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Causality between ADHD, ASD, and CVDs: A Two-Step, Two-Sample Mendelian Randomization Investigation

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Title: Causality between ADHD, ASD, and CVDs: A Two-Step, Two-Sample Mendelian Randomization Investigation
Language: English
Authors: Zequn Zheng, Dihui Cai (ORCID 0000-0002-8153-3647)
Source: Journal of Attention Disorders. 2025 29(1):3-13.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 11
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Descriptors: Attention Deficit Hyperactivity Disorder, Autism Spectrum Disorders, Heart Disorders, Correlation, Risk, Probability, Genetic Disorders, Physical Health, Educational Attainment, Smoking, Income, Obesity, Drug Use
DOI: 10.1177/10870547241288741
ISSN: 1087-0547
1557-1246
Abstract: Background: While observational studies have established a connection between attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and heightened risk for cardiovascular diseases (CVD), the causal relationships are not well-defined. This study is designed to examine the causality between ASD, ADHD, and CVD risk as well as investigate the mediating factors through which ADHD and ASD influence CVD. Methods and Results: Leveraging two-sample Mendelian randomization (MR) approaches and large scale GWAS summary stats, we examined underlying causal links between ASD and ADHD and the risk of CVDs. The analysis indicated that ADHD was related to an increased likelihood of developing coronary heart disease (OR [95% CI] 1.12 [1.03, 1.21], p = 0.008), heart failure (OR [95% CI] 1.14 [1.07, 1.22], p = 1.45 × 10-4), and large-artery stroke (OR [95% CI] 1.35 [1.09, 1.66], p = 0.005). In parallel, ASD showed a correlation with a greater atrial fibrillation risk (OR [95% CI] 1.09 [1.03, 1.16], p = 0.005] and heart failure (OR [95% CI] 1.11 [1.04, 1.19], p = 0.004). Additionally, we explored the mediating role of CVD risk factors through two-step MR and multivariable MR, highlighting the possible role of smoking, prescription opioid use, triglycerides, education, income, Townsend deprivation index, and obesity in the causal association of ADHD, ASD, on CVDs. Conclusion: This MR study highlights the necessity for rigorous cardiovascular surveillance and interventions to decrease adverse cardiovascular events in people with ADHD or ASD by preventing identified mediating risk factors.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1450545
Database: ERIC
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  Value: <anid>AN0181053483;gs001jan.25;2024Nov26.02:25;v2.2.500</anid> <title id="AN0181053483-1">Causality Between ADHD, ASD, and CVDs: A Two-Step, Two-Sample Mendelian Randomization Investigation </title> <p>Background: While observational studies have established a connection between attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and heightened risk for cardiovascular diseases (CVD), the causal relationships are not well-defined. This study is designed to examine the causality between ASD, ADHD, and CVD risk as well as investigate the mediating factors through which ADHD and ASD influence CVD. Methods and Results: Leveraging two-sample Mendelian randomization (MR) approaches and large scale GWAS summary stats, we examined underlying causal links between ASD and ADHD and the risk of CVDs. The analysis indicated that ADHD was related to an increased likelihood of developing coronary heart disease (OR [95% CI] 1.12 [1.03, 1.21], p =.008), heart failure (OR [95% CI] 1.14 [1.07, 1.22], p = 1.45 × 10<sup>−4</sup>), and large-artery stroke (OR [95% CI] 1.35 [1.09, 1.66], p =.005). In parallel, ASD showed a correlation with a greater atrial fibrillation risk (OR [95% CI] 1.09 [1.03, 1.16], p =.005] and heart failure (OR [95% CI] 1.11 [1.04, 1.19], p =.004). Additionally, we explored the mediating role of CVD risk factors through two-step MR and multivariable MR, highlighting the possible role of smoking, prescription opioid use, triglycerides, education, income, Townsend deprivation index, and obesity in the causal association of ADHD, ASD, on CVDs. Conclusion: This MR study highlights the necessity for rigorous cardiovascular surveillance and interventions to decrease adverse cardiovascular events in people with ADHD or ASD by preventing identified mediating risk factors.</p> <p>Keywords: cardiovascular disease; Mendelian randomization; autism spectrum disorder; causality; ADHD</p> <hd id="AN0181053483-2">Introduction</hd> <p>Cardiovascular diseases (CVDs), a group of conditions that affect blood vessels and the heart, persist as the foremost cause of global morbidity and mortality. The escalating health and economic burdens associated with CVDs are particularly pronounced due to the aging population ([<reflink idref="bib29" id="ref1">29</reflink>]). While smoking, diabetes, hypertension, obesity, and hyperlipidemia are known risk factors ([<reflink idref="bib31" id="ref2">31</reflink>]), recent observational studies posit certain psychiatric traits as potential contributors to CVD risk ([<reflink idref="bib1" id="ref3">1</reflink>]; [<reflink idref="bib27" id="ref4">27</reflink>]).</p> <p>Attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), neurodevelopmental conditions manifesting in childhood and often extending into adulthood, have garnered attention ([<reflink idref="bib14" id="ref5">14</reflink>]; [<reflink idref="bib35" id="ref6">35</reflink>]). Emerging evidence suggests that people with ASD or ADHD have higher rates of CVDs and the risk factors linked to them ([<reflink idref="bib11" id="ref7">11</reflink>]; [<reflink idref="bib23" id="ref8">23</reflink>]). A meta-analysis including 11 studies indicates that ADHD is associated with increased risk for CVDs ([<reflink idref="bib23" id="ref9">23</reflink>]). A review suggested that ADHD increased the CVD risk factors, such as substance use, sleep measures, socioeconomic factors, and obesity ([<reflink idref="bib30" id="ref10">30</reflink>]). The associations of ADHD and CVD were no longer significant after adjusting for educational attainment, and lifestyle factors ([<reflink idref="bib12" id="ref11">12</reflink>]). A Mendelian randomization (MR) study also showed that ADHD is causally associated with socioeconomic factors, such as education, income, and Townsend deprivation index (TDI; [<reflink idref="bib25" id="ref12">25</reflink>]), which is significantly related to CVDs. Notably, a U.S. case-control investigation defined a significant connection between ASD and CVD risk factors ([<reflink idref="bib7" id="ref13">7</reflink>]). A recent MR study also showed that ASD causally associated with CVDs and type 2 diabetes mellitus partially mediated this causal effect ([<reflink idref="bib19" id="ref14">19</reflink>]).