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. Author manuscript; available in PMC: 2024 Feb 1.
Published in final edited form as: J Nerv Ment Dis. 2022 Aug 24;211(2):100–107. doi: 10.1097/NMD.0000000000001584

Inhibition Predicts the Course of Depression and Anxiety Symptoms among Adolescents: The Moderating Role of Familial Risk

Elizabeth S Stevens 1, Carter J Funkhouser 1, Randy P Auerbach 2,3, Ardesheer Talati 2,3, Marc G Gameroff 2,3, Jonathan E Posner 2,3, Myrna M Weissman 2,3, Stewart A Shankman 4
PMCID: PMC9892173  NIHMSID: NIHMS1823852  PMID: 36044650

Abstract

Numerous theoretical models suggest that inhibition difficulties – the inability to moderate automatic responses – contribute to the onset and/or maintenance of internalizing symptoms. Inhibition deficits and internalizing disorders run in families and share overlapping genetic risk factors, suggesting that inhibition deficits may be particularly prognostic of internalizing symptoms in those with high familial risk. This study tested this hypothesis in a longitudinal sample during the transition from adolescence to early adulthood. As hypothesized, prospective associations between inhibition and anxiety and depressive symptoms eight years later were moderated by familial risk for depression. Specifically, poorer inhibition prospectively predicted greater anxiety and depressive symptoms in those at high (but not low) familial risk for MDD. These findings provide preliminary support for impaired inhibition as an indicator of risk for later internalizing symptoms in those at high familial risk.

Keywords: depression, anxiety, inhibitory control, vulnerability, adolescence

Anxiety and depression symptoms are highly prevalent, frequently co-occur (Kessler et al., 2005; Shankman & Klein, 2003), and are associated with high socioeconomic and disease burden (Greenberg et al., 2003; Kessler et al., 2009). These symptoms often begin during adolescence or young adulthood (Kessler et al., 2007), suggesting that identifying early vulnerability factors may help mitigate potential personal and societal costs. This goal is also consistent with NIMH's Research Domain Criteria (RDoC) initiative, which seeks to identify shared and/or unique vulnerabilities for psychopathologies with the goal of informing intervention and prevention efforts (Zalta & Shankman, 2016).

Individual differences in inhibition abilities may be one such vulnerability marker for depression and anxiety symptoms (Snyder et al., 2019). Inhibition can be defined as the ability to modulate prepotent/automatic responses to (a) respond in a goal-congruent manner, and/or (b) limit the influence of distracting stimuli on task performance (Friedman & Miyake, 2004; Miyake et al., 2000; Nigg, 2000). Inhibition is one executive function (Friedman & Miyake, 2004; Miyake et al., 2000), a set of higher-order processes that coordinate or integrate lower-level cognition and behavior, and help individuals allocate optimal levels of attention to salient stimuli and facilitate effective responding across contexts.

Inhibitory control is closely linked to emotion regulation, which is implicated in the development of symptoms of anxiety and depression (Cisler et al., 2010; Joormann & Gotlib, 2010). Numerous studies and theoretical models (for review, see De Raedt & Koster, 2010; Eysenck et al., 2007) posit a central role of compromised inhibitory processes and the related constructs of attentional control and emotion (dys)regulation in anxiety and depressive symptoms. For example, individuals with elevated anxiety symptoms exhibit poorer attentional control and/or inhibition as measured via self-report (e.g., Cox & Olatunji, 2017) or behavioral tasks (e.g., Stroop task, go-no-go tasks; Gorlin & Teachman, 2015; Zainal & Newman, 2017). Anxiety symptoms are also associated with attentional biases that may reflect underlying attentional control deficits (Bar-Haim et al., 2007). Similar results have been found for major depressive disorder (MDD; Gotlib & Joormann, 2010), particularly in youth, with one meta-analysis finding that inhibition (measured via the Stroop Interference Test) was the facet of executive functioning most strongly associated with depression (d = .77; Wagner et al., 2015). Longitudinal studies further support inhibitory functioning as a vulnerability factor for internalizing psychopathology. Among children and adolescents, poorer performance on behavioral tasks indexing inhibitory control predicted greater likelihood of developing MDD (Bufferd et al., 2014; Stange et al., 2016) and anxiety disorders (Muris, 2006; Oldehinkel et al., 2007; Zainal et al., 2017). Additionally, longitudinal neuroimaging studies have demonstrated that greater activation in brain regions associated with inhibition (e.g., medial prefrontal cortex) predict course of illness (Langenecker et al., 2018; White et al., 2018). Emotion (dys)regulation may play a mechanistic role in the association between inhibitory control deficits and psychopathology. For instance, difficulty inhibiting negative or goal-irrelevant information and removing this information from working memory may lead to maladaptive emotion regulation strategies (e.g., repetitive negative thinking; Joormann & Gotlib, 2010), which in turn are thought to increase risk for multiple psychopathologies (Synder et al., 2019).

