to 0.31 when all SNPs were used, and it went up from 0.27 to 0.31 when only SNPs with MAF ≥ 5% were used. The MAF ranged from 0.11 to 0.13 when its filter was set at 0, and it went up from 0.21 to 0.22 when only SNPs with MAF ≥ 5% were used. The diversity indices of the five populations were shown in Table The current study identified 1269, 2438, 1366, 1284 and 1342 ROHs in SH, NM, DZ, LZ and LW chicken population, respectively. ROHs were identified in each sampled bird. Population-wise, the average number of ROH segments was highest in the LZ (128.4 ROH/bird) compared to the other populations. The lowest and highest average length of ROHs were observed in DZ (54.64 Mb) and LZ (102.54 Mb), respectively. The number of SNPs harbored in the ROHs varied between the studied populations, and the maximum number  was located on GGA1 of the SH population. Similarly, the minimum number of SNPs in the ROHs (50) was located on GGA1 found in the LZ chicken population (Table ROH), genomic SNP-by-SNP inbreeding coefficient (FGRM), excess of homozygosity (FHOM) and correlation between uniting gametes (FUNI). As shown in Fig. ROH (0.110 ± 0.016) and low FHOM (− 0.029 ± 0.055), low FGRM (− 0.027 ± 0.046) and low FUNI (− 0.027 ± 0.052). We further analyzed the correlation among the four inbreeding coefficients which was 0.55 between FROH and FHOM, 0.51 between FROH and FUNI, 0.91 between FHOM and FUNI, 0.39 between FGRM and FUNI, respectively  that harbored signatures of selection in SH, NM, LZ and LW population, respectively. Further mining of this region revealed that only three genes  were located within it. The information of ROH islands, SNPs and genes harbored within the studied region were listed in Table Notably, the genomic region containing common QTLs spanned from 0.03 Mb to 1.13 Mb of GGA8, and harbored six top 0.1% ROH islands across the five populations. By focusing on GGA8, we calculated integrated haplotype homozygosity (iHS) for each population. In all the populations except for the DZ population, SNPs harbored in the top 0.1% ROH islands were strongly selected for Fig. , and theThis study used whole genome sequences of four Tibetan chicken populations reared on the Tibetan plateau to analyze genetic diversity, run of homozygosity, genomic inbreeding and selection signatures. A composite Tibetan local breed, Lhasa white was also included in the analyses to compare results among populations. Lhasa white is a synthetic breed generated by crossing male White Leghorn and female Tibetan chickens, which has been reared for over sixty years on the Tibetan plateau.Observed (Ho) and expected (He) heterozygosity values for SNPs with MAF ≥ 0.05 close to 0.3 were found in all populations. Similar values were reported in modern chicken populations using sequence data  but loweROH), genomic SNP-by-SNP inbreeding coefficient (FGRM), excess of homozygosity (FHOM) and correlation between uniting gametes (FUNI) were commonly accepted indicators for inbreeding assessment [ROH and FHOM, as well as FUNI were significantly high, similar to those reported in cattle [ROH as an accurate estimate of identity by descent (IBD).In our present study, the number and the distribution of ROHs identified in Tibetan native chickens were comparable to those reported in broiler chickens . Furthersessment . Herein,sessment , but mucsessment , 16 and sessment . Therefon cattle , pigs [2n cattle , horses n cattle  and moden cattle . This fuLGR4), enriched in the biological process of osteoblast in GO database, contributes to the regulation of energy metabolism including food intake and energy expenditure [BDNF), enriched in the positive regulation of synapse assembly is considered important for the temperature perception in chickens [STAT1 and STAT4 are members of Janus kinase (JAK)-signal transducer and activators of transcription (STAT) pathway that plays critical roles in facilitating various cellular reactions to cellular stress including hypoxia, ultraviolet light and hyperosmolarity [VAV3, NOS2, COL3A1 and PRKD1 were putative candidate genes associated with highland adaptation [Whole-genome sequencing allows detection of the ROH and its analysis enables reliable inference of the demographic history of animal populations. It also provides a new approach for the exploration and discovery of complex traits . The ROHenditure . Brain-dchickens . In ratschickens . STAT1 amolarity . Moreovemolarity , suggestaptation , implyinAMY2A, NTNG1 