Many maternal traits are associated with a neonate’s gestational duration, birth weight, and birth length. These birth outcomes are subsequently associated with late-onset health conditions. The causal mechanisms and the relative contributions of maternal and fetal genetic effects behind these observed associations are unresolved.p = 2.2 × 10−4). Both maternal and paternal transmitted height haplotype scores were highly significantly associated with birth weight and length (p < 1 × 10−17). The maternal transmitted BMI scores were associated with birth weight with a significant maternal effect (p = 1.6 × 10−4). Both maternal and paternal transmitted BP scores were negatively associated with birth weight with a significant fetal effect (p = 9.4 × 10−3), whereas BP alleles were significantly associated with gestational duration and preterm birth through maternal effects . The nontransmitted haplotype score for FPG was strongly associated with birth weight (p = 4.7 × 10−6); however, the glucose-increasing alleles in the fetus were associated with reduced birth weight through a fetal effect (p = 2.2 × 10−3). The haplotype scores for T2D were associated with birth weight in a similar way but with a weaker maternal effect (p = 6.4 × 10−3) and a stronger fetal effect (p = 1.3 × 10−5). The paternal transmitted birth weight score was significantly associated with reduced gestational duration (p = 1.8 × 10−4) and increased maternal systolic BP during pregnancy (p = 2.2 × 10−2). The major limitations of the study include missing and heterogenous phenotype data in some data sets and different instrumental strength of genetic scores for different phenotypic traits.Based on 10,734 mother–infant duos of European ancestry from the UK, Northern Europe, Australia, and North America, we constructed haplotype genetic scores using single-nucleotide polymorphisms (SNPs) known to be associated with adult height, body mass index (BMI), blood pressure (BP), fasting plasma glucose (FPG), and type 2 diabetes (T2D). Using these scores as genetic instruments, we estimated the maternal and fetal genetic effects underlying the observed associations between maternal phenotypes and pregnancy outcomes. We also used infant-specific birth weight genetic scores as instrument and examined the effects of fetal growth on pregnancy outcomes, maternal BP, and glucose levels during pregnancy. The maternal nontransmitted haplotype score for height was significantly associated with gestational duration (We found that both maternal height and fetal growth are important factors in shaping the duration of gestation: genetically elevated maternal height is associated with longer gestational duration, whereas alleles that increase fetal growth are associated with shorter gestational duration. Fetal growth is influenced by both maternal and fetal effects and can reciprocally influence maternal phenotypes: taller maternal stature, higher maternal BMI, and higher maternal blood glucose are associated with larger birth size through maternal effects; in the fetus, the height- and metabolic-risk–increasing alleles are associated with increased and decreased birth size, respectively; alleles raising birth weight in the fetus are associated with shorter gestational duration and higher maternal BP. These maternal and fetal genetic effects may explain the observed associations between the studied maternal phenotypes and birth outcomes, as well as the life-course associations between these birth outcomes and adult phenotypes. In a Mendelian randomization and haplotype genetic score analysis, Jing Chen and colleagues investigate contributions of maternal and fetal genetic effects to pregnancy outcomes, maternal phenotypes, and offspring adult health outcomes among mother-infant pairs. Maternal height, BMI, blood glucose, and blood pressure are associated with gestational duration, birth weight, and birth length. These birth outcomes are subsequently associated with late-onset health conditions.The causal mechanisms and the relative contributions of maternal and fetal genetic effects underlying these observed associations are not clear.We dissected the relative contributions of maternal and fetal genetic effects using haplotype genetic score analysis in 10,734 mother–infant pairs of European ancestry.Genetically elevated maternal height is associated with longer gestational duration and larger birth size. In the fetus, alleles associated with adult height are positively associated with birth size.Alleles elevating blood pressure are associated with shorter gestational duration through a maternal effect and are associated with reduced fetal growth through a fetal genetic effect. Alleles that increase blood glucose in the mother are associated with increased birth weight, whereas risk alleles for type 2 diabetes in the fetus are associated with reduced birth weight.Alleles raising birth weight in fetus are associated with shorter gestational duration and higher maternal blood pressure during pregnancy.Maternal size and fetal growth are important factors in shaping the duration of gestation.Fetal growth is influenced by both maternal and fetal effects. Higher maternal BMI and glucose levels positively associate with birth weight through maternal effects. In the fetus, alleles associated with higher metabolic risks are negatively associated with birth weight.More rapid fetal growth is associated with shorter gestational duration and higher maternal blood pressure.These maternal and fetal genetic effects can largely explain the observed associations between maternal phenotypes and birth outcomes, as well as the life-course associations between these birth outcomes and adult phenotypes. Epidemiological studies have demonstrated that maternal physical and physiological traits associate with birth outcomes. For example, maternal height is positively associated with gestational duration , 2, birtMendelian randomization (MR)  studies We previously developed an MR method that utilizes nontransmitted maternal alleles as a valid genetic instrument for maternal phenotypic effects on fetal/offspring outcomes . We showTo further our understanding of how various maternal phenotypes are correlated with pregnancy outcomes through maternal or fetal genetic effects and how fetal growth influences gestational duration and maternal physiological changes during pregnancy, we expanded our haplotype-based method by considering the mother–fetus duo (pregnancy) as the analytical unit  and explA prospective protocol for analysis was not prepared for this study; however, the assembly of the data sets and all the analyses were planned in advance of data analysis. We reported this study according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline  for crosWe used phenotype and genome-wide single-nucleotide polymorphism (SNP) data of 10,734 mother–infant pairs from 6 birth studies . These iWe focused on investigating the relationships between maternal height, prepregnancy BMI, BP, blood glucose levels, and pregnancy outcomes including gestational duration (as both quantitative and dichotomous preterm/term trait), birth weight, and birth