Only the posterior limb of the internal capsule (IC), comprised primarily of corticofugal fibers, showed higher axial diffusivity in 22q11DS. 22q11DS patients showed higher mean fractional anisotropy (FA) in callosal and projection fibers (IC and corona radiata) relative to controls, but lower FA than controls in regions with predominantly association fibers. Psychotic illness in 22q11DS was associated with more substantial diffusivity reductions in multiple regions. Overall, these findings indicate large effects of the 22q11.2 deletion on WM microstructure, especially in major cortico-cortical connections. Taken together with findings from animal models, this pattern of abnormalities may reflect disrupted neurogenesis of projection neurons in outer cortical layers.22q11.2 deletion syndrome (22q11DS)—a neurodevelopmental condition caused by a hemizygous deletion on chromosome 22—is associated with an elevated risk of psychosis and other developmental brain disorders. Prior single-site diffusion magnetic resonance imaging (dMRI) studies have reported altered white matter (WM) microstructure in 22q11DS, but small samples and variable methods have led to contradictory results. Here we present the largest study ever conducted of dMRI-derived measures of WM microstructure in 22q11DS . Using harmonization protocols developed by the ENIGMA-DTI working group, we identified widespread reductions in mean, axial and radial diffusivities in 22q11DS, most pronounced in regions with major cortico-cortical and cortico-thalamic fibers: the corona radiata, corpus callosum, superior longitudinal fasciculus, posterior thalamic radiations, and sagittal stratum (Cohen’s  It is the most common chromosomal microdeletion syndrome, with a prevalence of 1 per 3000 to 4000 live births . The delWM microstructural properties can be quantified noninvasively using diffusion magnetic resonance imaging (dMRI). Fractional anisotropy (FA), a widely used measure of white matter (WM) microstructural organization, is derived from a common dMRI reconstruction method, diffusion tensor imaging (DTI), and may reflect the coherence and density of fiber tracts in a voxel. Other DTI indices, axial diffusivity (AD) and radial diffusivity (RD), are also altered in a range of brain diseases . For exaDisturbances in WM microstructural organization have been frequently reported in 22q11DS; however, studies to date have been relatively small, with highly variable findings. While many studies reported lower FA in 22q11DS compared to healthy controls (HC) in major WM tracts, including commissural, association and projection fibers –22, seveContrasting findings in prior studies may also be due to different analytical techniques, ranging from tract-based spatial statistics (TBSS ) to voxeWM differences associated with psychosis are of interest in 22q11DS. Psychotic symptoms in 22q11DS have been associated with higher FA and lower WM diffusivities, but not always in the same regions across studies , 33, 34.Are there consistent group differences in WM microstructure between 22q11.2 deletion carriers and demographically matched HC?Are there differential age effects between groups, suggesting altered WM development in 22q11DS?Do 22q11DS participants with a psychotic disorder show more severe WM alterations, and do these differences overlap with those found in idiopathic schizophrenia?Does deletion size impact DTI indices?Is WM microstructure related to cognitive abilities, in 22q11DS and in HC?To address these uncertainties and determine factors that affect WM abnormalities in 22q11DS, the 22q11DS Working Group of the Enhancing Neuroimaging Genetics through Meta-Analysis Consortium (ENIGMA-22q11DS) performed a coordinated analysis of the raw dMRI data from ten independent studies, and meta-analyzed group differences and their modulators. We addressed these questions:dMRI data were contributed from ten previously collected studies to be analyzed as part of the ENIGMA-22q11DS working group. This analysis included 594 participants: 334 with 22q11DS  and 260 HC . Demographic characteristics are shown in Table All sites conducted structured diagnostic interviews at the time of scanning to determine lifetime psychiatric diagnoses. Wechsler IQ assessments were used to assess cognitive function  . The larAcquisition parameters of dMRI and T1-weighted MRI scans for each site are shown in Supplemental Tables meta-analysis, which runs statistical comparisons for each site separately and combines the summary statistics across sites, and a mega-analysis, in which data are harmonized and pooled from individual subjects, and statistical analysis is run on the full group. The meta-analysis included 540 subjects: 278 22q11DS probands  and 260 HC  from nine independent datasets derived from eight sites . Critical p-values were calculated for each set of models, specifically: (1) meta-analysis; (2) mega-analysis; and (3) mega-analysis including diagnosis-by-age interaction. Effect sizes were derived as explained in Supplemental Methods We used the Benjamini & Hochberg method to control for the family wise error rate . The persis; and  mega-anat-test for means with outlier removal (α = 0.05). Thereafter, we calculated the percent change of each DTI measure for each ROI from age 6 (minimum age in both groups) to peak/minimum, and from peak/minimum to age 46 and 52 . We compared the percent changes of each DTI measure for all ROIs between 22q11DS and HC groups by using Yuen’s method with bootstrap-t for trimmed means (α = 0.05) 2 and sex were included as covariates. FDR correction was performed as specified above (Section “Effects of 22q11DS and age on DTI-derived measures”).To assess potential differences in WM architecture as a function of clinical and genetic variability, we examined the effects of psychotic illness (35 with psychotic disorder vs 191 without psychosis) and deletion size (206 AD vs 15 AB) on DTI measures, within individuals with 22q11DS. In addition, given that IQ is a group-associated variable, we examined partial correlations with IQ within the 22q11DS , for both analyses. In contrast, ROIs in association fibers—the superior longitudinal fasciculus (SLF), fornix/stria terminalis (FXST), and external/extreme capsules (EC)—showed significantly lower FA in 22q11DS relative to HC . Figure d ~ 1.0) in the PCR and posterior thalamic radiation (PTR); both contain mostly thalamo-cortical/cortico-thalamic and corticofugal fibers from posterior brain areas. For all 18 ROIs, MD was lower in 22q11DS, as was AD, for 15 of the 18 ROIs. Only the PLIC showed significantly higher AD in 22q11DS relative to HC. For RD, all ROIs showing significant differences (15 of 18 ROIs) were lower in 22q11DS than HC, with largest effects (d ~ 0.7) in the corpus callosum and PCR , we wanted to determine whether the development of WM appears delayed or altered in 22q11DS. As shown in Supplementary Table We also investigated Poisson regression models to further evaluate effects of age on WM development. These models did not provide a substantially better fit to the data than the linear regression model used above, as determined by the residual standard error of the fits . Overall, these findings confirm that WM differences detected by DTI diffusivity measures are more severe in 22q11DS patients with psychotic disorder, and are particularly evident in young adulthood.Are the deletion-related WM changes more severe in those with psychotic disorder? Relative to 22q11DS subjects without psychosis, 22q11DS subjects with psychotic disorder showed overall lower diffusivity values, with significantly lower AD in the ALIC and PTR, both predominantly containing thalamic radiation fibers, in the cingulum of the cingulate gyrus (CGC) and the SLF, which mostly contain fronto-parietal and fronto-temporal association fibers, and the sagittal stratum (SS), which contains both posterior thalamic projection and temporal association fibers. 22q11DS-Psychosis was also associated with significantly lower RD and MD in the GCC, which contains callosal fibers, and significantly lower MD in the PLIC, where the superior thalamic radiation and cortico-pontine fibers are the major constituents. These differences were seen primarily between ages 20 and 26 for most ROIs; some ROIs  showed differences by age 16–17 Fig. . OverallNext, we compared our results for 22q11DS cases with and without psychosis to schizophrenia case-control results (2359 HC vs 1963 schizophrenia patients) , plottedDoes the extent of the deletion affect WM microstructure? Subjects with the large A–D deletion showed a trend toward lower AD in the anterior corona radiata and EC, and higher FA in the TAP; however, there were no statistically significant differences in relation to deletion size, after multiple comparisons correction , assessed by DTI. Our analysis pipeline , 40 alloIn contrast to findings in many neuropsychiatric disorders , 52, ourOur findings of higher FA in 22q11DS relative to controls in ROIs in commissural tracts , no detectable differences in ROIS where projection fibers predominate , and lower FA in ROIs in long association tracts  are consistent with findings in the mouse model of 22q11DS . SpecifiLgDel 22q11.2 mouse model mentioned above [We speculate that our findings may be related to three types of histopathological alterations in the WM of 22q11DS patients, all of which could reduce diffusivity. First, a recent neuropathology study of a 3-month-old infant with 22q11DS reported decreased neuronal frequencies in outer cortical layers and increased neuronal frequencies in deeper cortical layers . This ised above . Pyramided above . These aed above , 60, ulted above –63, and ed above , 55. PLIed above , 58, suged above , 63. FurSecond, DTI abnormalities may also reflect gliotic changes secondary to microvascular insults. Postmortem findings in 22q11DS adults indicate both deep WM gliosis associated with cerebrovascular changes . GliosisThe age trajectories of