Gestational diabetes mellitus (GDM) is the most common complication of pregnancy and is associated with an increased risk for type 2 diabetes. Racial/ethnic minority populations are at a higher risk than non-Hispanic white populations of developing type 2 diabetes after GDM. The aim of this study was to describe racial/ethnic differences in hyperglycemia and receipt of screening services in a nationally representative sample of women with a history of GDM.1c), and receipt of diabetes screening services.Our sample included 765 women from the US National Health and Nutrition Examination Survey (2007–2016) with a history of GDM. We used logistic, multinomial, linear, and proportional hazards regression to evaluate racial/ethnic differences in development of diabetes after GDM, hyperglycemia (measured by HbA1c ≥5.7%). However, non-Hispanic black women had 2.07  times the odds of being screened for diabetes compared with non-Hispanic white women (P = .02).Non-Hispanic black women had 63% higher risk and Hispanic women and “other” racial/ethnic women had more than double the risk for diabetes compared with non-Hispanic white women. Among women with a GDM history who did not receive a diagnosis of diabetes by the time of the study examination, both non-Hispanic black women and Hispanic women were more likely than non-Hispanic white women to be in the prediabetes or diabetes range (measured HbADelays in identification of hyperglycemia and diagnosis of diabetes in racial/ethnic minority women may reflect differential delivery of guideline-based care or poor follow-up of abnormal screening test results. Racial/ethnic minority women are disproportionately affected by type 2 diabetes. Among racial/ethnic minority women, non-Hispanic black women are at lowest risk for gestational diabetes mellitus (GDM) but highest risk for conversion to type 2 diabetes after GDM.1c levels and were more likely to have measured HbA1c values in the prediabetes or diabetes range.In this nationally representative population of US women with a history of GDM, non-Hispanic black women, compared with other racial/ethnic groups, were most likely to report receiving diabetes screening services in the past 3 years. However, non-Hispanic black and Hispanic women had higher HbAScreening for and prompt diagnosis of type 2 diabetes after GDM is critical in reducing complications. Differential receipt of follow-up services by racial/ethnic minority women may exacerbate disparities in the prevalence of type 2 diabetes.Gestational diabetes mellitus (GDM) affects 2% to 14% of all pregnancies in the United States and confers a significant and lifelong health challenge for both mother and infant, including an increased risk for type 2 diabetes . ApproxiClinical guidelines recommend postpartum glucose screening 4 to 12 weeks after a GDM pregnancy, yet an inadequate proportion of women with GDM receive these screenings –7.For people who do not receive a diagnosis of diabetes at the postpartum visit , clinical guidelines recommend enhanced rescreening . For peo1c) (a measure of hyperglycemia), and receipt of screening services based on clinical guidelines in a nationally representative sample of women with a history of GDM.The likelihood of developing type 2 diabetes after GDM differs across racial/ethnic groups. For example, black women with GDM are nearly 10 times as likely as women of all racial/ethnic groups without GDM to develop type 2 diabetes . We hypoWe analyzed data from the National Health and Nutrition Examination Survey (NHANES) for 2007–2016. NHANES is a cross-sectional, nationally representative survey of the US civilian noninstitutionalized population conducted by the National Center for Health Statistics . This st1c was measured by using high-performance liquid chromatography, standardized to the Diabetes Control and Complications Trial assay  or use of insulin; age at diabetes diagnosis was also reported by participants. For women who did not develop diabetes after GDM, receipt of screening for diabetes during the previous 3 years was determined by using the following question: “Have you had a blood test for high blood sugar or diabetes within the past three years?” Blood pressure, body mass index (BMI), waist circumference, and lipids were directly measured by using standard methods described previously . HbA1c wal assay .2 test as appropriate. For analyses, we defined undiagnosed diabetes as measured HbA1c equal to or greater than 6.5% in the absence of a diagnosis of diabetes or use of insulin and prediabetes as HbA1c from 5.7% to 6.4% in the absence of a diagnosis of diabetes or use of insulin. We used multinomial logistic regression to evaluate the association of race/ethnicity with undiagnosed diabetes (HbA1c ≥6.5%), prediabetes (HbA1c 5.7%–6.4%), and no diabetes (HbA1c <5.7%) at the time of NHANES examination among women with no diabetes (as defined by self-report diagnosis or use of insulin). We evaluated associations of race/ethnicity with HbA1c as a continuous outcome at the time of NHANES examination by using multivariable linear regression, stratified by women with and without diabetes.We assessed differences in participant characteristics across racial/ethnic groups by analysis of variance or χCox proportional hazards regression was used to assess the association of race/ethnicity with development of type 2 diabetes after GDM, using the difference between age at GDM diagnosis and age at diabetes diagnosis after pregnancy (if applicable) as the time to event; for participants who did not develop diabetes, we calculated follow-up time as the difference between GDM diagnosis and current age. Women were excluded if they reported an age at type 2 diabetes diagnosis that was before the age at GDM diagnosis or had missing information on age at type 2 diabetes diagnosis or GDM diagnosis. The proportional hazards assumption was assessed, and it was not violated.Associations of race/ethnicity, socioeconomic status, and access to health care with receipt of screening services were modeled by using logistic regression among women without diabetes (based on self-report or insulin use information). Analyses incorporated the NHANES sample weights and accounted for the complex sample survey design by using standard methods . We usedP < .001), BMI (P <.001), hypertension prevalence (P = .015), and waist circumference (P <.001) (P < .001), and 20.0% of Hispanic women reported not having access to a routine location for health care .Among 765 women with a history of GDM, 24.4% developed type 2 diabetes after GDM (weighted percentage). This did vary, although not significantly, across race/ethnicity and was highest among non-Hispanic black women (30.8%) and Hispanic women (31.0%) . ApproxiP <.001) . Hispani1c levels than did non-Hispanic white women. Among women with diabetes (by self-report or insulin use), non-Hispanic black and Hispanic women had 1.32% (P = .002) and 1.31% (P < .001) higher HbA1c, respectively, compared with non-Hispanic white women; the “other” racial/ethnic group did not differ significantly from the non-Hispanic white group (P = .57). Among women with no diabetes, non-Hispanic black and Hispanic women had 0.34% higher HbA1c , whereas the “other” racial/ethnic group had a 0.14% higher HbA1c (P = .03), compared with non-Hispanic white women. In fully adjusted models (P = .002) and for HbA1c ≥6.5% was 5.2-fold higher ; P = .02) among non-Hispanic black women than among non-Hispanic white women. Among Hispanic women, the relative risk ratio for prediabetes was 2.2-fold higher  and for HbA1c ≥6.5% was 6.7-fold higher  than among non-Hispanic white women.In a fully adjusted model , non-Hisd models , the relP = .01), Hispanic women more than double the risk , and “other” racial/ethnic women approximately double the risk  of developing type 2 diabetes following GDM compared with non-Hispanic whites  (P = .005) were more likely to have been screened, and women who reported no access to a routine place for health care  had 0.44 times the odds of being screened  (Among women without diabetes (defined by self-report or insulin use) at the NHANES examination, 67.1% reported having had a diabetes screening test at least once in the past 3 years. By race/ethnicity, this percentage was 67.1% among non-Hispanic white women, 77.3% among non-Hispanic black women, 59.2% among Hispanic women, and 72.6% among women in “other” racial/ethnic groups . In adjuP = .02) . Women w P =.02) . Other p1c levels. Among all racial/ethnic groups examined, non-Hispanic black women were most likely to have measured HbA1c values in the prediabetes (HbA1c 5.7%–6.4%) and diabetes range (HbA1c ≥ 6.5% in the absence of a diagnosis of diabetes). Both groups had higher rates of prediabetes and diabetes compared with non-Hispanic white women. Non-Hispanic black and Hispanic women had significantly higher mean HbA1c levels, regardless of current diagnosed diabetes status.In our study, non-Hispanic black and Hispanic women were at higher risk for developing type 2 diabetes after GDM compared with non-Hispanic white women, and they had higher HbARacial/ethnic disparities in risk for type 2 diabetes after GDM are well documented. Although non-Hispanic white and black women are at similar risk for GDM, black women have more than 2 times higher risk for developing type 2 diabetes after GDM compared with non-Hispanic white women . HeterogThe proportion of women reporting receipt of a diabetes screening test varied by race/ethnicity in the US population of women with a GDM history, despite the clinical recommendation that all women with GDM history be screened every 1 to 3 years. The finding that non-Hispanic black women without current diabetes, but with a history of GDM, were more likely to be screened for diabetes is consistent with their more adverse diabetes risk profile, including higher mean blood pressure, BMI, and prevalence of family history of diabetes. Despite being screened and demonstrating a higher prevalence of hyperglycemia, they were less likely to receive a diagnosis of diabetes. In unadjusted (crude) models, non-Hispanic black women had higher odds and Hispanic women had lower odds of being screened compared with non-Hispanic white women. This association became nonsignificant after adjustment for sociodemographic, clinical, and health care access factors for Hispanic women, but the association became stronger for non-Hispanic black women.The lower percentage of Hispanic women who