length. Maternal height, prepregnancy BMI, and the 3 pregnancy outcomes were available in most of the studies  . MaternaBecause gestational duration is a key determinant of birth weight and birth size, we only included pregnancies with spontaneous deliveries and excluded mother–child pairs without gestational duration information. Pregnancies with known gestational or fetal complications and pre-existing medical conditions were excluded. Detailed inclusion/exclusion criteria are provided in Supplementary Methods . PretermThis study involves reanalysis of existing data sets, and the proposed analytical aims are consistent with the original consent agreements under which the genomic and phenotypic data were obtained. Therefore, additional ethics approval was not required.Genome-wide SNP data were generated using either Affymetrix 6.0  or various Illumina genotyping arrays . Standardized genotype quality control procedures were applied to all data sets. Participants of non-European ancestry were identified and excluded using principal components analysis (PCA) . Genome-We constructed weighted genetic scores to instrument various maternal phenotypes using GWA SNPs and their estimated effect sizes reported by the most recent large GWA studies . SpecifiSmat , Sfet , and 3 haplotype genetic scores: Sh1, Sh2, and Sh3, respectively, based on the maternal transmitted (h1), maternal nontransmitted (h2), and paternal transmitted alleles (h3)  . It follX)  and each pregnancy outcome (Y)  using regression analyses. Maternal age, fetal sex, maternal height, and prepregnancy BMI were included as covariates. Because gestational duration influences birth weight and length in a nonlinear fashion, the first 3 orthogonal polynomials of gestational duration were included as covariates in the analysis of birth weight and length. These analytical models are described in more detail in the Supplementary Methods  by the corresponding genetic scores.The instrumental strength of the genetic scores was checked by the variance in a maternal phenotype explained (X) were replaced by their corresponding 3 haplotype genetic scores (Sh1 + Sh2 + Sh3). The associations between these haplotype scores can differentiate between maternal and fetal genetic effects  with a pregnancy outcome suggests a maternal (intrauterine phenotypic) effect, whereas an association of Sh3  with the pregnancy outcomes suggests fetal genetic effects. The 3 haplotype genetic scores of the same mother–child pairs  were simultaneously tested in a single-regression model , and hence, they had exactly the same sample size. Therefore, the effect size estimates of these haplotype scores and their associated p-values can be directly compared to assess the directions and relative contributions of the maternal and fetal effects.Associations between the haplotype genetic scores and the pregnancy outcomes were tested using regression models like those used in the association analysis described above, except that the maternal phenotypes  of the maternal transmitted haplotype (h1) should be equal to the summation of the maternal effect (βh2) of the nontransmitted haplotype (h2) and fetal genetic effect (βh3) of the paternal transmitted haplotype (h3). Thus, (βh1−βh3) and (βh1−βh2), respectively, represent the maternal effect and the fetal genetic effect of the maternal transmitted haplotype (h1). Therefore, the average maternal effect (βMY) of the 2 maternal haplotypes on a birth outcome (Y) can be expressed as (βh1−βh3+ βh2)/2, and the average fetal genetic effect (βFY) of the maternal and paternal transmitted haplotypes can be expressed as (βh1−βh2+ βh3)/2. Because these linear combinations also capture the maternal or fetal genetic effects of the maternal transmitted haplotype (h1), they are more powerful than the methods only using the maternal nontransmitted haplotype (h2) or the paternal transmitted haplotype (h3) as instruments, respectively, for maternal effect and fetal genetic effect.Whereas c scores  30]. Un. UnSh2 aY) caused by a certain amount of difference in a maternal phenotype (X) associated with one-unit genetic score. The maternal causal effect (Sh2) as the genetic instrument for maternal causal effect In light of these reviews, we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to invite you to submit a revised version that fully addresses the reviewers' and editors' comments. You will recognize that we cannot make a decision about publication until we have seen the revised manuscript and your response, and we expect to seek re-review by one or more of the reviewers. http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. 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Comments from the reviewers:*** Reviewer #1: The authors present a very interesting study on quantifying the causal effects of maternal and fetal traits on birth outcomes using genetic scores constructed haplotype genetic scores which combines the maternal and fetal effects as a single unit. Using a large number of mother/infant duos singleton of European ancestry - they were able to identify the causal effects of maternal height, pre-pregnancy BMI, blood pressure and blood glucose on pregnancy outcomes , birth weight and birth length. What the authors have shown is mechanistic insight into the observed association between maternal phenotypes and birth outcomes which has implications for life-course association birth outcomes and future adult outcomes. The results in itself are not particularly surprising that there are observed causal influences of maternal phenotypes on birth outcomes as this has been shown in many previous studies, including the authors own previous work but what is the novelty on this paper is actually the methodology itself. The authors developed a method which explicitly models maternal and fetal genetic effects using as a single analytic unit using instrumental variables of haplotype genetic scores. This means that a key advantage of this method is that they could explore whether any effects on fetal outcomes are associated gestational duration and whether fetal growth has an effect on gestational duration as well as maternal phenotypes in pregnancy. This is a complex analysis but presented in a way that is intuitive and generally easy to follow. The statistical methods underpinning all the analysis are a series of linear regression models, which have additive in nature, and then overall results are pooled across cohorts using meta-analysesThere are few comments I have which the authors could find useful:Abstract - Suggest conforming to PLOS Medicine style of three sections - background/methods&findings/conclusion. The methods are substantial so it would be useful to in the abstract to summarise the methodology and study designThe study is rationale is strong and extends previous work by others and the authors themselves in determining causal associations between maternal phenotypes and pregnancy outcomes and adult cardio metabolic diseases. There is a good body of evidence already that the effects of maternal characteristics on fetal outcomes. The authors extend this body of evidence by combing maternal/fetal