Is Low Cognitive Functioning a Predictor or Consequence of Major Depressive Disorder? A Test in Two Longitudinal Birth Cohorts (2024)

Dev Psychopathol. Author manuscript; available in PMC 2019 May 16.

Published before final editing as:

PMCID: PMC5842891

EMSID: EMS73935

Jonathan D. Schaefer, B.A.,^*,1 Matthew A. Scult, M.A.,^*,1 Avshalom Caspi, Ph.D,^1,2,3,4 Louise Arseneault, Ph.D,⁴ Daniel W. Belsky, Ph.D,^5,6 Ahmad R. Hariri, Ph.D,¹ Honalee Harrington, B.A.,¹ Renate Houts, Ph.D,¹ Sandhya Ramrakha, Ph.D,⁷ Richie Poulton, Ph.D,⁷ and Terrie E. Moffitt, Ph.D^1,2,3,4

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Sample

The Dunedin Multidisciplinary Health and Development Study is a 4-decade, longitudinal investigation of health and behavior in a population-representative birth cohort. Study members (N = 1,037; 91% of eligible births; 52% male) were all individuals born between April 1972 and March 1973 in Dunedin, New Zealand who were eligible for the longitudinal study based on residence in the province at age 3, and who participated in the first follow-up assessment at age 3. The cohort represents the full range of socioeconomic status on New Zealand’s South Island. In adulthood, the cohort matches the New Zealand National Health and Nutrition Survey on health indicators (e.g., BMI, smoking, GP visits) (). The cohort is primarily white; fewer than 7% self-identify as having partial non-Caucasian ancestry. Assessments were carried out at birth and at ages 3, 5, 7, 9, 11, 13, 15, 18, 21, 26, 32, and, most recently, 38 years, when 95% of the 1,007 Study Members still alive took part. At each assessment wave, each Study member is brought to the Dunedin research unit for a full day of interviews and examinations. The Otago Ethics Committee approved each phase of the Study and informed consent was obtained from all Study members.

Measures of Intelligence (IQ)

Childhood intelligence. We report results from the Wechsler Intelligence Scale for Children—Revised (WISC-R; Wechsler, 1974), using participants’ total scores averaged over the three assessment points at ages 7, 9, and 11 to represent intelligence in childhood.

Adult intelligence. We report results from the Wechsler Adult Intelligence Scale, 4^th Edition (WAIS-IV; Wechsler, 2008), administered at age 38.

Self-reported cognitive functioning

At age 38, Study members were queried about problems related to memory and attention. Study members reported how often in the past year (never, sometimes, or often) they experienced problems with keeping track of appointments, remembering why they went to a store, and repeating the same story to someone, among other items. Scores on each of the 17 questions were summed to create an overall measure of cognitive difficulties (M = 9.1; SD = 5.3; range = 0-31; internal consistency reliability = 0.83). Study members were also asked to rate the extent to which their cognitive difficulties interfered with their lives on a scale from 1 (some impairment) to 5 (severe impairment). Both self-reported cognitive difficulties (r = -0.15) and the extent of impairment (r = -0.16) were negatively correlated with adult full-scale IQ (both p’s < 0.0001).

Informant-reported cognitive problems

Informant reports of Study members’ cognitive function were obtained at age 38. Study members nominated people who “knew them well.” These informants were mailed questionnaires and asked to complete a checklist, including whether the Study member had problems with his or her attention and memory over the past year. The informant-reported attention problems scale consisted of four items: “Is easily distracted, gets side-tracked easily,” “Can’t concentrate, mind wanders,” “Tunes out instead of focusing,” and “Has difficulty organizing tasks that have many steps” (internal consistency reliability = 0.79). The informant-reported memory problems scale consisted of three items: “Has problems with memory,” “Misplaces wallet, keys, eyeglasses, paperwork,” and “Forgets to do errands, return calls, pay bills” (internal consistency reliability = 0.64). Both informant-reported attention problems (r = -0.26) and informant-reported memory problems (r = -0.14) were negatively correlated with adult full-scale IQ (both p’s < 0.0001).

