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Supplemental Information
SAMPLE CHARACTERISTICS,PARTICIPANTS’ STATE OF RESIDENCY,AND
STUDY ENROLLMENT
This study protocol was approved bythe Human Research
ProtectionOffices and IRBs of WashingtonUniversity School of
Medicine (IRB201105377), Emory UniversitySchool of Medicine (IRB
00059192),University of California, Los Angeles(IRB 14-000312), and
Albert EinsteinCollege of Medicine (IRB 2012-537).
The majority of the children in thisstudy resided in the states
of Missouri(n = 193), Georgia (n = 175),California (n = 131), and
New York(n = 65); the remaining familiesreported residency in
Illinois (n = 10),New Jersey (n = 2), Arizona (n = 1),Florida (n =
1), Jamaica (n = 1),Michigan (n = 1), Tennessee (n = 1)and Virginia
(n = 1). In Missouri, 1 ofthe 4 states from which children
wereenrolled in this study, the most recentCDC surveillance data
revealed that27.3% of AA children versus 38.9% ofNHW children
receiveda comprehensive developmentalevaluation by the age of 3
years (P, .03).
Study enrollment was based on localadvertisement and
recruitment;therefore, it was not possible to knowwhether there
were biases amongenrollees in comparison with allfamilies exposed
to advertisingmaterial or knowledgeable about thestudy, except by
comparing samplecharacteristics to epidemiologicallyacquired data
as conducted in theanalyses presented. Once familiesconsented to
participation in the
study, the dropout rate was negligible.Enrollment criteria
included thefollowing: (1) individual aged $3years, (2) $1
biological parentavailable to participate, (3) diagnosedwith or
suspected of having ASD, and(4) index child of AA or biracial
AAdescent. Prematurity (gestational age,34 weeks for single
births,33 weeks for multiple gestation) andother known genetic
conditions wereexclusion criteria. Approximately12% of the sample
were multiplexfamilies (n = 59 families: .1 childdiagnosed with ASD
participating inthe study). The mean age of childrendiagnosed with
ASD was115.9 months 6 59.0.
GENETIC CONFIRMATION OF AFRICANANCESTRY
We confirmed the presence of Africanancestry for each patient
usingmultidimensional scaling analysis ofsingle-nucleotide
polymorphismgenotype data. Subjects weregenotyped by using the
IlluminaOmni-2.5 microarray (Illumina, SanDiego, CA). After quality
filtering,multidimensional scaling wasperformed in PLINK
(http://zzz.bwh.harvard.edu/plink/) together withthe HapMap 3
reference
panel(https://www.sanger.ac.uk/resources/downloads/human/hapmap3.html).15,16
Examination ofthe first 2 principle componentsshows clear
separation of theancestral African populations fromHapMap (Luhya in
Webuye, Kenya;Maasai in Kinyawa, Kenya; Yoruba inIbadan, Nigeria)
and white
individuals from HapMap (Utahresidents with Northern and
WesternEuropean ancestry; Toscani in Italy).Patients from the
current studyexhibit principal component valuesbetween those
observed for whiteand African individuals fromHapMap3, reflecting
admixturebetween the populations andresembling the HapMap
populationAfrican ancestry in Southwest UnitedStates. Refer to
Supplemental Fig 1.
DEVELOPMENT OF EVENT HISTORYCALENDAR INTERVIEW:
DIAGNOSTICODYSSEY
The Event History CalendarInterview: Diagnostic Odyssey
toolcontains 6 sections: (1) first concernsand help-seeking
experiences; (2)demographics, socioeconomic status,household
composition, social capital;(3) first ASD diagnosis; (4) first
timespecial services were started (earlyintervention, private
interventions,and/or school-aged specialeducation); (5)
interactions withother gateway service systems; and(6) appraisal of
overall odyssey. Thisinterview uses event history calendarinterview
methods (researchmethods that aim to improve theaccuracy and
completeness of eventrecall by employing autobiographicalmemories
as cues for recollecting thedetails of interrelated events)
toenhance accuracy of parent orcaregiver recall regarding
theirexperiences seeking an ASD diagnosisand services for their
child.17,18 Eventhistory calendar interview methodsare incorporated
into the
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instrument’s design. Memory primingquestions are key components
ofadministration; parents are cued torecall details about salient
events,such as a special birthday party, asa landmark referent
event. As theinterview proceeds, other specialevents and key
milestones (eg, firstconcerns, age of diagnosis) or socialrole
changes (eg, births, divorce, jobchanges) are queried and are used
asa point of reference throughout theinterview. Highly
memorablepersonal and historical “landmarks”that informants can
vividly recall (eg,birthdays, starting a new job, moving,death in
the family, etc) are used toprime recall before asking
surveyquestions about life events at thecenter of inquiry.19221
Extensivedescriptions of these methods havebeen summarized in Belli
et al.17
To enable comparisons withpopulation-based benchmarkestimates,
the Diagnostic OdysseyInterview items regarding diagnosisand entry
to services were adaptedfrom national surveys when
possible,including the National Survey ofChildren with Special
Health CareNeeds, the Interactive AutismNetwork Online Survey, the
NationalLongitudinal Transitions Study-2, andthe Survey of Pathways
to Diagnosisand Services.22224 Other questionitems were adapted
from the PhenXToolkit, a web-based toolkit ofrecommended measures
ofphenotypes and environmentalexposures for biomedical
research.25
In some cases, questions and/orresponse categories were modified
tocapture potential culturally relevantdifferences. For example, a
queryabout to whom parents first reportedconcerns was modified to
includeresponse categories for child careproviders and clergy.
