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. Author manuscript; available in PMC: 2022 Feb 5.
Published in final edited form as: Brain Behav Immun. 2020 Jul 28;89:433–439. doi: 10.1016/j.bbi.2020.07.030

Genetic liability to major depression and risk of childhood asthma

A population-based cohort study on the association between polygenic risk score for major depression and childhood asthma

Xiaoqin Liu 1,2,*, Trine Munk-Olsen 1,2, Clara Albiñana 1,2, Bjarni Jóhann Vilhjálmsson 1,2,3, Emil Michael Pedersen 1,2, Vivi Schlünssen 4,5, Marie Bækvad-Hansen 2,6, Jonas Bybjerg-Grauholm 2,6, Merete Nordentoft 2,7,8, Anders D Børglum 2,9,10, Thomas Werge 2,11, David M Hougaard 2,6, Preben Bo Mortensen 1,2,3,10, Esben Agerbo 1,2,3
PMCID: PMC8817239  NIHMSID: NIHMS1618304  PMID: 32735934

Abstract

Objective:

Major depression and asthma frequently co-occur, suggesting shared genetic vulnerability between these two disorders. We aimed to determine whether a higher genetic liability for major depression was associated with increased childhood asthma risk, and if so, whether such an association differed by sex of the child.

Methods:

We conducted a population-based cohort study comprising 16,687 singletons born between 1991 and 2005 in Denmark. We calculated the polygenic risk score (PRS) for major depression as a measure of genetic liability based on the summary statistics from the Major Depressive Disorder Psychiatric Genomics Consortium collaboration. The outcome was incident asthma from age 5 to 15 years, identified from the Danish National Patient Registry and the Danish National Prescription Registry. Stratified Cox regression was used to analyze the data.

Results:

Greater genetic liability for major depression was associated with an increased asthma risk with a hazard ratio (HR) of 1.06 (95% CI: 1.01–1.10) per standard deviation increase in PRS. Children in the highest major depression PRS quartile had a HR for asthma of 1.20 (95% CI: 1.06–1.36), compared with children in the lowest quartile. However, major depression PRS explained only 0.03% of asthma variance (Pseudo-R2). The HRs of asthma by major depression PRS did not differ between boys and girls.

Conclusion:

Our results suggest a shared genetic contribution to major depression and childhood asthma, and there is no evidence of a sex-specific difference in the association.

Keywords: Asthma, cohort study, genetic liability, major depression, polygenic risk score, population-based

1. Introduction

The bidirectional relationship between asthma and major depression has been frequently noted in epidemiological studies (Ahmedani, et al., 2013, Choi, et al., 2019, Goodwin, et al., 2003). Subjects with asthma are more likely to develop major depression than those without asthma. Similarly, subjects with major depression have a higher risk of asthma than those without major depression (Choi, et al., 2019). However, the causes underlying the co-occurrence of major depression and asthma have not been elucidated. Both diseases are heritable: the heritability is approximately 40% for major depression and 82% for childhood asthma (Polderman, et al., 2015, Ullemar, et al., 2016). Therefore, genetic traits predisposing to both diseases could at least partly explain the co-occurrence.

Asthma is a heterogeneous disease (Pividori, et al., 2019), and different asthma phenotypes may have distinct and unique immunologic characteristics, mechanisms and causes (Ferreira, et al., 2019, Naeem and Silveyra, 2019). Although asthma can develop de novo throughout life, most cases develop in childhood, and asthma in adults is often the persistence or relapse of childhood asthma (Dharmage, et al., 2019). Childhood asthma is distinct from adult-onset asthma in terms of incidence, risk factors, progression, and genetic architectures (Ferreira, et al., 2019, Naeem and Silveyra, 2019). Furthermore, gender-specific differences have been reported in asthma for genetic expressions (Gautam, et al., 2019). Twin studies have been a valuable method for understanding the genetic correlation between two diseases by comparing monozygotic and dizygotic twins (Boomsma, et al., 2002). However, evidence for a genetic correlation between major depression and asthma from twin studies is conflicting (Brew, et al., 2018a, Wamboldt, et al., 2000). To our knowledge, only two studies directly investigated genetic liability for major depression and asthma risk. One study found that subjects with genetic liability for major depression were more likely to take asthma medication (Wu, et al., 2019). The other further demonstrated a genetic correlation of self-reported depression with prevalent asthma in adults (rg=0.17) (Lehto, et al., 2019). However, neither of these two studies distinguished between childhood and adult-onset asthma nor considered the probable sex difference in asthma risk.