as a single unit to model genetic scores using a haplotype genetic score as an instrumental variable. Figure 2 is useful, the models assumes paternal non-transmitted alleles h4 (which isn't described in the legend) has no bearing on the maternal or fetal affects. This seems like a logical assumption but is there any evidence to suggest that paternal non-transmitted phenotypes may influence maternal phenotypes? Methods - ALSPAC blood pressure measurements: authors used BP measurements between 30-36 weeks - was this an average or a single point estimate?Methods - PCA analysis to exclude non-European ancestry - how many were excluded in the end from non-European ancestry and how did this map up to what was self-reported as ethnicity? Methods - genotype data - From previous GWA (Table S4 provided) - it would appear that heritability of certain most of the traits investigated varies from high levels (height - H2 0.8) to low (birthweight H2 0.3). This makes logical sense as features such as birth weight are have strong environmental influences (i.e. smoking in pregnancy). Can the authors discuss how the variation in the GRS instruments may have on the overall results and how better instruments would explain higher levels of variation in the phenotypic traits. Methods - association tests between haplotype genetic scores and pregnancy outcomes. How were potential interactions between handled or identified between gene-gene or gene-environment?Methods - multivariate MR analysis - when combing the results from all datasets, given the heterogeneity in the datasets  as well as significant heterogeneity identified in several of the meta-analyses by Cochran's Q , it would have made sense to use a random-effects model. At least this should be considered in meta-analyses where there is a large amount of heterogeneity. This does have implications on the overall findings, but it would test the robustness of the pooling process. Results - association between genetic score and maternal phenotypes. The genetic scores explain > 20% of the maternal height variance but the remaining genotypes explain less than 5% variance of the maternal phenotypes - suggesting strong environmental influences which is not surprising. This also suggests that perhaps in the haplotype model exploring casual effects using the genetic instruments to consider incorporating more environmental covariates (presumably some of the birth cohorts would have collected these data - for instance ALSPAC). Though genetic risk scores may not associated with many of the environmental demographic factors, they might have some association with potential other maternal phenotypes indicative of maternal cardio-metabolic health which may have not been consideredResults - one of the limiting factors which have not been considered is maternal nutrient intake during pregnancy, and certain behavioural factors  which may have some link to genetic link towards to these behaviours. Could the authors comment whether these behavioural or nutrition factors could have a large influence on their findings. *** Reviewer #2: The proposed manuscript entitled "Haplotype genetic score analysis in 10,734 mother/infant pairs reveals complex maternal and fetal genetic effects underlying the associations between maternal phenotypes, birth outcomes and adult phenotypes" by Chen et al. seeks to dissect the maternal and fetal genetic effects and their complex relationship between maternal traits and offspring outcomes including gestational duration, birth weight, and birth length. They utilized haplotype scores and Mendelian randomization to identify that tall maternal stature and high maternal blood glucose casually increase birth size, in the neonate, height and blood pressure increasing alleles can lead to increased and decreased birth weight, alleles associated with increased birth weight reduce the time of gestation and increase maternal blood pressure. This is an interesting article with some intriguing results but there are several issues that first need to be addressed.1) The Abstract needs to be expanded on and fully elucidated for the journal and should include Background, Methods, and Findings and Conclusions. Also given the complexity of some of the underlying statistical genetics in the article it should include an Author Summary as well to better present this to a clinical audience. 2) The second paragraph in the introduction describes a lot of the recent work on the underlying maternal/fetal genetic relationship with birthweight but provides less information on the relationship between birthweight and some of the other fetal outcomes proposed here. This paragraph should be shortened and go into more detail regarding the latter as this is the major gap in the literature this paper is seeking to address.3) Throughout the manuscript when you discuss blood pressure it is unclear how this is defined. Are you using systolic or diastolic blood pressure as both are included in the supplementary tables or are you using a combined phenotype? 4) The authors used the program MR-PRESSO to avoid horizontal pleiotropy as the correctly mention the high correlation between traits. However, they do not provide any measure of horizontal pleiotropy. As the authors of the program mention, it is only useful when horizontal pleiotropy is < 50%. This should be addressed in some way in the manuscript. This is not clearly shown in the supplementary tables either. 5) For the meta-analysis was any specific computer program used and are the Q scores provided in any of the supplementary tables?6) The inclusion of the fasting blood glucose in ALSPAC 18 years later seems spurious, as most blood chemistry would be expected to change over time and not sure how this would impact any fetal measurements. Horse has already left the barn in this case. 7) In the results, the fact that there is a smaller sample size (2 cohorts) it would appear unsurprising that the blood pressure is half, also given that there is a potential age discrepancy between the two and blood pressure is notoriously heterogeneous.8) How is pre-term birth being assessed throughout, there is no clear definition provided but the term is used throughout the results. 