Schizophrenia risk and reproductive success: a Mendelian randomization study

Schizophrenia is a debilitating and heritable mental disorder associated with lower reproductive success. However, the prevalence of schizophrenia is stable over populations and time, resulting in an evolutionary puzzle: how is schizophrenia maintained in the population, given its apparent fitness costs? One possibility is that increased genetic liability for schizophrenia, in the absence of the disorder itself, may confer some reproductive advantage. We assessed the correlation and causal effect of genetic liability for schizophrenia with number of children, age at first birth and number of sexual partners using data from the Psychiatric Genomics Consortium and UK Biobank. Linkage disequilibrium score regression showed little evidence of genetic correlation between genetic liability for schizophrenia and number of children (rg = 0.002, p = 0.84), age at first birth (rg = −0.007, p = 0.45) or number of sexual partners (rg = 0.007, p = 0.42). Mendelian randomization indicated no robust evidence of a causal effect of genetic liability for schizophrenia on number of children (mean difference: 0.003 increase in number of children per doubling in the natural log odds ratio of schizophrenia risk, 95% confidence interval (CI): −0.003 to 0.009, p = 0.39) or age at first birth (−0.004 years lower age at first birth, 95% CI: −0.043 to 0.034, p = 0.82). We find some evidence of a positive effect of genetic liability for schizophrenia on number of sexual partners (0.165 increase in the number of sexual partners, 95% CI: 0.117–0.212, p = 5.30×10−10). These results suggest that increased genetic liability for schizophrenia does not confer a fitness advantage but does increase mating success.


Recommendation?
Major revision is needed (please make suggestions in comments) Comments to the Author(s) Schizophrenia risk and reproductive success: A Mendelian randomization study. Lawn et al.
This study investigated if increased genetic liability for schizophrenia was associated with reproductive advantage. The authors used GWAS summary statistics from the Psychiatric Genomics Consortium (PGC) for the schizophrenia, which were used in a genetic association analysis (by linkage disequilibrium score regression (LDSC)) and also used in a Mendelian randomization analysis as exposure data. The authors also used Uk Biobank data for which reproductive traits (age at first birth and number of children) as well as individual genotyped data were available. The study tested the genetic association and causal effect of schizophrenia genetic risk with number of children and age at first birth and reported that there was no significance. This is interesting study trying to tackle the old puzzle (how is schizophrenia maintained in the population given its apparent fitness costs?). The authors tested one of plausible reasons that increased genetic risk for schizophrenia is associated with reproductive advantage. However, there is no clear evidence from the analysis results.
I have a number of questions and comments.
1. The authors reported that the genetic correlations from LDSC analysis were not different from zero. Given that the true relationship between schizophrenia (genetic risk) and the reproductive traits, it may not be very good idea to use LDSC which is a linear additive model. For example, the authors should estimate genetic correlation between schizophrenia genetic risk and age at first birth less than its mean value.
A recent study (referenced as #24 in this paper) reported that a significant negative correlation between schizophrenia genetic risk and age at first birth < its mean. They also reported a significant heterogeneity between younger and older age at first birth.
5. If there are unmeasured confounders, how they will affect the results for the Mendelian randomization analysis? How did the authors control such unmeasured confounders or variables possibly having effects on the exposure and/or outcome data? Did the authors test reverse causal effects, i.e. causal effects of reproductive traits on the schizophrenia genetic liability? 6. I see there was relatedness quality control for UK Biobank (page 5). But how did the authors make sure there was no duplicated or close relatives between PGC and UK Biobank? 7. In Methods, it is not clear how many SNPs were used for the LDSC analyses. How many individuals were used for UK Biobank (for # children and age at first birth analyses)?

Review form: Reviewer 2
Is the manuscript scientifically sound in its present form? Yes

Do you have any ethical concerns with this paper? No
Have you any concerns about statistical analyses in this paper? No

Recommendation?
Accept with minor revision (please list in comments)

