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. Author manuscript; available in PMC: 2023 Sep 12.
Published in final edited form as: Biol Psychiatry. 2022 Aug 24;93(4):362–369. doi: 10.1016/j.biopsych.2022.08.012

The Relationship of Attention-deficit/Hyperactivity Disorder with Post-traumatic Stress Disorder: A Two-Sample Mendelian Randomization and Population-Based Sibling Comparison Study

Frank R Wendt 1,2,3,*, Miguel Garcia-Argibay 4,*, Brenda Cabrera-Mendoza 1,2, Unnur A Valdimarsdóttir 5,6,7, Joel Gelernter 1,2, Murray B Stein 8,9,10, Michel G Nivard 11, Adam X Maihofer 8,10,12; Post-Traumatic Stress Disorder Working Group of the Psychiatric Genomics Consortium, Caroline M Nievergelt 8,10,12, Henrik Larsson 4,13,#, Manuel Mattheisen 14,#, Renato Polimanti 1,2,#, Sandra Meier 14,#
PMCID: PMC10496427  NIHMSID: NIHMS1927362  PMID: 36335070

Abstract

Background

Attention-deficit/hyperactivity disorder (ADHD) and posttraumatic stress disorder (PTSD) are associated but it is unclear if this is a causal relationship or confounding. We used genetic analyses and sibling comparisons to clarify the direction this relationship.

Methods

Linkage Disequilibrium Score Regression and two-sample Mendelian randomization (MR) were used to test for genetic correlation (rg) and bidirectional causal effects using European ancestry genome-wide association studies of ADHD (20,183 cases and 35,191 controls) and six PTSD definitions (up to 320,369 individuals). Several additional variables were included in the analysis to verify the independence of the ADHD-PTSD relationship. In a population-based sibling comparison (N=2,082,118 individuals), Cox regression models were fitted to account for time at risk, a range of sociodemographic factors, and unmeasured familial confounders (via sibling comparisons).

Results

ADHD and PTSD had consistent rg (rg range, 0.43–0.52; P < .001). ADHD genetic liability was causally linked with increased risk for PTSD (Beta=0.367, 95% confidence interval (CI), 0.186-0.552, P=7.68x10−5). This result was not affected by heterogeneity, horizontal pleiotropy (MR Egger intercept=4.34x10−4, P=0.961), or other phenotypes, and was consistent across PTSD datasets. However, we found no consistent associations between PTSD genetic liability and ADHD risk. Individuals diagnosed with ADHD were at a higher risk for developing PTSD than their undiagnosed sibling (hazard ratio=2.37, 95% CI 1.98-3.53).

Conclusions

Our findings add novel evidence supporting the need for early and effective treatment of ADHD as patients with this diagnosis are at significantly higher risk to develop PTSD later in life.

Keywords: ADHD, PTSD, Comorbidities, Genome-wide association study, Epidemiology, Causal inference

Introduction

Although 50–85% of the individuals experience traumatic events over a lifetime, lifetime PTSD prevalence is approximately 7% (1, 2), suggesting differential resilience to stress and vulnerability to the disorder (2). ADHD has been suggested to be a putative risk factor for PTSD (3) due to its association with risk-taking behavior (RTB) and impulsivity resulting in higher likelihood of experiencing traumatic events (4). Stimulant medication for ADHD has been suggested to increase the risk of developing PTSD (5), although associations with PTSD have also been observed for unmedicated ADHD (6). While cross-sectional studies suggested an association between ADHD and PTSD (3), few prospective studies examined this link. A family study including 402 children diagnosed with ADHD and their siblings found a significant association between ADHD and increased risk of PTSD at 10-year follow-up (odds ratio [OR]=2.23 (7)). Similarly, an analysis examining 4,612 U.S. soldiers found that pre-deployment ADHD was associated with a higher risk of post-deployment PTSD (6). Other well-powered studies failed to observe such an association (3, 8). Since these prior results were mainly based on either military or clinical samples, as well as self-reported data, it remains unclear whether the co-occurrence of clinically diagnosed ADHD and PTSD is present in the general population.

Mendelian randomization (MR) and sibling comparisons are powerful research designs that can allow causal inference from observational data (9) (10, 11). To elucidate the nature of the relationship between ADHD and PTSD, we examined the potential causal role of ADHD for subsequent PTSD (i) using a two-sample MR approach based on data from the largest available meta-analyses of genome-wide association studies (GWAS) for these traits (12-14), and (ii) a population-based sibling comparison design. We also tested for influence of other variables on the pathway from ADHD to PTSD.