</p> <p>To date, no comprehensive MR studies have investigated the mediating factors that link these two conditions to CVD. Identifying such mediators could significantly contribute to the clinical prevention of CVD risk in patients with ADHD and ASD. To delve into the possible causal association between ASD, ADHD, and various CVDs, this study employs MR investigation. MR, a genetic variation-based epidemiological technique with instrumental variables (IVs), mitigates confounding factors inherent in observational studies, bolstering causal inference ([<reflink idref="bib17" id="ref15">17</reflink>]; [<reflink idref="bib32" id="ref16">32</reflink>]). The primary aim of this work is to examine the causal effects of ADHD and ASD on CVDs through MR analysis as well as investigate the mediating factors through which ADHD and ASD influence CVD. This understanding holds promise for informing the development of targeted intervention strategies, crucial for averting cardiovascular adverse events in populations affected by ADHD or ASD.</p> <hd id="AN0181053483-3">Methods</hd> <p></p> <hd id="AN0181053483-4">Study Design</hd> <p>Figure 1 delineates the study design, employing a two-sample MR analysis, mediation analysis, and multivariable MR (MVMR). The main goal was to determine the connection between genetic vulnerability to ASD and ADHD and the risk of various CVDs. Meanwhile, two-step MR and MVMR are used to assess the mediating effect of common risk factors. Utilizing single-nucleotide polymorphisms (SNPs) as IVs in MR analysis, three pivotal assumptions guided the methodological rigor: 1. Ensuring robust SNP-exposure associations; 2. Asserting SNP independence from confounding; 3. Emphasizing SNPs exclusively influencing outcomes through exposure variables ([<reflink idref="bib9" id="ref17">9</reflink>]).</p> <p>Graph: Figure 1. Overview of the study design. Note. ADHD = attention deficit hyperactivity disorder; ASD = autism spectrum disorder; GWAS = genome-wide association studies; MR-PRESSO = MR pleiotropy residual sum and outlier test; IVW = inverse variance weighted; TDI = Townsend deprivation index.</p> <hd id="AN0181053483-5">Dataset Sources</hd> <p>Recent advancements in genome-wide association studies (GWASs) have made available comprehensive summary-level data on ASD ([<reflink idref="bib15" id="ref18">15</reflink>]) and ADHD ([<reflink idref="bib10" id="ref19">10</reflink>]). This study incorporates data from these GWASs, alongside information from the FinnGen database and other relevant studies, to analyze CVDs and factors that may mediate their risk. The CVD outcomes analyzed include heart failure (HF), atrial fibrillation (AF), coronary heart disease (CHD), myocardial infarction (MI), and various types of strokes (including large-artery stroke (LAS), small-vessel stroke (SVS), and cardioembolic stroke (CES)). The study also evaluates intermediary risk factors, which cover a range of lifestyle, biochemical, socioeconomic, and health-related variables, including smoking initiation, prescription opioid use, triglycerides, education, income, TDI, and obesity. Table 1 delineates the summary data pertinent to the exposures, outcomes, and mediating factors involved in this investigation.</p> <p>Table 1. Data Sources.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left">Phenotypes</th><th align="center">Data source</th><th align="center">Phenotypic code</th><th align="center">Cases/controls</th><th align="center">Ancestry</th><th align="center">PMID</th></tr></thead><tbody><tr><td colspan="6">Exposure</td></tr><tr><td> ADHD</td><td>PGC+iPSYCH</td><td>ieu-a-1183</td><td>20,183/35,191</td><td>European</td><td>30478444</td></tr><tr><td> ASD</td><td>PGC+iPSYCH</td><td>ieu-a-1185</td><td>18,381/27,969</td><td>European</td><td>30804558</td></tr><tr><td colspan="6">Outcome</td></tr><tr><td> Myocardial infarction</td><td>CARDIoGRAMplusC4D</td><td>ieu-a-798</td><td>43,676/128,199</td><td>77% European</td><td>26343387</td></tr><tr><td> Heart failure</td><td>HERMES</td><td>ebi-a-GCST009541</td><td>47,309/930,014</td><td>European</td><td>31919418</td></tr><tr><td> Atrial fibrillation</td><td>Nielsen et al</td><td>ebi-a-GCST006414</td><td>60,620/970,216</td><td>European</td><td>30061737</td></tr><tr><td> Coronary heart disease</td><td>CARDIoGRAMplusC4D</td><td>ieu-a-7</td><td>60,801/123,504</td><td>77% European</td><td>26343387</td></tr><tr><td> Large-artery stroke</td><td>MEGASTROKE</td><td>ebi-a-GCST006907</td><td>4,373/406,111</td><td>European</td><td>29531354</td></tr><tr><td> Cardioembolic stroke</td><td>MEGASTROKE</td><td>ebi-a-GCST006910</td><td>7,193/406,111</td><td>European</td><td>29531354</td></tr><tr><td> Small-vessel stroke</td><td>MEGASTROKE</td><td>ebi-a-GCST006909</td><td>5,386/406,111</td><td>European</td><td>29531354</td></tr><tr><td colspan="6">Mediator</td></tr><tr><td> Smoking initiation</td><td>GSCAN</td><td>ieu-b-4877</td><td>311,629/321,173</td><td>European</td><td>30643251</td></tr><tr><td> Prescription opioid use</td><td>FinnGen</td><td>finn-b-RX_CODEINE_TRAMADOL</td><td>28,511/190,281</td><td>European</td><td><ext-link ext-link-type="url" href="https://gwas.mrcieu.ac.uk/datasets/finn-b-RX%5fCODEINE%5fTRAMADOL" /></td></tr><tr><td> Townsend deprivation index</td><td>UK Biobank</td><td>ukb-b-10011</td><td>462,464</td><td>European</td><td><ext-link