Comments to the Author(s)
Lawn et al reported in their paper entitled "Schizophrenia risk and reproductive success: A Mendelian randomization study" results of their study investigating whether the stable prevalence of schizophrenia (SCZ) over populations can be explained from some SCZ-induced reproductive advantages. They undertook this task with UK Biobank data for number of children and age at first birth in females and SCZ GWAS summary data using a set of advanced genetic analyses. In summary, no genetic associations were found between SCZ and number of children and age at first birth in females, using both LD score regression and two-sample Mendelian randomization analyses. These results were further observed from the non-significant association between SCZ genetic liability (risk score) and mean number of children and mean age at first birth. They, therefore, suggested two explanations for the stable prevalence of SCZ: SCZ-related genetic variants are too tiny to be under negative selection; and the mutation-selection balance. Overall, this is a very well-written and well-designed and executed study.
One suggestion is to add a caveat in the Discussion that the maintenance about genetic variation that we observe today (in a contemporary population) is the result of historical evolutionary forces. It is not necessarily the case that the human population is in some kind of equilibrium so that we can infer maintenance of schizophrenia-associated alleles from fitness present-day fitness associations. For example, reproduction has undergone dramatic changes in the last ~50 years because of the availability of contraceptives.
The (minor) specific comments below are provided to improve the manuscript. It would be better to re-do the analyses using the latest EA GWAS. However, since the results are unlikely to change substantially the authors should decide whether it is worth the effort.
2. Page 4 ('Exposure data' section): The author should explain more on why also use EA as the exposure data in analyses. For sensitivity comparison? If so, why choose EA, not other psychiatric disorders related to reproduction, such as autism?
3. Page 5 (line 37-38): I wonder if the authors checked the distribution of "number of children" phenotype (i.e are there any 'outlier' individuals who had a large number of children?). I am also interested in seeing the similarity of "number of children they had given birth to" (femalespecific) and "number of children they had fathered" (male-specific) from the true spouses (there are about 1200 known spouse pairs in UK Biobank and about 20,000 inferred spouse pairs), to check the divorce rate which may be a confounder for MR analyses.

Page 5 ('Outcome measures' section):
One suggestion is to also take reproductive failure (e.g ever have pregnancy termination, miscarriage) into account in the analyses as a covariate, particularly for the "childless" phenotype. 5. Page 5 (line 41): It is possible to generate a sample for age at first birth in males from identification of potential spouses? 6. Page 5 (line 54-55); Page 6 (line 7-8); Page 7 (line 11): how about fitting all the models (i.e. GWAS, MR, the genetic score-liability regression) with both assessment centre and genotype batch as covariates? 7. Page 7 (line 15): I wonder if it is possible to run MR using "number of children" or "age at first birth" as exposure and EA as outcome, to examine the potential bi-directional association between EA and number of children and age at first birth, depending on whether there is enough independent genome-wide significant (p < 5e-08) or suggestive (p < 1e-05) SNPs associated with number of children and age at first birth. The MR-Egger results for SCZ-age at first birth seems different from other models. The intercept of MR-Egger regression was estimated differently from 0 at a significance level of 5%, indicating the existence of pleiotropic SNP effects. If this is the case, the author should acknowledge it as a potential limitation.
10. Page 8 (line 16): Figure 2 showed some evidence for a 'U' shape curve between SCZ and age at first birth. Since there is a study (Ni et al. 2018 Scientific Reports) published recently also utilised UKB sample and found a 'U' shape relationship between age at first birth in women and SCZ, maybe it is worth trying to divide the sample into more quantiles (i.e 7 or 9) to check the relationship? 11. Page 11 (line 47): there is a typo in reference #3.
12. Supplementary Figures 1-3 (and description in main text): Comment. This looks like what might be expected under stabilising selection, even if the quadratic term is not statistically significant. Perhaps this could be lack of power? In the future (next few years), the accuracy of schizophrenia liability prediction is going to be better so the issue can be revisited.