Materials and Methods

Primary GWAS

We leveraged large non-overlapping ADHD and PTSD GWAS from European descent individuals. The ADHD data consisted of 55,374 individuals (20,183 cases defined by the International Classification of Diseases [ICD-10] code (F90.0) or structured or semi-structured clinical interviews and 35,191 controls) (12). In contrast to ADHD, for PTSD there were multiple adequately powered GWAS datasets available including different PTSD phenotype definitions (case-control status but also PTSD subdomains and/or symptom severity). Specifically, the PTSD case-control GWAS from the Million Veteran Program (MVP) analyzed 36,301 cases and 178,107 controls algorithmically defined using the US Veterans Administration Healthcare electronic health records (14). The PTSD quantitative GWASs were (i) Psychiatric Genomics Consortium (PGC) PTSD v2.5 excluding Yale-Penn and iPSYCH cohorts which were included in the ADHD study (N=173,709) (13), (ii-iv) MVP avoidance, hyperarousal, and reexperiencing symptom subdomains (N=168,689) (14), and (v) MVP PTSD Checklist 17-item questionnaire total score (PCL-17) of 168,689 individuals (14). In our analyses we included all these PTSD GWASs to ensure the generalizability of results across phenotype definitions and demographic characteristics (military/non-military) used in individual studies. All GWAS considered in this study included principal components of ancestry as covariates. The MVP PTSD GWASs further considered sex and age in their association models. Note that prior work has investigated whether cohort-specific details related to PTSD (e.g., military versus civilian cohorts) contribute to different genetic architectures (15). Notably, the genetic correlation between MVP PTSD traits and PGC PTSD traits is extremely high (15).

Linkage disequilibrium score (LDSC) Regression Analysis and Polygenic Scoring (PGS)

We used LDSC regression to assess the genetic correlations of ADHD and PTSD phenotypes (16) using the European ancestry linkage disequilibrium (LD) reference panel from the 1000 Genomes Project (17). PGS analysis was performed using genome-wide association statistics and the gtx R package incorporated in PRSice (18). Both directions for possible causality were investigated in the PGS analysis: (i) ADHD as the base and PTSD phenotypes as the target and (ii) ADHD as the target and PTSD phenotypes as the base (see Supplement).

Mendelian Randomization

The R package TwoSampleMR (19) was used to estimate bidirectional causal effects between traits. In the eMethods in the Supplement, we describe details for genetic instrument selection. Briefly, all genetic instruments consisted of LD-independent SNPs associated with the exposure at some P-value defined by the best-fit PGS between base and target phenotypes. As this relaxed genetic instrument selection threshold potentially violates the above MR assumptions, we applied the MR robust adjusted profile score (MR-RAPS) approach, which is a method designed to identify and estimate confounded associations using weak genetic instrument variables (20). If a variant’s effect size was estimated from meta-analysis, we verified where possible the consistency of SNP-phenotype association across meta-analyzed cohorts. SNP-I2 estimates indicated a lack of variability due to between-study heterogeneity (ADHD I2 adjusted P-value>0.780). MR-heterogeneity testing was used to evaluate possible violation of the MR assumptions. Leave-one-out testing was used to detect outlier SNPs. Causal estimates were reported after removing SNPs underlying significant heterogeneity and/or leave-one-out results (21-23). Unless otherwise noted, we report inverse variance weighted (IVW) effect estimates.

Multivariable MR (MVMR)

To investigate further whether other factors might be underlying or mediating the ADHD-PTSD relationship, we conducted a MVMR considering the following variables: household income and educational attainment (EA) as covariates, RTB, and lifetime trauma as mediators (details on GWASs (12, 14) are given in the eMethods in the Supplement). Note that RTB was used here instead of individual risky behaviors (e.g., number of sexual partners or automobile speeding propensity) to avoid reduction in MVMR power through inclusion of many highly correlated traits. MVMR was performed for the ADHD→PTSD relationship using only MVP PCL-17 as the outcome phenotype of interest due to the strong statistical power and the lack of sample overlap with the GWAS for all selected potentially confounding exposures. For each variable, we tested their two-sample MR effect on PCL-17 in the absence of heterogeneity and horizontal pleiotropy using a genetic instrument defined by the best-fit PGS. After estimating the univariable MR effect of each variable on PCL-17, we tested their effect with respect to the ADHD-PTSD relationship using the MVMR approach implemented in the MendelianRandomization R package (24). All mediators and covariate traits were included in a single MVMR analysis.