Assessment of Mental Disorders

Mental disorders were ascertained in the Dunedin Study longitudinally using a periodic sampling strategy: Every 2 to 6 years, Study members were interviewed about past-year symptoms in a private in-person interview at the research unit by trained interviewers with tertiary qualifications and clinical experience in a mental health-related field such as family medicine, clinical psychology, or psychiatric social work (i.e. not lay interviewers). Interviewers used the Diagnostic Interview Schedule for Children (DIS-C) at the younger ages (11-15 years) and the Diagnostic Interview Schedule at the older ages (18-38 years). At each assessment, interviewers were kept blind to Study members’ previous data, including mental health status. At ages 11, 13, and 15, diagnoses were made according to the then-current DSM-III and grouped for this article into a single wave reflecting the presence or absence of specific juvenile mental disorders. At ages 18 and 21, diagnoses were made according to the DSM-III-R (APA, 1987), and at ages 26, 32, and 38 diagnoses were made according to the DSM-IV (APA, 1994). This method led to 6 waves in total representing ages 11-15, 18, 21, 26, 32, and 38. In addition to symptom criteria, diagnosis required impairment ratings for that disorder ≥ 2 on a scale from 1 (some impairment) to 5 (severe impairment). Each disorder was diagnosed regardless of the presence of other disorders. Variable construction details, reliability and validity, and evidence of life impairment for diagnoses have been reported previously (; Kim-Cohen et al., 2003; Moffitt et al., 2007, 2010; Newman et al., 1996).

Sample

Participants were members of the Environmental Risk (E-Risk) Longitudinal Twin Study, a birth cohort of 2,232 British children. The sample was drawn from a larger birth register of twins born in England and Wales from 1994-1995 (). Full details on the sample have been previously reported (). Briefly, the E-Risk sample was constructed in 1999–2000, when 1,116 families (93% of those eligible) with same-sex 5-year-old twins participated in home-visit assessments. This sample comprised 56% monozygotic (MZ) and 44% dizygotic (DZ) twin pairs. Within zygosity, 48% of MZ twins were male, and 50% of DZ twins were male. Families were recruited to represent the UK population of families with newborns in the 1990s, on the basis of residential location throughout England and Wales and mother's age. Teenaged mothers with twins were over-selected to replace high-risk families who were selectively lost to the register through nonresponse. Older mothers having twins via assisted reproduction were under-selected to avoid an excess of well-educated older mothers. The study sample represents the full range of socioeconomic conditions in Great Britain, as reflected in the families’ distribution on a neighborhood-level socioeconomic index (ACORN [A Classification of Residential Neighborhoods], developed by CACI Inc. for commercial use) (): 25.6% of E-Risk families live in “wealthy achiever” neighborhoods compared to 25.3% nationwide; 5.3% vs. 11.6% live in “urban prosperity” neighborhoods; 29.6% vs. 26.9% live in “comfortably off” neighborhoods; 13.4% vs. 13.9% live in “moderate means” neighborhoods; and 26.1% vs. 20.7% live in “hard-pressed” neighborhoods. E-Risk underrepresents “urban prosperity” neighborhoods because such households are likely to be childless.

Follow-up home visits were conducted when the children were aged 7 (98% participation), 10 (96% participation), 12 (96% participation), and, most recently in 2012–2014, 18 years (93% participation). There were 2,066 children who participated in the E-Risk assessments at age 18, and the proportions of MZ (56%) and male same-sex (47%) twins were almost identical to those found in the original sample at age 5. The average age of the twins at the time of the assessment was 18.4 years (SD = 0.36); all interviews were conducted after the 18th birthday. Home visits at ages 5, 7, 10, and 12 years included assessments with participants as well as their mother (or primary caretaker); the home visit at age 18 included interviews only with the participants. Each twin participant was assessed by a different interviewer.

The Joint South London, Maudsley, and the Institute of Psychiatry Research Ethics Committee approved each phase of the study. Parents gave informed consent and twins gave assent between 5 and 12 years and then informed consent at age 18.

Measure of Intelligence (IQ)

Childhood intelligence. We administered a short version of the Wechsler Intelligence Scale for Children-Revised (WISC-R) when Study members were age 12 years. Using two subtests (Matrix Reasoning and Information), we prorated Study members’ IQs and standardized them to M = 100 (SD = 15), according to the method recommended by Sattler (2008).

Assessment of Depression

Unlike the Dunedin cohort, which underwent repeated diagnostic assessments from age 11 to 38, the E-Risk Study members participated in only one diagnostic interview at age 18, during which they were assessed for past-year DSM-IV symptoms of MDD using the Diagnostic Interview Schedule (DIS) (). As in the Dunedin Study, E-Risk Study members meeting symptom criteria for MDD also needed to report impairment ratings ≥ 2 on a scale from 1 (some impairment) to 5 (severe impairment) to receive a diagnosis.