In the present study, we conducted a cohort study to investigate whether a higher genetic liability for major depression was associated with an increased risk of asthma in children. This was done by assessing genetic liability for major depression using the measure of polygenic risk score (PRS). The PRS is a single summary measure of inherited susceptibility that integrates all available common variants that account for the variation in disorder risk, which is well suited to characterize shared genetic etiology of complex disorders (Purcell, et al., 2009). We hypothesized that if major depression and childhood asthma shared genetic mechanisms, an elevated risk of childhood asthma would be observed among children with a higher PRS for major depression compared to a lower PRS. Further, we sought to explore whether the probable association differed by the sex of the child.

2. Methods

2.1. Data sources

We conducted a population-based cohort study, utilizing linked information from Danish national registers and genetic data from the Integrative Psychiatric Research (iPSYCH) study. All Danish residents are assigned a unique ten-digit civil personal registration (CPR) number and registered in the Danish Civil Registration System (Pedersen, 2011). The Danish Civil Registration System holds information on date of birth, parity, emigration, and death for every resident. This unique CPR number enables accurate linkage at the individual level between the nationwide registers and the iPSYCH study. The Danish Newborn Screening Biobank stores dried blood spots taken after birth from nearly all infants born in Denmark since May 1st, 1981 (Norgaard-Pedersen and Hougaard, 2007). The Danish National Patient Registry contains data on inpatients since 1977, and since 1995 outpatients are included (Schmidt, et al., 2015). The Danish Psychiatric Central Research Register holds information on inpatient contacts at psychiatric hospitals and wards during 1969–1994 and outpatient contacts since 1995 (Mors, et al., 2011). The International Classification of Diseases, 8th Revision (ICD-8) codes were used until 1993 and ICD-10 codes from 1994 and onwards for the Danish Psychiatric Central Research Register and the Danish National Patient Register. The Danish National Prescription Registry contains information on the Anatomical Therapeutic Chemical (ATC) classification codes and the date of prescriptions dispensed in community pharmacies in Denmark since 1995 (Kildemoes, et al., 2011). Prescriptions for children were issued under the CPR number of the mother before 1996, and after this under the child’s own CPR number.

2.2. Study population

Our defined study population was derived from the iPSYCH2012 study, which has been described in detail elsewhere (Pedersen, et al., 2018). The iPSYCH2012 sample is a subset of the Danish population born between 1981 and 2005, including a random sample of 30,000 subjects drawn from the entire Danish population born in the same period (Figure 1). From this national fully representative sample of 30,000 subjects, we selected children born from 1991 to 2005 (N=19,304) in order to ensure we were able to retrieve information on asthma diagnosis after age five years, as full information on medication and hospital treatment were available since 1996 (Kildemoes, et al., 2011, Schmidt, et al., 2015). We excluded 2368 subjects with no information on genetic data, as well as 117 subjects with no linkage to their parents. Furthermore, since we started the follow-up from the children’s fifth birthday, we excluded 117 subjects who emigrated and 15 subjects who died before age 5 years. A total of 16,687 subjects were included in our study population.

Fig. 1.

Fig. 1.

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Flowchart illustrating the identification of the study population.

2.3. Exposure measure: Polygenic risk score for major depression

Genetic data were extracted from the blood samples obtained from the Danish Newborn Screening Biobank in Denmark. The deoxyribonucleic acid (DNA) samples were whole-genome amplified in triplicate as described previously (Borglum, et al., 2014, Hollegaard, et al., 2011) and genotyped in 23 waves with PsychChip arrays from Illumina according to the manufacturer’s instructions (Grove, et al., 2019). Information about non-genotyped markers was imputed using the 1000 Genomes Project phase 3 imputation reference panel (Pedersen, et al., 2018), and is explained in more detail by Shork et al. (Schork, et al., 2019). Quality control and imputation were performed using the bioinformatics pipeline Ricopili (Lam, et al., 2019).

We computed a combined PRS for major depression as a linear combination of BOLT-LMM PRS (Loh, et al., 2015) and LDpred PRS (Vilhjalmsson, et al., 2015). The BOLT-LMM PRS was trained on individual-level genotypes, and a subset of unrelated individuals of European ancestry in the iPSYCH2012 sample (22,469 cases and 25,882 controls) were used for training. The unrelated sample excludes one individual from each pair with relatedness p > 0.2 (second-degree relatedness). To avoid overfitting, we used 10-fold cross-validation by training the model using 9/10ths of the subset and testing it in the remaining tenth. After training the model, the BOLT-LMM PRS was derived as the weighted sum of the training set prediction betas on the test set genotypes. The linkage disequilibrium patterns were inferred for each training subset in each fold.

