## Abstract

Background: There  is  some  debate  regarding  the  utility  of  Attention-Deficit/  Hyperactivity  Disorder  (ADHD)  subtypes  as currently defined. Differences in co-occurring psychopathology among subtypes would support the validity of subtype definitions.

Objective: To  explore  how  ADHD  subtype  relates  to  co-occurring  psychopathology  in  a  large  population-based  sample  of children and adolescents (n=5744).

Method: Parents completed the Strengths and Weaknesses of ADHD-symptoms and Normal behavior (SWAN) questionnaire, the Child Behavior Checklist (CBCL) and the Social Responsiveness Scale (SRS). Methods including discriminant analysis, principal components analysis, and fractional polynomial regression were used to examine the relationship between ADHD diagnostic subtypes and co-occurring psychopathology.

Results: Children with different ADHD subtypes show differences on several CBCL subscales. A combination of CBCL subscales and SRS score had good ability to discriminate ADHD subtypes. Conversely, for the same overall number of ADHD symptoms, individuals who  present with both inattentive and hyperactive/impulsive symptoms exhibit higher severity of cooccurring psychopathology on a summary measure derived from principal components analysis of the CBCL subscales and SRS. This includes some subjects who fail to meet the DSM-IV-TR ADHD symptom criterion due to having less than 6 inattentive and less than six hyperactive-impulsive symptoms, yet have ADHD symptom severity similar to those with the inattentive or hyperactive-impulsive subtype.

Conclusions : Several convergent lines of analysis provide support for the continued use of ADHD subtypes (or current presentation symptom profiles), as evidenced by differences in co-existing psychopathlogy. We also found that current diagnostic criteria may fail to identify a potentially impaired group of individuals who have low-to-moderate levels of both inattention and hyperactivity/impulsivity.  Under  the  upcoming  DSM-5,  it  will  be  important  for  clinicians  to  consider  the  option  of  giving  an ADHD 'not elsewhere classified' diagnosis to such children.

Key Words:

ADHD, subtypes, comorbidity

1 Corresponding Author:

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Research Article                                                                                                                      Open Access

## Exploration of ADHD Subtype Definitions and Co-Occurring Psychopathology in a Missouri Population-Based Large Sibship Sample

Angela M. Reiersen 1 , MD, MPE, Alexandre A. Todorov, PhD

Department of Psychiatry, Washington University in St. Louis School of Medicine

## Introduction

There is some debate regarding the current DSM-IVTR  criteria  for  Attention-Deficit/Hyperactivity  Disorder (ADHD) and its three subtypes (predominantly inattentive, predominantly hyperactive-impulsive, and combined  type).  First,  the  correlation  between  the inattentive and hyperactive-impulsive domains is very high, with  evidence  of  high  genetic  overlap  between separate  ADHD  subtypes  or  symptom  dimensions (1).  Second,  from  a  clinical  intervention  standpoint, stimulants are the mainstay of pharmacological treatment,  regardless  of  subtype  (though  educational  accommodations will vary slightly depending on which type of symptoms predominate in the school setting). Third, children who present with a meaningful six to ten  symptoms  could  potentially  qualify  for  the  inattentive subtype or the hyperactive-impulsive subtype, provided that six or more of these symptoms fall into one  category.  A  more  likely  event,  given  the  high correlation  between  the  two  domains,  is  that  the symptoms would be roughly equally divided, so that the child would not technically qualify for a diagnosis of  ADHD  (e.g.,  five  symptoms  in  each  category). Below,  we  will  present  data  suggesting  significant impairment in such children. Improved definition and screening methods for ADHD and its subtypes may help  ensure  that  individuals  with  clinically  impairing ADHD symptoms can be identified and treated.

Differences in external (non-ADHD)  measures (such  as  cognitive  profiles,  genetic  associations,  and comorbidity patterns) among ADHD subtypes would help validate the current typology. They may suggest differences  in  etiology  and  treatment  needs  between ADHD subtypes. Also, if different ADHD subtypes are  associated  with  different  types  of  co-occurring problems and/or different levels of severity, this may support subtypes as prognostic indicators to guide the monitoring of specific types of co-occurring problems depending upon the ADHD symptom profile.

The  Child  Behavior  Checklist  has  previously  been used  to  examine  comorbid  psychopathology  in  children  with  ADHD  (2-5).  Some  studies  specifically examined differences in CBCL  measures among ADHD subtypes  (3,  5).  Though  results  vary  somewhat between studies, individuals with the combined subtype generally have the highest rates of cooccurring psychopathology where subtype differences are found.

Population-based studies conducted by our own research group investigated the validity of ADHD subtypes through analyses focusing on prevalence (6), sex differences  (6),  cognitive  function  (7),  comorbidity profiles (8-10), genetics (11-13), and longitudinal course (14). In these analyses, subtypes were defined both  according  to  DSM-IV  criteria  and  via  Latent Class  Analysis  (LCA),  a  form  of  mixture  modeling that  can  be  used  to  separate  subjects  into  discrete, more homogeneous groups characterized by specific symptom  profiles.  Three  of  these  latent  classes  (labeled  severe  inattentive,  mild  combined,  and  severe combined)  show  substantial  evidence  of  impairment (5),  while  those  characterized  by  pure  hyperactiveimpulsive  symptoms  show  little  evidence  of  impairment.  The  severe  inattentive  type  shows  modest agreement with DSM-IV inattentive subtype, and the severe combined type shows excellent agreement with DSM-IV combined subtype ADHD (8, 15-18). These previous  analyses  supported  inattentive  ADHD  as  a distinct  subgroup  based  on  genetic  associations  and co-occurring  problems  (5,  7,  8,  11-13),  but  failed  to take  into  account  the  fact  that  overall  severity  of combined type ADHD  compared  to inattentive ADHD  could  account  for  many  of  the  differences between these two subtypes.