ext-link-type="url" href="https://gwas.mrcieu.ac.uk/datasets/ukb-b-10011" /></td></tr><tr><td> Obesity</td><td>FinnGen</td><td>finn-b-E4_OBESITY</td><td>8,908/209,827</td><td>European</td><td><ext-link ext-link-type="url" href="https://gwas.mrcieu.ac.uk/datasets/finn-b-E4%5fOBESITY" /></td></tr><tr><td> Household income before tax</td><td>UK Biobank</td><td>ukb-b-7408</td><td>397,751</td><td>European</td><td><ext-link ext-link-type="url" href="https://gwas.mrcieu.ac.uk/datasets/ukb-b-7408" /></td></tr><tr><td> Triglycerides</td><td>Kettunen et al</td><td>met-c-934</td><td>21,545</td><td>European</td><td>27005778</td></tr><tr><td> Education</td><td>SSGAC</td><td>ieu-a-1239</td><td>766,345</td><td>European</td><td>30038396</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Note</emph>. ADHD = attention deficit hyperactivity disorder; ASD = autism spectrum disorder; GSCAN = GWAS & Sequencing Consortium of Alcohol and Nicotine use; SSGAC = Social Science Genetic Association Consortium; ConsortiumCARDIoGRAMplusC4D = Coronary Artery Disease Genome wide Replication and Meta-analysis (CARDIoGRAM) plus the Coronary Artery Disease (C4D) Genetics consortium; HERMES = Heart Failure Molecular Epidemiology for Therapeutic Targets.</p> <hd id="AN0181053483-6">Determining Instrumental Variables</hd> <p>For selecting IVs with genome-wide significance, we identified SNPs meeting the threshold (<emph>p</emph> < 5 × 10<sups>−8</sups>). We used a linkage disequilibrium (LD) criterion to guarantee the independence of these SNPs, classifying SNPs with a genetic distance greater than 10,000 kb and an <emph>r</emph><sups>2</sups> less than.001. Furthermore, to mitigate the risk of weak instrument bias, which can distort causal inference, we utilized <emph>F</emph>-statistics greater than 10. This criterion facilitated the validation of a strong and reliable association between the IVs and the studied exposure, enhancing the credibility of our findings ([<reflink idref="bib5" id="ref20">5</reflink>]). Ultimately, 11 and 10 qualifying IVs were included for the subsequent analyses of ADHD and ASD, respectively. The specific characteristics of the selected SNPs for predicting ADHD and ASD are outlined in Supplemental Table S1 and S2.</p> <hd id="AN0181053483-7">Statistical Analyses</hd> <p>We utilized the TwoSampleMR and MR-PRESSO R packages available within R (version 4.2.0) to scrutinize the causality between ADHD, ASD, and CVDs. Various MR strategies grounded on different IV assumptions Assuming total IVs are valid, the primary strategy chosen was the inverse variance weighted (IVW) method due to its dependability ([<reflink idref="bib20" id="ref21">20</reflink>]), supplemented by MR-Egger ([<reflink idref="bib2" id="ref22">2</reflink>]), Weighted median ([<reflink idref="bib3" id="ref23">3</reflink>]), and MR-PRESSO ([<reflink idref="bib34" id="ref24">34</reflink>]) method. The IVW method combines the Wald ratios of each SNP to estimate the overall causal effect, assuming no horizontal pleiotropy. The MR-Egger method, on the other hand, allows for the presence of pleiotropy by providing an intercept term that indicates the average pleiotropic effect across all SNPs. The Weighted median method offers a compromise between robustness and efficiency, as it can provide consistent causal estimates even if up to 50% of the IVs are invalid. MR-PRESSO identifies and corrects for outliers, further ensuring the integrity of our causal inference. Sensitivity analyses were conducted to address any heterogeneity and horizontal pleiotropy. Cochran's <emph>Q</emph> test was used to assess heterogeneity among the SNP-specific causal estimates. In the presence of significant heterogeneity (<emph>p</emph> <.05), the random-effects IVW method was utilized as the primary analytical strategy. In contrast, the fixed-effects IVW method would be applied when heterogeneity is not statistically significant. Meanwhile, MR-Egger regression was used to appraise potential horizontal pleiotropy. If found this would suggest the potential for biased estimation of the causal relationship. To maintain rigor in statistical testing, we implemented a multiple correction significance threshold defined as 0.05/7 = 0.007, accounting for the seven outcomes (different CVDs) analyzed. A <emph>p</emph>-value of <.05 was determined as nominal significance.</p> <hd id="AN0181053483-8">Mediation MR Analysis and MVMR</hd> <p>The mediation analysis design is depicted in Figure 2. Employing a two-step MR approach, it was determined to what degree risk factors mediate the causal link. In the initial step, confirmation of the causality of ADHD and ASD concerning these potential mediators was undertaken. In the second stage, the causal link between the mediators and the risk of CVDs causally associated with ASD or ADHD were evaluated. This methodological framework is designed to systematically dissect and quantify the mediating role of common risk factors within the observed causal relationships.</p> <p>Graph: Figure 2. Overview of two-step MR analysis of ADHD and ASD on various CVDs via potential mediators. In the first step, the causality of ADHD and ASD on potential mediators was confirmed. In the second step, IVs significantly associated with each mediator were employed to assess the causal effect between the mediators and the risk of CVDs causally linked to ADHD or ASD. Direct effect = the effect of ADHD or ASD on CVD risk after adjusting for the mediators (β1 – β2 × β3). Indirect effect = the effect of ADHD or ASD on CVD risk through the mediator (β2 × β3). Note. ADHD = attention deficit hyperactivity disorder; ASD = autism spectrum disorder; IVs = instrumental variables; SNPs = single-nucleotide polymorphisms; TDI = Townsend deprivation index.</p> <p>We used the function "mv_multiple" from the TwoSampleMR package to conduct MVMR. This method allows for the inclusion of multiple exposures in the MR analysis, thereby accounting for potential confounders and providing a more accurate estimate of the causal effect. By adjusting for obesity, we aimed to delineate the direct causal effects of ADHD and ASD on CVDs.