FA, MD, RD, and AD, as well as peak and minimum age estimates of our control sample, were similar to those reported previously . HoweverConsistent with some single-site studies suggesting inverse correlations between psychotic symptom severity in 22q11DS and diffusivity in the CC and long association tracts –31, 33, Notably, WM microstructural alterations in 22q11DS with psychosis showed a largely opposite pattern from those seen in idiopathic schizophrenia, involving primarily FA being higher (rather than lower), and lower (rather than higher) diffusivity measures. A previous single site study of 22q11DS and youth at clinical high risk for psychosis reported this directionally opposite pattern as well . This isWe did not find consistent effects of deletion size on WM architecture, and found little evidence that the relationship between WM microstructure and IQ differed between 22q11DS cases and HC. Sample size was quite limited for the A–B deletion type, and imaging protocols varied across sites, which may have affected our results. In addition, given highly variable psychotropic medications and medical comorbidities in 22q11DS patients, their effects could not be systematically investigated here. Previously, in a sample including many of the same participants as in the current analysis, we found that psychotropic medication was not significantly associated with cortical thickness or cortical surface area in 22q11DS patients . AdditioFuture studies with multishell acquisitions and novel biophysical models may resolve the contribution of the intra- and extra-axonal volume fractions and axonal diameters to these abnormalities , 73. QuaCollectively, our findings indicate large effects of the 22q11.2 deletion on WM microstructure. Diffusivity was more consistently affected than FA. In animal models, disruptions to predominantly cortico-cortical and cortico-thalamic/thalamo-cortical connections in 22q11DS may be attributable to disrupted early neurogenesis. Future translational studies will help to determine the neurobiological underpinnings of these alterations.Supplementary MethodsSupplementary TablesSupplementary Figures


Each year, about 15 million babies in the world are born too prematurely. Complication of preterm birth is the single largest direct cause of neonatal deaths and the second most common cause of under-5 deaths after infection. Therefore, assessing the proportion of preterm birth and associated factors among Mothers who gave Birth in Debretabor town health institutions have a paramount importance in designing an effective strategy to intervene.In this study preterm birth was 12.8%. Obstetric complication , maternal Mid Upper Arm Circumference less than 24 cm , antenatal care follow up < 4 visits , being HIV positive , Premature Rupture Of membrane , and being Anemic  were found to be statistically significant. Proportion of preterm birth was high in Debretabor town. Timely identification of obstetric complications and health education to improve antenatal care utilization will minimize the proportion of preterm birth. Preterm birth is defined by WHO as all viable births before 37 completed weeks of gestation or fewer than 259 days since the first day of woman’s last menstrual period . Each yeGlobally preterm neonates take the first place for neonatal intensive care unit (NICU) admission and longer hospital stay . ComplicOver 60% of preterm births occur in low- and middle-income countries (LMICs) and consistently risen in most countries . Study oEthiopia had reduced under-5 mortality by 67%, however, the reduction in neonatal mortality is not as impressive and premature birth is the leading cause accounts 37% .Studies estimated preterm birth rates ranged from 5% in developed countries to 26% in developing countries . One cohA cross-sectional study in the University of Ilorin teaching hospital, Ilorin, Nigeria, reported 11.8% , in CameStudies conducted in different areas reported risk factors for preterm birth: low socio-economic status, malnutrition, pregnancy-related complications and history of preterm birth , age lesTherefore determining factors has a great role in guiding health professionals and health policy makers to design the intervention strategy and applying necessary preventive and appropriate measures to decrease preterm birth.The source population was mothers who gave birth in Debretabor town health institutions and the study population was those mothers who gave birth during the study period.By considering single population proportion formula the final sample sizes were 575. Health institutions providing labor and delivery service in the town were systematically selected. Then the sample for each health institution was proportionally allocated based on their patient flow prior to the data collection period. Systematic sampling technique was employed to select the study participants from each health institution. Neonates born at less than 37 completed weeks of gestation but after viability (28 weeks of gestation) were taken as preterm, gestational age was calculated based on LNMP or first-trimester ultrasound result. Maternal nutritional status was assessed by measuring the left middle upper arm circumference (MUAC) using non-stretchable world food program MUAC tapes. Most screening programs have used a cut off of 21–23 cm. Given that there is no international consensus on the cut off to use, a MUAC of < 24 cm was chosen for this study.Data were collected by face to face interview and chart review using a structured and pre-tested questionnaire. Data were checked, coded and entered into EPI Info 7 and exported to SPSS 20 for analysis. Binary logistic regression was used to identify the associations between the dependent and independent variables. Those variables with a p-value of < 0.2 on binary logistic regression analysis were transferred to multivariable logistic regression. The degree of association was assessed using odds ratio with a 95% confidence interval and variables with a p-value < 0.05 were taken as statically significant.A total of 548 participants were completed the interview making 95.3% of response rate. The mean age of the study participants was 27.7 with SD of 5.8. Sixteen years old was the minimum and 41 years old was the maximum ages of clients participated in this study. Majority of the participants were 517 (94.2%) Orthodox Christians in religion. Majority 538 (98.2%) of the respondents were married and one-third 184 (33.4%) of the mothers were secondary and above on their educational status (Table Majority of the respondents 511 (93.3%) had ANC follow up and three-fifth of them had at least 4 visits 326 (59.5%). Nearly all of the respondents had used modern contraceptive 488 (89%) prior to their pregnancy and majority of them had their pregnancy wanted and planned 496 (90.4%). More than two-fifth of the respondents had birth to pregnancy interval greater than or equal to 36 months 231 (42.2%). One in ten mothers had Mid Upper Arm Circumference (MUAC) less than 24 cm (10%). Labour spontaneously started in 91.6% of the respondents. One-sixth of participants had one or more obstetric complications 92 (16.8%) ] and 11.5% was post term.After multivariable logistic regression, number of ANC visits less than 4 times, MUAC less than 24 cm, having PROM, being anemic, the complication in current pregnancy and being HIV positive were found to be statistically significant at a p-value of < 0.05.]. Mothers who had MUAC < 24 CM were 2.6 times more likely to develop preterm birth than their counterparts . Obstetric complications during the index pregnancy were 6.6 times more likely to develop preterm birth than mothers without any of the mentioned problems . Being HIV positive had 5.1 times increased the risk of giving preterm birth than their counterparts . Having anemia in the index pregnancy increased the risk of preterm birth by 2.9 times  In this study the proportion of preterm birth was found to be 12.8% with 95% CI (9.9%–15.7%). This finding was in line with findings in Africa (11.9%) and North America (10.9%) , a studyThe current finding was higher than the findings conducted in Sweden 5.03% , in GondHaving pregnancy complications during index pregnancy were 6.6 times more likely to have a preterm birth than mothers without these problems . This finding was parallel with findings in Ethiopia , NigeriaThe current study showed that having PROM were 3 times more likely to have a preterm birth than their counterparts . This finding was similar with findings in Tehran, Iran, , in KenyIn this finding being anemic were 2.9 times more likely to have a preterm birth than their counterparts . This finding was agreed with findings in Saudi Arabia , in EthiIn this study, mothers with less than four times ANC visit were 3 times at risk to give preterm birth than those with four and more visits . This finding is in line with a study in Cameron . This miThe current finding showed that maternal MUAC less than 24 cm were 2.6 times increased risk of developing preterm birth than mothers with MUAC greater than or equal to 24 cm with . This finding was agreed with a study in Bangladesh . This miThis study showed that HIV positive mothers were 5.1 times at increased risk of having a preterm birth than their counterparts . This finding is in line with a study in Ethiopia . This miThe proportion of preterm birth was high. Problem with current pregnancy, being anemic, being HIV positive, MUAC less than 24 cm and ANC visit less than four times were found to be statistically significant for preterm birth in the current pregnancy. So that, Ministry of health need to engage on educating the community to improve ANC service utilization through different methods and Upgrade capacity of health institutions to identify treat obstetric complications and nutritional counseling for mothers during their ANC follow up.This study was conducted through a cross-sectional study and may not show the cause and effect relationship.