reported being screened for diabetes is consistent with the observed lower percentage who had current health insurance and lower percentage reporting access to a routine location to obtain health care compared with non-Hispanic white women. More than 30% of Hispanic women with a GDM history were subsequently diagnosed with diabetes, higher than the percentage among non-Hispanic white women and similar to the percentage among non-Hispanic black women. However, among women that had not been diagnosed with diabetes, Hispanic women had lower odds of being screened for diabetes in the previous 3 years compared with all other racial/ethnic groups in unadjusted models. The association of race/ethnicity with receipt of screening became nonsignificant for Hispanic women after adjusting for measures of household income and access to a routine health care location. This finding suggests that access to screening services may play an important role in the observed lower likelihood of diabetes screening in this population.1c (Our findings also support research that non-Hispanic black women, in particular, are more likely to have undiagnosed prediabetes or diabetes and have a higher prevalence of suboptimal HbA1c –19. Thes1c . StudiesAlthough NHANES is a cross-sectional survey, it collects detailed information about pregnancy history and timing of diabetes diagnoses, allowing for estimation of diabetes risk after GDM. Additionally, non-Hispanic black and Hispanic women were oversampled to provide a large study population to evaluate racial/ethnic differences; Asian women were not oversampled in most survey years and, therefore, we were not able to look at this subpopulation separately. Finally, diabetes diagnosis information was collected via self-report; potential misclassification cannot be ruled out. However, the study is strengthened by inclusion of a nationally representative sample of US women with a GDM history and extensive information about their social and family history, health behaviors, health status and history, and several indicators related to access to health services.1c levels. Additional investigation to identify underlying factors contributing to this observed disparity will be particularly important to inform recommendations to ensure more equitable delivery of quality care across populations.Screening and diagnosis of GDM is critical in reducing complications in women and their infants, as well as preventing onset of type 2 diabetes. Differential receipt of follow-up services by racial/ethnic minority women may exacerbate observed disparities in the burden of type 2 diabetes. Our study showed racial/ethnic disparities in diabetes diagnosis, receipt of diabetes screening tests, and HbA


Elymus tangutorum (Nevski) Hand.-Mazz, a cool-season hexaploid perennial, is an important pasture bunchgrass species used for forages and grassland restoration in Qinghai-Tibet Plateau and northwest China. In this study, 27 E. tangutorum accessions from diverse origins of western China were evaluated using AFLP markers in an effort to delve into the genetic relationships among them. The effects of eco-environmental factors and geographical isolation on the genetic diversity and population structure were also elucidated.Understanding genetic diversity of wild plant germplasm and the relationships between ecogeographic and genetic characteristics may provide insights for better utilizing and conserving genetic resources. FST = 0.162) between Qinghai-Tibet Plateau (QTP) and Xinjiang (XJC), and high differentiation (FST = 0.188) among three Bayesian subgroups. A significant correlation (r = 0.312) between genetic and geographical distance was observed by Mantel test in the species level, while the weak correlation was detected between genetic and environmental distance for all accessions and most of geographical groups. In addition, a significant ecological influence of average annual precipitation on genetic distance was revealed in XJC group and the Bayesian subgroup A.On account of 554 polymorphic fragments amplified with 14 primer combinations, the mean values of some marker parameters including polymorphic information content, resolving power and marker index were 0.2504, 14.10 and 23.07, respectively, validating the high efficiency and reliability of the markers selected. Genetic dissimilarity index values among accessions ranged from 0.1024 to 0.7137 with a mean of 0.2773. STRUCTURE, UPGMA clustering and PCoA analyses showed that all accessions could be divided into the three main clusters; however, this results do not exactly coincide with geographic groups. We found medium differentiation  together, play a crucial role in genetic differentiation patterns. These findings underline the importance of local adaptation in shaping patterns of genetic variability and population structure in E. tangutorum germplasm collected in Western China.This study indicates that AFLP technique are a useful tool to measure genetic diversity in The online version of this article (10.1186/s41065-019-0082-z) contains supplementary material, which is available to authorized users. Elymus Linn. is the largest and most widely distributed genus in the tribe Triticeae, with 150 species grown in temperate regions of the world [Elymus species are also used as fodder grasses and ecological protection [Elymus tangutorum (Nevski) Hand.-Mazz, a perennial hexaploid species with the StYH genome (2n = 6x = 42), along with E. duhuricus Turcz. ex Griseb., E. excelsus Turcz. ex Griseb. and E. ivoroschilowii Probat. constitute the E. dahuricus complex [E. tangutorum differs morphologically from E. dahuricus Turcz. in the light of the short upward awns and its distribution in the Qinghai-Tibet Plateau (QTP), Xinjiang province of China and the Alpine regions of Central Asia. In QTP, E. tangutorum is widely used for the degraded grassland restoration, due to high productivity, drought resistance, cold tolerance, and adaptability [E. tangutorum has been widely studied. Most of studies mainly focused on the domestication, cultivation, phylogenesis and genome constitution [he world , 3. Besiome 2n = x = 42, aome 2n = x = 42, aElymus accessions of ecotypes, and/or cultivars [Elymus species, diverse PCR-based markers, employed in diversity and phylogeny studies, such as RAPD [E. tangutorum populations from Tibet province of China by AFLP analyses [Understanding genetic diversity of wild plant germplasm and the relationships between ecogeographic and genetic characteristics may provide insights for better utilizing and conserving genetic resources . Investiultivars , 9. DNA- as RAPD , ISSR [1 as RAPD , SRAP [1 as RAPD , ScoT [9 as RAPD , and AFL as RAPD –16 have analyses , 5, untiGenetic diversity in natural plant populations is held especially by the spatio-temporal environmental heterogeneity, i.e., genetic differentiation is strongly influenced through isolation by distance or local adaptation –19. To eE. tangutorum germplasm accessions indigenous from two contrasting climatic zones of Western China, namely Qinghai-Tibet plateau and Xinjiang province  to verify the potential influence of spatial and environmental factors on the patterns of detected population structure.Here, AFLP markers were used to analyze, on a regional scale, genetic diversity and structure of 27 wild nce Fig. . The goaE. tangutorum were germinated in vermiculite under identical conditions  in a plant growth chamber. Genomic DNA was extracted from bulked young leaves from five plants per accession employing a CTAB procedure [Twenty seeds of each accession of AFLP fingerprinting was carried out following Vos et al. 1995) with minor modifications , 27, but995 with i = 2 fi (1 − fi), where PICi is the PIC of ith marker, fi stand for the frequency of the present fragments and 1 − fi represent the frequency of absent fragments [Rp = ∑Ib, where Ib (fragment informativeness) defined as Ib = 1–2 × |0.5 − p|, where, p is the proportion of accessions in which the fragment is present [The discriminatory power of each AFLP primer combination was evaluated by calculating polymorphic information content (PIC), marker index (MI), and resolving power (RP) with polymorphic bands only. The formula to calculate PIC value of each primer combination is: PICragments . Marker ragments . The res present .http://web.stanford.edu/group/pritchardlab/structure.html). Following the suggestion by Forsberg et al. [http://taylor0.biology.ucla.edu/struct_harvest/) to detect optimum value of K based on ΔK method [To understand the genetic relationship among all 27 accessions, pair-wise genetic distance (GD) were calculated on the basis of the Dice’s coefficient by NTSYS-pc v2.10 software. To obtain a more detailed view of the distribution of genetic variation within and between different geographical groups (XJ vs QTP), mean GD among accessions belonging to the same and/or different groups was also calculated. Based on GD matrix, the principal coordinate analysis (PCoA) and Unweighted Pair Group Method with Arithmetic (UPGMA) clustering analysis were performed. The robustness of the dendrograms was assessed with 1000 bootstrap iterations by Freetree software . The Bayg et al.  for outcg et al. . We set g et al. , we usedK method . The outK method  using thK method  for bettK method , which hK method . GeograpK method .FST) value was using GenAlEx 6.5 was performed. The observed (Na) and effective number (Ne) of alleles, expected heterozygosity (HE), Shannon’s information index (I) [To validate the genetic variation among and within inferred subgroups according to geographic origins or STRUCTURE results, analysis of molecular variance (AMOVA) based on PhiPT  , and Neihttp://swww.diva-gis.org/). The geographic and environmental distance matrix was calculated based on the Euclidean distance between pairs of collection sites using NTSYS-pc v2.10. Correlation between geographical and genetic distances (Nei-Li coefficients) between accessions was measured by Mantel test with 9999 permutations using IBD (Isolation by Distance) software v1.53 [Based on geographical location of each accession, the corresponding environmental data (precipitation and temperature parameters) was obtained by DIVA-GIS  were polymorphic and 70 (12.6%) were unique (Tables E. tangutorum germplasm from western China could be characterized well by above AFLP dataset retaining abundant variation. Polymorphism information content (PIC) of each primer pair being 0.5 for AFLP as the dominant