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Availability of longitudinal body weight (BW) records allows the application of nonlinear models (NLINM) to predict phenotypic and genomic growth curves in dairy cattle. In this regard, we considered a data set including 31,722 BW records from 4,952 female Holstein cattle, during the period from birth (mo 0) to approximately age at first calving (mo 24). Parameters of the growth curves were estimated using 3 NLINM: the logistic (LOG), the Gompertz (GOM), and the Richards (RICH) functions. Residuals for the growth curve parameters from the NLINM applications were used as pseudo-phenotypes in the ongoing genomic analyses with different similarity matrices, including 2 genomic relationship matrices (G1 and G2), a combined pedigree and genomic relationship matrix (H), and 3 kernel matrices. The kernels were a weighted "alike by state" kernel function (K1), an exponential dissimilarity kernel (K2), and a Gaussian kernel (K3). On the basis of G1 and G2 matrices, genomic heritabilities for the growth curve parameters birth weight (W 0 ), mature weight (W m ), and growth rate (k), and the shape parameter (m; only available from RICH) were moderate to large, in the range from 0.29 (m from RICH) to 0.46 (k from RICH). Fitting the similarity matrices based on kernel functions contributed to an increase of the ratio of the variance explained by the similarity matrix in relation to the total variance (compared with the heritability when modeling G1 or G2). Genetic correlations between W 0 , W m , and k were always positive (>0.30), especially for the same growth curve parameters estimated from different NLINM (>0.90). The shape parameter m from RICH was negatively correlated with other growth curve parameters, from -0.29 to -0.95. In a next step, estimated genomic breeding values for growth curve parameters were input data for the respective NLINM, aiming to construct genomic growth curves. Prediction accuracies were correlations between genomic growth curves and genomic breeding values from random regression models for sires and female cattle. Considering all genotyped female cattle with pseudo-phenotypes, prediction accuracies were larger from RICH than from LOG and GOM. However, differences in prediction accuracies from the NLINM × similarity matrix combinations were quite small. Accordingly, in 5-fold cross-validations using heifer groups with masked phenotypes, very similar prediction accuracies across modeling approaches were identified. Especially for specific age months, genomic growth curve predictions were more accurate for sires than for female cattle, indicating that the relationships between animals in training and validation sets are more important than the selection of specific NLINM × similarity matrix combinations., (Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Objective: To determine the combined effect of 60 genetic variants (single nucleotide polymorphisms, SNPs), previously identified as being associated with birth weight, on fetal growth and placental haemodynamics throughout pregnancy., Design: Prospective birth cohort (Generation R Study)., Setting: General multiethnic population., Participants: 5374 singleton liveborn children with genome-wide association arrays and fetal growth data., Methods: Longitudinal and cross-sectional analyses of a genetic score of the total number of birth weight-increasing alleles across the 59 available SNPs and repeated fetal growth and haemodynamic measures., Main Outcome Measures: SD scores (SDS) of fetal weight, (femur) length, head circumference, umbilical artery pulsatility index, uterine artery mean resistance index and placental weight, in different periods of pregnancy until birth., Results: In longitudinal analyses, the effect of the genetic score on the fetal growth measures increased throughout pregnancy (p<0.001). At 20 weeks of gestation, the genetic score was not associated with any of the fetal growth measures, whereas at 30 weeks it was associated with all. The strongest effects were observed at birth: per SD increase in genetic score, birth weight increased by 0.15 SDS (95% confidence interval: 0.13 to 0.18), birth length by 0.12 SDS (0.08 to 0.19) and head circumference by 0.08 SDS (0.05 to 0.12). The genetic score was not associated with placental haemodynamics, but was associated with a 14 g (10 to 18) increase in placental weight per SDS increase in genetic score., Conclusions: Our results suggest that genetic variants related to birth weight exert their combined effect on fetal growth from second half of pregnancy onwards and have no effect on placental haemodynamics., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

Data on calving ease (CE) and birth, weaning weight (WW), and yearling weight (YW) were obtained from the American Simmental Association (ASA) and included pedigree and performance information on 11,640,735 animals. Our objective was to quantify differential response from selection for high CE vs. low birth weight (LBW) in first-calf Simmental heifers. We hypothesized that direct selection for CE should be used as the primary approach to reduce dystocia and mitigate losses in growth-related traits. WW and YW were adjusted to 205 and 365 d of age, respectively. Sire and maternal grandsire (co)variance components for CE, birth weight (BW), and 205-d weaning weight (205-d WW), and sire covariance components for 160-d postweaning gain (160-d gain) were estimated using a sire-maternal grandsire model. Direct and maternal expected progeny differences (EPD) for CE, BW, and 205-d WW and direct EPD for 160-d gain and 365-d yearling weight (365-d YW) for first-calf Simmental heifers population (465,710 animals) were estimated using a threshold-linear multivariate maternal animal model. This population was used to estimate genetic trends and as a selection pool (control) for various selection scenarios. Selection scenarios were high CE (HCE), LBW, the all-purpose selection index (API = -1.8 BW + 1.3 CE + 0.10 WW + 0.20 YW) of the ASA and its two derived subindices: (API1 = 1.3 CE + 0.20 YW) and (API2 = -1.8 BW + 0.20 YW), and lastly Dickerson's selection index (DSI = -3.2 BW + YW). Data for each selection scenario were created by selecting sires with EPD greater than or equal to the average along with the top 75% of dams. Comparison between selection scenarios involved evaluating the direct and maternal genetic trends from these scenarios. Direct heritabilities for CE, BW, 205-d WW, 160-d gain, and 365-d YW of Simmental cattle were 0.23, 0.52, 0.28, 0.21, and 0.33, respectively. The single trait, HCE, selection scenario, as opposed to LBW, increased the intercept for CE by 57.7% and the slopes (P < 0.001) for BW, 205-d WW, 160-d gain, and 365-d YW by 27.9%, 37.5%, 16%, and 28%, respectively. Comparisons of various selection scenarios revealed that the CE-based selection scenarios (HCE, API, and API1) had a greater response for CE and growth traits., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

This study examines the impact of genes associated with normal-range birth weight (2500-4500 grams) on self-rated health in mid-to-late life course. Fifty-eight previously identified genetic variants that explain the variation in the normal-range birth weight were used to construct a genetic measure of birth weight for the non-Hispanic white sample from the Health and Retirement Study. Our results show that the genetic tendency toward higher birth weight predicts better self-rated health in mid-to-late life course net of various demographic, socioeconomic, and health behavioral factors. We also examine the heterogeneous effects of birth-weight genes across birth cohorts and age groups. Moreover, to clarify the paradox that higher birth weight can predict both better self-rated health and higher BMI, we show the positive association between birth weight genes and BMI can only hold within the normal-range BMI (18 ≤ BMI < 30). Overall, these findings suggest the genetic factors underlying the normal-range birth weight can have life-courseimpacts on health.

Epidemiology studies suggested that low birthweight was associated with a higher risk of hypertension in later life. However, little is known about the causality of such associations. In our study, we evaluated the causal association of low birthweight with adulthood hypertension following a standard analytic protocol using the study-level data of 183,433 participants from 60 studies (CHARGE-BIG consortium), as well as that with blood pressure using publicly available summary-level genome-wide association data from EGG consortium of 153,781 participants, ICBP consortium and UK Biobank cohort together of 757,601 participants. We used seven SNPs as the instrumental variable in the study-level analysis and 47 SNPs in the summary-level analysis. In the study-level analyses, decreased birthweight was associated with a higher risk of hypertension in adults (the odds ratio per 1 standard deviation (SD) lower birthweight, 1.22; 95% CI 1.16 to 1.28), while no association was found between genetically instrumented birthweight and hypertension risk (instrumental odds ratio for causal effect per 1 SD lower birthweight, 0.97; 95% CI 0.68 to 1.41). Such results were consistent with that from the summary-level analyses, where the genetically determined low birthweight was not associated with blood pressure measurements either. One SD lower genetically determined birthweight was not associated with systolic blood pressure (β = - 0.76, 95% CI - 2.45 to 1.08 mmHg), 0.06 mmHg lower diastolic blood pressure (β = - 0.06, 95% CI - 0.93 to 0.87 mmHg), or pulse pressure (β = - 0.65, 95% CI - 1.38 to 0.69 mmHg, all p > 0.05). Our findings suggest that the inverse association of birthweight with hypertension risk from observational studies was not supported by large Mendelian randomization analyses.

Abnormal birth weight is the one of the major causes of adulthood diseases such as obesity, metabolic syndrome, cardiovascular disease, type 2 diabetes, and hypertension. Accumulating evidence has suggested that the placental trophoblast is one of the most important reasons that influence birth weight. Our previous study showed that miR-519a are correlated with low fetal birth weight through regulating trophoblast proliferation. To further clarify the detailed mechanisms on how it is regulated, we screened the placental-specific circular RNAs (circRNAs) via microarray assay. The result identified that circ-SETD2 was highly expressed in the placenta of the patients with fetal macrosomia compared with healthy donors. Furthermore, bioinformatic analyses and the luciferase reporter assay revealed that miR-519a possessing the binding sites for both circ-SETD2 and phosphate and tensin homolog was deleted on chromosome 10 (PTEN). Interestingly, upregulation of circ-SETD2 enhanced the proliferation and invasion of the human trophoblast-like cell line HTR8/SVneo cell. A parallel study performed by Western blotting showed that overexpression of circ-SETD2 reduced miR-519a levels and increased PTEN levels in HTR8/SVneo cells. Importantly, the enhancement of HTR8/SVneo cell activity by circ-SETD2 overexpression was nullified when the cells were cotransfected by circ-SETD2 and miR-519a, suggesting the involvement of the circ-SETD2/miR-519a/PTEN axis in trophoblast activity. Taken together, we illustrate the role of circ-SETD2, as an upstream signaling of miR-519a/PTEN, in placenta development via regulating trophoblast proliferation and invasion. These findings improve our understanding of the mechanisms of progression of fetal macrosomia and will guide future development of therapeutic strategies against the disease by targeting the circ-SETD2/miR-519a/PTEN axis., Competing Interests: The authors declare that they have no competing interests., (Copyright © 2020 Dan Wang et al.)