9) I would be very cautious regarding the fasting glucose results as this only comes from one cohort, so I am not sure there is strong evidence for the results here.10) In the meta-analysis was any sensitivity testing done, such as drop one cohort out and see if they have more influence on the overall results. *** Reviewer #3: This paper by Chen, Bacelis, et al. explores the contributions of maternal and fetal genetics, and maternal phenotypes, to pregnancy outcomes - a topic that has some significant general interest. Since I am not a statistical geneticist my critique is brief and based more on common sense than on technical considerations. Nonetheless, it might be useful since PLoS Medicine's target audience is broad. This is an extremely complex piece of work, involving phenotypic  and genotypic (SNP) data of 10,734 mother/infant pairs from six independently conducted birth studies. Each of these birth studies had different designs and different ways of obtaining both the genotypic and phenotypic data - which necessitated several significant compromises in their joint analysis. To cite just one example, maternal fasting plasma glucose (FPG) levels during pregnancy were available only in the HAPO study, while FPG was measured in over 4000 ALSPAC mothers not during pregnancy but in a follow-up data collection 18 years after the pregnancy.I believe the paper needs to be rewritten, and I have two suggestions:1. The concepts of maternal and fetal "genotype genetic scores" and "haplotype genetic scores" will be new for a general readership and are important for understanding the study. These concepts should be illustrated diagrammatically in a main figure. The current diagrams with arrows indicating potential maternal-fetal interactions are useful and should be kept - but should simplified to deal with only the strongest and most reproducible findings (see #2 below).2. More crucially, what are the strongest and most reproducible findings in this study? Because of the way the authors chose to analyze and describe all 6 birth studies in parallel, it is difficult or impossible to extract a clear notion of replication of any of the specific findings across these independently conducted and differently designed birth studies. The authors should consider analyzing one of the birth studies , and then vetting their strongest findings using the other 5 studies as replication sets. This approach would be easier to grasp and would have obvious advantages, both for distilling the most convincing results and for simplifying the tables, which are currently very difficult to read. The "study pooling" approach would not have to be totally discarded - it could be presented as supplemental data.***Any attachments provided with reviews can be seen via the following link:[LINK] 9 Apr 2020Attachmentresponse.docxSubmitted filename: Click here for additional data file. 22 May 2020Dear Dr. Zhang,Thank you very much for submitting your revised manuscript "Dissecting maternal and fetal genetic effects underlying the associations between maternal phenotypes, birth outcomes and adult phenotypes – a haplotype-based genetic score analysis in mother/child pairs" (PMEDICINE-D-19-03326R1) for consideration at PLOS Medicine. Your paper was re-evaluated by a senior editor and discussed among all the editors here. It was also discussed with an academic editor with relevant expertise, and sent to three independent reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:[LINK]In light of these reviews, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' remaining comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we may seek re-review by one or more of the reviewers. http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. Please submit a clean version of the paper as the main article file; a version with changes marked should be uploaded as a marked up manuscript.In revising the manuscript for further consideration, your revisions should address the specific points made by each reviewer and the editors. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/figures. While revising your submission, please upload your figure files to the PACE digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at PLOSMedicine@plos.org.In addition, we request that you upload any figures associated with your paper as individual TIF or EPS files with 300dpi resolution at resubmission; please read our figure guidelines for more information on our requirements: plosmedicine@plos.org) if you have any questions or concerns.We expect to receive your revised manuscript by May 29 2020 11:59PM. Please email us  and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***http://journals.plos.org/plosmedicine/s/competing-interests.We ask every co-author listed on the manuscript to fill in a contributing author statement, making sure to declare all competing interests. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. If new competing interests are declared later in the revision process, this may also hold up the submission. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT. You can see our competing interests policy here: Please use the following link to submit the revised manuscript: https://www.editorialmanager.com/pmedicine/Your article can be found in the "Submissions Needing Revision" folder. http://journals.plos.org/plosmedicine/s/submission-guidelines#loc-methods.To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it. Please ensure that the paper adheres to the PLOS Data Availability Policy  in the subtitle . We suggest incorporating that the study included Mendelian randomization as well. We suggest: “Dissecting maternal and fetal genetic contributions to the associations between maternal phenotypes, birth outcomes and adult phenotypes: a Mendelian randomization and haplotype-based genetic score analysis in 10,734 mother-infant pairs of European ancestry” or similar.In the title (and throughout), we suggest using a hyphen for “mother-infant” or “mother-child” pairs.4. Abstract: Background: We suggest revising the last sentence to “The causal mechanisms and the relative contributions of maternal and fetal genetic effects behind these observed associations are unresolved.”5. Abstract: Methods and Findings: We suggest revising to: Please clarify “these observed associations” as it is not clear what this is referencing.6. Abstract, and throughout: Please revise to avoid causal language, for example in the following sentence. “The maternal non-transmitted haplotype score for height was significantly associated with gestational duration (P=0.00022) and preterm birth (P=0.00097) confirming the causal effect of maternal height on gestational duration.” Similarly, please soften ‘maternal and fetal genetic effects’ to ‘maternal and fetal genetic contributions’ or similar, to avoid causal implications.7. Abstract, Methods and Findings: If scientific notation is used for p values, please use consistently throughout.8. Abstract, Methods and Findings: we suggest revising “...however, the glucose-increasing alleles in the fetus reduced birth weight…” to “glucose-increasing alleles in the fetus were associated with reduced birth weight…” or similar, to avoid inferring causality.9. Abstract, Conclusions (and throughout the manuscript): Please revise this paragraph to remove language that implies causality, such as “both maternal height and fetal growth affect the duration of gestation” . Refer to associations instead.10. Author Summary: Please place the author summary between the abstract and the introduction sections.11. Author Summary: What did the researchers do and find?: Please reduce causal language here.12. Author Summary: What do these findings mean?: Please reduce causal language, particularly in the second bullet point. For the first bullet point, we suggest revising to: “In this study, we observed that maternal size and fetal growth are important factors in shaping the duration of gestation.” or similar. 