Causal effects of Hirschsprung's disease on psychiatric disorders in the European population: a two-sample Mendelian randomization study

doi:10.21203/rs.3.rs-4996264/v1

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Causal effects of Hirschsprung's disease on psychiatric disorders in the European population: a two-sample Mendelian randomization study

https://doi.org/10.21203/rs.3.rs-4996264/v1

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Background: Previous studies have suggested a potential association between Hirschsprung's disease (HSCR) and psychiatric disorders. However, the causal relationship between HSCR and psychiatric disorders remains unclear. Therefore, we use Mendelian randomization to explore the causal relationship between HSCR and depression, anxiety, attention deficit and hyperactivity disorder(ADHD), and autism spectrum disorder(ASD).

Methods: Genome-wide association Studies (GWAS) meta-analyses with the largest possible sample size and independent individuals from European ancestry were selected. The genetic data for depression and anxiety are from FinnGen consortium, while the genetic data for ADHD and ASD are from the Psychiatric Genomics Consortium. Inverse variance weighted (IVW) was the main analysis method. The heterogeneity of the instrumental variables (IVs) was assessed using IVW and MR-Egger, and the horizontal pleiotropy of the IVs was assessed using MR-Egger and MR-PRESSO.

Results: The IVW analysis revealed a significant causal relationship between HSCR and ADHD(OR=1.010，95%CI=1.002-1.018；P=0.0119). However, there is no evidence to suggest a causal relationship between HSCR and depression, anxiety, and ASD. Furthermore, our sensitivity analysis did not reveal any evidence of heterogeneity or horizontal pleiotropy.

Conclusion: Our results suggest that HSCR increases the risk of ADHD. Therefore, greater attention should be paid to the psychological health of children with HSCR.

Hirschsprung's disease

Psychiatric disorders

Attention deficit and hyperactivity disorder

Depression

Hirschsprung’s disease (HSCR) is a congenital developmental abnormality of the enteric nervous system (ENS),characterized by a lack of ganglion cells in the distal lesion, resulting in functional intestinal obstruction above the ganglion level. Its incidence rate is 1/5000. The primary clinical manifestations of HSCR include delayed meconium discharge after birth, intractable constipation, abdominal distension, and vomiting [2]. Currently,the only treatment method for HSCR is surgical treatment, which restores normal intestinal function by removing the non-ganglionic intestinal segment and rebuilding the innervated intestine to the anal opening.Although the current surgery has a good effect, about 1/3 patients still have postoperative complications, including intestinal obstruction, malnutrition, constipation, enterocolitis, etc [1]. Poor prognosis often affects the quality of life and psychosocial function of patients with HSCR [15; 17]. With the development of bio-psycho-social medical model,the psychological disorders of HSCR patients are receiving increasing attention.

A study on the global burden of disease indicates that there is a growing burden of mental illness [55]. Mental disorders are among the leading causes of death worldwide [54]. Depression is an emotional disorder characterized by persistent feelings of sadness and loss of interest in almost all activities, and it is associated with an increased risk of suicide [33]. A cohort study based on the national population indicates that individuals with HSCR have a heightened risk of developing depression [4]. Anxiety is the most common mental illness after depression, characterized by anxiety or fear, which can have a negative impact on the quality of life of patients [34]. In a study of patients with HSCR, more than half of them showed high trait anxiety [6]. Attention deficit hyperactivity disorder (ADHD) is the most prevalent neurodevelopmental disorder, affecting 5.9% of young people and 2.5% of adults worldwide according to the 2021 World ADHD International Consensus Statement [23]. ADHD can lead to a wide range of mental and physical dysfunction and increase the risk of premature death [18]. Some studies suggest that the connection between the central nervous system and ENS may contribute to the development of ADHD in HSCR patients. However, another cohort study found that patients with HSCR did not have an increased risk of ADHD [27; 42]. It must be acknowledged that observational studies may encounter potential confounding factors, such as reverse causality and selection bias, which may affect their research results. Therefore, the exact relationship between HSCR and mental disorders remains elusive.

