Skip to main content
Download PDF

Association between human herpesviruses infections and childhood neurodevelopmental disorders: insights from two-sample mendelian randomization analyses and systematic review with meta-analysis

Italian Journal of Pediatrics volume 50, Article number: 248 (2024) Cite this article

Abstract

Background

The potential roles of viral infections in neurodevelopmental disorders (NDDs) have been suggested based on previous studies. Given the high prevalence of human herpesviruses (HHVs), the associations between HHVs infection and the risk of NDDs warrant explored.

Methods

Our study employs a two-sample Mendelian randomization (MR) analysis and systematic review with meta-analysis to investigate whether genetically predicted HHVs infection are linked to three main childhood NDDs—autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), and Tourette syndrome (TS). We utilized genetic variants associated with HHV infections in genome-wide association study (GWAS) summary datasets of European populations to establish instrumental variables and statistics for three NDDs obtained from Psychiatric Genomics Consortium. MR analysis was performed using inverse-variance weighted, MR Egger, weighted median, simple median, weighted mode, and MR-PRESSO. In addition, publications associating HHVs infection with three NDDs were systematically searched using PubMed, Web of Science, and three Chinese databases for meta-analyses.

Results

The MR results found no evidence to support a link between genetically predicted HHVs infection and the risk of NDDs based on existing datasets. Twenty-seven observational studies on children with HHVs infection and NDDs were considered eligible. Meta-analysis showed that cytomegalovirus and HHV-6 infection were related with ASD, while Epstein-Barr virus and cytomegalovirus infection were associated with TD in Chinese population. Conclusions: These results contribute to a comprehensive understanding of the possibilities underlying HHV infections in affecting childhood NDDs. Further research is necessary to include larger and more robust statistics of HHV infections and NDDs.

Trial registration

This systematic review was registered at PROSPERO as CRD42024554169. Retrospectively registered 26 July 2024.

Background

Neurodevelopmental disorders (NDDs) are a group of disorders affecting the development of the central nervous system (CNS) in children, including autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD) and tic disorders [1, 2]. ASD manifests through impaired social interaction, alongside restrictive and repetitive behaviors or interests. In 2018, the estimated prevalence of ASD among 8-year-old children in the United States was 2.3% [3], which increased to approximately 2.8% in 2020 [4]. ADHD, characterized by symptoms of inattention, hyperactivity, and impulsivity, stands as the most prevalent mental disorder affecting children and adolescents globally, with prevalence estimated at 6–7% [5]. Tourette syndrome (TS), as one kind of tic disorders, includes both phonic and motor tics, showed an estimated prevalence of 0.3% to 0.9% among school-age children aged 4–18 years [6]. These disorders could impact children's cognition, language, movement, and learning abilities, with some impairments even exist for a lifetime, resulting in health and social challenges [7, 8]. However, the etiology of NDDs is multifaceted and elusive, with genetic, neurological, and environmental factors likely contributing in combination. Perinatal infection is one of the potential risk factors for childhood NDDs [9,10,11,12,13]. Viral infections, which are common in humans, have been highlighted in previous studies for their correlations with ASD [14,15,16], ADHD [17, 18], and TS [19, 20].

Human herpesviruses (HHVs) are a group of double-stranded DNA viruses with the capacity to infect humans, comprising eight species categorized into three families. Alpha (α)-herpesviruses primarily reside in neurons, including HHV-1 and HHV-2—herpes simplex virus (HSV) 1 and 2, as well as HHV-3—varicella-zoster virus (VZV); beta (β)-herpesviruses encompass HHV-5—cytomegalovirus (CMV), HHV-6, and HHV-7, which persist in macrophages and lymphocytes; gamma (γ)-herpesviruses exclusively inhabit lymphocytes, including HHV-4—Epstein-Barr virus (EBV) and HHV-8 [21].

HHVs can be transmitted through contact and often result in latent infections, leading to a high prevalence but relatively low incidence in the population. Data from 2016 indicate that the global prevalence of HSV-1 among individuals aged 0–49 is approximately 67%, with an incidence rate of about 2%. For HSV-2, the prevalence is around 13%, while the incidence rate is only 0.6% [22]. The global burden of VZV infection in 2019 exceeded 80 million cases, with the highest disease burden observed among children under 5 years of age [23]. CMV demonstrates a global seroprevalence estimated at 83% in general population, reaching as high as 86% in the women of reproductive age [24]. The overall prevalence of congenital CMV (cCMV) infection in newborns is approximately 0.6% [25]. EBV infection affects over 90% of the global population, with the majority of children becoming seropositive by the age of 5 [26]. Furthermore, HHV-6 infects over 90% of infants and commonly persists throughout life [27], while HHV-7, closely related to HHV-6, similarly induces infections during childhood [28]. Given that HHVs can affect the fetus through perinatal infection or directly infect children, their potential association with neurodevelopment is of significant interest.

Mendelian randomization (MR) analysis follows Mendel's law of random distribution of parental alleles to offspring, serving as a method to infer causal relationships between phenotypes and diseases by utilizing genetic variants as instrumental variables (IVs) [29]. It is also referred to as "nature's randomized controlled trial." MR studies are less susceptible to reverse causation and confounding factors compared to observational studies [30]. In the absence of randomized controlled trials, MR holds the highest level of evidence in the hierarchy of evidence-based medicine [31]. In recent years, the emergence of genome-wide association studies (GWAS) has revealed associations between single nucleotide polymorphisms (SNPs) and diseases in specific populations [32]. This provides an excellent opportunity to use MR methods to investigate the causal effects of viral infections on NDDs.

This study, based on publicly available GWAS data, employs a two-sample MR approach to explore whether there are causal associations between HHVs and ASD, ADHD, and TS. Additionally, we conducted a systematic review of observational studies and performed selective meta-analyses to provide relevant evidence.

Methods

MR analysis

Study design

A two-sample MR analysis method was employed to investigate the potential relationship between HHVs and three main child NDDs (ASD, ADHD, and TS). To ensure the robustness of our findings, our MR study adhered to three fundamental assumptions: 1. Genetic variants exhibit significant associations with circulating cytokine levels (association hypothesis); 2. Genetic variants remain independent of other confounding factors (independence assumption); 3. Genetic variants should exclusively influence outcomes through exposure factors (exclusivity hypothesis) (Fig. 1). We adhered to the Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization (STROBE-MR) guidelines to ensure methodological rigor in the study, as shown in Additional file 1: STROBE-MR checklist.

Fig. 1
figure 1

The flow chart of two-sample Mendelian randomization study design on HHV infections and three childhood NDDs. All GWAS summary data were obtained from participants of European ancestry

Full size image

Data sources

We obtained summary data on genetic variants related to HHVs as exposures from the latest FinnGen (https://r10.finngen.fi/) and the IEU Open GWAS project (https://gwas.mrcieu.ac.uk/). Since no published data could be found for HHV-8, only GWASs for HHV1-7 were included in this study. Datasets were listed as followings: HSV infection: finngen_R10_AB1_HERPES_SIMPLEX (3,723 cases and 396,378 controls), finngen_R10_H7_HERPESKERATITIS (1,252 cases and 390,647 controls), and finngen_R10_AB1_ANOGENITAL_HERPES_SIMPLEX (1,986 cases and 400,197 controls); HSV-1 IgG: ebi-a-GCST006346 (645 cases), and HSV-2 IgG: ebi-a-GCST006347 (208 cases). VZV infection: finngen_R10_AB1_ZOSTER (5,488 cases and 396,478 controls); VZV IgG: ebi-a-GCST90006928 (8735 cases). EBV infection: finngen_R10_AB1_EBV (2,979 cases and 400,974 controls); EBNA1: ebi-a-GCST006361 (914 cases); VCA: ebi-a-GCST006362 (956 cases). CMV infection: finngen_R10_CMV_NOS (487 cases and 411,593 controls); CMV IgG: ieu-b-4900 (5,010 cases). HHV-6 IgG: ebi-a-GCST90006902 (8,735 cases). HHV-7 IgG: ebi-a-GCST90006908 (8,735 cases).