marker, 38% of polymorphic loci (195) possessed PIC values above 0.25, implying high discriminatory power of AFLP markers for E. tangutorum germplasm. In addition, the marker index (MI) and resolving power (RP) values for individual primer pair were recorded. There were positive correlations between PIC, RP and MI . The most discriminatory primer combinations among 14 primers were E-ATG/M-CTC  followed by E-AAC/M-GAC .The AFLP fingerprinting was performed on 27 wild i), all 27 accessions were assembled into three Bayesian subgroups designated as subgroup A , subgroup B  and subgroup C (red fraction ≥0.2). The three subgroups included 10, 8 and 9 accessions, respectively. Geographically, most of accessions from Xingjiang (XJC)  belonged to subgroup A and the rest resided in subgroup B (Et20) and C (Et04 and Et13). Six accessions from Sichuan (SCC) were part of subgroup B and the five remaining accessions were part of subgroup C. For the three accessions from Gansu (GSC), Et18 consisted in subgroups B and the remaining two belonged to subgroup C.The results of population using the STRUCTURE software showed a clear peak of the ΔK values when K was set at 2 Fig. . Samplesmax = 4, indicating that the sampled accessions belonged to four inferred genome fraction  at KBased on the 509 polymorphic fragments, estimates of the genetic distances (Dice’s coefficient) ranged from 0.1024 to 0.7137 with an average of 0.2773, implying a largely genetic divergence in the germplasm collections studied. Accessions Et08 and Et11 were most related due to a minimum genetic distance of 0.1024, while Et01 and Et23 were most divergent with the maximum genetic distance of 0.7137. The rest of accessions have exhibited different middle levels of genetic distances. Compared with 0.2611 of inter-group dissimilarity, the accessions from Xinjiang were more homogenous with lower dissimilarity values (0.2214), whereas the QTP accessions were more variable genetically with higher dissimilarity values (0.2785). These results were also confirmed by STRUCTURE analysis that most of Xinjiang accessions had pure type of genome fraction. The genetic distance matrix was used to build a hierarchical dendogram of genetic relationships based on the UPGMA clustering method  Fig.  illustraP value was found to be highest among accessions from subgroup A (67.69%) followed by subgroup C (65.16%). The markers were least informative for assessment of genetic variability of accessions from subgroup B with PP restricted to 53.25%. Similarly, subgroup A showed the highest intra-group diversity (I = 0.36 and He = 0.24), whereas subgroup B had the lowest intra-group diversity (I = 0.01 and He = 0.0.01).Geographically, the region of Gansu and Sichuan Province are both part of the QTP region. Hence, we merged the GSC and the SCC group into a new group named QTP group. The total gene diversity across different ecogeographical regions was estimated based on 509 polymorphic fragments  was detected  which were tested by GenAlex 6.5. The total FST = 0.162 indicated that the genetic variability is moderate between QTP and XJC groups. The three subgroups inferred from STRUCTURE showed 81 and 19% of total variance within and among the groups. This means that the total FST was 0.188 (P ≤ 0.01) and the derived three subgroups are highly structured by Bayesian inference panel. Significant differences in the FST were observed for all the pairwise comparisons of three subgroups inferred from STRUCTURE analysis (Table FST (0.274) found between subgroup A and subgroup C was confirmed by their great difference of inferred genome fraction . A similar result was found in each group except GSC  and Subgroup A   [E. nutans by ISSR (91.4%) [The practical availability of molecular markers in plant germplasm characterization depends on their power to discriminate the genotypically different accessions analyzed. In the present paper, the efficiency of AFLPs were assessed by recording different marker parameters concerning polymorphism, PIC (Polymorphic Information Content), MI (marker index) and RP (resolving power). In total, 509 AFLP polymorphic fragments with 91.77% of polymorphism were observed in the current work, which was obviously higher than previous works by AFLP in oT (89%)  and E. n (91.4%) . In all, (91.4%) , 43. Mor (91.4%) .Dactylis glomerata [Phalaris aquatica [E. tangutorum germplasm. A very strong and positive correlation observed among PIC, RP and MI value in present work indicates the use of any of three parameters to screen the informative primer combinations [E. tangutorum collections. The Shannon index is an accurate alternative measure of diversity due to no need for estimate of allele frequencies under Hardy-Weinberg equilibrium. The Shannon diversity detected in this study (0.34) was higher than those of E. sibiricus germplasm from western China by SCoT (I = 0.285) and EST-SSR (I = 0.237) markers [E. tangutorum (Table The polymorphic information content (PIC) values of 0.25 in current study demonstrated good marker discriminatory power in view of PIC value starting from 0 to 0.5 for dominant marker like AFLPs , 46. Thilomerata  and Phalaquatica .The Markaquatica , 50, hadinations ; althoug markers , 51, alsElymus tangutorum accessions and biogeographical patterns by different clustering approaches. The UPGMA tree, the PCoA scatter plot, and the STRUCTURE analyses revealed a similar or identical membership among 27 wild E. tangutorum accessions, with a general grouping pattern including three genetically distinct and consistent groups. When these accessions are grouped according to clusters distinguished from Xinjiang,which were grouped with QTP accessions in Clade II and Clade III respectively. Since projects , it is pprojects . Nonetheprojects . These rntiation , 57.E. tangutorum was frequently used to grassland restoration in Qinghai-Tibetan Plateau as mentioned above [Indeed, the genetic diversity and population structure are determined by joint effects of many factors including geographic distribution, life cycle, mating system, selection and adaptation . Consideed above , 60. TheE. nutans and E. sibiricus collections with similar origins [E. tangutorum, supported by clustering and AMOVA, was also probably driven by its mating system, which is one of the important life-history feature that strongly influence genetic diversity and population structure [Elymus dahuricus complex [E. tangutorum is probably a predominantly self-pollinated species with 0.9 of FST value. In their review, Hamrick and Godt [E. tangutorum accession in present investigation could be treated as a population consisting of seeds of neighboring individual plants collected from differently distant locations [E. tangutorum was present rather within than among groups, since the large-scale geographical group contained numerous accessions with distinctly genetic architecture. These results could be confirmed by that the totally average genetic distance (0.277) between all of accessions was higher than that (0.261) between accessions from the two main geographical groups (QTP and Xinjiang).Results of AMOVA analysis showed low genetic variation among regions accounted for only 16.2% of the germplasm collection, whereas within-region variation accounts for 83.8% of the total variability. Similarly, only 19% of variation was detected for Bayesian groups,. These results on variation among accessions within geographical groups were confirmed with previous studies for  origins , 57. Howtructure . As repoand Godt  claimed and Godt  assumed ocations . This siE. tangutorum accessions and most groups was weakly correlated  compared with the XJC group (r = 0.313), which was not significantly different from zero and might be related to the highly heterogeneous topography nature of the QTP collection. The complex topographic features and climate will work together to form varieties niches to influence the genetic variability [r = 0.685; P = 0.01 and r = 0.594; P = 0.05) in the XJC group and Bayesian subgroup A. A possible explanation for this results is that in Xinjiang with arid and/or semi-arid temperate climate, the lower precipitation hinders seed germination and lead to decrease plants’ genetic diversity [E. nutans germplasm from western China, the environmental divergence like elevation is also related to genetic distance  [r = 0.309), the correlation between the genetic diversity and environmental factor was still unraveled due to the small population size.In virtue of the evolutionary forces, the decisive factor to influence the maintenance of genetic variability is the spatial variation of environment and the ecological difference between habitats . Remarkaed Table  and simi species , 57. Witiability . Thus, siability . In the iversity . In the  = 0.01) . On the  = 0.01) . This coE. tangutorum and geographical and environmental factors  together plays a crucial role in genetic differentiation patterns. These findings highlight the importance of local adaptation in shaping patterns of genetic structure inferred in E. tangutorum accessions fromWestern China. Therefore, collecting and assessing E. tangutorum germplasm from major geographic regions and special ecogeographic environment such as Qinghai-Tibet Plateau, will help to expand the genetic base and sample the full extent of available variation.This study indicates that AFLP markers are a powerful tool to measure genetic diversity in Additional file 1:Table S1. Adaptor and primer sequences used for AFLP analysis. (DOCX 17 kb)Additional file 2:Figure S1. Bayesian clustering results for 27 accessions of Elymus tangutorum using the program TESS from K = 2 to K = 5. (TIF 686 kb)Additional file 3:Figure S2. Maps representing the mean membership proportions for K clusters of Elymus tangutorum. (TIF 80 kb)Additional file 4:Table S2. Different genetic diversity estimates for geographical groups and Bayesian subgroups of E. tangutorum based on AFLP results. (DOCX 18 kb)