Inhibition may also represent a familial vulnerability factor for anxiety and depression symptoms. Twin and family studies have shown that performance on neurocognitive tasks measuring inhibitory functioning (Friedman et al., 2018; Routledge et al., 2017) and anxiety and depressive symptoms (Kendler et al., 2003) are significantly heritable. Moreover, twin studies indicate that these symptoms and inhibition share partially overlapping genetic risk factors (Friedman et al., 2018; Gustavson et al., 2019; Routledge et al., 2017), suggesting that some genetic factors increase risk for both anxiety/depressive symptoms and inhibition difficulties. Given that inhibition may be a familial vulnerability factor, the prognostic association between inhibition and internalizing psychopathology may be specific to (or stronger for) those with a family history of psychopathology. Davidovich et al. (2016) found that adolescents who had reduced inhibitory control during an affective go/no go task and parents with recurrent MDD reported more depressive symptoms themselves compared to adolescents with intact inhibitory control. This study, however, was cross-sectional and no study to our knowledge has examined the interactive effect of family history and inhibition deficits on longitudinal outcomes.

The aims of the present study were the following. First, we examined concurrent and prospective associations between inhibitory control and symptoms of anxiety and depression, hypothesizing that impaired inhibitory control would be associated with greater symptoms. Second, we examined familial risk as a moderator, hypothesizing that the prospective associations between poorer inhibitory control and greater anxiety and depressive symptoms would be stronger in individuals at high familial risk for psychopathology.

Method

Participants

Participants were enrolled in a longitudinal, three-generation cohort study of families at high or low risk for MDD. Details of the sample have been reported elsewhere (Weissman et al., 2016). Briefly, probands (i.e., generation 1; G1) with a history of MDD were recruited from outpatient psychiatric clinics. Inclusion criteria required that probands within this group had at least one depressive episode that lasted at least four weeks, was at least moderate in severity, caused noticeable role impairment, and prompted outpatient treatment. Exclusion criteria for this group included a history of bipolar disorder, schizophrenia, or primary substance abuse disorder (Weissman et al., 2016). All G1s in this group had onset of MDD before age 40, and most before age 30. A second group of probands with no history of psychiatric illness/treatment were simultaneously selected from the same community. Offspring of G1s (i.e., G2s) were also enrolled. Participants completed up to seven waves of interviews and assessments over thirty years, and biological grandchildren of G1 probands (i.e., G3) were assessed beginning at wave 3. There were no cases of bipolar disorder or schizophrenia in any of the three generations. Procedures and training remained similar across all waves to minimize method variance. All study procedures were approved by the institutional review board at New York State Psychiatric Institute/Columbia University. Written informed consent was obtained from adults for themselves and minors, and verbal assent was obtained from minors.

The present study focused on G3s, as they were in the prime risk window for onset/escalation of internalizing psychopathology (Mage = 16.1, SD = 5.2; Kessler et al., 2005). Participants whose grandparents had no lifetime history of MDD were categorized as “low-risk” for psychopathology, while participants with one or more grandparent with a history of MDD were categorized as “high-risk” for psychopathology (Weissman et al., 2016).1 G3s who completed both the Simon task (described below) and diagnostic interviews were included in the present sample. One participant was excluded for poor Simon task data quality, yielding a final sample consisting of 21 high-risk and 27 low-risk participants (N=48). Demographic and clinical characteristics are presented in Table 1.

Table 1.

Sample demographic and clinical characteristics.