The LDpred PRS using external data from the most recent results from Major Depressive Disorder Psychiatric Genomics Consortium (PGC) collaboration (Howard, et al., 2019), excluding iPSYCH2012 sample (229,897 cases and 544,204 controls). The PGC Genome-wide association studies (GWASs) summary statistics for major depression were used for training LDpred, using the infinitesimal model on the overlapping set of single nucleotide polymorphisms (SNPs) with the iPSYCH genotypes. As the iPSYCH sample was not used for training, 5000 individuals were randomly selected from the subset of unrelated individuals of European ancestry in the iPSYCH2012 sample mentioned above and used for the linkage disequilibrium inference.

For both methods, the set of SNPs was restricted to variants with minor allele frequency> 1%, missing values <10%, and SNPs overlapping with HapMap3 (http://www.hapmap.org), ending with a total of 717,871 SNPs for the BOLT-LMM PRS and 166,906 SNPs for the LDpred PRS. The final PRS was a linear combination of BOLT-LMM PRS and LDpred PRS, where the regression coefficients were inferred using two-fold cross-validation. Finally, scores for previously excluded individuals (e.g., related and non-European ancestry individuals) were imputed by averaging over the prediction models. We performed an analysis using the iPSYCH2012 sample to compare the prediction accuracy (in terms of R2, liability scale) among three PRSs. The results showed that the R2 value was 1.5%, 2.8%, and 3.5% for BOLT-LMM PRS, LDpred PRS, and the combined PRS, respectively. Therefore, the combined PRS explained more variation in major depression in the iPSYCH data and was, therefore, used for our analyses.

2.4. Outcome measure: Childhood asthma

We defined childhood asthma between 5 and 15 years, fulfilling either of the two criteria below:

  1. At least one hospital contact for asthma (ICD-10 codes J45 and J46), or

  2. ≥ 2 prescriptions for asthma medication within a year.

The date of asthma onset was defined as the date of the first prescription for asthma medication or first hospital contact for asthma, whichever occurred first. Information on hospital contact was retrieved from the Danish National Patient Registry and asthma medication from the Danish National Prescription Registry. The ATC codes for asthma medications were: Inhaled β2-agonists (R03AC02–04, -12, and -13), inhaled glucocorticoids/corticosteroids (R03BA01, -02, and -05), fixed-dose combination of inhaled β2-agonists and glucocorticoids (R03AK06 and -07), and leukotriene receptor antagonists (R03DC03) (Liu, et al., 2018a). We defined and identified asthma after age 5 years as done in the previous study by our group (Liu, et al., 2018a) because the accurate diagnosis of asthma in children under five years of age is challenging (Bacharier, et al., 2008).

2.5. Covariates

The following covariates were identified and included in the models: calendar year at birth (1991–1995, 1996–2000, or 2001–2005) to address the possible secular trends in diagnostic practices, parental history of asthma before birth (Yes, or no), parental history of atopic disorders before birth (Yes, or no), parental history of psychiatric disorders before birth (Yes, or no), and parity (first-born, second-born or above). We retrieved information on the parental history of asthma and atopic disorders from the Danish National Patient Registry and parental psychiatric history from the Danish Psychiatric Central Research Register. The following ICD codes were used: Parental history of asthma (493 in ICD-8 and J45–J46 in ICD-10) and parental psychiatric disorders (290–309 in ICD-8 and entire F chapter in ICD-10). We considered that children had a parental atopic history if any of the following disorders were recorded in either of the parents: allergic rhinitis except bronchial asthma (507 in ICD-8 and J30.1, J30.2, J30.3, or J30.4 in ICD-10), or atopic dermatitis (691.0 in ICD-8 and L20 in ICD-10) (Liu, et al., 2018b).

We also considered the first 10 principal components to control for population structure, the genotype wave, and European ancestry (Yes, or no). We performed a principal component analysis on the iPSYCH2012 sample following the guidelines in Privé et al., 2019 (Privé, et al., 2019). We computed the Gnanadesikan-Kettenring pairwise Mahalanobis distance (Maronna and Ruben, 2002) of the first 10 principal components and classified individuals as children of non-European ancestry if they had a log-distance from the center larger than 3.