02-Nov-2018
Dear Miss Lawn, The editors assigned to your paper ("Schizophrenia risk and reproductive success: A Mendelian randomization study.") have now received comments from reviewers. While one reviewer is very positive about publication, the other reviewer raises a number of substantive points concerning your analysis which requires careful consideration.
We would like you to revise your paper in accordance with the referees' suggestions which can be found below (not including confidential reports to the Editor). Please note this decision does not guarantee eventual acceptance.
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Once again, thank you for submitting your manuscript to Royal Society Open Science and I look forward to receiving your revision. If you have any questions at all, please do not hesitate to get in touch. This study investigated if increased genetic liability for schizophrenia was associated with reproductive advantage. The authors used GWAS summary statistics from the Psychiatric Genomics Consortium (PGC) for the schizophrenia, which were used in a genetic association analysis (by linkage disequilibrium score regression (LDSC)) and also used in a Mendelian randomization analysis as exposure data. The authors also used Uk Biobank data for which reproductive traits (age at first birth and number of children) as well as individual genotyped data were available. The study tested the genetic association and causal effect of schizophrenia genetic risk with number of children and age at first birth and reported that there was no significance. This is interesting study trying to tackle the old puzzle (how is schizophrenia maintained in the population given its apparent fitness costs?). The authors tested one of plausible reasons that increased genetic risk for schizophrenia is associated with reproductive advantage. However, there is no clear evidence from the analysis results.
I have a number of questions and comments.
1. The authors reported that the genetic correlations from LDSC analysis were not different from zero. Given that the true relationship between schizophrenia (genetic risk) and the reproductive traits, it may not be very good idea to use LDSC which is a linear additive model. For example, the authors should estimate genetic correlation between schizophrenia genetic risk and age at first birth less than its mean value.
A recent study (referenced as #24 in this paper) reported that a significant negative correlation between schizophrenia genetic risk and age at first birth < its mean. They also reported a significant heterogeneity between younger and older age at first birth.
2. The trait, number of children, may be highly (negatively) correlated with age at first birth. Should the authors consider multivariate analysis (age at first birth and # children as multiple dependent variables)? Or, at least did they adjust the effects of age at first birth on # children?
3. How the authors controlled heterogeneity between male and females? I would suggest number of children analysis should be analysed for female only or male only.
4. Figures shows that there is not significant difference of mean # children (or age at first birth) across different schizophrenia genetic liability levels. However, this would be only one dimension of the relationship. The authors should check if there is significant difference of mean schizophrenia genetic liability across different # children or age at first birth.
5. If there are unmeasured confounders, how they will affect the results for the Mendelian randomization analysis? How did the authors control such unmeasured confounders or variables possibly having effects on the exposure and/or outcome data? Did the authors test reverse causal effects, i.e. causal effects of reproductive traits on the schizophrenia genetic liability? 6. I see there was relatedness quality control for UK Biobank (page 5). But how did the authors make sure there was no duplicated or close relatives between PGC and UK Biobank? 7. In Methods, it is not clear how many SNPs were used for the LDSC analyses. How many individuals were used for UK Biobank (for # children and age at first birth analyses)?

Reviewer: 2
Comments to the Author(s) Lawn et al reported in their paper entitled "Schizophrenia risk and reproductive success: A Mendelian randomization study" results of their study investigating whether the stable prevalence of schizophrenia (SCZ) over populations can be explained from some SCZ-induced reproductive advantages. They undertook this task with UK Biobank data for number of children and age at first birth in females and SCZ GWAS summary data using a set of advanced genetic analyses. In summary, no genetic associations were found between SCZ and number of children and age at first birth in females, using both LD score regression and two-sample Mendelian randomization analyses. These results were further observed from the non-significant association between SCZ genetic liability (risk score) and mean number of children and mean age at first birth. They, therefore, suggested two explanations for the stable prevalence of SCZ: SCZ-related genetic variants are too tiny to be under negative selection; and the mutation-selection balance. Overall, this is a very well-written and well-designed and executed study.
One suggestion is to add a caveat in the Discussion that the maintenance about genetic variation that we observe today (in a contemporary population) is the result of historical evolutionary forces. It is not necessarily the case that the human population is in some kind of equilibrium so that we can infer maintenance of schizophrenia-associated alleles from fitness present-day fitness associations. For example, reproduction has undergone dramatic changes in the last ~50 years because of the availability of contraceptives.
The (minor) specific comments below are provided to improve the manuscript. 2. Page 4 ('Exposure data' section): The author should explain more on why also use EA as the exposure data in analyses. For sensitivity comparison? If so, why choose EA, not other psychiatric disorders related to reproduction, such as autism?
3. Page 5 (line 37-38): I wonder if the authors checked the distribution of "number of children" phenotype (i.e are there any 'outlier' individuals who had a large number of children?). I am also interested in seeing the similarity of "number of children they had given birth to" (femalespecific) and "number of children they had fathered" (male-specific) from the true spouses (there are about 1200 known spouse pairs in UK Biobank and about 20,000 inferred spouse pairs), to check the divorce rate which may be a confounder for MR analyses.

Page 5 ('Outcome measures' section):
One suggestion is to also take reproductive failure (e.g ever have pregnancy termination, miscarriage) into account in the analyses as a covariate, particularly for the "childless" phenotype.

Page 5 (line 41):
It is possible to generate a sample for age at first birth in males from identification of potential spouses? 6. Page 5 (line 54-55); Page 6 (line 7-8); Page 7 (line 11): how about fitting all the models (i.e. GWAS, MR, the genetic score-liability regression) with both assessment centre and genotype batch as covariates? 7. Page 7 (line 15): I wonder if it is possible to run MR using "number of children" or "age at first birth" as exposure and EA as outcome, to examine the potential bi-directional association between EA and number of children and age at first birth, depending on whether there is enough independent genome-wide significant (p < 5e-08) or suggestive (p < 1e-05) SNPs associated with number of children and age at first birth. 9. Table 2 (line 14-15): The MR-Egger results for SCZ-age at first birth seems different from other models. The intercept of MR-Egger regression was estimated differently from 0 at a significance level of 5%, indicating the existence of pleiotropic SNP effects. If this is the case, the author should acknowledge it as a potential limitation.
10. Page 8 (line 16): Figure 2 showed some evidence for a 'U' shape curve between SCZ and age at first birth. Since there is a study (Ni et al. 2018 Scientific Reports) published recently also utilised UKB sample and found a 'U' shape relationship between age at first birth in women and SCZ, maybe it is worth trying to divide the sample into more quantiles (i.e 7 or 9) to check the relationship?
12. Supplementary Figures 1-3 (and description in main text): Comment. This looks like what might be expected under stabilising selection, even if the quadratic term is not statistically significant. Perhaps this could be lack of power? In the future (next few years), the accuracy of schizophrenia liability prediction is going to be better so the issue can be revisited.
Author's Response to Decision Letter for (RSOS-181049.R0) See Appendix A.