Characteristic N (%) or M (SD)
Sex (% Female) 23 (47.9%)
% High Familial Risk 21 (43.8%)
Baseline Follow-Up
Age 16.05 (5.22) 24.40 (5.34)
% Lifetime Anxiety Disorder 21 (43.8%) 21 (43.8%)
% Lifetime MDD 9 (18.8%) 16 (33.3%)
Anxiety Symptomsa 4.51 (5.18) 1.56 (2.78)
Depression Symptomsb 3.95 (4.61) 2.05 (3.52)
Processing Speed Standard Score - 10.15 (2.64)
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Note:

a

Hamilton Rating Scales for Anxiety/Revised Child Manifest Anxiety Scale.

b

Hamilton Rating Scales for Depression/Children's Depression Rating Scale. MDD = Major Depressive Disorder. Processing speed assessed from WISC/WAIS Coding.

Measures

Psychiatric Assessments.

The present study used data from waves 5 and 6, completed approximately eight years apart. Diagnoses were obtained at all waves using age-appropriate versions of the Schedule for Affective Disorders and Schizophrenia-Lifetime Version (Kaufman et al., 1997; Mannuzza et al., 1986; Orvaschel et al., 1982) using best estimate procedures (Leckman et al., 1982), which involved independent review of all assessments by experienced, doctoral-level clinicians. Parents and children separately rated symptoms for participants under 18. Interviews assessed the time-period since the previous interview (or since birth, for initial interviews), facilitating the ascertainment of lifetime diagnoses.

Current depression and anxiety symptoms were also assessed at baseline and eight years after baseline. Depressive symptoms were measured using the Hamilton Rating Scales for Depression (Ham-D; Hamilton, 1967) if the participant was an adult or the Children's Depression Rating Scale (CDRS; Poznanski et al., 1985) if the participant was a minor. Anxiety symptoms were assessed using either the Hamilton Rating Scales for Anxiety (Ham-A; Hamilton, 1959) for adults or the Revised Child Manifest Anxiety Scale (RCMAS; Perrin & Last, 1992) for minors. To merge the adult and child assessments of the same construct, the adult and children’s measures were combined into variables reflecting either depression symptom severity or anxiety symptom severity by standardizing the corresponding adult and child scores (e.g., the Ham-D and CDRS for depression) within the sample and merging them.

Cognitive Functioning.

Processing speed was assessed at wave 6 (i.e., eight years after baseline) using the Coding subtest from the Wechsler Intelligence Scale for Children (WISC-IV; Wechsler et al., 2004) or Adults (WAIS-IV; Wechsler, 2008), depending on the participant’s age. Processing speed was included as a covariate to minimize the confounding effect of processing speed in Simon performance. Coding scores on the WISC and WAIS were converted to age-adjusted standard scores, then combined and standardized to create a single index of processing speed.

Simon Task.

The Simon task, a widely used behavioral measure of inhibition, was administered during an fMRI scan at baseline (i.e., wave 5). Visual stimuli were presented via E-Prime software 1.1 (Psychology Software Tools, Inc., Sharpsburg, PA, USA) in 10 blocks of 102 trials each. For each trial, an arrow pointing either left or right was displayed either to the left or right of a fixation cross positioned at midline. Participants were instructed to indicate the direction of the arrow as quickly as possible by pressing a response box button, and reaction time (RT) was recorded. Each arrow was presented for 1300ms, with an interstimulus interval of 350ms. Most trials were ‘congruent,’ wherein arrows pointed in the same direction as their position on the screen (e.g., right-pointing arrow presented to the right of midline). Approximately 7% of trials were ‘incongruent,’ wherein arrows pointed in the direction opposite their position on the screen (e.g., left-pointing arrow presented to the right of midline). The incongruent condition is cognitively more difficult and taps inhibitory control whereas the congruent condition indexes general task performance. Incongruent trials were spaced pseudorandomly every 13-16 congruent trials. There were relatively few incorrect responses in each condition (Mcongruent = 13.3, SD = 19.4; Mincongruent = 13.9, SD = 9.03). Only correct trials were used in analyses to increase the homogeneity of included trials.