In  a  prospective  longitudinal  study  of  twins,  we found  that  compared  to  the  inattentive  subtype,  the diagnosis  of  combined  subtype  ADHD  (defined  by either  DSM  or  LCA)  is  more  stable  over  time  than other  subtype  diagnoses  (14).  While  combined  subtype  subjects  sometimes  switched  to  inattentive  subtype  five  years  later,  inattentive  subjects  tended  to remain  inattentive  if  they  still  had  a  diagnosis  five years  later.  Again,  overall  severity  could  underlie  the difference  in  subtype  stability  since  children  with more severe forms of a neurodevelopmental disorder (i.e. combined type ADHD) may be expected to have more  persistent  symptoms  over  time.  Hurtig  and colleagues reach a similar conclusion based on a retrospective study (19). For DSM-5, it has been proposed that ADHD subtypes be replaced by similarly defined 'specifiers' of current presentation, in part to emphasize  that  these  categories  represent  current  symptom profile rather than longitudinally stable subtypes (20). Even  though  the  concept  of  subtypes  will  be  deemphasized  by  this  change,  DSM-5  will  likely  still require six symptoms in at least one of the two symptom  domains  in  order  to  meet  the  overall  symptom criterion.  A  diagnosis  of  'ADHD  Not  Elsewhere Classified'  has  been  proposed  to  classify  individuals who do not meet the full  symptom criterion  due  to partial  remission  status  or  clinically  significant  but subthreshold  symptoms  (e.g.,  those  with  five  symptoms in each category) (20).

Using additional population-based data from a large sibship  sample,  the  current  analysis  attempts  to  further  explore  the  validity  of  ADHD  subtype  definitions  through  the  examination  of  co-occurring  psychopathology.  If,  for  example,  when  controlling  for overall severity of total ADHD symptoms, individuals with the inattentive ADHD subtype are more severely affected than combined type on any specific measures of  co-occurring  psychopathology, this would suggest that  inattentive  ADHD  is  a  distinct  subtype  rather than just a less severe form of combined type ADHD. Our focus on population-based samples avoids some of the biases inherent to clinical samples. In particular, children with hyperactive-impulsive symptoms may be brought  to  clinical  attention  due  to  their  disruptive behavior at school, while children with predominantly inattentive  ADHD  (especially  those  without  additional  psychopathology  warranting  clinical  attention) may be  overlooked  because  they  do  not  disrupt  the classroom.

## Methods

## Sample

Subjects are from the Missouri Large Sibship Sample (MO-BIGSIBS). Families with four or more children born in the state of Missouri were identified for study using  a  birth  records  database  (21).  As  the  parent study required genetic material from both parents in a later  phase, we only screened families in which both biological parents were available (parents could not be deceased or in prison). Families were excluded at the birth records review or tracking level if the family was known to have twins (due to other studies using twin samples), language difficulty that would prevent English-language  telephone  screening,  or if  a  parent  was deceased.  Individual  children  were  excluded  during the parent-report telephone screening if the child was adopted or not a full sibling, or had a parent-reported diagnosis  of  autism,  a  major  hearing  impairment,  a marked  medical  illness  such  as  cancer,  Down's  Syndrome, or intellectual disability  ('mental retardation' or IQ less than 70).

As  the  initial  screening  phase  involved  the  collection of relatively non-invasive parent-report interview and  questionnaire  data  to  be  stored  in  de-identified form, consent was required only from parent participants at this stage. After explanation of study procedures,  informed  consent  was  obtained  from  respondent parents and documented by study staff prior to an  initial  ADHD  screening  interview.  Parents  were informed that phase 1 of the study would include the initial telephone interview plus questionnaires regarding their children. They were also informed that they and their family may later be invited to participate in additional assessments on the basis of their responses to the initial telephone questions. A subset of families was eventually selected for more detailed phenotypic and  genetic  study,  which  required  written  consent from  parents  and  their  adult  offspring  participants, and  assent  from  minor  children.  The  current  manuscript  uses  only  the  phase  1  parent-report  screening data.  Ethical  approval  for  this  study  was  obtained through the Washington University Human Research Protection Office, which reviewed and approved the study protocols, including consent procedures.

The  MO-BIGSIBS  sample  includes  22,581  offspring,  some  of  them  young  adults,  with  complete data on sex, age at screening, and screening interview ADHD  items  (21).  The  current  analyses  focus  on children and adolescents age 7-17 years (n=5,744) at assessment, who have complete data on sex, age, lifetime ADHD symptoms from the screening interview, and  relevant  questionnaire  items.  Of  the  5,744  subjects,  98%  are  Caucasian,  2%  are  African-American, and less than 1% report other races/ethnicities. Fiftytwo percent of study subjects are male.

## Measures

In the initial screening phase, the best informant parent  (usually  mother)  reported  on  lifetime  occurrence of  each  of  the  standard  18  DSM-IV  ADHD  symptoms  for  each  of  their  offspring.    Each  lifetime ADHD  symptom  was  counted  as  positive  only  if there was reported impairment at  home  and/or school at some point in the child's life. The screening questions were taken from the ADHD section of the Missouri Assessment of Genetics Interview for Children  (MAGIC),  which  has  excellent  reliability  for parent-reported ADHD (22). A subset of parent informants  subsequently  completed  several  questionnaires regarding the offspring, including the Strengths and  Weaknesses  of  ADHD-symptoms  and  Normalbehavior  (SWAN)  scale,  the  Social  Responsiveness Scale (SRS), and the Child Behavior Checklist (CBCL).