Two-thirds of pregnant women exceed gestational weight gain recommendations. Excessive gestational weight gain (EGWG) appears to be associated with offspring’s complications induced by mechanisms that are still unclear. The aim of this study was to investigate whether umbilical cord leptin (UCL) and ghrelin (UCG) concentrations are altered in full-term neonates born to EGWG mothers and whether neonatal anthropometric measurements correlate with UCL and UCG levels and maternal serum ghrelin and leptin as well as urine ghrelin concentrations. The study subjects were divided into two groups, 28 healthy controls and 38 patients with EGWG. Lower UCL and UCG levels were observed in neonates born to healthy mothers but only in male newborns. In the control group UCG concentrations correlated positively with neonatal birth weight, body length and head circumference. In the control group maternal serum ghrelin levels correlated negatively with neonatal birth weight, body length and head circumference as well as positively with chest circumference. In the EGWG group UCG concentrations correlated negatively with neonatal birth weight and birth body length. UCL correlated positively with birth body length in EGWG group and negatively with head circumference in the control group. In conclusion, EGWG is associated with disturbances in UCL and UCG concentrations. According to the current state of knowledge, excessive gestational weight gain (EGWG) as well as pre-pregnancy obesity appear to be associated with long-term sequelae in the offspring. Prenatal life may be of importance as a ‘critical period’ since it is the time when the risk of development and persistence of dyslipidemia, overweight, obesity, impairments in cognition, neuropsychiatric disorders, cardiovascular diseases and metabolic syndrome in the future life of the offspring is increased ,2,3,4. MGestational weight guidelines of the Institute of Medicine (IOM)  provide Leptin, an adipocyte-derived satiety factor, is known to reduce food intake and raise/boost energy expenditure. However, due to the increase of leptin levels in the maternal blood in the second half of pregnancy, leptin resistance develops ,9, whichGhrelin, an acylated peptide hormone, plays a crucial role in energy homeostasis and it has been demonstrated to stimulate fetal development by binding to the growth hormone receptors . GhrelinDisrupted leptin and ghrelin secretion homeostasis may result in production of improper hypothalamic signals, thereby bringing a feeling of hunger, which will lead to excessive food consumption and lipogenesis. All of this has been displayed in both animal and human models .Even though numerous studies have performed leptin and ghrelin blood concentration measurements in both healthy and unhealthy individuals ,12,13, tComparative characteristics of the study groups are presented in We checked correlations between the neonatal anthropometric measurements and leptin and ghrelin levels. Taking into consideration the relatively small group of female infants in our study, we performed the correlation analysis only on male newborns in the EGWG and control groups. In the EGWG group the umbilical cord ghrelin levels correlated negatively with the neonatal birth weight and birth body length in all infants  as well The controls presented umbilical cord ghrelin levels correlating positively with the neonatal birth weight, birth body length and head circumference ; whereasMaternal pre-pregnancy BMI as well as gestational weight gain, connected to nutrition, have both independent and interacting effects not only on the fetal growth . The majOur study showed that levels of leptin and ghrelin in the umbilical cord blood were statistically higher in male infants of the EGWG group in comparison to healthy subjects. We hypothesize that these differences can be connected to disparities in body composition and hydration status. Our previous study revealed that mothers with EGWG were characterized by increased fat and lean tissues in the bioelectrical impedance analysis . UnfortuLecoutre et al.  observedPrevious studies revealed that females tended to have higher serum leptin levels than males . SimilarMany authors are of the opinion that leptin concentration is higher in the mother than in the newborn ,18,23,30Previous studies reported high ghrelin concentrations in the umbilical cord blood of pre-term and small-for-gestational-age infants. It was also reported that ghrelin levels were increased in the offspring of those women who had cigarette smoking habits and suffered from hypertension during pregnancy ,34. A liThere are many studies showing higher umbilical cord leptin levels in neonates born to obese mothers ,21 but tIt is worth highlighting that many of the above-quoted studies did not take into consideration the maternal BMI and weight gain during pregnancy. The results of our study revealed differences not only in the gestational weight gain between two groups of mothers but in the laboratory results as well. Lower levels of high-density lipoprotein cholesterol (HDL) as well as higher HgbA1c and triglycerides concentrations were present in the EGWG group. These results are consistent with the observations reported by other authors. Nonetheless, the offspring of the mothers from both studied groups presented similar anthropometric measurements, and their birth weight was also comparable. However, previous studies seem to confirm that the fetal metabolic programming may occur within normal birth weight ranges ,41.Researchers studying the relationship between ghrelin and anthropometric measurements revealed an inverse correlation between ghrelin concentrations and birth weight, height as well as BMI ,44,45,46The positive association detected in this study between the leptin concentration in the maternal serum and umbilical cord and neonatal anthropometric measurements confirms what was reported in the previous studies ,17,30,50As other studies have reported, in our study the mean leptin concentrations were also higher in female neonates than in male neonates even though the birth weight in both sexes was similar. This may suggest participation of sex hormones in leptin secretion ,50,51. TOur results seem to highlight the importance of maternal condition, including gestational weight gain, in further research into the umbilical cord ghrelin and leptin concentrations and their relationship with the fetal and/or neonatal anthropometry and metabolic state.The strength of this study lies in its novelty—the evaluation of the umbilical cord ghrelin levels of the EGWG mothers’ offspring as well as their associations with the maternal laboratory results and neonatal anthropometric measurements is an innovative approach. Nevertheless, the presented study has certain limitations. Firstly, it is indeed a relatively small-sample study. Secondly, we measured the levels of ghrelin and leptin in all the material only once. Therefore, it would be interesting to check how they change in time both in the mothers and in their offspring, which is quite motivating for us to continue our research into this issue and verify our results.n = 28), while the other consisted of those with excessive gestational weight gain . Informed consent was obtained from each study subject and infant mother.The study consisted of Caucasian, singleton-term-pregnancy mothers (who completed 37 weeks of pregnancy) and infants delivered at the Chair and Department of Obstetrics and Perinatology, the medical University of Lublin, Poland. The study material was obtained between March 2016 and February 2017. The women were recruited at the time of delivery. We took into account only those in full-term pregnancy, i.e., after the completed 37th week of pregnancy calculated on the basis of the date of the last menstrual period or ultrasound examination in case the date of the last menstrual period was unknown. Two groups were selected on the basis of gestational weight gain: one group included women with normal gestational weight gain  findings); metabolic disorders , mental illness, cancer, liver diseases, cardiovascular disorders, fetal malformation, premature membrane rupture and intrauterine growth retardation.The study protocol received approval of the Bioethics Committee of the Medical University of Lublin (no. KE-0254/221/2015 [25 June 2015] and no. KE-0254/348/2016 [15 December 2016]).Anthropometric measurements of mothers were performed shortly prior to and after delivery. Pre-pregnancy BMI values were determined during the first visits in the out-patients clinic, which were carried out up to 10 weeks of gestation. The following formula was used to calculate the gestational weight gain: the mother’s pre-pregnancy body mass subtracted from the weight at the day of delivery. We calculated gestational BMI gain as well. We defined gestational BMI loss as the difference between the mother’s BMI after delivery (during 48 h after delivery) and her BMI shortly prior to delivery. The newborn weights, lengths as well as the head and chest circumferences were measured right after delivery.g, at 20 °C for 15 min. After centrifugation all the collected cord blood serum as well as the serum and urine samples obtained from the studied mothers were stored at −80 °C. Ghrelin concentrations were determined with the use of kits available on the market and in agreement with the manufacturer’s instructions  via traditional enzyme-linked immunosorbent assay (ELISA). Detection range for ghrelin was 0.156–10 ng/mL. Concentrations of leptin in cord blood serum and maternal serum and urine were measured by means of commercially available kits and in agreement with the manufacturer’s instructions  via ELISA. The threshold of leptin sensitivity was equal to 7.8 pg/mL, while the reference range for women was 3877–77,273 pg/mL. Since the leptin urine levels in the majority of the studied subjects were below the threshold of sensitivity of the ELISA test, the “urine leptin” parameter was not included in our study results. The measurements of maternal serum levels of albumin, fasting blood glucose (FBG), hemoglobin A1c (HgbA1c) as well as the lipid profile were performed by an authorized laboratory. The cord blood samples’ collection was performed during delivery causing