RTs were averaged separately for the congruent and incongruent conditions. Analyses of RT averages assumes that RT data are normally distributed. However, research suggests that RT data are not normally distributed and instead are best fit by an exponentially-modified Gaussian (“ex-Gaussian”) distribution that reflects a combination of a normal (i.e., Gaussian) distribution and an exponential distribution that rises rapidly on the left side of the distribution and has a long tail to the right (e.g., Balota & Spieler, 1999). Ex-Gaussian distributions can be characterized using three parameters (mu, sigma, and tau) thought to reflect distinct (albeit correlated) processes. Mu represents the mean of the normal portion of the distribution and reflects average response time. Sigma represents the standard deviation of the normal portion of the distribution and reflects variability in response time. Tau captures the mean of the exponential portion of the distribution and reflects extreme (i.e., slow) responses at the tail of the distribution. Tau is thought to be influenced by attentional lapses and central decision-making processes (Hohle, 1965) and be especially reflective of inhibitory control abilities. Supporting this interpretation, tau (but not mu or sigma) has consistently discriminated between groups that are known to differ in inhibitory control (e.g., young adults versus older adults, individuals with versus without attention deficit/hyperactivity disorder; West et al., 2002; Leth-Steensen et al., 2000).

An ex-Gaussian distribution was fit to each participant’s data using the R package retimes (Massidda, 2013). Following procedures from studies examining RT data from a similar task (Bondy et al., 2018), ex-Gaussian parameters were estimated for each participant and condition via a bootstrapping approach (5,000 iterations) using maximum likelihood and implementing the Simplex method to establish the minimum of the objective function. Mu was obtained with a Gaussian kernel estimator (Van Zandt, 2000), and tau was then selected within the bootstrapped values based on maximum likelihood criterion. Sigma was not examined in this study because it has demonstrated poor retest reliability and validity (Bondy et al., 2018).

Data Analyses

Analyses were a series of multiple regression models. All models adjusted for participants’ age, sex, and processing speed (WISC/WAIS Coding standard scores) as these variables were associated with average RT in the incongruent condition (∣r∣s = .10−.43). Processing speed was also moderately associated with tau in the congruent condition (r = −.39, p = .006) and mu in the incongruent condition (r = −.37, p = .011), but was not significantly related to tau in the incongruent condition (r = −.09, p = .557) or mu in the congruent condition (r = −.21, p = .156; see Table 2). This approach increased the specificity of our findings to inhibitory control separate from processing speed. We also included the corresponding parameter from the congruent condition as a covariate to control for general task performance. Unsurprisingly, participants’ mean RTs in congruent and incongruent trials were highly correlated (r = .87, p < .001). Neither tau (r = .00, p = .977) nor mu (r = .12, p = .406) were significantly correlated across congruent and incongruent trials, however, supporting the inclusion of the two conditions as separate predictors when examining the effects of tau or mu. All longitudinal models additionally adjusted for baseline symptom severity by covarying for baseline scores on the dependent variable (i.e., either anxiety or depressive symptoms). All predictor variables were standardized.

Table 2.

Correlations between study variables.

Variable 1 2 3 4 5 6 7 8 9 10 11
1. Baseline anxiety Sx – – – – – – – – – – –
2. Baseline depressive Sx .72*** – – – – – – – – – –
3. Follow-up anxiety Sx .27 .31+ – – – – – – – – –
4. Follow-up depressive Sx .05 .22 .64*** – – – – – – – –
5. Tau congruent .04 −.23 −.09 .06 – – – – – – –
6. Tau incongruent .29+ .24 .39* .34* .00 – – – – – –
7. Mu congruent .13 .31+ .47** .31+ −.25+ .14 – – – – –
8. Mu incongruent −.21 −.30+ −.03 .08 .54*** −.42** .12 – – – –
9. Sex −.36* −.38* −.08 .07 .28+ .06 .00 .32* – – –
10. Baseline age .07 .05 −.02 .06 −.03 .12 −.34* −.21 .35* – –
11. Processing speed .06 .02 −.13 −.27+ −.39** −.09 −.21 −.37* .10 .17 –
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Note. Correlations involving sex are point biserial correlations; all other correlations are Pearson correlations. Sx = symptoms.

***

p < .001

**

p < .01

*

p < .05

+

p < .10.