Questions werereviewed and modified on the basis ofinput from the
study research team,an administrator from a federallyqualified
health care center thatoperates an ASD diagnostic clinic fora
predominately AA population, and
an AA research assistant from the StLouis site. The tool was
then pilottested in partnership with 10 AAfamilies and modified
accordingly.Average interview length is ∼45 to60 minutes. The
Diagnostic Odysseyinstrument was designed bycoauthors P.S, A.R.,
D.M., and J.C. forpurposes of this research protocol.
In a small validation sample of 25NHW children (mean age = 170.2
676.3), representing 3 of the networksites (Washington University =
13,Albert Einstein = 10, EmoryUniversity = 2), we conducted
theDiagnostic Odyssey Interviews bytelephone. In this sample,
NHWfamilies reported first concerns withtheir child’s development
at roughlythe same time as AA families (mean =24.2 months 6 31.6;
median = 15.0).
ASD CLINICAL SEVERITY AND VERBALOR NONVERBAL DESIGNATION
For selected analyses, clinical severitywas categorized on the
basis of ADI-Rsocial and restricted or repetitivebehavior domains
to provide anhistorical indicator of level of ASDsymptom burden in
early childhood(ie, around the time when diagnosesare first made).
Categorical verbaland nonverbal status was alsodetermined by using
ADI-Rdesignation (if ADI-R unavailable, SCQquestion 1 was
used).
DESCRIPTION OF COGNITIVEASSESSMENTS, CALCULATION OFPROXY-IQ FOR
PARTICIPANTS WITHASD, AND COGNITIVE ASSESSMENT OFUNDIAGNOSED
FIRST-DEGREERELATIVES
The Differential Ability Scales, SecondEdition (DAS-II) was
first attemptedon all participants with ASD between3 years, 0
months and 17 years, 11months. For participants who wereunable to
complete the nonverbalsubtests of the DAS-II, the Raven’sColoured
Progressive Matrices (CPM)was administered; similarly,
ifparticipants were unable to complete
the verbal subsets, the PeabodyPicture Vocabulary Test,
FourthEdition (PPVT-4) was administered.At the Emory site, the
Mullen Scalesof Early Learning (MSEL) wasadditionally administered
if the childwas unable to complete the othermeasures because of
level ofcognitive impairment, and a proxy forIQ was estimated.
Participants withASD aged $18.0 years old wereadministered the
Raven’s ProgressiveMatrices and PPVT-4. An IQ-proxyscore was
calculated for allindividuals with ASD by selecting 1available
cognitive standard score. Aclassification of “untestable due tolow
level of functioning” wasassigned for children who wereunable to
perform at the minimallevel required to calculate a verbal
ornonverbal IQ score on any of thecognitive measures, and
clinicianjudgement determined this wasattributable to low cognitive
ability(ie, rather than behavioraldisruptions).
Cognitive assessment of undiagnosedfirst-degree relatives was
conductedby using the Ravens ProgressiveMatrices. Distributions of
IQ scoresfor index cases and first-degreerelatives are presented
inSupplemental Table 8 andSupplemental Figs 2 and 3.
