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Elevated Polygenic Burden for Autism Spectrum Disorder Is Associated With the Broad Autism Phenotype in Mothers of Individuals With Autism Spectrum Disorder

  • Author Footnotes
    1 KN and JMS contributed equally to this work as joint first authors.
    Kritika Nayar
    Footnotes
    1 KN and JMS contributed equally to this work as joint first authors.
    Affiliations
    Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, Illinois
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  • Author Footnotes
    1 KN and JMS contributed equally to this work as joint first authors.
    Julia M. Sealock
    Footnotes
    1 KN and JMS contributed equally to this work as joint first authors.
    Affiliations
    Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
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  • Nell Maltman
    Affiliations
    Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, Illinois
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  • Lauren Bush
    Affiliations
    Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, Illinois
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  • Edwin H. Cook
    Affiliations
    Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois
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  • Author Footnotes
    2 LKD and ML contributed equally to this work as joint senior authors.
    Lea K. Davis
    Footnotes
    2 LKD and ML contributed equally to this work as joint senior authors.
    Affiliations
    Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
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  • Author Footnotes
    2 LKD and ML contributed equally to this work as joint senior authors.
    Molly Losh
    Correspondence
    Address correspondence to Molly Losh, Ph.D.
    Footnotes
    2 LKD and ML contributed equally to this work as joint senior authors.
    Affiliations
    Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, Illinois
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  • Author Footnotes
    1 KN and JMS contributed equally to this work as joint first authors.
    2 LKD and ML contributed equally to this work as joint senior authors.
Open AccessPublished:September 11, 2020DOI:https://doi.org/10.1016/j.biopsych.2020.08.029

      Abstract

      Background

      Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental disorder that encompasses a complex and heterogeneous set of traits. Subclinical traits that mirror the core features of ASD, referred to as the broad autism phenotype (BAP), have been documented repeatedly in unaffected relatives and are believed to reflect underlying genetic liability to ASD. The BAP may help inform the etiology of ASD by allowing the stratification of families into more phenotypically and etiologically homogeneous subgroups. This study explores polygenic scores related to the BAP.

      Methods

      Phenotypic and genotypic information were obtained from 2614 trios from the Simons Simplex Collection. Polygenic scores of ASD (ASD-PGSs) were generated across the sample to determine the shared genetic overlap between the BAP and ASD. Maternal and paternal ASD-PGSs were explored in relation to BAP traits and their child's ASD symptomatology.

      Results

      Maternal pragmatic language was related to child’s social communicative atypicalities. In fathers, rigid personality was related to increased repetitive behaviors in children. Maternal (but not paternal) ASD-PGSs were related to the pragmatic language and rigid BAP domains.

      Conclusions

      Associations emerged between parent and child phenotypes, with more associations emerging in mothers than in fathers. ASD-PGS associations emerged with BAP in mothers only, highlighting the potential for a female protective factor, and implicating the polygenic etiology of ASD-related phenotypes in the BAP.