Background: Birthweight marks an important milestone of health across the lifespan, including cardiometabolic disease risk in later life. The placenta, a transient organ at the maternal-fetal interface, regulates fetal growth. Identifying genetic loci where DNA methylation in placenta is associated with birthweight can unravel genomic pathways that are dysregulated in aberrant fetal growth and cardiometabolic diseases in later life., Results: We performed placental epigenome-wide association study (EWAS) of birthweight in an ethnic diverse cohort of pregnant women (n = 301). Methylation at 15 cytosine-(phosphate)-guanine sites (CpGs) was associated with birthweight (false discovery rate (FDR) < 0.05). Methylation at four (26.7%) CpG sites was associated with placental transcript levels of 15 genes (FDR < 0.05), including genes known to be associated with adult lipid traits, inflammation and oxidative stress. Increased methylation at cg06155341 was associated with higher birthweight and lower FOSL1 expression, and lower FOSL1 expression was correlated with higher birthweight. Given the role of the FOSL1 transcription factor in regulating developmental processes at the maternal-fetal interface, epigenetic mechanisms at this locus may regulate fetal development. We demonstrated trans-tissue portability of methylation at four genes (MLLT1, PDE9A, ASAP2, and SLC20A2) implicated in birthweight by a previous study in cord blood. We also found that methylation changes known to be related to maternal underweight, preeclampsia and adult type 2 diabetes were associated with lower birthweight in placenta., Conclusion: We identified novel placental DNA methylation changes associated with birthweight. Placental epigenetic mechanisms may underlie dysregulated fetal development and early origins of adult cardiometabolic diseases., Clinical Trial Registration: ClinicalTrials.gov, NCT00912132.

Reliable single-nucleotide polymorphisms (SNP) effects from genomic best linear unbiased prediction BLUP (GBLUP) and single-step GBLUP (ssGBLUP) are needed to calculate indirect predictions (IP) for young genotyped animals and animals not included in official evaluations. Obtaining reliable SNP effects and IP requires a minimum number of animals and when a large number of genotyped animals are available, the algorithm for proven and young (APY) may be needed. Thus, the objectives of this study were to evaluate IP with an increasingly larger number of genotyped animals and to determine the minimum number of animals needed to compute reliable SNP effects and IP. Genotypes and phenotypes for birth weight, weaning weight, and postweaning gain were provided by the American Angus Association. The number of animals with phenotypes was more than 3.8 million. Genotyped animals were assigned to three cumulative year-classes: born until 2013 (N = 114,937), born until 2014 (N = 183,847), and born until 2015 (N = 280,506). A three-trait model was fitted using the APY algorithm with 19,021 core animals under two scenarios: 1) core 2013 (random sample of animals born until 2013) used for all year-classes and 2) core 2014 (random sample of animals born until 2014) used for year-class 2014 and core 2015 (random sample of animals born until 2015) used for year-class 2015. GBLUP used phenotypes from genotyped animals only, whereas ssGBLUP used all available phenotypes. SNP effects were predicted using genomic estimated breeding values (GEBV) from either all genotyped animals or only core animals. The correlations between GEBV from GBLUP and IP obtained using SNP effects from core 2013 were ≥0.99 for animals born in 2013 but as low as 0.07 for animals born in 2014 and 2015. Conversely, the correlations between GEBV from ssGBLUP and IP were ≥0.99 for animals born in all years. IP predictive abilities computed with GEBV from ssGBLUP and SNP predictions based on only core animals were as high as those based on all genotyped animals. The correlations between GEBV and IP from ssGBLUP were ≥0.76, ≥0.90, and ≥0.98 when SNP effects were computed using 2k, 5k, and 15k core animals. Suitable IP based on GEBV from GBLUP can be obtained when SNP predictions are based on an appropriate number of core animals, but a considerable decline in IP accuracy can occur in subsequent years. Conversely, IP from ssGBLUP based on large numbers of phenotypes from non-genotyped animals have persistent accuracy over time., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Society of Animal Science.)

Background: Atrial fibrillation is a common cardiovascular disorder, characterized by irregular electrical activity in the upper chambers of the heart. Both chronic cardiometabolic risk factors and genetics have been shown to contribute to the development of atrial fibrillation. Birthweight has also been associated with risk of atrial fibrillation., Methods: In the current study, we utilized a genetic approach to study the effect of birthweight on atrial fibrillation. We used 2-sample Mendelian randomization to consider the impact of birthweight on incident atrial fibrillation using summary data from the Early Growth Genetics Consortium GWAS of birthweight and a large biobank-based GWAS of atrial fibrillation., Results: Using the framework of 2-sample Mendelian randomization, we found that a 1-SD genetic elevation of birthweight was associated with increased risk of atrial fibrillation (odds ratio, 1.27 [95% CI, 1.14-1.41]; P =1×10 -5 ) with sensitivity analyses demonstrating robustness of this result., Conclusions: Our findings clarify the directionality of the relationship between birthweight and atrial fibrillation, supporting the growing body of evidence that intrauterine growth has a lifelong impact on cardiovascular health.

Goat meat production, a widely extended activity in the more arid areas of Tunisia, relies on local breeds. These breeds are well adapted to produce under harsh conditions but have a very small size and low productivity. The aim of this study was to establish the basis for future genetic evaluations to improve growth potential of this local stock. A total of 13,095 body weights and pedigree of 945 kids in the caprine herd of the Arid Areas Institute of Médenine were used. Random regression (RR) and multiple trait (MT) models were analyzed and compared. All models included effects of age and weight of dam, age, sex and type of birth of the kid, and year × month of recording, plus random direct and maternal additive genetic and permanent environmental effects. RR and MT models behave similarly, with RR showing slightly better goodness of fit. Heritability estimates for direct (ranging from 0.15 to 0.4) and maternal (0.05 to 0.3) effects showed that efficient selection for weight is feasible in this population. Estimated correlations between ages were high (> 0.8) for direct effects across all ages and low (down to 0.2) for weights taken at distant ages for maternal effects. Estimated genetic correlations between direct and maternal components revealed an antagonistic relationship, especially at early ages. Recording of at least one weight in the first month of age of the kids to evaluate the maternal capacity and a later weight to evaluate direct effects on weight is recommended for genetic evaluations under field conditions.

Separation of autosomal and sex-linked direct additive genetic effects has significant role in sheep breeding programs. Hence, this study was conducted to determine the genetic parameters of autosomal and sex-linked effects for growth traits of Zandi sheep. The data set used in this study contained 7571 Zandi lambs, descendent of 220 sires and 1481 dams, which were collected from Zandi sheep breeding Station at Khojir, Tehran, Iran from 1992 to 2011. The fixed effects included of year (20 classes), season (winter and spring), sex (male or female), birth type (single or twin), and the age of dam (seven classes, 2-8 years old). The data were analyzed using REML methodology by WOMBAT software. In the most appropriate fitted model, based on Akaike's information criterion (AIC) and Bayesian information criterion (BIC), the values of direct autosomal heritabilities of birth weight (BW), kleiber ratio at weaning (KR), 6-month weight (6MW), and 9-month weight (9MW) were 0.12 ± 0.03, 0.29 ± 0.05, 0.14 ± 0.04, and 0.15 ± 0.04, respectively. Furthermore, weaning weight (WW), average daily gain from birth to weaning (ADG), and 12-month weight (12 MW) showed the values of 0.19 ± 0.03 and 0.22 ± 0.03, 0.13 ± 0.05 and 0.15 ± 0.03, and 0.15 ± 0.05 and 0.18 ± 0.05, respectively. Based on the best models through all traits, estimates of the direct sex-linked heritability ranged from 0.0 (WW, ADG, KR, and 6MW) to 0.02 ± 0.03 (12MW). The average of autosomal and sex-linked breeding values (BVs) of body growth traits except KR (for autosomal) and 9MW and 12MW (for sex-linked) were greater than zero. The Pearson's/Spearman's correlation coefficients varied between 0.344 and 0.599/0.30 and 0.61 for autosomal and sex-linked BVs. Direct autosomal and sex-linked additive correlations for growth traits were ranged from - 0.02 (BW-KR) to 0.98 (WW-ADG) and 0.04 (KR-9 MW) to 0.99 (WW-ADG), respectively. Our results revealed that the genetic parameters related to growth traits in Zandi sheep could be more useful in selection strategies.