Recommendation?
Accept with minor revision (please list in comments)

Comments to the Author(s)
The manuscript has been substantially improved and the authors have addressed most of my concerns.
In References, please check journal name format, e.g. PNAS or Proc Natl Acad Sci? Please also check update some preprints that have been already published in official journals.

Are the interpretations and conclusions justified by the results? Yes
Is the language acceptable? Yes

Recommendation?
Accept as is

Comments to the Author(s)
The authors have done a good job in their revision. The addition of the number of sexual partners adds interest. Please note that the genetic correlation in liability to schizophrenia between males and females is very high and to my knowledge not significantly different from 1.

17-Dec-2018
Dear Miss Lawn: On behalf of the Editors, I am pleased to inform you that your Manuscript RSOS-181049.R1 entitled "Schizophrenia risk and reproductive success: A Mendelian randomization study." has been accepted for publication in Royal Society Open Science subject to minor revision in accordance with the referee suggestions. Please find the referees' comments at the end of this email.
The reviewers and Subject Editor have recommended publication, but also suggest some minor revisions to your manuscript. Therefore, I invite you to respond to the comments and revise your manuscript.
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• Data accessibility It is a condition of publication that all supporting data are made available either as supplementary information or preferably in a suitable permanent repository. The data accessibility section should state where the article's supporting data can be accessed. This section should also include details, where possible of where to access other relevant research materials such as statistical tools, protocols, software etc can be accessed. If the data has been deposited in an external repository this section should list the database, accession number and link to the DOI for all data from the article that has been made publicly available. Data sets that have been deposited in an external repository and have a DOI should also be appropriately cited in the manuscript and included in the reference list.
If you wish to submit your supporting data or code to Dryad (http://datadryad.org/), or modify your current submission to dryad, please use the following link: http://datadryad.org/submit?journalID=RSOS&manu=RSOS-181049.R1 • Competing interests Please declare any financial or non-financial competing interests, or state that you have no competing interests.
• Authors' contributions All submissions, other than those with a single author, must include an Authors' Contributions section which individually lists the specific contribution of each author. The list of Authors should meet all of the following criteria; 1) substantial contributions to conception and design, or acquisition of data, or analysis and interpretation of data; 2) drafting the article or revising it critically for important intellectual content; and 3) final approval of the version to be published.
All contributors who do not meet all of these criteria should be included in the acknowledgements.
We suggest the following format: AB carried out the molecular lab work, participated in data analysis, carried out sequence alignments, participated in the design of the study and drafted the manuscript; CD carried out the statistical analyses; EF collected field data; GH conceived of the study, designed the study, coordinated the study and helped draft the manuscript. All authors gave final approval for publication.
• Acknowledgements Please acknowledge anyone who contributed to the study but did not meet the authorship criteria.
• Funding statement Please list the source of funding for each author.
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Once again, thank you for submitting your manuscript to Royal Society Open Science and I look forward to receiving your revision. If you have any questions at all, please do not hesitate to get in touch. Comments to the Author(s) The authors have done a good job in their revision. The addition of the number of sexual partners adds interest. Please note that the genetic correlation in liability to schizophrenia between males and females is very high and to my knowledge not significantly different from 1.

Reviewer: 1
Comments to the Author(s) The manuscript has been substantially improved and the authors have addressed most of my concerns.
In References, please check journal name format, e.g. PNAS or Proc Natl Acad Sci? Please also check update some preprints that have been already published in official journals.

07-Jan-2019
Dear Miss Lawn, I am pleased to inform you that your manuscript entitled "Schizophrenia risk and reproductive success: A Mendelian randomization study." is now accepted for publication in Royal Society Open Science. You can expect to receive a proof of your article in the near future. Please contact the editorial office (openscience_proofs@royalsociety.org and openscience@royalsociety.org) to let us know if you are likely to be away from e-mail contact. Due to rapid publication and an extremely tight schedule, if comments are not received, your paper may experience a delay in publication.
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