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Figure 1.
Sex-Specific Patterns of Autism Spectrum Disorder (ASD) Diagnoses Among Sibling Pairs
Sex-Specific Patterns of Autism Spectrum Disorder (ASD) Diagnoses Among Sibling Pairs

The numbers at each vertex indicate the total number of families observed to have a corresponding pattern of diagnoses and births.

Figure 2.
Distribution of Autism Spectrum Disorder (ASD) Diagnoses
Distribution of Autism Spectrum Disorder (ASD) Diagnoses

Individuals may have had multiple ASD diagnoses.

Figure 3.
Distribution of Number of Study Participants During Observation
Distribution of Number of Study Participants During Observation

The spike at 12-month intervals reflects the period of annual commercial insurance plan renewals or enrollment changes.

Figure 4.
Sibling Rates of Recurrence of Autism Spectrum Disorder (ASD)
Sibling Rates of Recurrence of Autism Spectrum Disorder (ASD)

Probability of a diagnosis of ASD in a younger sibling with an older sibling diagnosed with ASD, stratified by sex and birth order. Recurrence was more likely in a male sibling than in a female sibling regardless of whether the older sibling with the associated risk was male or female. Older female siblings with an ASD diagnosis were associated with higher rates of recurrence (in male or female siblings) than were older male siblings. Whiskers indicate 95% CIs.