Mendelian randomization (MR) analysis uses genetic variation as an instrumental variable (IV) to detect causal relationships between risk factors and diseases. Compared with traditional observational studies, MR Provides more reliable evidence of causality [56]. Due to the random distribution of genes during meiosis, MR can effectively eliminate confounding factors and overcome the influence of reverse causality by passing parental traits to offspring without interference from environmental conditions, socioeconomic status, or behavioral characteristics. Therefore, in recent years, MR has been increasingly utilized to infer the causal relationship between various diseases and mental disorders, such as heart failure, diabetes, chronic obstructive pulmonary disease, etc [13; 39; 58]. In this study, we conducted a two-sample Mendelian randomization (TSMR) analysis using data from the genome-wide association study (GWAS) to investigate the potential causal relationship between HSCR and various psychiatric disorders including depression, anxiety, ADHD, and autism spectrum disorder(ASD) from a genetic perspective.

1.Study design

According to the recommendations of the STROBEMR guidelines [20], this study utilized TSMR to investigate the causal relationship between HSCR and psychiatric disorders (depression, anxiety, ADHD, and ASD). The TSMR study should satisfy three fundamental hypotheses [50]: (1) the genetic IVs utilized must exhibit significant correlation with HSCR; (2) the genetic IVs must be independent of any potential confounding factors associated with the outcome; (3) the genetic IVs should only be linked to the outcome through HSCR and not through other causal pathways.(Fig.1)

Fig.1.MR assumptions and study design.

SNPs, single nucleotide polymorphisms. ADHD, attention deficit hyperactivity disorder. ASD, autism spectrum disorder.

2.Data sources

To minimize the potential bias introduced by racial factors, all genetic IVs utilized in this study were sourced from the European population. GWAS data consists of information that demonstrates the influence of single nucleotide polymorphisms (SNPs) on phenotype. In order to obtain the genetic information of HSCR, we searched the GWAS summary statistics of Fadista J et al. (PMC29379196) [22]. The study included 179 HSCR cases and 4,943 controls from the Danish Neonatal Screening Biobank, as well as replicated cases from the United States, Finland, and Sweden, which comprised 416 HSCR cases and 903 controls. This is the largest summary statistical data related to HSCR to date, including 6,162,479 SNPs.

GWAS summary statistics related to depression and anxiety were obtained from the FinnGen consortium (https://www.finngen.fi/fi). The summary statistical data for depression includes 234,24 cases and 192,220 control European samples (GWASID: finn-b-F5_DEPRESSIO).The summary statistical data for anxiety includes 20,992 cases and 197,800 controls (GWASID: finn-b-KRA_PSY_ANXIETY). The genetic data related to ADHD and ASD is sourced from the Psychiatric Genomics Consortium (PGC) database（ https://www.med.unc.edu/pgc/download-results ）. The summary statistical data of ADHD comes from a genome-wide association meta-analysis of 38,691 ADHD patients and 27,969 controls [16]. We obtained summary statistical data for ASD from a genome-wide association meta-analysis of 18,381 cases diagnosed with ASD and 27,969 controls [28]. Table 1 provides detailed information on the studies and datasets used in this study.

Table 1 Detailed information of the datasets used for Mendelian randomization analyses.

Traits	Sample size	Cases	Controls	Ancestry	PubMed ID/GWAS ID
HSCR	6,206	586	5,620	Europeans	29379196
Depression	215,644	23,424	192,220	Europeans	finn-b-F5_DEPRESSIO
Anxiety	218,792	20,992	197,800	Europeans	finn-b-KRA_PSY_ANXIETY
ADHD	225,534	38,691	186,843	Europeans	36702997
ASD	46,350	18,381	27,969	Europeans	30804558

HSCR, Hirschsprung’s disease. ADHD, attention deficit hyperactivity disorder. ASD, autism spectrum disorder.