and VAV3 genes on GGA8. AMY2A encodes a member of the alpha-amylase family of proteins, which is involved in carbohydrates and glycogen metabolism, affecting growth, carcass traits and feed intake efficiency in chicken [AMY2A was under selection for metabolism, energy availability and response to thermal stress in African chickens [NTNG1 is a responsible gene for axon and neurite growth [VAV3 is a member of the VAV gene family that plays vital role as guanosine nucleotide exchange factors for Rho GTPases and signaling adaptors downstream of protein tyrosine kinases [VAV3 had been identified as a candidate gene associated with highland adaptation in Ethiopians [VAV3 also functions putatively in the adaptation to the high altitude of Tibetan native chicken. Given that different chicken populations were reared in the Tibetan plateau for many decades, we speculated that this genomic region and the candidate genes on GGA8 might be under natural or artificial selection for adaptation to the high-altitude environment.ROH islands might be the representative genomic regions under natural and artificial selection . The iHS chicken . The prechickens . Similare growth . It was e growth . VAV3 is kinases . Specifihiopians  and Ethihiopians . This prhiopians . We therAMY2A, NTNG1 and VAV3. This region is suggested as a candidate genomic region for adaptation to the high-altitude environment, which should be further validated in the following studies. Our findings contribute to the understanding of genetic diversity, population inbreeding and the underlying genetic mechanism of the high-altitude adaptation, and may help in the design and implementation of breeding and conservation strategies for the chickens.In the present study, we used whole genome sequence data to characterize the genetic diversity and investigate the distribution of ROH across the genomes of five Tibetan indigenous chicken populations. Different LD, diversity and ROH patterns were observed in the five populations. Genetic diversity evaluated by observed heterozygosity was high in the five populations. The Nyingchi (LZ) population, which was distant from other populations had the highest proportion of long ROH fragments and ROH-based genomic inbreeding coefficient, reflecting recent inbreeding events. We identified a total of 343 ROH islands harboring 112 QTLs and 1429 genes. Five of such genes were involved in energy metabolism and STATs pathway. Specifically, ROH islands on GGA8 harbored genes including All birds were handled following the guidelines established by the Council for Animal Welfare of China. The experimental protocols were approved by the Science Research Department of the Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS).p-value < 10− 5. After these quality control steps, a total of 20,385,015 SNPs distributed across 33 autosomes in 105 birds were obtained for subsequent analyses. Among these birds, 20, 32, 25, 10 and 18 belonged to Shigatse, Nyemo, Dagze, Nyingchi and Lhasa white population, respectively.Genomic DNA was extracted from the blood of 114 female chickens. After purification and integrity verification of the DNA, whole-genome sequencing was performed using the Illumina HiSeq 2500 Sequencer  to generate 150 bp paired-end reads. To minimize mapping errors, low-quality reads were removed using FastQC software following Yan et al. . The cle2 threshold of 0.2. Principal components (PC) analysis was carried out with the pruned data in PLINK, and the first 2 PCs were extracted and plotted using R software. The observed heterozygosity (Ho) and the expected heterozygosity (He) were estimated based on allele frequency of all eligible SNPs, SNPs with minor allele frequency (MAF) ≥0.01 and SNPs with MAF ≥ 0.05, respectively, using ‘-hardy’ option in PLINK. Multiple-locus heterozygosity (MLH) was also calculated for each bird with formula O is the number of observed homozygotes, and N is the number of non-missing autosomal SNPs. The O and N were calculated using ‘-het’ option in PLINK. Further, PopLDdecay [The filtered SNPs were further pruned to obtain independent SNP markers using the ‘-indep-pairwise’ option, with a window size of 50 SNPs, a step of 10 SNPs, and rent}N-ON , where OpLDdecay  was usedpLDdecay , and thePrior to the ROH detection, the eligible SNPs with MAF ≥0.01 were separately filtered for each population. Long homozygous fragments were scanned in the pruned data using PLINK according to