Swedish Population-based Sibling Comparison Cohort

Using Sweden’s Total Population Register (STPR) and the Case of Death Register, we identified 2,082,087 individuals born between 1987 and 2007 who were alive and living in Sweden at age 6 with information on their biological relatives. Individuals were followed up from the age of 6 until PTSD diagnosis, death, emigration, or December 31, 2013, whichever occurred first. Parents and full siblings were identified using the Multi-Generation Register (25) and created a family ID variable using the unique personal identity number (PIN) from each biological parent (26). Individuals with ADHD were identified using the National Patient Register (NPR) (27) based on a registered diagnosis (ICD-10 code F90) or any record of a prescribed ADHD medication (methylphenidate hydrochloride [ATC code N06BA04], amphetamine [N06BA01], dextroamphetamine sulfate [N06BA02], atomoxetine hydrochloride [N06BA09], and lisdexamfetamine [N06BA12]) in the Prescription Drug Register (PDR) (28). Previous research has indicated high specificity for this register-based ADHD definition in Sweden (29) and shown that patterns of aetiological influences remain similar whether people with ADHD are identified through diagnoses or ADHD medication prescriptions (30). Only physicians specialised in psychiatry or neurology responsible for ADHD treatment are authorised to prescribe the medication in Sweden, which supports that prescription of ADHD medication is a valid indicator of ADHD diagnoses (31). PTSD was defined as the presence of an ICD-10 diagnosis code for PTSD (F43.1) in the NPR. Information about the covariates sex, highest parental EA, and household income were obtained from the STPR and Longitudinal Integration Database for Health Insurance and Labor Market Studies (LISA) (32). The mediator traumatic events during the study period was defined as the cumulative sum of the number of ICD-10 codes for sexual abuse, fire or explosion, transportation accident, exposure to a toxic substance, traumatic brain injury, physical assault, assault with a weapon, or death of a parent. Finally, based on the National Crime Register we defined the mediator RTB as any criminal conviction until the end of follow-up, marriage before age 18, divorce before age 20, or pregnancy before age 18 by using data from civil status and the Multi-Generation Register (25) (see Supplement).

Longitudinal Analyses in the Population-Based Sibling Comparison Cohort

A time-varying Cox regression model with age as the underlying time scale was fitted to determine the ADHD→PTSD relationship at the population level. Estimates were presented as hazard ratio (HR) with 95% confidence intervals (CI). First, a crude model adjusted for sex and year was fitted followed by a model adjusted with a) ADHD, cumulative traumatic events, and RTB allowed to vary over time and b) sex, birth year, household income, and parental EA defined as time-fixed covariates. To examine unmeasured familial confounding, we performed a Cox model with separated strata for each cluster of siblings (i.e., individuals with the same family ID). Proportionality assumption was tested using scaled Schoenfeld residuals. Data management and statistical analyses were performed using SAS software version 9.4 (SAS Institute, Cary, NC, USA) and R version 4.1.0. We were not able to evaluate the PTSD→ADHD relationship, as in only 31 individuals (0.001%) the onset of PTSD was prior to the ADHD diagnosis, consistent with current literature (33). Furthermore, we were not able to evaluate several specific RTBs of interest such as the number of sexual partners (data not available) and drinking/smoking behaviors (lack of validated registry data). The study had ethical approval from the Regional Ethical Review Board in Stockholm, Sweden (Dnr 2013/862–31/5). Requirement for informed consent was waived for the current study because it was a secondary analysis of existing data. Analyses followed the STROBE reporting guidelines.

Results

Genetic Correlation

Among PTSD phenotypes, PCL-17 had the highest genetic correlation with ADHD (rg=0.52, s.e.=0.037, P=1.83x10−37). There were no significant differences in rg when using other phenotype definitions of PTSD or its symptom domains (P-difference (Pdiff) between 0.122-0.399; eFigure 1, eTables 1 and 2). Furthermore, RTB, household income, EA, and lifetime trauma were genetically correlated with ADHD and PTSD (ADHD: ∣rg∣=0.3-0.52; P<1.02x10−19; PTSD: ∣rg∣=0.24-0.67; P<8.88x10−9).