Separate models were run for anxiety and depression and for tau and mu. In the first set of models, we examined cross-sectional associations between tau or mu and symptoms by regressing baseline anxiety symptoms (Ham-A/RCMAS) or depressive symptoms (Ham-D/CRSD) on the above covariates and tau or mu. Second, to examine prospective associations between tau or mu and subsequent symptoms, we ran similar models predicting anxiety symptoms (Ham-A/RCMAS) or depressive symptoms (Ham-D/CRSD) approximately eight years later. The prospective models included covariates (age, sex, processing speed, participants’ personal and familial risk status) and tau or mu as predictors. Subsequent models testing the moderating effects of familial risk included the interaction between tau or mu and familial risk as an additional predictor. Simple slopes testing was employed to probe significant interactions.

Finally, half of the sample (n = 24) met lifetime criteria for an anxiety disorder (panic disorder, specific phobia, social phobia, obsessive-compulsive disorder, posttraumatic stress disorder, or separation anxiety disorder) or MDD at baseline. Examining individuals with and without a personal history of an internalizing disorder obfuscates whether inhibitory control deficits are a risk marker versus a state or scar marker observed in individuals with a history of anxiety or depression (Zeiss & Lewinsohn, 1988). To examine whether inhibitory control deficits might be a risk marker for anxiety and/or depressive symptoms, we conducted exploratory sensitivity analyses testing these cross-sectional and prospective associations only in participants who had not did not meet lifetime criteria for an anxiety disorder or MDD at baseline.

Results

Cross-Sectional and Prospective Associations between Inhibitory Control and Symptoms

Table 3 contains results for the cross-sectional models. Independent of tau in the congruent condition, tau in the incongruent condition was positively associated with anxiety symptoms (β = .31, 95% CI [.01, .60], p = .047). The association between tau in the incongruent condition and depressive symptoms was not significant (β = .24, 95% CI [−.07, .55], p = .136). Mu in the incongruent condition was unrelated to anxiety or depressive symptoms (ps > .188). Cross-sectional associations between symptoms and tau or mu in the congruent condition were nonsignificant, with the exception that mu in the congruent condition was associated with depressive symptoms (β = .41, 95% CI [.10, .72], p = .012).

Table 3.

Cross-sectional associations between inhibitory control and internalizing symptoms.

Relation with Anxiety
Symptoms 		Relation with Depression
Symptoms
Predictor β 95% CI p β 95% CI p
Tau
 Covariates
  Sex −.40 [−.71, −.08] .017 −.29 [−.62, .04] .085+
  Age .12 [−.19, .43] .452 .10 [−.22, .43] .527
  Processing Speed .18 [−.15, .51] .287 −.03 [−.37, .32] .881
  Tau Congruent .20 [−.13, .53] .232 −.17 [−.52, .17] .326
 Inhibitory Control
  Tau Incongruent .31 [.01, .60] .047 .24 [−.07, .55] .136
Mu
 Covariates
  Sex −.33 [−.64, .01] .062+ −.30 [−.62, .03] .074+
  Age .21 [−.14, .57] .241 .23 [−.11, .56] .180
  Processing Speed .07 [−.27, .41] .683 .00 [−.34, .35] .982
  Mu Congruent .23 [−.11, .56] .181 .41 [.10, .72] .012
 Task Performance Speed
  Mu Incongruent −.08 [−.44, .28] .669 −.23 [−.56, .11] .188
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Note. Processing speed assessed from WISC/WAIS Coding.

+

p < .10. p < .05 is denoted by bolding.

Longitudinal models (Table 4) indicated that greater tau in the incongruent condition predicted greater subsequent anxiety symptoms at follow-up (β = .33, 95% CI [.02, .64], p = .042). As in the cross-sectional models, tau in the incongruent condition did not significantly predict depressive symptoms at follow-up (β = .27, 95% CI [−.05, .59], p = .104). Mu in the incongruent condition did not prospectively predict anxiety or depressive symptoms (ps > .624). Tau and mu in the congruent condition did not prospectively predict anxiety or depressive symptoms, with the exception that mu in the congruent condition significantly predicted anxiety symptoms (β = .49, 95% CI [.18, .80], p = .003).

Table 4.

Longitudinal associations between inhibitory control and internalizing symptoms approximately eight years later.