Although left ventricular hypertrophy (LVH) has been established as a predictor of cardiovascular events in chronic kidney disease (CKD), the relationship between the prevalence of LVH and CKD stage during the pre-dialysis period has not been fully examined.We measured left ventricular mass index (LVMI) in a cross-sectional cohort of participants in the Chronic Kidney Disease Japan Cohort (CKD-JAC) study to identify factors that are associated with increased LVMI in patients with stage 3–5 CKD.P = 0.0004], body mass index , systolic blood pressure , urinary albumin , and serum total cholesterol level .We analyzed the baseline characteristics in 1088 participants . Diabetes mellitus was the underlying disease in 41.7% of the patients, and mean age was 61.8 ± 11.1 years. LVH was detected in 23.4% of the patients at baseline. By multivariate logistic analysis, independent risk factors for LVH were past history of cardiovascular disease [odds ratio (OR) 2.364; 95% confidence interval ([CI) 1.463–3.822; The cross-sectional baseline data from the CKD-JAC study shed light on the association between LVH and risk factors in patients with decreased renal function. Further longitudinal analyses of the CKD-JAC cohort are needed to evaluate the prognostic value of LVH in CKD patients. Chronic kidney disease (CKD) is the leading risk factor for cardiovascular disease (CVD), a great threat to health and an economic burden . In Japa2. A cohort of CKD patients closely observed by the physicians is required to accurately analyze renal and CV events. However, few studies have been conducted on the prevalence of LVH in a pre-dialysis population [Renal dysfunction and albuminuria in CKD patients have been established as a risk factor for cardiovascular (CV) events independent of conventional CV risk factors –9. Populpulation –13.The aim of the present study was to clarify whether there is a close correlation between the prevalence of LVH and the stage of CKD classified according to eGFR and to identify factors related to LVH among the participants in the Chronic Kidney Disease Japan Cohort (CKD-JAC) .2. eGFR was calculated using a modified three-variable equation for eGFR in Japanese patients [− 0.287 × sCr− 1.094 , where sCr = serum creatinine.Baseline characteristics of CKD-JAC are described elsewhere . The folpatients : eGFR = All patients were classified on the basis of CKD stage as described in our previous paper . The folInformation on past medical history, including hypertension, acute myocardial infarction, angina pectoris, congestive heart failure, peripheral arterial disease, cerebrovascular disease, and prescription of antihypertensive agents, including angiotensin-converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs), calcium channel blockers (CCBs), diuretics, and b-blockers, statins, and antiplatelet agents, was collected from the medical records at each institution.2 in men and > 110 g/m2 in women [Blood pressure (BP) was measured in outpatient clinics with an automated sphygmomanometer after a 5-min rest. BP in the right arm was measured three times at intervals of 1 min, and the mean values were used for analyses. A mercury sphygmomanometer was used to measure the BP of patients who had frequent premature contractions, atrial fibrillation, or atrial flutter. Pulse pressure was calculated by subtracting diastolic BP from systolic BP. A two-dimensional guided M-mode echocardiographic study was performed in 1178 patients at each institution. Of them, the cases whose left ventricular end-diastolic diameter was not measured nor body surface area could not be calculated were excluded. Finally, this study included 1088 cases. Measurements included the diastolic thickness of the interventricular septum (IVST) and left ventricular posterior wall (PWT), and the internal diameter of the left ventricle at the end of diastole (LVDd) and the end of systole (LVDs). The modified Penn cube formula was used to calculate LV mass [in women . RelativHypertension was defined as systolic BP ≥ 140 mmHg and/or diastolic BP ≥ 90 mmHg or taking an antihypertensive agent. Diabetes mellitus (DM) was defined as HbA1C ≥ 6.5% or taking an antidiabetic agent. Diabetic patients were identified as those with diabetic nephropathy as the primary cause of CKD. Dyslipidemia was defined as serum triglyceride level > 150 mg/dl, or serum high-density lipoprotein (HDL) cholesterol level < 40 mg/dl in men and < 50 mg/dl in women.Whole blood, serum, and urine samples were collected for measurement of serum Cr, HbA1c, intact parathyroid hormone (iPTH), and urinary albumin and Cr levels at a central laboratory. Urinary albumin excretion was expressed as the albumin to Cr ratio (ACR). HbA1c was measured by the JDS method, and the value was converted to the A1C value measured by the NGSP method by adding 0.4% as determined by the Japanese Diabetes Society. Each clinical center measured serum Cr at each visit. A 24-h urine specimen was collected from each patient once a year to measure the amount of proteinuria.t test or one-way analysis of variance (ANOVA) were used to detect between-group differences. ACR values had a skewed distribution and were log-transformed to achieve a normal distribution. Logistic linear regression was used to investigate the relation of LVMI to eGFR, BMI, and log ACR. Univariate logistic regression analyses were performed in an attempt to identify factors related to LVH. Multivariate logistic regression analyses were used to identify independent variables related to LVH. We considered some variables that had a P value < 0.10 in univariate logistic regression analyses as independent variables for multivariate logistic regression analyses. The model included the variables as follows: sex, smoking status, complications of DM, dyslipidemia and hypertension, past history of congestive heart failure (CHF), angina pectoris, myocardial infarction (MI), stroke and peripheral artery disease (PAD), systolic and diastolic BPs, pulse pressure, BMI, eGFR, uric acid, ACR, A1C, iPTH, HDL cholesterol, triglyceride, calcium, phosphorus, and prescription of antihypertensive agents. The two-sided 95% confidence interval (CI) and odds ratio (OR) were calculated by estimation. A two-sided probability level of 5% was considered significant. All statistical analyses were performed using the SAS software program for Windows ver. 9.4 .All variables are reported as mean ± SD and frequency. Descriptive statistics of baseline characteristics were calculated by CKD stage, sex, and the presence or absence of LVH. CKD stages were defined according to the patient’s eGFR. Chi-squared test and Student’s N = 1088) who were examined by echocardiography (UCG), consisted of 694 Japanese men (63.8%) and 394 Japanese women (36.2%), 454 (41.7%) and 807 (74.2%) of whom had DM and dyslipidemia, respectively. Most of the subjects had hypertension (88.7%) and were being treated with an antihypertensive agent (92.5%), most of them with ACE inhibitors (25.8%)/ARBs (75.9%), as shown in Table We studied 2966 participants. Eleven participants  were excluded from 2977 of baseline participants . The basCKD was stage 3a in 128 patients (11.8%), stage 3b in 349 patients (32.1%), stage 4 in 427 patients (39.2%), and stage 5 in 184 patients (16.9%) . The prevalence of eccentric and concentric LVH was higher among patients with more advanced CKD stages . The prevalence of LVH was 255 of 1088 (23.4%) of the study population  of LVH in the present study was much lower than (30% <) that reported in previous studies in the pre-dialysis CKD population –21. The n = 1006, 92.5%), including ACE inhibitors  and/or ARBs .The prevalence rates of pre-existing CVD, i.e., MI (6.5%), angina (10.4%), CHF (5.5%), peripheral artery disease (3.7%), and stroke (12.3%), were higher than in the general Japanese population [More than 90% of the subjects were being treated with antihypertensive agents  of the 1088 study subjects, whereas LVMI tended to increase with the progression of CKD. In addition, the prevalence of eccentric and concentric LVH was higher among patients with more advanced CKD stages. CKD patients have a high prevalence of LVH, ranging from 34 to 74% in different studies, and its prevalence increases as renal function declines , 25, 26.Elevated systolic BP has a continuous, graded, and independent association with risk of coronary heart disease, stroke, and ESKD . LVH migIn accordance with the theory of non-hemodynamic LVH-promoting factors in our CKD patients, BMI was found to be a factor that was independently associated with LVH. Obesity is thought to be a risk factor independent of LVH, and heart disorders in obesity include structural adaptation with LVH and functional abnormalities . Kotsis Currently, information about sex differences in renal abnormalities and CVD in healthy individuals is limited and conflicting. In the Prevention of Renal and Vascular End-Stage Disease (PREVEND) study, the prevalence of microalbuminuria in men was almost double that observed in women, and for a higher value of age and BMI was greater in men than in women . In addiThe results of the present study have shown that albuminuria is an independent predictor of LVH in CKD patients. A recent study reported that higher ACR was associated with LV mass, size, systolic function, and diastolic function in CKD patients . This fiVarious abnormalities of mineral–bone metabolism are common in CKD patients, and mineral metabolism disorders such as hypocalcemia, hyperphosphatemia, and vitamin D deficiency have been found to be closely associated with CVD in CKD patients . The meaP = 0.55). Fourth, the definition of LVH in Japanese patients may be different from those in the USA. The LVMI value is dependent on body height and body weight. The cutoff values of LVMI were 125 g/m2 for men and 110 g/m2 for women in this study. These values were considered as 75 percentile of LVMI in this study. However, it is difficult to determine if the cutoff values of LVMI are suitable for use with the Japanese population. By contrast, the strengths of this study include its multicenter nature, the standard nephrology care, and the evaluation of patients with a wide range of eGFR.Some limitations have to be acknowledged in this study. First, selection bias cannot be ruled out, because patients were mostly enrolled at large-sized hospitals that can provide nephrology care . TherefoIn conclusion, the results of this study showed that the prevalence of LVH was low in stage 3–5 CKD patients treated by nephrologists in Japan. The cross-sectional baseline data from the CKD-JAC study shed light on the association between LVH and risk factors in patients with decreased renal function. Differences in the presence of previous CVD, blood pressure control, and metabolic state may lead to different outcomes of CVD in a longitudinal study. Future analysis of the CKD-JAC cohort will clarify whether the incidence of LVH varies with the causative disease during further follow-up.


