Skip to content
photos related to autism and publications about it
Strategic Plan Cover

IACC Strategic Plan

For Autism Spectrum Disorder Research

2012 Update

Question 1: When Should I Be Concerned?

What Is New in This Research Area, and What Have We Learned in the Past Two Years?

The past two years have seen several developments in the diagnosis of ASD, including changes to the definition in the Diagnostic and Statistical Manual of Mental Disorders (DSM), the standard text used by U.S. mental health professionals for clinical diagnosis, and promising developments in diagnostic instruments and early screening and detection. With the release of new national and international prevalence data, there is ongoing concern surrounding the prevalence of ASD, emphasizing the continued need to improve both monitoring and diagnosis.


Several noteworthy new studies from the U.S., South Korea, and England update the recognized prevalence of autism.

In the U.S., the Autism and Developmental Disabilities Monitoring Network (ADDM), supported by the Centers for Disease Control and Prevention (CDC), released its most recent surveillance data, showing a prevalence of 1 in 88 children or 1.1%—an increase of 78% since the first report in 2002—with larger increases among racial/ethnic minority groups (CDC, 2012). The average age when children were initially diagnosed with ASD, however, remains essentially unchanged, at 4–5 years of age. A second U.S. study found a sharp increase in autism in children (based on parent report) over an 11-year period (Boyle et al., 2011). Importantly, such an increase was not found for other neurodevelopmental disorders other than attention deficit hyperactivity disorder.

Looking internationally, a South Korean study found an ASD prevalence of 1 in 38, or 2.6%, of children when a large population sample of school-aged children was evaluated (Kim et al., 2011). Notably, two-thirds of those identified had not been previously diagnosed with autism or received any services. A British study found a prevalence of 1 in 100 adults, most of whom were not previously diagnosed with ASD (Brugha et al., 2011). The large majority of adults with ASD identified in this study were living independently but at lower levels of socioeconomic success than peers who did not have ASD.

Taken together, these studies suggest that some, but not all, of the increased prevalence observed in children is a result of improved identification and that there may still be a sizable population of children and adults with undiagnosed autism.


The Diagnostic and Statistical Manual of Mental Disorders (DSM) definition of autism will be revised in 2013 when the new version, DSM-5, is released. The goal is to consolidate all current diagnoses under one category (autism spectrum disorder), while making its criteria more appropriate to the diagnosis of very young children, adults, and girls. While early studies raised concerns that the new criteria would exclude some people from diagnosis, recent findings suggest that this will not happen and that the other goals of the revision will be achieved. Specifically, similar rates of diagnosis were reported in a study based on well-characterized research samples (Huerta et al., 2012) and in preliminary results of the DSM-5 validation studies (Regier et al., 2012). However, there is still a need for prospective studies of the new criteria with larger sample sizes, and no data have yet been collected on adults.

In addition to evaluating the new criteria, recent analyses suggest that the method by which diagnostic information is collected is also critically important. Diagnoses that include information from both clinician observation and parent or caregiver report were found to be more accurate than diagnoses that rely on just one approach or the other (Huerta et al., 2012; McPartland, Reichow & Volkmar, 2012).

Furthermore, because diagnostic criteria are based on behavioral evaluation, clinical diagnoses are inconsistent among practitioners. Variations in diagnostic data from the infant sibling studies (Ozonoff et al., 2011), the CDC ADDM surveillance network sites (CDC, 2012), and the Simons Simplex Collection sites (Lord et al., 2012) suggest that clinical diagnoses still remain more variable than they should. This situation may ultimately be resolved by the development of laboratory tests for autism biomarkers, refined by observation and reporting. Although the criteria for diagnosis are behavioral, the hope is that medical evaluation will identify subtypes and decrease this variability.

Early Screening and Detection

Work on early screening tools has accelerated during the past two years, with two studies using questionnaire-based tools to screen for children at risk for ASD as early as 12 months old in community settings (Pierce et al., 2011a; Turner-Brown et al., 2012). However, researchers continue to have difficulty attaining sufficient sensitivity (the number of children correctly identified as having autism) without excessive rates of "false positives," which are instances when children are identified as being at risk for autism but do not go on to receive an ASD diagnosis. Specificity—correctly identifying the children that do not have ASD by accurately distinguishing ASD from other developmental disabilities or typically developing children—also remains a challenge.