GWAS summary statistics for outcomes including ASD (18,381 cases and 27,969 controls) [33], ADHD (38,691 cases and 186,843 controls) [34], and TS (4,819 and 9,488 controls) [35] were downloaded from the Psychiatric Genomics Consortium (PGC) (https://pgc.unc.edu/for-researchers/download-results/). All GWASs were based on European populations.

Instruments selection

Initially, we applied a stringent genome-wide significance threshold (p < 5 × 10−8) to select highly correlated IVs. However, due to the limited number of SNPs meeting this criterion for most exposures, a more permissive significance threshold (p < 5 × 10−6) was adopted. Then we performed clumping (r2 < 0.001 and distance = 10,000 kb) to eliminate IVs exhibiting linkage disequilibrium. F-statistics were used to determine the strength of the relationship between selected IVs and exposure. When F > 10, IVs are considered strong instrumental variables. The F-statistic is calculated by F = R2(N − 2)/(1 − R2) and R2 = 2 × EAF × (1 − EAF) × beta2, where R2 is the proportion of exposure variability explained by each instrument and N is the sample size of the GWAS for the SNP-HHVs relationship [36]. Details of all SNPs clumped and the F-statistic and R2 are provided in Additional file 1: Table S1. Subsequently, a harmonization process was implemented, and palindromic SNPs were removed. We employed GWAS catalog (https://www.ebi.ac.uk/gwas/) to detect other phenotypes of individual SNPs to eliminate potential influence on the results.

Statistical analysis

A total of five main MR analysis methods namely inverse-variance weighted (IVW), MR Egger, weighted median, simple median, and weighted mode were used in this study. These analyses are only conducted when the number of IVs ≥ 3. The IVW method was designated as the primary analytical tool for deriving credible causal effect estimates [37]. Evaluation of potential pleiotropy and heterogeneity involved MR-Egger intercept, MR-PRESSO method, and Cochran's Q test. Absence of vertical pleiotropy was determined if the MR-Egger intercept did not significantly deviate from 0 [38]. The MR-PRESSO results can be used to determine the presence of outliers, and P > 0.05 indicates the absence of horizontal pleiotropy [39]. Heterogeneity, as assessed by Cochran's Q statistic, was considered non-existent when p > 0.05, leading to the adoption of the fixed-effects IVW model as the primary outcome. Additionally, a leave-one-out analysis was performed to estimate the impact of individual aberrant SNPs on the overall MR analysis, ensuring result robustness. A causal relationship was deemed statistically significant if the results of MR analysis meet the following three conditions: (1) the p value of the IVW method was less than corrected p-value for multiple testing; (2) consistency between IVW and other methods was observed; (3) no pleiotropy and heterogeneity were identified. While p < 0.05 was considered suggestively causal significant. All statistical analyses were conducted using the “TwoSampleMR” and “MendelianRandomisation” package in R version 4.3.0.

Systematic review with meta-analysis

Literature Search

This part of study was reported according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guideline [40], and the checklist was provided in Additional file 4: PRISMA checklist. The study protocol is also registered at PROSPERO (CRD42024554169). Five databases including PubMed (Medline), Web of Science, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform, and China Science and Technology Journal Database—were systematically searched from inception to 1 June 2024. To search relevant studies of HHV infection and NDD, MeSH terms of all kinds of HHVs, ASD, ADHD, and TS were used. Detailed information was listed in Addition file 4: Search terms and strategy. We also manually reviewed the references of retrieved studies to identify additional studies. The flowchart of literature search was displayed in Fig. 2.

Fig. 2
figure 2

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram for study selection for the systematic review on HHV infections and three childhood NDDs

Full size image

Inclusion and exclusion criteria

Inclusion: 1) studies comparing the prevalence of HHV infection between control groups and cases of NDDs, or comparing the prevalence of NDD between control groups and cases of HHV infection; 2) observational studies published after the year 2000; 3) NDD diagnoses based on established criteria, including Diagnostic and statistical manual of mental disorders (DSM), International Classification of Diseases (ICD), or assessments by qualified medical professionals; 4) detection of HHV infection indices, including antibodies or DNA, through body specimens such as blood, urine, or brain samples. Exclusion: 1) studies involving non-human subjects, case reports, or reviews lacking relevant information; 2) studies lacking valuable data or not providing full-text access.

Study selection and risk of bias assessment

After removing the duplicate publications using Endnote (version X9, Clarivate Analytics), two researchers (LF and ZW) independently screened the titles and abstracts of the literatures for eligibility and selected qualified studies based on search strategy and inclusion criteria. Any discrepancies were dissolved through discussion with a third researcher (JZ).

The Agency for Healthcare Research and Quality (AHRQ) evaluation criteria was used to evaluate the risk of bias in the observational studies [41]. The AHRQ criteria consist of 11 items, each of which is answered as "yes," "no," or "not reported." A "yes" response scores 1 point, while "no" and "not reported" responses score 0 points. Scores ranging from 0 to 3 are considered low quality, 4 to 6 are considered medium quality, and 8 to 11 are considered high quality. The specific assessments were provided in Additional file 4: Risk of bias assessments.

Data extraction and quality assessment

Data were extracted based on the PECOS (Population, Exposure, Comparator, Outcomes and Study design) framework. Bibliographic information includes author's name, year of publication. Background information includes study design, country, sample source, detection methods, sample collecting time, population size, number of positive in case and control groups, and statistical methods.

Then we used the Newcastle–Ottawa Rating Scale (NOS) to evaluate the quality of the observational studies [42]. Two researchers (XW and SW) followed the three evaluation parameters of NOS including selection, comparability, and outcome to give the “asterisk score” of each study. The score ranged from 1 to 9: 1–3, 4–6, and 7–9, which are considered low, medium, and high quality, respectively. The specific assessments were provided in Additional file 4: Quality assessments.

Statistical analysis

Meta-analysis was considered when at least two studies assessed the same HHV infection as a risk factor. The pooled odds ratio (pOR) was calculated with 95% CI using the size and number of HHV-positive infections in NDDs patients obtained from observational studies to assess the risk of HHV infection on NDDs by random effects models or fixed effects models. The Cochran's Q test was used to assess statistical heterogeneity between studies, and I2 statistics were used for quantification. The fixed-effects model of I2 is less than 50% and the random-effects model of I2 is more than 50%. Furthermore, Sensitivity analysis was conducted using the leave-one-out method. Subgroup analysis was performed on detection method, sample collection time, sample type, and geographic area when possible. A combination of a visual inspection of the funnel plot, and the Begg's test (number of studies ≥ 10) was used to investigate the existence and impact of the publication bias. Statistical analyses were conducted using the “meta” package in R version 4.3.0.