13. Methods: Construction of genetic scores paragraph on page 6: Please refer to “association” rather than “effect” to avoid causal implications: “To examine the effect of fetal growth (as proxied by birth weight) on pregnancy outcomes and maternal blood pressure and FPG…”14. Results: Please provide p values associated with all analyses. For example, on page 15, please provide p values associated with the OR for the association between birth weight and susceptibility to T2D .15. Discussion: At the beginning of the discussion, please summarize your findings in paragraph form rather than as a numbered list.16. Discussion: Please temper the causal language. Under the first paragraph, in point 1, we suggest revising the final sentence to: “These new results support our previous finding [15] with additional evidence.”17. Discussion: Final paragraph: We suggest revising this sentence to: “These maternal and fetal genetic effects may explain the observed associations between the studied maternal phenotypes and birth outcomes as well as the life-course associations between these birth outcomes and adult phenotypes.”18. Tables: Please define abbreviations for “OR” and “se” in the legends.19. Figure 3, 4, 5, 6: Please define abbreviations for FPG, BMI, BP, T2D in the figure legend.20. Supporting Information Tables: Please define all abbreviations, such as for SBP, DBP, FPG, BMI, se, sd in the legends, where appropriateComments from the reviewers:Reviewer #1: The authors have done a thorough job revising their manuscript. Appreciate the thought given to the responses and providing additional analyses. Given the number of the figures and tables already included and supplemental analyses, I would try to refrain any more further analyses as there already 5-6 key findings from the analyses. As with these types of studies, there could be even more analyses and permutations but it would be advisable at this stage to keep this to a minimum. I think any further analyses could be highlighted more as future research in the discussion. The only point I would add is that, perhaps in the discussion is that although the analysis was done as a cross-sectional study, the nature of the data used involves several birth cohorts which longitudinal data which opens up some future opportunities to explore later growth outcomes, including the relationship between glucose raising alleles on lower birth weight and how this relates to rapid growth in infancy (as we do observe LBW children tend to exhibit a period of rapid catch up growth as well in their first 1-2 years of life). This interplay between genetics, fetal growth, low birth rate, and subsequent growth in the first years of life would have potential to be answered using these same datasets the authors have collated. Food for thought in future exploration in more longitudinal designs. Reviewer #2: I thank the authors for their careful consideration of the previous comments regarding the proposed manuscript. I feel that they addressed the majority of my concerns in the updated manuscript. I do have a few minor suggestions.I feel that the Methods/Results section is very results heavy. There is a single sentence form methods and the rest is dedicated to results. However, I feel given the complexity of the methodology a few more details would be welcome here. I think you can focus on the main findings rather than all of the results. Also, there is not Author Summary included as indicated in their response. I think this would be useful for a clinical audience. Reviewer #4: All my comments have been adequately addressed.Any attachments provided with reviews can be seen via the following link:[LINK] 27 May 2020Attachmentresponse.rev2.docxSubmitted filename: Click here for additional data file. 9 Jul 2020Dear Dr. Zhang,Thank you very much for re-submitting your manuscript "Dissecting maternal and fetal genetic effects underlying the associations between maternal phenotypes, birth outcomes and adult phenotypes: a Mendelian randomization and haplotype-based genetic score analysis in 10,734 mother-infant pairs" (PMEDICINE-D-19-03326R2) for review by PLOS Medicine.I apologize with the delay in returning a decision on your manuscript. I have discussed the paper with my colleagues and the academic editor and it was also seen again by one of the reviewers. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:[LINK]plosmedicine@plos.org) will be in touch shortly about the production requirements for your paper, and the link and deadline for resubmission. DO NOT RESUBMIT BEFORE YOU'VE RECEIVED THE PRODUCTION REQUIREMENTS.Our publications team  and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. 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If you have any questions in the meantime, please contact me ; while blood pressure alleles were significantly associated with gestational duration and preterm birth through maternal effects .”3.Abstract: Conclusions: Please change “fetus” to “the fetus” in “...alleles raising birth weight in fetus are associated…”4.Abstract: Conclusions: Please change “...can largely explain” to “...may explain…”5.Author summary: “What did the authors do and find?”: Please revise the second bullet point to: --Genetically-elevated maternal height is associated with the longer gestational duration and larger birth size. In the fetus, alleles associated with adult height are positively associated with birth size.6.Author Summary: “What do these findings mean?” Please change “In fetus” to “In the fetus” in the second bullet point.7.Methods: Please reference the specific supporting information file/s where these are described: “A detailed description of these data sets can be found in the Supplementary Methods.”8.Methods: Under “Construction of Genetic Scores”: Please revise “For FPG, we used 22 SNPs associated with FPG levels identified in non-diabetic individuals” to “FPG levels identified in individuals without diabetes”9.Results: second paragraph: Please also present the results with CIs/ p values for maternal BMI associations with gestational duration or preterm birth risk even if they did not reach statistical significance.10.Results: third paragraph: Please present the results  for the associations observed in HAPO, between maternal blood pressure and gestational duration and birth weight.11.Results: bottom of page 14: It seems part of the results are presented with p values given in scientific notation, and some are not. Please be consistent with the formatting.12.Discussion: First sentence: “...to explicitly model the maternal and fetal genetic effects.” Can you please clarify this sentence- effects of/on what?13.Discussion: Second paragraph, first sentence: To mitigate the causal language, please revise to: “Our results support that maternal height influences the duration of gestation and fetal growth, and alleles associated with adult height also influence birth size through fetal genetic effects.” Similarly, please revise the last sentence of that paragraph: By utilizing the birth weight genetic score built on paternal transmitted allele, our findings also support causal effects of fetal growth on gestational duration and maternal blood pressure.”14.Discussion: Third paragraph, third sentence: Please revise to: “...demonstrated not