1.
Autism and Developmental Disabilities Monitoring Network Surveillance Year 2010 Principal Investigators. Prevalence of autism spectrum disorder among children aged 8 years—Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2010. https://www.cdc.gov/mmwr/preview/mmwrhtml/ss6302a1.htm?s_cid=ss6302a1_w. Published March 28, 2014. Accessed May 7, 2017.
2.
Ronald  A, Happé  F, Bolton  P,  et al.  Genetic heterogeneity between the three components of the autism spectrum: a twin study.  J Am Acad Child Adolesc Psychiatry. 2006;45(6):691-699.PubMedGoogle ScholarCrossref
3.
Sandin  S, Lichtenstein  P, Kuja-Halkola  R, Larsson  H, Hultman  CM, Reichenberg  A.  The familial risk of autism.  JAMA. 2014;311(17):1770-1777.PubMedGoogle ScholarCrossref
4.
Hallmayer  J, Cleveland  S, Torres  A,  et al.  Genetic heritability and shared environmental factors among twin pairs with autism.  Arch Gen Psychiatry. 2011;68(11):1095-1102.PubMedGoogle ScholarCrossref
5.
C Yuen  RK, Merico  D, Bookman  M,  et al.  Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder.  Nat Neurosci. 2017;20(4):602-611.PubMedGoogle ScholarCrossref
6.
Yuen  RK, Thiruvahindrapuram  B, Merico  D,  et al.  Whole-genome sequencing of quartet families with autism spectrum disorder.  Nat Med. 2015;21(2):185-191.PubMedGoogle ScholarCrossref
7.
Krumm  N, Turner  TN, Baker  C,  et al.  Excess of rare, inherited truncating mutations in autism.  Nat Genet. 2015;47(6):582-588.PubMedGoogle ScholarCrossref
8.
Iossifov  I, O’Roak  BJ, Sanders  SJ,  et al.  The contribution of de novo coding mutations to autism spectrum disorder.  Nature. 2014;515(7526):216-221.PubMedGoogle ScholarCrossref
9.
De Rubeis  S, He  X, Goldberg  AP,  et al; DDD Study; Homozygosity Mapping Collaborative for Autism; UK10K Consortium.  Synaptic, transcriptional and chromatin genes disrupted in autism.  Nature. 2014;515(7526):209-215.PubMedGoogle ScholarCrossref
10.
Schaefer  GB, Mendelsohn  NJ; Professional Practice and Guidelines Committee.  Clinical genetics evaluation in identifying the etiology of autism spectrum disorders: 2013 guideline revisions.  Genet Med. 2013;15(5):399-407.PubMedGoogle ScholarCrossref
11.
Atladóttir  HO, Henriksen  TB, Schendel  DE, Parner  ET.  Autism after infection, febrile episodes, and antibiotic use during pregnancy: an exploratory study.  Pediatrics. 2012;130(6):e1447-e1454.PubMedGoogle ScholarCrossref
12.
Harrington  RA, Lee  LC, Crum  RM, Zimmerman  AW, Hertz-Picciotto  I.  Prenatal SSRI use and offspring with autism spectrum disorder or developmental delay.  Pediatrics. 2014;133(5):e1241-e1248.PubMedGoogle ScholarCrossref
13.
Zerbo  O, Yoshida  C, Gunderson  EP, Dorward  K, Croen  LA.  Interpregnancy interval and risk of autism spectrum disorders.  Pediatrics. 2015;136(4):651-657.PubMedGoogle ScholarCrossref
14.
Ozonoff  S, Young  GS, Carter  A,  et al.  Recurrence risk for autism spectrum disorders: a Baby Siblings Research Consortium study.  Pediatrics. 2011;128(3):e488-e495.PubMedGoogle Scholar
15.
Grønborg  TK, Schendel  DE, Parner  ET.  Recurrence of autism spectrum disorders in full- and half-siblings and trends over time: a population-based cohort study.  JAMA Pediatr. 2013;167(10):947-953.PubMedGoogle ScholarCrossref
16.
Ruzich  E, Allison  C, Chakrabarti  B,  et al.  Sex and STEM occupation predict autism-spectrum quotient (AQ) scores in half a million people.  PLoS One. 2015;10(10):e0141229.PubMedGoogle ScholarCrossref
17.
Lai  MC, Lombardo  MV, Auyeung  B, Chakrabarti  B, Baron-Cohen  S.  Sex/gender differences and autism: setting the scene for future research.  J Am Acad Child Adolesc Psychiatry. 2015;54(1):11-24.PubMedGoogle ScholarCrossref
18.
Xie  F, Peltier  M, Getahun  D.  Is the risk of autism in younger siblings of affected children moderated by sex, race/ethnicity, or gestational age?  J Dev Behav Pediatr. 2016;37(8):603-609.PubMedGoogle ScholarCrossref
19.
Messinger  DS, Young  GS, Webb  SJ,  et al.  Early sex differences are not autism-specific: a Baby Siblings Research Consortium (BSRC) study.  Mol Autism. 2015;6:32.PubMedGoogle ScholarCrossref
20.
Werling  DM, Geschwind  DH.  Recurrence rates provide evidence for sex-differential, familial genetic liability for autism spectrum disorders in multiplex families and twins.  Mol Autism. 2015;6:27.PubMedGoogle ScholarCrossref
21.
Wood  CL, Warnell  F, Johnson  M,  et al.  Evidence for ASD recurrence rates and reproductive stoppage from large UK ASD research family databases.  Autism Res. 2015;8(1):73-81.PubMedGoogle ScholarCrossref
22.
R: a language and environment for statistical computing [computer program]. Vienna, Austria: R Foundation for Statistical Computing; 2015.
23.
Shattuck  PT, Durkin  M, Maenner  M,  et al.  Timing of identification among children with an autism spectrum disorder: findings from a population-based surveillance study.  J Am Acad Child Adolesc Psychiatry. 2009;48(5):474-483.PubMedGoogle ScholarCrossref
24.
Constantino  JN, Zhang  Y, Frazier  T, Abbacchi  AM, Law  P.  Sibling recurrence and the genetic epidemiology of autism.  Am J Psychiatry. 2010;167(11):1349-1356.PubMedGoogle ScholarCrossref
25.
Risch  N, Hoffmann  TJ, Anderson  M, Croen  LA, Grether  JK, Windham  GC.  Familial recurrence of autism spectrum disorder: evaluating genetic and environmental contributions.  Am J Psychiatry. 2014;171(11):1206-1213.PubMedGoogle ScholarCrossref
26.
Robinson  EB, Koenen  KC, McCormick  MC,  et al.  A multivariate twin study of autistic traits in 12-year-olds: testing the fractionable autism triad hypothesis.  Behav Genet. 2012;42(2):245-255.PubMedGoogle ScholarCrossref
27.
Jacquemont  S, Coe  BP, Hersch  M,  et al.  A higher mutational burden in females supports a “female protective model” in neurodevelopmental disorders.  Am J Hum Genet. 2014;94(3):415-425.PubMedGoogle ScholarCrossref
Original Investigation
November 2017