      Keywords

      Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is estimated to occur in 1 in 59 children below 8 years of age in the United States (
      • Baio J.
      • Wiggins L.
      • Christensen D.L.
      • Maenner M.J.
      • Daniels J.
      • Warren Z.
      • et al.
      Prevalence of autism spectrum disorder among children aged 8 years—Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2014.
      ). In their pioneering twin study, Folstein and Rutter (
      • Folstein S.
      • Rutter M.
      Genetic influences and infantile autism.
      ) evaluated monozygotic (i.e., identical) and dizygotic (i.e., fraternal) twins for infantile ASD, finding higher concordance for infantile ASD (i.e., both twins had the same diagnosis) in monozygotic twins (36%) than in dizygotic twins (0%) and suggesting that there is a genetic, heritable basis for ASD. A follow-up study (
      • Bailey A.
      • Le Couteur A.
      • Gottesman I.
      • Bolton P.
      • Simonoff E.
      • Yuzda E.
      • Rutter M.
      Autism as a strongly genetic disorder: Evidence from a British twin study.
      ) using an expanded sample revealed that 92% of monozygotic twin pairs were concordant for a broader spectrum of ASD-related social and cognitive atypicalities (compared with only 10% concordance in dizygotic pairs), suggesting that ASD and ASD traits are highly heritable. Indeed, a recent meta-analysis of ASD twin studies (
      • Tick B.
      • Bolton P.
      • Happé F.
      • Rutter M.
      • Rijsdijk F.
      Heritability of autism spectrum disorders: A meta-analysis of twin studies.
      ) presented almost perfect concordance of ASD between monozygotic twins (98%), adding to the evidence of the strong heritability of ASD. A substantial body of work has since identified a subclinical set of traits, including social reticence, rigid personality, and pragmatic (i.e., social) language differences, collectively known as the broad autism phenotype (BAP), that mirror the core symptoms of ASD in unaffected relatives.
      Component features of the BAP may constitute candidate endophenotypes, or heritable traits linked to a disorder that are observed in affected individuals and their unaffected relatives. Though many endophenotypes are likely polygenic themselves, they may be useful for study in complex, heterogeneous conditions such as ASD, by helping to identify etiologically homogeneous subgroups based on shared endophenotypes (
      • Wong E.H.F.
      • Fox J.C.
      • Ng M.Y.M.
      • Lee C.-M.
      Toward personalized medicine in the neuropsychiatric field.
      ,
      • Beauchaine T.P.
      • Constantino J.N.
      Redefining the endophenotype concept to accommodate transdiagnostic vulnerabilities and etiological complexity.
      ,
      • Woodbury-Smith M.
      • Nicolson R.
      • Zarrei M.
      • Yuen R.K.C.
      • Walker S.
      • Howe J.
      • et al.
      Variable phenotype expression in a family segregating microdeletions of the NRXN1 and MBD5 autism spectrum disorder susceptibility genes.
      ). Evidence that features of the BAP constitute candidate endophenotypes comes from studies showing significantly higher rates of BAP features in unaffected relatives of individuals with ASD than in the general population (
      • Bishop D.V.M.
      • Maybery M.
      • Wong D.
      • Maley A.
      • Hill W.
      • Hallmayer J.
      Are phonological processing deficits part of the broad autism phenotype?.
      ,
      • Frazier T.W.
      • Youngstrom E.A.
      • Hardan A.Y.
      • Georgiades S.
      • Constantino J.N.
      • Eng C.
      Quantitative autism symptom patterns recapitulate differential mechanisms of genetic transmission in single and multiple incidence families.
      ,
      • Hurley R.S.E.
      • Losh M.
      • Parlier M.
      • Reznick J.S.
      • Piven J.
      The Broad Autism Phenotype Questionnaire.
      ,
      • Sasson N.J.
      • Lam K.S.L.
      • Parlier M.
      • Daniels J.L.
      • Piven J.
      Autism and the broad autism phenotype: Familial patterns and intergenerational transmission.
      ), and even higher rates in multiplex families (
      • Losh M.
      • Esserman D.
      • Piven J.
      Rapid automatized naming as an index of genetic liability to autism.
      ,
      • Gerdts J.A.
      • Bernier R.
      • Dawson G.
      • Estes A.
      The broader autism phenotype in simplex and multiplex families.
      ), suggesting that BAP features are sensitive indices of genetic loading. ASD symptomatology in children was shown to correlate with BAP features in parents (
      • Stern Y.S.
      • Maltman N.
      • Roberts M.Y.
      The influence of maternal pragmatics on the language skills of children with autism.
      ,
      • Klusek J.
      • Martin G.E.
      • Losh M.
      Consistency between research and clinical diagnoses of autism among boys and girls with fragile X syndrome.
      ,
      • Levin-Decanini T.
      • Maltman N.
      • Francis S.M.
      • Guter S.
      • Anderson G.M.
      • Cook E.H.
      • Jacob S.
      Parental broader autism subphenotypes in ASD affected families: Relationship to gender, child’s symptoms, SSRI treatment, and platelet serotonin.
      ), even when BAP traits were noted before a parent went on to have a child with ASD (
      • Losh M.
      • Martin G.E.
      • Lee M.
      • Klusek J.
      • Sideris J.
      • Barron S.
      • Wassink T.
      Developmental markers of genetic liability to autism in parents: A longitudinal, multigenerational study.
      ). Further, BAP features have been shown to cosegregate with distinct patterns of neurocognitive performance in clinically unaffected relatives (
      • Losh M.
      • Esserman D.
      • Piven J.
      Rapid automatized naming as an index of genetic liability to autism.
      ,
      • Losh M.
      • Adolphs R.
      • Piven J.
      The broad autism phenotype.
      ,
      • Nayar K.
      • Gordon P.C.
      • Martin G.E.
      • Hogan A.L.
      • La Valle C.
      • McKinney W.
      • et al.
      Links between looking and speaking in autism and first-degree relatives: Insights into the expression of genetic liability to autism.
      ,
      • Hogan-Brown A.L.
      • Hoedemaker R.S.
      • Gordon P.C.
      • Losh M.
      Eye-voice span during rapid automatized naming: Evidence of reduced automaticity in individuals with autism spectrum disorder and their siblings.
      ,
      • Losh M.
      • Adolphs R.
      • Poe M.D.
      • Couture S.
      • Penn D.
      • Baranek G.T.
      • Piven J.
      Neuropsychological profile of autism and the broad autism phenotype.
      ,
      • Losh M.
      • Childress D.
      • Lam K.
      • Piven J.
      Defining key features of the broad autism phenotype: A comparison across parents of multiple- and single-incidence autism families.
      ), suggesting that there are links with underlying neural substrates affected by ASD genetic risk. Finally, unlike ASD, which by definition requires the presence of impairments in social interaction and communication and the presence of restricted and repetitive interests and behaviors, traits of the BAP have been observed to segregate independently in unaffected relatives (
      • Losh M.
      • Childress D.
      • Lam K.