DAS-II
The DAS-II is a battery of cognitiveassessments nationally
normed forchildren between the ages of 2 years,6 months to 17
years, 11 monthsacross a range of developmentalabilities. There are
20 subtests thatare grouped into the early years andschool-age
cognitive batteries andcombine to provide an overall
GeneralConceptual Ability score, or overall IQscore. The core
subtests from eachbattery were administered to thechildren on the
basis of their age andability level.
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Raven’s Progressive Matrices(Raven’s)
The Raven’s26 is an abstractreasoning measure that providesa
nonverbal estimate of fluidintelligence. Participants arepresented
with a nonverbal reasoningtask in which they are shown anincomplete
pattern construction andthen asked to identify the correctmissing
piece to complete the pattern.In the current study, we used
2versions of the scale, the StandardProgressive Matrices (SPM) and
theCPM. The SPM consists of 5 sets of12-item trials, printed in
black andwhite, and stimuli becomeincreasingly more challenging as
theitem administration within each setprogresses. The SPM version
wasadministered to any first-degreerelative without a diagnosis of
an ASDaged 11 years or older. The CPMcontains 3 sets (A, Ab, B) of
12 stimulipresented on a colored background.The CPM version was
administered toparticipants with a diagnosis of anASD and any
unaffected child underthe age of 11 years; if the
participantreached a ceiling on all items of theCPM, clinicians
administered theadditional 2 sections of the SPMversion.
Researchers have shown thatchildren and adults with ASD tend
toperform higher on the RavenProgressive Matrices than
othermeasures of nonverbal intelligence.27
PPVT-4
The PPVT-4 is a measure of receptivevocabulary knowledge that
providesan estimate of verbal intelligence. ThePPVT-4 was
administered toindividuals diagnosed with ASD ifthey were unable to
complete theverbal intelligence subtests of theDAS-II.
MSEL
The MSEL is used to assessdevelopmental abilities in
childrenfrom birth to 5 years, 8 months. Thereare 5 subtests on the
MSEL: grossmotor, visual reception, fine motor,
expressive language, and receptivelanguage. If a participant was
unableto complete the DAS-II secondary tolanguage or cognitive
skills beingbelow the 2 year, 6 month level, thenthe MSEL was used
to obtaina developmental quotient. Twochildren, at the Emory
University site,were administered the MSEL.
Derivation of IQ Proxy
An IQ-proxy was calculated for allindividuals with ASD by
selecting 1available cognitive standard score inthe following
order: (1) DAS-II, (2)Raven’s, (3) PPVT-4, (4) MSEL. Weconverted
Raven’s percentiles todeviation IQ scores for comparisonacross the
SPM and CPM versions toinvestigate the relationship betweenthe IQ
scores of individuals with ASDand their first-degree relatives.
Thecorrelation between Raven deviationIQ scores and proxy-IQ scores
forindividuals with ASD was r = .70, n =70, P , .001. Means and SDs
andcorrelations for cognitive measuresare presented in
SupplementalTable 7.
OVERLAP OF THE MISSOURI SAMPLEWITH 8-YEAR-OLDS ASCERTAINED
FROMTHE US CDC ADDM PROGRAM
ADDM and NIH MH100027 MissouriAutism Genetics Network Overlap
isas follows: We examined the extent towhich research subjects
overlappedwith and were representative ofindividually abstracted
data recordsidentified by the Missouri site of theCDC’s ADDM
Network. Cases wereselected for cross-data set analysis forCDC
surveillance birth years 1996,1998, 2000, 2002, 2004, 2006,
and2008. This analysis revealed that CDCsurveillance at the
Missouri ADDMsite failed to identify 56.3% (76 of135) of cases
enrolled into the AutismGenetics Network and subsequentlyconfirmed
as an ASD case bya licensed clinical psychologist orpsychiatrist.
This reflects long-standing disparities in communitydiagnosis that
have only recently
attenuated in the 2006 and 2008birth cohorts. Next, we
investigatedwhether cases that were ascertainedin Missouri by ADDM
reflected thenational racial disparity in comorbidID, as reported
by the CDC, for StLouis City and St Louis County. Fortypercent (333
of 824) of MissouriADDM (MO-ADDM) ASD casesgeocoded to St Louis
County or StLouis City from surveillance years2002 to 2012 had data
on intellectualability in their surveillance record.We found that
occurrence of ID,defined as a score #70 on the mostrecent cognitive
test, was significantlyhigher in AA children (37.6%, 26/69)compared
with NHW children(21.2%, 56 of 264, P , .001).
