Obesity has been linked to an increased prevalence of migraine, and to increased migraine attack frequency, but several questions are left unanswered by previous studies. We examined the relationship between obesity and headache in a large, population-based study where we could take into account body fat distribution, migraine subtypes and tension-type headache.The third population-based Nord-Trøndelag Health Study (HUNT3) included validated headache questionnaires and objective anthropometric measurements. Using a cross-sectional design, our sample consisted of 18,191 women and 14,985 men, aged 19 to 96 years. Of these 4290 (12.9%) had migraine, 4447 (13.4%) had frequent tension-type headache (TTH), and 24,439 were headache-free controls. A total of 5049 individuals with unclassified headache were excluded from the analyses. Using logistic regression, we modeled the association between obesity and headache prevalence, adjusting for relevant confounders.Both total body obesity (TBO) and abdominal obesity (AO) were associated with a higher prevalence of migraine when compared to headache-free controls , in particular for individuals < 50 years of age (OR 1.74 95% CI 1.54–1.98 and OR 1.89 95% CI 1.69–2.11). Similar results were seen for migraine with and without aura. Similar Overall, a weaker associations were as observed between obesity and TTH. There was a dose-response relationship between obesity categories and increased headache frequency in subjects with migraine. TBO was associated with migraine prevalence and attack frequency independent of AO.Both TBO and AO were associated with migraine prevalence and attack frequency. This association was largely limited to individuals < 50 years of age. TBO, rather than AO, may be a better measure of obesity in relation to migraine. The prevalence of overweight and obesity has increased substantially in the last decades, and is now one of the leading risk factors for disease and death worldwide , 2. TotaOur aim was to determine how obesity and body fat distribution TBO and AO were associated with migraine and TTH in a large population-based study. That included validated headache diagnoses and objective anthropomorphic measurements.Secondly, we explored how this association changed with age and sex, and whether there was a dose-response relationship between obesity measures and headache frequency.All inhabitants 20 years or older in Nord-Trøndelag county of Norway were invited to participate in the third Nord-Trøndelag Health Study (HUNT3) (2006–2008). The study population, including both participants and non-participants has been described in detail previously . In brieThe 14 headache questions in the second questionnaire (Q2) were designed mainly to determine whether the individual had headache, the frequency of headache, and, when headache were reported, to diagnose migraine and TTH according to slight modified the second version of the International Classification of Headache Disorders (ICHD-II) , 19. SubHeight and weight were measured with standardized weight scales and metric bands. The participants wore light clothes and no shoes. Height was measured to the nearest 1.0 cm, and weight to the nearest 0.5 kg. BMI was defined as weight/height2 and computed in kg/m2. BMI status in adults were categorized into four TBO levels; underweight (BMI < 18.5), normal weight (18.5 ≤ BMI < 25), overweight (25 ≤ BMI < 30) and obese (BMI ≥ 30) in accordance to World Health Organization (WHO) definitions .Waist circumference (WC) was measured to the nearest cm applying non-stretchable band horizontally at the umbilical level after the participants emptied their lungs, or midway between the last rib and the iliac cristae if the latter was larger. AO was defined from WC and categorized into three levels according to WHO criteria ; normal In accordance with a pre-planned strategy, it was decided to include the following variables available from HUNT3 as potential confounders because of their known impact on headache and obesity: sex (binary); age at participation (continuous); any history of diabetes (binary); current daily tobacco smoking (binary); and HADS-D (continuous). While HUNT3 included a wide range of health-related information, including several factors that have previously been associated with either headache or migraine , we limiP-values are reported, using 5% as a cut-off for statistical significance. Data analysis was performed with the IBM Statistical Package for the Social Sciences, version 26 .The association between headache and obesity was tested using logistic regression models. We estimated odds ratios (OR) and 95% confidence intervals (CI) for the association between anthropometric measures (exposure) and headache (outcome), using headache-free participants as controls. The exposure was either TBO categories (4 levels) or abdominal obesity (3 levels) as described above. Separate analyses were performed for migraine and TTH. Based on previous knowledge that body fat distribution and headache prevalence differ strongly by sex and age, we next performed analyses stratified by sex and by age < 50 years or ≥ 50 years of age. The cut-off of 50 years was based on the prior knowledge of headache prevalence and the hormonal changes in women during the menopause . Lastly,Our final sample consisted of 33,176 individuals, with a mean age of 54.4 years (range 19 to 96 years). Of these, 4290 (12.9%) had migraine and 4447 (13.4%) had TTH. Details are given in Table In adjusted analyses Tables  and 3, TResults for AO in adjusted analyses Tables  and 3 weTBO (BMI ≥ 30) and AO  were associated with both episodic and chronic migraine, with higher effect sizes for chronic than for episodic migraine Table . TBO andFor subjects with migraine, the association between headache frequency and TBO remained after additionally adjusting the model for AO  . In contrast, after adjusting for TBO , there was no remaining association between headache frequency and AO . In corresponding adjusted analyses for TTH, only a weak association remained between episodic TTH and AO, after adjusting for TBO (OR 1.10 95% CI 1.01–1.20).In this large population-based study both TBO and AO were associated with a higher prevalence of migraine. The associations were mostly limited to individuals < 50 years of age. There was a dose-response relationship between obesity categories and increased headache frequency in subjects with migraine. Regarding body fat distribution, the association between migraine and TBO was independent of AO, but not vice versa, suggesting that TBO may be a more important measure with regards to migraine prevalence and chronification. Similar, but weaker associations, were seen for TTH.The relationship between headaches and obesity was suggested in a prospective population-based 11-months follow-up study from US in 2003 . Study sObesity has also been associated with an increased prevalence of migraine. Two recent meta-analyses found that obese individuals had an overall increased risk of migraine of 14% versus 27% when compared with those with normal weight . HoweverBased on findings in pre-clinical and clinical studies various mechanisms have been suggested to explain the association between migraine and obesity, including metabolic and hormonal activity of adipose tissue, increased release of pro-inflammatory substances, neuroinflammation and neuropeptides involving hypothalamic function , 24, 25.A causal relationship between migraine and obesity can have important implications for clinicians, patients and future public health strategies, also in light of the increased risk of cardiovascular diseases in both migraine and obesity , 34, 35.Strengths of our study include the large and unselected population, and the use of validated headache diagnoses and standardized anthropometric measurements. The general health focus of the questionnaires decreases the risk of a specific selection bias in relation to headache diagnoses. In the multivariate analyses we could adjust for several relevant potential confounders. However, the possibility of residual confounding cannot be excluded in this observational study. The migraine diagnoses were validated and based on the ICHD-criteria . AlthougIn this large population-based study both total body obesity and abdominal obesity were associated with a higher prevalence of migraine. There was a dose-response relationship between increased obesity and increased headache frequency in subjects with migraine. These findings may have clinical implications for treatment of migraine and should be further investigated in population-based follow-up studies.