the following parameters: the minimum number of 50 SNPs in a ROH (−homozyg-snp 50), sliding windows of 50 SNPs (−homozyg-window-snp 50), allowance for not more than 5 missing SNPs (−homozyg-window-missing 5) and three heterozygous SNPs per window (−homozyg-window-het 3). The minimum length of an ROH segment was 300 kb (−homozyg-kb 300). The minimum SNP density was 1 SNP per 50 kb (−homozyg-density 50), and the maximum gap between two consecutive SNPs was 1000 kb (−homozyg-gap 1000). Finally, the rate in which a SNP was included in the total of sliding windows was at least 0.05 (−homozyg-window-threshold 0.05). After the run, the identified ROHs were classified according to their size into small (< 1 Mb), medium (1 ~ 3 Mb) and large (> 3 Mb) as previously delineated in chickens [ROH) was estimated using PLINK according to previous methods [ROH for each bird was calculated as i th individual, and Laut is the genome length of autosome covered by the SNPs in the sequence data. The inbreeding coefficient for an individual based on homozygous SNPs (FHOM) was computed as O is the number of observed homozygotes, E is the number of expected homozygotes by chance, and L is the number of non-missing autosomal SNPs. Genomic SNP-by-SNP inbreeding coefficient (FGRM) and the correlation between uniting gametes (FUNI) were computed in GCTA software as previously reported [Genomic inbreeding based on ROH (F methods . The FROreported . Pair-wiP < 0.05) GO terms and KEGG pathways.To identify the genomic regions that harbored common ROHs across the five chicken populations, we estimated the occurrences of SNPs in ROHs by counting the number of times when the SNP was detected in those ROHs using detectRUN package  implemenP value with the following formula piHS = −log10(1 − 2 | ∅(iHS) − 0.5| ), where ∅(iHS) represents the Gaussian cumulative distribution function, and piHS is the two sided P value associated with the neutral hypothesis of no selection [piHS higher than a threshold of 0.1% were considered as putative signatures of selection. Due to the limit of computing time and lack of accurate recombination rate of studied chickens, we only ran the selection signature analysis for candidate regions on GGA5 and GGA8 in the present study.To detect selection signatures in each ROH island, the integrated haplotype score (iHS) was calculated within each population. The iHS is a measure of the amount of extended haplotype homozygosity at a given SNP, that uses phased genotypes to identify putative regions of recent or ongoing positive selection in genomes . Herein,election . The piHAdditional file 1.


Background: The present work evaluates the association between circulating concentrations of Trimethylamine-N-oxide (TMAO), gamma butyrobetaine (γBB), and trimetyllisine (TML) in controls and patients with venous thromboembolism (VTE) with coagulation parameters. Methods: The study involved 54 VTE patients and 57 controls. Platelet function, platelet hyperreactivity, platelet adhesiveness, thrombosis-associated parameters, and thrombin generation parameters were studied. Plasma TMAO, γBB, and TML determination was performed using an ultra-high-performance liquid chromatography system coupled with mass spectrometry. Results: No differences were found for TMAO, γBB, or TML concentrations between controls and VTE patients. In thrombin generation tests, TMAO, γBB, and TML showed a positive correlation with lag time and time to peak. TMAO, γBB, and TML negatively correlated with peak height. No significant differences were observed regarding TMAO, γBB, and TML concentrations between the two blood withdrawals, nor when the control and VTE patients were analyzed separately. No correlation was observed between these gut metabolites and platelet function parameters. Conclusions: No differences were found regarding TMAO, γBB, and TML concentrations between the control and VTE groups. Some correlations were found; however, they were mild or went in the opposite direction of what would be expected if TMAO and its derivatives were related to VTE risk. Trimethylamine-N-oxide (TMAO) is a small organic compound formed in the liver and produced by the action of hepatic flavin monooxygenase 3 (FMO3) on trimethylamine (TMA). In turn, TMA is generated by the action of gut microbiota using precursors from the diet as choline or other choline-containing compounds, betaine, or L-carnitine, as a part of microbial-mammalian metabolism . TMAO