no hinderance to its course. The maternal serum and urine samples were taken after delivery, taking into account a 6 h fasting period. Samples were centrifuged at 1000× This is the second analysis based on subjects from the control group that was previously used in our study . In the p < 0.005 was assumed to be statistically significant. All the obtained results are presented as the median (interquartile range 25–75%) or as numbers and percentages. Differential significance test was conducted by means of Mann–Whitney U test. Correlation analyses used Spearman’s coefficient test and were performed with the use of Statistical Package for the Social Sciences software ; Our study revealed that the umbilical cord leptin and ghrelin levels were significantly higher in the offspring of the EGWG mothers, but only in the male newborns. Our study results indicate that the condition of the mother, i.e., her BMI values both in the periconceptional and periparturient periods as well as her metabolic parameters , may affect her offspring’s ghrelin and leptin concentrations at delivery. p < 0.0001) with comparable birth measurements in both studied groups. However, the possibility of fetal metabolic programming occurrence within the normal birth weight ranges, as has previously been reported by other authors [Differences in the correlations between the leptin and ghrelin concentrations  and the anthropometric results of the neonates are dependent on the studied group. This can be exemplified by the umbilical cord ghrelin which correlates negatively with the birth weight and birth body length in the EGWG group, while its correlation with the birth weight, birth body length and head circumference is positive in the control group. These significant correlation differences result from different levels of ghrelin in the umbilical cord blood (significantly higher level in the EGWG group, at  authors ,41, shou


Maternal lipid profiles during pregnancy are associated with risk for preterm birth. This study investigates the association between maternal dyslipidemia and subsequent preterm birth among pregnant women in the state of California. Births were identified from California birth certificate and hospital discharge records from 2007–2012 . Preterm birth was defined as <37 weeks completed gestation and dyslipidemia was defined by diagnostic codes. Subtypes of preterm birth were classified as preterm premature rupture of membranes (PPROM), spontaneous labor, and medically indicated, according to birth certificate data and diagnostic codes. The association between dyslipidemia and preterm birth was tested with logistic regression. Models were adjusted for maternal age at delivery, race/ethnicity, hypertension, pre-pregnancy body mass index, insurance type, and education. Maternal dyslipidemia was significantly associated with increased odds of preterm birth . This finding was consistent across all subtypes of preterm birth, including PPROM , spontaneous , and medically indicated . This study suggests that maternal dyslipidemia is associated with increased risk for all types of preterm birth. Preterm birth is defined as delivery prior to 37 weeks of completed gestation. The World Health Organization estimates that preterm birth affects 11% of pregnancies worldwide, representing nearly 15 million births in 2010 [Normal pregnancy is accompanied by metabolic changes, particularly in carbohydrate and lipid metabolism. The benefit of these changes is presumably to increase circulating glucose and triglycerides to nourish the growing fetus. Changes in carbohydrate metabolism are bimodal, in which fasting plasma glucose is decreased in early pregnancy, and impaired glucose tolerance occurs in late pregnancy . CirculaMany studies have investigated associations between maternal lipid levels during pregnancy and risk for preterm birth, although the lipid components and magnitude of associations have been inconsistent across studies –17. One Births were identified from California birth certificate and hospital discharge records from 2007–2012  as collected by the California Office of Statewide Health Planning and Development. Records were linked approximately 9–12 months prior to delivery through 9–12 months post-delivery . InclusiPreterm birth was defined as gestational age at delivery <37 weeks and term birth was defined as gestational age at delivery ≥37 weeks, according to best obstetric estimate. Births were further categorized into early preterm birth (<32 weeks), late preterm birth  version 9.4 . The associations between dyslipidemia and preterm birth were tested using logistic regression (PROC LOGISTIC). Dyslipidemia was modeled as a composite variable and as individual diagnostic codes. The associations were tested without adjustment and with adjustment for maternal age at delivery, hypertension , race/ethnicity, BMI, insurance type, and education. Maternal age at delivery was analyzed as a linear variable. Hypertension was coded as a binary variable and the absence of hypertension was used as the referent group. Race/ethnicity was categorized as Black, Asian, Caucasian or Hispanic, and Caucasian was used as the referent group. BMI was categorized according to standard cut-points , and ‘normal’ was used as the referent group . InsuranWe considered maternal age at delivery as a potential confounder, wherein we hypothesized that advanced maternal age would be associated with increased likelihood of diagnosis of dyslipidemia and an increased likelihood of delivering preterm –24. We aSeveral supplemental analyses were performed. These included: 1) stratification of analyses by BMI category to determine if BMI modifies the relationship between dyslipidemia and preterm birth; 2) consolidation of ICD-9 codes into cholesterol dyslipidemia and triglyceride dyslipidemia to determine if the type of dyslipidemia (cholesterol versus triglyceride) affects the results; and 3) examination of the individual impact of confounders, including race/ethnicity, hypertension, BMI, insurance type, maternal education and maternal age, on the association between dyslipidemia and preterm birth. All statistical analyses were performed with statistical power >99.9% to detect an odds ratio of 1.5.Demographic characteristics of the study population are presented in Results of the traditional logistic regression analyses are presented in Results of the traditional logistic regression analyses, stratified by type of dyslipidemia, are presented in Results of the traditional logistic regression analyses, stratified by BMI category, are presented in Results of the consolidation of ICD-9 codes into cholesterol dyslipidemia and triglyceride dyslipidemia are presented in To investigate the individual impact of confounders, including race/ethnicity, hypertension, BMI, insurance type, maternal education and maternal age, on the association between dyslipidemia and preterm birth, each confounder was individually added to the logistic regression models . AdjustiIn this retrospective cohort of 2.9 million pregnant women in California, maternal diagnosis of dyslipidemia was significantly associated with increased risk for preterm birth. To the best of our knowledge, this study represents the largest investigation of the association between clinical dyslipidemia and risk for preterm birth done to date and it is the only study that we know of to utilize hospital diagnostic codes to define dyslipidemia, which include both familial and non-familial forms of dyslipidemia. The size and diversity of the study population allowed for the investigation of the association between dyslipidemia and preterm birth, stratified by subtypes of dyslipidemia.Several previous studies have investigated associations between maternal lipid levels during pregnancy and risk for preterm birth –17. ThesOf particular interest in the present study is the consistency of the magnitude of association across all subtypes of preterm birth, after adjusting for potential confounders. These adjusted odds ratios ranged from 1.4–1.6 , providiDyslipidemia is often comorbid with obesity , and obeA limitation of this study is the lack of information regarding dyslipidemia diagnostic practices. Heterogeneity exists among practitioners in terms of the degree of follow-up testing of lipid levels. Thus, some women may have received a diagnosis after a single abnormal lipid panel, with no repeat testing, while other women may have received a diagnosis following multiple abnormal panels. Some women with dyslipidemia may not have a diagnosis because they have never had their lipid levels tested or they were treated before pregnancy and entered pregnancy with normal lipids. This type of non-differential misclassification would bias the results toward the null. There are currently, no-evidence based standards for how to treat women with dyslipidemia during pregnancy. The most common recommendations include lifestyle changes, glycemic control and close follow-up of the pregnancy . It is uIt should also be noted that an important limitation of the study is the lack of lipid level information. Such data would have allowed for discrimination between familial, monogenic dyslipidemias, which are characterized by markedly abnormal lipid levels, and non-familial, polygenic dyslipidemias, which typically manifest as less drastic changes in lipid levels. However, a Norwegian study of 895 women with familial hypercholesterolemia (FH) found no association between FH and risk for adverse pregnancy outcomes, including preterm birth . Thus, wIn conclusion, dyslipidemia, as both an aggregate exposure and individual subtypes, was significantly associated with a 1.5-fold increased risk for preterm birth after adjusting for potential confounders. These findings suggest that dyslipidemia may be a potential factor in the etiology of preterm birth, and may serve as a marker of increased risk for preterm birth. The identification of dyslipidemia as a risk factor for preterm birth is impactful for several reasons: 1) There are few known causal risk factors for preterm birth, as the causes of parturition and preterm birth remain largely unknown, 2) dyslipidemia may be modified by lifestyle changes and medication  and 3) sS1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.