</p> <hd id="AN0181053483-9">Results</hd> <p></p> <hd id="AN0181053483-10">Genetic Susceptibility to ADHD and ASD on CVD and Mediators</hd> <p>Genetically determined associations between ADHD or ASD and diverse CVDs are detailed in Figure 3 and Supplemental Tables S3 and S5. Using IVW analyses, the results indicated a genetic predisposition to ADHD significantly raises the likelihood of CHD at the nominal significance level (OR = 1.12; <emph>p</emph> = 0.008), HF (OR = 1.14; <emph>p</emph> = 1.45 × 10<sups>−4</sups>], and LAS (OR = 1.35; <emph>p</emph> =.005). ASD is genetically linked to an elevated AF risk (OR = 1.09; <emph>p</emph> =.005) and HF (OR = 1.11; <emph>p</emph> = 0.004; Figure 3).</p> <p>Graph: Figure 3. MR estimates of the causal associations of ADHD and ASD on CVDs. Note. nSNP = number of single nucleotide polymorphism, OR = odd ratio; CI = confidence interval; ADHD = attention deficit hyperactivity disorder; ASD = autism spectrum disorder.</p> <p>Table 2 and Supplemental Table S7 and S9 show the relationship between genetically predicted ASD and ADHD and cardiovascular risk-associated variables. IVW analyses revealed that ADHD was causally associated with smoking initiation (OR [95% CI] 1.13 [1.07, 1.20]; <emph>p</emph> = 6.15 × 10<sups>−5</sups>), triglycerides (β [95% CI].09 [0.01, 0.17]; <emph>p</emph> =.030), prescription opioid use (OR [95% CI] 1.12 [1.03, 1.21]; <emph>p</emph> =.008), education (β [95% CI] −.08 [−0.13, −0.04]; <emph>p</emph> = 1.68 × 10<sups>−4</sups>], income (β [95% CI] −.09 [−0.12, −0.07]; <emph>p</emph> = 1.39 × 10<sups>−16</sups>), and TDI (β [95% CI].08 [0.06, 0.09]; <emph>p</emph> = 2.49 × 10<sups>−18</sups>). Moreover, ASD's genetic predisposition is linked with an increase in obesity (OR [95% CI] 1.26 [1.07, 1.49]; <emph>p</emph> =.007; Table 2).</p> <p>Table 2. MR Results of ADHD and ASD on Mediators and Mediators on CVDs.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left">Analyses</th><th align="center">Number of SNPs</th><th align="center">β [95%CI]</th><th align="center">OR [95%CI]</th><th align="center"><italic>p</italic> Value</th></tr></thead><tbody><tr><td colspan="5">ADHD on mediators</td></tr><tr><td> Smoking initiation</td><td>7</td><td>.12 [0.06, 0.19]</td><td>1.13 [1.07, 1.20]</td><td>6.15E-05</td></tr><tr><td> Prescription opioid use</td><td>9</td><td>.11 [0.03, 0.19]</td><td>1.12 [1.03, 1.21]</td><td>.008</td></tr><tr><td> Triglycerides</td><td>9</td><td>.09 [0.01, 0.17]</td><td>-</td><td>.030</td></tr><tr><td> Education</td><td>9</td><td>−.08 [−0.13, −0.04]</td><td>-</td><td>1.68E-04</td></tr><tr><td> Income</td><td>9</td><td>−.09 [−0.12, −0.07]</td><td>-</td><td>1.39E-16</td></tr><tr><td> Townsend deprivation index</td><td>9</td><td>.08 [0.06, 0.09]</td><td>-</td><td>2.49E-18</td></tr><tr><td> Obesity</td><td>9</td><td>.12 [−0.01, 0.26]</td><td>1.13 [0.99, 1.30]</td><td>.076</td></tr><tr><td colspan="5">ASD on mediators</td></tr><tr><td> Smoking initiation</td><td>8</td><td>.03 [−0.04, 0.09]</td><td>1.03 [0.96, 1.10]</td><td>.452</td></tr><tr><td> Prescription opioid use</td><td>8</td><td>−.05 [−0.15, 0.05]</td><td>0.95 [0.86, 1.05]</td><td>.325</td></tr><tr><td> Triglycerides</td><td>10</td><td>.01 [−0.08, 0.09]</td><td>-</td><td>.881</td></tr><tr><td> Education</td><td>9</td><td>.02 [−0.04, 0.07]</td><td>-</td><td>.514</td></tr><tr><td> Income</td><td>9</td><td>−.02 [−0.07, 0.04]</td><td>-</td><td>.565</td></tr><tr><td> Townsend deprivation index</td><td>9</td><td>.03 [−0.01, 0.07]</td><td>-</td><td>.089</td></tr><tr><td> Obesity</td><td>8</td><td>.23 [0.06, 0.40]</td><td>1.26 [1.07, 1.49]</td><td>.007</td></tr><tr><td colspan="5">Smoking initiation on cardiovascular diseases</td></tr><tr><td> Coronary heart disease</td><td>90</td><td>.249 [0.165, 0.333]</td><td>1.28[1.18, 1.40]</td><td>7.21E-09</td></tr><tr><td> Heart failure</td><td>91</td><td>.262 [0.175, 0.349]</td><td>1.30[1.19, 1.42]</td><td>3.69E-09</td></tr><tr><td> Large-artery stroke</td><td>91</td><td>.437 [0.215, 0.658]</td><td>1.55[1.24, 1.93]</td><td>1.13E-04</td></tr><tr><td colspan="5">Obesity on cardiovascular diseases</td></tr><tr><td> Atrial fibrillation</td><td>8</td><td>.10 [0.07, 0.14]</td><td>1.11 [1.07, 1.15]</td><td>7.05E-08</td></tr><tr><td> Heart failure</td><td>8</td><td>.16 [0.12, 0.201]</td><td>1.18 [1.13, 1.23]</td><td>1.43E-12</td></tr><tr><td colspan="5">Triglycerides on cardiovascular diseases</td></tr><tr><td> Coronary heart disease</td><td>11</td><td>.26 [0.14, 0.39]</td><td>1.30 [1.15, 1.48]</td><td>5.08E-05</td></tr><tr><td> Heart failure</td><td>11</td><td>.11 [0.02, 0.21]</td><td>1.12 [1.02, 1.23]</td><td>.015</td></tr><tr><td> Large-artery stroke</td><td>11</td><td>−.04 [−0.20, 0.13]</td><td>0.96 [0.82, 1.14]</td><td>.662</td></tr><tr><td colspan="5">Education on cardiovascular diseases</td></tr><tr><td> Coronary heart disease</td><td>309</td><td>−.49 [−0.59, −0.39]</td><td>0.62 [0.56,0.68]</td><td>4.83E-21</td></tr><tr><td> Heart failure</td><td>309</td><td>−.35 [−0.43, −0.26]</td><td>0.71 [0.65,0.77]</td><td>7.12E-16</td></tr><tr><td> Large-artery stroke</td><td>309</td><td>−.71 [−0.95, −0.48]</td><td>0.49 [0.39,0.62]</td><td>3.24E-09</td></tr><tr><td colspan="5">Income on cardiovascular diseases</td></tr><tr><td> Coronary heart disease</td><td>43</td><td>−.50 [−0.73, −0.26]</td><td>0.61 [0.48, 0.77]</td><td>3.21E-05</td></tr><tr><td> Heart failure</td><td>45</td><td>−.20 [−0.34, −0.05]</td><td>0.82 [0.71, 0.95]</td><td>.008</td></tr><tr><td> Large-artery stroke</td><td>46</td><td>−.55 [−1.08, −0.02]</td><td>0.58 [0.34, 0.98]</td><td>.041</td></tr><tr><td colspan="5">Prescription opioid use on cardiovascular diseases</td></tr><tr><td> Coronary heart disease</td><td>6</td><td>−.27 [−0.63, 0.09]</td><td>0.76 [0.53, 1.09]</td><td>.139</td></tr><tr><td> Heart failure</td><td>6</td><td>.12 [0.01, 0.27]</td><td>1.15 [1.01, 1.31]</td><td>.039</td></tr><tr><td> Large-artery stroke</td><td>6</td><td>.07 [−0.35, 0.50]</td><td>1.07 [0.70, 1.64]</td><td>.740</td></tr><tr><td colspan="5">Townsend deprivation index on cardiovascular diseases</td></tr><tr><td> Coronary heart disease</td><td>18</td><td>.22 [−0.34, 0.77]</td><td>1.24 [0.71, 2.17]</td><td>.447</td></tr><tr><td> Heart failure</td><td>18</td><td>.50 [0.10, 0.90]</td><td>1.65 [1.11, 2.46]</td><td>.014</td></tr><tr><td> Large-artery stroke</td><td>18</td><td>1.25 [0.27, 2.23]</td><td>3.47 [1.30, 9.26]</td><td>.013</td></tr></tbody></table> </ephtml> </p> <p>2 <emph>Note</emph>. ADHD = attention deficit hyperactivity disorder; ASD = autism spectrum disorder; SNP = single nucleotide polymorphism, OR = odd ratio; CI = confidence interval.