The CBCL covers a wide range of problem behaviors (23), and the SRS is a 65-item quantitative measure of autistic traits (24, 25). SRS score is highly correlated with algorithm scores from the Autism Diagnostic Interview-Revised (ADI-R) (24). The SWAN (26)

Scale T Score

Anx/Dep SC

* HY

includes  18  items  based  on  DSM-IV  ADHD  symptoms  plus  additional  items  assessing  oppositionaldefiant behaviors (9 items) and three items related to sluggish cognitive tempo. SWAN items are scored on a seven-point scale (-3 to +3) in which positive scores indicate the presence of problem behaviors and negative scores indicate better than average behaviors.

Data  from  the  SWAN  was  used  to  define current DSM-IV-like  ADHD  diagnoses,  and  data  from  the screener  was  used to define lifetime DSM-IV-like ADHD diagnoses.  It was not possible to apply strict DSM-IV  criteria  in  determining  ADHD  diagnoses since  information  about  age-of-onset and  current impairment  specifically  from  ADHD  symptoms  was not collected. However, the lifetime ADHD symptom data from the screening interview and current symptom data from the SWAN allowed us to assign subjects  to  ADHD-like  diagnoses  using  the  DSM-IV ADHD symptom criterion. From the screener data, a diagnosis  of  Lifetime  DSM-IV  inattentive  ADHD (DSM-Life-IA) was assigned if there were at least six lifetime  inattentive  (IA)  symptoms  and  less  than  six lifetime  hyperactive-impulsive  (HI)  symptoms  based on the screening interview. Lifetime DSM-IV

Figure  1. Mean  CBCL  subscale  T-Scores  for  children  and  adolescents with  DSM-IV  Inattentive  (IA),  Hyperactive-Impulsive  (HY),  and  combined type (SC) ADHD. The SC subtype consistently scores higher than the IA or HY subtypes.

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hyperactive-impulsive  type  (DSM-Life-HI)  was  assigned if there were at least six HI symptoms but less than six IA symptoms. Lifetime  combined type ADHD (DSM-Life-C) was assigned if  there  were  at least six symptoms in each of the two categories (IA and HI).

Using  similar  algorithms,  current  DSM-IV-like  diagnoses  (DSM-IA,  DSM-HI,  and  DSM-C)  were  assigned  using  the  DSM-IV  ADHD  symptom  items from  the  SWAN.  SWAN-based  ADHD  symptoms were counted as present if the parent rated the child at  a  level  of  1  or  higher,  an  actually  stringent  cutoff that  typically  corresponds  to  the  90 th -95 th   percentile for each item (21).

## Data Analysis

Analyses were conducted using STATA 12 and SAS 9.3. We used ANOVA to Compare CBCL syndrome subscale T-scores across the four subject groups (unaffected  individuals  and  the  three  ADHD  subtypes), with a conservative Bonferoni correction for multiple testing  and with  standard errors adjusted for clustering  by  family.  Conversely,  we  considered  whether  a rule  could  be  developed  from  the  SRS  and  CBCL subscale data, to distinguish DSM-IV inattentive and hyperactive-impulsive subtypes, again taking into account the known  correlation between  the  two symptom  domains.  To  that  purpose,  we  use  seemingly-unrelated  bivariate  probit  regression  with  the robust clustering option (on family), beginning with a full model consisting of age, SRS, and the eight CBCL syndrome scale scores. This allowed us to test if the relationship  between  specific  variables  (e.g.,  age  or subscale score) and the liability to HI was the same as with the liability to IA. The analyses were conducted separately  for  males  and  females.  The  output  from this  analysis  consists  of  two  predicted  means  (probit scale, akin to predicted scores from linear regression) for  each  individual  subject,  one  for  IA  and  one  for HI. Receiver Operating Characteristics (ROC) Curves were  used  to  assess  the  sensitivity  and  specificity  of these probit  scores in predicting elevated IA and HI symptoms. The two probit scores were then used in a linear  discriminant  analysis  to  assess  the  ability  to distinguish between DSM-IV ADHD subtypes.

Table 1. Parameter estimates for females, ordered bivariate probit regression, predicting inattentive and hyperactive-impulsive symptom counts.

* = Retained for subsequent analyses.

Table 2. Parameter estimates for males, ordered bivariate probit regression, predicting inattentive and hyperactive symptom counts.