      • Piven J.
      Defining key features of the broad autism phenotype: A comparison across parents of multiple- and single-incidence autism families.
      ,
      • Constantino J.N.
      • Todd R.D.
      Autistic traits in the general population: A twin study.
      ,
      • Piven J.
      • Wzorek M.
      • Landa R.
      • Lainhart J.
      • Bolton P.
      • Chase G.
      • Folstein S.
      Personality characteristics of the parents of autistic individuals.
      ), potentially reflecting distinct genetic contributions to the component features of ASD (
      • Happé F.
      • Ronald A.
      • Plomin R.
      Time to give up on a single explanation for autism.
      ,
      • Gottesman II,
      • Gould T.D.
      The endophenotype concept in psychiatry: Etymology and strategic intentions.
      ,
      • Davidson J.
      • Goin-Kochel R.P.
      • Green-Snyder L.A.
      Expression of the broad autism phenotype in simplex autism families from the Simons Simplex Collection.
      ). Taken together, evidence suggests that the BAP may therefore help to leverage studies of ASD etiology by providing a distilled phenotypic expression of genetic liability to ASD with potentially more straightforward ties to underlying etiology than the complex and heterogeneous ASD phenotype (
      • Woodbury-Smith M.
      • Paterson A.D.
      • O’Connor I.
      • Zarrei M.
      • Yuen R.K.C.
      • Howe J.L.
      • et al.
      A genome-wide linkage study of autism spectrum disorder and the broad autism phenotype in extended pedigrees.
      ). Characterizing endophenotypes among clinically unaffected relatives may also provide insights into familial patterns of transmission, permitting focus on transmitting relatives for more refined analysis of ASD-risk loci (
      • Sasson N.J.
      • Lam K.S.L.
      • Parlier M.
      • Daniels J.L.
      • Piven J.
      Autism and the broad autism phenotype: Familial patterns and intergenerational transmission.
      ,
      • Woodbury-Smith M.
      • Paterson A.D.
      • O’Connor I.
      • Zarrei M.
      • Yuen R.K.C.
      • Howe J.L.
      • et al.
      A genome-wide linkage study of autism spectrum disorder and the broad autism phenotype in extended pedigrees.
      ).
      Family studies of ASD show an aggregation of cases within families, suggesting that there is an inherited genetic component to the disorder (
      • De La Torre-Ubieta L.
      • Won H.
      • Stein J.L.
      • Geschwind D.H.
      Advancing the understanding of autism disease mechanisms through genetics.
      ,
      • Sandin S.
      • Lichtenstein P.
      • Kuja-Halkola R.
      • Larsson H.
      • Hultman C.M.
      • Reichenberg A.
      The familial risk of autism.
      ). Family and population genetic studies revealed a complex architecture with genetic liability originating from rare, structural, de novo, and common variation (
      • De La Torre-Ubieta L.
      • Won H.
      • Stein J.L.
      • Geschwind D.H.
      Advancing the understanding of autism disease mechanisms through genetics.
      ,
      • Vorstman J.A.S.
      • Parr J.R.
      • Moreno-De-Luca D.
      • Anney R.J.L.
      • Nurnberger J.I.
      • Hallmayer J.F.
      Autism genetics: Opportunities and challenges for clinical translation.
      ). However, rare, structural, and de novo variants collectively explain less than 5% of the total liability of ASD (
      • Gaugler T.
      • Klei L.
      • Sanders S.J.
      • Bodea C.A.
      • Goldberg A.P.
      • Lee A.B.
      • et al.
      Most genetic risk for autism resides with common variation.
      ,
      • Robinson E.B.
      • St Pourcain B.
      • Anttila V.
      • Kosmicki J.A.
      • Bulik-Sullivan B.
      • Grove J.
      • et al.
      Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population.
      ). In contrast, common variants are estimated to explain most of the genetic contribution to ASD (
      • Gaugler T.
      • Klei L.
      • Sanders S.J.
      • Bodea C.A.
      • Goldberg A.P.
      • Lee A.B.
      • et al.
      Most genetic risk for autism resides with common variation.
      ,
      • Anney R.
      • Klei L.
      • Pinto D.
      • Almeida J.
      • Bacchelli E.
      • Baird G.
      • et al.
      Individual common variants exert weak effects on the risk for autism spectrum disorders.
      ). Genome-wide association studies estimate that heritability due to common variation is approximately 12% for ASD (
      • Grove J.
      • Ripke S.
      • Als T.D.
      • Mattheisen M.
      • Walters R.K.
      • Won H.
      • et al.
      Identification of common genetic risk variants for autism spectrum disorder.
      ). One method to assess associations with ASD genetics is by harnessing common variants through polygenic scoring.
      Polygenic scoring is a method of calculating an individual’s underlying genetic liability to a complex trait using weights derived from large-scale genome-wide association studies. A major benefit of polygenic scores (PGSs) is that a score can be calculated for any genotyped individual, regardless of diagnostic status. PGSs of ASD have been previously shown to imperfectly, but significantly, associate with ASD case-control status and ASD-related features (
      • Anney R.
      • Klei L.
      • Pinto D.
      • Almeida J.
      • Bacchelli E.
      • Baird G.
      • et al.
      Individual common variants exert weak effects on the risk for autism spectrum disorders.
      ), suggesting that PGS is a reliable measurement of inherited ASD genetic factors. Additionally, the range of derived PGSs allows for continuous measurement of use in correlational analyses with other complex phenotypes. For example, ASD-PGSs associate with general cognitive ability, logical memory, and verbal intelligence in the general population (
      • Clarke T.K.
      • Lupton M.K.
      • Fernandez-Pujals A.M.
      • Starr J.
      • Davies G.
      • Cox S.
      • et al.
      Common polygenic risk for autism spectrum disorder (ASD) is associated with cognitive ability in the general population.
      ). Given the polygenic and heterogeneous nature of ASD, polygenic analyses in family members of individuals with ASD can also help to further elucidate the relationship between polygenic scores and symptom domains (
      • Woodbury-Smith M.
      • Paterson A.D.
      • O’Connor I.
      • Zarrei M.
      • Yuen R.K.C.
      • Howe J.L.
      • et al.
      A genome-wide linkage study of autism spectrum disorder and the broad autism phenotype in extended pedigrees.
      ).
      This study examined PGSs within families of individuals with ASD, with the hypothesis that ASD-PGSs underlie both aggregate ASD expression and subclinical BAP features. Specifically, the study aimed to examine 1) whether ASD-PGS is correlated with BAP features in parents of individuals with ASD; 2) whether ASD-PGS is correlated with the same symptom domain features in individuals with ASD; and 3) whether these correlations also reflect significant parent–child phenotypic associations. Importantly, ours is not an analysis of transmission that seeks to make causal claims, but instead is one of correlation that seeks to understand the relationship between symptom domains and genetic scores within families.