caTMAO garnered attention some years ago due to its association with cardiovascular diseases (CVD), specifically atherothrombotic events in the context of myocardial infarction and stroke ,3,4. AccBacteria can participate in thrombosis etiology through various mechanisms, including TMAO production. Studies using animal models have provided evidence that TMAO promotes platelet responsiveness to multiple agonists by stimulating Ca2+ release from intracellular stores, heightening thrombosis potential . A recenVenous thromboembolism (VTE), which includes deep vein thrombosis (DVT) and pulmonary embolism (PE), is the third cause of cardiovascular death worldwide . DespiteOur hypothesis is that higher TMAO concentrations are associated with an increased risk of VTE. Therefore, our aims were, first, to evaluate the circulating concentrations of TMAO and two of its precursors, γBB and TML, in controls and patients with prior VTE events and, second, to study the correlation of TMAO, γBB, and TML with coagulation parameters.A final number of 111 individuals were enrolled in the study, including 66 females (59.5%) and 45 males (40.5%) with a mean age of 61.7 years (16.7). This is a sub-cohort of the original RETROVE (Riesgo de Enfermedad TROmboembólica VEnosa) cohort. Briefly, the RETROVE study was a case–control study that included 400 consecutive patients with VTE (older than 18 years) and 400 healthy volunteers without history of VTE who served as controls. The objective of the RETROVE Study was to identify biomarkers for VTE and to establish mathematical algorithms to predict its risk [The diagnosis of VTE was based on Doppler ultrasonography, tomography, magnetic resonance, arteriography, phlebography, and pulmonary gammagraphy. Inclusion criteria included all types of thrombosis except those related to cancer. VTE events were classified as spontaneous or non-spontaneous (one or more provoking factors within three months prior to an event), as shown in The study was approved by the Sant Pau Ethics Committee, nr. 04/2012, 7 February 2012, following the standards for medical research in humans recommended by the Declaration of Helsinki. All participants gave written informed consent before enrollment in accordance with the guidelines of the local ethics committee.g for 10 min. The analysis was performed using a PFA-100 analyzer. The 54 patients were selected from those with lower percentiles (<10%) from platelet occlusion times measured by PFA-100. The citrated whole blood samples were transferred to the reservoir of the disposable test cartridges (PFA_ADP and PFA_EPI) inserted into the instrument, and both closure times (CT) were recorded.For the PFA, blood samples were collected in the antecubital vein and anticoagulated with 1/10 volume of 0.129 mol/l sodium citrate . Platelet-rich plasma (PRP) was obtained by centrifugation at 160× PHR is a phenotype related to sticky platelet syndrome and characterized by an increase in dose-dependent platelet aggregation patterns activated by agonists adenosine 5′-diphosphate (ADP) and epinephrine (EPI) at low concentrations in PRP. The test was performed by light transmission aggregometry (LTA) , measuring the percentage of maximal aggregation and the percentage area under the curve (AUC). The agonists were diluted with physiological saline. ADP and EPI at 0.5 mmol/L were used to differentiate between hyper-responders and hypo-responders. Higher concentrations of ADP and EPI  were used as positive controls.−1). The second approach used was 2D and 3D evaluation by confocal microscopy. The studied parameters were aggregate size (AS), surface covered (SC), and number of objects (OB).PA was evaluated using two experimental approaches. The first was the IMPACT system, which uses whole blood samples on a plastic surface (750 rpm) and microfluidic devices to explore platelet adhesion on collagen type I  according to the manufacturer’s instructions. The VWF antigen was determined by the commercial VWF Antigen test REAADS kit . A RIS assay with platelets reproduces in vitro the ability of VWF to interact with the platelet receptor glycoprotein GPIb-IX-V complex, in the presence of ristocetin .Thrombosis-associated parameters included A disintegrin-like and metalloprotease with thrombospondin type 1 motif no. 13 (ADAMTS13), ristocetin cofactor (RIS), and von Willebrand factor (VWF). The ADAMTS13 antigen was determined using a TECHNOZYMg for 20 min. Thrombin generation