Does lower IQ in childhood predict increased risk of developing Major Depressive Disorder?

To address this question, we started with 957 (92.3%) of the original 1,037 Dunedin Study members, including only those individuals who (a) had participated in at least half of the six mental health assessment waves from ages 11 to 38 and (b) had available childhood IQ data. Because schizophrenia is often accompanied by depression, and is associated with pronounced pre-morbid and post-onset cognitive deficits as well as thought disorder symptoms (; Meier et al., 2014; Reichenberg et al., 2010; Schaefer et al., 2013), we further refined our analytic sample by excluding all Study members who received a diagnosis of schizophrenia by age 38 (N = 37). This step ensured that any observed associations between MDD and IQ were not driven by these individuals.

Of the remaining 920 Study members, 812 (88.3%) contributed 6 waves of mental health data, 67 (7.3%) contributed 5 waves of mental health data, 26 (2.8%) contributed 4 waves of mental health data, and 15 (1.6%) contributed 3 waves of mental health data. From ages 11 to 38, 431 (46.9%) of these Study members received a diagnosis of major depressive disorder (MDD) at one or more assessment waves. These Study members constituted the “ever-depressed” group. The remainder of the cohort (N = 489, 53.2%) did not meet criteria for a diagnosis of MDD between the ages of 11 and 38. These Study members constituted the “never-depressed” group. Together, these groups composed the full analytic sample (Figure 1A).

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Figure 1

Dunedin Study member flow diagrams for (A) our test of the cognitive reserve hypothesis and (B) our test of the cognitive scarring hypothesis.

As an initial test of the cognitive reserve hypothesis, we conducted a follow-forward analysis using a modified Poisson regression model with robust standard errors to estimate relative risk for the binary outcome of lifetime MDD (Zou, 2004). Methodologists have suggested that risk ratios are less inflated than odds ratios in situations where the outcome is common, which is the case for MDD in our sample (Cummings, 2009). The risk ratios presented can be understood as the ratio change in average risk of MDD for every one point increase in IQ. Using this approach, we found that risk of membership in the ever-depressed (N = 431; mean childhood IQ = 100.0, SD = 14.4) versus never-depressed group (N = 489; mean childhood IQ = 101.4, SD = 13.8) did not differ as a function of childhood IQ, controlling for sex (IRR = 0.997; 95% CI = 0.992, 1.002; p = 0.247).

Previous studies have suggested that low childhood IQ is associated with an increased risk of developing not only depression, but also a number of other psychiatric conditions, including anxiety and substance use disorders (; Gale et al., 2008; Koenen et al., 2009; Rajput et al., 2011). Thus, it is possible that our ability to detect a predictive relationship between childhood IQ and lifetime depression is limited by the presence of other psychiatric disorders in the “never-depressed” group. Fortunately, one advantage afforded by the Dunedin Study’s repeated mental health assessments is that they allowed us to identify the small group of individuals who have never met criteria for any of the mental disorders assessed by the Study (hereafter referred to as the “enduring-mental-health” group; Schaefer et al., 2017), and to use these Study members as a new comparison group (N = 161 who had childhood IQ data; mean childhood IQ = 102.3, SD = 14.0) (Figure 1A). We thus conducted an additional follow-forward analysis to test whether childhood IQ was a significant predictor of membership in the ever-depressed versus enduring-mental-health groups, controlling for sex. Consistent with our previous results, we found that childhood IQ still did not appear to distinguish between the two groups (IRR = 0.997; 95% CI = 0.994, 1.001; p = 0.136).

To provide a point of comparison, we also tested whether childhood IQ was a significant predictor of membership in the small group of Study members with schizophrenia (N = 37; mean childhood IQ = 94.0, SD = 17.6) versus the majority of the cohort who were never diagnosed with schizophrenia (N = 920; mean childhood IQ = 100.7, SD = 14.1), controlling for sex. Here, low childhood IQ was associated with higher risk of receiving a schizophrenia diagnosis (IRR = 0.968; 95% CI = 0.944, 0.992; p = 0.010).