      Methods and Materials

      Participants

      Participants were drawn from the Simons Simplex Collection (SSC), and the sample included a maximum of 2618 mothers, 2614 fathers, and 2621 children with ASD. Required inclusion criteria for SSC were that probands were between 4 and 18 years of age; had a nonverbal mental age above 18 months; had no history of neurological deficits, birth trauma, or perinatal complications; had no genetic evidence of fragile X syndrome or Down syndrome (
      • Fischbach G.D.
      • Lord C.
      The Simons Simplex Collection: A resource for identification of autism genetic risk factors.
      ); and had no ASD within third-degree relatives. Inclusion of both parents when available was preferred. All children included met DSM-IV or DSM-5 diagnostic criteria for ASD. The child sample included 348 female and 2273 male subjects. Parent and child participant characteristics are further described in Tables 1 and 2.
      Table 1Sample Characteristics for Parents of Individuals With ASD
      MeasureRolenMeanRangeSDAverage Scores, Mean (Range)Clinical Cutoffs, Score (% Met BAP)
      Based on Sasson et al. (70) updated norms.
      Group Difference
      BAPQ Aloof Total ScoreMother261828.6212–639.412.39 (1.00–5.25)3.45 (10)t5180.50 = 19.53, p < .0001
      Father261433.9712–6810.262.83 (1.00–5.67)4.13 (8)
      BAPQ Pragmatic Total ScoreMother261825.0411–607.332.09 (1.00–5.00)2.94 (8)t5217.74 = 14.57, p < .0001
      Father261428.0712–597.692.34 (1.00–4.92)3.23 (9)
      BAPQ Rigid Total ScoreMother261832.0812–688.802.68 (1.00–5.67)3.70 (8)t5230 = 9.76, p < .0001
      Father261434.4912–699.042.88 (1.00–5.75)3.91 (10)
      BAPQ Total ScoreMother261885.7536–16920.722.38 (1.00–4.69)3.17 (10)t5216.62 = 18.34, p < .0001
      Father261496.5340–17921.772.68 (1.11–4.97)3.55 (8)
      While total scores were used in analyses for the BAPQ, means for average scores are additionally reported along with clinical cutoffs to aid in interpretation.
      ASD, autism spectrum disorder; BAPQ, Broad Autism Phenotype Questionnaire Self Rating.
      a Based on Sasson et al. (
      • Sasson N.J.
      • Lam K.S.L.
      • Childress D.
      • Parlier M.
      • Daniels J.L.
      • Piven J.
      The Broad Autism Phenotype Questionnaire: Prevalence and diagnostic classification.
      ) updated norms.
      Table 2Sample Characteristics of Individuals With ASD
      MeasureDomainnMeanRangeSDT Scores, Mean (Range)Clinical Cutoff, Score
      Based on Sasson et al. (70) updated norms.
      Age, Years26218.932.80–17.903.57
      IQFSIQ200692.0038–16719.89
      ADOSCSS total25487.454–101.674+
      CSS RRB25617.821–101.846+
      CSS SA25617.222–101.744+
      ADI-Ra total score261920.308–305.6910+
      b verbal total score230716.506–264.288+
      b nonverbal total score26199.240–143.457+
      c total score26196.520–122.503+
      RBS-R
      While total scores were used in analyses for the SRS and RBS-R, means for T scores are additionally reported along with clinical cutoffs to aid in interpretation.
      Total score261527.060–10517.2933.14+
      SRS
      While total scores were used in analyses for the SRS and RBS-R, means for T scores are additionally reported along with clinical cutoffs to aid in interpretation.
      Total score261097.9311–17726.9579.51 (39–91)60+ (T score)
      a, reciprocal social interaction domain; ADI-R, Autism Diagnostic Interview–Revised; ADOS, Autism Diagnostic Observation Schedule; ASD, autism spectrum disorder; b, communication abnormalities domain; c, restricted and repetitive behavior domain; CSS, calibrated severity score; FSIQ, Full Scale IQ; RBS-R, Repetitive Behavior Scale–Revised; SRS, Social Responsiveness Scale.
      a Based on Sasson et al. (
      • Sasson N.J.
      • Lam K.S.L.
      • Childress D.
      • Parlier M.
      • Daniels J.L.
      • Piven J.
      The Broad Autism Phenotype Questionnaire: Prevalence and diagnostic classification.
      ) updated norms.
      b While total scores were used in analyses for the SRS and RBS-R, means for T scores are additionally reported along with clinical cutoffs to aid in interpretation.

      Phenotypic Measures

      Data Quality Control

      Parent and child phenotypes were derived based on clinical assessment and questionnaire measures aimed at characterizing BAP and ASD traits, respectively. Given the large sample size of the SSC, as well as the number of different measures included in the repository, a series of a priori analyses were completed to determine those measures that best captured a range of ASD-related traits within the constraints of a continuous distribution for PGS predictive analyses. For each parent measure, distributions were explored with all parents combined, as well as for mothers and fathers separately. For each child measure, distributions were similarly examined, though sex remained collapsed because of the smaller female sample. All variables were normally distributed, with only two measures demonstrating minimal positive skew (Repetitive Behavior Scale–Revised total scores and Autism Diagnostic Interview–Revised nonverbal scores). Parent–child correlations were examined to determine whether child phenotypes related to BAP traits in parents.

      Parent BAP Measures

      The Broad Autism Phenotype Questionnaire (BAPQ) (
      • Hurley R.S.E.
      • Losh M.
      • Parlier M.
      • Reznick J.S.
      • Piven J.
      The Broad Autism Phenotype Questionnaire.
      ) is a 36-item questionnaire that assesses the personality and pragmatic language traits that are associated with the core deficits of ASD and that are known to be associated with the BAP. Patterns of sex differences for parents of children with ASD emerged across BAPQ self-report subscales and total scores, which is consistent with prior findings (
      • Hurley R.S.E.
      • Losh M.
      • Parlier M.
      • Reznick J.S.
      • Piven J.
      The Broad Autism Phenotype Questionnaire.
      ,
      • Sasson N.J.
      • Nowlin R.B.
      • Pinkham A.E.
      Social cognition, social skill, and the broad autism phenotype.
      ). The BAPQ scores of mothers and fathers were significantly different from one another, showing elevated scores in fathers compared with those in mothers across domains (see Table 1). Mothers and fathers were therefore examined separately for all analyses. Both BAPQ self-report total score and the aloof, pragmatic language, and rigid subdomain scores were examined. Also see Assessing Use of Parent BAP Measures in the Supplement.