Progressive familial intrahepatic cholestasis (PFIC) is caused by variations in ATP8B1, ABCB11 or ABCB4 genes. Data on genetic variations in Indian patients with PFIC are lacking.Coding and splice regions of the three genes were sequenced in unrelated Indian children with PFIC phenotype. The variations identified were looked for in parents, 30 healthy persons and several variation databases, and their effect was assessed in-silico.Among 25 children (aged 1–144 months), nine (36%) had unique major genomic variations . Seven had homozygous variations, which were assessed as ‘pathogenic’ or ‘likely pathogenic’. These included: (i) four amino acid substitutions ; (ii) one 3-nucleotide deletion causing an amino acid deletion (ATP8B1: c.1587_1589delCTT/p.Phe529del); (iii) one single-nucleotide deletion leading to frame-shift and premature termination ; and (iv) a complex inversion of 4 nucleotides with a single-nucleotide insertion leading to frame-shift and premature termination . Two variations were found in heterozygous form: (i) a splice-site variation likely to cause abnormal splicing (ABCB11: c.784 + 1G > C), and (ii) a nucleotide substitution that created a premature stop codon (ABCB4: c.475C > T/p.Arg159Ter); these were considered as variations of uncertain significance. Three of the nine variations were novel.Nine major genomic variations, including three novel ones, were identified in nearly one-third  of Indian children with PFIC. No variation was identified in nearly two-thirds of patients, who may have been related to variations in promoter or intronic regions of the three PFIC genes, or in other bile-salt transport genes.The online version of this article (10.1186/s12876-018-0835-6) contains supplementary material, which is available to authorized users. Progressive familial intrahepatic cholestasis (PFIC) is a group of heterogeneous liver disorders of childhood with disruption of normal secretion of bile salts and/or phospholipids into the bile . It accoThe genomic variations underlying PFIC show geographic heterogeneity. Thus, some variations, such as G308V, D554N and I661T in ATP8B1 gene have been observed frequently in Caucasian groups , 7, but Data on PFIC in the Indian population are limited to a few case reports and case series –15. In pThe study included children with liver disease with clinical and biochemical findings that suggested a diagnosis of PFIC. The diagnosis was considered in all infants and children presenting with cholestatic liver disease, with no evidence of biliary obstruction on imaging or of another cause of liver injury. Cholestasis was defined in children as jaundice with itching and deranged liver function tests, and in neonates as jaundice with conjugated bilirubin exceeding 20% of total serum bilirubin . All children underwent clinical and laboratory work-up, including screening for TORCH  group of neonatal infections among infants, screening for metabolic liver disease , and Alagille syndrome . For patients with symptoms starting after 3 years of age, biochemical tests and liver biopsy examination were done to exclude Wilson disease and autoimmune hepatitis.Biochemical liver function tests including serum gamma-glutamyl transpeptidase (GGT) levels were measured in all patients. Those with elevated GGT levels were considered to have PFIC3, and those with normal GGT were considered to have PFIC1 or PFIC2. All patients with PFIC3 underwent MRCP; however, this was done selectively in those with PFIC1/PFIC2. All patients also underwent a liver biopsy as part of their diagnostic workup (not for this study); however, immunohistochemistry for bile salt export protein  and for multidrug resistance 3 protein  were not possible.In families with multiple cases, only one child was studied. For each child, clinical and biochemical data were recorded; in addition, family history of liver disease and history of prominent itching during third trimester of pregnancy in the mother were also noted, and a pedigree tree was drawn with special emphasis on consanguinity. From each subject, venous blood (~ 2 ml) was collected in EDTA, after obtaining written consent from one of the parents, and genomic DNA was extracted using the phenol-chloroform method . Blood sFrom the genomic DNA, all the coding exons (exons 2 to 28 for each gene) and the surrounding splice site regions were amplified using polymerase chain reaction with specific primers for genes ATP8B1 , ABCB11 http://jblseqdat.bioc.cam.ac.uk/gnmweb/download/soft/FinchTV_1.4/doc/) and Seqtrace (version 0.9.0) (https://code.google.com/archive/p/seqtrace/) softwares. The sequences were then aligned against genomic and messenger RNA reference sequences for ATP8B1 , ABCB11  and ABCB4  genes from National Centre for Biotechnology Information (NCBI) database. Each variation observed was manually verified.The nucleotide sequencing data obtained were analysed using Finch TV (1.4.0) (https://www.ncbi.nlm.nih.gov/projects/SNP/), Human Gene Mutation Database (HGMD) (http://www.hgmd.cf.ac.uk/ac/index.php), Exome Aggregation Consortium (ExAC) (http://exac.broadinstitute.org/), ClinVar NCBI (https://www.ncbi.nlm.nih.gov/clinvar/), 1000 genome browsers ]. Further, the effect of each variation on the amino acid sequence of the respective protein was assessed; this was followed by prediction of the effect of amino acid change on the protein function using several bioinformatics tools, namely PROVEAN [The sequence variation identified were looked up in various genomic variation databases [NCBI dbSNP . Their clinical and laboratory findings are shown in Table n = 7). The remaining two variations were present in heterozygous form and were assessed to be ‘of uncertain significance’ (n = 2); in both these patients, no other pathogenic variation was identified. Five of the 7 patients with homozygous variations and none of the two with heterozygous variations reported consanguinity .Overall, 9 patients were found to have 9 different major genomic variations Table . Of thesity Fig. .Table 2‘) showed no significant difference between the two groups, except that patients with genomic variations tended to be younger and more often had history of consanguinity, compared to those without variations.Of the nine patients with significant variations, four had these variations in the ATP8B1 gene, 3 in ABCB11 gene and 2 in ABCB4 gene. Of the nine variations identified, three  were novel. Four variations led to a single amino acid substitution, one led to shifting of reading frame and premature truncation, two led to creation of a stop codon at the variation site, one led to an in-frame deletion of one amino acid, and one was predicted to lead to loss of a splice site. The clinical and laboratory findings in the patients with identifiable variations are shown in Table 1n = 7), both parents were available for testing for four patients and one parent each was available for three patients; all of them showed the respective variation in heterozygous form. For the two patients with heterozygous variations, one parent each was available for testing; in either case, the tested parent too had the variation in a heterozygous form.The results of bioinformatic prediction of the effect of these genomic variations are shown in Additional file Three non-synonymous variations were identified in several children with PFIC Table . These vIn addition, 12 synonymous variations  was expected to lead to production of a truncated ATP8B1 protein , which would lack a part of the E1-E2 ATPase domain (aa 170–234), and the entire cation ATPase (aa 533–628) and phospholipase ATPase C domains (aa 919–1174), and hence be non-functional. This patient has been described in detail elsewhere as a case report . AnotherDEGALV motif, specific for P-type ATPases [Variations observed in our remaining six patients had been reported previously in other population groups. Of these, three were in ATP8B1 gene and had been previously shown to be associated with disease. First, an in-frame deletion p.Phe529del) had been previously reported in two patients – in homozygous form in a Japanese patient with severe disease needing liver transplant by 4 years of age 9del had , and in  ATPases , and was ATPases . Third,  ATPases , and the ATPases .Of the remaining three previously-reported variations, one was in ABCB11 gene. This variation in ABCB11 gene (p.Met183Thr) had been previously reported in a patient with PFIC2, who had a compound heterozygous state ; in our We also identified some missense and synonymous variations which were frequent in population-level genetic databases, and were predicted not to adversely affect protein structure or function, and hence were considered ‘benign’ or ‘likely benign’. One of these, the c.1331 T > C p.Val444Ala) substitution in ABCB11 gene may need particular mention. This variation has previously been variably reported to be associated with reduced activity of the protein and disease [4Ala subsImportantly, no coding region or splice-site variation was identified in any of the three genes studied in 16 of our 25 patients. This could have several explanations. In studies from other geographical regions too, variations are identified in only 30–50% of cases with PFIC phenotype . Second,As expected, we identified genomic variations more often in patients with history of consanguinity  than in those without . In the two patients who had homozygous variations in the absence of history of consanguinity, the parents may have had some shared ancestry which was missed on history taking; this is possible with close inbreeding prevalent in some communities in India.Our study identified major genomic variations in only about one-third of Indian children with PFIC. None of the nine variations that we identified  was particularly frequent, and three of these were novel. Further, our findings suggest that genomic variations responsible for PFIC in Indian patients may differ from those in other populations. Since we did not find any genomic variation in nearly two-thirds of our patients, it may be useful to undertake whole-exome or whole-genome sequencing studies in Indian children with PFIC to look for variations in promoter/intronic regions of the ATP8B1, ABCB11 and ABCB4 genes and in other genes involved in bile salt transport.Additional file 1:Table S1. Results of prediction of effect, using various bioinformatic tools, of various ‘pathogenic’ or ‘likely pathogenic’ non-synonymous genomic variations. Table S2. Results of prediction of effect, using various bioinformatic tools, of various ‘neutral’ non-synonymous genomic variations. Table S3. Synonymous genomic variations identified in Indian patients with PFIC syndrome (DOCX 24 kb).