</p> <hd id="AN0181053483-11">Causal Associations of Mediators With CVDs</hd> <p>The results of IVW indicated that the risk of CHD (OR [95% CI] 1.28 (1.18, 1.40) ], HF (OR [95% CI] 1.30 [1.19–1.42]), and LAS (OR [95% CI] 1.55 [1.24–1.93]) was positively correlated with the smoking initiation. The usage of prescription opioids was found to have a direct link to a higher HF risk (OR [95% CI] 1.15 [1.01, 1.31]). Furthermore, each 1 − standard deviation (<emph>SD</emph>) unit increase in triglycerides exhibited positive associations with CHD risk (OR [95% CI] 1.30 [1.15–1.48]) and HF (OR [95% CI] 1.12 [1.02–1.23]; Table 2; Supplemental Table S11).</p> <p>Moreover, the risk of CHD (OR [95% CI] 0.62 [0.56, 0.68]), HF (OR [95% CI] 0.71 [0.65, 0.77]), and LAS (OR [95% CI] 0.49 [0.39, 0.62]) was inversely correlated with a 1 − <emph>SD</emph> unit increase in education level. Similarly, a 1 − <emph>SD</emph> unit boost in income had an inverse association with the risk of CHD (OR [95% CI] 0.61 [0.48, 0.77]), HF (OR [95% CI] 0.82 [0.71, 0.95]), and LAS (OR [95% CI] 0.58 [0.34, 0.98]). Each 1 − <emph>SD</emph> unit increase in TDI demonstrated positive associations with the HF (OR [95% CI] 1.65 [1.11, 2.46]) and LAS (OR [95% CI] 3.47 [1.30, 9.26]). Additionally, obesity was positively associated with the AF (OR [95% CI] 1.11 [1.07, 1.15]) and HF (OR [95% CI] 1.18 [1.13, 1.23]; Table 2; Supplemental Table S11).</p> <hd id="AN0181053483-12">MR Sensitivity Analysis</hd> <p>The majority of statistical models exhibited consistent direction with the IVW analysis (Supplemental Table S3, S5, S7, S9, and S11). Heterogeneity was observed in the distribution of SNPs across some MR analyses, as indicated by Cochran's <emph>Q</emph> test (<emph>p</emph> <.05) and we conducted the random-effect IVW method in these MR analyses, while other analyses used the fixed-effects IVW method (Supplemental Table S4, S6, S8, S10, and S12). Moreover, near-zero intercepts in the MR-Egger tests indicate minimal evidence for horizontal pleiotropy, further validating no pleiotropy in used IVs (Supplemental Table S4, S6, S8, S10, and S12).</p> <hd id="AN0181053483-13">MR Estimates of Mediation Proportions</hd> <p>Table 3 presents the mediating effects of various factors in the link between ADHD or ASD and CVDs. Specifically, it presents the proportions mediated by different factors as follows: smoking initiation, with ADHD impacting CHD, HF, and LAS with proportions mediated of 28%, 25%, and 18% respectively; prescription opioid use mediating 12% of ADHD's effect on HF; triglycerides mediating ADHD's influence on CHD and HF by 22% and 8% respectively; education mediating the effects of ADHD on CHD, HF, and LAS by proportions of 38%, 22%, and 20% respectively; income mediating ADHD's effects on CHD, HF, and LAS by proportions of 43%, 15%, and 18% respectively; TDI mediating ADHD's impact on HF and LAS by 29% and 31% respectively; obesity mediating ASD's effects on AF and HF by 28% and 35% respectively (Table 3).</p> <p>Table 3. MR Estimates of Proportions Mediated by Mediators in the Causal Association of ADHD or ASD on CVDs.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left">Traits</th><th align="center">Total effect</th><th align="center">Direct effect</th><th align="center">Mediation effect</th><th align="center">Mediation proportions (%)</th></tr></thead><tbody><tr><td colspan="5">Smoking initiation</td></tr><tr><td> (ADHD vs. CHD)</td><td>0.109</td><td>0.078</td><td>0.031</td><td>28</td></tr><tr><td> (ADHD vs. HF)</td><td>0.130</td><td>0.098</td><td>0.032</td><td>25</td></tr><tr><td> (ADHD vs. LAS)</td><td>0.296</td><td>0.242</td><td>0.054</td><td>18</td></tr><tr><td colspan="5">Obesity</td></tr><tr><td> (ASD vs. AF)</td><td>0.085</td><td>0.061</td><td>0.024</td><td>28</td></tr><tr><td> (ASD vs. HF)</td><td>0.106</td><td>0.069</td><td>0.037</td><td>35</td></tr><tr><td colspan="5">Triglycerides</td></tr><tr><td> (ADHD vs. CHD)</td><td>0.109</td><td>0.085</td><td>0.024</td><td>22</td></tr><tr><td> (ADHD vs. HF)</td><td>0.130</td><td>0.120</td><td>0.010</td><td>8</td></tr><tr><td colspan="5">Education</td></tr><tr><td> (ADHD vs. CHD)</td><td>0.109</td><td>0.068</td><td>0.041</td><td>38</td></tr><tr><td> (ADHD vs. HF)</td><td>0.130</td><td>0.101</td><td>0.029</td><td>22</td></tr><tr><td> (ADHD vs. LAS)</td><td>0.296</td><td>0.236</td><td>0.060</td><td>20</td></tr><tr><td colspan="5">Income</td></tr><tr><td> (ADHD vs. CHD)</td><td>0.109</td><td>0.068</td><td>0.047</td><td>43</td></tr><tr><td> (ADHD vs. HF)</td><td>0.130</td><td>0.101</td><td>0.019</td><td>15</td></tr><tr><td> (ADHD vs. LAS)</td><td>0.296</td><td>0.236</td><td>0.052</td><td>18</td></tr><tr><td colspan="5">Prescription opioid use</td></tr><tr><td> (ADHD vs. HF)</td><td>0.130</td><td>0.115</td><td>0.015</td><td>12</td></tr><tr><td colspan="5">Townsend deprivation index</td></tr><tr><td> (ADHD vs. HF)</td><td>0.130</td><td>0.092</td><td>0.038</td><td>29</td></tr><tr><td> (ADHD vs. LAS)</td><td>0.296</td><td>0.204</td><td>0.092</td><td>31</td></tr></tbody></table> </ephtml> </p> <p>3 <emph>Note</emph>. Total effect = β1; Mediation effect = β2 × β3; Direct effect = β1 − β2 × β3; Mediation proportions = (β2 × β3)/β1. ADHD = attention deficit hyperactivity disorder; ASD = autism spectrum disorder; CHD = coronary heart disease; AF = atrial fibrillation; HF = heart failure; LAS = large artery stroke.