Association of ADHD PGS with PTSD

ADHDPGS was associated with all PTSD phenotypes (eFigure 2 and eTable 3). The strongest association was between ADHDPGS and MVP PCL-17 (r2=0.076%, P=9.61x10−30, P-value threshold (PT)=0.001). All significant MR estimates comparing genetic instruments from ADHD and PTSD phenotypes support a positive causal effect of ADHD on PTSD (Figure 1, eTables 1 and 2). Using a subset of 482 SNPs associated with ADHD (PT<0.001), the strongest association was observed between ADHD→PCL-17 (IVW Beta=0.367, 95% CI [0.186-0.552], P=7.68x10−5). This result was not affected by heterogeneity (Q=384.0, df=481, P=0.99) or horizontal pleiotropy (MR Egger intercept=4.34x10−4, P=0.96). Consistencies with PTSD phenotypes, all association estimates, and results of tests for heterogeneity and horizontal pleiotropy are reported in the Supplement (eTables 4 and 5).

Figure 1. ADHD and PTSD Mendelian Randomization Results.

Figure 1.

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(A) Casual effect of attention deficit hyperactivity disorder (ADHD) on posttraumatic stress disorder (PTSD) phenotypes (left), and PTSD phenotypes on ADHD (right). All estimates lack evidence of heterogeneity and horizontal pleiotropy among the genetic instruments. For clarity, inverse variance weighted (IVW) and MR robust adjusted profile score (MR-RAPS, which accounts for weak genetic instruments) estimates are shown graphically and estimates across MR methods are provided in eTable 4. Odds ratios and 95% confidence interval (CI) are reported for each MR test. The number of SNPs contributing to each genetic instrument is shown in parenthesis for each PTSD trait on the y-axis. Asterisks indicate significance after multiple testing correction accounting for all trait pairs and all MR causal inference methods applied (6 PTSD traits x 2 directions tested x 6 MR methods = 72 tests). (B) a directed acyclic diagram of multivariable MR results for ADHD and PTSD including bidirectional paths to covariates (green arrows) and direct causal paths to mediators (blue arrows) of the ADHD-PTSD relationship. All mediators and covariate traits were included in a single MVMR analysis. G indicates subsets of SNPs associated with one or more of the exposures. U indicates the effect of an unobserved confounder.

Association of PTSD PGS with ADHD

All PTSDPGS from the primary polygenic score analysis predicted ADHD after multiple testing correction (5% FDR) (eFigure 2 and eTable 3). The strongest prediction was using PGS derived from PCL-17 (r2=0.195%, P=2.47x10−23, PT=0.001). Associations between genetic instruments associated with PTSD phenotypes and ADHD were heterogeneous across PTSD definitions and MR methods. After removal of outliers contributing to heterogeneity and horizontal pleiotropy, the association of PTSD with ADHD was significant only with respect to certain phenotype definitions and some of these significant associations were very small (Figure 1, eTable 3): PGC PTSD v2.5→ADHD (IVW Beta=0.456, 95% CI [0.205-0.708], P=3.72x10−4); MVP PCL-Total→ADHD (IVW Beta=0.005, 95% CI [0.002-0.008], P=8.13x10−4); MVP PTSD Case/Control→ADHD (IVW Beta=0.024, 95% CI [0.011-0.038], P=4.51x10−4). Results of additional MR analyses are described in the eResults.

Multivariable Mendelian Randomization Analysis of ADHD effect on PTSD

RTB, household income, EA, and lifetime trauma were evaluated for a two-sample univariable association on PTSD as measured by the PCL-17. eTable 6 describes the PGS analysis defining each genetic instrument for univariable two-sample MR between covariate traits and PCL-17. RTB, household income, EA and lifetime trauma all exhibited significant associations with PCL-17 (eTable 5). In the MVMR analysis simultaneously considering all confounders and mediators, the effect of ADHD on PCL-17 (IVW Beta=0.372, 95% CI [0.191-0.524], P=0.001) was independent of other variables tested with no difference in effect size magnitude relative to the univariable estimate (Pdiff=0.62; eTables 5 and 7). The multivariable did not nullify the associations of any other phenotype but significantly reduced the association of RTB (Pdiff=9.32x10−30) and household income (Pdiff=5.99x10−12) on PCL-17 (eTable 7).

Association of ADHD with PTSD based on a Population-based Sibling Comparison Design