Results

MR analysis

In summary, 14 HHV-related GWASs and 3 GWASs of ASD, ADHD, and TS were included. After clumping and excluding weak SNPs with F-statistics < 10, SNPs from 7 HHV-related GWASs were included as IVs. Among these, 12 genetic variants were used as IVs for HSV infection, 4 genetic variants for herpes simplex keratitis and keratoconjunctivitis, 5 genetic variants for HSV genital infection, 14 genetic variants for herpes zoster, 16 genetic variants for EBV infection, 5 variants for unspecified cytomegalovirus diseases, and 11 variants for anti-CMV IgG levels (Table 1).

Table 1 Selection of robust instrumental variables in the GWASs of HHV infections
Full size table

Subsequently, a harmonization process and cofounders searching were implemented. After removal of palindromic SNPs and potential confounders, there were only 1 or 2 IVs associated with HSV keratitis and keratoconjunctivitis, as well as HSV anogenital infection. Therefore, 5 exposures related to HHV infection were finally included. After correction for multiple testing (5 exposures × 3 outcomes = 15 tests), p value was calculated as p = 0.05/15 = 3.3 × 10−3. The harmonized SNPs are provided in Additional file 1: Table S2 and the potential traits of confounders are listed in Additional file 1: Table S3.

Through preliminary MR analysis and sensitivity analysis, some outliers were found by leave-one-out analysis (HSV infection with ASD: rs4716482, rs2004786; zoster with ASD: rs8181185, rs13313427, rs81302; EBV with ASD: rs28529232, rs59257919, rs318497, rs112242506, rs10468923; EBV with TS: rs59257919, rs12358176, rs2618374; CMV infection with ASD: rs61825717; CMV infection with ADHD: rs13156302; CMV infection with TS: rs13156302; CMV IgG with ASD: rs7761068, rs12214648, rs146990284).

We reanalyzed the association after removed these outliers, and the results of IVW analysis were presented in a forest plot (Fig. 3). The detailed summary effect estimates for relationships between IVs and outcomes using all MR methods are provided in Table 2. All MR methods indicate no significant causal relationship between HSV, VZV, EBV, and CMV infections and ASD, ADHD, and TS.

Fig. 3
figure 3

Forest plot of inverse-variance weighted analyses for the associations between five HHV-related exposures and ASD, ADHD, and TS. P < 0.05 is considered suggestively causal significant. nsnp: number of single-nucleotide polymorphism; OR: odd ratio; CI: confidence interval

Full size image
Table 2 Effect estimates for association of HHV infections with ASD, ADHD, and TS by MR
Full size table

Cochrane's Q test and MR-PRESSO method indicated no heterogeneity (p > 0.05). Potential SNP directional pleiotropy was also not detected by MR-Egger regression analysis (intercept p > 0.05) (Table 2). Least-one-out sensitivity analysis results suggested that the associations were not apparently driven by any single SNP. The visualization of MR analyses including scatter plots, leave-one-out plots, and funnel plots are presented in Additional file 2: Figure S1-S5.

Systematic review with meta-analysis

A total of 1122 studies were identified from five databases, and 221 duplicate studies were removed. After screening the titles and abstract, 850 studies were excluded. Subsequently, after reviewing the full texts of the remaining studies, 27 eligible studies were included in the review (Fig. 2).

The included studies comprised 25 case–control studies (57 datasets) and 2 retrospective cohort studies. The case–control studies involved 2,024 cases with NDD and 10,759 controls, while the cohort studies included 202 cases of HHV infection and 566 controls without HHV infection. Of all included studies, 13 were from Europe, 10 from Asia, 3 from America, and 1 from Africa. HHV infection detection were assessed by antibodies (13 studies) using enzyme-linked immunosorbent assay (ELISA)/chemiluminescence immunoassay (CILA)/Enzyme immunoassays (EIA) and DNA (14 studies) using polymerase chain reaction (PCR). The samples analyzed included serum, whole blood, white blood cells, dried blood spot (DBS), urine and brain slices. DBS samples were collected within the first postnatal week of the enrolled population, and brain slices were obtained from postmortem brain tissues. More detailed information was provided in Table 3.

Table 3 Characteristics of the included studies
Full size table

We performed separate meta-analyses based on subfamilies of HHV. The results were listed in Table 4 and the forest plots, leave-one-out plots and funnel plots were provided in Additional file 3. The pooled estimates found that a higher proportion of ASD experienced CMV infection and HHV-6 infection when comparing with non-ASD (CMV-pOR: 2.66, 95% CI 1.15–6.15, I2 = 66%; HHV-6-pOR: 3.93, 95% CI 2.39–6.45, I2 = 19%) (Additional file 3: Figure S3/S6). The relative risk of EBV infection and CMV infection were significantly increased in Chinese TD populations (EBV-pOR: 8.48, 95% CI 3.51–20.50, I2 = 0%; CMV-pOR: 14.16, 95% CI 2.88–69.61, I2 = 83%) (Additional file 3: Figure S8/S9). A potential association between EBV infection and ASD was revealed by pOR 2.19 (95% CI 0.80–5.99; I2 = 77%) (Additional file 3: Figure S2). HSV infection and HHV-7 infection was not significantly associated with ASD (HSV-pOR: 1.83, 95%CI 0.57–5.84, I2 = 74%; HHV-7-pOR: 1.87, 95%CI 0.08–41.34, I2 = 74%) (Additional file 3: Figure S1/S7), CMV infection was also not significantly associated with ADHD (OR: 14.12, 95%CI 0.04–4727.02; I2 = 96%) (Additional file 3: Figure S10). However, in the retrospective cohort studies, the cCMV infection group showed no significant increase in the probability of ASD (OR: 4.61, 95% CI 0.46–46.08; I2 = 69%) and ADHD (OR: 0.59, 95% CI 0.17–2.05; I2 = 0%) comparing with control group (Additional file 3: Figure S11/S12).

Table 4 Meta-analysis and subgroup analysis of association between NDDs and HHVs
Full size table

The subgroup analyses stratified by continent, detection indicators, sample sources and collection time were performed, as shown in Table 3 and Additional file 3. CMV infection detected using DBS in the postnatal first week had a significant association with ASD (OR: 9.84, 95% CI 2.97–32.54, I2 = 0%) (Additional file 3: Figure S4/S5). Regarding detection indicators, a higher proportion of ASD patients was found EBV-DNA positive (OR: 5.88, 95% CI 2.98–11.59, I2 = 0%) and CMV-DNA positive (OR: 3.96, 95% CI 1.34–11.74, I2 = 56%) (Additional file 3: Figure S2/S4). An increased risk of TD was also observed in CMV-DNA positive patients (OR: 15.69, 95% CI 5.53–44.54, I2 = 0%) (Additional file 3: Figure S8). The risk of ASD in EBV or CMV positive patients did not significantly increase in either America or Europe, whereas an increased proportion of ASD patients experienced CMV infection in Asia (pOR: 5.64, 95% CI 1.05–30.24, I2 = 84%) (Additional file 3: Figure S5) and HHV-6 infection in America (pOR: 4.44, 95% CI 1.45–13.56, I2 = 0%) (Additional file 3: Figure S6).