</p> <hd id="AN0181053483-14">Obesity-Adjusted Causal Effects of ADHD and ASD on CVD</hd> <p>Using MVMR methods, we adjusted for obesity to assess the independent effects of ADHD and ASD on CVDs. The results indicate that ADHD has a significant causal effect on CHD (OR = 1.11; 95% CI [1.01, 1.22]; <emph>p</emph> =.04), HF (OR = 1.11; 95% CI [1.05, 1.17]; <emph>p</emph> = 1.28E-4), and LAS (OR = 1.44; 95% CI [1.08, 1.92]; <emph>p</emph> =.01). ASD was causally linked to an increased risk of HF (OR = 1.21; 95% CI [1.04, 1.40] <emph>p</emph> =.01), although the association with HF did not reach statistical significance (OR = 1.19; 95% CI [0.98, 1.43]; <emph>p</emph> =.07; Table 4). The obesity-adjusted causal effects of ADHD and ASD on CVD are generally smaller, with ASD's association with HF tending toward null. These findings underscore the importance of considering obesity as a mediator.</p> <p>Table 4. MVMR Estimates of the Significant Causal Association of ADHD or ASD on CVDs Adjusted for Obesity.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left">Exposure</th><th align="center">Outcome</th><th align="center">OR [95% CI]</th><th align="center"><italic>p</italic> Value</th></tr></thead><tbody><tr><td rowspan="3">ADHD</td><td>Coronary heart disease</td><td>1.11 [1.01,1.22]</td><td>.04</td></tr><tr><td>Heart failure</td><td>1.11 [1.05,1.17]</td><td>1.28E-04</td></tr><tr><td>Large-artery stroke</td><td>1.44 [1.08,1.92]</td><td>.01</td></tr><tr><td rowspan="2">ASD</td><td>Atrial fibrillation</td><td>1.21 [1.04,1.40]</td><td>.01</td></tr><tr><td>Heart failure</td><td>1.19 [0.98,1.43]</td><td>.07</td></tr></tbody></table> </ephtml> </p> <p>4 <emph>Note</emph>. MVMR = multivariable MR; ADHD = attention deficit hyperactivity disorder; ASD = autism spectrum disorder; CVD = cardiovascular diseases; OR = odd ratio; CI = confidence interval.</p> <hd id="AN0181053483-15">Discussion</hd> <p>This study systematically establishes potential causal relationships between susceptibility to ADHD and the risks of CHD, HF, and LAS, along with the causality between genetic susceptibility to ASD and a higher risk of AF and HF, employing various MR analyses. We also identified several mediators that play a significant role in the causal effects of ADHD on CVD and the mediating effect of obesity in the causal relationship of ASD on AF and HF.</p> <p>A recent extensive Swedish cohort study involving 5,389,519 adults reveals a significant association between ADHD and an increased risk of any CVD, regardless of psychotropic medications and family history of CVD ([<reflink idref="bib22" id="ref25">22</reflink>]). Moreover, a prospective population cohort study with 8,016 individuals suggests increased susceptibility to cardiovascular risk factors in childhood ADHD patients, including BMI, triglyceride levels, and current smoking ([<reflink idref="bib33" id="ref26">33</reflink>]). Consistent with existing literature ([<reflink idref="bib8" id="ref27">8</reflink>]; [<reflink idref="bib25" id="ref28">25</reflink>]), this study finds genetically predicted ADHD causally associated with CHD, HF, and LAS. Smoking, triglycerides, prescription opioid use, and socioeconomic factors (education, income, and TDI) play significant roles in the process of ADHD leading to CVD. Notably, the indices of socioeconomic status—education, income, and TDI—manifest complex interplay, and their mediating effects may overlap.</p> <p>To date, the relationship between obesity and ADHD has been explored. A MR study demonstrated a bidirectional causal relationship between obesity and ADHD ([<reflink idref="bib6" id="ref29">6</reflink>]). However, another MR study indicated that ADHD had a 6.1% increased causal effect on high waist circumference (WC; OR = 1.061, 95% CI [1.024, 1.099]) and an 8.2% increased causal effect on high waist-to-hip ratio (WHR; OR = 1.082, 95% CI [1.035, 1.131]), but no causal effect on body mass index (BMI), hip circumference (HC), body fat percentage (BFP), or basal metabolic rate (BMR)([<reflink idref="bib24" id="ref30">24</reflink>]). In our study, we did not find a significant causal relationship between ADHD and obesity. There could be several reasons for this: first, our study used a different population for the obesity-related GWAS. Second, ADHD has been primarily associated with WC and WHR, whereas obesity is defined qualitatively as a BMI greater than 30. This could explain the discrepancies in our findings. Nevertheless, the association between obesity, ADHD, and CVD cannot be denied. Given effects of ADHD on various CVDs tend to attenuate after adjusting for obesity factor ([<reflink idref="bib21" id="ref31">21</reflink>]), we further investigated obesity through multivariable analysis. Our findings revealed that, after adjusting for obesity, the effects of ADHD and ASD on CVD were both reduced, indicating that obesity plays a significant role in these relationships. More comprehensive and systematic studies are needed in the future to explore the impact of obesity and related indicators in these relationships.</p> <p>Observational studies present divergent results regarding the association between ASD and CVD. A case-control study reports a higher prevalence in adults with ASD ([<reflink idref="bib7" id="ref32">7</reflink>]), while a Danish nationwide registry study suggested less frequent occurrences of ischemic heart diseases in the ASD group ([<reflink idref="bib26" id="ref33">26</reflink>]). Furthermore, obesity, a well-established CVD risk factor, is found to be more likely in children with ASD ([<reflink idref="bib7" id="ref34">7</reflink>]; [<reflink idref="bib13" id="ref35">13</reflink>]). Our research indicates a causal relationship between ASD and AF and HF, with obesity playing a significant mediating role. The reliability of findings from the Danish study is constrained by its small sample size.</p> <p>Given the substantial proportion of individuals with ADHD or ASD developing CVDs, early interventions are crucial for enhancing cardiovascular health. The study reveals probable mediators of ADHD and ASD leading to CVD, providing a foundation for sensible therapeutic practices to enhance cardiovascular outcomes.