Research has suggested that artificial light at night (LAN) may disrupt circadian rhythms, sleep, and contribute to the development of obesity. However, almost all previous studies are cross-sectional, thus, there is a need for prospective investigations of the association between LAN and obesity risk. The goal of our current study was to examine the association between baseline LAN and the development of obesity over follow-up in a large cohort of American adults.The study included a sample of 239,781 men and women (aged 50–71) from the NIH-AARP Diet and Health Study who were not obese at baseline (1995–1996). We used multiple logistic regression to examine whether LAN at baseline was associated with the odds of developing obesity at follow-up (2004–2006). Outdoor LAN exposure was estimated from satellite imagery and obesity was measured based on self-reported weight and height.We found that higher outdoor LAN at baseline was associated with higher odds of developing obesity over 10 years. Compared with the lowest quintile of LAN, the highest quintile was associated with 12% and 19% higher odds of developing obesity at follow-up in men (OR (95% CI) = 1.12 ) and women ), respectively.Our findings suggest that high LAN exposure could predict a higher risk of developing obesity in middle-to-older aged American adults. Obesity has been a growing epidemic in the United States (US), with its prevalence in adults almost tripling between the 1960s and 2018 . AlthougNumerous studies have focused on individual-level risk factors for obesity, such as diet, physical activity, sleep, and psychosocial stress –10. A grUsing data from the NIH-AARP Diet and Health study, a large US cohort of middle- to older-aged men and women, we examined outdoor residential LAN at baseline in relation to the odds of developing obesity over about 10 years. We hypothesized that a higher level of LAN exposure at baseline was associated with higher odds of developing obesity after 10 years. We also conducted subgroup analyses to examine whether the association between LAN exposure and odds of developing obesity may differ by multiple individual and environmental factors including race, education, sleep duration, and neighborhood poverty.We used data from the NIH-AARP Diet and Health Study, which recruited AARP members aged 50–71 from six US states  and two metropolitan areas (Atlanta in Georgia and Detroit in Michigan). Details of the study have been described . Briefly2) or a history of emphysema or end-stage renal disease (N = 5071), which may have significant impact on weight changes. We then restricted our analytic subset to “well-geocoded” addresses , excluding only street name matches or addresses identified only to the ZIP code or administrative unit level . Our final analytic sample size was 239,781 . For our main analyses that examined the association between baseline LAN and the odds of prospectively developing obesity at follow-up, we focused on 190,204 participants  who were not obese (BMI < 30) at baseline.Of the 566,398 participants who completed the baseline questionnaire, 318,713 also completed the follow-up questionnaire. Of these, we excluded 52,210 participants who had missing values on weight and height measures at either baseline or follow-up. We further excluded 2324 participants who reported extreme body mass index (BMI) values (< 15 or > 50 kg/m2) was calculated. Obesity was defined as BMI ≥30. We also calculated changes in weight by subtracting baseline weight from weight at follow-up.Participants reported their height (in inches and feet) and weight (in pounds) at baseline and follow-up, from which BMI (kg/m2/sr) [low LAN exposure) as the reference group for analyses.Annual residential outdoor LAN was derived from satellite data from the US Defense Meteorological Satellite Program’s (DMSP’s) Operational Linescan System, maintained by the National Oceanic and Atmospheric Administration’s (NOAA’s) Earth Observation Group. Since previous studies have shown that the low-dynamic range 6-bit DMSP data do not provide sufficient variability in urban areas with high LAN levels,  we used 2/sr) . ExposurTo examine the associations between residential outdoor LAN and odds of developing obesity, we used multiple logistic regression models to calculate odds ratios (OR) and 95% confidence intervals (CI). We used multiple linear regression to calculate beta coefficient and 95% CI for changes in weight as a continuous variable. We considered a series of regression models. In Model 1 (base model), we adjusted for age (continuous), sex  and baseline BMI (continuous). In Model 2, considered as the main model, we adjusted for some additional potential confounders, including race/ethnicity , education , location , marital status , and census tract median home value (quintiles), poverty rate (quintiles), and population density (quintiles). We considered important risk factors of obesity as potential covariates, including physical activity, sedentary behavior and diet. However, because LAN influences circadian rhythms that play a central role in regulating diurnal behaviors such as eating and exercise, these behavioral factors are more likely to be mediators, instead of confounders of our analysis. In addition, adjusting them in the model had minimal impact on our results (changes in effect estimates< 1%). Therefore, we decided to not include them in the models. We conducted analyses in the overall population and in men and women separately to examine sex-specific associations. Additional subgroup analyses were performed according to potential effect modifiers, including sleep duration, education, race, and poverty rate at census tract level. To test for trend, we modeled the midpoint of LAN quintiles as continuous variables and used the Wald test to evaluate statistical significance. Statistical significance for interactions was tested using a likelihood ratio test comparing a model with the cross-product term to one without.N = 239,781) across quintiles of residential outdoor LAN at 1996 were presented in Table 5 vs 37.9% for Q1) but less likely to be white (84.5% vs 96.3%) or married (59.4% vs 78.2%). In addition, those living in areas with higher LAN were less likely to be current smokers (10.7% vs 9.2%), less likely to report engaging in physical activities ≥5 times/week (18.2% vs 21.6%), or getting7–8 h of sleep per night (40.1% vs 46.9%). Finally, areas with higher levels of LAN also had higher home values (198 k vs 154 k USD) and higher population density (3685 vs 304 per km2).Individual characteristics at baseline (p-for-trend = 0.50), or in sex-specific analysis .First, we examined the cross-sectional relationship between residential outdoor LAN and obesity at baseline Table S. After aN = 190,204) and found that people living in areas with higher baseline LAN were more likely to develop obesity at follow-up, and the association remained after adjusting for multiple confounders (Table Q5 vs Q1 (95% CI), 1.15 (1.05–1.25), p-for-trend = 0.0001). In sex-specific analyses, we observed similar results for both men (1.12 (1.00–1.25), 0.039) and women , 0.012; Table Table Sp-trend, 0.001 and 0.0001, respectively).In prospective analyses, we focused on participants who were not obese at baseline N = 190,04 and fop-values for interaction were statistically significant , abdominal obesity  and dyslipidemia 1.72, 0.02) [Previous cross-sectional studies have consistently reported a positive association between indoor and outdoor LAN and obesity. A Japanese study of 528 elderly individuals found that LAN > 3 lx measured by photometer at home was associated with higher odds of obesity  . Similar2, 0.02) . Two mor2, 0.02) . In anot2, 0.02) . In contP < .001 for trend) [To the best of our knowledge, few studies have examined the prospective relationship between LAN and obesity. In more than 700 elderly Japanese with photometer-measured LAN, Obayashi et al. reported that exposure to an average indoor LAN of 3 lx or higher was associated with higher gain in BMI and waist-to-height ratio over 21 months . Using qr trend) . ConsistSeveral possible mechanisms may explain the associations found in our study. Exposure to LAN suppresses melatonin, a key hormone in circadian regulation, and may lead to circadian disruption , 39. A gIn the last several decades, legislation has been passed in various places to control nighttime light pollution in the US. According to the National Conference of State Legislatures, at least 18 states and territories, including the District of Columbia and Puerto Rico, have laws in place to reduce light pollution . SpecifiThis study has some limitations. First of all, outdoor LAN measured by satellite imagery is only a proxy measure of the actual LAN exposure experienced at the individual level, and we did not have information about indoor LAN and use of curtains and/or blinds, which may lead to exposure misclassification. More information on individuals’ residential history, collected from multiple sources or by other spatial approaches, holds potential to improve the accuracy of this study . Second,Despite these limitations, our study has a number of strengths. Most importantly, its longitudinal design has allowed us to examine prospective associations between LAN and the odds of developing obesity. In addition, our large sample size allowed us to conduct subgroup analysis to evaluate the consistency of the relationship according to several sociodemographic, lifestyle, and neighborhood factors.In conclusion, our prospective analyses of a large US cohort of older men and women suggest that LAN may contribute to the development of obesity. Our findings could provide potentially important evidence for not only researchers, but also policy makers and public health professionals to develop regulations and interventions that aim at reducing nighttime light pollution in the neighborhood.Additional file 1: Table S1. Cross-sectional Relationship between LAN and odds of obesity at baseline . Table S2. The association between LAN at baseline and changes in weight between baseline and follow up. Table S3. Prospective association a between baseline LAN and risk of developing obesity at follow-up among non-obese women  at baseline according to subgroups with different education, race, and neighborhood characteristics. Table S4. Prospective association a between baseline LAN and risk of developing obesity at follow-up among non-obese men  at baseline according to different education, race, and neighborhood characteristics.