| Predictor of Inattentive Symptom Count             | Coefficient   | Standard Error   | z     | p      | 95% CI           |
|----------------------------------------------------|---------------|------------------|-------|--------|------------------|
| * SRS                                              | 0.022         | 0.003            | 8.19  | <0.001 | 0.017 to 0.027   |
| * Anxious/Depressed                                | -0.025        | 0.009            | -2.91 | 0.004  | -0.042 to -0.008 |
| * Withdrawn/Depressed                              | -0.030        | 0.007            | -4.48 | <0.001 | -0.043 to -0.017 |
| * Somatic Complaints                               | 0.022         | 0.006            | 3.60  | <0.001 | 0.010 to 0.034   |
| * Attention problems                               | 0.149         | 0.008            | 18.35 | <0.001 | 0.133 to 0.165   |
| * Rule-Breaking                                    | 0.030         | 0.008            | 3.82  | <0.001 | 0.015 to 0.045   |
| Age                                                | -0.020        | 0.009            | -2.32 | 0.020  | -0.037 to -0.003 |
| Social Problems                                    | -0.012        | 0.009            | -1.36 | 0.175  | -0.029 to 0.005  |
| Thought Problems                                   | -0.020        | 0.008            | -2.44 | 0.015  | -0.036 to -0.004 |
| Aggressive Behavior                                | -0.011        | 0.009            | -1.43 | 0.154  | -0.027 to 0.004  |
| Predictor of Hyperac- tive-Impulsive Symptom Count | Coefficient   | Standard Error   | z     | p      | 95% CI           |
| * Age                                              | -0.031        | 0.009            | -3.25 | 0.001  | -0.049 to -0.012 |
| * SRS                                              | 0.021         | 0.003            | 7.86  | <0.001 | 0.015 to 0.026   |
| * Withdrawn/Depressed                              | -0.067        | 0.008            | -7.94 | <0.001 | -0.084 to -0.051 |
| * Thought Problems                                 | 0.021         | 0.008            | 2.76  | 0.006  | 0.006 to 0.036   |
| * Attention Problems                               | 0.057         | 0.007            | 8.28  | <0.001 | 0.044 to 0.071   |
| * Aggressive Behavior                              | 0.055         | 0.009            | 6.30  | <0.001 | 0.038 to 0.072   |
| Social Problems                                    | 0.009         | 0.009            | 1.00  | 0.319  | -0.009 to 0.027  |
| Somatic Complaints                                 | 0.013         | 0.006            | 2.04  | 0.041  | 0.001 to 0.025   |
| Anxious/Depressed                                  | 0.003         | 0.009            | 0.35  | 0.724  | -0.014 to 0.020  |
| Rule-Breaking                                      | -0.007        | 0.009            | -0.78 | 0.434  | -0.025 to 0.011  |

* = Retained for subsequent analyses.

| Predictor of Inattentive Symptom Count             | Coefficient   | Standard Error   | z     | p      | 95% CI           |
|----------------------------------------------------|---------------|------------------|-------|--------|------------------|
| * SRS                                              | 0.021         | 0.002            | 9.84  | <0.001 | 0.017 to 0.025   |
| * Anxious/Depressed                                | -0.027        | 0.007            | -3.74 | <0.001 | -0.042 to -0.013 |
| * Withdrawn/Depressed                              | -0.017        | 0.006            | -2.78 | 0.005  | -0.029 to -0.005 |
| * Thought Problems                                 | 0.028         | 0.007            | -3.86 | <0.001 | -0.043 to -0.014 |
| * Attention problems                               | 0.159         | 0.008            | 19.31 | <0.001 | 0.143 to 0.176   |
| Somatic Complaints                                 | 0.001         | 0.007            | 0.22  | 0.827  | -0.012 to 0.015  |
| Social Problems                                    | -0.006        | 0.008            | -0.67 | 0.501  | 0.022 to 0.011   |
| Age                                                | 0.000         | 0.008            | 0.04  | 0.968  | -0.015 to 0.016  |
| Rule-Breaking                                      | 0.016         | 0.008            | 1.85  | 0.065  | -0.001 to 0.032  |
| Aggressive Behavior                                | -0.012        | 0.007            | -1.63 | 0.103  | -0.026 to 0.002  |
| Predictor of Hyperac- tive-Impulsive Symptom Count | Coefficient   | Standard Error   | z     | p      | 95% CI           |
| * Age                                              | -0.059        | 0.008            | -7.02 | <0.001 | -0.075 to -0.042 |
| * SRS                                              | 0.019         | 0.002            | 8.78  | <0.001 | 0.015 to 0.024   |
| * Withdrawn/Depressed                              | -0.060        | 0.007            | -8.57 | <0.001 | -0.073 to -0.046 |
| * Attention Problems                               | 0.087         | 0.006            | 13.76 | <0.001 | 0.075 to 0.100   |
| * Aggressive Behavior                              | 0.045         | 0.007            | 6.25  | <0.001 | 0.031 to 0.059   |
| Anxious/Depressed                                  | -0.015        | 0.007            | -2.03 | 0.042  | -0.029 to -0.001 |
| Somatic Complaints                                 | -0.012        | 0.007            | -1.85 | 0.064  | -0.025 to 0.001  |
| Social Problems                                    | 0.011         | 0.008            | 1.35  | 0.178  | -0.005 to 0.027  |
| Thought Problems                                   | 0.013         | 0.007            | 1.88  | 0.060  | -0.001 to 0.026  |
| Rule-Breaking                                      | -0.004        | 0.008            | -0.54 | 0.590  | -0.021 to 0.012  |

Given  the  relatively  high  levels  of  correlation  between  them,  we  also  conducted  a  principal  components analysis of SRS total score and CBCL subscale scores in a preliminary assessment of whether a summary measure of these individual scales and subscales could  be  used  to  distinguish  between  ADHD  subtypes.  We implemented principal components analysis using the principal-component factor (pcf) method available  in  STATA,  which  analyzes  a  correlation matrix  in  which  the  communalities  (numbers  on  the diagonal of the correlation matrix) are assumed to be 1.  We  examined  the  relationship  between  the  first unrotated factor from this analysis and the first factor from  the  SWAN  principal  components  analysis  for individuals  with  only  inattentive  symptoms,  only  hyperactive-impulsive  symptoms,  and  both  types  of symptoms.