</p> <p>The study's strengths lie in the utilization of CVD GWASs data where the population is non-overlapping with the population analyzed in ADHD and ASD GWASs, mitigating the risk of type 1 error. Additionally, the incorporation of multiple MR studies enhances the reliability and robustness of IVW estimates. Nevertheless, certain limitations merit acknowledgment. The exclusive inclusion of participants of European descent raises potential concerns regarding the external validity of the results to a wider, more ethnically diverse population. Acknowledging these variations in CVD risk factors and prevalence across ethnicities is pivotal for a nuanced interpretation of the results. Future research must broaden participant diversity for wider applicability. Moreover, the study focuses on a subset of mediating factors, leaving unexplored dimensions. Drug therapy for ADHD has been proven to be associated with CVD ([<reflink idref="bib36" id="ref36">36</reflink>]). Due to the fact that MR research is not applicable to this area of research, we are not exploring the impact of drugs. In the future, exploring additional components, notably the influence of ADHD medications, will enrich the study's scope and deepen our understanding of the complex relationships. In addition, the emergence of new GWAS data may not be fully encapsulated within our research. Consequently, we recommend that future studies incorporate these recently published GWAS datasets in conjunction with our analyses to ensure the comprehensiveness of the findings. Finally, we acknowledge that the ORs observed are relatively small. Our mediation analysis indicates that while intermediary factors do contribute to the complex relationships between ADHD, ASD, and CVD, their impact remains modest. This finding aligns with the study by Burgess et al., which also highlighted that small effect sizes can still offer valuable insights into the mechanisms linking these diseases ([<reflink idref="bib4" id="ref37">4</reflink>]). It's important to recognize that minor effect sizes are a common occurrence in MR studies, largely due to the involvement of multiple genes, each exerting a small individual effect ([<reflink idref="bib18" id="ref38">18</reflink>]). Despite their modest nature, these small effect sizes do not diminish the significance or validity of our findings. Instead, they underscore the necessity of large sample sizes and replication studies. The literature consistently demonstrates that the cumulative impact of multiple genetic variations significantly contributes to the overall disease risk ([<reflink idref="bib16" id="ref39">16</reflink>]; [<reflink idref="bib28" id="ref40">28</reflink>]). Moreover, even minor genetic influences are essential for understanding the underlying biological pathways and could provide important clues for identifying potential therapeutic targets.</p> <hd id="AN0181053483-16">Conclusion</hd> <p>This MR study provides suggestive genetic evidence linking genetically inferred ADHD and ASD with CVDs. It underscores the role of mediating factors such as smoking, prescription opioid use, triglycerides, education, income, TDI, and obesity, in shaping the causal impact of ADHD or ASD on CVD. These insights underscore the importance of vigilant cardiovascular monitoring for individuals diagnosed with ADHD or ASD by preventing identified mediating risk factors.</p> <hd id="AN0181053483-17">Supplemental Material</hd> <p>Graph: Supplemental material, sj-docx-1-jad-10.1177_10870547241288741 for Causality Between ADHD, ASD, and CVDs: A Two-Step, Two-Sample Mendelian Randomization Investigation by Zequn Zheng and Dihui Cai in Journal of Attention Disorders</p> <p>This work appreciates the UK Biobank, HERMES Consortium, FinnGen studies, CARDIoGRAMplusC4D Consortium, PGC, SSGAC, GSCAN, and IEU Open GWAS project for sharing data publicly.</p> <ref id="AN0181053483-18"> <title> Reference </title> <blist> <bibl id="bib1" idref="ref3" type="bt">1</bibl> <bibtext> Amarasekera S., Jha P. (2022). Understanding the links between cardiovascular and psychiatric conditions. 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Interested readers can find the supportive data within the main text of this article and its accompanying Supplemental Materials.</bibtext> </blist> <blist> <bibtext> The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.</bibtext> </blist> <blist> <bibtext> The author(s) received no financial support for the research, authorship, and/or publication of this article.</bibtext> </blist> <blist> <bibtext> This study involves a re-analysis of openly accessible datasets. Noteworthy is the fact that every piece of data used herein has been ethically sanctioned in their original investigations. Consequently, no further ethical clearance is deemed requisite for the scope of this analysis.</bibtext> </blist> <blist> <bibtext> Dihui Cai</bibtext> </blist> <blist> <bibtext>Graph https://orcid.org/0000-0002-8153-3647</bibtext> </blist> <blist> <bibtext> Supplemental material for this article is available online.</bibtext> </blist> </ref> <aug> <p>By Zequn Zheng and Dihui Cai</p> <p>Reported by Author; Author</p> <p></p> <p>Zequn Zheng is currently pursuing a Ph.D. in the School of Medicine at Shantou University</p> <p>Dihui Cai is currently pursuing a Ph.D. in the School of Medicine at Tongji University. Their primary research focus is on cardiovascular diseases.</p> </aug> <nolink nlid="nl1" bibid="bib29" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib31" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib27" firstref="ref4"></nolink> <nolink nlid="nl4" bibid="bib14" firstref="ref5"></nolink> <nolink nlid="nl5" bibid="bib35" firstref="ref6"></nolink> <nolink nlid="nl6" bibid="bib11" firstref="ref7"></nolink> <nolink nlid="nl7" bibid="bib23" firstref="ref8"></nolink> <nolink nlid="nl8" bibid="bib30" firstref="ref10"></nolink> <nolink nlid="nl9" bibid="bib12" firstref="ref11"></nolink> <nolink nlid="nl10" bibid="bib25" firstref="ref12"></nolink> <nolink nlid="nl11" bibid="bib19" firstref="ref14"></nolink> <nolink nlid="nl12" bibid="bib17" firstref="ref15"></nolink> <nolink nlid="nl13" bibid="bib32" firstref="ref16"></nolink> <nolink nlid="nl14" bibid="bib15" firstref="ref18"></nolink> <nolink nlid="nl15" bibid="bib10" firstref="ref19"></nolink> <nolink nlid="nl16" bibid="bib20" firstref="ref21"></nolink> <nolink nlid="nl17" bibid="bib34" firstref="ref24"></nolink> <nolink nlid="nl18" bibid="bib22" firstref="ref25"></nolink> <nolink nlid="nl19" bibid="bib33" firstref="ref26"></nolink> <nolink nlid="nl20" bibid="bib24" firstref="ref30"></nolink> <nolink nlid="nl21" bibid="bib21" firstref="ref31"></nolink> <nolink nlid="nl22" bibid="bib26" firstref="ref33"></nolink> <nolink nlid="nl23" bibid="bib13" firstref="ref35"></nolink> <nolink nlid="nl24" bibid="bib36" firstref="ref36"></nolink> <nolink nlid="nl25" bibid="bib18" firstref="ref38"></nolink> <nolink nlid="nl26" bibid="bib16" firstref="ref39"></nolink> <nolink nlid="nl27" bibid="bib28" firstref="ref40"></nolink>