Association of Sex With Recurrence of Autism Spectrum Disorder Among Siblings

Author Affiliations
  • 1Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
  • 2Aetna Inc, Hartford, Connecticut
  • 3Independent Coauthor, Dingmans Ferry, Pennsylvania
  • 4Department of Pediatrics, Harvard Medical School, Boston, Massachusetts
  • 5Computational Health Informatics Program, Boston Children’s Hospital, Boston, Massachusetts
  • 6Department of Human Genetics, David Geffen School of Medicine, UCLA (University of California, Los Angeles)
  • 7Department of Psychiatry, David Geffen School of Medicine, UCLA (University of California, Los Angeles)
JAMA Pediatr. 2017;171(11):1107-1112. doi:10.1001/jamapediatrics.2017.2832
Key Points

Question  What are the sex-specific recurrence rates of autism spectrum disorder among siblings?

Findings  In this population analysis of 1 583 271 families with 2 children, a significantly increased risk of recurrence of autism spectrum disorder was found among males than among females.

Meaning  An older female sibling diagnosed with autism spectrum disorder is associated with greater risk of recurrence in the younger sibling compared with an older diagnosed male sibling, and male siblings are more likely to experience recurrence than female siblings regardless of the sex of the diagnosed sibling.

Abstract

Importance  Autism spectrum disorder (ASD) is known to be more prevalent among males than females in the general population. Although overall risk of recurrence of ASD among siblings has been estimated to be between 6.1% and 24.7%, information on sex-specific recurrence patterns is lacking.

Objective  To estimate high-confidence sex-specific recurrence rates of ASD among siblings.

Design, Setting, and Participants  This observational study used an administrative database to measure the incidence of ASD among children in 1 583 271 families (37 507 with at least 1 diagnosis of ASD) enrolled in commercial health care insurance plans at a large US managed health care company from January 1, 2008, through February 29, 2016. Families in the study had 2 children who were observed for at least 12 months between 4 and 18 years of age.

Main Outcomes and Measures  The primary measure of ASD recurrence was defined as the diagnosis of ASD in a younger sibling of an older sibling with an ASD diagnosis.

Results  Among the 3 166 542 children (1 547 266 females and 1 619 174 males; mean [SD] age, 11.2 [4.7] years) in the study, the prevalence of ASD was 1.96% (95% CI, 1.94%-1.98%) among males and 0.50% (95% CI, 0.49%-0.51%) among females. When a male was associated with risk in the family, ASD was diagnosed in 4.2% (95% CI, 3.8%-4.7%) of female siblings and 12.9% (95% CI, 12.2%-13.6%) of male siblings. When a female was associated with risk in the family, ASD was diagnosed in 7.6% (95% CI, 6.5%-8.9%) of female siblings and 16.7% (95% CI, 15.2%-18.4%) of male siblings.

Conclusions and Relevance  These findings are in agreement with the higher rates of ASD observed among males than among females in the general population. Our study provides more specific guidance for the screening and counseling of families and may help inform future investigations into the environmental and genetic factors that confer risk of ASD.

Introduction

Autism spectrum disorder (ASD) comprises a group of common neurodevelopmental disabilities of mostly unknown etiologic factors. Recent studies have suggested that the prevalence of ASD in the general US population may be greater than 1%,1 with approximately 4 times more males affected than females. Autism spectrum disorder has a strong genetic component, with heritability estimates ranging from 50% to 90%.2-4 Recent whole-genome and exome studies have implicated an increasing number of genes and pathways in ASD, highlighting its extreme locus heterogeneity.5-9 At present, clinical genetics evaluation is recommended after an ASD diagnosis and is estimated to result in an identified etiologic factor in 30% to 40% of patients.10 Because the cause of most cases of ASD cannot yet be explained using genetic approaches, several groups have sought to associate environmental exposures with ASD.11-13 However, the risk conferred by genomic variation in combination with environmental exposures remains unknown. Understanding the rate at which ASD diagnoses are shared among siblings in a family will aid in the interpretation of the genetic and environmental factors that increase the familial risk for ASD, leading to improved screening and counseling at the point of care.