Among 2,082,118 individuals (1,518,115 individuals nested within 665,342 families with at least 2 siblings [M=2.28, range=2-15]), 79,006 (3.79%) were diagnosed with ADHD (see Table 1). Individuals with ADHD had a higher prevalence of PTSD (Prevalence=15.02, 95% CI [14.19-15.9]) compared with those without ADHD (Prevalence=1.62, 95% CI [1.56-1.67]; prevalence ratio=9.30, 95% CI [8.70, 9.93]). Since the proportionality assumption was not met for the variable sex, we stratified the analyses on sex to accommodate a distinct baseline hazard function for each stratum level. In the crude model, individuals diagnosed with ADHD showed an increased rate of PTSD compared to undiagnosed HR=6.92, 95% CI [6.34-7.56]. The association between ADHD and PTSD attenuated after adjustment for demographic factors, cumulative traumatic events, and RTB HR=4.32, 95% CI [3.93-4.75]. This association was similar between males and females (HRmales=4.44, 95% CI [3.98-4.96], HRfemales=3.79, 95% CI [3.16-4.55]), with no statistically significant differences between them (p=0.154). Results from the sibling comparison showed an increased risk for developing PTSD in individuals diagnosed with ADHD compared to their undiagnosed full siblings, HR=2.37, 95% CI [1.58-3.55] after adjustments (see Figure 2).

Table 1.

Descriptive statistics for population-based sibling study

Characteristic Without ADHD
(N = 2,003,112)		 With ADHD
(N = 79,006)
Person-years 21,436,933 912,035
Sex
  Females 985,912 (49.22%) 25,505 (32.28%)
  Males 1,017,200 (50.78%) 53,501 (67.72%)
Parental education
  High 464,991 (23.68%) 10,555 (13.74%)
  Low 290,567 (14.79%) 16,632 (21.66%)
  Medium 1,208,479 (61.53%) 49,605 (64.60%)
  No information 39,075 2,214
Disposable income (SEK) parental 2,119 (1,669, 2,634) 1,924 (1,441, 2,396)
  No information 39,075 2,214
Traumatic events
  Sexual abuse 4,508 (0.23%) 889 (1.13%)
  Fire or explosion 20,409 (1.02%) 1,336 (1.69%)
  Transportation accident 153,933 (7.68%) 10,271 (13.00%)
  Exposure to toxic substance 181,797 (9.08%) 15,082 (19.09%)
  Traumatic brain injury 107,552 (5.37%) 7,260 (9.19%)
  Physical assault 13,043 (0.65%) 1,734 (2.19%)
  Assault with a weapon 2,403 (0.12%) 391 (0.49%)
  Death of a family member < 18 45,758 (2.28%) 3,312 (4.19%)
Risk-taking behaviors
  Criminal conviction 114,875 (5.73%) 15,053 (19.05%)
  Pregnancy before age 18 2,201 (0.11%) 332 (0.42%)
  Divorce before age 20 201 (0.01%) 22 (0.03%)
  Marriage before age 18 612 (0.03%) 27 (0.03%)
PTSD
  Without PTSD 1,999,875 (99.84%) 77,819 (98.50%)
  With PTSD 3,237 (0.16%) 1,187 (1.50%)
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Figure 2. Effect of ADHD on PTSD based on a Population-based Sibling Comparison Design.

Figure 2.

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Hazard ratio and 95% confidence interval (CI) for the association between attention deficit hyperactivity disorder (ADHD) and posttraumatic stress disorder (PTSD).

Discussion

Most of the data suggesting an association between ADHD and PTSD risk are from observational studies (3). While statistical associations do not imply causality, the hypothesis that ADHD is an antecedent risk factor for PTSD is supported by findings that ADHD onset was consistently observed earlier than PTSD onset (33). With two-sample MR and population-based sibling comparisons, we found consistent evidence for an association between ADHD genetic liability and an increased risk of PTSD. Importantly, we demonstrate that the positive relationship between ADHD and PTSD is concordant across several MR methods that apply various adjustments to account for different pleiotropic scenarios that may affect the instrumental variables. In line with these findings, studies of trauma-exposed cohorts found a significantly increased risk of PTSD in those with ADHD (3). This indicates that the increased risk for PTSD in individuals with ADHD cannot be explained solely by an increased rate of trauma exposure in this population or RTB tendencies, household income, or EA in individuals with ADHD (34) or PTSD (35). While we observed support for mediation by these factors, more research is needed to identify the role of plausible mediators. This is important as it may lead to new secondary prevention targets.

Conversely, our findings regarding the association with PTSD on ADHD were highly inconsistent. In most of the cases, the associations observed are null or very small. This could be explained by the genetic effects shared across the psychopathology spectrum and is potentially in line with the controversy around the idea that ADHD could arise de novo in adulthood. Population-based studies suggested that ADHD in adulthood may be idiopathic and that the adult-onset form of the disorder is categorically different from the childhood-onset form (36-38). However, adult-onset ADHD is rare and usually arises in the context of a complex psychiatric history and not on its own (39). Thus, our findings might reflect these differences by observing an increased risk of ADHD in individuals with PTSD depending on ADHD age of onset and psychiatric comorbidity. In other words, our results indicate that individuals diagnosed with ADHD are clearly at a higher risk to develop PTSD later in life while the risk of individuals diagnosed with PTSD to develop subsequently ADHD seems much more rare and likely to be negligible. The most common scenario underlying the comorbidity of ADHD and PTSD can accordingly be estimated as an initial ADHD diagnosis followed by a PTSD diagnosis. Preventative efforts should therefore primarily focus on this directionality.