Lamb live weight is one of the key drivers of profitability on sheep farms. Previous studies in Ireland have estimated genetic parameters for live weight and carcass composition traits using a multi-breed population rather than on an individual breed basis. The objective of the present study was to undertake genetic analyses of three lamb live weight and two carcass composition traits pertaining to purebred Texel, Suffolk and Charollais lambs born in the Republic of Ireland between 2010 and 2017, inclusive. Traits (with lamb age range in parenthesis) considered in the analyses were: pre-weaning weight (20 to 65 days), weaning weight (66 to 120 days), post-weaning weight (121 to 180 days), muscle depth (121 to 180 days) and fat depth (121 to 180 days). After data edits, 137 402 records from 50 372 lambs across 416 flocks were analysed. Variance components were derived using animal linear mixed models separately for each breed. Fixed effects included for all traits were contemporary group, age at first lambing of the dam, parity of the dam, a gender by age of the lamb interaction and a birth type by rearing type of the lamb interaction. Random effects investigated in the pre-weaning and weaning weight analyses included animal direct additive genetic, dam maternal genetic, litter common environment, dam permanent environment and residual variances. The model of analysis for post-weaning, muscle and fat depth included an animal direct additive genetic and litter common environment effect only. Significant direct additive genetic variation existed in all cases. Direct heritability for pre-weaning weight ranged from 0.14 to 0.30 across the three breeds. Weaning weight had a direct heritability ranging from 0.17 to 0.27 and post-weaning weight had a direct heritability ranging from 0.15 to 0.27. Muscle and fat depth heritability estimates ranged from 0.21 to 0.31 and 0.15 to 0.20, respectively. Positive direct correlations were evident for all traits. Results revealed ample genetic variation among animals for the studied traits and significant differences between breeds to suggest that genetic evaluations could be conducted on a per-breed basis.

Genetic parameters were estimated for haemoglobin (Hb) levels in sows and piglets as well as sow reproductive performance and piglet survival. Reproductive traits were available between 2005 and 2014 for 7857 litters from 1029 Large White and 858 Landrace sows. In 2012 and 2013, Hb levels, sow BW and sow back fat depth were measured on 348 sows with 529 litters 5 days prior to farrowing. In addition, Hb levels were available for 1127 one-day-old piglets from 383 litters (a maximum of three piglets per litter) of 277 sows with Hb levels. The average Hb levels in sows (sow Hb), their litters (litter Hb, based on average Hb of three piglets) and individual piglets (piglet Hb) were 112 ± 12.6 g/l, 103 ± 15.3 g/l and 105 ± 21.7 g/l, respectively. Heritabilities for Hb levels were 0.09 ± 0.07 for sow Hb, 0.19 ± 0.11 for litter Hb and 0.08 ± 0.05 for piglet Hb. Estimates for the permanent environment effect of sows were 0.09 ± 0.09 for sow Hb, 0.11 ± 0.12 for litter Hb and 0.12 ± 0.03 for piglet Hb. In comparison, heritabilities for both number of stillborn piglets and pre-weaning survival were lower (0.05 ± 0.01 and 0.04 ± 0.01). Sow BW had no significant heritability, while sow back fat depth was lowly heritable (0.10 ± 0.08). Positive genetic correlations were found between sow Hb and litter Hb (0.64 ± 0.47) and between litter Hb and sow back fat depth (0.71 ± 0.53). Higher litter Hb was genetically associated with lower number of stillborn piglets (-0.78 ± 0.35) and higher pre-weaning survival (0.28 ± 0.33). Negative genetic correlations between sow Hb and average piglet birth weight of the litter (-0.60 ± 0.34) and between piglet Hb and birth weight of individual piglets (-0.37 ± 0.32) indicate that selection for heavier piglets may reduce Hb levels in sows and piglets. Similarly, selection for larger litter size will reduce average piglet birth weight (rg: -0.40 ± 0.12) and pre-weaning survival (-0.57 ± 0.13) and may lead to lower litter Hb (-0.48 ± 0.27). This study shows promising first results for the use of Hb levels as a selection criterion in pig breeding programs, and selection for higher Hb levels may improve piglet survival and limit further reduction in Hb levels in sows and piglets due to selection for larger and heavier litters.

Background: Published data regarding the association between glutathione S-transferase M1 (GSTM1) and glutathione S-transferase T1 (GSTT1) gene polymorphisms and risk of low birth weight (LBW) remains inconclusive, and data on the interactions between the two gene polymorphisms and smoking for LBW susceptibility is lacking. To clarify these associations, a meta-analysis was conducted. Methods: A comprehensive literature search was conducted in multiple databases until 11 January 2018. The pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using fixed or random effects model. Results: Thirty-eight studies from 17 articles concerning maternal and neonatal GSTM1 and GSTT1 gene polymorphism with LBW risk were included in this meta-analysis, and nine studies from five articles provided data of maternal tobacco exposure status during pregnancy. Maternal GSTM1 null genotype was associated with increased LBW risk (OR = 1.27, 95% CI: 1.12-1.45). There was a nonsignificant but positive association (OR = 1.19, 95% CI: 0.97-1.46) between the maternal GSTT1 null genotype and the LBW risk in the overall analysis. There was a null association between neonatal GSTM1 or GSTT1 polymorphism and LBW risk. There were significant associations between the maternal GSTM1 null and GSTT1 null genotype and LBW risk (for the former, OR = 3.85, 95% CI: 1.68-8.81; for the later, OR = 1.88, 95% CI: 1.01-3.50) in individuals with active smoking, respectively. Conclusion: Maternal GSTM1 and GSTT1 null genotypes, but not neonatal genotypes, are suggested to increase LBW susceptibility, and there are interactions between active smoking and these polymorphisms in the development of LBW.

Purpose: To investigate the predictive performance of placental growth factor (PlGF) and soluble FMS-like kinase 1 (sFlt-1) on birth weight and small for gestational age (SGA), in a large, population-based cohort. Methods: Women enrolled in the population-based, prospective Odense Child Cohort Study with early (GA < 20 weeks) and/or late (≥20 weeks) pregnancy blood samples ( n  = 1937) were included. The association between log-transformed values of the biomarkers and birth weight Z-score was studied using multivariate regression models. The prediction of SGA overall, and in women developing preeclampsia, by biomarkers was evaluated using receiver operating characteristic analyses. Results: No substantial associations between early pregnancy biomarkers and SGA were seen. PlGF measured in late pregnancy demonstrated the strongest association with birth weight Z-score (adjusted β-coefficient = 0.43 [95%CI = 0.35; 0.50]). The area under curve (AUC) for predicting SGA was higher for sFlt-1/PlGF compared to sFlt-1 (0.74 versus 0.63, p  = .006) and reached excellent prediction for SGA after preeclampsia (AUC 0.94). Optimal sFlt-1/PlGF ratio cut-offs had higher negative predictive value (NPV) and positive predictive value (PPV) for SGA (cut-off > 5.0; NPV = 99.1%, PPV = 5.4%) compared to each marker individually. Conclusion: The sFlt-1/PlGF ratio is a potential predictor of SGA in population-based screening, particularly when preeclampsia is also present.

Objective: To quantitate the association between birth weight and phenotypes of physical indicators in adulthood, i.e. BMI and waist circumference (WC) and to what degree genetic or environmental factors affect birth weight-obesity association. Methods: A total of 6 623 gender matched twin pairs aged 25 to 79 years were recruited through the Chinese National Twin Registry. The twins reported their own birth weight, current height and weight, and WC using a self-administered questionnaire. BMI was calculated according to the self-reports of body height and weight. Within twin-pair design was used to quantitate the association between birth weight and phenotypes related to obesity while bivariate structural equation models were used to decompose the phenotype correlation. Results: After adjusted for multiple factors, twin-pair analyses within monozygotic (MZ) showed that, on average, a 1.0 kg increase in birth weight corresponded to an increase of 0.33 kg/m(2) in BMI and 0.95 cm in WC in adulthood ( P <0.001). Bivariate structural equation models showed significant positive unique environmental correlation between birth weight and the two obesity-related phenotypes. Conclusion: The study supported the role of twin-specific supply line factors on relationship between birth weight and physical indicators in adulthood.

With an increase in the number of animals genotyped there has been a shift from using pedigree relationship matrices (A) to genomic ones. As the use of genomic relationship matrices (G) has increased, new methods to build or approximate G have developed. We investigated whether the way variance components are estimated should reflect these changes. We estimated variance components for maternal sow traits by solving with restricted maximum likelihood, with four methods of calculating the inverse of the relationship matrix. These methods included using just the inverse of A (A-1), combining A-1 and the direct inverse of G (HDIRECT-1), including metafounders (HMETA-1), or combining A-1 with an approximated inverse of G using the algorithm for proven and young animals (HAPY-1). There was a tendency for higher additive genetic variances and lower permanent environmental variances estimated with A-1 compared with the three H-1 methods, which supports that G-1 is better than A-1 at separating genetic and permanent environmental components, due to a better definition of the actual relationships between animals. There were limited or no differences in variance estimates between HDIRECT-1, HMETA-1, and HAPY-1. Importantly, there was limited differences in variance components, repeatability or heritability estimates between methods. Heritabilities ranged between <0.01 to 0.04 for stayability after second cycle, and farrowing rate, between 0.08 and 0.15 for litter weight variation, maximum cycle number, total number born, total number still born, and prolonged interval between weaning and first insemination, and between 0.39 and 0.44 for litter birth weight and gestation length. The limited differences in heritabilities suggest that there would be very limited changes to estimated breeding values or ranking of animals across models using the different sets of variance components. It is suggested that variance estimates continue to be made using A-1, however including G-1 is possibly more appropriate if refining the model, for traits that fit a permanent environmental effect., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Society of Animal Science.)