## Results

Thirteen percent of the 5,744 subjects meet symptom criteria  for lifetime ADHD  based  on  the  screening interview,  and  11%  for current ADHD based on the SWAN.  The current inattentive  group  (DSM-IA)  includes  119  females  and  213  males,  the  hyperactiveimpulsive  (DSM-HI)  group  includes  26  females  and 52  males,  and  the  combined  type  ADHD  group (DSM-C) includes 31 females and 94 males. The baseline  (currently  unaffected)  group  includes  2,602  females and 2,527 males.

As seen in previous studies, subjects with combined type ADHD have more severe psychopathology than other  ADHD  subtypes  (Figure  1).  Not  surprisingly, the highest separation is attained for the CBCL attention problems  and  aggressive behavior subscales. There are no statistical differences between the DSMHI and DSM-IA subtypes on the social problems and rule-breaking behavior subscales. Although  clearly different  from  baseline,  we  find  no  difference  between  the  DSM-IA, DSM-HI, and DSM-C subtypes on  the  withdrawn/depressed  and  the  somatic  complaints subscales. Finally, there is a gradual increase in severity  on  the  anxious/depressed  subscale,  in  the order baseline < DSM-IA < DSM-HI < DSM-C, but without clear group separation.

Bivariate ordered probit regression models are summarized in Tables 1-2. In females, when predicting  inattentive  symptom  counts,  we  retained  SRS score as well as scores on five CBCL subscales: anxious/depressed,  withdrawn/depressed,  somatic  com- plaints, attention problems, and rule-breaking. In the model  for  hyperactivity  symptoms,  we  retained  age, SRS and four CBCL subscales: withdrawn/ depressed, thought problems, attention problems, and aggressive behavior. The residual correlation (between the IA and HI latent dimensions) was 0.33 (95% CI: 0.27 - 0.41). Follow-up  ROC  analyses  for  these  two  models  to predict  the  presence or absence of six of more inattentive  or  hyperactive-impulsive  symptoms,  respectively, show good specificity and sensitivity (AUC=0.93 and 0.90).

The residual correlation between the IA and HI latent dimensions was comparable in the male subsample (0.39, 95% CI: 0.33 - 0.45). There were significant associations  of  the  latent  inattentive  dimension  with SRS  score  and  scores  on  the  CBCL  subscales  for anxious/depressed,  withdrawn/    depressed,  thought problems and attention problems. For the HI dimension,  age,  SRS  and  the  CBCL  subscale  scores  for withdrawn/depressed, attention problems and aggressive behavior were significant.  Follow-up ROC analyses  using  the  predicted  values  from  these  models  to predict  the  presence  or  absence  of  six  or  more  inattentive  or  hyperactive-impulsive  symptoms  show,  as for females, good specificity and sensitivity (AUC=0.93 and 0.91, for inattention and hyperactivity-impulsivity, respectively).

We then used linear discriminant analysis to assess the  ability  to  distinguish  between  ADHD  subtypes using information from age, gender, the SRS and the CBCL subscales (Table 4). The measures used in the discriminant analyses are the predicted means (probit) from the models described previously. Note that different predictors are used depending on the outcome measure  (e.g.,  inattentive  vs.  hyperactive/  impulsive symptoms) and gender, as described above.  Based on these  measures  which  were  not  designed  to  assess ADHD, the ability to discriminate between unaffected and the combined subtype was very good, with positive  predictive  values  (PPV)  and  negative  predictive values  (NPV)  over  83%  and  96%,  respectively.  In females,  the  lowest  PPV  was  observed  for  discriminating  between  the  inattentive  and  combined  subtypes. In males, the lowest PPV was for the contrast between  the hyperactive/impulsive  and  combined subtypes.

Table 3. Principal Components Analysis of SWAN items.

(N=5744 children) Principal components analysis of the 18 SWAN ADHD symptom items yields the well documented two factor solution, accounting for approximately 80% of the variance. The first principal component is severity score, with loadings approximately equal. The second associates positive loadings to inattentive items and negative loadings to hyperactivity items. Abbreviated version of item content is shown in the left column.

| Swan Item               |   Factor 1 |   Factor 2 |   Uniqueness |
|-------------------------|------------|------------|--------------|
| 1. Careless mistakes    |       0.80 |       0.36 |         0.23 |
| 2. Sustain attention    |       0.85 |       0.28 |         0.19 |
| 3. Listen               |       0.86 |       0.14 |         0.25 |
| 4. Finish work          |       0.83 |       0.37 |         0.17 |
| 5. Organize tasks       |       0.82 |       0.41 |         0.16 |
| 6. Sustain effort       |       0.82 |       0.35 |         0.21 |
| 7. Keep track of things |       0.82 |       0.35 |         0.20 |
| 8. Ignore stimuli       |       0.79 |       0.17 |         0.34 |
| 9. Remember activities  |       0.83 |       0.26 |         0.23 |
| 10. Sit still           |       0.86 |      -0.20 |         0.23 |
| 11. Stay seated         |       0.87 |      -0.21 |         0.19 |
| 12. Running/Climbing    |       0.79 |      -0.22 |         0.33 |
| 13. Play quietly        |       0.82 |      -0.35 |         0.20 |
| 14. Control activity    |       0.85 |      -0.35 |         0.16 |
| 15. Control talking     |       0.80 |      -0.37 |         0.23 |
| 16. Control blurting    |       0.83 |      -0.32 |         0.21 |
| 17. Await turn          |       0.84 |      -0.35 |         0.17 |
| 18. Control intruding   |       0.80 |      -0.33 |         0.26 |

Table 4. Percentage correct ADHD subtype classification based on scores derived from age, gender, SRS, and CBCL subscales.