Diabetes is associated with higher risk of colorectal cancer (CRC). Uncertainty remains about the relevance of duration of diabetes and about the association of blood glucose with CRC risk among individuals without diabetes.The prospective China Kadoorie Biobank recruited 512 713 participants in 2004–2008 from 10 diverse areas in China. After 10 years of follow-up, 3024 incident cases of CRC  were recorded among 510 136 participants without prior cancer at baseline. Cox regression was used to estimate adjusted HRs for CRC associated with diabetes (previously diagnosed or screen-detected) and, among those without previously diagnosed diabetes, with levels of random plasma glucose (RPG).p for trend 0.03). Among those without previously diagnosed diabetes, RPG was positively associated with CRC, with adjusted HRs per 1 mmol/L higher baseline RPG of 1.04 (1.02 to 1.05) for CRC, again similar for colon and rectal cancer . The associations of diabetes and RPG appeared stronger in men than in women, but the differences were non-significant (p for heterogeneity 0.3 and 0.2).Overall 5.8% of participants had diabetes at baseline. Individuals with diabetes had an adjusted HR of 1.18 (95% CI 1.04 to 1.33) for CRC, with similar risk for colon and rectal cancer (1.19 [1.01 to 1.39] vs 1.14 [0.96 to 1.35]). The HRs decreased with longer duration of diabetes (Among Chinese adults, diabetes and higher blood glucose levels among those without known diabetes are associated with higher risk of CRC. Colorectal cancer (CRC) ranks as the third most common cancer and the fourth leading cause of cancer-related death globally.5 6In China, the prevalence of diabetes has increased from 2.5% in the 1990s to 11.6% in 2013, with approximately 60% of diabetes undetected.Details of the CKB design, survey methods and population characteristics have been described elsewhere.At local study assessment clinics, participants completed an interviewer-administered laptop-based questionnaire on sociodemographic characteristics, smoking, alcohol consumption, diet, physical activity, personal and family medical history and current medication. A range of physical measurements were recorded by trained technicians, including height, weight, hip and waist circumference, bio-impedance, lung function, blood pressure and heart rate, using calibrated instruments with standard protocols.A 10 mL non-fasting (with the time since the participant last ate recorded) blood sample was collected from participants into an EDTA vacutainer . Immediate on-site testing of random plasma glucose (RPG) level was undertaken using the SureStep Plus System (Johnson & Johnson), regularly calibrated with manufacturer quality control solution. Participants with RPG levels≥7.8 mmol/L and <11.1 mmol/L were invited to return for a fasting plasma glucose (FPG) test the next day. RPG data were unavailable for 8341 participants (because of a delay in making the on-site test available in certain regions).Previously diagnosed diabetes was defined by the question ‘Has a doctor ever told you that you had diabetes?’. Among positive respondents, additional information about age at diagnosis and current use of certain medications for the treatment of diabetes  and cardiovascular diseases  was collected. Among those without previously diagnosed diabetes, screen-detected diabetes was defined as: (1) RPG≥7.0 mmol/L if the time since last eating was ≥8 hour; (2) ≥11.1 mmol/L if the time since last eating was <8 hour or (3) a FPG≥7.0 mmol/L on subsequent testing.From August to October 2008 (~2.6 years after the baseline survey) 19 788 (~5%) surviving participants were randomly selected to attend a resurvey. The data collection and survey procedures were much the same as in the baseline survey. RPG data were available for 19 712 (99.6%) resurvey participants.The vital status of each participant was determined periodically through China CDC’s Disease Surveillance Points (DSP) system and national health insurance system, supplemented by regular checks against local residential and administrative records and by annual active confirmation through street committees or village administrators.10.1136/jech-2018-210651.supp1Supplementary file 1We excluded individuals with a prior history of cancer at baseline (n=2577), leaving 510 136 individuals for the main analysis online . Mean vaCox proportional hazards models were used to estimate adjusted HRs of CRC incidence associated with diabetes and RPG levels at baseline, stratified by age-at-risk (5 year groups), sex and study area (10 areas) and adjusted for age at baseline, education , smoking , alcohol  and total physical activity. Cox models with a time-updated exposure for diabetes duration were used to estimate the association of diabetes duration with CRC risk, with the same adjustment. Incident diabetes cases  that occurred during the follow-up were also included. We also used Cox models with a time-updated exposure in which individuals with incident diabetes were considered as exposed from their time of diagnosis. Duration was defined as the time interval between diabetes diagnosis and time at risk. The analysis for RPG was conducted in participants without previously diagnosed diabetes (n=486 189). RPG was categorised into five groups , selected to include the FPG thresholds for impaired fasting glucose and diabetes. RPG was also modelled as a continuous variable to estimate risk associated with a 1 mmol/L higher level of RPG. The analysis for RPG was additionally adjusted for fasting time. For analyses involving more than two categories, all HRs are presented with ‘floating’ SEs to facilitate comparisons between groups.12In sensitivity analyses, we examined the associations for diabetes and for RPG in subgroups defined by age-at-risk , sex, region, education, smoking, alcohol, physical activity, BMI, waist-to-hip ratio (WHR) and history of cardiovascular disease (CVD). We also repeated the analyses for diabetes excluding CRC cases that occurred in the first 2 or 5 years of follow-up. For the associations of diabetes with CRC risk, we further adjusted for diabetes medication  and reported the HRs of CRC associated with diabetes medication. Statistical analyses were done using SAS V.9.3 and R V.2.14.2.Among all 510 136 participants, the mean (SD) age was 51.5 (10.7) years and 59% were women. The prevalence of previously diagnosed and screen-detected diabetes was 3.1% and 2.7%, respectively. The mean (SD) RPG was 5.7 (1.1), 11.8 (5.7) and 13.3 (5.4) mmol/L among participants without any diabetes, with previously diagnosed diabetes and with screen-detected diabetes, respectively. Participants with diabetes were older and more likely to have higher levels of BMI, higher SBP, lower physical activity and to have CVD, hypertension and a family history of diabetes . Among aDiabetes was associated with an 18% higher risk of CRC  reported a 27% higher risk of CRC associated with diabetes and showed similar associations by sex and by anatomical site. cases reIn addition to diabetes, a few prospective cohort studies have reported on the association between blood glucose and CRC risk. A meta-analysis of six prospective cohort studies (62 814 CRC cases) reported a pooled RR of 1.015 (1.012 to 1.019) per 18 mg/dL higher FPG, with similar RRs by sex and by anatomical site.Hyperglycaemia and insulin resistance have been hypothesised as the underlying mechanisms linking diabetes and CRC.The strengths of the CKB include a prospective design, a large and diverse study population, large numbers of CRC cases by sex and by anatomical site and careful adjustment for other risk factors for CRC. One major limitation of CKB was that screen-detected diabetes was defined using RPG and therefore may be subject to misclassification. However, our result was consistent with previous studies that used fasting plasma glucose or postload plasma glucose to define screen-detected diabetes.In summary, among Chinese adults, diabetes was associated with higher risk of CRC. Among participants without prior diagnosis of diabetes, RPG was positively associated with risk of CRC. The associations for diabetes and RPG did not seem to differ by sex or by anatomical site. Given that the majority of diabetes cases are undiagnosed in China, early detection of diabetes could help identify a group of individuals at higher risk of CRC. Although future studies are warranted, lifestyle modifications to prevent diabetes and to lower blood glucose levels may lower risk of developing CRC.Studies conducted in Western populations have shown that diabetes is associated with higher risk of colorectal cancer (CRC).However, evidence has been inconclusive about the relevance of duration of diabetes and whether the associations differ by sex or by anatomical site.Moreover, evidence is limited whether blood glucose levels are associated with risk of CRC.In this Chinese population, we found that diabetes was associated with higher risk of CRC, with lower risk associated with longer duration of diabetes.Among participants without diabetes, there was a positive association of random plasma glucose (RPG) with CRC risk.The associations of diabetes and of RPG were similar in men and in women and for colon and for rectal cancer. Early detection of diabetes could help identify a group of individuals at higher risk of CRC.


Pitt-Hopkins syndrome (PTHS) is a genetic neurodevelopmental disorder associated with intellectual disability. Although the genetic mechanisms underlying the disorder have been identified, description of its behavioural phenotype is in its infancy. In this study, reported behavioural and psychological characteristics of individuals with PTHS were investigated in comparison with the reported behaviour of age-matched individuals with Angelman syndrome (AS) and Cornelia de Lange syndrome (CdLS).n = 24), assessing behaviours associated with autism spectrum disorder (ASD), sociability, mood, repetitive behaviour, sensory processing, challenging behaviours and overactivity and impulsivity. For most measures, data were compared to data for people with AS (n = 24) and CdLS (n = 24) individually matched by adaptive ability, age and sex.Questionnaire data were collected from parents/caregivers of individuals with PTHS  occurring at significantly higher rates than in AS (41.7%) and aggression (54.2%) occurring at significantly higher rates than in CdLS (25%). Individuals with PTHS also evidenced lower reported mood than individuals with AS.Behaviours which may be characteristic of PTHS include those associated with ASD, including deficits in social communication and reciprocal social interaction. High rates of aggression and self-injurious behaviour compared to other genetic syndrome groups are of potential clinical significance and warrant further investigation. An atypical sensory profile may also be evident in PTHS. The specific aetiology of and relationships between different behavioural and psychological atypicalities in PTHS, and effective clinical management of these, present potential topics for future research. Pitt-Hopkins syndrome  is a genetic neurodevelopmental disorder associated with an abnormal expression of the basic helix-loop-helix transcription factor 4 gene (TCF4) located on chromosome 18q21 (OMIM #602272). PTHS was first identified in 1978 by Pitt and Hopkins )Further areas of potential behavioural atypicality and difficulty for people with PTHS include high rates of anxiety (81%) , aggressThe set of behaviours associated with a specific genetic syndrome has often been referred to as a “behavioural phenotype” , 29, defThe current study assessed reported behavioural characteristics in a cohort of people diagnosed with PTHS, using measures with established psychometric properties and history of utility for investigation of behavioural phenotypes of genetic neurodevelopmental syndromes associated with ID e.g. , 31, 35), 3531, 3Comparisons were made with age- and ability-matched participants from two other genetic syndrome groups: AS and CdLS. Selection of these two groups for comparison was based on a number of factors. First, both AS and CdLS are associated with ID which may be profound , 25, potParticipants with PTHS were recruited via the Pitt Hopkins UK family support group. All families who had provided consent to be contacted by the syndrome support group were invited to take part in the present study via research advertisements shared by email and social media platforms. Twenty-four families responded to this invitation and provided consent to participate in the present study.Parents/caregivers of individuals with PTHS were invited to complete online questionnaires, using LimeSurvey 2.00+ software. The online survey contained information sheets, consent forms, a background information questionnaire including demographic questions and questions about the person’s diagnosis and genetic mutation and informant-report questionnaires assessing behavioural, psychological, social and physical characteristics commonly reported in ID populations.All participants had a diagnosis of PTHS, made by a clinical geneticist, paediatrician, or via medical research participation. Reported genetic mutations were 11 unspecified mutations of TCF4, nine deletions, one frameshift mutation, one translocation, one sequence repetition and one splice site mutation, ascertained through parent-report of syndrome diagnosis details .n = 12). Eleven participants (45.8%) were fully mobile , and two participants (8.3%) were verbal (defined as able to speak or sign more than 30 words). Nine