Sheep, an important source of meat, dairy products and wool, play an essential part in the global agricultural economy. Body weight and body conformation are key traits in the sheep industry; however, their underlying genetic mechanisms are poorly understood. In this study, a GWAS was implemented to identify promising genes possibly linked to birth weight (BW) and body conformation traits in neonatal sheep, using a high-throughput chip (630 K). After quality control, 277 individuals and 518 203 variants were analyzed using gemma software in a mixed linear model. A total of 48 genome-wide suggestive SNPs were obtained, of which four were associated with BW, four with withers height (WH), 11 with body length (BL) and 29 with chest girth (CG). In total, 39 genes associated with BW and body conformation traits were identified by aligning to the sheep genome (Ovis aries&#95;v4.0), and most of them were involved in the cell cycle and body development. Promising candidate genes found included the following: FOS like 2 or AP-1 transcription factor subunit (FOSL2) for BW; potassium voltage-gated channel subfamily D member 2 (KCND2) for WH; transmembrane protein 117 (TMEM117), transforming growth factor beta induced (TGFBI), and leukocyte cell-derived chemotaxin 2 (LECT2) for BL; and trafficking kinesin protein 1 (TRAK1) and LOC101102529 for CG. These results provide cues for similar studies aiming at uncovering the genetic mechanisms underlying body development, and marker-assisted selection programs focusing on BW and body conformation traits in sheep., (© 2020 Stichting International Foundation for Animal Genetics.)

Non-additive genetic effects are important to increase the accuracy of estimating genetic parameters for growth traits. The aim of this study was to estimate genetic parameters and variance components, specially dominance and epistasis genetic effects, for growth traits (birth weight (BW), weaning weight (WW), 3 (W3), 6 (W6), 9 (W9), and 12 (W12) month weight) in Adani goats. Analyses were carried out using Bayesian method via Gibbs sampler animal model by fitting of 18 different models. All fixed effects (sex, type of birth, age of dam, and year) showed significant effects on BW, WW, W3, and W6, whereas the type of birth and age of dam were not significant on W9 and W12. With the best model, direct heritability estimates were 0.347, 0.178, 0.158, 0.359, 0.278, and 0.281 for BW, WW, W3, W6, W9, and W12 traits, respectively. Maternal permanent environmental effect was significant for BW and WW, but maternal genetic effect was significant only for W3. Dominance and epitasis effects were significant almost for all traits and as a proportion of phenotypic variance were ranged from 0.115 to 0.258 and 0.107 to 0.218, respectively. The range of accuracy of breeding values estimated for growth traits with appropriate evaluation models was from 0.521 to 0.652, 0.616 to 0.694, and 0.548 to 0.684 for the all animals, 10% of the best males and 50% of the best females, respectively. When dominance and epistasis effects added to models, the error variance was reduced and the accuracy of estimated breeding values increased. The accuracy of the best model showed a significant difference with the accuracy of other models (p < 0.01). The result of the present study suggests that non-additive genetic effects should be in genetic evaluation models for goat growth traits because of its effect on accuracy of estimated breeding values.

The objective of this study was to estimate group- and breed-specific genetic parameters for reproductive traits in Chinese Duroc, Landrace, and Yorkshire populations. Records for reproductive traits between April 1998 and December 2017 from 92 nucleus pig breeding farms, which were involved in the China Swine Genetic Improvement Program, were analysed. Due to weak genetic connectedness across all farms, connectedness groups consisting of related farms were used. Three, two and four connectedness groups for Duroc, Landrace and Yorkshire were firstly established according to the genetic connectedness rating among farms. For each connectedness group a five-trait animal model was implemented, and via restricted maximum likelihood procedure the genetic parameters were estimated for five reproductive traits i.e., total number born (TNB), number born alive (NBA), litter weight at farrowing (LWF), farrowing interval (FI) and age at first farrowing (AFF). The average of heritabilities among connectedness groups ranged from .01 (for FI in Yorkshire) to .30 (for AFF in Duroc). Estimates of repeatability for litter traits ranged from .14 to .20 and were consistent for each breed, and for FI, the estimates varied from .01 to .11 across breeds and groups. The estimated genetic correlations among litter traits (i.e., TNB, NBA and LWF) were all significantly high (>.56) and similar across breeds. Averaged genetic correlations over three breeds were -.25, -.27, -.18, -.04, -.10, -.02, and .28 for FI-TNB, FI-NBA, FI-LWF, AFF-TNB, AFF-NBA, AFF-LWF and FI-AFF, respectively. The standard errors of the estimates were all very low (<0.01) in most situations. Results from this study suggest that selection based on TNB which is currently used in dam line selection index can improve NBA and LWF simultaneously. However, care should be taken on FI and AFF as they are both greatly influenced by non-genetic factors such as management and measurement., (© 2019 Blackwell Verlag GmbH.)

Improving the genetic process of growth traits is one of the major goals in the beef cattle industry, as it can increase meat production and reduce the cost of raising animals. Although several quantitative trait loci affecting growth traits in beef cattle have been identified, the genetic architecture of these economically important traits remains elusive. This study aims to map single nucleotide polymorphisms (SNPs) and genes associated with birth weight (BW), yearling weight (YW), average daily gain from birth to yearling (BYADG), and body weight at the age of 18 months (18MW) in a Chinese Simmental beef cattle population using a weighted, single-step, genome-wide association study (wssGWAS). Phenotypic and pedigree data from 6022 animals and genotypes from 744 animals (596,297 SNPs) were used for an association analysis. The results showed that 66 genomic windows explained 1.01-20.15% of the genetic variance for the four examined traits, together with the genes near the top SNP within each window. Furthermore, the identified genomic windows (>1%) explained 50.56%, 57.71%, 61.78%, and 37.82% of the genetic variances for BW, YW, BYADG, and 18MW, respectively. Genes with potential functions in muscle development and regulation of cell growth were highlighted as candidates for growth traits in Simmental cattle ( SQOR and TBCB for BW, MYH10 for YW, RLF for BYADG, and ARHGAP31 for 18MW). Moreover, we found 40 SNPs that had not previously been identified as being associated with growth traits in cattle. These findings will further advance our understanding of the genetic basis for growth traits and will be useful for the molecular breeding of BW, YW, BYADG, and 18MW in the context of genomic selection in beef cattle., Competing Interests: The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Background Preterm delivery and low birth weight are prospectively associated with low cardiorespiratory fitness (CRF). However, whether birth weight, within the at-term range, is associated with later CRF is largely unknown. Thus, the aim of the current study was to examine this issue and whether such association, if any, is explained by shared and/or nonshared familial factors. Methods and Results We conducted a prospective cohort study, including 286 761 young male adults and a subset of 52 544 siblings born at-term. Objectively measured data were retrieved from total population registers. CRF was tested at conscription and defined as the maximal load obtained on a cycle ergometer. We used linear and nonlinear and fixed-effects regression analyses to explore associations between birth weight and CRF. Higher birth weight, within the at-term range, was strongly associated with increasing CRF in a linear fashion. Each SD increase in birth weight was associated with an increase of 7.9 (95% CI, 7.8-8.1) and 6.6 (95% CI; 5.9-7.3) Wmax in the total and sibling cohorts, respectively. The association did not vary with young adulthood body mass index. Conclusions Birth weight is strongly associated with increasing CRF in young adulthood among men born at-term, across all categories of body mass index. This association appears to be mainly driven by factors that are not shared between siblings. Hence, CRF may to some extent be determined already in utero. Prevention of low birth weight, also within the at-term-range, can be a feasible mean of increasing adult CRF and health.