To determine if ID documented byADDM was confirmed
amongparticipants who were directlyassessed in our research study,
wereviewed IQ scores of childrenidentified by both MO-ADDM and
theAutism Genetics Network. Seven outof 8 children identified by
MO-ADDMwith a documented IQ score of #70performed in the ID range
oncognitive testing as assessed underthe Autism Genetics
Networkprotocol [ranging from IQ #75 or“untestable” because of
cognitiveability] (see Supplemental Table 9),indicating strong
agreement betweenthe epidemiological (CDC) and clinical(Autism
Genetics Network)ascertainment strategies.
Mean parent-report SocialResponsiveness Scale T-scores and
IQscores did not differ significantlywhen comparing children who
wereidentified by both MO-ADDM and theAutism Genetics Network
researchprogram with children enrolled solelyin the Autism Genetics
Networkresearch program; SocialResponsiveness Scale scores were
asfollows: matched sample (N = 46),mean = 83.21, SD = 12.54;
AutismGenetics Network only (N = 61), mean= 79.89, SD = 10.85; P ,
.15; IQScores: matched sample (N = 31),mean = 79.29, SD = 10.85,
Autism
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Genetics Network only (N = 56) mean= 84.55, SD = 17.69; P ,
.19.
Finally, the ADDM network collectsdata on several associated
features orconditions that are known to beassociated with ASD but
are notnecessarily part of the diagnosticcriteria. This includes
the mention ofseizures or seizure-like activity. Whilereviewing
surveillance records,ADDM Network clinician reviewersdocument if
there was mention of anyof the 15 ADDM associated features.For the
co-occurrence of seizures orepilepsy, seizure-like activity
wascoded for 31% of NHW comparedwith 33% of AA Missouri ADDM
ASDcases from surveillance years 2002 to2010 (n = 1232 ASD
cases).
HIERARCHICAL REGRESSION ANALYSIS
Building models hierarchicallyenabled examination of
theproportion of variance uniquelyattributable to a given
predictorabove and beyond predictorsincluded in reduced models.
Forexample, the proportion of varianceuniquely attributable to age
of ASDdiagnosis may be calculated as 4R2 =(R2 model 3) – (R2 model
2), and theproportion of variance uniquelyattributable to age of
walking onsetmay be calculated as 4R2 = (R2model 4) – (R2 model 3).
Income andage of ASD diagnosis were logtransformed to adjust for
skew, andgestation duration (,37 weeks vs$37 weeks) and age of
walkingonset (,16 months vs $ 16 months)were dichotomized. For the
primaryregression analysis, we restricted thesample to subjects who
werediagnosed before the age of 8 years sowe could more directly
compare ourresults to CDC surveillance data andbecause there was a
wide range ofages represented by the groupdiagnosed after 96
months, whichwould potentially confoundassociations between early
predictorsand cognitive characteristics of thesubjects. Likelihood
ratio tests were
used to determine the significance ofincremental variance
explained (ΔR2).Statistical analyses were performed inSPSS 25.0 and
R 3.5.1. (IBM SPSSStatistics, IBM Corporation).
STRATIFICATION OF THE SAMPLE BASEDON IQ-PROXY SCORES OF
PARTICIPANTSWITH ASD
The sample was stratified based onthe IQ-proxy scores of
theparticipants with ASD as follows: (1)IQ # 70 or untestable
because of lowlevel of functioning; (2) IQ = 71 to 99;(3) IQ $ 100.
On the basis of thestratification of this variable, ananalysis of
variance was conducted tocompare mother’s Raven deviation
IQ,father’s Raven deviation IQ, andaverage of parent Raven
deviation IQ(Supplemental Table 15).
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SUPPLEMENTAL FIGURE 1Genetic confirmation of African ancestry.
ACE, Autism Center of Excellence (NIH MH10027 Autism Genetics
Network, Phase II: Increasing the Representationof Human
Diversity); ASW, African Ancestry in Southwest United States; CEU,
Utah Residents with Northern and Western European ancestry; CHB,
HanChinese in Beijing, China; CHD, Chinese in Metropolitan Denver,
Colorado; GIH, Gujarati Indians in Houston, Texas; JPT, Japanese in
Tokyo, Japan; LWK, Luhyain Webuye, Kenya; MEX, Mexican Ancestry in
Los Angeles, California; MKK, Maasai in Kinyawa, Kenya; TSI,
Tuscans from Italy; YRI, Yoruba in Ibadan, Nigeria.Examination of
the first three principal components shows that ACE samples are
genetically most similar to HapMap samples of African origin (MKK,
LWK,ASW). The fourth principal component distinguishes between the
African populations and shows that ACE samples are most similar to
individuals ofAfrican ancestry from the Southwest United States
(ASW).