The etiology of prostate cancer (PCa) is multiple and complex. Among the causes recently cited are chronic infections engendered by microorganisms that often go unnoticed. A typical illustration of such a case is infection due to mollicutes bacteria. Generally known by their lurking nature, urogenital mollicutes are the most incriminated in PCa. This study was thus carried out in an attempt to establish the presence of these mollicutes by PCR in biopsies of confirmed PCa patients and to evaluate their prevalence.Mycoplasma genitalium, M. hominis, M. fermentans, Ureaplasma parvum, and U. urealyticum. PCR products were then sequenced to confirm species identification. Results significance was statistically assessed using Chi-square and Odds ratio tests.A total of 105 Formalin-Fixed Paraffin-Embedded prostate tissues collected from 50 patients suffering from PCa and 55 with benign prostate hyperplasia were subjected to PCR amplification targeting species-specific genes of 5 urogenital mollicutes species, M. genitalium, M. hominis, and M. fermentans in all tested patients. Strikingly, Ureaplasma spp. were detected among 30% (15/50) of PCa patients. Nucleotide sequencing further confirmed the identified ureaplasma species, which were distributed as follows: 7 individuals with only U. parvum, 5 with only U. urealyticum, and 3 co-infection cases. Association of the two ureaplasma species with PCa cases proved statistically significant (P < 0.05), and found to represent a risk factor. Of note, Ureaplasma spp. were mostly identified in patients aged 60 and above with prostatic specific antigen (PSA) level > 4 ng/ml and an invasive malignant prostate tumor (Gleason score 8–10).PCR amplification showed no positive results for Ureaplasma spp. with PCa arguing in favour of their potential involvement in this condition. Yet, this finding, though statistically supported, warrants a thorough investigation at a much larger scale.This study uncovered a significant association of The online version contains supplementary material available at 10.1186/s13027-021-00344-9. Streptococcus bovis to colon cancer [Salmonella thyphii to gallbladder cancer [Chlamydia pneumoniae to lung cancer [Bartonella species to vascular cancer [Helicobacter pylori to gastric cancer [Cancer is a major public health issue, considered as one of the leading causes of death worldwide. According to latest records of the International Agency for Research on Cancer, World Health Organization (WHO), the Prostate Cancer (PCa) ranked fourth among the most common cancers worldwide with 1.28 million cases . In factn cancer , Salmoner cancer , Chlamydg cancer , Bartoner cancer , and Helc cancer , 20. Yetc cancer , it is sMycoplasma pneumoniae, which was among the first species suspected to be associated with human leukemia [M. fermentans, M. penetrans, and M. hyorhinis has been demonstrated in vitro [ras and c-myc. Prolonged infection with mycoplasma was found to lead to prominent chromosomal alteration , to morphological changes, and to uncontrolled cell growth [M. hominis, M. genitalium, and U. urealyticum, a potential involvment in PCa has been suggested since these species were detected by PCR in patients suffering from this type of cancer [Regarding mycoplasmas, the smallest known free-living bacteria, their oncogenic potential and role in cancer development have been investigated as early as the 1960s . Actuallleukemia . Since tleukemia . Howeverin vitro –27. Addil growth . For M. f cancer –33. Thesf cancer , 35.A rising incidence of PCa was observed in Asian patients from China, India, and Malaysia , 37. It’M. genitalium, M. hominis, M. fermentans, U. urealyticum, and U. parvum by PCR amplification targeting species-specific genes.Here, we investigated the possible involvment of urogenital mollicutes in PCa in a cohort of Saudi patients from Aseer region. We sought to demonstrate the presence of A total of 105 Saudi patients with inflamed, swelling, and painful prostate gland, referred to Aseer Central Hospital  during the years 2010 to 2017, were enrolled in this work. All patients were presenting suspicious and abnormal digital rectal examination (DRE) findings and/or elevated PSA (Prostate Specific Antigen) level (≥ 4 ng/ml). Patients age ranged from 46 to 104 years. Data about Gleason score and PSA were recorded.Prostate specimens were obtained from patients either by transrectal ultrasound (TRUS)-guided biopsy or by surgery . Both procedures were carried out by specilized physicians in the Central Hospital of Aseer Region .TRUS biopsy was performed using an endfiring 7.5-MHz biplane transrectal probe attached to an ultrasonography device . No local anesthetic injection was used as most of the patients tolerated the procedure very well. However, all of them received a general pain killer (75 mg intramuscular pethidine (demerol) injection pre-procedural statin). Biopsy was performed half an hour after pethidine injection. To prevent patients from post-interventional complications, three oral doses of Ciprofloxacillin (500 mg) were administrated to them before, during, and after the biopsy procedure.TURP was undertaken by urological surgeons. The procedure was carried out under general anaesthesia using bipolar devices. Gentamicin antibiotic (160 mg) was administrated intravenously to patients 1 h before the TURP surgical procedure.All patients specimens were placed in biocassettes and were dehydrated in histokinette with 10% formalin solution for 24 h. Then, they were embedded in paraffin blocks, sectioned with a microtome into slices of 4 μm thick and stained with hematoxylin-eosin (H & E). Differentiation between the benign and malignant prostatic specimens, as well as the aggressiveness classification of the cancerous tissues according to Gleason score  were donFormalin-Fixed Paraffin-Embedded (FFPE) prostate tissues were forwarded to the laboratory of mycoplasmas, Institut Pasteur, Tunis, for further manipulations.Total genomic DNA was extracted from sections of FFPE prostate tissue using the QIAamp® DNA FFPE Tissue Kit  according to the supplier’s instructions. For each biopsy, up to eight sections of 5 to 10 μm thick were cut using a microtome and placed in a sterile 2-ml microcentrifuge tube. Sections of FFPE prostate tissue were subjected to paraffin dissolution using xylene , followed by homogenization and enzymatic digestion with proteinase K and lysis buffer. Samples were incubated overnight at 56 °C and lysates were purified using the QIAamp MinElute columns to obtain high quality DNA for PCR.M. hominis PG21 (ATCC 23114), M. genitalium G37 (ATCC 33530), M. fermentans PG18 (ATCC 19989), U. urealyticum (ATCC 27618), and U. parvum (ATCC 27813), in order to be used as controls in the PCR reactions. These mollicutes species were cultivated on appropriate SP4 broth medium, prepared according to the previously described formulation [Using the classical phenol/chloroform DNA extraction method , genomicmulation . AntigenQuantity and quality of DNA were assessed by Nanodrop absorbance measurement and by electrophoresis on 1% agarose gel stained with CYBR safe. The obtained purified DNAs were stored at − 20°С until needed.p120’ gene (coding for DUF885 family protein) for M. hominis, mgpA gene (coding for Adhesin P1 protein) for M. genitalium, the gene conding for the Insertion Sequence like-element (IS1630I) for M. fermentans, and ureB gene (coding for beta subunit of the urease enzyme) for Ureaplasma spp. An internal control specific to the human mitochondrial cytochrome c oxidase subunit III gene (named MT-CO3) was also included. Details about these target genes and their respective primer sequences are presented in Table Taq buffer, 1 mM MgCl2, 0.2 mM dNTP , 1 pmol of each primer, 1.5 U of HotStarTaq DNA polymerase , and 1–2 μl (approximately 150 ng) of genomic DNA. All samples were subjected to a first denaturation step at 95°С for 10 min and then to 35 cycles at 94°С for 1 min (denaturation), 55°С for 1 min , and 72°С for 1 min (elongation). The cycling was ended by an extension step at 72 °C for 10 min. Ten microliters of each amplicon were electrophoresed on a 2% agarose gel stained with CYBR safe and visualized under UV light.For each mollicutes species, PCR assays were designed to amlify 16S rRNA gene along with a specific gene fragment; PCR products were cleaned-up using the ExoSAP protocol. For this purpose, exonuclease I  and shrimp alkaline phosphatase  enzymes were used to remove leftover primers and remaining dNTPs, respectively. Sequencing was performed using the BigDye Terminator v3.1 cycle sequencing kit , according to the manufacturer’s instructions. Sequencing products were run in Applied Biosystems® 3130 Genetic Analyzer (USA) available at the sequencing facility of Institut Pasteur, Tunis. For each PCR amplicon, both strands were sequenced. The derived nucleotide sequences were aligned with reference sequences downloaded from GenBank using the BioEdit Sequence Alignment Editor, version 7.2.5.P value < 0.05 was considered statistically significant. Odds ratio with a 95% confidence interval was also calculated to estimate the role of mollicutes as a risk factor in PCa disease. Odds ratio values > 1 indicated that mollicutes infections might be a risk factor for the PCa. All these tests were performed using the Statistical Package for Social Science (SPSS) 20.0 software .Statistical analyses were performed using Excel tools  to assess the prevalence of mollicutes species among the studied population. The chi-square test was computed to evaluate the potential relationship between the urogenital mollicutes infections and PCa. The mean age of Saudi men included in this study was 76.08 years for those suffering from PCa and 72.18 years for those diagnosed with BPH. Within both groups, patients aged between 70 and 79 years were the most frequent . In both groups, the least common patients were those aged under 60, particularly in the PCa category with only 2 cases (4%). Regarding PSA records, levels were > 4 ng/ml in 92% (48/50) of patients with PCa and 70% (38/55) of patients displaying BPH. Interestingly, high PSA levels exceeding 20 ng/ml were recorded for a large number of PCa patients (62%), whereas only 13% amongst BPH cases showed such high levels. After anatomopathology examination, Gleason score attribution was only applied to patients suffering from PCa. Patients with aggressive PCa were found to be nearly three times more frequent than those with non-aggressive PCa . The characteristics of the study population are summarized in Table Electrophoresis and Nanodrop quantification have shown that genomic DNA extracted