Evaluating marginal genetic correlation of associated loci for complex diseases and traits between European and East Asian populations

Lu, Haojie; Wang, Ting; Zhang, Jinhui; Zhang, Shuo; Huang, Shuiping; Zeng, Ping

doi:10.1007/s00439-021-02299-8

Cited by 12 publications

(29 citation statements)

References 91 publications

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“…Third, reproducibility is a well-known important principle in evaluating the findings of association studies [ 160 ]; however, at this time, we are unaware of other similar large-scale European-only summary statistics that could be employed for replication of our association discoveries. Again, because of unavailability of relevant data, we primarily focused on our pleiotropy analysis in the European population; therefore, due to the trans-ethnic diversity of genetic architecture in many complex traits including psychiatric disorders [ 161 ], it is unclear whether our findings can be transportable to other ancestral groups such as East Asians.…”

Section: Discussionmentioning

confidence: 99%

A comprehensive gene-centric pleiotropic association analysis for 14 psychiatric disorders with GWAS summary statistics

Qiao

Shao

et al. 2021

BMC Med

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Background Recent genome-wide association studies (GWASs) have revealed the polygenic nature of psychiatric disorders and discovered a few of single-nucleotide polymorphisms (SNPs) associated with multiple psychiatric disorders. However, the extent and pattern of pleiotropy among distinct psychiatric disorders remain not completely clear. Methods We analyzed 14 psychiatric disorders using summary statistics available from the largest GWASs by far. We first applied the cross-trait linkage disequilibrium score regression (LDSC) to estimate genetic correlation between disorders. Then, we performed a gene-based pleiotropy analysis by first aggregating a set of SNP-level associations into a single gene-level association signal using MAGMA. From a methodological perspective, we viewed the identification of pleiotropic associations across the entire genome as a high-dimensional problem of composite null hypothesis testing and utilized a novel method called PLACO for pleiotropy mapping. We ultimately implemented functional analysis for identified pleiotropic genes and used Mendelian randomization for detecting causal association between these disorders. Results We confirmed extensive genetic correlation among psychiatric disorders, based on which these disorders can be grouped into three diverse categories. We detected a large number of pleiotropic genes including 5884 associations and 2424 unique genes and found that differentially expressed pleiotropic genes were significantly enriched in pancreas, liver, heart, and brain, and that the biological process of these genes was remarkably enriched in regulating neurodevelopment, neurogenesis, and neuron differentiation, offering substantial evidence supporting the validity of identified pleiotropic loci. We further demonstrated that among all the identified pleiotropic genes there were 342 unique ones linked with 6353 drugs with drug-gene interaction which can be classified into distinct types including inhibitor, agonist, blocker, antagonist, and modulator. We also revealed causal associations among psychiatric disorders, indicating that genetic overlap and causality commonly drove the observed co-existence of these disorders. Conclusions Our study is among the first large-scale effort to characterize gene-level pleiotropy among a greatly expanded set of psychiatric disorders and provides important insight into shared genetic etiology underlying these disorders. The findings would inform psychiatric nosology, identify potential neurobiological mechanisms predisposing to specific clinical presentations, and pave the way to effective drug targets for clinical treatment.

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Section: Discussionmentioning

confidence: 99%

A comprehensive gene-centric pleiotropic association analysis for 14 psychiatric disorders with GWAS summary statistics

Qiao

Shao

et al. 2021

BMC Med

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“…Results after taking genetic factors into account Furthermore, after taking genetic factors into account by including a GRS of growth trait, we discovered that smoking during pregnancy was still signi cantly associated with offspring's height and body size at ten years old especially in the European cohort, with the estimated effects nearly unchanged compared to those generated without considering GRS (Tables S5-S7). Note that, the GRS itself was positively correlated with height or body size in the European population (Table S8); the negative relation between the GRS and height in the South Asian and African populations was possibly due to racial heterogeneity, which resulted in the poor performance of genetic transferability across diverse populations [37,38].…”

Section: Estimated Relation For Strati Cation Analysis In the Europea...mentioning

confidence: 99%

Long-term adverse influence of smoking during pregnancy on height and body size of offspring at ten years old in the UK Biobank cohort