Discussion

This study employed a two-sample MR analysis to investigate the association between HHVs and ASD, ADHD, and TS. We included HSV, VZV, EBV, and CMV-related SNPs as IVs after removing weak SNPs in MR analysis and no association was found between these HHVs infection and risk of ASD, ADHD, and TS. According to meta-analysis, ASD patients had a greater proportion of CMV and HHV-6 infection than non-ASDs. The relative risk of EBV and CMV infection was much higher in Chinese TD populations.

Previous studies have proposed an association between viral infections and ASD, yet the precise mechanisms remain unclear and may involve several possibilities: direct infection of the CNS, infection in peripheral sites triggering CNS-related conditions, or modulation of immune responses affecting ASD [15]. Viruses can damage neurons through cell lysis or inducing apoptosis. Activation of the immune system after viral infections can also affect neurons through inflammatory responses, release of free radicals, imbalance in cytokines, and production of autoantibodies [69]. Neurobehavioral disorders, including ASD, are associated with structural and functional deficits in CNS neurons [70].

Our results did not find that HSV or VZV infections increase the risk of ASD. HSV infection in early embryonic development HSV has been proposed to activate the immune system and induce inflammatory responses, leading to abnormal growth in the cerebral cortex, which commonly observed in children with ASD [71]. However, due to the low incidence of congenital HSV infection and the limited sample size of the study, the detection rate of HSV DNA was 0 in both the ASD and control groups [47, 48]. For HSV infection, regardless of the time of infection, there was significant heterogeneity among different studies. This variability could be influenced by factors such as ethnicity, region, detection methods, and social factors. VZV is also a neurotropic virus associated with CNS inflammation and CNS diseases like multiple sclerosis, shares some pathological features with ASD [72]; however, evidence supporting its direct involvement in ASD pathogenesis remains scarce. Only a small-scale case–control study has indicated a higher VZV antibodies seropositivity among children with ASD compared to controls [50]. Future research with larger sample sizes is needed to further explore the potential correlation.

CMV has the potential to invade the CNS at any stage of neural development, provoke inflammation by inhibiting host antiviral defenses such as interferon, and elicit local infiltration of macrophages and T cells at infection sites, thereby altering immune function and causing developmental anomalies in specific brain regions or structures, potentially contributing to ASD [73]. The subgroup analysis revealed that CMV infection detected from DBS collected within one week after birth was significantly associated ASD. The detection of CMV infection in older children showed no significant correlation with ASD. This is because most studies detect CMV antibodies, which may include postnatal or asymptomatic infections that do not affect neurodevelopment. It indicates that congenital or perinatal CMV infection is a high-risk factor for ASD. This finding is consistent with the results of a systematic review published in 2017 on cCMV infection and ASD. In addition to the direct damage to the brain caused by cCMV, the immune response following maternal CMV infection during pregnancy can also affect the fetal nervous system [74]. However, MR analysis found no evidence between ASD and CMV. A recent MR study based on another European population GWAS also failed to establish a significant association between CMV infection and ASD [75]. It appears that CMV and ASD share no common genetic susceptibility based on current data. CMV infection may correlate with ASD through complicated immune responses.

There is limited research investigating the roles of EBV in the pathogenesis of ASD. Combining the results from the current observational studies, it was found that EBV infection may be associated with ASD. Sensitivity analysis revealed that removing the study by Ivan et al. [52] resulted in significant correlation, suggesting that this study is one source of heterogeneity. This may be due to the use of CLIA technology for detecting EBV antibodies, which generally has higher sensitivity compared to methods like ELISA. Additionally, subgroup analysis showed that congenital or perinatal EBV infection is significantly associated with ASD. This suggests that, similar to CMV, EBV may be involved in ASD-related neural damage or immune responses during early embryonic development. Future research is warranted to explore the mechanisms by which congenital EBV infection affects children's neurodevelopment.

HHV-6 and HHV-7 are common pathogens causing exanthema subitum in infants and can also lead to febrile seizures and encephalitis [76]. HHV-8 is the causative agent of Kaposi's sarcoma [77]. Our results suggest that more patients with ASD had HHV-6 infection when comparing with non-ASD control group. Although there are currently no studies on the mechanism by which HHV-6 associating with ASD, it is known that HHV-6 can enter the CNS through the nasopharynx and olfactory pathways, infecting various neural cells [78]. Additionally, HHV-6 is usually acquired between 6 and 15 months of age, suggesting its potential role in children's neurodevelopment [79]. A comprehensive understanding of HHV-6 and its relationship with ASD in the future will help elucidate why HHV-6 increases the risk of ASD. Moreover, research on the association between HHV-7/8 infections and ASD is limited and seems to show no significant correlation. Further studies with large sample sizes or multicenter approaches are needed.

In comparison to ASD, research concerning ADHD is relatively sparse. Currently, the prevailing pathogenesis of ADHD includes autoimmune and viral infection hypotheses. It was speculated that lentiviral particles may lay dormant within the CNS, with viral proteins potentially translated upon exposure to exogenous antigens and other stimuli, causing immune response dysregulation [80]. Human CMV may influence the pathogenesis of ADHD by regulating glutamate uptake and transporter expression in astrocytes [81]. However, a retrospective study conducted in an Asian population failed to observe a significant increase in subsequent ADHD incidence among individuals with CMV infection [58]. Similarly, in the Turkish population, no statistical differences were noted in serum IgG levels of HSV-1, VZV, EBV and CMV between ADHD patients and healthy children [17]. In addition, research into HSV-1 susceptibility genes did not reveal an accumulation in ADHD cases [82], indirectly suggesting minimal influence of HSV on ADHD incidence. In a Greek birth cohort study, HSV-1/2, EBV, and CMV infection were not associated with elevated ADHD test scores [83]. Nonetheless, a notable disparity persisted between simply increased ADHD test scores and clinical ADHD diagnoses, underscoring the need for further follow-up investigations to bolster these findings.

In terms of TD, its etiology remains elusive, with a potential involvement of genetic, immune, psychological, and environmental factors [84]. While viral infections are mostly associated with immune responses, the ‘kindling hypothesis’ has been proposed by some researchers, suggesting that infections may trigger sustained hypersensitivity reactions, leading to tic symptoms due to immune imbalance [85]. Antibodies or T cells produced after viral infections may also cross-react with autoantigens, exacerbating tic symptoms through an autoimmune response [86]. Furthermore, acute and chronic infection could increase the level of various pro-inflammatory cells [87], directly or indirectly activate the metabolism and decomposition of tryptophan in the CNS via pro-inflammatory cytokines, thereby affecting the neurotransmitter balance in the brain and contributing to tic symptoms [88]. Additionally, post-infection defects in T-regulatory cells leading to diminished autologous reactive lymphocyte capacity, potentially elucidating diverse tic symptoms observed in certain TS patients [89].

Despite these insights, limited attention has been given to exploring the association between HHVs and TD around the world. A case report mentioned that a girl without any history of neuropsychiatric illness appeared multiple motor and vocal tics one month following herpetic encephalitis [90]. Another case report documented an association between recurrent HSV-1 infection and exacerbation of tic symptoms in children with TS [91]. Several studies in China have found that EBV and CMV infection significantly correlated with TD (Table 3), potentially due to immune system dysregulation triggered by these infections. Given the constraints of single regional reports and small sample sizes, general conclusion cannot be drawn from the meta-analysis of all Chinese studies. In light of our MR analysis results, we have not found a direct association between HHVs infection and the risk of TS based on European population, the potential role of viral infection in initiating and/or exacerbating TS symptoms cannot be dismissed, which requires further research.