Background: A link between suboptimal fetal growth and higher risk of cardiovascular disease (CVD) is well documented. It has been difficult to assess the contribution of environmental versus genetic factors to the association, as these factors are closely connected in nuclear families. We investigated the association between offspring birthweight and CVD mortality in parents, aunts and uncles, and examined whether these associations are explained by CVD risk factors., Methods: We linked Norwegian data from the Medical Birth Registry, the Cause of Death Registry and cardiovascular surveys. A total of 1 353 956 births (1967-2012) were linked to parents and one maternal and one paternal aunt/uncle. Offspring birthweight and CVD mortality association among all relationships was assessed by hazard ratios (HR) from Cox regressions. The influence of CVD risk factors on the associations was examined in a subgroup., Results: Offspring birthweight was inversely associated with CVD mortality among parents and aunts/uncles. HR of CVD mortality for one standard deviation (SD) increase in offspring birthweight was 0.72 (0.69-0.75) in mothers and 0.89 (0.86-0.92) in fathers. In aunts/uncles, the HRs were between 0.90 (0.86-0.95) and 0.93 (0.91-0.95). Adjustment for CVD risk factors in a subgroup attenuated all the associations., Conclusions: Birthweight was associated with increased risk of CVD in parents and in aunts/uncles. These associations were largely explained by CVD risk factors. Our findings suggest that associations between offspring birthweight and CVD in adult relatives involve both behavioural variables (especially smoking) and shared genetics relating to established CVD risk factors., (© The Author(s) 2019. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Maternal pre-pregnancy body mass index (BMI) is positively associated with offspring birth weight (BW) and BMI in childhood and adulthood. Each of these associations could be due to causal intrauterine effects, or confounding (genetic or environmental), or some combination of these. Here we estimate the extent to which the association between maternal BMI and offspring body size is explained by offspring genotype, as a first step towards establishing the importance of genetic confounding., Methods: We examined the associations of maternal pre-pregnancy BMI with offspring BW and BMI at 1, 5, 10 and 15 years, in three European birth cohorts (n ≤11 498). Bivariate Genomic-relatedness-based Restricted Maximum Likelihood implemented in the GCTA software (GCTA-GREML) was used to estimate the extent to which phenotypic covariance was explained by offspring genotype as captured by common imputed single nucleotide polymorphisms (SNPs). We merged individual participant data from all cohorts, enabling calculation of pooled estimates., Results: Phenotypic covariance (equivalent here to Pearson's correlation coefficient) between maternal BMI and offspring phenotype was 0.15 [95% confidence interval (CI): 0.13, 0.17] for offspring BW, increasing to 0.29 (95% CI: 0.26, 0.31) for offspring 15 year BMI. Covariance explained by offspring genotype was negligible for BW [-0.04 (95% CI: -0.09, 0.01)], but increased to 0.12 (95% CI: 0.04, 0.21) at 15 years, which is equivalent to 43% (95% CI: 15%, 72%) of the phenotypic covariance. Sensitivity analyses using weight, BMI and ponderal index as the offspring phenotype at all ages showed similar results., Conclusions: Offspring genotype explains a substantial fraction of the covariance between maternal BMI and offspring adolescent BMI. This is consistent with a potentially important role for genetic confounding as a driver of the maternal BMI-offspring BMI association., (© The Author(s) 2019. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Pathological myopia is one of the leading causes of blindness globally. Lower birth weight (BW) within the normal range has been reported to increase the risk of myopia, although findings conflict. We sought to estimate the causal effect of BW on refractive error using Mendelian randomisation (MR), under the assumption of a linear relationship., Methods: Genetic variants associated with BW were identified from meta-analysis of a genome-wide association study (GWAS) for self-reported BW in 162 039 UK Biobank participants and a published Early Growth Genetics (EGG) consortium GWAS (n=26 836). We performed a one-sample MR analysis in 39 658 unrelated, adult UK Biobank participants (independent of the GWAS sample) using an allele score for BW as instrumental variable. A two-sample MR sensitivity analysis and conventional ordinary least squares (OLS) regression analyses were also undertaken., Results: In OLS analysis, BW showed a small, positive association with refractive error: +0.04 D per SD increase in BW (95% CI 0.02 to 0.07; p=0.002). The one-sample MR-estimated causal effect of BW on refractive error was higher, at +0.28 D per SD increase in BW (95% CI 0.05 to 0.52, p=0.02). A two-sample MR analysis provided similar causal effect estimates, with minimal evidence of directional pleiotropy., Conclusions: Our study suggests lower BW within the normal range is causally associated with a more myopic refractive error. However, the impact of the causal effect was modest (range 1.00 D covering approximately 95% of the population)., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

Genomic imprinting leads to mono-allelic expression of genes based on parent of origin. Therian mammals and angiosperms evolved this mechanism in nutritive tissues, the placenta, and endosperm, where maternal and paternal genomes are in conflict with respect to resource allocation. We used RNA-seq to analyze allelic bias in the expression of 91 known imprinted genes in term human placentas from a prospective cohort study in Mali. A large fraction of the imprinted exons (39%) deviated from mono-allelic expression. Loss of imprinting (LOI) occurred in genes with either maternal or paternal expression bias, albeit more frequently in the former. We characterized LOI using binomial generalized linear mixed models. Variation in LOI was predominantly at the gene as opposed to the exon level, consistent with a single promoter driving the expression of most exons in a gene. Some genes were less prone to LOI than others, particularly lncRNA genes were rarely expressed from the repressed allele. Further, some individuals had more LOI than others and, within a person, the expression bias of maternally and paternally imprinted genes was correlated. We hypothesize that trans-acting maternal effect genes mediate correlated LOI and provide the mother with an additional lever to control fetal growth by extending her influence to LOI of the paternally imprinted genes. Limited evidence exists to support associations between LOI and offspring phenotypes. We show that birth length and placental weight were associated with allelic bias, making this the first comprehensive report of an association between LOI and a birth phenotype., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Being born small (SGA) or large for gestational age (LGA) is associated with adverse birth outcomes and metabolic diseases in later life of the offspring. It is known that aberrations in growth during gestation are related to altered placental function. Placental function is regulated by epigenetic mechanisms such as DNA methylation. Several studies in recent years have demonstrated associations between altered patterns of DNA methylation and adverse birth outcomes. However, larger studies that reliably investigated global DNA methylation are lacking. The aim of this study was to characterize global placental DNA methylation in relationship to size for gestational age. Global DNA methylation was assessed in 1023 placental samples by LC-MS/MS. LGA offspring displayed significantly higher global placental DNA methylation compared to appropriate for gestational age (AGA; p < 0.001). ANCOVA analyses adjusted for known factors impacting on DNA methylation demonstrated an independent association between placental global DNA methylation and LGA births (p < 0.001). Tertile stratification according to global placental DNA methylation levels revealed a significantly higher frequency of LGA births in the third tertile. Furthermore, a multiple logistic regression analysis corrected for known factors influencing birth weight highlighted an independent positive association between global placental DNA methylation and the frequency of LGA births (p = 0.001).

Imprinted genes play a pivotal role in placental processes underlying fetal development, and much interest centers on discerning whether these loci, via changes in DNA methylation and/or gene expression, inform disruptions in appropriate fetal growth. In this study, we comprehensively profiled DNA methylation across the placental imprintome and assessed the relationship with gene expression levels and aberrant fetal growth.Placental DNA methylation across 153 imprinted loci, including imprint control regions (ICR) and surrounding non-ICR regions, was surveyed using the Nimblegen TruSeq bisulfite sequencing platform among participants enrolled in the Rhode Island Child Health Study (RICHS, n = 163). Methylation and gene expression associations were assessed using eQTM analysis. Differential methylation analysis contrasting small (SGA) and large for gestational age (LGA) infants against appropriate for gestational age (AGA) infants was assessed using the DMRcate R package.We identified 34 SGA-related differentially methylated regions (DMRs) and 9 LGA-related DMRs (FDR<0.05), and these BW-DMRs predominated in promoter and intronic regions. We observed overall hypomethylation among SGA-DMRs overlapping maternally expressed (paternally imprinted) genes while no parent-of-origin effect was observed among LGA DMRs. Three BW-DMRs, mapping to GABRG3, IGF1R and MEST , were common to SGA and LGA placenta. We did not observe significant correlations between BW-DMR-associated CpG methylation and gene expression levels.We report the first in-depth characterization of the placental imprintome in a population-wide setting. Our findings reveal growth-related differences in methylation without concomitant expression differences in regions that extend beyond typically interrogated imprinted loci, highlighting potentially novel placental biomarkers of growth and development.

There is increasing interest within the genetics community in estimating the relative contribution of parental genetic effects on offspring phenotypes. Here we describe the user-friendly M-GCTA software package used to estimate the proportion of phenotypic variance explained by maternal (or alternatively paternal) and offspring genotypes on offspring phenotypes. The tool requires large studies where genome-wide genotype data are available on mother- (or alternatively father-) offspring pairs. The software includes several options for data cleaning and quality control, including the ability to detect and automatically remove cryptically related pairs of individuals. It also allows users to construct genetic relationship matrices indexing genetic similarity across the genome between parents and offspring, enabling the estimation of variance explained by maternal (or alternatively paternal) and offspring genetic effects. We evaluated the performance of the software using a range of data simulations and estimated the computing time and memory requirements. We demonstrate the use of M-GCTA on previously analyzed birth weight data from two large population based birth cohorts, the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Norwegian Mother and Child Cohort Study (MoBa). We show how genetic variation in birth weight is predominantly explained by fetal genetic rather than maternal genetic sources of variation.

Background: Leptin regulates satiety and energy homoeostasis, and plays a key role in placentation in pregnancy. Previous studies have demonstrated regulation of leptin gene (LEP) expression and/or methylation in placenta and cord blood in association with early life exposures, but most have been small and have not considered the influence of genetic variation. Here, we investigated the relationship between maternal factors in pregnancy, infant anthropometry and LEP genetic variation with LEP promoter methylation at birth and 12 months of age., Methods: LEP methylation was measured in cord (n = 877) and 12-month (n = 734) blood in the Barwon Infant Study, a population-based pre-birth cohort. Infant adiposity at birth and 12-months was measured as triceps and subscapular skinfold thickness. Cross-sectional regression tested associations of methylation with pregnancy and anthropometry measures, while longitudinal regression tested if birth anthropometry predicted 12-month LEP methylation levels., Results: Male infants had lower LEP methylation in cord blood (-2.07% average methylation, 95% CI (-2.92, -1.22), p < 0.001). Genetic variation strongly influenced DNA methylation at a single CpG site, which was also negatively associated with birth weight (r = -0.10, p = 0.003). Pre-eclampsia was associated with lower cord blood methylation at another CpG site (-6.06%, 95% CI (-10.70, -1.42), p = 0.01). Gestational diabetes was more modestly associated with methylation at two other CpG units. Adiposity at birth was associated with 12-month LEP methylation, modified by rs41457646 genotype. There was no association of LEP methylation with 12-month anthropometric measures., Conclusions: Infant sex, weight, genetic variation, and exposure to pre-eclampsia and gestational diabetes, are associated with LEP methylation in cord blood. Infant adiposity at birth predicts 12-month blood LEP methylation in a genotype-dependent manner. These findings are consistent with genetics and anthropometry driving altered LEP epigenetic profile and expression in infancy. Further work is required to confirm this and to determine the long-term impact of altered LEP methylation on health.