International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes identified in hospital discharge data, without case confirmation. However, little is known about how well these codes identify NAS or how the October 1, 2015, transition from ICD-9-CM to the tenth revision of ICD-CM (ICD-10-CM) codes affected estimated NAS incidence. This report describes a pilot project in Illinois, New Mexico, and Vermont to use birth defects surveillance infrastructure to obtain state-level, population-based estimates of NAS incidence among births in 2015  and 2016 (Illinois) using hospital discharge records and other sources (varied by state) with case confirmation, and to evaluate the validity of NAS diagnosis codes used by each state. Wide variation in NAS incidence was observed across the three states. In 2015, NAS incidence for Illinois, New Mexico, and Vermont was 3.0, 7.5, and 30.8 per 1,000 births, respectively. Among evaluated diagnosis codes, those with the highest positive predictive values (PPVs) for identifying confirmed cases of NAS, based on a uniform case definition, were drug withdrawal syndrome in a newborn  and drug withdrawal, infant of dependent mother . The methods used to assess NAS incidence in this pilot project might help inform other states’ NAS surveillance efforts.Neonatal abstinence syndrome (NAS) is a drug withdrawal syndrome that can occur following prenatal exposure to opioids (https://www.marchofdimes.org), in collaboration with CDC, awarded grants to CDC-funded, state-based birth defects programs in Illinois, New Mexico, and Vermont to adapt birth defects surveillance methodology to conduct active, population-based surveillance for NAS or passive case-finding with case confirmation. Each state defined a population-based 2015 birth cohort in which to identify infants with NAS; Illinois extended data collection to include a 2016 birth cohort. All three states used hospital discharge data to identify potential cases using infant ICD-9-CM diagnosis codes 779.5  and 760.72  and ICD-10-CM codes P96.1  and P04.49 , as well as other infant and maternal diagnosis codes of interest to the state. Illinois used two additional data sources: 1) the Illinois birth defects registry’s Adverse Pregnancy Outcomes Reporting System,https://gmcboard.vermont.gov/health-data-resources/vhcures), for commercial claims data, as a part of a Birth Information Network established for surveillance for birth defects and other congenital conditions. In all three states, potential cases were identified among the 2015–2016 birth cohorts and then deduplicated.Through a competitive application process, the March of Dimes, a nonprofit that works to improve the health of mothers and their babies , not explained by another etiology or a documented infant diagnosis of NAS with pharmacologic treatment;Documented history of maternal use during pregnancy of prescription or illicit drugs associated with NAS or laboratory confirmation of recent maternal drug use or fetal exposure to such drugs;Severity of illness that resulted in a prolonged (>2 days) neonatal hospitalization.https://www.cdc.gov/mmwr/preview/mmwrhtml/mm6408a3.htm) was expanded for this project to include “or a documented infant diagnosis of NAS with pharmacologic treatment” in the first criterion.* The original clinical case definition (§ provided the highest estimate of NAS (62.3); incidence estimates based on hospital discharge data (29.6) and commercial claims data (1.6) were lower. The overall incidence of NAS in Illinois in 2016 remained at 3.0 per 1,000 births.In 2015, NAS incidence was 3.0 per 1,000 births in Illinois, 7.5 in New Mexico, and 30.8 in Vermont . In IlliIn all three states, the diagnosis codes with the highest PPVs for identifying confirmed cases of NAS, based on a uniform case definition were drug withdrawal syndrome in a newborn  and drug withdrawal, infant of dependent mother  .No standardized way to conduct state-based NAS surveillance in the United States exists, and there is no standardized national surveillance system; most published NAS estimates are based on ICD-9-CM or ICD-10-CM diagnosis codes from hospital discharge data, without case confirmation, and few studies have validated these diagnosis codes for NAS surveillance  , might underestimate the incidence of NAS. Illinois’ NAS incidence from this report was lower than a published hospital discharge data–based regional estimate  but similar to a 2013 estimate in Iowa (2.2)  resulted in the highest PPVs. ICD-9-CM code 779.5 has been the most commonly used infant drug withdrawal code in the United States and is the most specific ICD-9-CM code for NAS  surveillance in the United States is based largely on diagnosis codes in hospital discharge data, without validation of these codes or case confirmation.Estimates of NAS incidence during 2015 were 3.0 per 1,000 births for Illinois, 7.5 for New Mexico, and 30.8 for Vermont. Of the four diagnosis codes evaluated, those for infant drug withdrawal (779.5 and P96.1) had the highest positive predictive values for identifying confirmed NAS cases.NAS surveillance based solely on diagnosis codes in hospital discharge data might slightly overestimate NAS incidence. These findings could help inform NAS surveillance in other states.


Low birth weight is defined as infant born with weight of less than 2500 g. It is one of the major public health problems worldwide. In Ethiopia, there are limited evidences on factors contributing to low birthweight.To assess factors associated with low birth weight babies in Hawassa University Comprehensive Specialized Hospital, Hawassa, Ethiopia from March to April, 2018.An unmatched case control study was conducted at Hawassa University Comprehensive Specialized Hospital. All low birth weight newborns and two unmatched controls for each case were included in the study from March to April, 2018. Data were collected through face to face interview using a structured and pre-tested questionnaire. The collected data were managed with Epi-data version 3.1 software and exported to the Statistical Package for Social Science (SPSS) version 22. Bivariate and multivariate binary logistic regression were used to identify factors associated with low birth weight at p-value < 0.05 with their respective odds ratios and 95% confidence interval. Hosmer-Lemeshow test was used to assess goodness-of-fit., 95% CI: 1.58, 5.29)], lack of nutritional counseling , presence of complications during pregnancy  and lack of iron supplementations during pregnancy  were significantly associated with Low birth weight.In this study 330 mother-newborn pairs (110 cases and 220 controls) were participated making 100% response rate. Among the participants 325(98.48%) were married, 164 (49.7%) were Protestant, 296 (89.7%) had ANC follow up and 212 (64.24%) were multipara. Mothers’ mid-upper arm circumference less than 220 mm [(AOR) =2.89Mothers’ mid-upper arm circumference less than 220 mm, lack of nutritional counseling, presence of complications and lack of iron supplementations during current pregnancy were significantly associated with low birth weight. Counseling on nutrition during prenatal care needs attention of service providers. The World Health Organization (WHO) defines low birth weight (LBW) as a birth weight of infant of 2499 gram or less regardless of gestational age . Low birOverall, it is estimated that 15% to 20% of all births worldwide are LBW, representing more than 20 million births a year . There iIn Ethiopia, different studies showed variable prevalence of low birth weight. The variations were further reflected in the Ethiopia Demographic Household Survey with the highest rates in 2005 (14%) and lowest in 2011 (11%), although the trend reverts to 13.1% in 2016 report , 14.6% iDifferent studies identified different factors associated with low birthweight. In Laelay Maichew districts, sex of neonate, less than four antenatal care follow ups, unwanted and unplanned pregnancy, and maternal dietary intake per 24 hours during pregnancy were associated with LBW . PregnanOther risk factors, such as maternal age of less than 20 years, mothers with a history of abortion, lack of formal education, residing in rural areas, maternal body mass index less than 18 kg/m2, absence of antenatal care, history of chat chewing, maternal anemia, malnutrition, poor nutrition both before and during pregnancy, extra meal during pregnancy, and lack of iron/folic acid supplementation during pregnancy were all associated with LBW –18. DespAn institutionally based case-control study was conducted at Hawassa University Comprehensive Specialized Hospital (HUCSH) from March to April 25, 2018. Hawassa city is located 273 km south of Addis Ababa, Ethiopia. Currently, Hawassa University Comprehensive Specialized Hospital provides health services for more than 18 million people; and the average number of deliveries per month was around deliveries.All post-partum mother-newborn pairs who visited Hawassa University Comprehensive Specialized Hospital were the source population. Live newborn babies with birth weights less than 2500grams were considered as cases and newborn babies with birth weight of 2500grams to 4000grams were considered as controls.The sample size was calculated using Open Epi Version Two statistical software for unmatched case control with the assumption of 95% confidence level, power 80%, control to case ratio of one to two, minimum detectable odds ratio of two, and proportion of case among exposed group  of 25.3% . The finFive bachelor prepared nurses were trained and collected the data through face to face interviews with the post-partal mothers. The weight of the baby was collected through observation when baby is weighted using calibrated Seca scale and rounded to 100gram. Maternal mid upper arm circumference was measured using tape meter, socio demographic data, obstetric history and presence of any complication during pregnancy were collected through maternal interview. In addition, client’s medical records were reviewed for possible diagnosis of complications and gestational age. The questionnaire was initially developed in English version and translated to the local language (Amharic) for better understanding by participants. Data related to nutrition (frequency of feeding and type of diet) were collected using the Food Frequency Questionnaires (FFQs). The level of house hold food insecurity was assessed using the Household Food Insecurity Access Scale (HFIAS). This scale categorized the subjects in to four groups as secure, mild, moderate and severe insecurity .The collected data were checked for completeness, coded, and