Wu¹,

Hao²,

Zhu³

et al. 2022

Preprint

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Background To explore the long-term relation between smoking during pregnancy and early childhood growth in the UK Biobank cohort. Methods To estimate the effect of smoking during pregnancy on offspring height and body size at ten years old, we performed a cross-population comparison to examine whether such influence could be repeatedly observed among three different ethnic groups in the UK Biobank cohort (n = 22,140 for European, n = 7,094 for South Asian, and n = 5,000 for African). Especially, we applied the UK Biobank European sibling cohort (n = 9,953 for height and n = 7,239 for body size) to control for unmeasured familial confounders and incorporated a polygenic risk score to adjust for potential genetic effect. Results We discovered that children whose mothers smoked during pregnancy had greater risk of being shorter or fatter at age ten in the full UK Biobank European cohort, with 15.3% (95% confidence intervals (CIs): 13.0 ~ 17.7%) higher risk for height and 32.4% (95%CIs: 29.5 ~ 35.4%) larger risk for body size. Similar associations were identified in the South Asian and African populations. These associations were robust and remained significant in the European sibling cohort (12.6% [95%CIs: 5.0 ~ 20.3%] for height and 36.1% [95%CIs: 26.3 ~ 45.9%] for body size) after controlling for family factors or genetic influence. Conclusion Smoking during pregnancy can promote offspring's height defect and obesity in childhood.

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“…One of the important findings of trans-ethnic GWASs is that a few of association signals identified in one population are found to be replicated in others in the sense that trait-associated genes exhibit consistently statistical association and effect direction in multiple populations [12,14,[17][18][19][20][21], indicating that the same trait shares similar genetic components across diverse continental populations [22][23][24][25][26][27][28]. Indeed, current GWASs have sought to identify traitassociated genetic loci in the hope that discoveries in one population are likely transferred to others.…”

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confidence: 99%

“…Understanding of shared genetic foundation for traits across diverse populations has profound implications from both statistical and practical perspectives. First, it helps improve power for trans-ethnic analysis by integrating multiple studies from various ethnicities [11,[32][33][34][35], increase accuracy of trans-ethnic genetic risk prediction in racial and ethnic minorities [28,36], and enhance resolution in fine-mapping causal genes in various populations [37,38]. Second, it offers additional insight into biological mechanism underlying complex diseases and helps measure the extent of interaction between genetic and environmental influences on disease risk [14].…”

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confidence: 99%

“…To assess the common genetic component underlying traits across distinct populations, novel trans-ethnic genetic correlation has been proposed using only summary statistics data [26,28,42]. Conceptually, transethnic genetic correlation quantifies the extent to which a set of SNPs exert the same or similar effects on phenotypic variation in various ancestral groups.…”

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confidence: 99%

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Detecting associated genes for complex traits shared across East Asian and European populations under the framework of composite null hypothesis testing

Qiao

Shao

et al. 2022

J Transl Med

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Background Detecting trans-ethnic common associated genetic loci can offer important insights into shared genetic components underlying complex diseases/traits across diverse continental populations. However, effective statistical methods for such a goal are currently lacking. Methods By leveraging summary statistics available from global-scale genome-wide association studies, we herein proposed a novel genetic overlap detection method called CONTO (COmposite Null hypothesis test for Trans-ethnic genetic Overlap) from the perspective of high-dimensional composite null hypothesis testing. Unlike previous studies which generally analyzed individual genetic variants, CONTO is a gene-centric method which focuses on a set of genetic variants located within a gene simultaneously and assesses their joint significance with the trait of interest. By borrowing the similar principle of joint significance test (JST), CONTO takes the maximum P value of multiple associations as the significance measurement. Results Compared to JST which is often overly conservative, CONTO is improved in two aspects, including the construction of three-component mixture null distribution and the adjustment of trans-ethnic genetic correlation. Consequently, CONTO corrects the conservativeness of JST with well-calibrated P values and is much more powerful validated by extensive simulation studies. We applied CONTO to discover common associated genes for 31 complex diseases/traits between the East Asian and European populations, and identified many shared trait-associated genes that had otherwise been missed by JST. We further revealed that population-common genes were generally more evolutionarily conserved than population-specific or null ones. Conclusion Overall, CONTO represents a powerful method for detecting common associated genes across diverse ancestral groups; our results provide important implications on the transferability of GWAS discoveries in one population to others.

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Evaluating marginal genetic correlation of associated loci for complex diseases and traits between European and East Asian populations

Cited by 12 publications

References 91 publications

A comprehensive gene-centric pleiotropic association analysis for 14 psychiatric disorders with GWAS summary statistics

A comprehensive gene-centric pleiotropic association analysis for 14 psychiatric disorders with GWAS summary statistics

Long-term adverse influence of smoking during pregnancy on height and body size of offspring at ten years old in the UK Biobank cohort

Detecting associated genes for complex traits shared across East Asian and European populations under the framework of composite null hypothesis testing

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