Predicting Anxiety
Symptoms 		Predicting Depression
Symptoms
Predictor β 95% CI p β 95% CI p
Tau
 Covariates
  Sex .21 [−.14, .56] .246 .24 [−.13, .60] .203
  Age −.25 [−.58, .08] .146 −.12 [−.47, .24] .519
  Processing Speed −.24 [−.57, .09] .152 −.33 [−.67, .02] .073+
  Baseline Anx or Dep Sx .21 [−.12, .53] .219 .18 [−.16, .52] .300
  Familial MDD Risk .47 [.16, .79] .006 .40 [.06, .74] .026
  Tau Congruent −.24 [−.57, .10] .165 −.07 [−.42, .29] .711
 Inhibitory Control
  Tau Incongruent .33 [.02, .64] .042 .27 [−.05, .59] .104
Mu
 Covariates
  Sex .11 [−.23, .45] .533 .19 [−.20, .57] .340
  Age −.03 [−.37, .31] .861 .02 [−.37, .42] .904
  Processing Speed −.13 [−.44, .18] .409 −.29 [−.64, .06] .110
  Baseline Anx or Dep Sx .16 [−.14, .46] .293 .15 [−.22, .52] .425
  Familial MDD Risk .45 [.15, .76] .006 .39 [.05, .73] .031
  Mu Congruent .49 [.18, .80] .003 .28 [−.10, .65] .149
 Task Performance Speed
  Mu Incongruent −.08 [−.41, .25] .624 −.01 [−.39, .36] .945
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Note. Processing speed assessed from WISC/WAIS Coding. Anx = Anxiety. Dep = Depression.

+

p < .10. p < .05 is denoted by bolding.

Familial Risk as a Moderator of Associations between Inhibitory Control and Symptoms

Finally, we tested whether inhibitory control interacted with familial risk for MDD to prospectively predict symptoms of anxiety and/or depression. In models prospectively predicting anxiety symptoms, familial risk interacted with tau in the incongruent condition (β = .45, 95% CI [.10, .80], p = .017), but not mu in the incongruent condition (β = .17, 95% CI [−.18, .52], p = .343). Simple slopes (see Figure 1) indicated that poorer inhibition (tau) prospectively predicted greater anxiety symptoms in high-risk individuals (β = .81, 95% CI [.30, 1.33], p = .004), but not low-risk individuals (β = .09, 95% CI [−.25, .43], p = .597). In models prospectively predicting depressive symptoms, familial risk interacted with tau in the incongruent condition (β = .42, 95% CI [.02, .82], p = .041), but not mu in the incongruent condition (β = .27, 95% CI [−.13, .67], p = .187). Follow up-simple slopes analysis yielded similar patterns of results to those for anxiety symptoms: poorer inhibitory control (tau) prospectively predicted greater depressive symptoms in high-risk (β = .72, 95% CI [.14, 1.30], p = .020), but not low-risk (β = .06, 95% CI [−.32, .43], p = .769), individuals.

Figure 1.

Figure 1.

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Prospective associations between inhibitory control and symptoms of anxiety (panel A) and depression (panel B).

Associations between Inhibitory Control and Symptoms in Individuals without a Personal History

Neither tau nor mu in the incongruent condition were cross-sectionally or prospectively associated with anxiety or depressive symptoms when examined only in individuals without a personal history of an anxiety disorder or MDD at baseline (ps > .120).

Discussion

The present study examined cross-sectional and prospective associations between inhibitory control and symptoms of anxiety or depression, and whether these associations depended on familial risk. Consistent with hypotheses, initial results indicated that tau in the incongruent condition – which reflects lapses in attention consistent with poorer inhibitory control – was cross-sectionally and prospectively associated with anxiety symptoms. Cross-sectional and prospective associations between inhibitory control and depressive symptoms were not significant. Average speed of responding (mu) in the incongruent condition was not significantly associated with symptoms. Moderation analyses revealed that inhibitory control deficits at baseline predicted greater anxiety and depression symptoms eight years later in those with high (but not low) familial risk for MDD. Prior studies examining similar questions in preschool and school-aged children have similarly found that inhibition-related constructs (i.e., executive control) predicted anxiety and depression symptoms (Gramszlo et al., 2018; Nelson et al., 2018) even up to seven years later (Kertz et al., 2016), whereas general cognitive abilities did not. The current study extends these findings to a critical risk window for developing internalizing pathology: the transition from adolescence to young adulthood.