Base=baseline (unaffected); IA=inattentive subtype; HI= hyperactiveimpulsive subtype; CB= combined subtype ADHD.  Linear discriminant analysis readily distinguishes between ADHD subtypes using information from age, gender, SRS score and CBCL subscales. The ability to discriminate between unaffected and combined subtype ADHD was very good, with positive predictive values (PPV) and negative predictive values (NPV) over 83% and 96%, respectively. In females, the lowest PPV was observed for discriminating between inattentive and combined subtypes. In males, the lowest PPV was for the contrast between the hyperactive/impulsive and combined subtypes

| Gender   | Contrast    | Base   | IA   | HI   | CB   | PPV   | NPV   |
|----------|-------------|--------|------|------|------|-------|-------|
| Females  | Base vs. IA | 93%    | 80%  | --   | --   | 80%   | 93%   |
|          | Base vs. HI | 88%    | --   | 65%  | --   | 65%   | 88%   |
|          | Base vs. CB | 96%    | --   | --   | 89%  | 89%   | 96%   |
|          | IA vs. HI   | --     | 75%  | 87%  | --   | 87%   | 75%   |
|          | IA vs. CB   | --     | 78%  | --   | 56%  | 56%   | 78%   |
|          | HI vs. CB   | --     | --   | 78%  | 74%  | 74%   | 78%   |
| Males    | Base vs. IA | 89%    | 73%  | --   | --   | 73%   | 89%   |
|          | Base vs. HI | 89%    | --   | 73%  | --   | 74%   | 90%   |
|          | Base vs. CB | 95%    | --   | --   | 83%  | 83%   | 96%   |
|          | IA vs. HI   | --     | 76%  | 67%  | --   | 67%   | 76%   |
|          | IA vs. CB   | --     | 77%  | --   | 67%  | 67%   | 77%   |
|          | HI vs. CB   | --     | --   | 74%  | 66%  | 65%   | 73%   |

A principal  components analysis of the 18 SWAN current ADHD symptom items yields the well docu- mented two factor  solution,  accounting  for  approximately 80% of the variance (Table 3). The factor loadings are remarkably close to what we observe for the lifetime  ADHD  screener  data.  The  first  component represents 'severity', with approximately  uniform factor  loadings  across  all  items.  The  second  component assigns a positive loading to inattentive items and a negative loading to hyperactive-impulsive items, and differentiates  between  predominantly  inattentive  versus hyperactive-impulsive, with the same overall level of severity. The factor loadings are fairly uniform, but not  identical.    Thus,  the  correlation  between  simple symptom  counts  and  factor scores is very high (>95%),  but  imperfect.  The  implication  is  that  a number of children could be 'misdiagnosed' under a simple counting scheme that assigns equal weight to all items (in Figure 2, a number of such 'misdiagnoses' are visible).

There  are  strong  correlations  and  partial  correlations  between  the  SRS  total  score  and  CBCL  subscores  (Table  5).  Figure  3  plots  the  predicted  first factor  score  (without  rotation)  derived  from  these measures,  against  the  first  factor  score  for  the  18 SWAN ADHD items.  Three  curves  are  shown,  for individuals  with  zero  hyperactive/impulsive  symptoms (green), zero inattentive symptoms (orange), and at  least  one  symptom  of  each  category  (red).  Inasmuch as SWAN Factor 1 correlates very highly with the actual number of symptoms, this shows that, for the same number of symptoms, individuals who present with both inattentive and hyperactive/impulsive symptoms  also  tend  to  present  with  higher  severity with respect to a summary score of the SRS and the CBCL  subscales.  Note  that  at  low  SWAN  severity scores,  the  lines  are  almost  flat,  and  the  mean  SRSCBCL factor scores are not different between groups. At  higher  SWAN  severity  scores,  the  slopes  of  the lines  increase  and  there  is  a  statistically  significant separation of the predicted SRS-CBCL severity factor scores between groups, with the lowest severity in the HI-only  group,  intermediate  severity  in  the  IA-only group, and the highest severity in the group with both IA and HI symptoms.

There are 250 individuals in our sample with at total of at least 6 current DSM-IV ADHD symptoms, who do  not  meet  criteria  for  a  specific  DSM-IV  ADHD subtype. On average, these 250 individuals have four inattentive and three hyperactive-impulsive  symptoms. In Figure 2, these subjects would be near the center of the scatter-plot, just below the affection cutoff  by  DSM-IV  symptom  criteria.  Interestingly,  this group appears to have higher severity of co-occurring psychopathology than pure inattentive or pure hyperactive-impulsive subjects with equivalent total ADHD severity (Figure 3).