Does lower IQ in childhood exert an effect on an individual’s later risk of developing Major Depressive Disorder independent of family-wide and genetic risk?

An even more powerful approach to testing the cognitive reserve hypothesis is to compare two children growing up in the same family. If the cognitive reserve hypothesis is correct, the sibling with higher IQ should be at lower risk of developing MDD. We tested this hypothesis in E-Risk Longitudinal Twin Study the using the following mixed-effects model:

In this specification, IQ effects are parsed into between-twin pair effects and within-twin pair effects using a logistic regression model, where i is used to index twin pairs and j represents individual twins within pairs, so π_ij and X_ij represent, respectively, the probability of receiving a depression diagnosis and childhood IQ values for the j^th twin of the i^th pair, whereas $\bar{X}$_i represents the mean childhood IQ of both twins within the i^th pair. The between-twin pair regression coefficient (β_B) estimates whether pairs of twins with higher average age-12 IQ are at lower risk of being diagnosed with MDD at age 18. In contrast, the within-twin pair regression coefficient (β_w) estimates whether the twin with higher IQ than his or her co-twin is less likely to be diagnosed with MDD than his or her co-twin.

We first estimated this model using data from all available twin pairs (MZ and DZ) in E-Risk. A significant between-twin-pair effect would reflect family-wide factors common to both twins that influence IQ and MDD and may underlie their association. A significant within-twin-pair effect, on the other hand, would indicate that possessing low IQ in childhood predicts MDD independent of any factors that are shared between siblings growing up in the same family (Carlin et al., 2005). We then estimated this model using only the MZ twin pairs in the E-Risk Study. Because MZ twins are genetically identical, a significant within-twin pair effect would rule out the possibility that the association between IQ and MDD arises solely due to a shared genetic susceptibility that elevates risk of both phenotypes.

The parameters estimated from each of these models are reported in Table 1. Of the original 2,232 Study members, we included 2,003 (89.7%), excluding twins if they belonged to a twin pair in which (a) 1 or more twins lacked IQ data at age 12, or (b) both twins lacked mental health assessment data at age 18. Of these 2,003 Study members, 404 (20.2%) received a diagnosis of MDD. Both the full-cohort and MZ-twin-only models indicated that neither between-twin-pair nor within-twin-pair differences in IQ tested at age 12 appear to predict risk of MDD at age 18, consistent with our results from the follow-forward analysis conducted in the Dunedin Cohort. These findings did not support the assumption that lower IQ is causally related to increased risk of subsequent depression.

Could lower IQ in childhood predict particularly early-onset or severe MDD?

Although childhood IQ did not predict risk of future MDD in either cohort, it is still possible that a predictive relationship might exist between IQ in childhood and specific types of MDD, especially given previous research indicating a link between lower cognitive functioning and higher rates of relapse/recurrence, increased symptom severity, and impaired global functioning among depressed individuals (Jaeger et al., 2006; Majer et al., 2004; ). Thus, we next tested the hypotheses that childhood IQ would predict measures of MDD age-of-onset, persistence, self-rated impairment, number of diagnostic criteria endorsed, clinical attention, or psychiatric comorbidity in the Dunedin Cohort.

Age of onset. We tested whether childhood IQ predicted an earlier age of depression onset by conducting a Cox proportional hazards regression using data from the full analytic sample (N = 920), controlling for sex. We recorded the assessment wave during which each Study member in the ever-depressed group received his or her first diagnosis of MDD as the age of depression onset (M = 23.3, SD = 7.0, range = 15-38). We found that childhood IQ did not significantly predict depression age of onset (HR = 1.00; 95% CI = 0.99, 1.00; p = 0.381), indicating that Study members with low IQ did not appear to develop depression any earlier than Study members with higher IQ.

Persistent course. We calculated depression recurrence/persistence for each Study member in the ever-depressed group (N = 431) as the proportion of waves during which that Study member met diagnostic criteria for MDD (M_proportion = 0.30, SD = 0.16, range = 0.17-1.00). We then conducted a linear regression that predicted the proportion of waves each Study member had received an MDD diagnosis as a function of childhood IQ, controlling for sex. We found no significant association between childhood IQ and this measure (b = -0.001; 95% CI: -0.002, 0.000; t(428) = -1.31; p = 0.19), indicating that Dunedin Study members with low IQ who were diagnosed with MDD did not appear to spend significantly more Study waves suffering from depression than their higher-IQ peers with MDD.