from all mollicutes reference strains as well as DNA collected from all FFPE human samples were of high quality and quantity (DNA concentration ranged from 100 to 1750 ng/μl). This has been confirmed by the efficient amplification of a 208-bp fragment of the human mitochondrial DNA. Indeed, all the 105 samples (100%) produced this targeted fragment at its expected size . Interestingly, PCR-based detection of ureaplasma species was positive in 18 cases. The biotyping of Ureaplasma spp. revealed U. parvum and U. urealyticum in ten (20%) and eigth (16%) samples, respectively. The 99-bp and 100-bp PCR products corresponding to the amplification of U. parvum and U. urealyticum specific urease coding genes are shown in Figs. Ureaplasma spp. . The Odds Ratio values were found to be infinite, suggesting that infection with each of ureaplasma species could constitute a risk factor in PCa disease. Results of mollicutes detection in archival tissues are summed up in Table None of the 105 prostate samples was found to contain DNA of mycoplasma species. Indeed, all PCR amplifications targeting 16S rRNA and specific genes of m in ten 0% and ei Figures  and S2. Ureaplasma spp. positive PCR were detected in 15 patients with PCa. These positive cases were distributed as follows; 7 patients were found to be infected with only U. parvum, 5 with only U. urealyticum, and 3 were co-infected with both species. Based on their Gleason score, tumors of most of the PCa patients infected with U. urealyticum are categorized as aggressive . For those infected with U. parvum, the rate of aggressive tumors was also high .The 18 Ureaplasma spp. were detected, 12 were diagnosed with an aggressive PCa (Gleason score between 8 and 10), which represents 80% (12/15). These 15 patients were found to belong to different age intervals. Aside from one PCa patient, all the others  are aged more than 60 years. Moreover, the majority of these patients  showed high PSA levels, exceeding 20 ng/ml. The caracterization based on different parameters  of the group of patients diagnosed with PCa and found to harbor Ureaplasma spp. DNA is presented in Fig. Considering both ureaplasma species and taken into account the three cases of co-infection, statistics showed that among the 15 patients in which Helicobacter pylori in the case of gastric cancer [Because of its wide-ranging impact on the human health and social life, cancer has prompted scientific research to delve into its causes and risk factors. Millions of new cases and deaths are recorded worlwide every year . Severalc cancer  as well c cancer .Chlamydia trachomatis and Trichomonas vaginalis, the prostatitis-associated Escherichia coli and Pseudomonas, human papilloma virus, and the pro-inflammatory bacteria Propionibacterium acnes [While the role of viruses in carcinogenesis has long been established, the possible involvement of bacteria is beginning to gain more and more acceptance –57. Withum acnes . Howeverum acnes , 60. Verum acnes , 62.M. hominis, M. genitalium, M. fermentans, U. urealyticum, and U. parvum) in prostate tissues from KSA patients with PCa or BPH, using PCR coupled to nucleotide sequencing. In KSA, no studies have been undertaken so far dealing with the etiopathogenesis of PCa. The only available data are about the incidence and mortality rates related to this cancer [In this study, we have searched for the presence of a panoply of urogenital mollicutes species . This rate is the highest among the reported cases. Indeed, only one case of positive U. urealyticum PCR was reported in each of the Australian and the Iranian studies already mentioned above [U. parvum was identified at a rate of 20% (10/50). This is the first study that reports the detection of this species in patients with PCa. Furthermore, the coinfection with U. urealyticum and U. parvum of the same patient with PCa is a new finding reported for the first time by our study. However, this result remains to be consolidated. Apart from some new clues unveiled by our study, we found some similarities with other studies in terms of species identification and rates. This could explain the role played by several factors such as hereditary susceptibility, environmental factors, or even the methods used to identify Mycoplasma species and their genes [Ureaplasma spp. only in patients suffering from PCa lends further support to the hypothesis suggesting their involvement in the etiology of this type of cancer.A total of 15 Saudi patients tested were found to harbor ed above , 31. In ir genes . The facUreaplasma spp. is the primary cause of prostate carcinogenesis. However, according to the Gleason score values (8–10), the presence of Ureaplasma spp. could have contributed to the worsening of cancer progression. Indeed, patients with PCa harbouring ureaplasmas displayed invasive malignant tumours of the prostate. These findings are recorded in patients over 60 years old and with PSA values > 4 ng/ml. Like viruses, mycoplasmas are notoriously known for their ability to cause low-grade chronic inflammation and silent infection, a hallmark thought to gradually compromise the immune system of their hosts, thereby promoting cancer transformation. Nevertheless, their detection in tumour microenvironment does not imply that they are causally involved in carcinogenesis. Actually, many factors like the high prevalence of the infectious agent in the general population, the extended latency, the asymptomatic infections, and the immune system status of patients could make difficult establishing a causality link [In the case of our study, though the results are statistically supported, one can not formally conclude that the presence of ity link . Also, oity link .To sum up, the role of microbes in cancer is still a subject of debate and it is obvious that all these results further lead us to provide more evidence of the role that mollicutes can play in prostate cancer. Appropriate animal models and in vitro cell cultures could be very useful to achieve this goal.Ureaplasma spp. infection is in favor of their potential involvement in prostate cancer or, most likely, points to their contribution in worsening its progression. These data are worth to be considered by the Saudi health policy makers during decision-making processes regarding the control and follow-up of PCa epidemiology in KSA.To our knowledge, this study is the first to be conducted in KSA aiming to characterize the PCa from an etiological standpoint. The finding that only patients with PCa were significantly associated with Additional file 1: Figure S1. PCR amplification of Ureaplasma parvum 16S rRNA gene. Lane M: 1 kb + DNA ladder. Lanes 1–5: Specificity of primers of U. parvum 16S rRNA gene with DNA from human mitochondrion, M. hominis, M. fermentans, M. genitalium, and U. urealyticum. Lane 6: No DNA (negative control). Lane 7: DNA from U. parvum type strain ATCC 27845 (positive control). Lanes 8–15: DNA from prostate biopsies of patients (PCa cohort).Additional file 2: Figure S2. PCR detection of Ureaplasma urealyticum 16S rRNA gene. Lane M: 1 kb + DNA ladder. Lanes 1–5: Specificity of primers of U. urealyticum 16S rRNA gene with DNA from human mitochondrion, M. hominis, M. fermentans, M. genitalium, and U. parvum. Lane 6: No DNA (negartive control). Lane 7: DNA from U. urealyticum type strain ATCC 27618 (positive control). Lanes 8–15: DNA from prostate biopsies of patients (PCa cohort).


Escherichia coli ER2566 strain (NC_CP014268.2) was developed as a BL21 (DE3) derivative strain and had been widely used in recombinant protein expression. However, like many other current RefSeq annotations, the annotation of the ER2566 strain was incomplete, with missing gene names and miscellaneous RNAs, as well as uncorrected annotations of some pseudogenes. Here, we performed a systematic reannotation of the ER2566 genome by combining multiple annotation tools with manual revision to provide a comprehensive understanding of the E. coli ER2566 strain, and used high-throughput sequencing to explore how the strain adapted under external pressure.The lacI gene in the transcribed RNA, which was not detected at the genomic level by Sanger sequencing.The reannotation included noteworthy corrections to all protein-coding genes, led to the exclusion of 190 hypothetical genes or pseudogenes, and resulted in the addition of 237 coding sequences and 230 miscellaneous noncoding RNAs and 2 tRNAs. In addition, we further manually examined all 194 pseudogenes in the Ref-seq annotation and directly identified 123 (63%) as coding genes. We then used whole-genome sequencing and high-throughput RNA sequencing to assess mutational adaptations under consecutive subculture or overexpression burden. Whereas no mutations were detected in response to consecutive subculture, overexpression of the human papillomavirus 16 type capsid led to the identification of a mutation  positioned 19-bp away from the E. coli ER2566 strain not only improved the RefSeq data but uncovered a key site that might be involved in the transcription and translation of genes encoding the lactose operon repressor. We proposed that our pipeline might offer a universal method for the reannotation of other bacterial genomes with high speed and accuracy. This study might facilitate a better understanding of gene function for the ER2566 strain under external burden and provided more clues to engineer bacteria for biotechnological applications.The ER2566 strain was used by both the general scientific community and the biotechnology industry. Reannotation of the  Escherichia coli expression system is one of the most well-characterized classical expression systems for recombinant protein expression in biological science. E. coli offers clear advantages over other expression systems, including a clear genetic background, fast breeding, low cost, high cell density cultures, and high protein expression levels [E. coli expression systems [E. coli ER2566 strain is a common laboratory tool that takes advantage of the expression and growth properties of the B line strain [The n levels –3. Indee systems . The E. e strain .Along with the rapid development of biological laboratory techniques, there has been a significant advance in sequencing technologies. However, this has not been matched by the production of better sequences; rather, sequencing advancements have led to the deposition of an increased number of “draft” bacterial genomes into public databases , which tYcjW as a regulator of the complex interaction between carbohydrate metabolism and H2S production in bacteria [E. coli by