SUPPLEMENTAL FIGURE 2Distribution of IQ-proxy scores for
participants with ASD by Diagnostic Statistical Manual (DSM)–IV
classifications of ID severity. UNT, untestable.
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SUPPLEMENTAL FIGURE 3Distributions of IQ scores for first-degree
relatives in families with ASD. The distributions for IQ-proxy
scores (n = 250; mean = 75.8, SD = 21.9) and Ravendeviation IQ
scores (n = 103; mean = 87.2, SD = 22.4) for participants diagnosed
with ASD are presented in this figure. Raven deviation IQ was
highlycorrelated with IQ-proxy scores (n = 70, r = 0.70, P ,
.0001). A comparison of the distributions in first-degree relatives
of participants with ASD ispresented for nondiagnosed siblings (n =
90; mean = 105.1, SD = 14.3), mothers (n = 162; mean = 91.2, SD =
12.5) and fathers (n = 135; mean = 90.9, SD =13.6). IQ scores of
first-degree relatives are uniform and normally distributed.
SUPPLEMENTAL TABLE 6 Summary Scores of Standardized Assessments
for Participants With ASD
Mean Scores
Male Female Total
N Mean (SD) N Mean (SD) N Mean (SD)
Parent-report SRS T-score 448 77.0 (12.0) 114 78.9 (13.6) 562
77.4 (12.3)Parent-report SCQ total 455 17.6 (6.6) 116 16.8 (6.9)
571 17.4 (6.7)ADOS social affect total 462 11.7 (4.3) 116 10.9
(4.6) 578 11.5 (4.4)ADOS restricted repetitive behavior total 462
4.1 (2.4) 116 3.6 (2.3) 578 4.0 (2.4)Vineland communication total
450 70.3 (14.8) 114 69.1 (15.2) 564 70.0 (14.9)Vineland daily
living skills total 449 70.3 (13.8) 114 69.0 (11.9) 563 70.0
(13.4)Vineland socialization total 450 66.4 (12.5) 114 66.6 (12.7)
564 66.5 (12.5)Vineland adaptive behavior composite 445 67.7 (12.0)
114 66.8 (11.9) 559 67.5 (12.0)ADI-R reciprocal social interaction
total 320 20.4 (5.8) 74 19.9 (6.8) 394 20.3 (6.0)ADI-R
communication verbal total 256 15.1 (4.1) 64 14.8 (5.1) 320 15.0
(4.3)ADI-R communication nonverbal total 64 11.8 (2.6) 10 11.5
(2.9) 74 11.7 (2.6)ADI-R restricted, repetitive, and stereotyped
behavior total 320 6.2 (2.4) 74 5.7 (2.9) 394 6.1 (2.5)
The table summarizes all subjects across all sites for whom each
respective measure was available. SRS, Social Responsiveness
Scale.
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SUPPLEMENTAL TABLE 7 Means and Pearson Coefficients of
Correlations of Cognitive Measures BySite
n WUSTL n Emory n UCLA n Einstein
DAS-II, mean (SD) 141 82.9 (15.4) 143 75.7 (23.1) 89 80.9 (17.5)
36 94.4 (17.0)Raven, mean (SD) 145 90.3 (20.6) 10 76.0 (19.7) 30
62.6 (22.4) 22 85.9 (14.7)PPVT-4, mean (SD) 47 62.3 (32.3) 15 39.2
(25.5) 42 46.1 (26.1) 27 64.1 (20.6)IQ proxy, mean (SD) 189 81.6
(18.7) 159 73.7 (24.2) 128 75.0 (22.0) 62 89.9 (17.2)Untestable 12
— 14 — 0 — 2 —DAS-II and Raven, correlation 102 0.7** — N.I. — N.I.
— N.I.DAS-II and PPVT-4, correlation — N.I. — N.I. — N.I. —
N.I.Raven and PPVT-4, correlation 41 0.8** — N.I. 27 0.7** 20
0.2
N.I., number insufficient to calculate a robust coefficient of
correlation; UCLA, University of California, Los Angeles;
WUSTL,Washington University in St. Louis; —, not applicable.**
Indicates P value significant at .01 level (2-tailed).