3.Selection of IVs

According to convention, the threshold is generally set to p<5 × 10^-8. In order to obtain a sufficient number of SNPs closely related to HSCR, we uses p<5 × 10^-6 as the screening threshold for exposure factors, and select independent SNPs with r²<0.01 and LD distance ≤ 10000 kb to avoid the impact of linkage disequilibrium(LD) on the results. In addition, we use the PhenoScanner V2 website (http://www.phenoscanner.medschl.cam.ac.uk/) removes SNPs associated with potential confounding factors that may affect the risk of psychiatric disorders, smoking, alcohol consumption, body mass index, obesity, insomnia and drug use were identified as confounding factors in this study. Finally, we use F statistics to evaluate the intensity of exposure factors, and the formula is as follows: F = beta²/sd², where beta represents the effect of SNPs on exposure, and sd represents standard deviation [9]. When the F-statistic value exceeds 10, it suggests a low likelihood of weak IVs. SNPs with F-statistic values below 10 are excluded to mitigate bias stemming from weak IVs [45]. Lastly, SNPs that satisfy all three hypotheses were selected, and the exposure and outcome datasets were combined. Palindromic SNPs in the merged dataset were excluded, and the remaining SNPs were utilized as IVs for subsequent MR analysis.

4.Statistical analysis

Mendelian randomization analysis

This study utilized TSMR to evaluate the causal relationship between HSCR and psychiatric disorders.We utilize the inverse variance weighted (IVW) as the primary analysis method. The IVW method is a meta-analysis approach that integrates the Wald ratio of each SNP, assuming that IVs can only impact results through exposure, and demonstrates strong detection performance for causal relationships [35]. If the results from the IVW method are significant (P<0.05) without detecting pleiotropy and heterogeneity, they can still be considered reliable even if other methods yield non-significant results. In addition, we also used MR Egger, weighted median, simple mode, and weighted mode to supplement the IVW analysis results.

Sensitivity analyses

We use Cochran's q test to evaluate the heterogeneity of the genetic effects of the selected exposure factors. If the p-value is greater than 0.05, it indicates no heterogeneity, and a fixed effects IVW model is used. If heterogeneity exists, a random-effects IVW model is used [26]. To detect horizontal pleiotropy, we conducted an MR Egger intercept test. If the P-value of MR-Egger intercept is >0.05, it indicates that there is no horizontal pleiotropy [10]. In addition, the leave-one-out method was used for sensitivity analysis to explore the impact of removing a single SNP on the overall results [32]. Finally, to ensure the accuracy of the results, we tested and calibrated the horizontal multi-directional outliers in the IVW model using MR pleiotropy residual sum and outlier (MR-PRESSO) [53].

In this study, we used the Bonferroni calibration method to correct the p-value. Therefore, we believe that the Bonferroni correction threshold p<0.0125 (p<0.05/4) is statistically significant and can serve as evidence for the existence of causal relationships. If the p-value is between 0.0125 and 0.05, it is considered suggestive evidence of causality. We conducted statistical analysis using R (version 4.3.2) and used odds ratio (OR; 95% confidence interval (95% CI)) to represent the MR analysis results.

1.IVs selection

After screening for SNPs closely related to HSCR (P<5 × 10^-6), removing any linkage disequilibrium (r²<0.01 and LD distance ≤ 10000 kb), and excluding SNPs potentially influenced by confounding factors or outcome variables through the PhenoScannerV2 database(not found), 18 SNPs were ultimately selected that met all three hypotheses simultaneously. Upon calculating the F-value, it was determined that the maximum F-value was 214.80 and the minimum was 21.15, and the F-value of each SNP was greater than 10, indicating that HSCR and the phenotype related to psychiatric disorders were less likely to be affected by weak IV bias. Then, by extracting the GWAS summary data of the outcome of psychiatric disorders, merging with the exposure data, and deleting the palindrome sequence. The IVs ultimately used to evaluate the causal association between HSCR and depression, anxiety, ADHD, and ASD were 15, 15, 14, and 15 SNPs, respectively.