The sibling recurrence rate, defined as the probability of a child having ASD with 1 or more siblings with ASD, has been estimated to be 6.1% to 18.7%.14,15 However, sex-specific recurrence rates in the general US population remain largely unknown; these data are particularly important for a sexually dimorphic disorder such as ASD, for which the strongest risk factor is being male.16,17 Recent studies have examined sex-specific ASD recurrence in siblings in small, targeted cohorts14,18-21 or birth cohorts,3 but the sex-specific recurrence among siblings in the general US population remains to be quantified. Thus, we performed a large, retrospective population analysis of the rate at which sibling pairs are commonly or singly diagnosed with ASD. The data for this analysis were derived from diagnostic billing codes at a commercial managed health care company in the United States, yielding the largest such study to date, to our knowledge.

Methods

Our study population was drawn from a deidentified administrative database at Aetna, a commercial managed health care company. At the time of analysis, the database contained International Classification of Diseases, Ninth Revision (ICD-9) diagnostic billing codes for more than 63 million individuals in the United States during a 98-month time frame from January 1, 2008, through February 29, 2016. No race, ethnicity, or socioeconomic data were present in the database. The Harvard Medical School Institutional Review Board waived the requirement for approval, as it deemed this analysis of the database to not be human subjects research.

Using subscriber-to-member relationship information contained in the enrollment data, we identified all families with exactly 2 children between the ages of 4 and 18 years and with at least 12 months of medical coverage. The children in these families constituted our study population. A small fraction of the designated siblings in these families may have been genetically unrelated or half-siblings. Because there is no way to identify and exclude these siblings from our analysis, we acknowledge that this caveat may lead to underestimation of the rates of recurrence. However, this limitation should be comparable for males and females.

In total, 3 166 542 children were evaluable from 1 583 271 families. Of these, 39 460 children from 37 507 families had received a diagnosis of ASD (ICD-9 code in the 299 group), indicating an overall population incidence of 1.25% (95% CI, 1.23%-1.26%). The male to female ratio of the overall study population was 1.05, and the male to female ratio of those with ASD was 4.10.

To examine the sex-specific association of an older sibling’s ASD diagnosis with diagnosis in the younger sibling (ie, recurrence), we performed a multiple logistic regression on the 21 074 two-child families in the study population whose oldest child had received a diagnosis of ASD. The younger sibling’s diagnosis status was modeled as a function of the child’s mean age during the observation period and the interaction between the birth-ordered sexes of the sibling pair (male and male, male and female, female and male, and female and female). Because the database contains only birth year and not full birth dates, we could not with certainty identify twins. Thus, any sibling pairs with the same birth year were excluded from this portion of the analysis. The child’s age was determined to not be significantly associated with ASD diagnosis in the younger sibling (see Results) and was omitted from the final model. Recurrence probabilities and their respective 95% CIs were calculated from the logistic regression. P values describing the significance of the difference between pairs of estimated recurrence rates and their associated SEs were calculated using a z-test on the log odds-scale values derived from the regression model. P < .05 (2-tailed) was considered significant. All calculations were performed using a combination of custom written queries in Microsoft SQL Server 2014 (Microsoft Corp) and R statistical software.22

Results
Overview

In a general population cohort of 3 166 542 children from 1 583 271 sibling pairs, the overall prevalence of ASD was 1.25% (95% CI, 1.23%-1.26%); the prevalence was 1.96% (95% CI, 1.94%-1.98%) among males and 0.50% (95% CI, 0.49%-0.51%) among females. The male to female ratio of the study population was 1.05 and of individuals with ASD was 4.1, consistent with previous findings.17Figure 1 summarizes sex-specific ASD diagnoses in the 4 types of sibling pairs studied.

Figure 2 shows the distribution of ASD diagnoses by age in the study cohort. The timing of diagnosis peaked at 5 to 6 years of age and decreased thereafter, consistent with previous reports.1,23 Each child may have received multiple diagnoses during the observation period, and diagnoses may have occurred before or after the required 12-month observation period between 4 and 18 years of age. Because the rate of diagnosis varied with age, we examined the effect of including adjustments for age when measuring the association of a sibling’s ASD diagnosis. Age was determined to not be a significant covariate (odds ratio, 1.01; 95% CI, 1.00-1.02; P = .13) in the logistic regression. Inclusion of age in the model yielded no statistically significant difference in the recurrence probabilities for any of the sibling pairs when computed at 4 years of age vs 18 years of age (the useful range of the model). Thus, age was omitted from the regression analysis.