Self-rated impairment. Dunedin Study members were asked to rate the functional impairment caused by their depressive symptoms on a scale from 1 (some impairment) to 5 (severe impairment) at each assessment wave between the ages of 18 and 38. We recorded self-rated impairment in this cohort as the maximum impairment rating given between the ages of 18 and 38 (M = 4.05, SD = 0.88, range = 2-5) by each Study member who met diagnostic criteria for MDD at least once during this same period (N = 412). We limited our analysis of impairment to this age range because self-ratings of impairment were not collected in earlier assessments.

We conducted a linear regression model predicting self-rated impairment as a function of childhood IQ, controlling for sex. We found that childhood IQ was a significant predictor of self-rated impairment (b = -0.01; 95% CI: -0.01, 0.00; t(409) = -2.05; p = 0.041), suggesting that individuals with lower IQs who develop MDD tend to rate their depression as more impairing than their higher-IQ peers with MDD. Such an effect is likely to be of little practical significance, however, as each 1-point increase in IQ is associated with a predicted decrease of only 1/100^th of a point on a 5-point self-rated impairment scale.

Symptom count. We calculated symptom count as the number of MDD criteria endorsed by Study members between the ages of 18 and 38 (M = 15.03, SD = 7.78, range = 4-41) by each Study member who met diagnostic criteria for MDD at least once during this same period (N = 413). We limited our analysis of symptom criteria to this age range because symptom count data from earlier waves were not available.

We conducted a linear regression predicting symptom count between the ages of 18 and 38 as a function of childhood IQ, controlling for sex. We found no significant association between childhood IQ and this measure (b = -0.02; 95% CI: -0.07, 0.03; t(410) = -0.86; p = 0.392), suggesting that Study members with lower IQs tended to endorse a similar number of MDD symptoms relative to Study members with higher IQs.

Clinical attention. Dunedin Study members reported if they had contacted a professional (i.e. a general practitioner, psychologist, or psychiatrist) for a mental health problem or received psychiatric medication between the ages of 20 and 38. Of the 350 Study members diagnosed with MDD during this same period in the full analytic sample (with present treatment contact data), 249 (71.1%) endorsed some form of treatment contact. We conducted a Poisson regression model with robust standard errors to calculate risk ratios for the binary outcome of treatment contact as a function of childhood IQ, controlling for sex. We found no significant association between childhood IQ and this measure (IRR = 1.002; 95% CI: 0.997, 1.006; p = 0.464), suggesting that individuals with lower IQs who develop MDD were no more likely to receive treatment than their higher-IQ peers with MDD.

Comorbidity. In the Dunedin Study, we operationalized comorbidity as the number of diagnostic families (including depressive disorders, anxiety disorders, substance use disorders, attention-deficit/hyperactivity disorder, and conduct disorder) represented in a Study member’s complete history of psychiatric diagnoses accumulated between the ages of 11 and 38 years (M = 1.70, SD = 1.21, range 0-5 in the full analytic sample; M = 2.54, SD = 0.97, range 1-5 in the ever-depressed group). We did not include schizophrenia in our count of psychiatric comorbidities because Study members who developed schizophrenia were excluded from the analytic sample.

We tested the association between childhood IQ and lifetime psychiatric comorbidity using a Poisson regression model that predicted the count of diagnostic families represented in each Study member’s diagnostic history between the ages of 11 and 38 as a function of childhood IQ, controlling for sex. We found an association between childhood IQ and comorbidity in both the full analytic sample (N = 920; IRR = 0.993; 95% CI: 0.989, 0.996; p <0.001), and among ever-depressed Study members (N = 431; IRR = 0.995; 95% CI: 0.991, 0.999; p = 0.025).

Figure 2A charts mean IQ as a function of psychiatric comorbidity in the context of MDD. Here we plot IQ scores for Dunedin Study members who have never had depression, Study members who have had depression only, and Study members who have had depression alongside 1 or more additional psychiatric conditions. Figure 2A shows that early IQ deficits were pronounced only among depressed Study members with multiple psychiatric comorbidities. Interestingly, Dunedin Study members with “pure” depression—that is, those who were diagnosed only with depression between the ages of 11 and 38 years—appeared to have slightly higher IQs in childhood than Study members who were never diagnosed with depression. We confirmed this observation through follow-forward analysis using Poisson regression, which indicated that Dunedin Study members with higher IQs were more likely to experience pure depression than no depression at all, controlling for sex (N = 543; IRR = 1.019; 95% CI = 1.001, 1.037; p = 0.040).