2.6. Statistical analysis

We followed children from their fifth birthday until the first occurrence of asthma, emigration, death, their 15th birthday, or December 31, 2016, whichever came first. We converted the genetic risk score into z-scores according to the distribution in our study subjects based on the following formula: (observed value -mean)/standard deviation. We analyzed the standardized genetic risk score as continuous variables, reported as a unit change for one standard deviation increase in PRS. The standardized scores were split into quartiles, and the differences were compared with the lowest quartile as the reference group.

We used Kaplan-Meier curves to illustrate the cumulative incidence of asthma by the quartiles of PRS for major depression. We used Cox regression models to calculate the hazard ratios (HRs) with 95% confidence intervals (CIs) of asthma according to major depression PRS, stratified by sex of the child. We included major depression PRS both as a continuous variable and a categorical variable in quartiles to examine whether there was a linear or a dose-response relation between major depression PRS and childhood asthma. To account for the increase in the probability of chance findings, we applied a Bonferroni corrected P-value of 0.025 for α = 0.05. The proportionality assumption was tested by visually inspecting "log-log" plots. We fitted both unadjusted and adjusted Cox models incorporating genotype wave, the top 10 population principal components, and the calendar year at birth. The adjusted models were additionally controlled for the following covariates assessed before the time of birth: parental history of asthma, parental history of atopic disorders, parental psychiatric disorders, as well as parity and European ancestry. The proportion of variance in childhood asthma status explained by PRS was determined by pseudo R2 derived from the difference between the full (PRS for major depression and covariates) and the null model (only covariates). Analyses were performed in Stata, version 15.0 (StataCorp, College Station, TX, USA).

2.7. Ethical considerations

Approval for the study was obtained from the Danish Scientific Ethics Committee (Project ID: 1-10-72-287-12), the Danish Data Protection Agency (Project ID: 2012-41-0110), and the Danish Neonatal Screening Biobank Steering Committee. No informed consent is needed for register-based study in Denmark.

3. Results

Of 16,687 children included in the analysis, 8566 (51.3%) were boys and 8121 (48.7%) girls. During a maximum of 10 years of follow-up, 1149 boys and 859 girls developed asthma after 5 years of age. Descriptive characteristics of the samples by asthma occurrence and sex of the child are presented in Table 1.

Table 1.

Characteristics of subjects by asthma occurrence and sex of the child. Figures are numbers (%).

Characteristics Boys (N=8566) Girls (N=8121)
No asthma
(N=7417)		 Asthma
(N=1149)		 No asthma
(N=7262)		 Asthma
(N=859)
Parental history of asthma
 Yes 471 (6.4) 141 (12.3) 518 (7.1) 113 (13.2)
 No 6946 (93.6) 1008 (87.7) 6744 (92.9) 746 (86.8)
Parental history of atopic disorders
 Yes 145 (2.0) 47 (4.1) 142 (2.0) 28 (3.3)
 No 7272 (98.0) 1102 (95.9) 7120 (98.0) 831 (96.7)
Parental history of psychiatric disorders
 Yes 379 (5.1) 64 (5.6) 356 (4.9) 63 (7.3)
 No 7038 (94.9) 1085 (94.4) 6906 (95.1) 796 (92.7)
Parity
  First-born 3230 (43.5) 542 (47.2) 3190 (43.9) 394 (45.9)
  Second-born or later 4187 (56.5) 607 (52.8) 4072 (56.1) 465 (54.1)
European ancestry
 Yes 6437 (86.8) 989 (86.1) 6274 (86.4) 745 (86.7)
 No 980 (13.2) 160 (13.9) 988 (13.6) 114 (13.3)
Calendar year at birth
 1991–1995 2653 (35.8) 452 (39.3) 2597 (35.8) 337 (39.2)
 1996–2000 2113 (28.5) 332 (28.9) 2089 (28.8) 258 (30.0)
 2001–2005 2651 (35.7) 365 (31.8) 2576 (35.5) 264 (30.7)
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3.1. Parental disease history and childhood asthma in the children

Parental disease history measures and captures both genetic susceptibilities and shared environment; therefore, we investigated the risk of childhood asthma according to parental history of asthma, other atopic disorders, and psychiatric disorders by sex of the child (Figure 2). After controlling for covariates listed in Table 1, neither the parental history of atopic disorders nor the parental history of asthma was differentially associated with childhood asthma in both boys and girls. Girls with parental psychiatric history had an increased risk of asthma in comparison to girls with no parental psychiatric history (HR=1.48, 95% CI: 1.14–1.93). In comparison, the association between parental psychiatric history and asthma was not observed in boys (HR=1.09, 95% CI: 0.85–1.41). However, the difference between boys and girls did not reach statistical significance (p value=0.09).