2.MR analysis for the causal effects of HSCR on psychiatric disorders

The IVW method revealed that HSCR was associated with a high risk of ADHD (OR = 1.010, 95% CI [1.002-1.018], P = 0.0119). The Bonferroni-corrected threshold p = 0.0119 (p < 0.05 CI 4 = 0.0125) indicated that the causal relationship was still significant. However, there is no evidence of a causal relationship between HSCR and the risk of depression (OR = 1.000, 95% CI [0.991-1.009], P = 0.9112). The IVW method has no evidence to support the causal relationship between HSCR and anxiety (OR = 1.007, 95% CI [0.997 1.017], P = 0.1554). For ASD, we found no genetic association with HSCR (OR = 0.997, 95% CI [0.982-1.011], P = 0.6457).

The causal effects of HSCR on psychiatric disorders are shown in Fig.2 .

Fig.2.

nSNP,numbers of single nucleotide polymorphism. ADHD, attention deficit hyperactivity disorder. ASD, autism spectrum disorder.

3.Sensitivity analysis

We conducted a series of sensitivity analyses to evaluate the robustness of the above results. No horizontal multiplicity was found in our MR analysis, because the p values of all MR-egger intercept tests were greater than 0.05. the results showed that there was no horizontal multiplicity (MR-Egger intercept=0.0119,p=0.2097) in the results of HSCR and ADHD (Fig.3). No heterogeneity was found in Cochran's Q test, and P values were all > 0.05. Among them, there was no heterogeneity between HSCR and ADHD (Q=12.12, Q_P=0.5178). The leave-one-out analysis showed that the results were robust, and there was no significant deviation of individual SNPs on the overall causal estimation (Fig.S2). The MR-PRESSO test results did not show any possibility of horizontal pleiotropy. The above results further prove the reliability and stability of the conclusions of this study. (Table 2)

Fig.3.Scatter plots of MR analyses. (A) Scatter plot for analyzing the causal association between HSCR and depression; (B) Scatter plot for analyzing the causal association between HSCR and anxiety; (C) Scatter plot for analyzing the causal association between HSCR and ADHD; (D) Scatter plot for analyzing the causal association between HSCR and ASD

ADHD, attention deficit hyperactivity disorder. ASD, autism spectrum disorder.

Table 2 Heterogeneity and pleiotropy tests for the associations of HSCR with psychiatric disorders.

Outcome	Cochran Q test		MR-Egger		MR-PRESSO
Outcome	Q value	P	Intercept	P	Global tese p	Outlier test
Depression	12.09	0.5990	-0.0102	0.3225	0.4293	NA
Anxiety	16.09	0.3080	-0.0085	0.4605	0.2750	NA
ADHD	12.12	0.5178	0.0119	0.2097	0.5436	NA
ASD	22.7	0.0653	-0.0280	0.0973	0.0717	NA

ADHD, attention deficit hyperactivity disorder. ASD, autism spectrum disorder. NA, not applicable.

Hirschsprung's disease (HSCR) is a congenital condition characterized by the loss of ganglion cells, leading to chronic constipation, bloating, and vomiting in patients. While most pediatric patients have a good postoperative prognosis, some may experience persistent obstruction and intestinal dysfunction in the early years. By adulthood, approximately 10% of patients continue to suffer from fecal contamination, significantly impacting their quality of life. Research indicates that compared to healthy peers, HSCR patients have lower quality of life, and social psychological function is an important predictive indicator of patient quality of life [29]. These psychosocial problems appear when the patient is very young. If they are not solved, they may increase the incidence rate of mental disorders [51].

Based on the potential association between HSCR and psychiatric disorders, our study represents the first attempt to use TSMR analysis in order to investigate genetic causality between HSCR and four major psychiatric disorders. Our MR Study shows that HSCR is associated with a higher risk of ADHD. However, our findings from this TSMR Study do not support a genetic causal relationship between HSCR and the risk of other psychiatric disorders, including depression, anxiety, and ASD.