SUPPLEMENTAL TABLE 8 Average IQ Scores for Participants With ASD
and Their First-DegreeRelatives by Site
n Age Raven IQ IQ Proxy
Emory, mean (SD)Participants with ASD 139 7.7 (3.8) n = 8, 67.8
(27.1) n = 126, 71.4 (24.0)Nondiagnosed siblings 55 10.1 (5.0)
105.1 (15.3) 105.1 (15.3)Mother 131 38.5 (6.9) 92.3 (12.1) —Father
106 39.7 (7.8) 92.3 (13.3) —
WUSTL, mean (SD)Participants with ASD 130 10.6 (4.8) n = 95,
88.8 (21.4) n = 124, 80.2 (18.7)Nondiagnosed siblings 35 8.2 (2.4)
n = 34, 104.8 (12.9) 105.1 (12.8)Mother 31 37.5 (7.6) 86.52 (13.2)
—Father 29 40.1 (9.0) 85.79 (13.8) —
Total, mean (SD)Participants with ASD 269 9.1 (4.6) n = 103,
87.2 (22.4) n = 250, 75.8 (21.9)Nondiagnosed siblings 90 10.3 (4.5)
n = 89, 105.0 (14.3) 105.1 (14.3)Mother 162 38.3 (7.0) 91.2 (12.5)
—Father 135 39.8 (8.0) 90.9 (13.6) —
WUSTL, Washington University in St. Louis; —, not
applicable.
SUPPLEMENTAL TABLE 9 Measured IQ Scores of Study Participants
Who Overlapped With the CDCADDM Surveillance Program
NIH MH100027 Autism Genetics Network Raven IQ Score
Participant 1 45Participant 2 75Participant 3 90Participant 4
Untestablea
Participant 5 Untestablea
Participant 6 Untestablea
Participant 7 43Participant 8 55
Description of this subset is provided in Overlap of the
Missouri Sample with 8-Year-Olds Ascertained From the US CDCADDM
Program in Supplemental Information.a Children classified as
untestable were unable to complete the measure due to low level of
cognitive functioning.
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SUPPLEMENTAL TABLE 10 Stratification of Sample Based on IQ
Scores of Participants With ASD:Analysis of Variance
N Mean SD ANOVA, P
Mother Raven deviation IQ .53Untestable or #70 77 90.3 12.671–99
61 91.3 12.7$100 24 93.6 11.9
Father Raven deviation IQ .75Untestable or #70 63 91.8 14.271–99
53 90.0 14.0$100 19 90.1 11.0
Average of parental IQ .77Untestable or #70 78 90.9 12.071–99 61
91.1 11.2$100 24 92.8 9.0
There were no significant differences in average IQ proxy scores
for children with ASD across all 3 groups.
SUPPLEMENTAL TABLE 11 ASD Severity Scores (ADI-R domains) of
Participants With ASD Stratifiedby Categories of Cognitive
Outcome
N Mean ADI-R Domain Scores SD ANOVA, P
ADI-R social interaction .002Untestable or #70 92 21.8 6.171–99
99 19.1 6.0$100 33 18.5 5.2
ADI-R verbal communication .06Untestable or #70 55 16.0 4.371–99
94 14.7 4.5$100 32 13.8 4.4
ADI-R nonverbal communication .76Untestable or #70 37 11.9
2.571–99 5 12.0 2.8$100 1 10.0 —
ADI-R restricted repetitive behavior .91Untestable or #70 92 6.3
2.371–99 99 6.3 2.4$100 33 6.1 2.6
Subjects are categorized as either verbal or nonverbal on the
basis of question 30 of the ADI-R, and the communicationscore is
dichotomized accordingly. There was a significant association
between cognitive impairment and the degree ofsocial-communicative
impairment indexed by developmental history on the ADI-R, but this
was driven exclusively by thegroup of children in the deficient or
untestable range of IQ; the association did not extend to the other
subgroups or tovariation in restricted interests or repetitive
behavior. —, not applicable.