Although causal factors underlying the association between ADHD and PTSD remain unclear, several possibilities can be considered. Preclinical work in rodents indicated prenatal nicotine exposure to result in an ADHD-like phenotype (40) in mice as well as impairment in fear extinction learning (41), traits strongly resembling the fear extinction deficiencies of patients (42). In humans, abnormalities in fear circuits during extinction learning and extinction recall (43) similar to those documented in PTSD have been observed in individuals with ADHD (44). A long-lasting effect of methylphenidate on fear extinction has been described (45), suggesting that adequate treatment of ADHD might lower the subsequent risk of developing PTSD in individuals with ADHD; however, the permissive effects of ADHD medications have also been described (5). Preliminary data also suggests a therapeutic benefit of methylphenidate in treatment of PTSD (46). Further research is needed to better understand the neurobiological underpinnings that are common to ADHD and PTSD. Such research could more accurately describe vulnerable neural circuitry that may be helpful in the development of targeted prevention and treatment strategies for PTSD in individuals with ADHD.

Our findings could have an important clinical impact by encouraging clinicians to screen for PTSD in individuals with ADHD and/or monitor its symptoms more closely. By underlining the increased risk for PTSD in ADHD our results might help guide the development of screening and preventative efforts, potentially reaching individuals at high risk. This relationship was independent of several covariates and mediating variables. Most notably of which was the large causal effect of RTB on PCL-Total. While RTB is one major behavioral source of exposure to traumatic experiences, it also strongly correlates with the externalizing behaviors commonly observed in individuals diagnosed with ADHD. This might be of particular interest considering the recent traumatic event of the COVID-19 pandemic. The extent to which the presence of ADHD may define a PTSD subtype that might benefit from different treatments needs to be explored in future research.

Our study investigating the relationship between ADHD and PTSD has several strengths. We conducted a causal inference analysis using the largest available GWAS that showed a consistent causal association between ADHD and PTSD assessed in cohorts developed using different study designs (12, 14). We also used complementary two-sample MR methods for sensitivity analysis (47). The MVMR analysis enabled us to establish that the association of ADHD with PTSD could not be accounted for by many potential confounding factors (RTB, household income, EA, and lifetime trauma). Additionally, the sibling comparison analyses permitted us to rule out any potential familial confounding effects. Finally, the population-based cohort design provided additional context to the ADHD→PTSD findings by extending the associations from military and clinical samples (who were primarily included in the GWASs) to the general population.

There are also limitations to this study. Different measures were used to define ADHD, PTSD, and confounding factors across analyses. The population-based study ADHD diagnoses relied on register-based records and an overestimation of the association between ADHD and PTSD is possible as more severely affected individuals are more likely to seek treatment. Similarly, the population-based sibling comparison cohort was significantly younger than the individuals included in the GWAS samples. However, despite this age discrepancy, we observed a remarkable consistency in our findings. Future studies could benefit from longitudinal cohort studies involving a deeper clinical phenotyping to supplement register-based records. While we were able to examine specific symptom dimensions of PTSD in our MR analyses, we could not assess the impact of specific symptom dimensions of ADHD or age of onset, because no well-powered GWAS were available for these phenotypes, to our knowledge (48). Large differences in the effect magnitude of ADHD symptom dimensions on PTSD may attenuate the overall estimates for the unstratified analysis. Although our different sensitivity analyses did not indicate the presence of relevant biases, our MR and sibling comparison findings could still be affected by unmeasured confounders. Therefore, our findings, while largely consistent across methods, cannot definitively establish a causal relationship of ADHD with subsequent PTSD. Finally, the analyses were conducted using GWAS data of European ancestry and the Swedish population, thus the generalizability of our results to other populations might be limited.

This MR and population-based sibling comparison study found robust evidence for an association between ADHD and increased risk for PTSD. The findings are clinically relevant because they may help identify individuals who are at high risk of developing PTSD and may benefit from preventive efforts.

Supplementary Material

Supplemental Tables
Supplemental Text

Table 2.