Table 5. Correlations (bottom) and partial correlations (top) between SRS score and CBCL subscale scores. All correlations significant with p < 0.0001 (Bonferoni adjusted). Correlations between the SRS score and CBCL scales on N = 4982; Correlations between CBCL subscales on N = 5737. Only partial correlations greater than 0.10 are shown. Note that while the overall correlation shows Rule-breaking (Rule) is positively correlated with the Anxious/Depressed (Anx/Dep) scale, the partial correlation indicates these two scales are negatively correlated after controlling for other psychopathology. CBCL subscale abbreviations: Attention= Attention problems; Thought= Thought problems; Anx/Dep= Anxious/Depressed; With/Dep=Withdrawn/Depresssed; Somatic=Somatic complaints; Social= Social problems; Rule= Rule-breaking; Aggr=Aggressive behavior

|           | SRS    | Attention   | Thought   | Anx/Dep   | With/Dep   | Somatic   | Social   | Rule     | Aggr   |
|-----------|--------|-------------|-----------|-----------|------------|-----------|----------|----------|--------|
| SRS       | -- --  | 0.2874      | 0.1302    |           | 0.3398     |           | 0.2891   |          |        |
| Attention | 0.6300 | -- --       | 0.1769    |           |            |           | 0.1410   | 0.1253   | 0.1647 |
| Thought   | 0.5305 | 0.5133      | -- --     | 0.1574    |            | 0.1719    |          |          |        |
| Anx/Dep   | 0.5399 | 0.4037      | 0.4892    | -- --     | 0.2387     | 0.1970    | 0.2700   | - 0.1203 | 0.1368 |
| With/Dep  | 0.6140 | 0.4098      | 0.4118    | 0.5438    | -- --      | 0.1372    |          | 0.1308   |        |
| Somatic   | 0.3539 | 0.3160      | 0.4119    | 0.4617    | 0.3882     | -- --     |          |          |        |
| Social    | 0.6728 | 0.5801      | 0.4918    | 0.6071    | 0.5092     | 0.4145    | -- --    |          | 0.2236 |
| Rule      | 0.4354 | 0.5040      | 0.3982    | 0.3073    | 0.3757     | 0.2728    | 0.4409   | -- --    | 0.5246 |
| Aggr      | 0.5700 | 0.5967      | 0.4934    | 0.5006    | 0.4390     | 0.3706    | 0.6274   | 0.6867   | -- --  |

## Discussion

This  analysis  supports  the  continued  use  of  ADHD subtypes, or 'presentations', as they may be called in DSM-5  (20), as suggested by differences in cooccurring  psychopathology.    As  different  psychopathology  subscales  were  more  or  less  associated  with IA versus HI symptoms (and with ADHD subtypes), the  pattern  of  ADHD  symptom  presentation  may inform  clinicians  about  risk  for  various  co-occurring conditions  and  overall  severity  or  impairment.  We observe ADHD subtype differences in severity of cooccurring  psychopathology,  not  only  at  the  extreme, but  also  in  the  range  of  mild  to  moderately  severe ADHD.  Children  with  low-level  symptoms  in  both the inattentive and the hyperactive-impulsive domain, but  with  a  significant  number  of  total  symptoms overall, are likely to be just as impaired (or more impaired)  than  individuals  with  the  same  overall  total ADHD severity but with symptoms in only one of the two domains.

Our results underscore the fact that current diagnostic criteria may fail to identify a potentially impaired group of children with significant levels of both inattention and hyperactivity-impulsivity. These children, who could be classified as ADHD Not Oth- erwise Specified (ADHD-NOS) according to DSMIV, have significant impairment and co-occurring problems. As these individuals have, on average, 4 inattentive and 3 hyperactive-impulsive symptoms, they could also be described as having a mild combined subtype of ADHD. In a separate Missouri population-based sample, analyses indicated that a 'mild combined' form of ADHD was one of 3 clinically impaired latent class ADHD subtypes (5), and was also characterized by elevated levels of autistic traits (9). On the other hand, it could be argued that some children with moderate ADHD symptoms may not have true ADHD but rather another disorder with symptoms that overlap with ADHD. Arguably, depression or oppositional-defiant disorder, for example, might respectively lead to high internalizing or externalizing symptoms, and mimic the pure inattentive or pure hyperactive-impulsive ADHD subtype. Differences in comorbid psychopathology between subtypes (Figure 3) could be due to the inclusion of individuals with disorders other than ADHD that mimic ADHD symptoms.

The CBCL and the SRS did rather well in distinguishing ADHD subtypes in this population-based sample, even though they were not designed for that purpose. This supports the use of quantitative measures of ADHD (such as the SWAN) and  other forms of psychopathology (i.e., SRS, CBCL) in order to obtain a more complete picture of overall severity and co-occurring problems. In particular, even after removing SRS items with wording that may pick up on ADHD-like symptoms, SRS scores remain mildly elevated for hyperactive-impulsive and inattentive SWAN Factor 1 (Severity)

Inattentive

6 IA sx Hyperactive

6 HY sx

ADHD, and even further elevated in combined type ADHD (9). Children with ADHD symptoms plus very high (clinically elevated) SRS scores may have a combination of ADHD plus a true autism spectrum disorder. However, it may be that moderately elevated SRS scores in the context of ADHD are sometimes indicators of general psychosocial impairment, social impairment directly due to ADHD symptoms, and/or social anxiety symptoms, resulting in SRS scores that are above normal but not in a range indicating a clinical diagnosis of autism spectrum disorder. The SRS may be a measure of overall level of psychopathology across its entire scoring range, such that children with the highest severity levels of ADHD, or even the highest levels of overall psychopathology, will always show some autistic-like social impairment. Within this conceptualization, children with autism might be considered to have the most severe and pervasive form of childhood psychopathology.

Figure 2. Relationship between severity and symptom type factors derived from the SWAN, and DSM-IV diagnosis.  Each circle is an observation. Color indicates DSM-IV subtype (Blue= No diagnosis, Green= Inattentive, Orange= Hyperactive-Impulsive, Red= Combined type ADHD).  Black lines: Created using linear regression of factor 2 on factor 1, using only those subjects with exactly 6 inattentive or exactly 6 hyperactive-impulsive symptoms. Some individuals in the center of the plot do not meet the DSM-IV symptom criterion (<6 symptoms in both categories), but actually have a total severity factor score equal to some individuals classified as having inattentive or hyperactiveimpulsive type ADHD.