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SUPP
LEMEN
TALTABLE12
Hierarchical
Regression
Analyses
PredictingCognitive
andClinical
Outcom
esin
theFullSample
Model
IQProxy
Vineland-IISocial
Outcom
esVineland-IIAdaptiveComposite
Outcom
es
(1)
(2)
(3)
(4)
(1)
(2)
(3)
(4)
(1)
(2)
(3)
(4)
Intercept,b(SE)
58.9***(17.2)
78.0***(18.0)
58.6**
(20.6)
65.4**
(20.1)
56.8***(9.2)
81.5***(8.3)
87.3***(9.6)
88.4***(9.6)
58.3***(8.7)
83.6***(8.4)
91.1***(9.7)
92.9***(9.6)
Income,b(SE)
1.9(1.6)
1.6(1.7)
1.6(1.6)
0.8(1.6)
0.9(0.8)
0.6(0.8)
0.6(0.8)
0.5(0.8)
0.8(0.8)
0.3(0.8)
0.3(0.8)
0.1(0.8)
Sex,female,b(SE)
20.7(4.0)
22.6(4.4)
23.4(4.3)
24.0(4.2)
20.4(2.1)
2.1(1.9)
2.3(2.0)
2.2(2.0)
21.1(2.0)
0.7(2.0)
1.0(2.0)
0.8(1.9)
Gestation,37
wk,b(SE)
21.5(4.5)
20.7(4.6)
20.3(4.6)
0.1(4.4)
0.5(2.3)
1.5(2.0)
1.4(2.0)
1.5(2.0)
0.9(2.2)
1.1(2.0)
1.1(2.0)
1.2(2.0)
ASDseverity,b
(SE)
—20.8**(0.3)
20.7**(0.3)
20.6*
(0.3)
—21.2***
(0.1)
21.2***
(0.1)
21.2***
(0.1)
—21.0***
(0.1)
21.0***
(0.1)
21.0***
(0.1)
Ageof
diagnosis,b(SE)
——
4.5(2.5)
4.8*
(2.4)
——
21.4(1.1)
21.3(1.1)
——
21.8(1.1)
21.7(1.1)
Walking
onset$16
mo,b(SE)
——
—211.9***(3.5)
——
—22.2(1.6)
——
—23.7*
(1.6)
Observations
217
181
181
181
230
196
196
196
230
196
196
196
R20.0
0.1
0.1
0.1
0.0
0.3
0.3
0.3
0.0
0.3
0.3
0.3
Adjusted
R220.0
0.0
0.1
0.1
20.0
0.3
0.3
0.3
20.0
0.3
0.3
0.3
—,not
applicable.
*P,
.05.
**P,
.01.
***P,
.001.
ARTICLE
PEDIATRICS Volume 146, Number 3, September 2020 9
-
SUPP
LEMEN
TALTABLE13
Hierarchical
Regression
Analyses
PredictingCognitive
andClinical
Outcom
esWithin
theVerbal
Subsam
ple
Model
IQProxy
Vineland-IISocial
Outcom
esVineland-IIAdaptiveComposite
Outcom
es
(1)
(2)
(3)
(4)
(1)
(2)
(3)
(4)
(1)
(2)
(3)
(4)
Intercept,b(SE)
62.4***(16.2)
77.2***(16.9)
68.4***(19.7)
72.7***(19.3)
61.6***(9.2)
86.5***(8.4)
94.5***(9.7)
95.0***(9.8)
60.9***(8.5)
84.9***(8.2)
97.2***(9.4)
98.3***(9.3)
Income,b(SE)
1.72
(1.5)
1.6(1.6)
1.5(1.6)
1.0(1.5)
0.5(0.9)
0.2(0.8)
0.2(0.8)
0.2(0.8)
0.8(0.8)
0.3(0.8)
0.4(0.7)
0.2(0.7)
Sex,female,b(SE)
0.7(3.9)
23.9(4.2)
24.3(4.2)
24.8(4.1)
20.5(2.3)
0.9(2.1)
1.3(2.1)
1.2(2.1)
21.7(2.1)
20.6(2.0)
20.1(2.0)
20.2(2.0)
Gestation,37
wk,b(SE)
21.0(4.4)
20.8(4.5)
20.6(4.5)
20.2(4.4)
0.7(2.5)
1.4(2.2)
1.2(2.2)
1.2(2.2)
0.6(2.3)
0.2(2.2)
20.1(2.1)
20.0(2.1)
ASDseverity,b
(SE)
—20.6*
(0.3)
20.6*
(0.3)
20.5(0.3)
—21.1***
(0.1)
21.2***
(0.1)
21.1***
(0.1)
—21.0***
(0.1)
21.0***
(0.1)
22.0***
(0.1)
Ageof
diagnosis,b(SE)
——
2.1(2.4)
2.4(2.3)
——
21.9(1.2)
21.9(1.2)
——
22.9*
(1.1)
22.8*
(1.1)
Walking
onset$16
mo,b(SE)
——
—210.5**
(3.5)
——
—21.3(1.8)
——
—22.9(1.7)
Observations
194
163
163
163
192
163
163
163
192
163
163
163
R20.0
0.1
0.1
0.1
0.0
0.3
0.3
0.3
0.0
0.3
0.3
0.3
Adjusted
R220.0
0.0
0.0
0.1
20.0
0.3
0.3
0.3
20.0
0.3
0.3
0.3
—,not
applicable.
