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Summary of Advances Cover 2014
Summary of Advance
In Autism Spectrum Disorder Research
Question 7: What Other Infrastructure and Surveillance Needs Must Be Met?

Prevalence of autism spectrum disorder among children aged 8 years—autism and developmental disabilities monitoring network, 11 sites, United States, 2010
Developmental Disabilities Monitoring Network Surveillance Year 2010 Principal Investigators; Centers for Disease Control and Prevention (CDC). MMWR Surveill Summ. 2014 Mar 28;63(2):1-21. [PMID: 24670961]

The Autism and Developmental Disabilities Monitoring Network (ADDM Network) estimates ASD prevalence in the United States (U.S.). It does this by systematically gathering and analyzing data, including ASD diagnoses, among children 8 years of age whose parents or guardians live in ADDM Network sites in the U.S. Such monitoring (surveillance) first involves collecting, organizing, and analyzing data from many sources, including health clinics, specialized programs for children with developmental disabilities, and records of children receiving special education services in public schools. Trained clinicians then determine and verify a child’s ASD status (case status) based on the data and criteria provided by the American Psychiatric Association in its Diagnosis and Statistical Manuals of Mental Disorders (DSM). The current study is a report by the ADDM Network’s principal investigators primarily presenting their ASD prevalence estimates for 2010 based on data on 5,338 children 8 years of age with verified ASD diagnoses and case status living in 11 ADDM Network sites that year. The main finding was an estimated overall prevalence rate of 14.7 per 1,000 or 1 in 68 children 8 years of age. Further, the estimated rate varied from site to site, from a low of 5.7 per 1,000 for the ADDM site in Alabama to a high of 21.9 per 1,000 for the ADDM site in New Jersey. Four of the 11 ADDM sites with limited or no access to children’s education records reported the lowest rates, possibly due to the lack of key data such as special education reports and intellectual ability ratings.

Other findings indicated that more boys (one in 42) than girls (one in 189) in the communities were identified with ASD. In addition, non-Hispanic white children were somewhat more likely to be identified with ASD than non-Hispanic black children, but much more likely to be identified with ASD than Hispanic children. The researchers were also interested in what data they were able to collect from seven sites on the levels of intellectual ability in ASD, finding that at these sites, 31% of the 8-year-old children with ASD had IQ scores in the range of intellectual disability (ID), 23% were in the borderline range, and 46% were in the average or above average range (IQ greater than 85). Further, they found that ASD prevalence was lower for ASD co-occurring with ID (4.7 per 1,000) than for ASD not co-occurring with ID (10.2 per 1,000). The researchers also calculated that about half the children studied were over 4 years old before they had their earliest known ASD diagnosis. In discussing their findings, the authors noted their estimates of ASD prevalence do not represent the entire country; their reports are “far more accurate” when they have access to school records; and they intend to further investigate the socioeconomic factors that may be influencing relatively late diagnoses and treatments, such as interventions more effectively applied early in a child’s life. The researchers also noted an observation they are not yet able to explain but certainly intend to explore further—they observed a shift in who is being identified with ASD. In most years until recently, the highest percentage of the ASD cases were found among children with low levels of intellectual ability, but now that trend is changing to the point where in 2010, 46% of the ASD cases were among children with average or above average intellectual ability. Last, the ADDM Network researchers made a series of recommendations, including but not limited to improving recognition and documentation of ASD symptoms in children “with an emphasis on those whose early symptoms may often be missed,” including girls as well as boys, children without ID, and children in all racial/ethnic groups, as well as lowering the age when children are first evaluated for ASD and subsequently enrolled in community support services.

The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism
Di Martino A, Yan CG, Li Q, Denio E, Castellanos FX, Alaerts K, Anderson JS, Assaf M, Bookheimer SY, Dapretto M, Deen B, Delmonte S, Dinstein I, Ertl-Wagner B, Fair DA, Gallagher L, Kennedy DP, Keown CL, Keysers C, Lainhart JE, Lord C, Luna B, Menon V, Minshew NJ, Monk CS, Mueller S, Müller RA, Nebel MB, Nigg JT, O’Hearn K, Pelphrey KA, Peltier SJ, Rudie JD, Sunaert S, Thioux M, Tyszka JM, Uddin LQ, Verhoeven JS, Wenderoth N, Wiggins JL, Mostofsky SH, Milham MP. Mol Psychiatry. 2014 Jun;19(6):659-67. [PMID:23774715]