Herring et al. led to the identification of mutations that conveyed a selective growth advantage during adaptation to a glycerol-based growth medium [Next-generation sequencing (NGS) is a cost-effective tool for the study of gene function and experimental bacterial evolution. Indeed, NGS technology was used by Luhachack and colleagues to successfully identify the function of the transcription factor bacteria , and whoh medium . Even thh medium , and bach medium , among oh medium .lacI gene at the RNA level, which may be involved in the transcription and translation of genes encoding the lactose operon repressor. Our reannotation and sequencing results will provide a better understanding of some of the biological processes of the ER2566 strain, and may offer insight into future biotechnological applications in bacterial engineering.In this study, we employed a series of automated annotations and combined this with manual inspections with high-throughput analyses to reannotate the ER2566 genome. As a result of our analysis, we further propose a universal reannotation pipeline for other bacterial genomes that can be undertaken with high speed and accuracy. Our reannotation eliminated 190 hypothetical genes and pseudogenes from the RefSeq annotation, and now includes an additional 237 coding sequences with definitive gene names and functions. The number of miscellaneous noncoding RNAs was also increased from 15 to 245. Subsequently, we applied whole-genome sequencing and RNA-sequencing to assess for mutational adaptations that occur following continuous subculture pressure or overexpression burden. We detected a mutation located within the 3′ non-coding region  19-bp away from the E. coli strain ER2566 through a reannotation pipeline, as illustrated in Fig. The process of genome reannotation combined with detailed manual reviewing encompasses the re-identification and labeling of characteristic features of a sequenced genome, and is a process that has been performed extensively for numerous organisms, including bacteria , 17. UnlWe employed a series of automated annotation tools combined with manual inspection to reannotate the ER2566 genome Fig. S. In our − 6, all CDSs were annotated to provide accurate information regarding the sequences and functions of the enrolled proteins. A total of 4023 (96.2%) of the 4180 CDSs were annotated as protein-coding genes, with the remaining CDSs  marked as hypothetical genes, with no registration in the Swiss-Prot database, and 21 CDSs (0.5%) marked as pseudogenes by manual inspection. To improve upon this prediction, three other well-established gene finders-GLIMMER, Zcurve and GeneMark-were independently used, identifying 4231, 4287, and 4213 CDSs, respectively. These putative CDS sets were subsequently filtered by Blastn against the first Prodigal-predicted CDS set. Overall, an additional 428 CDSs were found: 194 CDSs were identified using GLIMMER, 123 using GeneMark, and 201 using ZCURVE. These additional 428 CDSs were then searched against the Swiss-Prot database by Blastp with a stricter threshold e-value < 10− 10, coverage > 80%, and an identity > 70%. This filtered out 402 of these additional CDSs, resulting in an additional 43 genes. This led to a total of 4066 protein-coding CDSs (4023 + 43) included in the reannotation of the ER2566 genome, along with 136 CDSs for hypothetical genes.For the systematic reannotation of the CDS, the prediction and identification of coding genes occurred in two stages Fig. S. In the lacZ1, lacZ2, and ECBD_2906, respectively), and one related pseudogene, C2566_RS05305, was removed; these changes are consistent with previous results [lacY upstream and the lactose operon repressor gene lacI downstream, both of which are essential to the lac operon system. This reannotation had uncovered genes related to the transcription and translation of genes encoding the lactose operon repressor in ER2566 strain.Due to trimming or splitting, genes with real function can often be incorrectly assigned as pseudogenes through protein homology alignment. In our reannotation, we manually reviewed and analyzed 194 pseudogenes from the RefSeq database annotation. In total, 123 of the 194 pseudogenes were directly identified as coding genes and are now found in the reannotated list. While the remaining pseudogenes without any function had been retained. These newly identified protein-coding genes included 34 mobile genetic elements that encode transposases and had been considered to be important in evolution as a common type of genetic change. For instance, a genomic positive strand region , previously annotated as a pseudogene without function, was identified to harbor two genes, insA and insB, which are homologues of the insertion element protein, IS1, and related to DNA binding and transposase activity  is widely used to provide protein expression evidence and could confirm the validity of the annotation, which was used to identify the short protein-coding genes that have numerous functions . Thus, tE. coli ER2566 strain have been identified, including 85 tRNAs, 22 rRNAs, and 12 ncRNAs [Miscellaneous RNAs, such as transfer RNA (tRNA), ribosomal RNA (rRNA), and other non-coding RNAs (ncRNA), play pivotal biological roles in cellular activity. To date, about 119 RNAs molecules in the 2 ncRNAs . MeanwhiGenomic variations in bacterial species usually reflect an evolutionary response that occurs under various external—usually unfavorable—environmental stressors. Thus, we next performed variant calling to identify any nucleotide-level differences , insertions and deletions (indels), and/or structural variations) in the ER2566 strain. There are two approaches for variant calling: by mapping reads against the reference genome directly or by assembling a de novo genome to compare against a reference genome. In most cases, mapping reads produces a better resolution for SNPs and indels than genome assembly, whereas the latter is optimal for identifying structural variants and regions with high divergence. Here, we used both methods to interrogate the ER2566 genome Fig. .Fig. 4FE. coli ER2566 strain in our lab did not cause mutation in the genomic sequence.First, we re-sequenced the whole genome of the ER2566 strain grown in our laboratory under consecutive subculturing. Two different-sized insert libraries  were built, and a total of 10.0 million paired-end reads of 90 bp in length were generated using an Illumina HiSeq 2000. The raw reads were mapped to the C2566 reference genome (NC_CP014268.2) with a good coverage depth (> 100-times). No SNP or indel was detected. A pipeline optimized for longer assembly was designed to accomplish the re-sequencing of our ER2566 strain. Various de novo assembly softwares were used to construct a confident and long  scaffold, and assembly results for each step were assessed by alignment of final sequences back to the reference genome Fig. S. One invRNA-seq is widely used in quantitative gene expression studies for the identification of non-annotated transcripts and polymorphisms, and for RNA editing in transcribed regions. Thus, to identify any variations in the ER2566 genome due to overexpression pressure, we used RNA-seq to analyze the transcriptomes of the ER2566 strain growing at 37 °C without plasmids  or overexpressing human papillomavirus 16 type capsid protein L1 via plasmid-based inducible expression  . Cells were grown at 37 °C with sharking at 180 rpm in Luria-Bertani (LB) broth  under the pressure of continual passaging.The E. coli ER2566 with the pTO-T7-HPV16L1 vector was cultured in 250 mL LB broth containing 20 μg/mL kanamycin at 37 °C with shaking at 180 rpm. Upon reaching an OD600 of 1.0, 5 mL of culture was transferred into a flask containing 500 mL LB and 20 μg/mL kanamycin, and incubated at 37 °C with shaking at 180 rpm. At OD600 of 0.8, the culture was induced with a final concentration of 0.1 mM/L isopropyl-β-d-thiogalactopyranoside (IPTG) and incubated for 6 h at 37 °C with shaking at 180 rpm.The gene encoding human papillomavirus 16 type L1 (HPV16L1) was cloned into the pTO-T7 expression vector. Genomic DNA was extracted using a cetyltrimethylammonium bromide (CTAB)-based protocol . Total gCells were harvested by centrifugation at 7000 rpm for 10 min at room temperature and total RNA was extracted using the MasterPure RNA Purification Kit, according to the manufacturer’s protocol (Lucigen). DNase was added to reduce the chance of genomic DNA contamination. Total RNA was extracted in 50 μL RNase-free DEPC-treated water. RNA concentration was measured using an RNA Assay Kit in a Qubit 2.0 Fluorometer. A total of 3 μg RNA per sample was used as the input material for RNA sample preparations. Libraries of RNA-seq template were constructed using the NEBNext Ultra RNA Library Prep Kit for Illumina , following the manufacturer’s recommendations. Sequencing was performed on an Illumina HiSeq 2500 platform and 125-bp paired-end reads were generated .https://github.com/tseemann/barrnap), Infernal 1.1 [The ER2566 strain (NC_CP014268.2) whole genome was downloaded from the NCBI Reference Sequence Database as an input file for Prokka, a widely used annotation software that annotates a bacterial genome in about 10 min on a laptop . To attarnal 1.1  and MinCrnal 1.1  for our rnal 1.1 , GeneMarrnal 1.1  and ZCURrnal 1.1 ) were usThe quality of the raw reads were determined using FastQC , and appDraft contigs were created using SPAdes , with opAdditional file 1: Table S1. The list of the ruled-out genes in the reannotation.Additional file 2: Table S2. The list of newly added protein-coding in the reannotation.Additional file 3: Table S3. The list of complete CDSs in the reannotation.Additional file 4: Table S4. Comparison with BL21(DE3) and ER2566 annotation.Additional file 5. An integrated proteogenomics search database of ER2566 strain.Additional file 6: Table S5. The list of newly added miscellaneous ncRNAs in the reannotation.Additional file 7: Table S6. The transcription level of the newly added ncRNAs.Additional file 8: Table S7. The top 50 the highly expressed genes.Additional file 9. The re-sequenced ER2566 genome. (FASTA 4436 kb)Additional file 10. The reannotation of ER2566 genome.Additional file 11: Figure S1. The analysis pipeline for genomic re-annotation.Additional file 12: Figure S2. The workflow of CDSs reannotation.Additional file 13: Figure S3. Pairwise alignment and visualization. Assembly results for each step are assessed by alignment of final sequences back onto the reference genome. The visualization results are quickly achieved by Nucmer.