measurement was performed using a semi-automated calibrated automated thrombogram . The measured parameters were lag time (LAG), time to peak (TTP), peak height (PEAK), and endogen thrombin potential (ETP).Thrombin generation was measured in platelet-poor plasma (PPP), which was obtained by centrifugation at 2000× g); plasma aliquots were stored at –80 °C until analysis. TMAO and its derivatives were determined using an ultra-high performance liquid chromatography system coupled with mass spectrometry (uhLC-MS). The internal standards (IS) used for the study were d3-methylcarnitine (d3-MeCar) to quantify the γBB and TMAO concentrations and 13C3-TML for TML, both at 5 ppm. A human serum pool spiked with standards was used to prepare the calibration curves . To determine TMAO and its metabolite (γBB and TML) concentrations, blood samples were collected in EDTA tubes with subsequent centrifugation , containing the two IS, were mixed and vortexed for 20 s. After 30 min of re-equilibration on ice, the samples were centrifuged at 25,100× g for 10 min at 4 °C. The supernatant was transferred to a specific vial prior to LC-MS analysis. The extracts were analyzed using an uhLC system coupled with a 6490 triple-quadrupole mass spec-trometer  with an electrospray ion source (LC-ESI-QqQ) working in positive mode. An Acquity UPLC BEH HILIC column  and a gradient mobile phase consisting of water with 50 mM ammonium acetate (phase A) and acetonitrile (phase B) were used for chromatographic. Details of the chromatographic conditions have been previously described and can be found elsewhere [Briefly, 25 µL of human plasma and 300 µL of acetonitrile:methanol:water .Categorical variables are described using frequencies and percentages while continuous variables are described using median and the percentiles 25 and 75. A non-parametric Mann–Whitney U test was used to assess the differences in gut-derived metabolites between the control and VTE groups, and a Wilcoxon signed rank test was used to assess differences in time (before–after) within groups. Correlations between continuous variables were conducted using Spearman’s Rho correlation; p = 0.764). No differences were observed regarding gender distribution, age range, body mass index (BMI), and the presence of other comorbidities. There was a slightly significant increase in the number of patients treated with anti-platelet drugs in the VTE group. No differences were found in platelet count and hepatic function between the two groups. A significant decrease in PFA and estimated glomerular filtration rate (eGFR) was observed in VTE patients compared to the control group  and 32 females (59.3%)—with a median age of 61.5 (47–78) years, and 57 control subjects—23 males (40.4%) and 34 females (59.6%)—with a median age of 64 (48–75) years. Regarding the follow-up time between the two groups, no differences were observed between control and VTE groups .Regarding gut-derived metabolites and the presence/absence of VTE, no differences were found in TMAO, γBB, or TML concentrations between the control and VTE groups in the baseline measurement (p = 0.024) and between TML and VWF . In these same samples, the most significant association with gut microbiota metabolites was found in parameters measuring thrombin generation, such as LAG, TTP, PEAK, and ETP. As shown in For thrombosis-associated parameters, samples collected at baseline presented with a significant positive correlation between TMAO and RIS . In these same samples, when searching for correlation among gut-derived metabolites and PHR, no correlations were found except for a mild significant one between γBB and PHR at endpoint (p = 0.037).For samples collected at endpoint, no correlations were found between platelet adhesiveness function tests measured as platelet AS, SC, or OB and gut-derived metabolites (data not shown). However, a slightly negative correlation between TMAO and AS was observed , γBB , and TML ; and at the endpoint: TMAO , γBB , and TML . PFA_ADP at both time points presented with similar non-significant results (data not shown). Other thrombosis-associated parameters  did not present an association with TMAO, γBB, and TML (data not shown). The platelet function analysis, measured as PFA_EPI, was not significantly correlated with gut-related metabolites measured at baseline: TMAO  or when the control and VTE patients were analyzed separately (data not shown). Concerning TMAO, γBB, and TML