<!-- image -->

This study has some limitations.  We could not confirm true DSM-IV ADHD diagnoses given the absence of age-of-onset and current impairment data, but the purpose of the current analyses was to examine the relationship between ADHD symptoms and co-occurring psychopathology, not to determine

Combined prevalence of categorical diagnoses defined exactly as in DSM-IV. Because we did not consider age-of-onset or impairment criteria, our estimated SWAN-based ADHD prevalence (11%) could be slightly higher than the number meeting full criteria for true DSMIV ADHD. However, lifetime ADHD symptoms were not considered positive unless impairment at home and/or school was reported, and 95% of subjects classified as having current ADHD based on the SWAN had at least one lifetime impairing ADHD symptom on the telephone screening interview, indicating that most had a history of impairment from their ADHD symptoms. Therefore, we expect our estimates to be close to the true prevalence of DSMIV ADHD (with consideration of impairment) in Missouri children. Reasonably consistent with our estimates, the United States Centers for Disease Control and Prevention (CDC) reported an ADHD prevalence of 10.8 percent for 4-to-17-year-old children in Missouri for the year 2007 based on parentreported history of ADHD diagnosis (27), and an estimated 6.7 percent of Missouri 14-to-17-year-old children were taking medication for ADHD in 20072008 (28).  It may also be argued that our method of ascertainment (large families) might limit the generalizability of this study. Although our sample is not subject to the referral bias that occurs with clinicbased samples, our sample was selected based on large family size and availability of parents for potential future genetic study. There is also the possibility that parents who have ADHD symptoms themselves might be less likely to return questionnaires. However, we found no evidence for selection bias based on ADHD diagnosis in this sample (21). The sample is also almost entirely Caucasian, so it is unclear whether the current findings are generalizable to individuals of other racial and ethnic backgrounds. Also, we were unable to control for socioeconomic factors since we did not have socioeconomic data regarding the study subjects.

ADHD subtypes are useful concepts in terms of understanding a child's symptoms and formulating appropriate educational plans and behavioral interventions. However, the requirement that a child meet a specific DSM-IV ADHD subtype category in order to be diagnosed and treated is not satisfactory. The current study suggests it may be important to consider both overall severity and relative contribution of inattentive vs. hyperactive-impulsive symptoms.  Indeed, if only total severity is used, it is possible that some clinically impaired individuals with impairing inattentive-only symptoms might be missed. However if at Main Factor from SRS and CBCL subscales

8 - Both inattentive and hyperactive/impulsive symptoms

-2

least 6 symptoms in one or the other symptom category is required, then clinically impaired individuals with just a few symptoms in each category (i.e., 5 inattentive plus 5 hyperactive-impulsive symptoms) may be missed. These individuals may be best identified by measures of total severity (i.e., a total symptom count or a quantitative symptom rating based on an instrument such as the SWAN).

Figure 3. Plot of the first factor score from a factor analysis of SRS total score and CBCL subscores, against the first factor score for the 18 SWAN ADHD symptoms. The curves were built using fractional polynomials (shaded area: approximate 99% confidence interval) and indicate predicted mean SRS-CBCL factor score given the SWAN severity score. Three curves are shown, for individuals with zero hyperactive/impulsive symptoms (green), zero inattentive symptoms (orange), and at least one symptom of each category (red). Inasmuch as SWAN Factor 1 correlates very highly with the overall number of symptoms, this shows that, for the same number of symptoms, individuals who present with both inattentive and hyperactive/ impulsive symptoms tend to present with higher severity with respect to the SRS score and CBCL subscales.

<!-- image -->

In  terms  of  clinical  relevance,  we  found  that  children  with  mild  to  moderate  ADHD  symptoms  may have different levels of co-occurring psychopathology depending on ADHD subtype, those with both inattentive  and  hyperactive-impulsive  symptoms  having the  highest  overall  levels.  Also,  children  and  adolescents who have several ADHD symptoms but do not technically meet current ADHD criteria due to lack of 6  symptoms  in  one  or  the  other  symptom  category should  not  be  overlooked.  In  the  DSM-IV  context, such individuals could be given a diagnosis of ADHD Not Otherwise Specified (NOS) if they have clinically significant impairment from their ADHD symptoms. Proposed changes for DSM-5 include replacement of ADHD-NOS by a 'Not Elsewhere Classified (NEC)' diagnosis which could be used to describe individuals who fail to meet the full ADHD criteria due to sub- threshold number of symptoms (20). It will be important for clinicians to consider using the new ADHDNEC diagnosis for clinically impaired individuals who have approximately 6-10 total ADHD symptoms but less than six symptoms in each of the two symptom domains.

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## Acknowledgements

This  work  is  dedicated  to  Richard  D.  Todd,  Ph.D., M.D.,  who  initiated  data  collection  for  this  project. Dr.  Todd  died  from  complications  of  leukemia  August  22,  2008.  This  work  was  supported  by  award numbers R01-MH-067921 (PI-RDT, then AAT), R01-MH-083823 (PI-AAT), and K08-MH-080287 (PI-AMR)  from  the  National  Institute  of  Mental Health (NIMH). The content is solely the responsibility  of  the  authors  and  does  not  necessarily represent the official views of the NIMH or the National Institutes of Health.