Professionals’ limited knowledge on mental health and their stigmatizing attitudes toward mental illness can delay the diagnosis of autism. We evaluated the knowledge on Autism Spectrum Disorder (ASD) and stigmatizing attitudes in 93 physicians at Dutch Youth and Family Centers (YFC). These physicians screen for psychiatric symptoms in children. We show that their general ASD knowledge scored 7.1 (SD 1.2), but their specific ASD knowledge was only 5.7 (SD 1.7) . Our physicians had positive attitudes toward mental illness (CAMI scores 2.18 (SD 0.33) to 2.22 (SD 0.40) on a 5-point Likert scale) but they had higher levels of stigmatizing attitudes than other Western healthcare professionals. Their levels were considerably lower than in non-Western professionals. We found no relations between ASD knowledge, stigmatizing attitudes and demographic variables. In conclusion, ASD knowledge and stigmatizing attitudes toward mental illness in Dutch YFC physicians require attention.The online version of this article (10.1007/s10597-020-00568-w) contains supplementary material, which is available to authorized users. Autism spectrum disorders (ASD), as described in the DSM-5 . The individual consultations focus on medical and developmental screening, while the collective program offers vaccinations and information programs  general information about ASD and its early detection, (2) early signs of ASD and early detection during consultation, and (3) communication and referral. Each session was preceded by homework consisting of background information on ASD and clinical assignments.We present the baseline measurements of the Dutch Live Online LearningThe online course was obligatory for 93 YFC physicians in the Greater Rotterdam area. Groups of eight to eleven physicians started the intervention study each month between January and November 2016. A few days before the start of the study, we invited the YFC physicians to a test session on the online learning environment. They were asked to complete 3 questionnaires (described below) at the end of this session. The day before the start of the intervention study, a member of our research team checked whether the physicians had completed the questionnaires. If not, they were asked to complete the questionnaire at the beginning of the first intervention session.We developed a two-part questionnaire, the Autism Spectrum Disorder Knowledge Questionnaire—physicians’ edition (AKQ-P)The AKQ-P was evaluated and revised in three stages. First, an expert panel of 25 psychologists and one social worker with experience in working with children with ASD answered and reviewed the questionnaire during a group meeting. Then this was repeated by 24 YFC physicians from the Dordrecht region in the Netherlands. Finally, the questionnaire was tested during a pilot intervention by five of the ten YFC physicians who had participated in the course’s development. All these physicians were not part of the intervention.We assessed stigmatizing attitudes toward mental illness using the Dutch translation of the Community Attitudes to Mental Illness (CAMI) questionnaire /Spooled) for all the comparable CAMI scale scores. A positive Cohen’s d value indicates that a study had a lower CAMI scale score than the score we had in our cohort. Cohen’s d represents a sizable difference if the 95% CI does not include zero, while effect sizes can be interpreted as small (0.20–0.49), medium (0.50–0.79) or large (≥ 0.80)  Cohen .All participants provided written informed consent before taking part in our study. The Medical Ethics Committee of Leiden University Medical Center approved the study, classifying it as not falling under the Dutch Act on Medical Research Involving Human Subjects (WMO) (ref. P15.131). All authors declared that they have no conflict of interest and certify their responsibility.Sample characteristics are presented in Table Our results show that general ASD knowledge was 7.1 SD 1.2), but specific ASD knowledge was less at 5.7 (SD 1.7) . A minority (9.7%) of the YFC physicians scored poorly on general ASD knowledge  and a much larger group (41.9%) scored poorly on specific ASD knowledge. Table , but speTable p < 0.05), and higher levels of benevolent attitudes toward people with mental illness (r(90) = 0.220, p < 0.05). We found no correlations between specific ASD knowledge, the CAMI’s social restrictiveness and community mental health ideology scales, age, experience and income level (p > 0.05). Nor were any correlations found between general ASD knowledge and these factors (p > 0.05).Table p = 0.901); the linear regression accounted for 2.8% of the explained variability. In adjusted analyses for sex, age, experience, and income level, the physicians’ general ASD knowledge score and ethnicity were entered into our regression, resulting in a non-significant prediction model  = 0.719, p = 0.656).To further evaluate the correlations we did find, we performed linear regression analyses, and could show that specific ASD knowledge was not associated with the authoritarianism score  = 0.361, p = 0.610) and accounted for 5.7% of the explained variability. In adjusted analyses for sex, age, experience, and income level, the physicians’ general ASD knowledge score and ethnicity were entered into the model, resulting in a non-significant prediction model  = 1.076, p = 0.388).To evaluate the CAMI’s benevolence scores, a second linear regression was performed. First, specific ASD knowledge score was entered, revealing that a higher specific ASD knowledge score was associated with a more positive benevolence attitude  = 0.752, Thus, our analyses found no relationships between general or specific ASD knowledge, stigmatizing attitudes toward mental illness, age, experience, or income level in the 93 YFC physicians.d. On 26/36 scales, the Dutch YFC physicians showed higher levels of stigmatizing attitudes toward mental illness than those seen in other Western healthcare professionals. However, on 20 scales that were compared with scores of non-Western professionals, Dutch YFC physicians had lower levels of stigmatizing attitudes.Figure We show that Dutch YFC physicians have sufficient general knowledge on ASD, but that a considerable number of them scored less well on specific ASD knowledge. They generally hold positive attitudes toward mental illness, but do show higher levels of stigmatizing attitudes than other Western healthcare professionals. They have lower stigmatizing attitude than non-Western professionals. We found no relationship between the level of ASD knowledge, stigmatizing attitudes toward mental illness and physician-related demographic factors.Specific autism knowledge, as measured by our knowledge questionnaire, was insufficient in 41.9% of them. These YFC physicians play a vital role in identifying ASD symptoms in children in the Netherlands as they screen around 95% of them between the ages of two weeks and four years  was developed for evaluating both ASD knowledge and stigma and has strong psychometric properties Below is the link to the electronic supplementary material.


Many CpGs become hyper or hypo-methylated with age. Multiple methods have been developed by Horvath et al. to estimate DNA methylation (DNAm) age including Pan-tissue, Skin & Blood, PhenoAge, and GrimAge. Pan-tissue and Skin & Blood try to estimate chronological age in the normal population whereas PhenoAge and GrimAge use surrogate markers associated with mortality to estimate biological age and its departure from chronological age. Here, we applied Horvath’s four methods to calculate and compare DNAm age in 499 subjects with type 1 diabetes (T1D) from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study using DNAm data measured by Illumina EPIC array in the whole blood. Association of the four DNAm ages with development of diabetic complications including cardiovascular diseases (CVD), nephropathy, retinopathy, and neuropathy, and their risk factors were investigated.p < 0.0001). DNAm age was not associated with the risk of CVD or retinopathy over 18–20 years after DNAm measurement. However, higher PhenoAge  and GrimAge  were associated with higher albumin excretion rate (AER), an indicator of diabetic renal disease, measured over time. GrimAge was also associated with development of both diabetic peripheral neuropathy  and cardiovascular autonomic neuropathy . Both HbA1c  and T1D duration  were associated with higher PhenoAge. Employment  and leisure time  physical activity were associated with lower Pan-tissue and Skin & Blood, respectively. BMI  and current smoking  were positively associated with Skin & Blood and GrimAge, respectively. Blood pressure, lipid levels, pulse rate, and alcohol consumption were not associated with DNAm age regardless of the method used.Pan-tissue and GrimAge were higher whereas Skin & Blood and PhenoAge were lower than chronological age (Various methods of measuring DNAm age are sub-optimal in detecting people at higher risk of developing diabetic complications although some work better than the others. CpGs are regions of DNA where a cytosine is followed by a guanine nucleotide. Cytosines within CpGs can be methylated, and CpG methylation levels affect gene expression. Many CpGs become hyper or hypo-methylated with age –4. In 20r| < 0.11) [Pan-tissue performed sub-optimally estimating fibroblast age in in vitro studies. Therefore, Horvath et al. described Skin & Blood DNAm age using a similar method to Pan-tissue which performed remarkably well across a wide spectrum of cells that are most frequently used in in vitro studies, including the blood (Supplementary Table  < 0.11) .Pan-tissue and Skin & Blood were both developed using chronological age as a surrogate for biological age. Therefore, they may not capture CpGs that signal departure of biological age from chronological age. In a newer method called PhenoAge, chronological age was replaced with a surrogate measure of phenotypic age developed using clinical data. A Cox penalized regression model was applied where the hazard of mortality was regressed on 42 clinical markers and chronological age to select variables for inclusion in the phenotypic age score. Nine clinical markers and chronological age were selected and used to estimate the 10-year mortality risk score which was then converted into units of years. Finally, the resulting phenotypic age estimate was regressed on CpG methylation levels using an elastic net regression model . However, telomere length, another indicator of aging, has been investigated in T1D, and it was found to be significantly shorter in T1D compared to non-diabetic subjects . Shorter–17 years apart, to investigate changes in DNAm age over time.Here, we investigated DNAm age calculated by all four methods in 499 subjects with T1D from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study and its association with diabetic complications  and their risk factors –16. We ap < 0.0001) (Table Characteristics of the subjects with EPIC DNAm data are summarized in Table 1) Table .Table 1p = 1.18E−4, 6.49E−3, and 1.03E−4, respectively). The difference between chronological age and PhenoAge did not differ significantly by chronological age  and GrimAge  were positively associated with repeated measures of albumin excretion rate  which remained significant after adjustment of HbA1c levels. The effect of GrimAge on AER increased over time (GrimAge × EDIC year interaction β (SE) = 0.0013 (0.0005), p = 5.10E−3) whereas effect of PhenoAge was not significantly different over