Figure 3 shows the distribution of study participants (including older and younger siblings) for number of months of observation. The spikes at 12-month intervals can be attributed to the data being derived from an administrative database at a US managed health care company, and commercial health plans typically renew or change enrollment on an annual basis. The spike at 98 months represents the siblings who were enrolled for the entire 98-month observation period recorded in the data set. The quartiles of the distribution were 24, 44, and 72 months; 75% of the children had at least 24 months of observation, 50% had at least 44 months of observation, and 20% had at least 72 months of observation.

Approximately 15% of the claims that met the coding criteria for the study population did not record a specialty for the servicing health care provider. Among the remaining 85% of claims, the top 10 most frequently recorded specialties, accounting for greater than 90% of the claims with an ASD diagnosis, were mental health professional, physical rehabilitation professional, family practice, mental health provider, pediatrics, acute short-term hospital, dentistry, children’s hospital, neurology, and rehabilitation facility. The remaining 57 recorded specialties each accounted for 1% or less of all ASD diagnosis claims for the study population.

ASD Recurrence Rates

We estimated sex-specific recurrence rates of ASD by fitting a logistic regression on the 21 074 families with 2 children in the study population whose oldest child had received a diagnosis of ASD. Figure 4 shows the estimated recurrence probabilities with 95% CIs for each of the 4 possible ordered sibling pairings.

The probability of ASD recurrence in a younger male sibling with an older diagnosed female sibling was the highest of all 4 ordered sibling pairs (16.7%; 95% CI, 15.2%-18.4%). The next highest probability of recurrence was in a younger male with an older diagnosed male sibling (12.9%; 95% CI, 12.2%-13.6%). The probability of recurrence in a younger female sibling with an older diagnosed female sibling was 7.6% (95% CI, 6.5%-8.9%). The lowest probability of recurrence was observed for a younger female sibling with an older diagnosed male sibling (4.2%; 95% CI, 3.8%-4.7%). All pairwise comparisons of these sex-specific recurrence rates indicated a statistically significant difference (P < .001).

When a female or male older sibling had a diagnosis of ASD, a younger male sibling had a higher probability of an ASD diagnosis than a female participant. Furthermore, a female sibling with an ASD diagnosis appeared to be a stronger indicator of risk than a similarly diagnosed male sibling.

Discussion

Because these data were derived from insurance company–based ICD-9 codes for a large sample population, we were able to amass a larger data set than in most studies in ASD in which diagnosis was determined in a clinical research setting. Thus, this study of a population of 37 507 families with ASD is larger than than those in several studies published in the past decade and therefore enables a broad-based estimate of recurrence in the context of medical care. Despite the obvious methodological differences in ascertainment of ASD cases, the risk of recurrence seen in these data is generally similar to estimates from recently reported retrospective studies3,24 but lower than the highest estimates found in a smaller prospective infant sibling cohort.14

Consistent with some prior studies, we found a difference in the rate of recurrence in individuals of the same sex depending on the sex of their sibling. For families with 2 children, the rate of recurrence of ASD in a male child was approximately 1 in 7.7 if the other sibling with ASD was male. If the other sibling with ASD was female, the rate of recurrence was 1 in 6, an approximately 1.3-fold higher risk of recurrence. These rates are consistent with a model in which females require a higher number of genetic or environmental risk factors to manifest ASD than do males.

This finding does not fit into a model of X-linked mutations or germline mosaicism but may be consistent with multiple alleles or mutations of modest effect and a protective environment for unexplained reasons in the developing female brain. The rate of recurrence of ASD among female children is 7.6% if the affected sibling is female and 4.2% if male. Thus, the risk associated with a female sibling diagnosed with ASD is higher than that associated with a male sibling, a finding that is in line with several genetic models. In the multivariate model of Risch et al,25 a female sibling with a previous diagnosis of ASD was found to be associated with an increased rate of recurrence in a male sibling, consistent with our observations. This finding is also consistent with those of Robinson et al26 of British and Swedish twin cohorts in which siblings of female probands with ASD had significantly more autistic traits than did siblings of male probands with ASD. Whether the female protective effect is inherent in differences in structure of the brain and hormonal milieu or in unidentified specific genetic variants remains a matter of continued investigation. Regardless of the mechanism, recent studies support the hypothesis that the female protective effect results in female probands having a higher mutational burden, as determined by exome sequencing in neurodevelopmental disorders.27 Therefore, males with a similar or lesser genetic burden acquired through the family shared with the female proband may manifest the disorder but the converse may not be true.