entered into Epi Data Version 3.1 software and exported to SPSS Version 22 for analysis. Continuous data were categorized, mean and standard deviations computed, cross tabulation was done, and variables with very few frequencies were merged, when possible. The socio demographic and other profiles of the cases and control were compared using chi-square test.p-value < 0.05. Hosmer-Lemeshow test was used to assess goodness-of-fit.Association between birth weight and independent variables were identified using bivariable and multivariable logistic regression model. In the bivariable model, variables with p-value ≤ 0.2 were selected for multivariable logistic regression model. In the multivariable logistic regression, an association was considered significant at 95% confidence level and A total of 330 women (110 cases and 220 controls) participated in this study. The minimum and maximum ages of participants were 18 and 40 years respectively with a mean and standard deviation of 26.92 ±4.69 years. Among the participants 325(98.48%) were married, 118(35.76%) were Sidama in ethnicity, and 164 (49.7 %) were Protestant. There is a significant difference among cases and controls in terms of mother’s age, place of residence, level of education, as well as presence of Refrigerator and animal breeding in the house (see Table The minimum age at first birth was 14 years and the maximum age was 35 years with a mean and standard deviation (±SD) of 21.88 ± 3.56 years. Similarly, the minimum and maximum gestational age at first ANC visit was four weeks and 32 weeks respectively with a mean and standard deviation of 18 ± 5weeks and 2 days. In this study, 296 (89.7%) had ANC follow up during the current pregnancy and 212 (64.24 %) were multipara. The minimum and maximum birth weights of the newborns were 1000gm and 4000 gm respectively with a mean and standard deviation (±SD) of 2800±600gm. The mean gestational age at birth was 37 ± 1.8 weeks with minimum of 30 weeks and maximum of 42 weeks (see Table In this study 320 (97.3%) of participants were considered household food secure and the remaining 10 were not.Factors associated with low birth weight  was less than 220 mm were four times higher compared to those whose MUAC was greater than 220 mm. This finding aligns with a study based on the Ethiopian Demographic Health Survey analysis, which concluded that maternal nutritional status is significantly associated with low birth weight , 22, 24.The odds of delivering low birth weight newborns among mothers with complications during pregnancy were two times higher than their counter parts. Previous studies conducted in Gondar, Bale zone, Adwa, and southern Iran also identified the presence of HIV infection, eclampsia/preeclampsia, and anemia as significantly associated with low birth weight as these predispose the fetus to intrauterine growth restrictions , 18, 24.This study showed that the odds of delivering low birth weight newborns among mothers who did not use iron tablets during current pregnancy were two times higher compared to those who used iron tablets during pregnancy. Similar evidence reported in studies conducted in Addis Ababa and Adwa, where iron utilization during pregnancy was found to be protective for LBW , 21. It Almost all factors associated with low birth weight in this study were preventable and can be controlled easily. Strengthening the integration of nutrition counseling in to ANC help could to improve maternal nutritional status during pregnancy . Even thLack of nutritional counseling during pregnancy, , maternal mid upper arm circumference less than 220mm, and presence of complication during pregnancy were significantly associated with low birth weight. Focusing on nutritional counseling and adherence to iron supplementations need great attention from care providers during prenatal care.


R2 > 0.97. Critical variables for IP prediction were identified: neonatal platelets and neutrophils; orotracheal intubation; birth weight; sex; arterial blood gas parameters (pCO2 and HCO3); gestational age; use of fortifier; patent ductus arteriosus; maternal age and maternal morbidity. These models may allow quality improvement in medical practice.Intestinal perforation (IP) associated with necrotizing enterocolitis (NEC) is one of the leading causes of mortality in premature neonates; with major nutritional and neurodevelopmental sequelae. Since predicting which neonates will develop perforation is still challenging; clinicians might benefit considerably with an early diagnosis tool and the identification of critical factors. The aim of this study was to forecast IP related to NEC and to investigate the predictive quality of variables; based on a machine learning-based technique. The Back-propagation neural network was used to train and test the models with a dataset constructed from medical records of the NICU; with birth and hospitalization maternal and neonatal clinical; feeding and laboratory parameters; as input variables. The outcome of the models was diagnosis: (1) IP associated with NEC; (2) NEC or (3) control (neither IP nor NEC). Models accurately estimated IP with good performances; the regression coefficients between the experimental and predicted data were  Intestinal perforation (IP) associated with necrotizing enterocolitis (NEC), also known as surgical NEC, is one of the leading causes of death in preterm infants, with up to 30–50% mortality compared with only 21% in those medically treated for NEC ,5. Globaa priori assumptions regarding the relationship between variables. The short-elapsed time needed to calculate the IP diagnosis makes the online application of such models possible. We have previously used BPNN in a biomedical context, with accurate results for the prediction of neonatal and maternal biochemical blood parameters [Despite the existence of prediction tools and early recognition of NEC, it remains challenging to estimate intestinal perforation, as it results from intricate interrelationship between multiple factors, being difficult to predict in individual cases. In this regard, machine learning models are able to predict outcomes from complex non-linear interactions , which arameters ,27. SuchThis was an observational retrospective study. Data were obtained from patient records hospitalized in the Neonatal Intensive Care Unit (NICU) of a tertiary care hospital from January 2015 to August 2017. Informed consent was not required .N = 27), (2) NEC group (according to Bell’s staging criteria) (N = 23) and (3) Intestinal perforation associated with NEC group (Bell’s Stage IIIB) (N = 26). We excluded 15 cases with incomplete clinical information as well as spontaneous or not associated with NEC intestinal perforation, as well as digestive tract malformations. Control neonates were not stage I NEC (or any NEC stage). We carefully collected a balanced dataset with a similar number of samples per group.This work was designed to forecast IP related to NEC and to investigate the predictive quality of variables. For this purpose, we developed two estimation models for intestinal perforation associated with NEC: (a) an ANN model at birth and (b) an ANN model at birth and during hospitalization. Three groups of neonates were compared: (1) control group without NEC nor intestinal perforation but with similar gestational age  greater or equal to 30 . Chorioamnionitis was defined as an acute inflammation or infection of any combination of fetal membranes, amniotic fluid, decidua and chorion of the placenta. Numerical data were expressed by a number, whereas absence or presence (no or yes) was expressed as 0 or 1, respectively. Differences in numerical variables between groups were analyzed by ANOVA, and categorical variables were analyzed by Pearson’s Chi-square test . Twenty-three variables were chosen for the IP associated with NEC model at birth, while 35 parameters were selected for the IP associated with NEC model at birth and during hospitalization . The anthropometric/clinical maternal and neonatal characteristics are depicted in Taking into account variables already reported in the literature, as well as others proposed during meetings with the clinical staff, we chose 113 variables that included maternal and neonatal data recorded at birth and during hospitalization. Within these, we collected maternal and neonatal clinical/demographic data , diagnosis, oxygen therapy at birth, enteral feeding, laboratory, and clinical findings. Routine laboratory tests are performed for all premature neonates <35 weeks and, within the first 24 h for closer monitoring, and included arterial pH, blood gases and hematologic data. Maternal obesity was defined as a Body Mass Index /height (mN = 76 neonates) was randomly divided into training (80%) and testing, validation (20%). The input variables were normalized in the range of 0.1 to 0.9, as previously described [−12, as well as validation of the model by the slope and intercept statistical test (see The architecture of ANN models comprised three layers of neurons (nodes) connected together: an input layer (parameters predicting the outcome), a hidden layer (activation transfer functions) and an output layer: the prediction of diagnosis, either (1) no NEC nor IP, (2) NEC or (3) IP associated with NEC. The database , HCO3, base deficit (BD), diastolic arterial blood pressure (DBP), number of total leukocytes (L), neutrophils (N), platelets (P), and catheter location (CL). Input variables range is shown in Twenty-three input variables were chosen from the entire database with the following maternal parameters: maternal age (MA), maternal morbidity , maternal morbidity  in whicR2) was then obtained from linear regression models for each ANN model:The regression coefficient  in order to differentiate from NEC or no NEC (Control) diagnosis and to investigate key factors for the prediction. For this purpose, extracted data from maternal and neonatal records were used to train two BPNN models: (1) an IP model with birth variables or (2) an IP ANN model with birth and hospitalization parameters. Such design will allow to explore the importance of risk factors at birth compared to hospitalization parameters, obtained from a sensitivity analysis of both models.N = 27) were chosen while NEC (N = 23) or control groups (N = 27) were carefully selected in order to have similar gestational ages in all groups. Neonatal birth weight was significantly higher in the control group (1384 ± 95.5 g) compared to NEC or IP groups .All neonates with IP associated with NEC diagnosis in NICU  and transfer functions were tested, finding the best performance to be the hyperbolic