time (PhenoAge × EDIC year interaction p = 0.85) (Table p = 9.24E−3) and cardiovascular autonomic neuropathy . These associations also remained significant after further adjustment for time-weighted HbA1c (Table Epigenetic ages were not significantly associated with the development of CVD or retinopathy. Although DNAm ages were not associated with estimated glomerular filtration (eGFR), both PhenoAge (5) Table . Pan-tisp = 8.00E−4) and GrimAge (p = 9.99E−5) compared to females whereas females had on average 1.5 years higher PhenoAge compared to males (p = 0.005) (Table p = 0.026) and 0.01 years per 1-month increase in T1D duration (p = 0.043) (Table β (SD) = 0.45 (0.29), p = 0.12) or intensive (β (SD) = 0.15 (0.48), p = 0.76) therapy group (interaction p = 0.56). Skin & Blood increased 0.09 years per one-unit increase in BMI (p = 0.048) (Table p = 0.045), and those who achieved one to two times the recommended level of physical activity during leisure time on average had 0.8 years lower Skin & Blood compared to those who did not achieve the recommended level (p = 0.022) (Table p = 9.03E−50). The other factors were not significantly associated with epigenetic ages (Table The univariable associations of different factors with EAAs are shown in Supplementary Table p < 0.0001) (Supplementary Table Characteristics of the subjects with 450K data are summarized in Supplementary Table p = 0.01) .Chronological age and all four epigenetic ages were highly correlated  . Association of C-peptide with Pan-tissue was not significantly different in the two treatment groups (p = 0.61). Sex, cohort, treatment group, T1D duration, and time-weighted HbA1c were not significantly associated with epigenetic ages  and their risk factors.All four epigenetic ages were correlated with chronological age and with each other, but there were significant differences between them. Pan-tissue and Skin & Blood were developed to predict chronological age in healthy individuals whereas PhenoAge and GrimAge used biological biomarkers associated with time-to-death to predict differences in life expectancy of individuals. In addition, they were developed and tested in datasets measured in different tissues by different arrays  and used different statistical methods. As a result, there have been only low to moderate correlations between them , 9. Pan-With the exception of PhenoAge, the difference between the epigenetic ages and chronological age decreased in older subjects. This is consistent with previous findings where longitudinal changes in Pan-tissue EAA were tracked using linear mixed models (LMMs) within five different cohorts and showed that epigenetic age increases at a slower rate than chronological age across the life span especially in older populations .N = 58) of CVD events. Another study did not find any significant association between Pan-tissue and incidence of CVD in women from African, Caucasian, and Hispanic ancestry [β = 1.10 and HR = 1.07, respectively) [We did not find significant association between epigenetic ages and development of CVD. Studies have investigated the association of Pan-tissue and risk of developing CVD in non-diabetic subjects. In 2543 African Americans, the hazard ratio of fatal coronary heart disease increased by 1.03 per year increase in Pan-tissue over a ≈ 17-year follow-up period (144 events) . Similarctively) . Howeverctively) . HoweverTo our knowledge, association of DNAm age with risk of developing nephropathy, retinopathy, or neuropathy has not been investigated before. We did not observe any significant association between DNAm age and development of nephropathy and retinopathy. However, we found higher GrimAge and PhenoAge to be associated with higher levels of repeated measures of AER, an indicator of decreasing renal function. These associations remained significant even after adjusting for time-weighed HbA1c indicating that at least part of the effects is independent of HbA1c levels. This result is consistent with previous findings where GrimAge has been associated with albuminuria in non-diabetic subjects . Of the Intensive therapy and keeping HbA1c levels close to the normal range has been associated with decreased risk of developing diabetic complications . In our Males had higher Pan-tissue and GrimAge compared to females consistent with previous findings , 21, 25 The majority of known risk factors for diabetic complications were not associated with the four epigenetic ages. Two studies have investigated the association of CVD risk factors with Pan-tissue in non-diabetic subjects, but they reported conflicting results , 25. In N = 63) using Illumina 450K array in whole blood and 16–17 years later in monocytes which gave us the opportunity to investigate the difference between the two arrays and the change in epigenetic age over time. In 450K whole blood data, on average, Pan-tissue had the highest estimated value whereas in EPIC data GrimAge was estimated higher than the other epigenetic ages. In addition, Skin & Blood, which was on average lower than chronological age in EPIC data, was on average higher than chronological age in 450K data. Therefore, it appears that the type of array can affect the estimated epigenetic age. However, this could also be due to subjects being highly selected (two extremes of HbA1c and complications risk) in 450K data. Epigenetic ages in whole blood and monocyte measured 16–17 years apart were always correlated indicating that DNAm age is consistent over time and in multiple cell types. This is consistent with previous findings showing that Pan-tissue is consistent across life span [We also investigated epigenetic age in a smaller subset . Theife span . In addiN = 132) are available for one of them [We investigated the physical distance between all CpGs that are included in Pan-tissue, Skin & Blood, and PhenoAge epigenetic age calculations and T1D GWAS loci , 37: all of them . Of thesWe found that although all four epigenetic ages are correlated with each other and with chronological age, however, there are significant differences between them in subjects with T1D. We also found that DNAm age is consistent over time, but type of array (450K vs. EPIC) and cell type can affect the estimated epigenetic age. None of the epigenetic ages were associated with CVD or retinopathy, but PhenoAge and GrimAge were both associated with decreasing renal function as measured by AER. GrimAge was also associated with both DPN and CAN. Only PhenoAge was positively associated with HbA1c levels and T1D duration, two major risk factors for diabetic complications. Some of the other risk factors of diabetic complications were associated with individual epigenetic ages. Therefore, it seems that the investigated epigenetic ages all work sub-optimally in detecting subjects with T1D who are at higher risk to develop complications. However, PhenoAge and specifically GrimAge performed better that Pan-tissue and Skin & Blood suggesting that including biomarkers associated with aging-related mortality improves the accuracy of DNAm measurement. Nevertheless, only some of the risk factors of diabetic complication which are also among the main factors associated with aging-related mortality in the general population were considered in their development (serum creatinine and glucose in PhenoAge and smoking pack-years in GrimAge), and major factors such as hypertension, lipid levels, BMI, and HbA1c which is a better indicator of glycemic levels in long-term compared to serum glucose were not considered , 9. InclThe study subjects were from the DCCT/EDIC study. Subjects with T1D aged 13–39 years were recruited into DCCT in 1983–1989 in two cohorts. The primary prevention cohort included participants with 1–5 years of diabetes and no pre-existing retinopathy or nephropathy. The secondary cohort included participants with 1–15 years of diabetes and pre-existing mild retinopathy. Subjects were randomly assigned to receive intensive or conventional diabetes therapy . The DCCN = 499) representing about 125 randomly selected adult subjects from each cohort-treatment group who provided informed consent and had sufficient DNA through a 2-year time period prior to DCCT closeout  . DNAm was also measured by Infinium Human Methylation 450K BeadChip array in a smaller subset from the DCCT/EDIC  in the whole blood during the same 2-year time period prior to DCCT closeout and in monocytes at EDIC follow-up year 16–17. These included 32 subjects from the conventional treatment group with mean DCCT HbA1c > 9.1% (76 mmol/mol) and significant progression of retinopathy and/or nephropathy from the DCCT closeout to EDIC year 10, and 31 subjects from the intensive treatment group with mean DCCT HbA1c < 7.3% (56 mmol/mol) and no development of retinopathy and nephropathy until EDIC year 10 [Genome-wide DNAm was measured in whole blood by Illumina Infinium Human Methylation EPIC BeadChip array in a subset of DCCT participants  [p value > 0.01 or > 10% probes with bead number < 3. Samples were also excluded if their SNP genotypes did not match with those from GWAS-array (concordance threshold = 0.8). Illumina HumanCoreExome BeadArray  data imputed to 1000 Genomes  was used for this comparison [The R package meffil (er 2018)  was usedmparison . One sammparison . Blood cmparison  implemenmparison .https://dnamage.genetics.ucla.edu/ (accessed December 2018) with the normalization option selected.Pan-tissue , Skin & CVD was described as any CVD from DNA collection date to EDIC follow-up year 20 .2 [Nephropathy was described as first occurrence of sustained (2 consecutive) eGFR < 60 ml/min/1.73 m2 , 47 or A2  from DCC2  was usedRetinopathy was defined as severe non-proliferative diabetic retinopathy (SNPDR), proliferative diabetic retinopathy (PDR), or clinically significant macular edema (CSME) from DCCT closeout to EDIC follow-up year 18 .Neuropathy was defined as DPN at EDIC year 13/14 and CAN at EDIC year 13/14 and/or EDIC year 16/17 .T tests were used to determine if epigenetic ages were significantly different from chronological age and if the four epigenetic ages differed significantly.Spearman correlation was used to test for correlation between chronological age and DNAm age and between the four epigenetic ages. Paired sample EAA was calculated by subtracting chronological age from epigenetic age . EPIC array was performed in seven batches. Therefore, batch was included in all multivariable analyses of EPIC data. Since whole blood is a combination of 7 different cell types  and their proportions affect DNAm and epigenetic ages, six predicted cell proportions were included as covariates in all multivariable analyses of whole blood. Neutrophils were excluded as the seven cell proportions sum to one.Cox proportional hazard models were used to test association of DNAm age with development of CVD, nephropathy, and retinopathy using EPIC data. Logistic regression was used to test association of DNAm age with development of neuropathy during EDIC. Subjects who developed complications during DCCT (before DNAm measurement) were excluded from their corresponding analysis. We also investigated association of DNAm age with repeated measures of renal function, eGFR , and AER  from DCCT closeout to EDIC follow-up year 18 using LMMs. Two models were fit for both Cox and LMMs. Model 1 included sex, age, and T1D duration at the time of DNAm measurement along with batch and cell proportions. Model 2 included all covariates in model 1 plus repeated cross-sectional measures of HbA1c .Additional file 1:.