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Figure 2

Mean (A) childhood IQ, (B) change in IQ from childhood to adulthood, and (C) subjective adult cognitive functioning by lifetime psychiatric comorbidity in the Dunedin Cohort.

Finally, we used modified Poisson regression with robust standard errors to test whether low childhood IQ predicted the emergence of certain types of lifetime psychiatric comorbidities, but not others. We found that children who went on to develop MDD (N = 420) with lower childhood IQs were also at increased risk of developing anxiety disorders (IRR = 0.993; 95% CI = 0.989, 0.996; p < 0.001), attention-deficit/hyperactivity disorder (IRR = 0.949; 95% CI = 0.929, 0.969; p < 0.001), and conduct disorder (IRR = 0.983; 95% CI = 0.971, 0.996; p = 0.008), but not substance use disorders (IRR = 0.999; 95% CI = 0.993, 1.006; p = 0.861).

Are individuals with a history of MDD more likely to show evidence of or report lingering cognitive impairment as adults?

We next used data from the Dunedin Study to test for enduring cognitive deficits in previously-depressed Study members whose MDD had remitted by age 38, the time of adult cognitive assessment. Evidence of intellectual decline among these remitted individuals could be interpreted as evidence of a lingering depression-induced “scar” on cognitive functioning (Lewinsohn et al., 1981). For these analyses, we used data from 744 Study members who were assessed for mental disorder at age 38 but who did not meet criteria for a diagnosis of past-year MDD at age 38. This decision allowed us to separate the lingering cognitive “scarring” effects of a diagnostic history of MDD from the contemporaneous effects of a current episode of MDD. Similar to previous analyses, we also required these individuals to have (a) participated in at least half of the six mental health assessment waves from ages 11 to 38, (b) available childhood and adult IQ data, and (c) never received a diagnosis of schizophrenia. These individuals were divided into two groups: those with a previous history of MDD (N = 277; mean adult IQ = 101.2, SD = 14.4), and those with no previous history of MDD (N = 467; mean adult IQ = 101.0, SD = 14.4) (Figure 1B).

We conducted a series of one-way ANOVAs testing whether Study members with a previous history of MDD differed from Study members without such a history on age-38 IQ, self-reported cognitive functioning, or informant-reported cognitive functioning, controlling for sex. As shown in Table 2, we found that Study members with a history of depression scored lower on our subjective measures of cognitive functioning (i.e., self- and informant-report), but not on any of our objective measures of cognitive functioning (i.e. WISC-R and WAIS-IV IQ, IQ change from childhood to adulthood). Taken together, these results suggest that Study members with a history of depression were more likely to report that their cognitive functioning was impaired despite little to no measurable change (on average) in objective cognitive functioning as assessed by IQ tests.

Is there evidence of cognitive scarring following an episode of particularly severe or early-onset MDD?

One criticism of the analyses summarized in Table 2 is that, in comparing only those individuals who were not depressed at age 38, we potentially ignore many of the most severe, chronic cases of MDD who continued to meet diagnostic criteria at the age-38 assessment wave. Consequently, we next tested whether any of our six clinical indicators (i.e., MDD age-of-onset, persistence/recurrence, self-rated impairment, number of diagnostic criteria endorsed, clinical attention, and comorbidity) predicted change in IQ from childhood (ages 7-11) to adulthood (age 38). If cognitive scarring is more common following severe or early-onset cases of MDD, higher scores on these indicators should predict a more severe decline in IQ following a depressive episode.

As shown in Table 3, only psychiatric comorbidity was found to predict a steeper decline in IQ from childhood to adulthood. This finding suggests that the cognitive scarring reported following a depressive episode may be more attributable to disorders commonly comorbid with MDD rather than the experience of a depressive episode per se. Figure 2B charts mean change in IQ between childhood (ages 7-11) and adult (age 38) assessments as a function of psychiatric comorbidity in the context of MDD, whereas Figure 2C does the same with each of our four subjective measures of cognitive functioning. Consistent with Figure 2A, Figures 2B and 2C show that evidence of IQ decline and high subjective impairment was apparent only for depressed Study members with multiple psychiatric comorbidities.

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