Simplified ASD assessment tools for use across the lifespan are also in development (Allison, Auyeung & Baron-Cohen, 2012), but they have not yet met the need to appropriately identify adolescents and adults of all ages with ASD (Pilling et al., 2012). Additionally, new research continues to highlight disparities in identification of ASD by gender, race, and ethnicity (Valicenti-McDermott et al., 2012; Ko?ovská et al., 2012), while gaps remain in understanding the reasons for these disparities and evidence-based ways to close these gaps.

Early Diagnosis

Symptoms of autism may not be visible in the first year of life and currently are not measured reliably until the end of the second year. However, several groups are looking for performance-based measures to bridge that gap. For example, one study in toddlers as young as 14 months showed a strong correlation between a preference for fixating on geometric images and subsequent ASD diagnosis (Pierce et al., 2011b). Similarly, another research group found an association between atypical eye contact at 7–13 months and subsequent diagnosis of ASD (Bedford et al., 2012). A relationship was also identified between differences in vocalization at 6, 9, and 12 months and diagnosis of ASD at 24 months (Paul et al., 2011), and research suggested that a child's temperament in the first two years of life, including characteristics such as increased perceptual sensitivity or reduced interest in cuddling, may predict a future ASD diagnosis (Clifford et al., 2012).

Brain recording and imaging techniques are also showing promise in identifying early biomarkers for autism. Using brain imaging (diffusion tensor imaging, DTI), researchers have identified white matter fiber tract development differences in 6-month-old infants who would later be diagnosed with ASD (Wolff et al., 2012). This suggests that aberrant development of brain pathways may precede the manifestation of autistic behaviors in the first year of life.

Other research has explored electroencephalography (EEG) data as a potential biomarker and quantifier of risk in the first year (Bosl et al., 2012; Elsabbagh et al., 2012). It is thought that EEG signals may contain information about the architecture of the neural networks in the brain and that early detection of abnormalities in EEG signals could be used as a biomarker for ASD and other developmental cognitive disorders. Using this type of signal processing approach—specifically multiscale entropy—to determine if a neural "signature" of autism risk could be observed, researchers were able to classify high risk versus low risk with over 80% accuracy at nine months of age (Bosl et al., 2012). However, it is uncertain whether this is predictive of which infants develop ASD. Another research group found that atypical event related potential (ERP) responses to eye gaze in high-risk infants predicts which infants developed ASD (Elsabbagh et al., 2012). It is too early to tell if this work translates to the general infant population, but it may point the way to very early identification of ASD in children from known at-risk groups. Finally, other studies have made progress toward detecting biomarkers for autism through blood screening, by analyzing gene pathways (Skafidas et al., 2012), or patterns of gene expression (Glatt et al., 2012).

What Gaps Have Emerged in the Past Two Years?

Diagnosis and Prevalence

The age at which autism is diagnosed in most children has not changed, even though diagnosis is now possible significantly earlier. Better diagnostic tools and skills have been developed, but their existence has not yet translated to earlier detection in the general population.

Data systems—using the existing ADDM infrastructure or other data collection sites—to understand how the upcoming DSM-5 changes impact diagnosed prevalence and age at identification are recommended. Autism Speaks has funded a study to prospectively examine the impact of DSM-5 criteria on diagnosis at one ADDM site, but more studies are needed with both younger and older individuals.

Prevalence estimates from CDC's ADDM program are now available every two years based on large U.S. populations; however, these data are based on retrospective cohorts of children at eight years of age. Population-based data on younger children are needed, and new data collection is underway for children that are four years of age. However, the goal of obtaining rapidly available population-based estimates on large community samples continues to be a challenge.

The American Psychiatric Association (APA) has proposed a new disorder—Social Communication Disorder (SCD)—to describe people with communication disabilities that are not severe enough to warrant an ASD diagnosis. The community is very concerned that there are no therapies or services currently associated with SCD and that this diagnosis will be interpreted as mild ASD without the need for supports. Further research on SCD and its relationship to ASD is needed, and it will be important to follow this new diagnosis group with longitudinal studies.

The British study identifying the prevalence of ASD in the adult population in the United Kingdom (U.K.) (Brugha et al., 2011) suggests that a significant portion of the adult ASD population remains undiagnosed, despite the existence of screening tools and increasingly widespread public awareness of autism. Unrecognized adults with autism have emerged as an overlooked and underserved population. Some studies show that adults with autism continue to be socially disadvantaged and have significantly lower academic and career attainments as compared to adults in similar settings who do not have ASD (Brugha et al., 2011; Henninger & Taylor, 2012). Autism is a lifelong disability, yet research efforts to date have primarily focused on childhood and adolescent detection and intervention. More emphasis must be placed on individuals of all ages.