Fig. 2.

Fig. 2.

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The adjusted hazard ratio of childhood asthma by characteristics and sex of the child.

The variables in the figure were mutually adjusted and further adjusted for the calendar year at birth.

3.2. PRS for major depression and risk of childhood asthma

The cumulative incidence of asthma before 15 years was 13.6% (95% CI: 12.9–14.4%) in boys and 10.9% (95% CI: 10.2–11.6%) in girls. Children in the highest quartile of major depression PRS had a higher cumulative incidence of childhood asthma than those in the lowest quartile (Figure 3).

Fig. 3.

Fig. 3.

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The unadjusted cumulative incidence of asthma before 15 years by quartiles of the polygenic risk score for major depression and sex of the child.

The genetic liability for major depression was associated with an increased risk of childhood asthma with a HR of 1.06 (95% CI: 1.01–1.10) per one standard deviation increase in PRS. For stratified analyses by sex: the corresponding HR was 1.03 (95% CI: 0.97–1.09) in boys and 1.10 (95% CI: 1.03–1.18) in girls. Children in the highest quartile of PRS for major depression had an HR of 1.20 (95% CI: 1.06–1.36), compared to those in the lowest quartile. The PRS for major depression explained 0.03% of the variance in childhood asthma (Pseudo-R2). The HRs of asthma by per one standard deviation increase or quartile of PRS for major depression did not differ between boys and girls, although the point estimates were higher in girls (Table 2).

Table 2.

The hazard ratio of asthma occurrence according to the polygenic risk score for major depression per standard deviation increase and in quartiles by sex of the child.

Polygenic risk score for
depression		 Boys (n = 8566) Girls (n = 8121) In total (n = 16,687)c P-value for the interaction of
sex × PRS
Crude HR a P Adjusted HR b P Crude HR a P Adjusted HR b P Crude HR a P Adjusted HR b P
PRS quartile
Lowest quartile 1 (ref) – 1 (ref) – 1 (ref) – 1 (ref) – 1 (ref) – 1 (ref) – –
2nd quartile 1.09 (0.92–1.29) 0.306 1.07 (0.91–1.27) 0.395 1.05 (0.86–1.27) 0.716 1.06 (0.87–1.28) 0.692 1.07 (0.94–1.22) 0.305 1.06 (0.94–1.21) 0.363 0.817
3rd quartile 1.10 (0.93–1.30) 0.283 1.09 (0.92–1.28) 0.351 1.09 (0.90–1.32) 0.370 1.09 (0.90–1.32) 0.363 1.10 (0.97–1.24) 0.166 1.09 (0.96–1.23) 0.198 0.955
Highest quartile 1.17 (0.99–1.38) 0.062 1.16 (0.98–1.37) 0.079 1.29 (1.06–1.56) 0.020 1.29 (1.07–1.26) 0.019 1.21 (1.07–1.37) 0.003 1.20 (1.06–1.36) 0.005 0.468
Per SD increase 1.03 (0.97–1.09) 0.338 1.03 (0.97–1.09) 0.392 1.11 (1.03–1.18) 0.008 1.10 (1.03–1.18) 0.009 1.06 (1.01–1.11) 0.015 1.06 (1.01–1.10) 0.020 0.132
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Abbreviations: HR: hazard ratio, PRS: polygenic risk score, SD: standard deviation.

Adjusted pseudo-R2 = 0.01% for genetic risk score of major depression in boys, 0.05% in girls, and 0.03% in children in general.

a

The first 10 principal components, the genotype wave and calendar year at birth were adjusted both in the crude and adjusted models.

b

In the adjusted models, we further controlled for European ancestry, parental history of asthma, atopic disorders, psychiatric disorders before birth, and parity.

c

Stratified on the sex of the child.

4. Discussion

In our analysis of a population-based representative sample of 16,687 children included in the iPSYCH study, we found that a higher PRS for major depression was associated with an elevated risk of childhood asthma. We further found no evidence that the association between genetic liability for major depression and asthma differed by sex of the child.