      Proband ASD Measures

      The following measures were explored in relationship with paternal and maternal BAPQ subscale and total scores: 1) Autism Diagnostic Observation Schedule (ADOS) calibrated severity scores (CSSs) (
      • Lord C.
      • Risi S.
      • Lambrect L.
      • Cook Jr., E.H.
      • Leventhal B.L.
      • DiLavore P.C.
      • et al.
      The Autism Diagnostic Observation Schedule–Generic: A standard measure of social and communication deficits associated with the spectrum of autism.
      ,
      • Gotham K.
      • Risi S.
      • Pickles A.
      • Lord C.
      The autism diagnostic observation schedule: Revised algorithms for improved diagnostic validity.
      ), a diagnostic tool that measures ASD symptom severity across the domains of social reciprocity, language use, and restricted and repetitive behaviors and interests (RRBs); 2) Autism Diagnostic Interview–Revised (ADI-R) (
      • Lord C.
      • Rutter M.
      • Le couteur A.
      Autism Diagnostic Interview-Revised: A revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders.
      ), a parent interview that assesses the child’s symptoms related to ASD; 3) Repetitive Behavior Scale–Revised (RBS-R) (
      • Lam K.S.L.
      • Aman M.G.
      The Repetitive Behavior Scale-Revised: Independent validation in individuals with autism spectrum disorders.
      ), a parent-report questionnaire used to measure the breadth of RRBs in individuals with ASD; 4) Social Responsiveness Scale (SRS) (
      • Constantino J.N.
      Social Responsiveness Scale.
      ) parent report (
      • Constantino J.N.
      • Todd R.D.
      Intergenerational transmission of subthreshold autistic traits in the general population.
      ), a measure of social ability in individuals with ASD; 5) Social Communication Questionnaire (
      • Rutter M.
      • Bailey A.
      • Lord C.
      The Social Communication Questionnaire.
      ), a short parent-report measure that evaluates communication skills and social functioning in individuals with ASD; 6) Aberrant Behavior Checklist (
      • Aman M.G.
      Aberrant Behavior Checklist.
      ), an informant-report measure that measures the severity of a range of problem behaviors; 7) Child Behavior Checklist (
      • Achenbach T.M.
      • Rescorla L.A.
      Manual for the ASEBA School-Age Forms and Profile.
      ), a parent-report questionnaire used to assess emotional and behavioral problems in children; and 8) Vineland Adaptive Behavior Scales (
      • Sparrow S.S.
      • Cicchetti D.V.
      The Vineland Adaptive Behavior Scales.
      ), a measure of adaptive functioning completed by parents. The Social Communication Questionnaire, Aberrant Behavior Checklist, Child Behavior Checklist, and Vineland Adaptive Behavior Scales were dropped from subsequent analyses given the lack of associations observed between these measures and parent BAPQ, to reduce the number of variables contributing to the regression models.
      As part of the SSC data-collection procedures, different IQ assessments were administered to participants based on age and cognitive ability and are described in SSC IQ Measurements in the Supplement.

      Genetic Data Quality Control

      SSC samples were genotyped on one of three Illumina platforms: 1Mv1, 1Mv3, or Omni2.5 (Illumina, San Diego, CA). Preimputation quality control (see Genotyping Quality Control and Imputation in the Supplement for details) was performed on each of the platforms separately using PLINK version 1.9 (
      • Purcell S.
      • Neale B.
      • Todd-Brown K.
      • Thomas L.
      • Ferreira M.A.R.
      • Bender D.
      • et al.
      PLINK: A tool set for whole-genome association and population-based linkage analyses.
      ). All of the arrays were combined to perform imputation using the Michigan Imputation Server with the Haplotype Reference Consortium reference panel. Final sample size included 7,650,164 single nucleotide polymorphisms on 7254 individuals.

      Polygenic Score Generation

      Summary statistics were obtained from the Psychiatric Genomics Consortium’s meta-analysis of ASD (
      • Grove J.
      • Ripke S.
      • Als T.D.
      • Mattheisen M.
      • Walters R.K.
      • Won H.
      • et al.
      Identification of common genetic risk variants for autism spectrum disorder.
      ) after removing the SSC sample. PGSs were generated using PRScs-auto (
      • Ge T.
      • Chen C.Y.
      • Ni Y.
      • Feng Y.C.A.
      • Smoller J.W.
      Polygenic prediction via Bayesian regression and continuous shrinkage priors.
      ), using the CEU sample from 1000 Genomes as the linkage disequilibrium reference panel. PRScs uses a Bayesian framework to model linkage disequilibrium from an external reference and applies a continuous shrinkage prior on single nucleotide polymorphism effect sizes to adjust for linkage disequilibrium. Using PLINK version 1.9 with the PRScs-adjusted summary statistics, PGSs were generated. PGSs were calculated on 7254 individuals with 1,113,041 single nucleotide polymorphisms. The PGSs showed no significant differences between arrays (p = .89); therefore, no further adjustment for array platform was made (Figures S1 and S2). PGSs were z score scaled for subsequent analyses so that the effect estimates were per standard deviation increase in PGS.

      Statistical Analysis

      A series of linear regression analyses were conducted across all analyses, unless otherwise specified, using base-R or the lm package for RStudio (Integrated Development for R; RStudio, PBC, Boston, MA). The p value significance thresholds were corrected for multiple testing across the entire study using both Bonferroni (0.05/195 = 3 × 10−4) and false discovery rate. False discovery rate was used in addition to Bonferroni because of the nonindependence of phenotypic variables.

      Parent–Child Phenotype Associations

      All measures reported above were included in phenotypic analyses. Each parent–child association was explored using linear models in R for mothers and fathers separately, so there were single observations per parent–child pair. No covariates were added to the regression model (
      • Dennis M.
      • Francis D.
      • Cirino P.
      • Schachar R.
      • Barnes M.
      • Fletcher J.
      Why IQ is not a covariate in cognitive studies of neurodevelopmental disorders.
      ). All measures are age corrected, and there was no significant difference between male and female subjects with ASD along any phenotypic measures. However, because proband IQ correlated with all proband and parent phenotypic variables (p values <.05), analyses were rerun with a subset of probands with IQ <70 (n = 269) and ≥70 (n = 1737) to examine potential differences in parent BAPQ and proband phenotypic associations by low- and high-IQ proband groups, respectively (for results, see IQ-Stratified Phenotype-Phenotype Associations in the Supplement). For significant associations that emerged between parent–child pairs, we used Fisher z transformation tests to empirically test whether detected parent–child associations were stronger in mother–child versus father–child dyads (for results, see Fisher’s z Transformation Tests Assessing the Strength of Phenotypic Associations in the Supplement).