We aimed to examine the global prevalences of central obesity according to age, sex, race, place of residence, geographical region, national income level, and the definitions of central obesity. MEDLINE and Embase were searched. Studies with sample size of ≥ 500 and investigated individuals aged ≥ 15 years were included. Metaprop (a Stata command) was adopted to conduct a meta-analysis of prevalence, and the Freeman-Tukey Double Arcsine Transformation was used to stabilize the variances. A random-effects model was used to evaluate the prevalence and 95% confidence intervals (CI) of central obesity. There were 288 studies involving 13,233,675 individuals in this analysis. The overall prevalence of central obesity was 41.5% (95% CI 39.9–43.2%). A higher prevalence was found in older individuals, female subjects, urban residents, Caucasians, and populations of higher income level countries. Regarding regional variations, the highest prevalence was found in Sothern America  and Central American . Its prevalence was rapidly rising from 1985 to 2014. From 1985–1999 to 2010–2014, younger subjects aged 15–40 years showed a more drastic rise in prevalence (16.3 to 33.9%) than subjects aged > 40 years (43.6 to 57.9%). Male individuals have a more drastic rise (25.3 to 41.6%) than females (38.6 to 49.7%). Major increasing in prevalence of the condition in the past three decades, particularly in certain subgroups. These findings could act as a useful reference to inform public health strategies to minimize the impact of central obesity on population health.The online version of this article (10.1007/s10654-020-00650-3) contains supplementary material, which is available to authorized users. Central obesity is defined by the World Health Organization defined central obesity as a waist circumference (WC) of greater than 94 cm and 80 cm for males and females, respectively. The International Diabetes Federation proposed different cut-off points for different ethnic groups  [4].Central obesity could contribute to an increased risk of many medical conditions, including cardiovascular diseases (CVD)Determining the regional and time-trend prevalence of central obesity is important as it may inform resource allocation and policy making to reduce its disease burden through health education, screening and early intervention. However, the reported prevalence of central obesity in existing literature may be affected by the research settings , the characteristics of the population groups studied , sampling methods, diagnostic criteria, and other factors. A systematic review is required to obtain a comprehensive examination of central obesity as a global disease burden. As there is no such previous study identified, we aim to perform a systematic review and meta-analysis of the worldwide and time-trend prevalence of central obesity.MEDLINE and Embase were searched for population-based, epidemiological studies reporting the prevalence of central obesity from our previous database of metabolic syndrome. A pre-determined search strategy (Supplementary Table 1) was used to search literature according to the quality of reporting of the MOOSE  guidelines (Supplementary Table 2) A multidisciplinary group conducted the meta-analysis led by MCSW with JH, JW, PSFC, and VL as reviewers. Consensus was reached by referral to a third reviewer (XC) when there was disagreement. All returned citations were screened by title and abstract first, followed by full texts if relevant. The pre-determined criteria in the initial screening stage were studies (1) investigating the prevalence of central obesity; (2) using observational design; (3) reporting original data. Citations remained were eligible for full-text screening. Only population-based studies were reviewed, and they were defined as those that involved all residents in a specific region as the sampling frame based on a sampling method that was representative of that region. Additionally, the studies should: (1) have a sample size of no less than 500 participants; (2) have investigated individuals aged no less than 15 years; (3) adopt clinical approaches of Adult Treatment Panel (ATP III), International Diabetes Federation (IDF), World Health Organization (WHO) or Joint Interim Statement (JIS) to assess central obesity; and (4) contain sufficient information to calculate the number of individuals with central obesity. If there were citations based on the same study, the one reporting the most detailed information was used.Basic information collected from the individual studies consists of the name of first author; year of publication; study time period (the period in which the study was performed); country and region of recruitment ; age range; sex; as well as ethnicity of the study participants. Relevant information was extracted to estimate prevalence, and the data retrieved included definitions of central obesity; sample size and case numbers; and crude/age-specified/sex-specified prevalence rate. Different criteria of central obesity were shown in Supplementary Table 3. The classification of regions including income group were clarified in Supplementary Table 4. Two reviewers  independently evaluated the quality of each included citation using the modified Newcastle–Ottawa-Quality Assessment Scale (NOS) Stata version 14.0 . The graphic compositions were performed by R version 3.3.2 (R Core Team).A systematic, analytical method was used to compute the pooled prevalence rate of central obesity from all included studies. A Stata command, “metaprop”, was adopted to conduct meta-analysis of rates to generate pooled estimates with exact binomial and score test-based confidence intervals (CIs) In the literature search, 29,095 citations were identified, of which 20,160 were from Embase and 8,935 were from MEDLINE  were judged to have high quality in both patient definition and data representativeness. Prevalence figures were presented for Western Europe (11 studies), Northern Europe (10), Eastern Europe (10), Southern Europe (21), Eastern Asia (100), Western Asia (25), Southern-Central Asia (30), South-Eastern Asia (8), Northern America (31), Central America (5), Southern America (21), and Africa (16). Trained staffs were recruited to measure the waist circumference in 273 studies (94.8%) while other studies did not mention how the data were collected .2 99.9%). Time trend was classified by 4 periods , 38.3% , 46.3%  and 48.3% , respectively. Regarding age-specific prevalence, the older group (age > 40 years)  had a higher prevalence than the younger group (15–40 years) . Besides, the overall prevalence was higher in female  than male individuals .The results of meta-analysis were presented in Figs. 2 99.6%) during 1985–1999 to 33.9%  during 2010–2014. For adults aged > 40 years, it increased from 43.6%  during 1985–1999 to 57.9%  during 2010–2014. We chose the age of 40 years as a cut-off due to this value was adopted in more primary studies. For male individuals, the prevalence increased from 25.3%  during 1985–1999 to 41.6%  during 2010–2014. For female adults, it increased from 38.6%  during 1985–1999 to 49.7%  during 2010–2014.When the time trend was analysed by different sex and age groups, an even sharper increase was observed among young adults and male subjects than other subgroups Fig. . Among a2 99.8%) had a higher prevalence than individuals living in rural regions  . Diagnostic criteria using WHO, ATP, IDF and JIS are the most common used. The prevalence of central obesity based on WHO is 53.6% , ATP is 35.9% , IDF is 48.3%  and JIS is 35.9% . When compared with Caucasian  and African  population, Asian people  were reported to have lower prevalence. Regarding regional variations, the highest prevalence was found in Sothern America  and Central American  followed by Southern Europe  . The prevalence in Africa was 49.6% . The prevalence was higher in high-income  than low-income countries .Individuals living in urban regions , criteria (p = 0.099–0.849), measurement method (p = 0.657), or study quality (p = 0.330). In the univariate meta-regression analysis age (p = 0.007), region (p = 0.042), place (p < 0.001), period (p < 0.001), and study quality (p = 0.042) were associated with the heterogeneity observed. However, in the multivariate regression analysis, only age (p = 0.001), place (p < 0.001), and period (p < 0.001) remained to be the sources of heterogeneity. It was found that the prevalence of central obesity was higher in studies on older individuals  1.23, 95% CI 1.09–1.38), residents in urban regions , and the more recent decade .We performed a meta-regression analysis to investigate study-level factors that may impact the estimation on prevalence of central obesity and contribute to heterogeneity across studies (Supplementary Table 7). The results showed that the estimation on prevalence of central obesity was not substantially altered by region .This systematic review provided a comprehensive and up-to-date analysis on the global prevalence of central obesity by different sociodemographic characteristics, its various diagnostic criteria, national income of countries where the study subjects were living in; as well as its temporal tend by age and sex, respectively. We found a rising trend in overall prevalence since the 1990s and this trend was more drastic in young adults and male individuals. A higher prevalence was found in older subjects, females, urban regions, Caucasians, and people from higher income countries.The overall prevalence of central obesity was estimated to be 41.5% (95% C.I. 39.9–43.2%), with an obvious increase since the 1990s from 31.3% (1985–1999) to 48.3% (2010–2014). This increasing trend of prevalence in central obesity could be attributed to economic development and urbanization which could lead to an unfavourable change in dietary habits  The prevalence of central obesity among individuals aged > 40 were around twice as much as that in younger adults aged 15–40 (48.0 vs. 23.8%). This is well understood by researchers as the basal metabolic rate is lower in old adults than in young adults The global prevalence of central obesity was estimated to be higher among females when compared with males . In additional to the biological differences where females generally have higher body fat proportion than that of males and need more essential fat, cultural factors and social restrictions may also explain this gender difference. Women generally have less physical activity because of a lower education level, sedentary lifestyle and a higher level of housework engagement The prevalence of central obesity was 44.7% in high-income and 43.6% in upper-middle income countries, compared with 30.1% in lower-middle income and 30.6% in low-income countries. Economic development is associated with a high risk of obesity I2 > 98%). The included studies had a long-time span (from 1985 to 2014); adopted different sampling methods; and possessed a huge between-study variation in sample size and age range. Nevertheless, a pervious study indicated that the measurement of heterogeneity by I2 can be influenced by large sample size and could be large (> 75%),This study was the first comprehensive meta-analysis that examined the global prevalence of central obesity taking sociodemographic variables, peoples’ races, geographical regions, and national income into consideration. It has a large sample size of over 13 million subjects. However, several limitations should be addressed. Firstly, the degree of heterogeneity in this study was large  may represent cost-effective means to control its growing burden. However, the measurements should be tailored for individual country or population as the epidemiology of central obesity could vary between countries or populations.MCSW, JH, JW, and ZJZ participated in study concept and design. MCSW, JH, JW, PSFC, VL, XC, CL and ZJZ participated in acquisition, analysis, or interpretation of data. MCSW and JH drafted the manuscript. All authors, including HHXW and XQL, provided critical revision of the manuscript for important intellectual content. All authors read and approved the final manuscript. All authors included on a paper fulfil the criteria of authorship. There is no one else who fulfils the criteria but has not been included as an author.Supplementary file1 (DOCX 277 kb)Below is the link to the electronic supplementary material.