participants (37.5%) had normal vision, 14 (58.3%) had poor vision and one participant (4.2%) was blind/almost blind. Twenty-three participants (95.8%) had normal hearing and one participant (4.2%) was deaf/almost deaf.The mean age of the PTHS group was 11.2 years  and 50% of the sample were male  , Social Due to violations of assumptions of parametric tests , non-parametric tests were used throughout.U analyses were conducted to identify significant differences between PTHS and matched syndrome groups individually. Categorical data derived from the SCQ  and CBQ (yes/no presentation of behaviours within the previous month) were compared between groups using chi-square analyses and Fisher’s exact tests. Effect sizes were calculated in concordance with guidelines for non-parametric tests [In order to compare individuals with PTHS with matched AS and CdLS groups, a series of Kruskal-Wallis tests were conducted to analyse group differences in total and subscale scores of questionnaires. Participants under the age of 4 years were excluded from SCQ data analysis, as this measure is not validated in children younger than 4 years . Post hoic tests  and inteic tests .aData for the SQID and the SEQ were not available for matched comparison groups. The analysis was therefore conducted in relation to previously published data. To assess sociability, single-sample Wilcoxon tests were performed to compare PTHS median scores for totals and subscales from the SQID with median scores presented by Moss and colleagues  for indip < 0.05 were reported as significant, but interpretation should be cautious, with attention also paid to effect sizes.The relatively large number of group comparisons used in this study increases the likelihood of type 1 errors (inappropriately rejecting the null hypothesis). However, low power due to the relatively low n increases the likelihood of type 2 errors (inappropriately accepting the null hypothesis), which may involve overlooking clinically important group differences. Therefore, effects at χ2(1) = 12.16, p < .001) and more individuals with PTHS with normal hearing compared to the CdLS group (χ2(1) = 19.5, p < .001).There were no significant differences between groups in adaptive ability, age, verbal ability, mobility or sex , described as moderate severity by 29.2%, with seven individuals (35%) needing corrective treatment. Other frequent health difficulties were epilepsy/seizures , ear problems  and skin problems . See Table The most frequently reported lifetime health difficulties were gastrointestinal problems , the Communication subscale  and the Reciprocal Social Interaction subscale . No significant differences were found between individuals with PTHS and CdLS on the total SCQ or any of the subscales. According to the SCQ, a significantly greater proportion of individuals with PTHS (95.5%) met the cut-off score to indicate possible ASD compared to AS (68.2%) (χ2 = 5.5 (1), p = .023), with a relative risk of 1.4 .There were significant between-group differences on the total score, Unfamiliar  and Familiar  total scores. However, individuals with PTHS had higher sociability scores than those with CdLS on Unfamiliar total scores  suggesting individuals with PTHS show higher levels of sociability with unfamiliar adults relative to individuals with CdLS.Significant differences in sociability scores were evident, when data from the PTHS group were compared to data from AS and CdLS groups derived from Moss et al. , using tStereotyped Behaviour, Compulsive Behaviour or Insistence on Sameness, see Table There were no significant differences between PTHS, AS and CdLS groups on the RBQ total scores or any subscale score  and Social Contexts (91.7%).The median scores of individuals with PTHS fell into the “deficient” range for χ2 = 4.15, p = .042, RR = 1.7, 95% CI = .99–2.91), and a significantly greater proportion of individuals with PTHS showed physical aggression compared to individuals with CdLS . Fewer people with PTHS (37.5%) displayed destruction of property relative to AS (54.2%) or CdLS (54.2%), although these differences did not reach statistical significance.A large proportion of the individuals with PTHS had displayed self-injurious behaviour (70.8%) and/or physical aggression (54.2%) in the last month; property destruction was also reported for 37.5% of the sample  and Mood subscale . No significant differences were evident between any of the groups on the Interest and Pleasure subscale  and wheIt is important to consider the specific profile of ASD phenomenology in syndrome groups, as evidence suggests the profile of ASD-related behaviours may differ from idiopathic ASD (e.g. ) and mayThe current data suggest difficulties with both social communication and restricted/repetitive behaviours in PTHS, supporting earlier literature presented by Zollino and colleagues . SpecifiRepetitive behaviours were comparable across all three syndrome groups in the current study. Most notably, rates of compulsive behaviour and insistence on sameness were markedly low in these groups, as previously reported in the AS and CdLS literature . SpecifiHigh rates of physical aggression and self-injury in the PTHS group should also be explored at a functional level. Further research may aim to delineate potentially contributory factors to these behaviours, in relation to cognitive, biological and environmental correlates. It is possible, for example, that the sensory processing difficulties documented in this study may contribute to physical aggression (e.g. see ), and giThis study employed a number of measures with known psychometric properties in ID research e.g. , 31, 35), 3531, 3Although the AS and CdLS groups are relatively representative of their syndromes described within literature e.g. , 24, 25), 2524, 2This study also did not employ direct genetic testing. All participants had a confirmed genetic mutation of the TCF4 gene as reported by parents/caregivers; however, it was not possible to delineate potential genotype-phenotype relationships. Results indicate possible behavioural differences between PTHS and AS groups, despite phenotypic similarities noted in the literature; this may be useful in distinguishing clinically between these syndromes and in appropriate targeting of diagnostic tests. Genetic analysis of both AS and PTHS can be complex, as a number of pathogenic variants involving the UBE3A gene and the TCF4 gene can lead to an AS or PTHS diagnosis, respectively . RoutineIndividuals with PTHS showed greater impairment in reciprocal social interaction and social communication than those with AS, with a greater proportion of those with PTHS than AS meeting cut-off scores for ASD symptomatology. Individuals with PTHS also evidenced high rates of stereotyped behaviour and atypical sensory processing, which may be further indicative of a profile of behaviour in PTHS which has features in common with ASD . Fu


Motoric cognitive risk (MCR) syndrome is characterized by slow gait and memory complaints that could be used to predict an increased risk of dementia. This study aims to determine the MCR syndrome and its risk factors among low-income (B40) older adults in Malaysia.t test were employed to examine differences in socioeconomic, demographic, chronic diseases and lifestyle factors between MCR and non-MCR groups. Risk factors of MCR syndrome were determined using hierarchical logistic regression.Data from TUA cohort study involving 1366 older adults (aged 60 years and above) categorized as low-income were analysed, for risk of MCR syndrome based on defined criteria. Chi-square analysis and independent p = 0.001), single/widow/widower/divorced , living in rural area , older age  and had lower years of education  than non-MCR group. After adjustment for age, gender and years of education, participants living in rural area , with obesity , diabetes , heart disease  and cancer  were associated with increased risk of MCR syndrome.A total of 3.4% of participants fulfilled the criteria of MCR syndrome. Majority of them were female (74.5%, Only 3.4% of older adults from low-income group were identified as having MCR syndrome. Women, those living in rural areas, had obesity, diabetes, heart disease and cancer were more likely to have MCR syndrome. Further investigation on MCR as a predementia syndrome will help in development of preventive strategies and interventions to reduce the growing burden of dementia, especially among individuals with low socioeconomic status. Malaysia is fast becoming an aging nation and is expected to reach this status by year 2035 . Aging iGait speed has been accepted as a simple, reliable and valid functional measurement of motor control, strength and gait pattern . StudiesA multi-country study reported that the pooled prevalence of MCR syndrome among older adults aged 60 and above was 9.7% . A recenAs yet little is known about the occurrence of MCR syndrome and its risk factors among low-income populations. In Malaysia, the low income or B40 group is the bottom 40% of households with an income of less than RM3, 900 per month. The median and mean household income for this group is RM3, 000 per month and RM2, 848 per month, respectively . The preThe participants eligible for this study were selected from baseline data of a population-based study focusing on neuroprotective model for healthy longevity (TUA) . The TUAMCR syndrome was first proposed by Verghese et al.  which isSubjects were defined as not having dementia if they scored less than 14 in Mini Mental State Examination (MMSE). A single dichotomous question “Do you feel you have more problems with memory than most?” on Geriatric Depression Scale (GDS) was administered by trained enumerators to elicit the presence of subjective memory complaints. Participants who answered “yes” on this question were defined as having subjective memory complaints. The same question was used to define subjective cognitive complaints in Doi et al.’s  study, a2. The presence of chronic diseases  was determined using a self-reported medical history questionnaire. Participants were classified as having depressive symptoms if they scored five and above on a 15-items Geriatric Depressive Scale (GDS).Potential sociodemography risk factors comprising age, gender, educational years, smoking habit, alcohol consumption, marriage status, and strata status  were determined using a sociodemography questionnaire. Obesity was defined as body mass index (BMI) ≥ 30 kg/mp <  0.05. Comparison of characteristics between MCR and non-MCR groups were analysed using chi-squared (χ2) tests for categorical variables and independent t-test for continuous variables. Hierarchical binary logistic regression was employed to determine the risk factors of MCR syndrome, adjusted for age, gender and educational years. Results were reported as adjusted odd ratio and 95% confidence interval (CI).All data were analysed using IBM Statistical Package for Social Science (SPSS) version 22 . Significant value was set at p = 0.001). As shown in Table p <  0.001). Majority of them were also living in rural area (p = 0.011), unmarried, divorced, widow or widower (p = 0.002).A total of 3.4% of the subjects fulfilled the criteria for MCR syndrome. Women had a higher prevalence of MCR syndrome (74.5%) compared to men 25.5%) (5.5% (p =p <  0.001), being female  and living in rural area  increased risk of having MCR syndrome. Other factors associated with increased risk of MCR syndrome were obesity , diabetes , cardiovascular disease , and cancer .Table n = 271), Japan (n = 514) and Korea (n = 549) were also smaller as compared to the present study [This study showed that the prevalence of MCR syndrome among low- income community dwelling older adults in an Asian country  was 3.4%. This figure is lower than findings from studies conducted in other Asian countries. A meta-analysis showed that the MCR syndrome prevalence among adults from Korea, China, Japan (Kurihara Project) and India , ranged from 10 to 15% . The difnt study .Demographic characteristics of the elderly varied in rural and urban settings in terms of loneliness, lack of financial stability, and emotional strain . Single p <  0.001) [Previous studies showed no significant gender disparities in MCR prevalence , 13. How  0.001) . This co  0.001)  and lose  0.001)  putting Similar to the previous studies, participants with MCR were older, less educated, had obesity and diabetes , 13. A mPrevious studies also reported that participants with MCR were more depressed compared to non-MCR group , 13. OurThe strength of this study is that it is one of very few studies investigating MCR among low-income populations in Asia. The limitation of the present study is that the true causal relationships could not be derived as this was a cross sectional study. Nevertheless, the multiple factors associated with MCR syndrome in the present study were in agreement with the risk factors of cognitive impairment and dementia . Future In conclusion, Malaysian older adults from the low-income (B40) group, especially women living in rural areas, with obesity, diabetes, heart disease and cancer were at a higher risk of MCR syndrome. The cost effective MCR concept can be easily applied in various settings, particularly in rural areas that lack of healthcare facilities, to identify high-risk individuals. Further investigation on MCR as a predementia syndrome will help in development of preventive strategies and interventions to reduce the growing burden of dementia, especially among individuals with low socioeconomic status.