Bioethical Issues

As the field increasingly shifts toward pre-symptomatic diagnosis, a series of new, complex bioethical issues are emerging, since diagnosis and treatment could be indicated for an infant without behavioral symptoms. Many in the autism community have expressed concern that research into early detection will lead to prenatal tests for ASD and that the existence of such tests may have family planning implications. On the other hand, very early detection in infants may be one of the keys to providing the best outcomes for people who will grow up with ASD in the future. Prenatal testing could also have significant quality of life implications if it facilitates effective early intervention. Work leading to prenatal tests for ASD potential should be informed by a full discussion of the bioethical issues surrounding the use of these technologies, including those cited above.


Allison C, Auyeung B, Baron-Cohen S. Toward brief "Red Flags" for autism screening: The Short Autism Spectrum Quotient and the Short Quantitative Checklist for Autism in toddlers in 1,000 cases and 3,000 controls [corrected]. J Am Acad Child Adolesc Psychiatry. 2012 Feb;51(2):202–212.e7 [PMID: 22265366]

Bedford R, Elsabbagh M, Gliga T, Pickles A, Senju A, Charman T, Johnson MH; BASIS team. Precursors to social and communication difficulties in infants at-risk for autism: gaze following and attentional engagement. J Autism Dev Disord. 2012 Oct;42(10):2208-18. [PMID: 22278030]

Bosl W, Tierney A, Tager-Flusberg H, Nelson C. EEG complexity as a biomarker for autism spectrum disorder risk. BMC Med. 2011 Feb 22;9:18. [PMID: 21342500]

Boyle CA, Boulet S, Schieve LA, Cohen RA, Blumberg SJ, Yeargin-Allsopp M, Visser S, Kogan MD. Trends in the prevalence of developmental disabilities in US children, 1997-2008. Pediatrics. 2011 Jun;127(6):1034-42. [PMID: 21606152]

Brugha TS, McManus S, Bankart J, Scott F, Purdon S, Smith J, Bebbington P, Jenkins R, Meltzer H. Epidemiology of autism spectrum disorders in adults in the community in England. Arch Gen Psychiatry. 2011 May;68(5):459-65. [PMID: 21536975]

Centers for Disease Control and Prevention (CDC); Autism and Developmental Disabilities Monitoring Network - Surveillance Year 2008 Principal Investigators. Prevalence of autism spectrum disorders - Autism and Developmental Disabilities Monitoring Network, 14 Sites, United States, 2008. MMWR Surveill Summ. 2012 Mar 30; 61(3):1-19 [PMID: 22456193]

Clifford SM, Hudry K, Elsabbagh M, Charman T, Johnson MH; The BASIS Team. Temperament in the first 2 years of life in infants at high-risk for autism spectrum disorders. J Autism Dev Disord. 2012 Aug 24. [Epub ahead of print] [PMID: 22918859]

Elsabbagh M, Mercure E, Hudry K, Chandler S, Pasco G, Charman T, Pickles A, Baron-Cohen S, Bolton P, Johnson MH; BASIS Team. Infant neural sensitivity to dynamic eye gaze is associated with later emerging autism. Curr Biol. 2012 Feb 21;22(4):338-42. [PMID: 22285033]

Glatt SJ, Tsuang MT, Winn M, Chandler SD, Collins M, Lopez L, Weinfeld M, Carter C, Schork N, Pierce K, Courchesne E. Blood-based gene expression signatures of infants and toddlers with autism. J Am Acad Child Adolesc Psychiatry. 2012 Sep;51(9), 934-944. [PMID: 22917206]

Henninger NA, Taylor JL. Outcomes in adults with autism spectrum disorders: a historical perspective. Autism. 2012 Aug 21. [Epub ahead of print] [PMID: 22914775]

Huerta M, Bishop SL, Duncan A, Hus V, Lord C. Application of DSM-5 criteria for autism spectrum disorder to three samples of children with DSM-IV diagnoses of pervasive developmental disorders. Am J Psychiatry. 2012 Oct 1;169(10):1056-64. [PMID: 23032385]

Kim YS, Leventhal BL, Koh YJ, Fombonne E, Laska E, Lim EC, Cheon KA, Kim SJ, Kim YK, Lee H, Song DH, Grinker RR. Prevalence of autism spectrum disorders in a total population sample. Am J Psychiatry. 2011 Sep;168(9):904-12. [PMID: 21558103]