*P,
.05.
**P,
.01.
***P,
.001.
10
-
SUPP
LEMEN
TALTABLE14
Hierarchical
Regression
Analyses
PredictingCognitive
andClinical
Outcom
esWithin
theVerbal
Sub-SampleDiagnosed#
96Month
Model
IQProxy
Vineland-IISocial
Outcom
esVineland-IIAdaptiveComposite
Outcom
es
(1)
(2)
(3)
(4)
(1)
(2)
(3)
(4)
(1)
(2)
(3)
(4)
Intercept,b(SE)
63.9***(18.2)
73.5***(19.2)
46.6(24.3)
55.0*(23.3)
59.3***(10.6)
88.4***(9.4)
97.0***(11.9)
98.7***(12.0)
61.0***(9.4)
88.0***(8.9)
93.7***(11.4)
96.2***(11.3)
Income,b(SE)
1.6(1.7)
1.6(1.8)
1.3(1.8)
0.4(1.7)
0.7(1.0)
0.1(0.9)
0.2(0.9)
0.0(0.9)
0.7(0.9)
20.0(0.8)
0.1(0.8)
20.2(0.8)
Sexfemale,b(SE)
2.8(4.6)
22.6(5.0)
23.1(5.0)
23.6(4.7)
22.1(2.7)
20.8(2.5)
20.7(2.4)
20.8(2.4)
21.8(2.4)
20.2(2.3)
20.1(2.3)
20.3(2.3)
Gestation,37
wk,b(SE)
22.3(4.9)
22.1(5.0)
0.0(5.1)
0.1(4.9)
2.2(2.9)
3.5(2.4)
2.8(2.5)
2.8(2.5)
2.4(2.6)
2.4(2.3)
2.0(2.4)
2.0(2.4)
ASDseverity,b
(SE)
—20.4(0.3)
20.4(0.3)
20.3(0.3)
—21.2***
(0.1)
21.2***
(0.1)
21.2***
(0.1)
—21.0***
(0.1)
21.0***
(0.1)
21.0***
(0.1)
Ageof
diagnosis,b(SE)
——
7.1(4.0)
7.8*
(3.8)
——
22.3(2.0)
22.2(2.0)
——
21.5(1.9)
21.3(1.9)
Walking
onset$16
mo,b(SE)
——
—213.5***(3.9)
——
—22.7(2.0)
——
—24.1*
(1.9)
Observations
142
115
115
115
141
115
115
115
141
115
115
115
R20.0
0.0
0.1
0.2
0.0
0.4
0.4
0.4
0.0
0.3
0.3
0.4
Adjusted
R220.0
20.0
0.0
0.1
20.0
0.4
0.4
0.4
20.0
0.3
0.3
0.3
—,not
applicable.
*P,
.05.
**P,
.01.
***P,
.001.
ARTICLE
PEDIATRICS Volume 146, Number 3, September 2020 11
-
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SUPPLEMENTAL TABLE 15 Delay in age of First Walking in the
Interactive Autism Network National Volunteer Register.
n NHW n AA or Biracial AA x2 P
Mean Age at First Walk (SD) Proportion $16 m WithinRace, %
Mean Age at FirstWalk (SD)
Proportion $16 m WithinRace, %
Participants with ASD 2220 13.5 (6.7) 18.5 66 13.0 (2.6) 13.6
.31Participants with ASD and ID 703 15.9 (8.5) 34.7 61 14.1 (6.0)
24.6 .11Nondiagnosed siblings 5190 12.3 (5.7) 7.4 211 12.2 (9.5)
6.6 0.67
For sample details, see Frazier TW, Youngstrom EA, Hardan AY,
Georgiades S, Constantino JN, Eng C. Quantitative autism symptom
patterns recapitulate differential mechanisms of
genetictransmission in single and multiple incidence families. Mol
Autism. 2015;6:58
12
http://www.cdc.gov/nchs/slaits/spds.htmhttp://www.cdc.gov/nchs/slaits/spds.htm