ASD is a complex, lifelong condition with symptoms that vary substantially among individuals. Large ASD studies that yield important advancements are currently facilitated by allowing researchers worldwide open access to genetic data. However, no similar open sharing has occurred for brain imaging data, which is also important to understanding and treating ASD. In response, a multicenter research team created the Autism Brain Imaging Data Exchange (ABIDE) to compile and openly share brain imaging data for scientific research. Among other uses, brain imaging can help researchers understand how parts of the brain are interconnected and how this connectivity may be altered in mental disorders. Currently, ABIDE contains more than 1,100 brain scans of individuals 7–64 years of age; roughly half have ASD and half are unaffected controls. The imaging data were collected from individuals who were not performing any mental tasks (resting-state functional magnetic resonance imaging, or R-fMRI). In addition to the imaging data, the scientists have compiled basic information, including age, sex, IQ, and diagnosis, for each subject. To demonstrate the utility of ABIDE, the researchers examined the basic biological connections within the brains of subjects with ASD compared with those of a control group. They selected the data from scans of 360 male subjects with ASD; the control group included 403 males of the same age without ASD. Compared with the functioning of brains in the control group, the researchers found some individuals with ASD exhibited decreased nerve connectivity and others showed increased connectivity, although decreased connectivity was the predominant characteristic observed; these mixed observations are consistent with previous studies. The reduced connectivity was particularly noticeable in two areas of the brain associated with social processing, cognition, and affect (outward display of emotions, such as facial expression). The researchers’ analysis also revealed altered connectivity in brain circuits important for learning and sensory-motor function; this finding warrants future research. In addition, this study showed disrupted connectivity between the two hemispheres of the brain in people with ASD and hints that this altered connectivity may be more extensive than indicated in previous studies. Some of the differences in brain functionality observed in individuals with ASD appeared to remain the same across age groups, implying that brain maturity has no impact on some aspects of functional connectivity; however, in the future, more imaging of children under age 6 is needed to confirm this observation. In general, ongoing efforts to image the brains of children and adolescents with ASD will help researchers gain a better understanding of the developing brain. The ABIDE R-fMRI resource provides an unprecedented opportunity for scientists to replicate key analyses and make new discoveries. The researchers expect that by collecting and consolidating multiple international data sets, ABIDE can help increase the pace of scientific advances.

Potential impact of DSM-5 criteria on autism spectrum disorder prevalence estimates
Maenner MJ, Rice CE, Arneson CL, Cunniff C, Shieve A, Carpenter LA, Braun KVN, Kirby, RS, Bakian AV, Durkin MS. JAMA Psychiatry. 2014 Mar;71(3):292-300. [PMID: 24452504]

Determining how many children have ASD in any given time period depends on the criteria used to diagnose them. The primary reference guide for such diagnoses is the Diagnostic and Statistical Manual of Mental Disorders (DSM) published by the American Psychiatric Association (APA). In 2013, APA released a new version of the DSM (DSM-5), which revised diagnostic criteria for ASD. Unlike in the previous versions, the DSM-5 classifies ASD as a single disorder, without any subtypes such as autistic disorder and Asperger disorder; it recognizes only two domains of impairment—social communication and restricted repetitive patterns of behavior, interests, or activities; and specifies only seven distinct diagnostic criteria compared to the 12 diagnostic criteria previously needed. Some experts have suggested that the new criteria may reduce the number of children diagnosed with ASD. Also, the revised diagnostic criteria pose challenges for monitoring prevalence of ASD over time and differentiating changes in prevalence due to risk factors from changes associated with diagnostic criteria. The current study aimed to evaluate the potential effects of the new criteria on ASD prevalence by using DSM-5 criteria on ASD prevalence estimation data previously measured under the earlier DSM version. The study looked at prevalence estimates of ASD among 8-year-old children living in 11 Autism and Developmental Disabilities Monitoring (ADDM) Network sites within the United States in 2006 and three additional ADDM Network sites in 2008. After reviewing the data that served as the basis for these estimates, experts determined that 6,577 of the children had a verifiable ASD diagnosis (ASD case status) based on the previous version of the DSM. The researchers then sought to determine how many of these diagnosed children would also likely be diagnosed using DSM-5 criteria. The researchers determined that 81.2% (5,339) met criteria for ASD diagnosis based on the DSM-5. Of those children who did not, most fell short of an ASD diagnosis by only one criterion. The researchers then adjusted ASD prevalence estimates from the ADDM Network for 2006 and 2008 so that the estimates included only children who met the DSM-5 diagnostic criteria. The results were that prevalence estimates fell in both years, from nine to 7.4 per 1,000 for 2006 and from 11.3 to 10 per 1,000 for 2008. DSM-5 had a smaller effect on prevalence in 2008 than it did in 2006, which may suggest that the DSM-5 will not change the trend of increasing ASD prevalence over time. However, the authors caution other researchers to take care when interpreting trends in ASD prevalence that include data based on differing diagnostic criteria.

Question 7

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