We investigated the relationship between litter size at birth and within-litter birth weight (BW) characteristics of laboratory mice as a pilot mammal for pig. We obtained records of number born alive (NBA) and total and mean litter BW (LWB, MWB), and maximum and minimum values of within-litter BW (MaxIWB, MinIWB), range and standard deviation (Range, SDIWB), skewness (Skew), and kurtosis (Kurt) of within-litter BW for 656 litters at first parity. Pearson's correlations of NBA were highly positive with LWB (0.92), weakly negative with MWB (-0.31), MaxIWB (-0.19), and MinIBW (-0.33), and those of MWB were negligible with Range, SDIWB, Skew, and Kurt (-0.10 to 0.06). Estimated heritabilities, treated as dam traits, were 0.32 for NBA, 0.39 for LWB, 0.24 for MWB, 0.28 for MaxIWB, 0.05 for MinIWB, 0.16 for Range, 0.17 for SDIWB, and 0.00 for Skew and Kurt. Estimated genetic correlation between NBA and LWB was high (0.95). Therefore, LWB could be promising for efficiently improving NBA. The estimated genetic correlation of NBA was negligible with MWB (0.00), positive with MaxIWB (0.10), Range (0.48), and SDIWB (0.36), and negative with MinIWB (-0.36), suggesting that selection for increased NBA brings larger SDIWB and lighter MinIWB., (© 2020 Japanese Society of Animal Science.)

The objectives of this study were to compare the genetic parameters for calving difficulty (CD), which were treated as both a calf trait (CD&#95;calf) and as a dam trait (CD&#95;dam), and to clarify genetic relationships of these CDs with body size traits of calves at birth and carcass traits. In total, the CD records and calf body measurements of 2,258 Japanese Black cattle heifers were used in this study, in addition to the carcass records of 4,300 feedlot steers and heifers. Direct heritability of CD&#95;calf (0.44) was higher than maternal heritability of CD&#95;calf (0.30), as well as CD&#95;dam heritability (0.25). Direct genetic correlations between CD&#95;calf and calf body size were moderate to strongly positive (0.64 to 0.81). The correlations between EBVs of CDs and carcass weight were also positive (0.30 to 0.64). These positive relationships showed that genetically improving CD (reducing dystocia) could produce smaller calves and carcasses. In contrast, the correlations between CDs and beef marbling score were weak, suggesting that improving CD would not influence meat quality traits. Fitting an animal model to CD&#95;calf could be more preferred to fitting the model to CD&#95;dam, because the former could separate the genetic effects of dams and calves., (© 2020 Japanese Society of Animal Science.)

Stabilizing selection is thought to be common in wild populations and act as one of the main evolutionary mechanisms, which constrain phenotypic variation. When multiple traits interact to create a combined phenotype, correlational selection may be an important process driving adaptive evolution. Here, we report on phenotypic selection and evolutionary changes in two natal traits in a semidomestic population of reindeer (Rangifer tarandus) in northern Finland. The population has been closely monitored since 1969, and detailed data have been collected on individuals since they were born. Over the length of the study period (1969-2015), we found directional and stabilizing selection toward a combination of earlier birth date and heavier birth mass with an intermediate optimum along the major axis of the selection surface. In addition, we demonstrate significant changes in mean traits toward earlier birth date and heavier birth mass, with corresponding genetic changes in breeding values during the study period. Our results demonstrate evolutionary changes in a combination of two traits, which agree closely with estimated patterns of phenotypic selection. Knowledge of the selective surface for combinations of genetically correlated traits are vital to predict how population mean phenotypes and fitness are affected when environments change., (© 2019 The Authors. Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.)

Heritabilities of litter size traits at birth (total number born (TNB), number born alive (NBA), and number still born (NSB)) and their genetic correlations with body measurement (body height, body length, front width (FW), chest width (CW), hind width, chest depth, chest girth, front cannon circumference, and rear cannon circumference) and production traits (ages at the start and end of performance testing (D30 and D105), average daily gain (ADG), backfat thickness, and loin muscle area) in purebred Duroc pigs were estimated. Records of performance testing for 2,835 animals and farrowing records of 1,168 litters from 437 dams were used. Genetic parameters were estimated using single-trait and two-trait animal models. Permanent environment effect was considered for litter size traits and common litter environmental effect was considered for body measurement and production traits. The estimated heritability was 0.10 ± 0.06 for TNB, 0.16 ± 0.06 for NBA, and 0.08 ± 0.05 for NSB. Positive genetic correlation of NBA was estimated with D30, D105, and ADG (0.51, 0.11, and 0.39). The estimated genetic correlation of NBA was 0.47 ± 0.17 with FW and 0.55 ± 0.18 with CW, implying that FW and CW could be promising indicator traits for efficiently improving NBA., (© 2020 Japanese Society of Animal Science.)

Background: Differences between an individual's estimated epigenetic gestational age (EGA) and their actual gestational age (GA) are defined as gestational age acceleration (GAA). GAA is associated with increased birthweight and birth length. Whether these associations persist through childhood is yet to be investigated., Methods: We examined the association between GAA and trajectories of height and weight from birth to 10 years (n = 785) in a British birth cohort study, the Avon Longitudinal Study of Parents and Children (ALSPAC). EGA of participants was estimated using DNA methylation data from cord blood using a recently developed prediction model. GAA of participants, measured in weeks, was calculated as the residuals from a regression model of EGA on actual GA. Analyses were performed using linear spline multilevel models and adjusted for maternal age, maternal pre-pregnancy BMI, maternal smoking during pregnancy, and maternal education., Results: In adjusted analyses, offspring with a one-week greater GAA were born on average 0.14 kg heavier (95% confidence interval (CI) 0.09, 0.19) and 0.55 cm taller (95% CI 0.33, 0.78) at birth. These differences in weight persisted up to approximately age 9 months but thereafter began to attenuate. From age 5 years onwards, the association between GAA and weight reversed such that GAA was associated with lower weight and this association strengthened with age (mean difference at age 10 years - 0.60 kg, 95% CI - 1.19, - 0.01). Differences in height persisted only up to age 9 months (mean difference at 9 months 0.15 cm, 95% CI - 0.09, 0.39). From age 9 months to age 10 years, offspring with a one-week greater GAA were of comparable height with those with no GAA (mean difference at age 10 years - 0.07 cm, 95% CI - 0.64, 0.50)., Conclusions: Gestational age acceleration is associated with increased birth weight and length and these differences persist to age 9 months. From age 5 years onwards, the association of GAA and weight reverses such that by age 10 years, greater GAA is associated with lower childhood weight. Further work is required to examine whether the weight effects of GAA strengthen through adolescence and into early adulthood.

Background: Single nucleotide polymorphism (SNP) arrays have facilitated discovery of genetic markers associated with complex traits in domestic cattle; thereby enabling modern breeding and selection programs. Genome-wide association analyses (GWAA) for growth traits were conducted on 10,837 geographically diverse U.S. Gelbvieh cattle using a union set of 856,527 imputed SNPs. Birth weight (BW), weaning weight (WW), and yearling weight (YW) were analyzed using GEMMA and EMMAX (via imputed genotypes). Genotype-by-environment (GxE) interactions were also investigated., Results: GEMMA and EMMAX produced moderate marker-based heritability estimates that were similar for BW (0.36-0.37, SE = 0.02-0.06), WW (0.27-0.29, SE = 0.01), and YW (0.39-0.41, SE = 0.01-0.02). GWAA using 856K imputed SNPs (GEMMA; EMMAX) revealed common positional candidate genes underlying pleiotropic QTL for Gelbvieh growth traits on BTA6, BTA7, BTA14, and BTA20. The estimated proportion of phenotypic variance explained (PVE) by the lead SNP defining these QTL (EMMAX) was larger and most similar for BW and YW, and smaller for WW. Collectively, GWAAs (GEMMA; EMMAX) produced a highly concordant set of BW, WW, and YW QTL that met a nominal significance level (P ≤ 1e-05), with prioritization of common positional candidate genes; including genes previously associated with stature, feed efficiency, and growth traits (i.e., PLAG1, NCAPG, LCORL, ARRDC3, STC2). Genotype-by-environment QTL were not consistent among traits at the nominal significance threshold (P ≤ 1e-05); although some shared QTL were apparent at less stringent significance thresholds (i.e., P ≤ 2e-05)., Conclusions: Pleiotropic QTL for growth traits were detected on BTA6, BTA7, BTA14, and BTA20 for U.S. Gelbvieh beef cattle. Seven QTL detected for Gelbvieh growth traits were also recently detected for feed efficiency and growth traits in U.S. Angus, SimAngus, and Hereford cattle. Marker-based heritability estimates and the detection of pleiotropic QTL segregating in multiple breeds support the implementation of multiple-breed genomic selection.