correlations, a positive statistically significant correlation was observed for the three metabolites over time, as follows: TMAO at baseline vs. TMAO at endpoint , γBB at baseline vs. γBB at endpoint , and TML at baseline vs. TML at endpoint .The median (interquartile range) plasma concentrations for TMAO, γBB, and TML at baseline were 3.75 (2.08–7.53) μmol/L, 0.56 (0.46–0.70) μmol/L, and 0.67 (0.54–0.86) µmol/L, respectively, and 3.5 (2.1–6.8) μmol/L, 0.5 (0.49–0.70) μmol/L, and 0.66 (0.56–0.84) μmol/L, respectively, at endpoint. No significant differences were observed regarding TMAO, γBB, and TML concentrations between the two blood withdrawals (The present work investigated the association between TMAO and two of its gut-derived intermediate metabolites (γBB and TML) with some hemostasis parameters used in clinical practice for the study of VTE risk.2+ release from intracellular stores [Our initial hypothesis was based on previous studies indicating a relationship between TMAO and thrombosis in animal models ,7,14,15 r stores . Specifir stores . The samr stores ,17. In pr stores .In contrast to the above-mentioned works, no differences were found in our study regarding TMAO, γBB, and TML concentrations between the control and VTE groups at baseline and follow-up. This leads to the idea that, in the context of VTE, the implication of TMAO and its gut-derived metabolites may be limited, at least in our cohort of patients. This negative result agrees with the recent study of Reiner et al. in which no statistical association between TMAO and the risk of VTE recurrence in patients was found, despite demonstrating that TMAO presented with a significant U-shape association with all-cause mortality . To our Regarding the hemostasis parameters, only several mild correlations were found in our cohort of patients between the microbiota metabolites and platelet function or thrombosis-associated parameters. These include a mild positive correlation for samples measured at baseline for RIS and VWF for TMAO and TML, respectively. Some correlations were also observed for parameters evaluating thrombin generation: LAG and TTP positively correlated with TMAO, TML, and γBB; PEAK negatively correlated with TMAO, TML, and γBB; and ETP negatively correlated with TMAO. These negative correlations are in the opposite direction of what would be expected if TMAO and its derivatives were related to VTE risk. Thus, the obtained results are not in line with the initial hypothesis of an association between TMAO and VTE, regardless of the numerous human studies relating TMAO to the impairment of coagulation parameters. A previous work with a cohort of 1627 patients found a weak correlation of TMAO with markers of platelet activation and showed that platelet reactivity and TMAO could be used as a mortality predictor even after adjusting for confounding factors . InteresRegarding TMAO and its derivative metabolite measurement over time, TMAO has been previously described as stable when stored at −80 °C for a period of five years, despite multiple freeze–thaw cycles . The firSeveral limitations should also be considered. Due to technical limitations, it was not possible to determine all coagulation parameters at both sampling times. Platelet function analysis, platelet hyperreactivity, and thrombin generation parameters were only analyzed in samples obtained at baseline, whereas platelet adhesiveness and thrombosis-associated parameters were only analyzed in samples obtained at endpoint. It can neither be ruled out that individual factors such as dietary habits or physical activity may have influenced the studied parameters over time, thus limiting our analysis with respect to the time when the VTE event occurred. This limitation is, however, difficult to overcome because the acute response has a major influence over many aspects of metabolism and might therefore have a major influence on TMAO concentration during the acute phase of VTE. In fact, a small study by Matsuzawa et al.  demonstrSimilar to the results by Reiner et al. , our worNo differences were found regarding TMAO, γBB, and TML concentrations between the control and VTE groups. Mild correlations were found in our VTE cohort between the microbiota metabolites and some of the coagulation parameters studied. In all cases, the correlations were mild or went in the opposite direction of what would be expected if TMAO and its derivatives were related to VTE risk.