tangential function (TANSIG) in the hidden layer and the Log-sigmoid function (LOGSIG) in the output layer. For both models, 30,000 runs (with 1000 epochs) were applied in the hidden layer (from one neuron to two or three neurons). For the ANN model predicting IP at birth, the final architecture was 23 input variables, 3 neurons in the hidden layer, and 1 neuron in the output layer : 23-3-1; while the final topology for the ANN IP model at birth and during hospitalization was 35-2-1. The representative neural architecture for the estimation of IP diagnosis is depicted in R2 = 0.9764 and R2 = 0.98029 for the IP model with birth variables  in the modeling of the IP diagnosis . At birtonal age .2, use of fortifier, maternal age, OTI, HCO3, indirect oxygen, and gastric residuals were the key factors with the highest relative contribution to the estimation of intestinal perforation. These variables were followed by birthweight, PPV, maternal age, first day of oral feeding, hypotension and early sepsis , the regression coefficients between the experimental and predicted data were 2 and HCO3), use of milk fortifier and maternal age. Therefore, attention should be paid to these parameters.Identification of critical factors and the assessment of how output changes by varying input variable values one by one, added knowledge in the field and will permit additional understanding of risk factors for the prediction of a future intestinal perforation associated with NEC. Previously unreported key variables for the prediction of IP in both models were: orotracheal intubation, arterial blood gas parameters , by finding variables involving literature-known factors, that may allow an early diagnosis and follow-up of premature neonates. With respect to previously described risk factors for intestinal perforation associated with NEC, lower birth weight ,33,34, dIn the matched prospective multicenter cohort study by Berkhout et al., multivariable logistic regression modeling demonstrated only 2 independent variables to be associated with an increased risk of NEC: administration of predominantly formula feeding and the cumulative number of parenteral feeding days. Remarkably, administration of any antibiotics initiated within 24 h after birth was associated with a reduced risk of NEC .We found that male gender was a highly predictive parameter for intestinal perforation associated with NEC compared to only NEC. There are only a few studies where male gender has been significantly associated to increased risk of NEC ,38 or noIn regard to maternal factors, older age (>38 years) followed by preeclampsia or hypertension determined perforation by NEC in the ANN models. In contrast, Lee et al. reported a lack of association between preeclampsia and NEC, demonstrating that neutrophil-to-lymphocyte ratio (NLR) at the time of admission and multiparity was associated with the occurrence of NEC . Zhang eRecent studies performed in twins have suggested that a genetic variation in an intergenic region of chromosome 8, labeled as the “NECRISK” region may be associated with increased risk for surgical NEC. Although no specific genes have been identified, pathway analyses have indicated possible pathways related to growth factor, calcium, and G-protein signaling, and others associated with inflammation that may contribute to NEC complications .From laboratory findings, a higher neutrophil count and lower platelet numbers predicted perforation by the models. In this regard, thrombocytopenia has been associated with NEC and perforation in several studies .2 and HCO3) were the most important variables to predict IP associated with NEC. It is known that a high base deficit from umbilical cord arterial samples at birth can contribute to NEC in growth-restricted infants [p < 0.0001) and identified a lower risk for surgery in patients with a later onset of NEC and higher pH values [In our study, arterial blood gases  however, the use of anthropometric, clinical and laboratory findings as well as a balanced dataset gave accurate results. Another important limitation is the fact that it is a single center study nonetheless, our institution is a tertiary care hospital that concentrates complicated pregnancies from all over the country. We also have to recall that both ANN models predict the diagnosis of intestinal perforation associated with NEC within the limits of the variables range (We have to acknowledge the limitation of this work to be the relatively small dataset size (es range . Also, aThe strengths of this work include a complete maternal and patient information from variables at birth and associated with the course of the disease taking into account lifestyle, morbidity, anthropometric, clinical, enteral feeding, mechanical ventilation, blood gas, medications and laboratory findings of the study population from three balanced groups. We report both key factors as well as less-important factors for the prediction of IP. Learning by ANN to estimate a pattern of intestinal perforation associated with NEC from individual cases relied on several variable parameters, making such tools highly valuable for clinical setting since they allow a more precise prediction of the outcome.Both BPNN models were able to accurately estimate intestinal perforation associated with NEC. Furthermore, key maternal and neonatal variables were found by the models involving well-known factors reported in the literature, as well as new parameters that may allow the early diagnosis and follow-up of premature neonates at risk of surgical NEC. Our results highlight the value of integrating maternal and neonatal variables at birth and during hospitalization variables in BPNN models to better estimate surgical NEC. A suggestion for new modeling will be to incorporate data from birth, day 3 and day 7, as well as from multi-center studies. We hope our models may be useful to preselect at-risk patients for perforation associated with NEC before randomization for a strict follow-up that could result in different surgical interventions.


The fine control of birth timing is important to human survival and evolution. A key challenge in studying the mechanisms underlying the regulation of human birth timing is that human parturition is a unique to human event — animal models provide only limited information. The duration of gestation or the risk of preterm birth is a complex human trait under genetic control from both maternal and fetal genomes. Genomic discoveries through genome-wide association (GWA) studies would implicate relevant genes and pathways. Similar to other complex human traits, gestational duration is likely to be influenced by numerous genetic variants of small effect size. The detection of these small-effect genetic variants requires very large sample sizes. In addition, several practical and analytical challenges, in particular the involvement of both maternal and fetal genomes, further complicate the genetic studies of gestational duration and other pregnancy phenotypes. Despite these challenges, large-scale GWA studies have already identified several genomic loci associated with gestational duration or the risk of preterm birth. These genomic discoveries have revealed novel insights about the biology of human birth timing. Expanding genomic discoveries in larger datasets by more refined analytical approaches, together with the functional analysis of the identified genomic loci, will collectively elucidate the biological processes underlying the control of human birth timing. Gestational duration is an important complex human trait controlled by multiple physiological processes. Despite years of research efforts, the biological mechanisms underlying human birth timing remain poorly understood. Genetic studies have the potential to provide new biological insights by identifying associated genes and pathways. In this review, we attempt to discuss several key topics related to the genetic research of human gestational duration.Multiple lines of evidence have suggested a substantial genetic influence on the gestational duration and the risk of preterm birth Twin studies Preterm birth, although empirically defined as a single clinical entity based on gestational age (<37 weeks), is the final outcome that can arise from many pathological processes with involvement of a wide variety of molecular pathways Up to now, our knowledge about the regulation of parturition mainly comes from animal studies The second characteristic of the commonly used animal models is the relatively abrupt transition from uterine quiescence to activation, probably triggered by a major hormonal switch . However, in human pregnancy, the transition from uterine quiescence to activation may be a more complex process controlled by many modular regulatory mechanisms These major differences make it difficult to extrapolate the regulatory mechanisms of parturition and the molecular etiologies of preterm birth from animal models to human. Indeed, different species have evolved different strategies to optimize their reproductive success, and many reproductive features have undergone substantial evolutionary divergence The mechanics of human birth is also important in human evolution. Even compared with our close relatives, human birth has several distinctive features, including the orientation of the fetus as it passes through the birth canal, the way the fetus emerges from the birth canal, difficulty during labor, and the helpless state of the infants at birth Many physiological changes and disorders during or even after pregnancy can also influence the fitness of the mothers and infants. For example, gestational diabetes mellitus can cause macrosomia, in which the fetus grows too large to fit through the maternal pelvis Birth timing and pregnancy phenotypes are defined by both the maternal and the fetal genomes. These two genomes are correlated by sharing the maternally transmitted chromosomes . The invSimilar to other complex human traits, gestational duration is likely to be influenced by numerous genetic variants of small effect size and the detection of these small genetic effects requires very large sample sizes. In addition to the problems common for all the genetic studies of complex traits First, it is often difficult to accurately measure gestational age. Ultrasound measurement of fetal crown-rump length (CRL) in the first trimester is the most accurate method; however, this method still has a measurement error of ±5–7 days Second, parturition, term or preterm, could be initiated by various biological pathways and accompanied by different clinical presentations, e.g., with or without