In spite of the high prevalence of HHV infection in the population, unlike influenza, most infections are asymptomatic or latent. Nonetheless, silent viral infections can still induce immune responses, potentially leading to NDDs [15]. Asymptomatic infections possess the capability to reactivate at any point in life [92], and studies based on subjective reported infections may result in either overestimation or underestimation of infection cases. Furthermore, children included in studies may not exhibit strong immune responses to HHVs present in their bodies, leading to false negatives due to low antibody levels or false positives owing to variations in detection sensitivity. Even with viral DNA detection, challenges persist regarding low detection rates in blood samples [48]. Additionally, some previous studies were observational, prone to bias in participant selection and outcome assessment blinding. The limited number of studies included in the meta-analysis makes it challenging to identify the sources of publication bias. Visually, the funnel plot for CMV and ASD appears asymmetrical; however, statistical tests of the funnel plot suggest the absence of publication bias (Rank correlation on funnel plot asymmetry: z-score = 0.70, p = 0.484 > 0.05). It is important to note that these statistical tests often have low power, meaning that even if the statistical results do not provide evidence of asymmetry, the possibility of bias cannot be entirely ruled out [93]. Besides, most observational studies involved cases with multiple viral co-infections, complicating the interpretation of causality and potentially leading to false-positive results.

Our MR analysis also has some limitations. Firstly, the data used in this study are from European populations, thus limiting the generalizability of conclusions globally due to disparities in HHV infection rates across regions. Future MR analyses in diverse populations are still needed. Secondly, although IVs were derived from recent large-scale GWAS studies, the final analysis included fewer strongly correlated variables, leading to the adoption of lenient thresholds. Moreover, a greater number of weak IVs related to viral infections, particularly antibody levels, were not included in the MR analysis under stringent criteria (F > 10). More robust IVs are needed to supplement the research in the future. Thirdly, genetic variants of outcomes were extracted from publicly available summary data from the PGC, where missing EAF values in NDDs preclude the supplementation of EAF values from normal populations. Consequently, reverse MR analysis or MR Steiger analysis cannot be conducted, leaving room for exploration of the directionality between exposure and outcome.

Conclusions

Our results offer evidence that HSV, VZV, EBV, and CMV infections do not directly increase the risk of ASD, ADHD, and TS through two-sample MR analyses. HHV-6 infection and cCMV infection were associated with an increased risk of ASD based on the results of meta-analysis. These findings, along with previous published studies, highlight the complexity of viral infections in childhood NDDs. To further investigate the contribution of HHV infections to the risk of ASD, ADHD, and TD, larger population studies, comprehensive data of HHV infections, and more robust analyses are warranted.

Data availability

The majority of data presented in the study are included in the article and supplemental files, the sources of original datasets are presented in the Methods and R codes used and/or analyzed are available from the corresponding author on reasonable request.

Abbreviations

NDDs:

Neurodevelopmental disorders

CNS:

Central nervous system

ASD:

Autism spectrum disorder

ADHD:

Attention deficit hyperactivity disorder

TS:

Tourette syndrome

HHVs:

Human herpesviruses

HSV:

Herpes simplex virus

VZV:

Varicella-zoster virus

CMV:

Cytomegalovirus

EBV:

Epstein-Barr virus

MR:

Mendelian randomization

IVs:

Instrumental variables

GWAS:

Genome-wide association studies

SNPs:

Single nucleotide polymorphisms

IVW:

Inverse-variance weighted

PRISMA:

Preferred Reporting Items for Systematic reviews and Meta-Analyses

DSM:

Diagnostic and statistical manual of mental disorders

ICD:

International Classification of Diseases

NOS:

Newcastle-Ottawa Rating Scale

ELISA:

Enzyme-linked immunosorbent assay

CILA:

Chemiluminescence immunoassay

EIA:

Enzyme immunoassays

PCR:

Polymerase chain reaction

DBS:

Dried blood spot

References

  1. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders: Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision. Arlington: American Psychiatric Association; 2022.

    Book  Google Scholar 

  2. World Health Organization. International statistical classification of diseases and related health problems. 11th ed. (ICD-11): World Health Organization; 2021.

  3. Hirota T, King BH. Autism spectrum disorder: a review. JAMA. 2023;329(2):157–68.

    Article  CAS  PubMed  Google Scholar 

  4. Maenner MJ, Warren Z, Williams AR, Amoakohene E, Bakian AV, Bilder DA, et al. Prevalence and characteristics of autism spectrum disorder among children aged 8 years - autism and developmental disabilities monitoring network, 11 sites, United States, 2020. Morbid Mortal Wkly Rep Surveill Summaries (Washington, DC: 2002). 2023;72(2):1–14.

    Google Scholar 

  5. Salari N, Ghasemi H, Abdoli N, Rahmani A, Shiri MH, Hashemian AH, et al. The global prevalence of ADHD in children and adolescents: a systematic review and meta-analysis. Ital J Pediatr. 2023;49(1):48.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Johnson KA, Worbe Y, Foote KD, Butson CR, Gunduz A, Okun MS. Tourette syndrome: clinical features, pathophysiology, and treatment. Lancet Neurol. 2023;22(2):147–58.

    Article  PubMed  Google Scholar 

  7. Thapar A, Cooper M, Rutter M. Neurodevelopmental disorders. Lancet Psych. 2017;4(4):339–46.

    Article  Google Scholar 

  8. Whiteford HA, Degenhardt L, Rehm J, Baxter AJ, Ferrari AJ, Erskine HE, et al. Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010. Lancet (London, England). 2013;382(9904):1575–86.

    Article  PubMed  Google Scholar 

  9. Spann MN, Sourander A, Surcel HM, Hinkka-Yli-Salomäki S, Brown AS. Prenatal toxoplasmosis antibody and childhood autism. Autism Res. 2017;10(5):769–77.

    Article  PubMed  Google Scholar 

  10. Knuesel I, Chicha L, Britschgi M, Schobel SA, Bodmer M, Hellings JA, et al. Maternal immune activation and abnormal brain development across CNS disorders. Nat Rev Neurol. 2014;10(11):643–60.

    Article  CAS  PubMed  Google Scholar 

  11. Ibi D, Yamada K. Therapeutic targets for neurodevelopmental disorders emerging from animal models with perinatal immune activation. Int J Mol Sci. 2015;16(12):28218–29.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Atladóttir HO, Thorsen P, Schendel DE, Østergaard L, Lemcke S, Parner ET. Association of hospitalization for infection in childhood with diagnosis of autism spectrum disorders: a Danish cohort study. Arch Pediatr Adolesc Med. 2010;164(5):470–7.

    Article  PubMed  Google Scholar 

  13. Atladóttir HO, Thorsen P, Østergaard L, Schendel DE, Lemcke S, Abdallah M, et al. Maternal infection requiring hospitalization during pregnancy and autism spectrum disorders. J Autism Dev Disord. 2010;40(12):1423–30.

    Article  PubMed  Google Scholar 

  14. Libbey JE, Sweeten TL, McMahon WM, Fujinami RS. Autistic disorder and viral infections. J Neurovirol. 2005;11(1):1–10.