Consistent with the partially overlapping genetic variance between performance on neurocognitive tasks measuring inhibition and internalizing psychopathology (Friedman et al., 2018; Gustavson et al., 2019; Routledge et al., 2017), the prospective associations between inhibitory control and anxiety and depressive symptoms were moderated by familial risk for MDD. Inhibitory control deficits predicted higher future anxiety/depression symptoms for individuals at high, but not low, familial risk for MDD. Low inhibitory control may therefore compound preexisting (familial) vulnerability to internalizing symptoms, perhaps by impairing cognitive or emotion regulation abilities. Multiple studies have shown that individuals reporting high trait negative affectivity and low inhibitory control evidence greater information processing biases (e.g., attentional bias to threat) and anxiety symptoms, whereas those with higher inhibitory control exhibit weaker or nonsignificant relationships between such dispositional factors and anxiety (for a review, see Lonigan et al., 2004). The critical impact of familial risk has been shown in other studies with this multigenerational sample (Weissman et al., 1987; Weissman et al., 2016). Given that inhibitory control abilities have also been shown to be genetic/familial (e.g., Liu et al., 2021), the present findings suggest that inhibitory control may be a familial vulnerability factor for internalizing psychopathology. However, it is worth noting that familial risk for MDD did not moderate prospective associations between inhibitory control and internalizing symptoms when familial risk was operationalized using parental history rather than grandparental history. Statistical power was lower when defining familial risk using parental history rather than grandparental history due to a greater imbalance in group sizes. Thus, the nonsignificant moderating effects of parental history may have been type II errors.

Importantly, the effects for inhibitory control (as indexed by tau in the incongruent condition) were independent of tau in the congruent condition. The incongruent condition is more cognitively difficult and likely to tap inhibitory control abilities than the congruent condition, but controlling for the congruent condition adds specificity and additional rigor to the analyses. We also controlled for general processing speed (WAIS/WISC), increasing confidence that our findings are specific to inhibitory control. Relatedly, the use of ex-Gaussian parameters versus standard RT measures may achieve more reliable and/or valid indices of inhibitory control (McAuley et al., 2006).

The patterns of effects observed in this study were generally similar across anxiety and depressive symptoms, although some associations were only statistically significant for anxiety symptoms. The similar patterns of results are unsurprising given the frequent co-occurrence of anxiety and depressive symptoms (Kessler et al., 2005; Shankman & Klein, 2003), and suggests that inhibitory control is a transdiagnostic prospective predictor of internalizing symptoms in individuals with high familial risk for MDD. These findings broadly align with theoretical models of anxiety and depression in which poor inhibitory control relates to or exacerbates worry/rumination (De Raedt & Koster, 2010; Eysenck et al., 2007; Joormann & Gotlib, 2010), and may be one mechanism by which negative affect and internalizing symptoms are maintained or exacerbated over time. The fact that these associations were independent of participants’ baseline symptom severity further supports the interpretation that inhibitory control predicts development or exacerbation of symptoms. That said, exploratory analyses indicated that inhibitory control was not associated with internalizing symptoms when estimated only in individuals without a personal history of an internalizing disorder at baseline, suggesting that inhibitory control deficits may be a correlate or scar (rather than risk factor) of internalizing symptoms. These analyses were underpowered and effects were generally in the same direction as in the primary analyses, however. Examining whether inhibitory control is a risk factor for internalizing symptoms in higher-powered studies would be a valuable future direction.

If replicated, these findings may facilitate identifying and intervening with adolescents at risk for developing internalizing psychopathology. Inhibitory functioning tests are commonly administered to at-risk adolescents (e.g., in schools), and our findings indicate that these tests could be utilized to identify those who would benefit from screening for current or future internalizing symptoms. Although still in early phases, research indicates that increasing abilities related to inhibitory control positively impacts internalizing symptoms (e.g., Sari et al., 2016). Early interventions involving training inhibitory control abilities could potentially improve resilience to internalizing symptoms. This could functionally mimic cognitive behavioral therapy and related strategies that aim to increase cognitive flexibility, which promotes adaptive responding to future life stressors (Hoppitt et al., 2014).