It must be acknowledged that traditional observational studies are subject to confounding factors, reverse causality, and various biases that may lead to spurious associations between exposure and outcomes. Therefore, the causal relationship between exposure and disease outcomes as derived from traditional observational studies is not entirely accurate. However, MR Studies utilize a wide range of GWAS studies to select genetic variation as an IV, thereby avoiding the influence of confounding factors. This allows for broader sensitivity analysis and more reliable causal analysis [8]. Our MR Analysis provides favorable evidence for a shared genetic influence between HSCR and ADHD, suggesting that HSCR significantly increases the risk of ADHD, which supplements previous studies.

So far, the precise mechanism connecting HSCR with ADHD has not been fully elucidated, and the following hypotheses are worthy of consideration. Maternal exposure during pregnancy may be a common environmental factor leading to HSCR and ADHD. The occurrence of HSCR is closely related to maternal pregnancy risk factors. Research has shown that maternal obesity during pregnancy is a risk factor for childhood HSCR [40]. Furthermore, a meta-analysis on the relationship between pre pregnancy obesity in pregnant women and neurodevelopmental outcomes in children found that pre pregnancy obesity also increases the risk of ADHD in children [48]. Vitamin A is an essential nutrient and a precursor to retinoic acid, which plays a crucial role in the effective migration of ENS precursors in the developing intestine and the formation of migratory cell pods [24]. Research has found that lower maternal vitamin A levels increase the risk of children developing HSCR [31]. It is noteworthy that Li et al. discovered a higher incidence of vitamin A deficiency in children with ADHD compared to normal children. However, the underlying mechanism behind this phenomenon remains unclear [37]. In addition, a case report describing the association between congenital hypothyroidism and HSCR speculates on the importance of thyroid hormone levels and the development of HSCR [52]. Thyroid hormones play a crucial role in the fetal neural development. Ran S et al. found that maternal hypothyroidism is associated with an increased risk of ADHD in offspring [47].

ICAM-1 is a transmembrane glycoprotein that mediates biological activities such as cell adhesion, chemotaxis, and lymphocyte homing, and participates in inflammation and immune responses, playing a role in physiological and pathological processes [57]. Previous studies have revealed the role of ICAM-1 in some neurological and psychiatric disorders [5; 44]. Belgin et al. found that ICAM-1 mediated inflammatory response may be involved in the pathogenesis of ADHD [3]. In addition, ICAM-1 expression was increased in HSCR pathologic ganglia, suggesting that the function of antigen presenting cells in hypertrophic nerve trunks and abnormal transitional ganglia may be partially mediated by ICAM-1 [36]. Changes in neurobehavior are usually associated with changes in the level of neurotransmitters. Gamma-Aminobutyric acid (GABA) is a crucial neurotransmitter in the pathophysiology of ADHD [30]. Increasing evidence suggests that a reduction in GABA levels is closely associated with an increased risk of developing ADHD [19; 21]. Interestingly, Sukhada et al found loss of GABA neurons in the small intestinal ENS of HSCR mice [7]. Other research has indicated a potential link between the occurrence of HSCR and ADHD with the downregulation of EGR1 gene expression [25; 43].

The gut microbiota is considered a crucial regulatory factor in connecting the brain-gut axis. Since the establishment of a stable gut microbiota coincides with the development of the central nervous system in early life, disruption of the microbiota may have a negative impact on neurodevelopment [11; 14]. Multiple studies have shown a decrease in gut microbiota diversity in both ADHD and HSCR children, which may be another link between HSCR and ADHD [12; 46]. Lin et al. discovered that the early use of antibiotics in children is associated with an increased risk of ADHD [38]. Due to surgical treatment and the high incidence of Hirschsprung-associated enterocolitis (HAEC), patients with HSCR often receive antibiotics at a young age. In addition, fecal incontinence is a common long-term functional problem in HSCR patients. Research has found that the prevalence of fecal incontinence is higher in children with ADHD, which may also be one of the causes of ADHD in HSCR patients [41].