    Article  PubMed  Google Scholar 

  15. Shuid AN, Jayusman PA, Shuid N, Ismail J, Kamal Nor N, Mohamed IN. Association between viral infections and risk of autistic disorder: an overview. Int J Environ Res Public Health. 2021;18(6):2817.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Al-Beltagi M, Saeed NK, Elbeltagi R, Bediwy AS, Aftab SAS, Alhawamdeh R. Viruses and autism: A Bi-mutual cause and effect. World J Virol. 2023;12(3):172–92.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Bekdas M, Tufan AE, Hakyemez IN, Tas T, Altunhan H, Demircioglu F, et al. Subclinical immune reactions to viral infections may correlate with child and adolescent diagnosis of attention-deficit/hyperactivity disorder: a preliminary study from Turkey. Afr Health Sci. 2014;14(2):439–45.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Ginsberg Y, D’Onofrio BM, Rickert ME, Class QA, Rosenqvist MA, Almqvist C, et al. Maternal infection requiring hospitalization during pregnancy and attention-deficit hyperactivity disorder in offspring: a quasi-experimental family-based study. J Child Psychol Psychiatry. 2019;60(2):160–8.

    Article  PubMed  Google Scholar 

  19. Tsai CS, Yang YH, Huang KY, Lee Y, McIntyre RS, Chen VC. Association of tic disorders and enterovirus infection: a nationwide population-based study. Medicine. 2016;95(15):e3347.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Kattner AA. What makes tics tick? Insights into Tourette syndrome. Biomed J. 2022;45(2):219–26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Dreyfus DH. Herpesviruses and the microbiome. J Allergy Clin Immunol. 2013;132(6):1278–86.

    Article  CAS  PubMed  Google Scholar 

  22. James C, Harfouche M, Welton NJ, Turner KM, Abu-Raddad LJ, Gottlieb SL, et al. Herpes simplex virus: global infection prevalence and incidence estimates, 2016. Bull World Health Organ. 2020;98(5):315–29.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Huang J, Wu Y, Wang M, Jiang J, Zhu Y, Kumar R, et al. The global disease burden of varicella-zoster virus infection from 1990 to 2019. J Med Virol. 2022;94(6):2736–46.

    Article  CAS  PubMed  Google Scholar 

  24. Zuhair M, Smit GSA, Wallis G, Jabbar F, Smith C, Devleesschauwer B, et al. Estimation of the worldwide seroprevalence of cytomegalovirus: A systematic review and meta-analysis. Rev Med Virol. 2019;29(3):e2034.

    Article  PubMed  Google Scholar 

  25. Kenneson A, Cannon MJ. Review and meta-analysis of the epidemiology of congenital cytomegalovirus (CMV) infection. Rev Med Virol. 2007;17(4):253–76.

    Article  PubMed  Google Scholar 

  26. Nowalk A, Green M. Epstein-barr virus. Microbiol Spectr. 2016;4(3):10.1128/microbiolspec.DMIH2-0011-2015. https://doiorg.publicaciones.saludcastillayleon.es/10.1128/microbiolspec.DMIH2-0011-2015.

  27. Zerr DM, Meier AS, Selke SS, Frenkel LM, Huang ML, Wald A, et al. A population-based study of primary human herpesvirus 6 infection. N Engl J Med. 2005;352(8):768–76.

    Article  CAS  PubMed  Google Scholar 

  28. Hall CB, Caserta MT, Schnabel KC, McDermott MP, Lofthus GK, Carnahan JA, et al. Characteristics and acquisition of human herpesvirus (HHV) 7 infections in relation to infection with HHV-6. J Infect Dis. 2006;193(8):1063–9.

    Article  PubMed  Google Scholar 

  29. Emdin CA, Khera AV, Kathiresan S. Mendelian Randomization. JAMA. 2017;318(19):1925–6.

    Article  PubMed  Google Scholar 

  30. Davies NM, Holmes MV, Davey SG. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ (Clinical research ed). 2018;362:k601.

    Article  PubMed  Google Scholar 

  31. Arsenault BJ. From the garden to the clinic: how Mendelian randomization is shaping up atherosclerotic cardiovascular disease prevention strategies. Eur Heart J. 2022;43(42):4447–9.

    Article  PubMed  Google Scholar 

  32. Visscher PM, Brown MA, McCarthy MI, Yang J. Five years of GWAS discovery. Am J Hum Genet. 2012;90(1):7–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Grove J, Ripke S, Als TD, Mattheisen M, Walters RK, Won H, et al. Identification of common genetic risk variants for autism spectrum disorder. Nat Genet. 2019;51(3):431–44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Demontis D, Walters GB, Athanasiadis G, Walters R, Therrien K, Nielsen TT, et al. Genome-wide analyses of ADHD identify 27 risk loci, refine the genetic architecture and implicate several cognitive domains. Nat Genet. 2023;55(2):198–208.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Yu D, Sul JH, Tsetsos F, Nawaz MS, Huang AY, Zelaya I, et al. Interrogating the genetic determinants of Tourette’s syndrome and other tic disorders through genome-wide association studies. Am J Psychiatry. 2019;176(3):217–27.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Papadimitriou N, Dimou N, Tsilidis KK, Banbury B, Martin RM, Lewis SJ, et al. Physical activity and risks of breast and colorectal cancer: a Mendelian randomisation analysis. Nat Commun. 2020;11(1):597.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Palmer TM, Sterne JA, Harbord RM, Lawlor DA, Sheehan NA, Meng S, et al. Instrumental variable estimation of causal risk ratios and causal odds ratios in Mendelian randomization analyses. Am J Epidemiol. 2011;173(12):1392–403.

    Article  PubMed  Google Scholar 

  38. Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015;44(2):512–25.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Verbanck M, Chen CY, Neale B, Do R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet. 2018;50(5):693–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ (Clinical research ed). 2021;372:n71.

    PubMed  Google Scholar 

  41. Rostom A, Dube C, Cranney A, Saloojee N, Sy R, Garritty C, et al. Celiac disease. Evid Rep Technol Assess (Summ). 2004;104:1–6.

    Google Scholar 

  42. Wells GA, Wells G, Shea B, Shea B, O'Connell D, Peterson J, et al., editors. The Newcastle-Ottawa Scale (NOS) for Assessing the Quality of Nonrandomised Studies in Meta-Analyses 2014.

  43. Mora M, Quintero L, Cardenas R, Suarez-Roca H, Zavala M, Montiel N. Association between HSV-2 infection and serum anti-rat brain antibodies in patients with autism. Invest Clin. 2009;50(3):315–26.

    PubMed  Google Scholar 

  44. Lintas C, Altieri L, Lombardi F, Sacco R, Persico AM. Association of autism with polyomavirus infection in postmortem brains. J Neurovirol. 2010;16(2):141–9.

    Article  CAS  PubMed  Google Scholar 

  45. Lin J, Cai L, Zou S. Etiological analysis of 268 cases of autism in children. Acta Academiae Medicinae Jiangxi. 2010;50(5):100–4.

    Google Scholar 

  46. Gentile I, Zappulo E, Bonavolta R, Maresca R, Riccio MP, Buonomo AR, et al. Prevalence of herpes simplex virus 1 and 2 antibodies in patients with autism spectrum disorders. In vivo (Athens, Greece). 2014;28(4):667–71.

    PubMed  Google Scholar 

  47. Zappulo E, Riccio MP, Binda S, Pellegrinelli L, Pregliasco F, Buonomo AR, et al. Prevalence of HSV1/2 congenital infection assessed through genome detection on dried blood spot in individuals with autism spectrum disorders. In vivo (Athens, Greece). 2018;32(5):1255–8.