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  Data: Causality between ADHD, ASD, and CVDs: A Two-Step, Two-Sample Mendelian Randomization Investigation
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  Data: <searchLink fieldCode="AR" term="%22Zequn+Zheng%22">Zequn Zheng</searchLink><br /><searchLink fieldCode="AR" term="%22Dihui+Cai%22">Dihui Cai</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-8153-3647">0000-0002-8153-3647</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Attention+Disorders%22"><i>Journal of Attention Disorders</i></searchLink>. 2025 29(1):3-13.
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  Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
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  Data: 11
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  Data: Journal Articles<br />Reports - Research
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  Data: <searchLink fieldCode="DE" term="%22Attention+Deficit+Hyperactivity+Disorder%22">Attention Deficit Hyperactivity Disorder</searchLink><br /><searchLink fieldCode="DE" term="%22Autism+Spectrum+Disorders%22">Autism Spectrum Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Heart+Disorders%22">Heart Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Correlation%22">Correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Risk%22">Risk</searchLink><br /><searchLink fieldCode="DE" term="%22Probability%22">Probability</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+Disorders%22">Genetic Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Physical+Health%22">Physical Health</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Attainment%22">Educational Attainment</searchLink><br /><searchLink fieldCode="DE" term="%22Smoking%22">Smoking</searchLink><br /><searchLink fieldCode="DE" term="%22Income%22">Income</searchLink><br /><searchLink fieldCode="DE" term="%22Obesity%22">Obesity</searchLink><br /><searchLink fieldCode="DE" term="%22Drug+Use%22">Drug Use</searchLink>
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  Data: 10.1177/10870547241288741
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  Data: 1087-0547<br />1557-1246
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  Data: Background: While observational studies have established a connection between attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and heightened risk for cardiovascular diseases (CVD), the causal relationships are not well-defined. This study is designed to examine the causality between ASD, ADHD, and CVD risk as well as investigate the mediating factors through which ADHD and ASD influence CVD. Methods and Results: Leveraging two-sample Mendelian randomization (MR) approaches and large scale GWAS summary stats, we examined underlying causal links between ASD and ADHD and the risk of CVDs. The analysis indicated that ADHD was related to an increased likelihood of developing coronary heart disease (OR [95% CI] 1.12 [1.03, 1.21], p = 0.008), heart failure (OR [95% CI] 1.14 [1.07, 1.22], p = 1.45 × 10-4), and large-artery stroke (OR [95% CI] 1.35 [1.09, 1.66], p = 0.005). In parallel, ASD showed a correlation with a greater atrial fibrillation risk (OR [95% CI] 1.09 [1.03, 1.16], p = 0.005] and heart failure (OR [95% CI] 1.11 [1.04, 1.19], p = 0.004). Additionally, we explored the mediating role of CVD risk factors through two-step MR and multivariable MR, highlighting the possible role of smoking, prescription opioid use, triglycerides, education, income, Townsend deprivation index, and obesity in the causal association of ADHD, ASD, on CVDs. Conclusion: This MR study highlights the necessity for rigorous cardiovascular surveillance and interventions to decrease adverse cardiovascular events in people with ADHD or ASD by preventing identified mediating risk factors.
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  Data: 2024
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        Value: 10.1177/10870547241288741
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        PageCount: 11
        StartPage: 3
    Subjects:
      – SubjectFull: Attention Deficit Hyperactivity Disorder
        Type: general
      – SubjectFull: Autism Spectrum Disorders
        Type: general
      – SubjectFull: Heart Disorders
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      – SubjectFull: Risk
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      – SubjectFull: Genetic Disorders
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      – SubjectFull: Physical Health
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      – SubjectFull: Educational Attainment
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      – SubjectFull: Smoking
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      – SubjectFull: Income
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      – SubjectFull: Obesity
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      – TitleFull: Causality between ADHD, ASD, and CVDs: A Two-Step, Two-Sample Mendelian Randomization Investigation
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              Y: 2025
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