The association between lower birth weight and increased disease risk in adulthood has drawn attention to the physiological processes that shape the gestational environment. We implement genome-wide transcriptional profiling of maternal blood samples to identify subsets of genes and associated transcription control pathways that predict offspring birth weight. Female participants (N = 178, mean = 27.0 years) in a prospective observational birth cohort study were contacted between 2009 and 2014 to identify new pregnancies. An in-home interview was scheduled for early in the third trimester (mean = 30.3 weeks) to collect pregnancy-related information and a blood sample, and birth weight was measured shortly after delivery. Transcriptional activity in white blood cells was determined with a whole-genome gene expression direct hybridization assay. Fifty transcripts were differentially expressed in association with offspring birth weight, with 18 up-regulated in relation to lower birth weight, and 32 down-regulated. Examination of transcription control pathways identified increased activity of NF-κB, AP-1, EGR1, EGR4, and Gfi families, and reduced the activity of CEBP, in association with lower birth weight. Transcript origin analyses identified non-classical CD16+ monocytes, CD1c+ myeloid dendritic cells, and neutrophils as the primary cellular mediators of differential gene expression. These results point toward a systematic regulatory shift in maternal white blood cell activity in association with lower offspring birth weight, and they suggest that analyses of gene expression during gestation may provide insight into regulatory and cellular mechanisms that influence birth outcomes.

We estimated genetic parameters in Landrace and Large White pig populations for litter traits at farrowing (total number born, number born alive, number stillborn, total litter weight at birth (LWB), and mean litter weight at birth) and those at weaning (litter size at weaning (LSW), total litter weight at weaning (LWW), mean litter weight at weaning (MWW), and survival rate from farrowing to weaning). We analyzed 65,579 records at farrowing and 6,306 at weaning for Landrace, and 52,557 and 5,360, respectively, for Large White. Single-trait and two-trait repeatability animal models were exploited to estimate heritability and genetic correlation respectively. Heritability estimates of LSW were 0.09 for Landrace and 0.08 for Large White. Genetic correlations of LSW with MWW were -0.43 for Landrace and -0.24 for Large White. Genetic correlations of LSW with LWW and LWB ranged from 0.5 to 0.6. The genetic correlation of MWW with LWW was positive, but that with LWB was negligible. The results indicate that utilizing LWW or LWB could improve LSW efficiently, despite the antagonistic genetic correlation between LSW and MWW., (© 2019 Japanese Society of Animal Science.)

Background: Increasing evidence suggests that prenatal exposure to arsenic, even at common environmental levels, adversely affects child health. These adverse effects include impaired fetal growth, which can carry serious health implications lifelong. However, the mechanisms by which arsenic affects fetal health and development remain unclear., Methods: We addressed this question using a group of 46 pregnant women selected from the New Hampshire Birth Cohort Study (NHBCS), a US cohort exposed to low-to-moderate arsenic levels in drinking water through the use of unregulated private wells. Prenatal arsenic exposure was assessed using maternal urine samples taken at mid-gestation. Samples of the fetal portion of the placenta were taken from the base of the umbilical cord insertion at the time of delivery, stored in RNAlater and frozen. We used RNA sequencing to analyze changes in global gene expression in the fetal placenta associated with in utero arsenic exposure, adjusting for maternal age. Gene set enrichment analysis and enrichment mapping were then used to identify biological processes represented by the differentially expressed genes. Since our previous analyses have identified considerable sex differences in placental gene expression associated with arsenic exposure, we analyzed male and female samples separately., Results: At FDR < 0.05, no genes were differentially expressed in female placenta, while 606 genes were differentially expressed in males. Genes showing the most significant associations with arsenic exposure in females were LEMD1 and UPK3B (fold changes 2.51 and 2.48), and in males, FIBIN and RANBP3L (fold changes 0.14 and 0.15). In gene set enrichment analyses, at FDR < 0.05, a total of 211 gene sets were enriched with differentially expressed genes in female placenta, and 154 in male placenta. In female but not male placenta, 103 of these gene sets were also associated with reduced birth weight., Conclusions: Our results reveal multiple biological functions in the fetal placenta that are potentially affected by increased arsenic exposure, a subset of which is sex-dependent. Further, our data suggest that in female infants, the mechanisms underlying the arsenic-induced reduction of birth weight may involve activation of stress response pathways.

Accurate prediction of an individual's phenotype from their DNA sequence is one of the great promises of genomics and precision medicine. We extend a powerful individual-level data Bayesian multiple regression model (BayesR) to one that utilises summary statistics from genome-wide association studies (GWAS), SBayesR. In simulation and cross-validation using 12 real traits and 1.1 million variants on 350,000 individuals from the UK Biobank, SBayesR improves prediction accuracy relative to commonly used state-of-the-art summary statistics methods at a fraction of the computational resources. Furthermore, using summary statistics for variants from the largest GWAS meta-analysis (n ≈ 700, 000) on height and BMI, we show that on average across traits and two independent data sets that SBayesR improves prediction R 2 by 5.2% relative to LDpred and by 26.5% relative to clumping and p value thresholding.

Background: Weight at birth is an important predictor of neonatal mortality and morbidity in dogs. In addition, the birthweight of the puppies in a litter influences the decision to perform a cesarean section. The goal of the present study was to estimate heritabilities for the puppy birth weight in Labrador retrievers., Results: Of the 1138 Labrador retriever litters whelped at the Guiding Eye for the Blind between September 2001 and February 2018, 1013 were included in the analyses after data editing. Puppy weight at birth was the target trait, measured on a continuous scale in pounds, and converted to grams. Linear mixed models were used to identify factors influencing puppy weight at birth. The analyses showed that the sex of the puppy, litter size, length of gestation, adult weight of the dam, parity, year of birth and inbreeding coefficient of the puppies and dams contributed to the variance of the puppy birth weight. Dam and litter effects were included as random effects. A multiple trait derivative free restricted maximum likelihood approach was used to estimate variance components and genetic parameters with two animal models, one without covariates (Model 1) and one with covariates (Model 2). Sex of the puppy and litter size had moderate effects, whereas gestation length, adult weight of the dam, parity, year of birth and inbreeding coefficients of the dam and the puppies had minor effects. Estimates for Model 1 and Model 2 were 0.21 and 0.17 for the direct heritabilities, 0.22 and 0.22 for the maternal additive genetic heritabilities, 0.07 and 0.07 for the maternal permanent environmental proportions, and 0.14 and 0.08 for the environmental proportion of the litter., Conclusions: In order to estimate reliable breeding values for puppy weight at birth, sex of puppy, litter size, length of gestation and the adult weight of the dam should be included. Estimates could benefit from weighing the dams prior to each mating.

This study used pedigree information and data collected from 1979 to 2012 at the Raeini Cashmere goat breeding station, located in Baft City in Kerman Province in southeastern Iran. Genetic and phenotypic parameters for early reproductive traits of breeding does, including total numbers of kids born at first kidding (LSB1), total numbers of kids weaned at first kidding (LSW1), total birth weight of all kids born at first kidding (LWB1), total weaning weight of all kids weaned at first kidding (LWW1), and age at first kidding (AFK), were estimated using a Bayesian approach via Gibbs sampling. Posterior means for heritability estimates of LSB1, LSW1, LWB1, LWW1, and AFK were statistically significant, with values of 0.12, 0.23, 0.17, 0.15, and 0.46, respectively. Low-to-moderate additive genetic variation was present for the studied reproductive traits. Estimated genetic correlations among LSB1, LSW1, LWB1, and LWW1 were statistically significant and ranged from 0.12 between LWB1 and LWW1 to 0.72 between LSB1 and LSW1. Corresponding phenotypic correlation estimates were also statistically significant and ranged from 0.04 between LWB1 and LWW1 to 0.55 between LSB1 and LSW1. Posterior means of genetic and phenotypic correlations between AFK and other studied traits were statistically significant only for LSB1 and LWB1. For LSB1, LSW1, LWB1, and LWW1, we conclude that genetic and phenotypic improvement in any of these traits in Raeini Cashmere does would favorably influence all of the other traits. However, does that first kidded at younger ages have smaller litters at birth and lower litter birth weights at their first parity.