premature rupture of membranes (PROM) or other pregnancy complications. Despite their different clinical presentations, these subgroups may share similar biological mechanisms Third, birth timing is influenced by maternal as well as fetal genome, which complicates the statistical genetic analysis. Several analytical approaches have been proposed, but none of these provide an optimal solution Because of these difficulties, genetic studies of gestational duration and preterm birth have had limited success in the past decade. Only very recently did a large two-stage genome-wide study convincingly identify and replicate robust association of six genomic loci The initial effort to identify genetic associations with gestational duration or preterm birth was mostly based on a “candidate gene” approach, focusing on polymorphisms of a specific gene or a panel of genes with suspected functional relevance. A recent comprehensive review of 92 candidate gene studies published between 2007 and 2015 identified 119 candidate genes that have been suspected to be associated with preterm birth The first published GWA study of spontaneous preterm birth utilized the phenotype and genotype data from the Danish National Birth Cohort EBF1, EEFSEC, AGTR2, WNT4, ADCY5, and RAP2C) in the maternal genome robustly associated with gestational duration and preterm birth  play an important role in the duration of pregnancy. Another identified gene region (EEFSEC) suggests that lack of selenium, rather than genes involved in selenoprotein synthesis, might affect preterm birth risk.Similar to many other GWA findings, the functional involvement of these identified loci has not been previously hypothesized. However, the functional roles of these loci in uterine development, maternal nutrition, and vascular control support their mechanistic involvement in birth timing control , which hLike for most other human complex traits, the effect sizes of the six identified associations are uniformly small. In combination, these loci only explain <1% of phenotypic variation in duration of gestation or preterm birth risk More recently, by performing a large scale GWA meta-analysis of more than 80,000 infants from 19 studies, Liu et al. reported a locus on 2q13 in the fetal genome associated with gestational duration with genome-wide significance. The locus harbors genes encoding the proinflammatory cytokines IL-1α and IL-1β, which are central to the induction of uterine activation proteins that precede labor These large studies confirmed that GWA in large datasets is a feasible approach to identify genetic variants associated with gestational duration and preterm birth risk. It can be anticipated that, in foreseeable future, more genomic loci will be discovered and replicated by even larger GWA studies.HSPG2 gene shared by all sisters HSPA1L rare variants in several families. Using high-coverage whole-genome sequencing (WGS) data from 816 parent–offspring trio families, Li et al. de novo mutation burden in preterm birth fetal genomes and those preterm-associated de novo mutations preferentially affect genes involved in early fetal brain development. As the cost of next-generation sequencing will continue to drop, WES or WGS studies in typical families or in large number of samples would eventually reveal many robust rare variant associations that would be missed by the GWA approach.During the past several years, advances in DNA sequencing technologies have enabled genome-wide assessment of rare genetic variants and their role in complex traits Epidemiologic studies in two European populations indicate that a substantial portion of preterm birth risk is maternally determined, thus suggesting a role of mitochondrial inheritance A wide variety of maternal physical and physiological traits and environmental exposures have been associated with pregnancy outcomes. For example, maternal height, weight Genomic data offer the potential to disentangle causal relationships from epidemiological correlations using Mendelian randomization (MR) MR has also been used to study the impacts of intrauterine exposures on health outcomes in offspring Genetic studies usually aim to understand the relationship between genotype and phenotype in individual organisms. Accordingly, the default analytical or sampling units in these studies are individual organisms. Gestational duration and more broadly pregnancy phenotypes, however, are outcomes of a pregnancy event involving both mother and her fetus (sometimes more than one). This fundamental difference requires the analysis of pregnancy phenotypes using a different conceptual framework, in which mother/fetus duos  are more appropriate analytical units.Conventional genetic methods usually regard maternal gestational phenotypes or fetal pregnancy outcomes exclusively pertaining either to mothers or infants and examine genetic associations separately in mothers or in infants A. This cTreating mother/fetus duo (pregnancy) as the analytical unit B provideY) can be modeled by a linear model (Y ∼ h1 + h2 + h3). A list of questions related to the various genetic effects on a pregnancy outcome can be explicitly modeled and tested by different linear hypotheses of these three haplotypes. For example, the parent-of-origin effect in infants can be tested by a hypothesis H0: h1−h2 = h3 . This method can be regarded as the genotype-based test in mother/fetus duos involving three alleles. The advantage of this method is the joint modeling of various maternal and fetal genetic effects.At the single-locus level, the joint effects of the three haplotypes  on a pregnancy phenotype , which will collect genomic data and pregnancy phenotype data from millions of mothers.http://www.birthcohorts.net/) have been established to study the early-life developmental origins of diseases In academic settings, many birth cohorts  as analytical units provides a conceptual framework for pregnancy phenotypes. Many statistical genetic methods can be extended under this framework to accommodate the integrated analysis of the maternal and fetal genome.As indicated by many recent GWA studies complemented with WGS, variants associated with complex traits are overwhelmingly common Human leukocyte antigen (HLA) genes have been suspected to play an important role in pregnancy Gestational duration is, by its nature, a time-to-event variable. As such, a more appropriate statistical approach should be the time-to-event analysis  It is well known that male fetuses have on average shorter gestational duration and higher risk of preterm birth than female fetuses vice versa be influenced by, many maternal phenotypes and physiological changes during pregnancy. Therefore, integrated analysis of multiple pregnancy phenotypes could provide a more complete understanding about the shared genetic causes and interactions between these various phenotypes. Indeed, several gene loci associated with gestational duration have also been associated with birthweight Many pregnancy outcomes such as birthweight and birth length are primarily defined by the duration of gestation. Gestational duration can also influence, or Genetic studies in human populations only identify genomic loci with naturally occurring variants statistically associated with a trait or a disease phenotype. These associated loci might implicate genes or pathways and guide biological insight. However, elucidation of the molecular, cellular, and physiological mechanisms behind a genetic association requires additional functional analysis. These “post-GWA” studies are usually highly domain specific and context dependent There are several challenges in the functional analysis of the genomic loci associated with gestational duration. First, the regulation of birth timing involves multiple maternal and fetal gestational tissues, and the gene expression patterns of these tissues were highly heterogeneous Another challenge is related to our limited physiological knowledge about human birth timing. In order to bridge the gap between molecular phenotype  and organismal phenotype , it is necessary to investigate relevant cellular phenotypes or intermediate physiological phenotypes with more direct connections to specific biological processes. However, most of the physiology of pregnancy that we learned from animal models is not paralleled in human studies. Pathway or network analysis of many associated loci might provide clues about relevant biological processes and cell types.•There is a substantial genetic influence on the gestational duration and the risk of preterm birth.•The biology underlying human birth timing control is complex, and animal studies only provide limited information.•The duration of gestation is important to human health and also has many evolutionary implications.•Genomic studies in large samples could reveal genomic associations and implicate novel biological insights.•Genomics can be used as an epidemiological tool to study the causal relationship between maternal phenotypes (or exposures) and offspring outcomes.•Sample size is the key to successful GWA studies, and replication in smaller but well-phenotyped samples is necessary to validate the findings.•Duration of gestation is defined by maternal and fetal genomes — joint genomic analysis in mother/fetus pairs has unique strength in dissecting the various genetic effects.•Integrated analysis of multiple pregnancy phenotypes will reveal the shared genetic causes and the interactions between these phenotypes.•Functional genomic analysis aided by data generated from other omics studies will accelerate the translation from GWA findings to biological knowledge.The significant health impact, the profound implications of birth timing in human evolution, and the genetic involvement of both maternal and fetal genomes make the genetics of human birth timing a medically significant, scientifically intriguing, and a challenging problem. Despite the many practical and analytical challenges, large-scale genomic studies will continue to reveal more associated genomic loci and the overall genetic architecture of human birth timing. In these studies, the integrated genomic analysis in mother/fetus pairs has unique strength to dissect various genetic effects. Functional analysis of the identified genomic loci, facilitated by the accumulation of gestational tissue- and stage-specific functional genomic data, together with the data generated from other omics studies will collectively provide a deeper insight into the key biological processes and cellular physiology of human birth timing.All authors declare that they have no real, or potential, conflicts of interest.