only by the evidence supporting a causal effect of maternal height (size of the mother) on gestational duration, but also…”15.Discussion: Please revise this sentence in the concluding paragraph to better reflect your findings: “Our findings related to gestational age-adjusted birth weight suggest that rapid fetal growth might reduce gestational duration and increase maternal blood pressure.” or similar.16.Grants support: Please remove this section from the manuscript body, and ensure that all relevant information is included in the sections Competing Interests, Financial Disclosures, and Data Availability.17.Figure 1 legend: In point 4, “Fetal” should be “fetal”18.Figure 3 legend: Please describe the asterisk shown with fetal birth weight.19.Supplementary information file: For the “Genotype Data” you refer to lists of SNPs published as supporting information in other publications- if you are able to, please include supporting information tables with these data in the event that files from other publications are inaccessible.20.Supplementary Table S1 and S2: Please incorporate these into the main paper. 21.Supplementary Figure S1: Please define “QC” in the legend22.Supplementary Figure S2: If possible, please elaborate on what is demonstrated by this figure.23.Supplementary Figure S5, S6, and S7: Please increase the font size on the histogram axes, it is difficult to read them. Please explain in the legend why FPG has an asterisk in Figure S6.24.Supplementary Figure S8-S12: Please increase font sizes slightly.25.Supplementary Figure S16 and S17: Please increase the font sizes slightly.26.Supporting information file: Please replace "subject" with participant, patient, individual, or person.27.Supporting information file: Under “Blood glucose and TD susceptibility”: Please replace “96,496 non-diabetic individuals” with “96,496 individuals without diabetes”Comments from Reviewers:Reviewer #1: I have re-reviewed the response by the authors and manuscript detail and agree that the authors have detailed their rationale now for including exact p-values. This is appropriate for the context of their analysis and interpretation of the findings.Any attachments provided with reviews can be seen via the following link:[LINK] 21 Jul 2020Dear Dr. Zhang, On behalf of my colleagues and the academic editor, Dr. Fasil Tekola-Ayele, I am delighted to inform you that your manuscript entitled "Dissecting maternal and fetal genetic effects underlying the associations between maternal phenotypes, birth outcomes and adult phenotypes: a Mendelian randomization and haplotype-based genetic score analysis in 10,734 mother-infant pairs" (PMEDICINE-D-19-03326R3) has been accepted for publication in PLOS Medicine. PRODUCTION PROCESSBefore publication you will see the copyedited word document (in around 1-2 weeks from now) and a PDF galley proof shortly after that. The copyeditor will be in touch shortly before sending you the copyedited Word document. We will make some revisions at the copyediting stage to conform to our general style, and for clarification. When you receive this version you should check and revise it very carefully, including figures, tables, references, and supporting information, because corrections at the next stage (proofs) will be strictly limited to (1) errors in author names or affiliations, (2) errors of scientific fact that would cause misunderstandings to readers, and (3) printer's (introduced) errors.If you are likely to be away when either this document or the proof is sent, please ensure we have contact information of a second person, as we will need you to respond quickly at each point.PRESSA selection of our articles each week are press released by the journal. You will be contacted nearer the time if we are press releasing your article in order to approve the content and check the contact information for journalists is correct. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. PROFILE INFORMATIONhttps://www.editorialmanager.com/pmedicine, log in, and click on the "Update My Information" link at the top of the page. Please update your user information to ensure an efficient production and billing process.Now that your manuscript has been accepted, please log into EM and update your profile. Go to Thank you again for submitting the manuscript to PLOS Medicine. We look forward to publishing it. Best wishes, Caitlin Moyer, Ph.D.Associate Editor PLOS Medicineplosmedicine.org


Low birth weight (LBW) is defined as the birth weight of live born infants below 2500 g, regardless of gestational age. It is a public health problem caused by factors that are potentially modifiable. The purpose of this study was to determine the socioeconomic, obstetric, and maternal factors associated with LBW in Lumbini Provincial Hospital, Nepal.  The study was conducted using case control study design with 1 : 2 case control ratio. A total of 105 cases and 210 controls were taken in this study. Data were entered on Epi data software version 3.1 and exported to Statistical Package for Social Science (SPSS) software version 25 for analysis. Characteristics of the sample were described using mean and standard deviation. Bivariate analysis was done to assess the association between dependent and independent variables. The ultimate measure of association was odds ratio. Variables found to be associated with bivariate analysis were entered into a multivariable logistic regression model to identify predictors of LBW.  The mean age of the participants was 25.98 years with ±4.40 standard deviation. Mothers with literate educational background , housewife , vaginal mode of delivery , gestational age <37 weeks , history of LBW , and maternal weight <50 kilograms  were significantly associated with LBW.  Educational and occupational status, mode of delivery, gestational age, maternal weight, and history of LBW were found to be independent predictors of LBW. There is need of developing coordination with education sector for increasing educational status of mothers and adolescent girls. Social determinants of health need to be considered while developing interventional programs. Similarly, interventional programs need to be developed considering identified predictors of low birth weight. The World Health Organization (WHO) defines low birth weight (LBW) as the birth weight of live born infants below 2500 g, regardless of gestational age . Global Risk factors for low birth weight are mainly associated with socioeconomic and maternal factors. Socioeconomic factors associated with low birth weight include place of residence, occupation, educational status, and wealth index . SimilarPrevious studies conducted in Nepal have shown that the prevalence of low birth weight ranges from 9.4% to 21.6% –15. FurtInstitutional-based case control study was conducted at Lumbini Provincial Hospital, located at Butwal, Lumbini zone, Nepal, from June to July 2019. The hospital was established in 1967 and named as Lumbini zonal hospital and later upgraded to Lumbini Provincial Hospital in 2019. Currently, the catchment population of the hospital is four million and serves to thirteen districts of the western