Aims: To assess outcomes of women in the Pregnancy and Neonatal Diabetes Outcomes in Remote Australia (PANDORA) cohort with gestational diabetes mellitus (GDM) managed by lifestyle modification compared with women without hyperglycaemia in pregnancy., Methods: Indigenous (n = 97) and Europid (n = 113) women managed by lifestyle modification were compared to women without hyperglycaemia (n = 235). Multivariate linear and logistic regressions assessed whether GDM-lifestyle women had poorer outcomes compared to women without hyperglycaemia., Results: Women with GDM-lifestyle had higher body mass index and lower gestational weight gain than women without hyperglycaemia. On univariate analysis, gestational age at delivery was lower and induction rates were higher in women with GDM-lifestyle than without hyperglycaemia. On multivariable regression, GDM-lifestyle was associated with lower gestational age at delivery (by 0.73 weeks), lower birthweight z-score (by 0.26, p = 0.007), lower likelihood of large for gestational age (LGA) [OR (95% CI): 0.55 (0.28, 1.02), p = 0.059], and greater likelihood of labour induction [2.34 (1.49, 3.66), p < 0.001] than women without hyperglycaemia., Conclusion: Women with GDM managed by lifestyle modification had higher induction rates and their offspring had lower birthweight z-scores, with a trend to lower LGA than those without hyperglycaemia in pregnancy. Further studies are indicated to explore reasons for higher induction rates., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Thai native cattle (Bos indicus) have high fertility rates and strong mothering abilities; however, their slight size, slow growth rate and low meat quality have not proved suitable for a commercial fattening system. Their progeny from crossbreeding with exotic sire particularly the Bos Taurus could present greater production performance. Lowline Angus sires and frozen semen were used to produce Lowline Angus x Thai native crossbreds. All cattle were raised in the same condition which was mainly through a grazing system. Throughout 5 years of data collection, calves' gender, birth weight, and weight gains were recorded until 1 year of age. There was no interaction effect between calves' gender, breed, and birth season on weight at birth and yearling, as well as growth rate. The birth weight of male calves (14.0 kg) were greater than female calves (13.3 kg). The calves' birth weights did not differ between levels of Lowline Angus blood, but all crossbred males were found to be significantly bigger than indigenous females. It must be noted that yearling weight did not differ between breeds. However, females 75% Lowline Angus, 25% Thai native crossbred (139.3 kg) weighed significantly higher than Thai native purebred females (115.9 kg). The calves' birth weights had positive correlation with Lowline Angus blood levels: birth weights increased when Lowline Angus blood levels were increased. The sharpness in the growth curve of Lowline Angus crossbreds was higher than purebred Thai indigenous cattle. Moreover, the 25% Lowline Angus crossbred had the highest graph slope as opposed to the 50% or 75% Lowline Angus crossbred. The growth performance of Lowline Angus x Thai native crossbred was shown unsuccessful under low-quality grazing situation. Additive effect of the crossbred presented quite low but well adapted to tropical environment. Greater productivity performance of the crossbred possibly will be excess with a higher quality feedlot condition.

A substantial body of literature has shown robust associations between prenatal smoking exposure and DNA methylation levels. The pattern of DNA methylation can be used as a molecular signature of past prenatal smoking exposure and might also provide mechanistic insights into associations between prenatal smoking exposure and adverse health outcomes. In this issue of the Journal, Cardenas et al. (Am J Epidemiol. 2019;188(11):1878-1886) evaluated whether DNA methylation mediates the association between prenatal smoking and low birth weight in a tissue that is mechanistically relevant to birth weight-the placenta-using formal mediation analyses. They found that methylation levels, at 5 loci, mediated smoking exposure effects on birth weight but only among children whose mothers smoked during pregnancy. Given the use of formal mediation methods and measurement in a mechanistically relevant tissue, this work has the potential to inform novel directions for intervention. Replication of these findings in larger and more racially and ethnically diverse samples, repeated measures to better tease apart the timing of DNA methylation changes with respect to exposure and birth weight, and continued use of intervention-focused mediation methods are needed before the impact of these findings will be fully realized., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: The aetiology of thyroid cancer is poorly understood, but it is possible that this malignancy has origins early in life. It is, however, currently unknown if birthweight, as an indicator of prenatal growth, is related to thyroid cancer risk., Objective: To investigate if birthweight is associated with the later risk of thyroid cancer and its histological types., Methods: 246,141 children (120,505 girls, 125,636 boys) from the Copenhagen School Health Records Register, born 1936-1989, were prospectively followed in the Danish Cancer Registry. Cox regressions were used to estimate hazards ratios (HR) and 95% confidence intervals (CI)., Results: During follow up, 241 individuals (172 women, 69 men) were diagnosed with thyroid cancer (162 papillary, 53 follicular). Birthweight was significantly and positively associated with risk of thyroid cancer overall (HR = 1.30 [95% CI: 1.03-1.64] per kilogram). There were no sex differences in the associations. Birthweight was positively and significantly associated with follicular thyroid cancer (HR = 1.74 [95% CI: 1.07-2.82] per kilogram), and although there was an indication of a positive association, it did not reach statistical significance for the more common papillary type (HR = 1.20 [95% CI: 0.90-1.59] per kilogram)., Conclusion: A heavier weight at birth is associated with an elevated risk of total and follicular thyroid cancer, which underscores that prenatal exposures may be important in thyroid cancer aetiology., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Background: Gene set analysis is a popular approach to examine the association between a predefined gene set and a phenotype. Few methods have been developed for a continuous phenotype. However, often not all the genes within a significant gene set contribute to its significance. There is no gene set reduction method developed for continuous phenotype. We developed a computationally efficient analytical tool, called linear combination test for gene set reduction (LCT-GSR) to identify core subsets of gene sets associated with a continuous phenotype. Identifying the core subset enhances our understanding of the biological mechanism and reduces costs of disease risk assessment, diagnosis and treatment., Results: We evaluated the performance of our analytical tool by applying it to two real microarray studies. In the first application, we analyzed pathway expression measurements in newborns' blood to discover core genes contributing to the variation in birth weight. On average, we were able to reduce the number of genes in the 33 significant gene sets of embryonic stem cell signatures by 84.3% resulting in 229 unique genes. Using immunologic signatures, on average we reduced the number of genes in the 210 significant gene sets by 89% leading to 1603 unique genes. There were 180 unique core genes overlapping across the two databases. In the second application, we analyzed pathway expression measurements in a cohort of lethal prostate cancer patients from Swedish Watchful Waiting cohort to identify main genes associated with tumor volume. On average, we were able to reduce the number of genes in the 17 gene sets by 90% resulting in 47 unique genes., Conclusions: We conclude that LCT-GSR is a statistically sound analytical tool that can be used to extract core genes associated with a continuous phenotype. It can be applied to a wide range of studies in which dichotomizing the continuous phenotype is neither easy nor meaningful. Reduction to the most predictive genes is crucial in advancing our understanding of issues such as disease prevention, faster and more efficient diagnosis, intervention strategies and personalized medicine., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Background: Lower birth weight is associated with diabetes although the underlying mechanisms are unclear. Muscle mass could be a modifiable link and hence a target of intervention. We assessed the associations of birth weight with muscle and fat mass observationally in a population with little socio-economic patterning of birth weight and using Mendelian randomization (MR) for validation., Methods: In the population-representative "Children of 1997" birth cohort (n = 8,327), we used multivariable linear regression to assess the adjusted associations of birth weight (kg) with muscle mass (kg) and body fat (%) at ~17.5 years. Genetically predicted birth weight (effect size) was applied to summary genetic associations with fat-free mass and fat mass (kg) from the UK Biobank (n = ~331,000) to obtain unconfounded estimates using inverse-variance weighting., Results: Observationally, birth weight was positively associated with muscle mass (3.29 kg per kg birth weight, 95% confidence interval (CI) 2.83 to 3.75) and body fat (1.09% per kg birth weight, 95% CI 0.54 to 1.65). Stronger associations with muscle mass were observed in boys than in girls (p for interaction 0.004). Using MR, birth weight was positively associated with fat-free mass (0.77 kg per birth weight z-score, 95% CI 0.22 to 1.33) and fat mass (0.58, 95% CI 0.01 to 1.15). No difference by sex was evident., Conclusion: Higher birth weight increasing muscle mass may be relevant to lower birth weight increasing the risk of diabetes and suggests post-natal muscle mass as a potential target of intervention., Competing Interests: The authors have declared that no competing interests exist.

Importance: Observational studies have shown associations of birth weight with type 2 diabetes (T2D) and glycemic traits, but it remains unclear whether these associations represent causal associations., Objective: To test the association of birth weight with T2D and glycemic traits using a mendelian randomization analysis., Design, Setting, and Participants: This mendelian randomization study used a genetic risk score for birth weight that was constructed with 7 genome-wide significant single-nucleotide polymorphisms. The associations of this score with birth weight and T2D were tested in a mendelian randomization analysis using study-level data. The association of birth weight with T2D was tested using both study-level data (7 single-nucleotide polymorphisms were used as an instrumental variable) and summary-level data from the consortia (43 single-nucleotide polymorphisms were used as an instrumental variable). Data from 180 056 participants from 49 studies were included., Main Outcomes and Measures: Type 2 diabetes and glycemic traits., Results: This mendelian randomization analysis included 49 studies with 41 155 patients with T2D and 80 008 control participants from study-level data and 34 840 patients with T2D and 114 981 control participants from summary-level data. Study-level data showed that a 1-SD decrease in birth weight due to the genetic risk score was associated with higher risk of T2D among all participants (odds ratio [OR], 2.10; 95% CI, 1.69-2.61; P = 4.03 × 10-5), among European participants (OR, 1.96; 95% CI, 1.42-2.71; P = .04), and among East Asian participants (OR, 1.39; 95% CI, 1.18-1.62; P = .04). Similar results were observed from summary-level analyses. In addition, each 1-SD lower birth weight was associated with 0.189 SD higher fasting glucose concentration (β = 0.189; SE = 0.060; P = .002), but not with fasting insulin, 2-hour glucose, or hemoglobin A1c concentration., Conclusions and Relevance: In this study, a genetic predisposition to lower birth weight was associated with increased risk of T2D and higher fasting glucose concentration, suggesting genetic effects on retarded fetal growth and increased diabetes risk that either are independent of each other or operate through alterations of integrated biological mechanisms.