@article{Ni2019d,
title = {The genetic relationship between female reproductive traits and six psychiatric disorders},
author = {G Ni and et al },
url = {https://www.ncbi.nlm.nih.gov/pubmed/31427629},
year = {2019},
date = {2019-08-19},
journal = {Scientific Reports},
abstract = {Female reproductive behaviours have important implications for evolutionary fitness and health of offspring. Here we used the second release of UK Biobank data (N = 220,685) to evaluate the association between five female reproductive traits and polygenic risk scores (PRS) projected from genome-wide association study summary statistics of six psychiatric disorders (N = 429,178). We found that the PRS of attention-deficit/hyperactivity disorder (ADHD) were strongly associated with age at first birth (AFB) (genetic correlation of -0.68 ± 0.03), age at first sexual intercourse (AFS) (-0.56 ± 0.03), number of live births (NLB) (0.36 ± 0.04) and age at menopause (-0.27 ± 0.04). There were also robustly significant associations between the PRS of eating disorder (ED) and AFB (0.35 ± 0.06), ED and AFS (0.19 ± 0.06), major depressive disorder (MDD) and AFB (-0.27 ± 0.07), MDD and AFS (-0.27 ± 0.03) and schizophrenia and AFS (-0.10 ± 0.03). These associations were mostly explained by pleiotropic effects and there was little evidence of causal relationships. Our findings can potentially help improve reproductive health in women, hence better child outcomes. Our findings also lend partial support to the evolutionary hypothesis that causal mutations underlying psychiatric disorders have positive effects on reproductive success.},
keywords = {14575, genetics, psychiatric disorders, reproductive traits},
pubstate = {published},
tppubtype = {article}
}

@article{Ni2019c,
title = {Genotype-covariate correlation and interaction disentangled by a whole-genome multivariate reaction norm model},
author = {Guiyan Ni and Julius van der Werf and Xuan Zhou and Elina Hyppönen and Naomi R. Wray and S. Hong Lee },
url = {https://www.nature.com/articles/s41467-019-10128-w},
year = {2019},
date = {2019-05-20},
journal = {Nature Communications},
abstract = {The genomics era has brought useful tools to dissect the genetic architecture of complex traits. Here we propose a multivariate reaction norm model (MRNM) to tackle genotype–covariate (G–C) correlation and interaction problems. We apply MRNM to the UK Biobank data in analysis of body mass index using smoking quantity as a covariate, finding a highly significant G–C correlation, but only weak evidence for G–C interaction. In contrast, G–C interaction estimates are inflated in existing methods. It is also notable that there is significant heterogeneity in the estimated residual variances (i.e., variances not attributable to factors in the model) across different covariate levels, i.e., residual–covariate (R–C) interaction. We also show that the residual variances estimated by standard additive models can be inflated in the presence of G–C and/or R–C interactions. We conclude that it is essential to correctly account for both interaction and correlation in complex trait analyses.},
keywords = {14575, genetics},
pubstate = {published},
tppubtype = {article}
}

@article{Ni2018d,
title = {Age at first birth in women is genetically associated with increased risk of schizophrenia},
author = {G Ni and J Gratten and N Wray and SH Lee},
url = {https://www.ncbi.nlm.nih.gov/pubmed/29977057},
year = {2018},
date = {2018-07-05},
journal = {Scientific Reports},
abstract = {Previous studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is -0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.},
keywords = {14575, featured, genetics, schizophrenia},
pubstate = {published},
tppubtype = {article}
}