part of Nepal.st June and 31st July 2019. Similarly, control was defined as a mother who delivered a baby weighing at least 2500 g and not exceeding 4000 g in the same health facility and time frame. Newborn baby fulfilling the definition of case and control and mothers giving informed consent was included in the study. Similarly, in this study, stillbirths and newborn baby with congenital abnormalities was set as exclusion criteria.Postpartum mothers who recently delivered live newborn babies were taken as study population. A case was defined as a mother who delivered a baby weighing less than 2500 g in Lumbini Provincial Hospital between 1The sample size was calculated using Open Epi Version 3.01 statistical software for unmatched case control study. Basic parameters assumed for calculating sample size was 95% confidence level, power of study 80%, ratio of control to case 2 : 1, minimum detectable odds ratio of two, and proportion of control exposed 35% . The calData were collected using a structured questionnaire which was prepared after reviewing similar studies conducted in Nepal and other similar country settings. The questionnaire consisted of sociodemographic, socioeconomic, and obstetric information. Obstetric information was collected by reviewing the obstetric records of the participants. One-day training was provided to two hospital staff having bachelor's degree in nursing educational background for data collection procedure. All the filled questionnaires were reviewed and checked for errors by the principal investigator on regular basis.Data were entered on Epi data software version 3.1 and exported to Statistical Package for Social Science (SPSS) software version 25 for analysis. Characteristics of the sample were described using mean and standard deviation. Bivariate analysis was carried out to assess the association between dependent and independent variables. The ultimate effect measure (measure of association) was odds ratio, and 95% confidence intervals were used to determine statistical significance. Variables found to be associated with bivariate analysis were entered into the multivariate logistic regression model to identify predictors of LBW.Ethical approval was obtained from the Universal College of Medical Science and Teaching Hospital Institutional Review Committee (UCMS/IRC/067/19). Permission was also obtained from the Medical Superintendent and Obstetric Department of Lumbini Provincial Hospital to access the participants and their records. The study was explained to participants, and written informed consent with sign or thumb print was obtained for data collection.st June and 31st July 2019. A total of 315 mothers (105 cases and 210 controls) participated in the study. The mean age of mothers was found to be 25.98 years with ±4.40 standard deviation. Among study participants, 227 (72.1%) mothers were of the age group of 20–30 years, 169 (53.7%) were of upper caste, 281 (89.2%) were literate, 188 (59.7%) were living in nuclear family, and 250 (79.4%) were housewives.Proportion of mothers with a history of abortion and low birth weight was 28 (8.9%) and 24 (7.6%), respectively. Preterm delivery was prevalent in 48 (15.2%) mothers. Proportion of mothers with ANC visit of 4 or more was 251 (79.7%). Mean weight and hemoglobin level of mothers were found to be 54.53 kg and 10.20 g/dl with a standard deviation of ±6.69 and ± 1.19, respectively. Proportion of mothers with weight more than or equal to 50 kg was 240 (76.2%) and hemoglobin level more than 11 g/dl was 72 (22.9%). Majority of women were not having adequate amount of rest and sleep during day and night time. Proportion of women with rest time of more than 2 hours in day time and ≥8 hours in night time was 39 (12.4%) and 62 (19.7%), respectively.This study aimed at determining the sociodemographic, maternal, and obstetric predictors of low birth weight. Literate mothers were 68% less likely to have low weight babies compared to their illiterate counterpart. This finding is consistent with other studies where literate mothers were found to have a protective effect against LBW –21. MothThe odds of delivering LBW baby among mothers with a previous history of LBW were five times higher than that of mothers with no previous history of LBW. This finding is similar to the study conducted in Ethiopia . SimilarRegular ANC during pregnancy is beneficial for both the pregnant mother and developing baby as obstetric complications can be identified during ANC and managed timely . StudiesDespite extensive endeavors made in the study, it could not avert three basic limitations. First, the study findings cannot be generalized to mothers attending private hospitals or clinics, mothers delivering baby at home, and mothers living in areas other than the study area. Second, being a case control study, the study participants may have been subjected to recall bias. The third limitation of this study was we could not assess the relationship between weight gain during pregnancy and risk of LBW as data related to maternal weight during regular intervals of pregnancy was not available in our study. However, we took maternal weight during first trimester as a proxy for prepregnancy maternal weight which could have been a better measure for assessing LBW .Educational and occupational status, mode of delivery, gestational age, maternal weight, and history of LBW were found to be independent predictors of LBW. There is need of developing coordination with education sector for increasing educational status of mothers and adolescent girls. Social determinants of health need to be considered while developing interventional programs. Similarly, interventional programs need to be developed considering identified predictors of low birth weight.


SAM68 is an mRNA-binding protein involved in mRNA processing in the nucleus that forms membraneless compartments called SAM68 Nuclear Bodies (SNBs). We found that intersectin 1 (ITSN1), a multidomain scaffold protein harboring five soluble SH3 domains, interacts with SAM68 proline-rich motifs (PRMs) surrounded by self-adhesive low complexity domains. While SAM68 is poorly soluble in vitro, the interaction of ITSN1 SH3 domains and mRNA with SAM68 enhances its solubility. In HeLa cells, the interaction between the first ITSN1 SH3 domain (SH3A) and P0, the N-terminal PRM of SAM68, induces the dissociation of SNBs. In addition, we reveal the ability of another SH3 domain (SH3D) of ITSN1 to bind to mRNAs. ITSN1 and mRNA may thus act in concert to promote SAM68 solubilization, consistent with the absence of mRNA in SNBs in cells. Together, these results support the notion of a specific chaperoning of PRM-rich SAM68 within nuclear ribonucleoprotein complexes by ITSN1 that may regulate the processing of a fraction of nuclear mRNAs, notably SAM68-controlled splicing events related to higher neuronal functions or cancer progression. This observation may also serve as a putative model of the interaction between other PRM-rich RBPs and signaling proteins harboring SH3 domains.The online version of this article (10.1007/s00018-020-03610-y) contains supplementary material, which