    CAS  PubMed  Google Scholar 

  48. Sweeten TL, Croen LA, Windham GC, Odell JD, Stubbs EG, Torres AR. Brief report: low rates of herpesvirus detection in blood of individuals with autism spectrum disorder and controls. J Autism Dev Disord. 2019;49(1):410–4.

    Article  PubMed  Google Scholar 

  49. Maltsev D, Solonko I, Sydorenko O. The assessment of microbial infection in children with autism spectrum disorders and genetic folate cycle deficiency. BMC Pediatr. 2024;24(1):200.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Gentile I, Zappulo E, Bonavolta R, Maresca R, Riccio MP, Buonomo AR, et al. Exposure to Varicella Zoster Virus is higher in children with autism spectrum disorder than in healthy controls. Results from a case-control study. In vivo (Athens, Greece). 2014;28(4):627–31.

    PubMed  Google Scholar 

  51. Gentile I, Zappulo E, Riccio MP, Binda S, Limauro R, Scuccimarra G, et al. No evidence of congenital varicella zoster virus infection assessed through dried blood spot in children with autism spectrum disorders. Futur Virol. 2017;12(7):333–7.

    Article  CAS  Google Scholar 

  52. Gentile I, Zappulo E, Bonavolta R, Maresca R, Messana T, Buonomo AR, et al. Prevalence and titre of antibodies to cytomegalovirus and Epstein-Barr virus in patients with autism spectrum disorder. In vivo (Athens, Greece). 2014;28(4):621–6.

    PubMed  Google Scholar 

  53. Kawashti MI, Amin OR, Rowehy NG. Possible immunological disorders in autism: concomitant autoimmunity and immune tolerance. Egypt J Immunol. 2006;13(1):99–104.

    PubMed  Google Scholar 

  54. Sakamoto A, Moriuchi H, Matsuzaki J, Motoyama K, Moriuchi M. Retrospective diagnosis of congenital cytomegalovirus infection in children with autism spectrum disorder but no other major neurologic deficit. Brain Develop. 2015;37(2):200–5.

    Article  Google Scholar 

  55. Engman ML, Sundin M, Miniscalco C, Westerlund J, Lewensohn-Fuchs I, Gillberg C, et al. Prenatal acquired cytomegalovirus infection should be considered in children with autism. Acta Paediatrica (Oslo, Norway: 1992). 2015;104(8):792–5.

    Article  PubMed  Google Scholar 

  56. Gentile I, Zappulo E, Riccio MP, Binda S, Bubba L, Pellegrinelli L, et al. Prevalence of congenital cytomegalovirus infection assessed through viral genome detection in dried blood spots in children with autism spectrum disorders. In vivo (Athens, Greece). 2017;31(3):467–73.

    CAS  PubMed  Google Scholar 

  57. Korndewal MJ, Oudesluys-Murphy AM, Kroes ACM, van der Sande MAB, de Melker HE, Vossen A. Long-term impairment attributable to congenital cytomegalovirus infection: a retrospective cohort study. Dev Med Child Neurol. 2017;59(12):1261–8.

    Article  PubMed  Google Scholar 

  58. Lin CH, Chou IC, Lee IC, Hong SY. Cytomegalovirus infection in infancy may increase the risk of subsequent epilepsy and autism spectrum disorder in childhood. Children (Basel, Switzerland). 2021;8(11):1040.

    PubMed  Google Scholar 

  59. Hassan ZR, Zekry KM, Heikal EA, Ibrahim HF, Khirala SK, Abd El-Hamid SM, et al. Toxoplasmosis and cytomegalovirus infection and their role in Egyptian autistic children. Parasitol Res. 2023;122(5):1177–87.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Nicolson GL, Gan R, Nicolson NL, Haier J. Evidence for mycoplasma ssp., Chlamydia pneumoniae, and human herpes virus-6 coinfections in the blood of patients with autistic spectrum disorders. J Neurosci Res. 2007;85(5):1143–8.

    Article  CAS  PubMed  Google Scholar 

  61. Gentile I, Zappulo E, Coppola N, Bonavolta R, Portella G, Cernia DS, et al. Prevalence of HHV-6 and HHV-8 antibodies in patients with autism spectrum disorders. In Vivo (Athens, Greece). 2013;27(6):843–9.

    PubMed  Google Scholar 

  62. Chai R, Zhu H, Chai Y, Sun B, Yin G, Liu S, et al. Study on the primary cause of the children with attention deficit hyperactivity disorder. Chin J Behavior Med Sci. 2005;11(5):1–2, 5.

  63. Chen J, Zhao H, Li J, Xie C, Xi Y. Relationship between twitch obstacles disease and pathogenic microorganism infection. Immune Children J Appl Clin Pediatr. 2012;27(19):1536–7.

    Google Scholar 

  64. Chen Y, Zhou K, Qiu H. Relationship between tic disorders in children and infection and immunity. J Chin Phys. 2017;19(1):98–100.

    Google Scholar 

  65. Xu J, Du S, Jia L, Dong Z, Zhao Y, Zhao Z. Correlation between tic disorders in children and infection with pathogenic microorganisms and their immunity. Psychol Mag. 2020;15(11):199.

    Google Scholar 

  66. Kuang G, Jiang Y, He L, Deng P. Human cytomegalovirus infection in children with tic disorders. Chin J Behavior Med Sci. 2001;15(3):201–2.

    Google Scholar 

  67. Kuang G, Jiang Y, Fu P, Zhou C, Xin X. Clinical significance of HCMV-DNA detection and T lymphocyte subgroups in children with tic disorder. Chin J Behavior Med Sci. 2005;14(3):238–9.

    Google Scholar 

  68. Chen Y, Liu G, Lin Q, Chen S, Wang Y, Chen D. Human parvovirus B19 and immune function in children with tic disorder. Chin Mental Health J. 2006;20(4):218–20.

    Google Scholar 

  69. Amor S, Puentes F, Baker D, van der Valk P. Inflammation in neurodegenerative diseases. Immunology. 2010;129(2):154–69.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Karim S, Mirza Z, Kamal MA, Abuzenadah AM, Azhar EI, Al-Qahtani MH, et al. The role of viruses in neurodegenerative and neurobehavioral diseases. CNS Neurol Disord: Drug Targets. 2014;13(7):1213–23.

    Article  CAS  PubMed  Google Scholar 

  71. Ganguli S, Chavali PL. Intrauterine viral infections: impact of inflammation on fetal neurodevelopment. Front Neurosci. 2021;15:771557.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Zerboni L, Reichelt M, Arvin A. Varicella-zoster virus neurotropism in SCID mouse-human dorsal root ganglia xenografts. Curr Top Microbiol Immunol. 2010;342:255–76.

    CAS  PubMed  Google Scholar 

  73. Schottstedt V, Blümel J, Burger R, Drosten C, Gröner A, Gürtler L, et al. Human Cytomegalovirus (HCMV) - Revised. Transfusion Med Hemother: offizielles Organ der Deutschen Gesellschaft fur Transfusionsmedizin und Immunhamatologie. 2010;37(6):365–75.

    Article  Google Scholar 

  74. Slawinski BL, Talge N, Ingersoll B, Smith A, Glazier A, Kerver J, et al. Maternal cytomegalovirus sero-positivity and autism symptoms in children. Am J Reprod Immunol New York, NY: 1989. 2018;79(5):e12840.