      Genotype–Phenotype Analyses

      All phenotypic data reported above were used for polygenic analyses; however, sample sizes differed by measure as follows: BAPQ aloof, pragmatic, rigid, and total scores (nmothers = 1812, nfathers = 1808), ADOS total CSS (n = 1765), ADOS RRB CSS (n = 1782), ADOS social affect CSS (n = 1782), ADI-R reciprocal social interaction domain total (n = 1826), ADI communication abnormalities domain nonverbal total (n = 1826), ADI-R communication abnormalities domain verbal total (n = 1644), ADI-R restricted and repetitive behavior domain total (n = 1826), RBS-R total (n = 1824), SRS total (n = 1827), and IQ scores (n = 1443). All scores were z score scaled for analysis so that the odds ratios were per 1 SD increase in PGS.

      Parental BAPQ Phenotypes and Parental PGSs

      The association between parental PGSs and parental BAPQ phenotypes was explored between maternal or paternal PGSs and maternal or paternal BAPQ phenotypic scores, respectively, adjusting for top-10 principal components to adjust for ancestry. Sex differences in the association between ASD-PGS and BAPQ phenotypes were formally assessed using a linear regression with interaction term between ASD-PGSs and sex, controlled for the main effects of sex, ASD-PGSs, and top-10 principal components.

      Proband Phenotypes and Proband PGSs

      Proband PGSs and proband phenotypic associations adjusted for proband sex and top-10 principal components to account for ancestry.

      Parental BAPQ Phenotypes and Proband PGSs

      Associations between parent phenotypes and proband PGSs were examined by parent sex between maternal and/or paternal BAPQ scores and the proband PGSs.

      Associations Between Proband Phenotypes and Parental PGSs

      Separate analyses were performed between each proband phenotype and maternal and paternal PGSs to determine associations between proband phenotypes and parent PGSs.

      Associations Between High-BAPQ Parents and Male Probands PGSs

      To assess potential sex differences in associations between BAPQ and common genetic variation, we selected high-BAPQ mothers and fathers and tested their ASD-PGSs against male proband ASD-PGSs. Within each BAPQ domain, individuals with high BAPQs were defined as those in the fourth quartile of scores. Differences in ASD-PGSs with probands were determined separately in mothers and fathers using t tests. Results are presented in Figures S5 and S6 and Associations Between High BAPQ Parents and Male Probands Polygenic Scores in the Supplement.

      Results

      Detailed statistical reporting is presented in Table 3 and Tables S1 and S2, with findings summarized below.
      Table 3Associations Between Parental ASD-PGSs and BAPQ Phenotypes
      PhenotypePGS Subjectp ValueβSE
      AloofMother.0190.530.23
      Father.0950.420.25
      PragmaticMother.001
      Associations passing false discovery rate testing correction.
      0.580.18
      Father.0900.320.19
      RigidMother.0580.400.21
      Father.3600.200.22
      TotalMother.002
      Associations passing false discovery rate testing correction.
      1.520.50
      Father.0750.930.52
      ASD, autism spectrum disorder; BAPQ, Broad Autism Phenotype Questionnaire; PGS, polygenic score.
      a Associations passing false discovery rate testing correction.

      Parent–Child Phenotypic Associations

      Further details of parent–child phenotypic associations are provided in Figure 1 and Tables S1 and S2.
      Figure thumbnail gr1
      Figure 1Heat map of associations between (left panel) paternal and (right panel) maternal Broad Autism Phenotype Questionnaire (BAPQ) scores and proband clinical-behavioral scores. a, reciprocal social interaction domain; ADI-R, Autism Diagnostic Interview–Revised; ADOS, Autism Diagnostic Observation Schedule; b, communication abnormalities domain; c, restricted and repetitive behavior domain; CSS, calibrated severity score; FDR, false discovery rate; RBS-R, Repetitive Behavior Scale–Revised; RRB, restricted and repetitive behaviors and interests domain; SA, social affect subscale; SRS, Social Responsiveness Scale. ∗Associations passing the FDR-corrected significance threshold. ∗∗Associations passing the Bonferroni-corrected significance threshold.

      Autism Diagnostic Observation Schedule

      There was no significant association between maternal or paternal BAPQ scores and proband ADOS total CSS or any of the ADOS subscales (social affect CSS, RRB CSS).

      Autism Diagnostic Interview–Revised

      A significant positive association was detected between maternal scores on the BAPQ pragmatic subscale and proband ADI-R reciprocal social interaction and nonverbal communication total scores (Figure S3A). There were additional significant associations between maternal BAPQ aloof and proband ADI-R total nonverbal communication scores as well as between maternal BAPQ total scores and proband ADI-R reciprocal social interaction scores. There were no other significant associations between maternal BAPQ aloof, rigid, or total scores and proband ADI-R scores. There were no significant associations with paternal BAPQ scores and proband ADI-R scores overall.

      Social Responsiveness Scale

      All maternal BAPQ scores were significantly positively associated with proband SRS total scores. In contrast, only paternal BAPQ pragmatic and BAPQ total scores related to SRS total scores in probands overall. No association was observed between paternal BAPQ rigid or BAPQ aloof and proband SRS scores overall.

      Repetitive Behavior Scale–Revised

      Maternal BAPQ pragmatic, rigid, and total scores were all associated with proband RBS-R total scores overall. In contrast, paternal BAPQ rigid, total, and pragmatic scores overall (Figure S3B) were significantly positively associated with proband RBS-R total scores. No significant association between paternal or maternal BAPQ aloof scores and proband RBS-R total scores emerged.