is available to authorized users. Membraneless compartments participate in the organization of cellular constituents –4 and inHowever, while many nuclear RBPs have the capacity to self-aggregate and generate condensates, they have to remain soluble to sustain their function and what preserves the solubility of these proteins in the nucleus has been under focus recently , 21, 22.To explore the putative role of ITSN1 in controlling the spatial distribution of RBPs, we first determined whether the interactions between ITSN1 and RBPs harboring PRMs were relevant in a cellular context. The results indicate that, among the selected RBPs, SRC associated in mitosis of 68-kDa protein (SAM68) interacts significantly with ITSN1. SAM68 is a member of the STAR family, composed of proteins that are conserved through yeast, mammals and plants. SAM68 controls various aspects of RNA metabolism, including pre-mRNA splicing. Besides its central and conserved RNA-binding domain, SAM68 possesses flanking proline-rich motifs and RG-rich domains that are prone to self-attraction making SAM68 an insoluble protein in vitro –39. In cSH3) containing five SH3 domains  were amplified using primers containing the PacI and AscI restriction sites and inserted into the backbone entry plasmid RFP-MBD-pCR8/GW/TOPO previously digested with the corresponding restriction enzymes. The inserted cDNAs were verified by sequencing. Next, sequences encoding ITSN1SH3-RFP-MBD and SAM68-RFP-MBD were subcloned from pCR8/GW/TOPO plasmids into the Gateway® pEF-Dest51 plasmid (Invitrogen™) using the LR recombination reactions (Invitrogen™) according to the manufacturer’s protocol. The preparation of plasmid pEF-Dest51-TDP43-RFP-MBD was described previously  sample. Spectra were analyzed using CCPNmr Analysis 2.4.1 software [15N-labeled SH3D domain free and in complex with CA6 or T12 ssDNA (Eurofins) at a 1:1.2 molar ratio. The number of dummy scans and scans was, respectively, set to 16 and 32. Shaped pulse length and power were calculated by considering an amide 1H bandwidth of 4.5 ppm and a chemical shift offset of 8.5 ppm. Data were recorded with 2048 points along the direct dimension, 128 t1 increments and a relaxation delay of 0.2 s corresponding to an experimental time of 23 min for each spectrum. For all experiments, 2,2- Dimethyl-2-silapentane-5-sulfonic acid was used as an external reference in pure D2O for chemical shift referencing.NMR experiments were conducted at 298 K on a Bruker AVIII HD 600 MHz spectrometer equipped with a triple-resonance cryoprobe and were processed with Topspin 3.5 package. software . To probsoftware  were acqt test.The analysis of the statistical significance and correlation analysis were performed in GraphPad Prism 6 software using unpaired two-tailed SH3) used as bait, and different RBPs, used as preys . The observed interaction of SAM68 with ITSN1Duolink® in situ fluorescence protocol and we confirmed the spatial proximity between ITSN1 and SAM68 in HeLa cells . To decipher whether ITSN1 interacts directly or indirectly with SAM68, in vitro pull-down assays analysis experiments were performed with recombinant proteins, SAM68-His, GST-ITSN1SH3, GST-SRCSH3 (SH3 domain of SRC kinase fused to GST) and TDP-43-His that were produced and purified in E. coli. GST-SRCSH3 was used as a positive control, since SAM68 is a well-known partner of SRC tyrosine kinase family [SH3 under the conditions of increased ITSN1SH3 amounts .To further probe the relevance of the interaction of ITSN1 and SAM68 with alternative approaches to the microtubule bench, we analyzed the spatial distribution of endogenous ITSN1 and SAM68 via proximity ligation assays (PLA) performed according to the e family , 54, whiSAM68 has both structured and unstructured domains and displays a strong tendency for homodimerization and multimerization –39. ConsSH3 .ΔEH1-GFP or ITSN1sΔEH1-ΔSH3A-GFP, respectively). The analysis was performed at the single cell level to quantify the positive or negative correlation between ITSN1 expression level and SAM68 enrichment in NBs. Adding-back ITSN1 containing all its SH3 domains (ITSN1sΔEH1-GFP) decreased the enrichment of SAM68 in NBs but not when SH3A (ITSN1sΔEH1-ΔSH3A-GFP) has been truncated  andFinally, given that mRNA and ITSN1 act in synergy to increase SAM68 solubility in vitro Fig. c, we wonKeeping soluble RBPs that harbor self-adhesive property is a major challenge  for cells to sustain RNA biogenesis and mRNA processing in the nucleus and to prevent a dramatic formation of RBP condensates. We propose here, a mechanism based on the specific chaperoning of RBPs by structured domains present in nuclear proteins. Several nuclear proteins harbor multiple SH3 domains (listed in Supplementary Table 1). These domains can be considered as chaperone candidates owing to their characteristic beta-barrel structure, elevated solubility and affinity for PRMs, especially the RxxPxxP and PxxPxR sequences that are present in many RBPs (listed in Supplementary Table 2). The cellular and in vitro results obtained in this study point towards a specific interaction between ITSN1, a protein with five SH3 domains and SAM68 in cells  has been confirmed and linked also with altered splicing functions [Interestingly, mRNA recognition by the SH3D of ITSN1 together with SAM68, may help to recruit specific mRNAs to regulate their splicing. This could notably be critical in multiple cancer types, where SAM68 is overexpressed and regulates expression and alternative splicing of several proto-oncogenes  but alsounctions . A genomSupplementary material 1 (PDF 11189 kb)Below is the link to the electronic supplementary material.


Thymic hyperplasia is a common finding among newborns, but cyst formation might produce mediastinal symptoms. Lethal outcome is reported when accompanied by massive intrathoracic hemorrhage. The clinical picture in our case was characterized from profuse multiple hemorrhagic foci and respiratory distress syndrome, with an unclear role of the thymic cyst. Thymic hyperplasia is a common finding among newborns, but cyst formation might produce mediastinal symptoms. Lethal outcome is reported when accompanied by massive intrathoracic hemorrhage. The clinical picture in our case was characterized from profuse multiple hemorrhagic foci and respiratory distress syndrome, with an unclear role of the thymic cyst. The pregnancy was at its term and the mother had two other healthy children before the third delivery. The child weighted 3300 grams, with cephalic presentation; he breathed spontaneously but some minutes later deep cyanosis and lack of pulse prompted resuscitation efforts. The APGAR score of three was registered a quarter hour after the birth and some moments later he was pronounced dead.A thorough autopsy was performed; profuse hemorrhagic foci were found in almost all of his viscera. A retrosternal plum‐like bilocular cystic formation was seen and photographed Figure . The cysThere are reports of respiratory distress syndrome among infants related to thymic hyperplasia.None declared.ES and GV: involved in manuscript writing, data collection, and literature reviewing.