Although some prior studies have not described a sex association in ASD, our data set is the largest to date to report sex-specific recurrence rates among siblings and should be factored into genetic counseling for families in the absence of a known explanatory cause of ASD in the family. Sandin et al3 identified a pattern of sex-specific adjusted relative risk of recurrence for ASD that is consistent with our analysis. Although that study found the difference in relative risk of recurrence to not be statistically significant, the sex-specific rates of recurrence reported in our study are significantly different. The sample size of our study enabled a high-confidence analysis of sex-specific ASD rates of recurrence in the general population, which prior studies were underpowered to detect.3 These findings could be incorporated into screening and counseling for families with no known ASD etiologic factors.

Limitations

This study relied on data from an insurance claims database. Although all data were based on patients’ medical information, the precise basis or severity of the ASD could not be determined from the provided data. Additional, precise genetic relationships could not be determined; some study members listed as siblings may have been half-siblings or genetically unrelated.

Conclusions

Autism spectrum disorder is a neurodevelopmental disorder that is known to affect males at a higher rate than females in the general population and to cluster in families. This study estimated the frequency with which the disease recurred in female and male sibling pairs and the rate of recurrence in sex-heterogeneous families. Our findings support the hypothesis that the disease clusters in families owing to shared genetic or environmental factors. Our findings also support previous observations that ASD affects males more than females even within families. For families that have a child who has been diagnosed with ASD, the findings of this research provide better likelihood estimates of disease recurrence among subsequent offspring and may help guide counseling and support services.

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Article Information

Corresponding Author: Isaac Kohane, MD, PhD, Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck St, Boston, MA 02115 (isaac_kohane@harvard.edu).

Accepted for Publication: June 27, 2017.

Published Online: September 25, 2017. doi:10.1001/jamapediatrics.2017.2832

Author Contributions: Dr Palmer had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Palmer, Beam, Spettell, Mandl, Fox.

Acquisition, analysis, or interpretation of data: Palmer, Beam, Agniel, Eran, Manrai, Spettell, Steinberg, Nelson, Kohane.

Drafting of the manuscript: Palmer, Eran, Fox.

Critical revision of the manuscript for important intellectual content: Palmer, Beam, Agniel, Manrai, Spettell, Steinberg, Mandl, Nelson, Kohane.

Statistical analysis: Palmer, Beam, Agniel, Eran, Manrai, Fox.

Obtained funding: Kohane.

Administrative, technical, or material support: Spettell, Kohane.

Study supervision: Mandl, Kohane.

Conflict of Interest Disclosures: None reported.