Ko?ovská E, Biskupstø R, Carina Gillberg I, Ellefsen A, Kampmann H, Stórá T, Billstedt E, Gillberg C. The rising prevalence of autism: a prospective longitudinal study in the Faroe Islands. J Autism Dev Disord. 2012 Sep;42(9):1959-66. [PMID: 22271195]

Lord C, Petkova E, Hus V, Gan W, Lu F, Martin DM, Ousley O, Guy L, Bernier R, Gerdts J, Algermissen M, Whitaker A, Sutcliffe JS, Warren Z, Klin A, Saulnier C, Hanson E, Hundley R, Piggot J, Fombonne E, Steiman M, Miles J, Kanne SM, Goine-Kochel RP, Peters SU, Cook EH, Guter S, Tjernagel J, Green-Snyder LA, Bishop S, Esler A, Gotham K, Luyster R, Miller F, Olson J, Richler J, Risi S. A multisite study of the clinical diagnosis of different autism spectrum disorders. Arch Gen Psychiatry. 2012 Mar;69(3):306-13. [PMID: 22065253]

McPartland JC, Reichow B, Volkmar FR. Sensitivity and specificity of proposed DSM-5 diagnostic criteria for autism spectrum disorder. J Am Acad Child Adolesc Psychiatry. 2012 Apr;51(4):368-83. [PMID: 22449643]

Ozonoff S, Young GS, Carter A, Messinger D, Yirmiya N, Zwaigenbaum L, Bryson S, Carver LJ, Constantino JN, Dobkins K, Hutman T, Iverson JM, Landa R, Rogers SJ, Sigman M, Stone WL. Recurrence risk for autism spectrum disorders: a Baby Siblings Research Consortium study. Pediatrics. 2011 Sep;128(3):e488-95. [PMID: 21844053]

Paul R, Fuerst Y, Ramsay G, Chawarska K, Klin A. Out of the mouths of babes: vocal production in infant siblings of children with ASD. J Child Psychol Psychiatry. 2011 May;52(5):588-98. [PMID: 21039489]

Pierce K, Carter C, Weinfeld M, Desmond J, Hazin R, Bjork R, Gallagher N. Detecting, studying, and treating autism early: the one-year well-baby check-up approach. J Pedatr. 2011 Sep;159(3):458-465.e1-6. [PMID: 21524759]

Pierce K, Conant D, Hazin R, Stoner R, Desmond J. Preference for geometric patterns early in life as a risk factor for autism. Arch Gen Psychiatry. 2011 Jan;68(1):101-9. [PMID: 20819977]

Pilling S, Baron-Cohen S, Megnin-Viggars O, Lee R, Taylor C; Guideline Development Group. Recognition, referral, diagnosis, and management of adults with autism: summary of NICE guidance. BMJ. 2012 Jun 27;344:e4082. [PMID: 22740567]

Regier DA, Narrow WE, Clarke DE, Kraemer HC, Kuramoto SJ, Kuhl EA, Kupfer DJ. DSM-5 field trials in the United States and Canada, part II: test-retest reliability of selected categorical diagnoses. Am J Psychiatry. Jan 2013;170:59-70. [PMID: 23111466]

Skafidas E, Testa R, Zantomio D, Chana G, Everall IP, Pantelis C. Predicting the diagnosis of autism spectrum disorder using gene pathway analysis. Mol Psychiatry. 2012 Sep 11. [Epub ahead of print] [PMID: 22965006]

Turner-Brown LM, Baranek GT, Reznick JS, Watson LR, Crais ER. The First Year Inventory: a longitudinal follow-up of 12-month-old to 3-year-old children. Autism. 2012 Aug 2. [Epub ahead of print] [PMID: 22781058]

Valicenti-McDermott M, Hottinger K, Seijo R, Shulman L. Age at diagnosis of autism spectrum disorders. J Pediatr. 2012 Sep;161(3):554-6. [PMID: 22683037]

Wolff JJ, Gu H, Gerig G, Elison JT, Styner M, Gouttard S, Botteron KN, Dager SR, Dawson G, Estes AM, Evans AC, Hazlett HC, Kostopoulos P, McKinstry RC, Paterson SJ, Schultz RT, Zwaigenbaum L, Piven J; IBIS Network. Differences in white matter fiber tract development present from 6 to 24 months in infants with autism. Am J Psychiatry. 2012 Jun;169(6):589-600. [PMID: 22362397]

Back to Top