4.1. Genetic liability for major depression and the risk of asthma

Previous studies have consistently reported an association between maternal depression and childhood asthma (Brew, et al., 2018b, Liu, et al., 2015, Magnus, et al., 2018), which may be at least partly explained by unmeasured genetic or environmental factors. In the present study, we found a genetic overlap between major depression and childhood asthma, as the genetic liability for major depression was slightly higher among children with childhood asthma. The association remained unchanged after further adjustment for parental history of asthma, atopic disorders, and psychiatric disorders, as well as parity and European ancestry, implying that genetic information adds to established risk factors. Our finding provides direct clues that the associations between maternal depression and asthma in offspring may be at least partially genetically confounded, bearing in mind that the associations between PRS for major depression and asthma are of small magnitude, and the variation explained by PRS is limited.

4.2. Sex difference in the association between major depression PRS and the risk of asthma

There is good evidence for gender-specific differences in asthma occurrence. For instance, boys are more likely to develop asthma than girls in early childhood, whereas this pattern is reversed after puberty (Reed, 2006). A recent genetic study further demonstrated sex differences in genetic expressions on asthma in boys and girls (Gautam, et al., 2019). In the current study, we did not observe a sex-specific association between PRS for major depression and asthma, although the point estimates of associations between major depression PRS and childhood asthma were higher in girls than those in boys. In line with this, a non-significant stronger association between parental history of psychiatric disorders and asthma was observed in girls than in boys. However, the ability to detect a potential interaction effect depends upon both the strength of the interaction term and sample size, and a small interaction effect cannot be excluded entirely based on the size of our study sample.

4.3. Strengths and limitations

Our study is based on a random representative sample of the entire Danish population included in the iPSYCH sample, one of the largest population-based cohorts for genetic studies worldwide. We defined asthma according to register-based asthma diagnosis and dispensed asthma medications, which minimizes information bias as this data is based on data from a health care system providing free and equal care to all citizens in the country. However, we cannot rule out the misclassification of asthma due to the undertreatment of asthma and the overtreatment of transient wheeze. However, we expect this misclassification to be non-differential, and, therefore, would have biased our results toward no association. Although our study has a large sample size of 16,687 children, we may have had insufficient statistical power to examine any sex-specific difference. Moreover, to ensure we had full information to determine childhood asthma status, our study population comprised of individuals born from 1991 to 2005. The oldest individuals in our study at the end of the study were 25 years with a mean age of 19.0 (4.1) years, representing a relatively young cohort. Consequently, most of them would not be old enough to receive a depression diagnosis; thus, our data were not suitable for detailed analyses exploring the association of the diagnosis of major depression with childhood asthma. Lastly, children of European ancestry make up around 90% of our study subjects. PRS may be influenced by differences in allele frequency, estimated effect size, and population structure across different ethnic groups (Marquez-Luna, et al., 2017), and replication in other populations will be needed.

5. Conclusions

Our findings suggest a shared genetic risk for major depression and childhood asthma. However, only a small proportion of asthma risk was attributable to higher genetic liability for major depression. There is no evidence that the association between genetic liability for major depression and childhood asthma differs between boys and girls.

Highlights.

Major depression and asthma frequently co-occur, suggesting shared genetic vulnerability between these two disorders. Limited evidence exists on this topic. In this population-based cohort study using data from Danish national registers and the iPSYCH study, which comprised 16,687 singletons, greater genetic liability for major depression was associated with increased childhood asthma risk. Children in the highest major depression polygenic risk score quartile had a hazard ratio for asthma of 1.20 (95% CI: 1.06–1.36), compared with children in the lowest quartile. Major depression and childhood asthma may share a common genetic contribution.

Acknowledgments:

The authors gratefully acknowledge the Psychiatric Genomics Consortium (PGC) and the research participants and employees of 23andMe, including for providing the summary statistics used to generate the polygenic risk scores.

Funding:

This study is supported by iPSYCH, the Lundbeck Foundation Initiative for Integrative Psychiatric Research (R155-2014-1724). Liu X. was funded by the Danish Council for Independent Research (Project No. DFF-5053-00156B) and is supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 891079. Liu X. and Munk-Olsen T. are supported by the National Institute of Mental Health (NIMH) (R01MH122869). Munk-Olsen T. and Agerbo E. are also supported by Niels Bohr Professorship Grant from the Danish National Research Foundation and the Stanley Medical Research Institute. Munk-Olsen T. is also supported by the Lundbeck Foundation (R313-2019-569), AUFF NOVA (AUFF-E 2016-9-25), and Fabrikant Vilhelm Pedersen og Hustrus Legat.

Role of the funder/sponsor:

The funders had no role in study design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Footnotes

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Financial disclosure: The authors have no financial relationships relevant to the article to disclose.

Declaration of competing interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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