      Genotype–Phenotype Associations

      Further details of associations between genotype and phenotype are given in Figure 2 and Table 3.
      Figure thumbnail gr2
      Figure 2Heat map of associations between paternal, maternal, and proband polygenic scores with clinical-behavioral features of autism spectrum disorder and the broad autism phenotype. a, reciprocal social interaction domain; ADI-R, Autism Diagnostic Interview–Revised; ADOS, Autism Diagnostic Observation Schedule; ASD, autism spectrum disorder; b, communication abnormalities domain; BAPQ, Broad Autism Phenotype Questionnaire; c, restricted and repetitive behavior domain; CSS, calibrated severity score; FDR, false discovery rate; PGS, polygenic score; RBS-R, Repetitive Behavior Scale–Revised; RRB, restricted and repetitive behaviors and interests domain; SA, social affect subscale; SRS, Social Responsiveness Scale. ∗Associations passing the FDR-corrected significance threshold.

      Parental BAPQ Phenotypes and Parental ASD-PGSs

      Maternal polygenic scores were associated with BAPQ pragmatic and total scores. However, paternal ASD-PGSs were not associated with any phenotype tested. Additionally, the effect estimates of maternal PGSs on maternal pragmatic, rigid, and total BAPQ scores were increased compared with the effect estimates of paternal PGSs on paternal BAPQ scores. No BAPQ domain showed a significant interaction between sex and ASD-PGS (aloof p = .489, pragmatic p = .243, rigid p = .331, total p = .249). See Figure S4.

      Proband Phenotypes and Proband ASD-PGSs

      Proband ASD-PGSs were not associated with any phenotype tested.

      Parental BAPQ Phenotypes and Proband ASD-PGSs

      Proband ASD-PGSs did not show any association with mother’s or father’s BAPQ scores.

      Proband Phenotypes and Parental ASD-PGSs

      None of the tested proband phenotypes showed an association with maternal or paternal ASD-PGS.