Summary of the results from the Cox proportional hazards model

Overall Males Females Sibling
analysis		 Siblings, age
difference
<11years		 Siblings, age
difference
<6years
Unadjusteda 6.92
(6.34-7.56)		 5.51
(4.64-6.55)		 7.57
(6.83-8.39)		 - - -
Confoundersb 6.72
(6.14-7.36)		 5.20
(4.35-6.22)		 7.39
(6.65-8.20)		 2.81
(1.94-4.05)		 2.75
(1.90-3.97)		 2.78
(1.89-4.09)
Fully adjustedc 4.32
(3.93-4.75)		 4.44
(3.98-4.96)		 3.79
(3.16-4.55)		 2.37
(1.62-3.47)		 2.33
(1.59-3.42)		 2.37
(1.58-3.55)
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Results are shown as hazard ratios including the 95% confidence interval in brackets.

a

Model adjusted for year and sex.

b

Model adjusted for year, sex, disposable parental income, and parental education.

c

Model adjusted for year, disposable parental income, cumulative count traumatic events, parental education, early marriage, early divorce, early pregnancy, and criminal conviction.

KEY RESOURCES TABLE

Resource Type Specific Reagent or Resource Source or Reference Identifiers Additional Information
Add additional rows as needed for each resource type Include species and sex when applicable. Include name of manufacturer, company, repository, individual, or research lab. Include PMID or DOI for references; use “this paper” if new. Include catalog numbers, stock numbers, database IDs or accession numbers, and/or RRIDs. RRIDs are highly encouraged; search for RRIDs at https://scicrunch.org/resources. Include any additional information or notes if necessary.
Other both sexes included PGC-PTSD GWAS, PMID: 31594949, 34865855
Other both sexes included MVP-PTSD GWAS, PMID: 33510476
Other both sexes included PGC-ADHD GWAS, PMID: 30478444
Other both sexes included Sweden’s Total Population Register (STPR) and the Case of Death Register, PMID: 20949391
Software; Algorithm not applicable LDSC, PMID: 26414676
Software; Algorithm not applicable PRSice, PMID: 25550326
Software; Algorithm not applicable TwoSampleMR, PMID: 29846171
Software; Algorithm not applicable MR-RAPS, DOI: 10.1214/19-AOS1866
Software; Algorithm not applicable MendelianRandomization, PMID: 25632051
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Acknowledgement

Funding/Support: This study was funded by the National Institutes of Health (R21 DC018098, R33 DA047527, and F32 MH122058) and the Canadian Institute for Health Research (CIHR) Canadian Research Chairs (CRC) stipend (award number 1024586). Financial support for the PGC-PTSD was provided by the Cohen Veterans Bioscience, Stanley Center for Psychiatric Research at the Broad Institute, One Mind, and the National Institute of Mental Health (NIMH; R01MH106595, R01MH124847, R01MH124851). Michel G. Nivard is supported by NIMH grant R01MH120219, ZonMW grants 849200011 and 531003014 from The Netherlands Organisation for Health Research and Development, a VENI grant awarded by NWO (VI.Veni.191G.030) and is a Jacobs Foundation Fellow.

Role of the Funder/Sponsor:

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

List of PGC-PTSD consortium authors

Adam X. Maihofer, Karmel W. Choi, Jonathan R.I. Coleman, Nikolaos P. Daskalakis, Christy A. Denckla, Elizabeth Ketema, Rajendra A. Morey, Renato Polimanti, Andrew Ratanatharathorn, Katy Torres, Aliza P. Wingo, Clement C. Zai, Allison E. Aiello, Lynn M. Almli, Ananda B. Amstadter, Soren B. Andersen, Ole A. Andreassen, Paul A. Arbisi, Allison E. Ashley-Koch, S. Bryn Austin, Esmina Avdibegovic, Anders D. Borglum, Dragan Babic, Marie Bækvad-Hansen, Dewleen G. Baker, Jean C. Beckham, Laura J. Bierut, Jonathan I. Bisson, Marco P. Boks, Elizabeth A. Bolger, Bekh Bradley, Meghan Brashear, Gerome Breen, Richard A. Bryant, Angela C. Bustamante, Jonas Bybjerg-Grauholm, Joseph R. Calabrese, Jose Miguel Caldas-de-Almeida, Chia-Yen Chen, Anders M. Dale, Shareefa Dalvie, Jürgen Deckert, Douglas L. Delahanty, Michelle F. Dennis, Seth G. Disner, Katharina Domschke, Laramie E. Duncan, Alma Dzubur Kulenovic, Christopher R. Erbes, Alexandra Evans, Lindsay A. Farrer, Norah C. Feeny, Janine D. Flory, David Forbes, Carol E. Franz, Sandro Galea, Melanie E. Garrett, Aarti Gautam, Bizu Gelaye, Joel Gelernter, Elbert Geuze, Charles F. Gillespie, Aferdita Goci Uka, Scott D. Gordon, Guia Guffanti, Rasha Hammamieh, Michael A. Hauser, Andrew C. Heath, Sian M.J. Hemmings, David Michael Hougaard, Miro Jakovljevic, Marti Jett, Eric Otto Johnson, Ian Jones, Tanja Jovanovic, Xue-Jun Qin, Karen-Inge Karstoft, Milissa L. Kaufman, Ronald C. Kessler, Alaptagin Khan, Nathan A. Kimbrel, Anthony P. King, Nastassja Koen, Henry R. Kranzler, William S. Kremen, Bruce R. Lawford, Lauren A. M. Lebois, Catrin Lewis, Israel Liberzon, Sarah D. Linnstaedt, Mark W. Logue, Adriana Lori, Bozo Lugonja, Jurjen J. Luykx, Michael J. Lyons, Jessica L. Maples-Keller, Charles Marmar, Nicholas G Martin, Douglas Maurer, Matig R. Mavissakalian, Alexander McFarlane, Regina E. McGlinchey, Katie A. McLaughlin, Samuel A. McLean, Divya Mehta, Rebecca Mellor, Vasiliki Michopoulos, William Milberg, Mark W. Miller, Charles Phillip Morris, Ole Mors, Preben Bo Mortensen, Elliot C. Nelson, Merete Nordentoft, Sonya B. Norman, Meaghan O'Donnell, Holly K. Orcutt, Matthew S. Panizzon, Edward S. Peters, Alan L. Peterson, Matthew Peverill, Robert H. Pietrzak, Melissa A. Polusny, John P. Rice, Victoria B. Risbrough, Andrea L. Roberts, Alex O. Rothbaum, Barbara O. Rothbaum, Peter Roy-Byrne, Kenneth J. Ruggiero, Ariane Rung, Bart P. F. Rutten, Nancy L Saccone, Sixto E. Sanchez, Dick Schijven, Soraya Seedat, Antonia V. Seligowski, Julia S. Seng, Christina M. Sheerin, Derrick Silove, Alicia K Smith, Jordan W. Smoller, Scott R. Sponheim, Dan J. Stein, Jennifer S. Stevens, Martin H. Teicher, Wesley K. Thompson, Edward Trapido, Monica Uddin, Robert J. Ursano, Leigh Luella van den Heuvel, Miranda Van Hooff, Eric Vermetten, Christiaan Vinkers, Joanne Voisey, Yunpeng Wang, Zhewu Wang, Thomas Werge, Michelle A. Williams, Douglas E. Williamson, Sherry Winternitz, Christiane Wolf, Erika J. Wolf, Rachel Yehuda, Keith A. Young, Ross McD. Young, Hongyu Zhao, Lori A. Zoellner, Magali Haas, Heather Lasseter, Allison C. Provost, Rany M Salem, Jonathan Sebat, Richard Shaffer, Tianying Wu, Stephan Ripke, Mark J. Daly, Kerry J. Ressler, Karestan C. Koenen, Murray B. Stein, Caroline M. Nievergelt.

Footnotes

Conflict of Interest Disclosures: Henrik Larsson reports receiving grants from Shire Pharmaceuticals; personal fees from and serving as a speaker for Medice, Shire/Takeda Pharmaceuticals and Evolan Pharma AB; and sponsorship for a conference on attention-deficit/hyperactivity disorder from Shire/Takeda Pharmaceuticals and Evolan Pharma AB, all outside the submitted work. Murray B. Stein has in the past 3 years received consulting income from Actelion, Acadia Pharmaceuticals, Aptinyx, atai Life Sciences, Boehringer Ingelheim, Bionomics, BioXcel Therapeutics, Eisai, Clexio, EmpowerPharm, Engrail Therapeutics, GW Pharmaceuticals, Janssen, Jazz Pharmaceuticals, and Roche/Genentech. Dr. Stein has stock options in Oxeia Biopharmaceuticals and EpiVario. He is paid for his editorial work on Depression and Anxiety (Editor-in-Chief), Biological Psychiatry (Deputy Editor), and UpToDate (Co-Editor-in-Chief for Psychiatry). Renato Polimanti and Joel Gelernter are paid for their editorial work on the journal Complex Psychiatry. The other authors report no conflict of interest.

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