The present study had several strengths, including use of a multigenerational, diagnostically well-characterized, high-risk sample, multiple experimental controls to strengthen specificity of the effects, and longitudinal follow-up over eight years. There were also several notable limitations. First, the sample was small, which likely impacted statistical power to detect significant associations. Second, although most participants were adolescents at baseline and analyses covaried for age, the age range was relatively large. Examining similar questions in a more homogeneously aged sample could facilitate more nuanced interpretations regarding the relevance of developmental stage to the associations between inhibitory control, familial risk, and internalizing symptoms. Third, although the Simon task allowed for examination of the relationship between nonaffective inhibitory control and symptoms, future studies should consider additionally utilizing tasks measuring inhibitory control using affective stimuli. Fourth, psychiatric treatment history was not accounted for and it is possible that familial risk for MDD was confounded with treatment (e.g., exposure to psychotropic medications). Fifth, although we considered both anxiety and depressive symptoms, it is unclear whether these associations are specific to these symptoms. For example, inhibitory control is also associated with externalizing symptoms (Leth-Steensen et al., 2000), and it is important to determine whether the moderating effect of familial risk extends to externalizing symptoms. Additionally, these symptoms are common in numerous depressive and anxiety disorders as well as other psychopathologies (Kessler et al., 2005), precluding inferences regarding diagnostic specificity. Sixth, we used data from a study that began data collection in 1982 and followed up participants over the ensuing decades and generations. Due to this long follow-up period, the assessments administered to the original G1 participants are now somewhat outdated. Seventh, although this study focused on inhibitory control, there are other potential moderators that might interact with familial risk to play a role in the development of anxiety and depressive symptoms (e.g., peer functioning; Funkhouser et al., 2022). Elucidating other moderators is an important future direction. Eighth, the moderating effect of familial risk may further vary as a function of the characteristics of familial depression (e.g., age of onset, recurrence, comorbidities). The small sample size and the homogeneity of the G1 participants with MDD made it infeasible to consider these various characteristics in this study, but this would be an important future direction given the typical heterogeneity of MDD. Ninth, there were relatively few incorrect responses during the inhibitory control task, suggesting the task may not have been sensitive enough to detect unsuccessful inhibitory control. The relevance of inhibitory control to internalizing dimensions should be evaluated in subsequent studies with more challenging paradigms.

Conclusions

In sum, this study found that inhibitory control (as measured by the ex-Gaussian parameter tau) prospectively predicted anxiety and depressive symptoms eight years later in individuals with high (but not low) familial risk for MDD. These findings suggest that inhibitory control may be a familial vulnerability factor for internalizing psychopathologies.

Conflicts of Interest and Source of Funding:

This work was supported by the National Institute of Mental Health [grants R01MH036197, R01MH119771 and F31MH123042]. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or of any other sponsor. Dr. Weissman has received research funding from the Brain and Behavior Foundation and the Templeton Foundation, and has received royalties from Perseus Press, Oxford Press, APA Publishing, and Multihealth Systems. Dr. Posner has received research funding from Takeda and Aevi Genomics and received a consultancy from Innovation Science. None of these represent a conflict of interest for this paper, and the other authors have no potential conflicts of interest to disclose. All authors have read and approved the submitted manuscript. Dr. Stevens and Mr. Funkhouser initially conceptualized the paper, conducted all the statistical analyses, and drafted the initial manuscript. Dr. Auerbach contributed the analytic plan. Drs. Talati, Gameroff, Posner, and Weissman designed and acquired the data and critically evaluated the paper for intellectual content. Dr. Shankman oversaw the overall development of the paper and interpretation of the results.

This study was conducted according to acceptable research standards, received institutional review board/ethics approval, and obtained informed consent of study subjects.

Footnotes

1

We also tested whether prospective associations differed between participants with (n = 34 [70.8%]) versus without (n = 14 [29.2%]) a parental history of MDD. Parental MDD history did not moderate any of the prospective associations between the ex-Gaussian parameters and anxiety or depressive symptoms (ps > .557).

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