All of the above factors may be important confounding factors between HSCR and ADHD. We need to recognize that the pathogenesis of HSCR is a complex whole, and overemphasizing one link may lead to neglecting and losing another link. Due to the current lack of GWAS data in genetic databases, further refinement of the pathogenesis of HSCR is limited. Therefore, this study remains the most effective method for determining the causal relationship between HSCR and ADHD. As the GWAS database continues to expand and update, IVs will also become more enriched. We have reason to believe that sufficient genetic data can predict the probability of ADHD in HSCR patients and provide early and timely intervention.

In our MR research, there are several advantages. Firstly, we used the largest GWAS summary dataset currently available for HSCR, and multiple GWAS summary datasets from different sources were used for four psychiatric disorders, so there was almost no overlap between the exposed and outcome populations in the sample. Secondly, MR research is a method of studying causal relationships based on genetic variation as an IV, which minimizes the possibility of reverse causality and potential confusion in observational studies, greatly improving the reliability and persuasiveness of our research. Thirdly, obtaining GWAS data from samples of European ancestry effectively reduces bias caused by population racial differences. Fourthly, we perform a series of rigorous steps to screen SNPs to obtain effective IVs, and calculate the statistical strength of each IV to reduce bias in weak IVs. Finally, we conducted heterogeneity, pleiotropy and sensitivity analysis of MR Results to ensure the robustness of our results.

Our MR research still has some limitations. Firstly, all GWAS summary statistical data used in this study were sourced from the European population. Considering the existence of racial genomic heterogeneity, our research conclusions may not represent other races. More large sample size, multicenter genetic engineering experiments with different populations are needed to further validate the results of this study. Secondly, due to the limitations of GWAS data aggregation, it is not possible to conduct stratified analysis on factors such as type of HSCR, age, and gender. Thirdly, this study did not determine the threshold value in accordance with the convention when screening SNPs. In order to obtain more SNPs, we adjusted the P-value and r² value to an acceptable range. In addition, MR has the advantage of evaluating the direct impact of exposure factors on results, while ignoring intermediate effects or effects generated through other pathways [49]. Although our MR study has shown a causal relationship between HSCR and the risk of ADHD, we cannot infer the relative weights of genetic and environmental factors that contribute to ADHD. This may limit the full understanding of the causal chain and requires further study.

Our results suggest that HSCR increases the risk of ADHD. Therefore, greater attention should be paid to the psychological health of children with HSCR.

[Funding]

This work was supported by CQMU Program for Youth Innovation in Future Medicine (No. W0125); General program of Clinical medical research, National Center for Clinical Medical Research in Child Health and Disease (No. NCRCCHD-2022-GP-03).

[Acknowledgement]

We thank the participants and investigators involved in the Psychiatric Genomics Consortium resource for providing GWAS data (https://www.med.unc.edu/pgc/download-results). We want to acknowledge the participants and investigators of the FinnGen study (https://www.finngen.fi/fi).

[Authors’ contributions]

Author contributions Study concept and design: Zhengxing Jiang and Yujie Wang; Acquisition of the data: Xiaohong Die, Jinping Hou, Wei Feng; Analysis and interpretation of the data: Yi Wang; Drafting of the manuscript: Zhengxing Jiang; Criticalrevision of the manuscript for important intellectual content: Wei Feng. All authors read and approved the final manuscript.

[Data Availability]

See the "Methods" section.

[Declaration of Interest Statement]

All authors declared that there were no conflicts of interests in the study. The funders had no influence on the data collection, analyses or conclusions of the study, and the views expressed in the study were from all the authors themselves and not related to the funders.

[Ethics Approval]

Not applicable.

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Causal effects of Hirschsprung's disease on psychiatric disorders in the European population: a two-sample Mendelian randomization study

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