Apium nodiflorum) is an edible vegetable with potential as a new crop. However, little information is available regarding the antioxidant properties of the plant and the individual phenolics accounting for this capacity are unknown.Fool’s watercress  free radical scavenging capacity, and the total phenolics content (TPC) via the Folin-Ciocalteu procedure. The individual phenolics constituents were determined via high performance liquid chromatography (HPLC) as aglycones.−1 DW and 22.3 mg of chlorogenic acid equivalents g−1 DW, respectively, much higher than those of celery and parsley. Significant differences for both DPPH and TPC, which may be explained by either genotype or environmental factors, were detected among groups established according to geographical origin. Quercetin was identified as the major phenolic present in the leaves of the species, unlike parsley and celery, in which high amounts of apigenin and luteolin were determined. Quercetin represented 61.6% of the phenolics targeted in fool’s watercress, followed by caffeic acid derivatives as main hydroxycinnamic acids.The average DPPH and TPC of fool’s watercress were 28.1 mg Trolox gThe study reports the high antioxidant properties of fool’s watercress based on a large number of populations. Results suggest that quercetin accounts for an important share of the antioxidant capacity of this potential new crop. The study also provides a basis for future breeding programs, suggesting that selection by geographical locations may result in differences in the antioxidant properties. Eruca sativa Mill. and Diplotaxis tenuifolia (L.) DC.) and watercress (Rorippa nasturtium-acquaticum Hayek) have been adapted and developed as common crops  Lag., commonly known as fool’s watercress or water celery, is a perennial herb from Apiaceae family. Well adapted to damp soils, it can be easily found, forming clamps, in fresh, shallow water courses such as streams or ditches. The species is broadly distributed along the temperate areas of central and southern Europe, northern Africa and western and central Asia  Nyman) and celery (Apium graveolens L. var. dulce) are good sources of apigenin (−1 FW (−1 FW (Foeniculum vulgare Mill.) (Coriandrum sativum L.) are rich in quercetin derivatives, with a total value of 494 mg 100 g−1 DW, and also present relevant contents of p-coumaric acid derivatives. However, we have not found references to the phenolic constituents of the edible organs of fool’s watercress.Flavonoids and phenolic acids are commonly found in Apiaceae  and dailapigenin , with len  . And BarWe consider that there is a need to evaluate the antioxidant properties and phenolic composition of fool’s watercress since this edible species has potential as a source of antioxidants. So far, little information on the diversity for phenolics content and antioxidant activity in the species is available . The stuThe Horta Nord of Valencia (Spain), an area with many irrigation ditches used for centuries by the farmers, was prospected. The prospection took place in the spring season of 2015 and was focused on the locations where ditches are still in use and a regular water flow is provided . A totalThe aerial part was air-dried in oven at 37 °C, with low humidity conditions, for three days, in order to prevent water activity . Dried s−1 DW).The antioxidant activity was measured as the 2,2-diphenyl-1-picrylhydrazyl hydrate (DPPH) free radical scavenging capacity as described by −1 DW).Total phenolics were extracted from subsamples of 0.125 g with 5 mL acetone (70% v/v) containing glacial acetic acid (0.5% v/v) and determined according to the Folin-Ciocalteu procedure  as indictert-butyl-4-methylphenol (BHT) (Sigma-Aldrich) (Phenolic compounds were extracted from subsamples of 0.1 g with 1.5 mL methanol (80% v/v) including 0.1% (w/v) 2,6-di-Aldrich) . Then, aAldrich) , to a fi−1 and the absorbance was fixed at 320 nm. The study of flavonoids was performed as described by −1 and a fixed absorbance of 360 nm, using the same solvents as above. The gradient elution started with 40% (B) following to 100% (B) at 10 min and maintained for 5 min, then decreasing to the initial conditions at 20 min and equilibrated for 5 min.Samples were analysed on a HPLC 1220 Infinity LC System . A BRISA C18 column  was used and the injection volume was 10 µl. Mobile phase consisted of two solvents, (A) 0.1% formic acid in water and (B) methanol with gradient elution. Hydroxycinnamic acids profile was studied under the following conditions : startinApiaceae were selected and used in this study , and with published data. Standards from common phenolics described in is study , which tThe average values of DPPH and total phenolics content (TPC) in each sample were used to obtain the mean value and the average standard error of the seven geographical groups of fool’s watercress (FW1-FW7), celery , and parsley . Data were analysed using a one-way factorial analysis of variance (ANOVA) considering the groups as a factor and significant differences between groups were calculated with the Student-Newman-Keuls test. Ten selected populations of fool’s watercress with low and high antioxidant activities and overall representing four geographical groups, plus the two samples of celery and the two of parsley, were analysed for phenolic profile by HPLC, in triplicates. Finally, Pearson pairwise comparisons were performed in order to evaluate correlations between DPPH, TPC and the content in phenolics determined as sum of the individual phenolics targeted.P < 0.001) between fool’s watercress and celery and parsley was found for the DPPH scavenging capacity  and 12.8-fold higher compared to parsley (2.20 mg Trolox g−1 DW). Values of the seven geographical groups considered in fool’s watercress ranged from 15.17 to 36.97 mg Trolox g−1 DW , with continuous variation among them (A highly significant variation (capacity . The aveong them .P < 0.001)  to 26.19 mg CAE g−1 DW (FW7), which meant that geographical groups with the lowest content were comparable to celery and parsley. As in the DPPH radical-scavenging activity, a continuous variation was observed for the total of groups established with significant differences (P < 0.01).In the case of TPC, differences were less remarkable in absolute values but also highly significant (< 0.001) . Celery −1 DW , with a mean value of 4.19 mg g−1 DW (−1 DW) while those with low content belonged to the geographical groups FW2 and FW5 . Populations from geographical group FW4 showed intermediate content . On the other hand, the mean values for celery and parsley were 7.63 and 4.76 mg g−1 DW, respectively.Ten populations of fool’s watercress from diverse geographical groups  and overall representing samples with low and high antioxidant capacity and TPC were used for analysing the phenolic profile of the species and comparing it with those of celery and parsley . The cong g−1 DW . Samples−1 of total compounds)  . In genep-coumaric and represented 3.0% of the total phenolics. On the contrary, the four hydroxycinnamic acids targeted were detected in fool’s watercress and celery. The relative concentration of these compounds in leaves of celery ranged from 0.5% for ferulic acid to 4.5% for caffeic acid derivatives. Ferulic acid was also the minor phenolic acid detected in fool’s watercress (1.2%), followed by p-coumaric acid (4.2%). Caffeic acid derivatives were determined as the main hydroxycinnamic acids of fool’s watercress (19.4%).Differences in the composition of phenolic acids were also determined. The only hydroxycinnamic acid detected in leaves of parsley was r = 0.903 (P < 0.001). For those samples of fool’s watercress that were analysed by HPLC, correlation coefficient values between DPPH, TPC and the content in targeted phenolics were also studied. The content in targeted phenolics as sum of the individual compounds presented high correlation coefficients with both the DPPH scavenging activity and TPC .The Pearson linear correlation coefficient (r) between the DPPH radical-scavenging activity and TPC in fool’s watercress populations was A. nodiflorum, F. vulgare, Montia fontana L. and Silene vulgaris (Moench) Garcke.) and obtained the highest values for DPPH and TPC in fool’s watercress. In addition, fool’s watercress also has high antioxidant activity compared to other common aromatic herbs and spices from the same family. The present study highlights the antioxidant capacity of fool’s watercress in terms of DPPH scavenging activity and TPC. These results are in agreement with published data. For example, Comparison among different geographical groups of fool’s watercress revealed moderate differences for the TPC and the DPPH radical scavenging activity. The production and accumulation of these secondary metabolites can be affected by the environmental conditions and stress situations as well as by genetic diversity . Thus, dApiaceae in fresh herbs such as coriander, dill or fennel (p-coumaric acid and ferulic acid), the four of them have been previously detected in fennel  Chromatogram obtained with the conditions described by (A) Chromatogram obtained with the conditions described by Click here for additional data file.10.7717/peerj.6296/supp-2Data S1Raw data file includes the content in total phenolics , and the DPPH value , for the twenty-five populations of fool’s watercress (Nod-001 to Nod-025), two of parsley (Cri-01 and Cri-02), and two of celery (Grav-01 and Grav-02). The file also includes the content of individual phenolics (micrograms per gram of dry matter) targeted by HPLC for the selected samples. Each data correspond to one individual measurement.Click here for additional data file.