    Article  Google Scholar 

  75. Zhang M, Ming Y, Du Y, Xin Z. Two-sample Mendelian randomization study does not reveal a significant relationship between cytomegalovirus (CMV) infection and autism spectrum disorder. BMC Psychiatry. 2023;23(1):559.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Agut H, Bonnafous P, Gautheret-Dejean A. Human herpesviruses 6A, 6B, and 7. Microbiol Spectr. 2016;4(3):10.1128/microbiolspec.DMIH2-0007-2015. https://doiorg.publicaciones.saludcastillayleon.es/10.1128/microbiolspec.DMIH2-0007-2015.

  77. Hengge UR, Ruzicka T, Tyring SK, Stuschke M, Roggendorf M, Schwartz RA, et al. Update on Kaposi’s sarcoma and other HHV8 associated diseases. Part 1: epidemiology, environmental predispositions, clinical manifestations, and therapy. Lancet Infect Dis. 2002;2(5):281–92.

    Article  PubMed  Google Scholar 

  78. Harberts E, Yao K, Wohler JE, Maric D, Ohayon J, Henkin R, et al. Human herpesvirus-6 entry into the central nervous system through the olfactory pathway. Proc Natl Acad Sci USA. 2011;108(33):13734–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. De Bolle L, Naesens L, De Clercq E. Update on human herpesvirus 6 biology, clinical features, and therapy. Clin Microbiol Rev. 2005;18(1):217–45.

    Article  PubMed  PubMed Central  Google Scholar 

  80. Zhou R, Xia Q, Shen H, Yang X, Zhang Y, Xu J. Diagnosis of children’s attention deficit hyperactivity disorder (ADHD) and its association with cytomegalovirus infection with ADHD: a historical review. Int J Clin Exp Med. 2015;8(8):13969–75.

    PubMed  PubMed Central  Google Scholar 

  81. Zhang L, Li L, Wang B, Qian DM, Song XX, Hu M. HCMV induces dysregulation of glutamate uptake and transporter expression in human fetal astrocytes. Neurochem Res. 2014;39(12):2407–18.

    Article  CAS  PubMed  Google Scholar 

  82. Carter CJ. Susceptibility genes are enriched in those of the herpes simplex virus 1/host interactome in psychiatric and neurological disorders. Pathogens Dis. 2013;69(3):240–61.

    Article  CAS  Google Scholar 

  83. Karachaliou M, Chatzi L, Roumeliotaki T, Kampouri M, Kyriklaki A, Koutra K, et al. Common infections with polyomaviruses and herpesviruses and neuropsychological development at 4 years of age, the Rhea birth cohort in Crete, Greece. J Child Psychol Psychiatry. 2016;57(11):1268–76.

    Article  PubMed  Google Scholar 

  84. Jiang J, Chen M, Huang H, Chen Y. The Aetiology of tourette syndrome and chronic tic disorder in children and adolescents: a comprehensive systematic review of case-control studies. Brain Sci. 2022;12(9):1202.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Krause DL, Müller N. The relationship between Tourette’s syndrome and infections. Open Neurol J. 2012;6:124–8.

    Article  PubMed  PubMed Central  Google Scholar 

  86. Hoekstra PJ, Manson WL, Steenhuis MP, Kallenberg CG, Minderaa RB. Association of common cold with exacerbations in pediatric but not adult patients with tic disorder: a prospective longitudinal study. J Child Adolesc Psychopharmacol. 2005;15(2):285–92.

    Article  PubMed  Google Scholar 

  87. Hoekstra PJ, Anderson GM, Limburg PC, Korf J, Kallenberg CG, Minderaa RB. Neurobiology and neuroimmunology of Tourette’s syndrome: an update. Cell Mol Life Sci: CMLS. 2004;61(7–8):886–98.

    CAS  PubMed  PubMed Central  Google Scholar 

  88. Behen M, Chugani HT, Juhász C, Helder E, Ho A, Maqbool M, et al. Abnormal brain tryptophan metabolism and clinical correlates in Tourette syndrome. Movement Disord: 2007;22(15):2256–62.

    Article  PubMed  Google Scholar 

  89. Kawikova I, Leckman JF, Kronig H, Katsovich L, Bessen DE, Ghebremichael M, et al. Decreased numbers of regulatory T cells suggest impaired immune tolerance in children with tourette syndrome: a preliminary study. Biol Psychiat. 2007;61(3):273–8.

    Article  CAS  PubMed  Google Scholar 

  90. Northam RS, Singer HS. Postencephalitic acquired Tourette-like syndrome in a child. Neurology. 1991;41(4):592–3.

    Article  CAS  PubMed  Google Scholar 

  91. Budman CL, Kerjakovic M, Bruun RD. Viral infection and tic exacerbation. J Am Acad Child Adolesc Psychiatry. 1997;36(2):162.

    Article  CAS  PubMed  Google Scholar 

  92. Lee SM, Mitchell R, Knight JA, Mazzulli T, Relton C, KhodayariMoez E, et al. Early-childhood cytomegalovirus infection and children’s neurocognitive development. Int J Epidemiol. 2021;50(2):538–49.

    Article  PubMed  Google Scholar 

  93. Sterne JA, Sutton AJ, Ioannidis JP, Terrin N, Jones DR, Lau J, et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ (Clinical research ed). 2011;343:d4002.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We thank all the GWASs for making the summary data accessible, and we thank all the researchers and participants who contributed to those studies.

Funding

Not applicable.

Author information

Author notes

  1. Liwei Fang, Zuojun Wang and Jingyi Zhao contributed equally to this work and share the first authorship.

Authors and Affiliations

  1. Pediatric Neurorehabilitation Center, Pediatric Department, The First Affiliated Hospital of Anhui Medical University, Hefei, China

    Liwei Fang, Zuojun Wang, Jingyi Zhao, Xun Wu, Shunxin Wang & De Wu

  2. Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People’s Republic of China, Hefei, Anhui, China

    Hui Gao

Authors
  1. Liwei Fang
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Zuojun Wang
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Jingyi Zhao
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Xun Wu
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Shunxin Wang
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Hui Gao
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. De Wu
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

DW proposed the study concept and revised the manuscript; HG designed the protocol for the systematic review and meta-analysis; LF contributed to the study design, performed the Mendelian Randomization analysis and meta-analysis, and was the primary contributor to the manuscript writing; ZW participated in the literature search and analysis for the systematic review and meta-analysis and contributed to writing the section on tic disorders; JZ contributed to the literature search and writing of the ADHD section; XW and SW participated in the literature search and meta-analysis. All authors read and approved the final submitted version of manuscript.

Corresponding authors

Correspondence to Hui Gao or De Wu.

Ethics declarations

Ethics approval and consent to participate

The data used in this study are publicly available from previous studies with relevant participant consent and ethical approval.

Competing interests

The authors declare that there is no conflict of interest.

Consent for publication

Not applicable.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fang, L., Wang, Z., Zhao, J. et al. Association between human herpesviruses infections and childhood neurodevelopmental disorders: insights from two-sample mendelian randomization analyses and systematic review with meta-analysis. Ital J Pediatr 50, 248 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13052-024-01820-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13052-024-01820-9

Keywords

Italian Journal of Pediatrics

ISSN: 1824-7288

Contact us