References
1.
Autism and Developmental Disabilities Monitoring Network Surveillance Year 2010 Principal Investigators. Prevalence of autism spectrum disorder among children aged 8 years—Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2010. https://www.cdc.gov/mmwr/preview/mmwrhtml/ss6302a1.htm?s_cid=ss6302a1_w. Published March 28, 2014. Accessed May 7, 2017.
2.
Ronald  A, Happé  F, Bolton  P,  et al.  Genetic heterogeneity between the three components of the autism spectrum: a twin study.  J Am Acad Child Adolesc Psychiatry. 2006;45(6):691-699.PubMedGoogle ScholarCrossref
3.
Sandin  S, Lichtenstein  P, Kuja-Halkola  R, Larsson  H, Hultman  CM, Reichenberg  A.  The familial risk of autism.  JAMA. 2014;311(17):1770-1777.PubMedGoogle ScholarCrossref
4.
Hallmayer  J, Cleveland  S, Torres  A,  et al.  Genetic heritability and shared environmental factors among twin pairs with autism.  Arch Gen Psychiatry. 2011;68(11):1095-1102.PubMedGoogle ScholarCrossref
5.
C Yuen  RK, Merico  D, Bookman  M,  et al.  Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder.  Nat Neurosci. 2017;20(4):602-611.PubMedGoogle ScholarCrossref
6.
Yuen  RK, Thiruvahindrapuram  B, Merico  D,  et al.  Whole-genome sequencing of quartet families with autism spectrum disorder.  Nat Med. 2015;21(2):185-191.PubMedGoogle ScholarCrossref
7.
Krumm  N, Turner  TN, Baker  C,  et al.  Excess of rare, inherited truncating mutations in autism.  Nat Genet. 2015;47(6):582-588.PubMedGoogle ScholarCrossref
8.
Iossifov  I, O’Roak  BJ, Sanders  SJ,  et al.  The contribution of de novo coding mutations to autism spectrum disorder.  Nature. 2014;515(7526):216-221.PubMedGoogle ScholarCrossref
9.
De Rubeis  S, He  X, Goldberg  AP,  et al; DDD Study; Homozygosity Mapping Collaborative for Autism; UK10K Consortium.  Synaptic, transcriptional and chromatin genes disrupted in autism.  Nature. 2014;515(7526):209-215.PubMedGoogle ScholarCrossref
10.
Schaefer  GB, Mendelsohn  NJ; Professional Practice and Guidelines Committee.  Clinical genetics evaluation in identifying the etiology of autism spectrum disorders: 2013 guideline revisions.  Genet Med. 2013;15(5):399-407.PubMedGoogle ScholarCrossref
11.
Atladóttir  HO, Henriksen  TB, Schendel  DE, Parner  ET.  Autism after infection, febrile episodes, and antibiotic use during pregnancy: an exploratory study.  Pediatrics. 2012;130(6):e1447-e1454.PubMedGoogle ScholarCrossref
12.
Harrington  RA, Lee  LC, Crum  RM, Zimmerman  AW, Hertz-Picciotto  I.  Prenatal SSRI use and offspring with autism spectrum disorder or developmental delay.  Pediatrics. 2014;133(5):e1241-e1248.PubMedGoogle ScholarCrossref
13.
Zerbo  O, Yoshida  C, Gunderson  EP, Dorward  K, Croen  LA.  Interpregnancy interval and risk of autism spectrum disorders.  Pediatrics. 2015;136(4):651-657.PubMedGoogle ScholarCrossref
14.
Ozonoff  S, Young  GS, Carter  A,  et al.  Recurrence risk for autism spectrum disorders: a Baby Siblings Research Consortium study.  Pediatrics. 2011;128(3):e488-e495.PubMedGoogle Scholar
15.
Grønborg  TK, Schendel  DE, Parner  ET.  Recurrence of autism spectrum disorders in full- and half-siblings and trends over time: a population-based cohort study.  JAMA Pediatr. 2013;167(10):947-953.PubMedGoogle ScholarCrossref
16.
Ruzich  E, Allison  C, Chakrabarti  B,  et al.  Sex and STEM occupation predict autism-spectrum quotient (AQ) scores in half a million people.  PLoS One. 2015;10(10):e0141229.PubMedGoogle ScholarCrossref
17.
Lai  MC, Lombardo  MV, Auyeung  B, Chakrabarti  B, Baron-Cohen  S.  Sex/gender differences and autism: setting the scene for future research.  J Am Acad Child Adolesc Psychiatry. 2015;54(1):11-24.PubMedGoogle ScholarCrossref
18.
Xie  F, Peltier  M, Getahun  D.  Is the risk of autism in younger siblings of affected children moderated by sex, race/ethnicity, or gestational age?  J Dev Behav Pediatr. 2016;37(8):603-609.PubMedGoogle ScholarCrossref
19.
Messinger  DS, Young  GS, Webb  SJ,  et al.  Early sex differences are not autism-specific: a Baby Siblings Research Consortium (BSRC) study.  Mol Autism. 2015;6:32.PubMedGoogle ScholarCrossref
20.
Werling  DM, Geschwind  DH.  Recurrence rates provide evidence for sex-differential, familial genetic liability for autism spectrum disorders in multiplex families and twins.  Mol Autism. 2015;6:27.PubMedGoogle ScholarCrossref
21.
Wood  CL, Warnell  F, Johnson  M,  et al.  Evidence for ASD recurrence rates and reproductive stoppage from large UK ASD research family databases.  Autism Res. 2015;8(1):73-81.PubMedGoogle ScholarCrossref
22.
R: a language and environment for statistical computing [computer program]. Vienna, Austria: R Foundation for Statistical Computing; 2015.
23.
Shattuck  PT, Durkin  M, Maenner  M,  et al.  Timing of identification among children with an autism spectrum disorder: findings from a population-based surveillance study.  J Am Acad Child Adolesc Psychiatry. 2009;48(5):474-483.PubMedGoogle ScholarCrossref
24.
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