      Discussion

      This study examined PGSs within families of individuals with ASD, with the goal of exploring parent and child genotype–phenotype and phenotype–phenotype associations, as well as familial polygenic liability associated with ASD. While previous studies examined transmission disequilibrium in ASD genetic variants (
      • Weiner D.J.
      • Wigdor E.M.
      • Ripke S.
      • Walters R.K.
      • Kosmicki J.A.
      • Grove J.
      • et al.
      Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders.
      ), this study evaluated the role of the familial relationship as an explanation for phenotypic similarity. Overall, results demonstrated relationships between parent and child clinical-behavioral phenotypes regardless of IQ, as well as associations between maternal PGSs and features of the BAP. Given the likelihood of increased de novo mutations in simplex families studied here, our results further emphasize the role of inherited genetic risk associated with ASD and the constituent features of ASD and the BAP.
      Consistent with prior work (
      • Weiner D.J.
      • Wigdor E.M.
      • Ripke S.
      • Walters R.K.
      • Kosmicki J.A.
      • Grove J.
      • et al.
      Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders.
      ,
      • Rubenstein E.
      • Chawla D.
      Broader autism phenotype in parents of children with autism: A systematic review of percentage estimates.
      ), despite elevated scores of BAP trait expression emerging in fathers versus mothers, results revealed more robust relationships between maternal BAPQ scores and child clinical-behavioral traits (see Fisher’s z Transformation Tests Assessing the Strength of Phenotypic Associations in the Supplement). Maternal language-related phenotypes were consistently associated with more severe ASD symptomatology in probands, including strong associations between maternal pragmatic language scores and children’s social and nonverbal communication skills measured by the ADI-R, particularly in those children with lower IQ. Similar parent–child associations have been observed in other studies examining language-related phenotypes, where subtle differences in language fluency in mothers with the BAP were related to more severe symptoms in their children with ASD (
      • Nayar K.
      • Gordon P.C.
      • Martin G.E.
      • Hogan A.L.
      • La Valle C.
      • McKinney W.
      • et al.
      Links between looking and speaking in autism and first-degree relatives: Insights into the expression of genetic liability to autism.
      ) [although a recent study in a smaller sample of mothers and fathers showed no relationships between maternal pragmatic language and child language features (
      • Sasson N.J.
      • Faso D.J.
      • Parlier M.
      • Daniels J.L.
      • Piven J.
      When father doesn’t know best: Selective disagreement between self-report and informant report of the broad autism phenotype in parents of a child with autism.
      )]. Such a pattern of lineality may suggest a stronger inherited maternal effect for language-related phenotypes in ASD (though parents and children influence one another’s language patterns as well). Whereas the maternal effect appeared to be centered around language-related phenotypes, paternal BAP features appeared to be more associated with the RRB/rigid domain, particularly in those children with higher IQ. In contrast, all domains of the BAP in mothers were related to RRBs in probands regardless of proband IQ. Despite there being no prior family history of ASD in the families included in this study, these patterns of familiality may be further evidence that constituent features related to ASD combine additively to increase ASD risk (
      • Flippin M.
      • Watson L.R.
      Parental broad autism phenotype and the language skills of children with autism spectrum disorder.
      ).
      One important consideration is that all associations between parent and child phenotypes emerged in parent-report measures (i.e., SRS, RBS-R, ADI-R) where mothers were typically the informant. It is possible that reporting bias existed that may have influenced results (although this possibility is true for most studies examining parent–child correlates, where data are generally derived from questionnaires completed by parents). It is also possible that because questionnaire measures typically provide a wider range of scores, variability is better captured (e.g., the RBS-R total scores in the present sample range from 0 to 105 [Table 2] compared with the ADOS severity scores, which range from 1 to 10). Significant associations emerging from parent–child association analyses of the ADI-R (and not the ADOS) could also be due to the different age ranges tapped by these measures—i.e., the ADI-R emphasizes early development, when ASD traits are often most apparent, whereas the ADOS captures a small window of current behaviors during the 40- to 60-minute direct-assessment period.
      In line with findings from phenotypic analyses within families, analyses of parents’ ASD-PGSs also demonstrated a robust maternal genetic effect on mothers’ phenotypes, such that polygenic variants associated with ASD predicted maternal BAP features, including pragmatic language differences. The effect estimates of maternal PGSs on BAPQ scores were in some cases almost double the effect of paternal PGSs on paternal BAPQ scores, which could indicate an effect of sex on ASD-risk genes on the BAP. However, interaction tests showed that the ASD-PGSs of mothers and fathers did not have statistically different effect estimates with BAPQ domains. Since interaction terms require a substantially larger sample size to achieve statistical significance than main effects, the lack of a significant interaction could be due to low power rather than lack of true biologic differences. Thus, larger studies with greater power to detect sex interactions should consider conducting similar analyses. Sex differences are well documented in both diagnostic rates and phenotypic expression in male and female subjects with ASD (
      • Pohl A.
      • Jones W.R.
      • Marrus N.
      • Zhang Y.
      • Klin A.
      • Constantino J.N.
      Behavioral predictors of autism recurrence are genetically independent and influence social reciprocity: Evidence that polygenic ASD risk is mediated by separable elements of developmental liability.
      ,
      • Lai M.C.
      • Lombardo M.V.
      • Auyeung B.
      • Chakrabarti B.
      • Baron-Cohen S.
      Sex/gender differences and autism: Setting the scene for future research.
      ), and they have been hypothesized to result from a female protective effect (
      • Young H.
      • Oreve M.J.
      • Speranza M.
      Clinical characteristics and problems diagnosing autism spectrum disorder in girls.
      ), where female subjects require greater inherited risk than males to exhibit ASD. Although large-scale studies have shown no appreciable difference in the common variant liability between male and female subjects with ASD (
      • Tsai L.
      • Stewart M.A.
      • August G.
      Implication of sex differences in the familial transmission of infantile autism.
      ), studies have shown an enrichment of loss-of-function de novo variants and rare copy number variants in female cases compared with controls (
      • Mitra I.
      • Tsang K.
      • Ladd-Acosta C.
      • Croen L.A.
      • Aldinger K.A.
      • Hendren R.L.
      • et al.
      Pleiotropic mechanisms indicated for sex differences in autism [published correction appears in PLoS Genet 2017 13:e1006831].
      ). The different phenotypic and genotypic–phenotypic associations that emerged among mothers versus fathers may provide evidence for a female genetic protection for common variation as it relates to the ASD phenotypic spectrum. Mothers with increased BAPQ scores showed no difference in ASD-PGSs compared with male probands with ASD, whereas fathers with increased BAPQ scores showed significantly lower ASD-PGSs than male probands with ASD (see Figures S5 and S6 and Associations Between High BAPQ Parents and Male Probands Polygenic Scores in the Supplement). Moreover, father BAPQ scores were correlated with some phenotypes in children with IQ >70, while mother BAPQ scores were associated more broadly with phenotypes among all children (i.e., both low- and high-IQ groups) (see IQ-Stratified Phenotype-Phenotype Associations in the Supplement). Taken together, though they should be interpreted with caution, these findings are consistent with the possibility of a female protective effect (
      • Mitra I.
      • Tsang K.
      • Ladd-Acosta C.
      • Croen L.A.
      • Aldinger K.A.
      • Hendren R.L.
      • et al.
      Pleiotropic mechanisms indicated for sex differences in autism [published correction appears in PLoS Genet 2017 13:e1006831].
      ,
      • Jacquemont S.
      • Coe B.P.
      • Hersch M.
      • Duyzend M.H.
      • Krumm N.
      • Bergmann S.
      • et al.
      A higher mutational burden in females supports a “female protective model” in neurodevelopmental disorders.
      ) and warrant further investigation in additional cohorts. The discrepancy between studies may be due to the generally smaller female ASD sample sizes included in prior work (
      • Pohl A.
      • Jones W.R.
      • Marrus N.
      • Zhang Y.
      • Klin A.
      • Constantino J.N.
      Behavioral predictors of autism recurrence are genetically independent and influence social reciprocity: Evidence that polygenic ASD risk is mediated by separable elements of developmental liability.
      ) in comparison with the larger sample sizes of unaffected mothers with increased genetic liability to ASD included in this study, likely increasing power to detect a female protective effect on domain phenotypes. As such, this study may inform understanding of familial transmission of ASD-related traits, which may help to enhance power to detect genetic phenotypic variants associated with ASD.
      Finally, the lack of association of proband ASD-PGSs or parental BAP scores with proband clinical-behavioral features, as well as of parental PGSs with proband clinical-behavioral phenotypes, were somewhat surprising. Lack of association may be a reflection of the phenotypic homogeneity present in the SSC sample (given the stringent selection criteria of the SSC) and/or potentially higher intellectual ability of parents in the SSC (though this metric was not directly assessed in parents in the SSC sample), which has been found to be associated with greater polygenic risk (
      • Clarke T.K.
      • Lupton M.K.
      • Fernandez-Pujals A.M.
      • Starr J.
      • Davies G.
      • Cox S.
      • et al.
      Common polygenic risk for autism spectrum disorder (ASD) is associated with cognitive ability in the general population.
      ,
      • Constantino J.N.
      Data from the Baby Siblings Research Consortium confirm and specify the nature of the female protective effect in autism: A commentary on Messinger et al.
      ,
      • Bulik-Sullivan B.
      • Finucane H.K.
      • Anttila V.
      • Gusev A.
      • Day F.R.
      • Loh P.R.
      • et al.
      An atlas of genetic correlations across human diseases and traits.
      ,
      • Okbay A.
      • Beauchamp J.P.
      • Fontana M.A.
      • Lee J.J.
      • Pers T.H.
      • Rietveld C.A.
      • et al.
      Genome-wide association study identifies 74 loci associated with educational attainment.
      ). Additionally, the large age range in ASD probands may affect the ability to find genetic associations with social communication traits, which have been shown to vary during adolescence (
      • Hagenaars S.P.
      • Harris S.E.
      • Davies G.
      • Hill W.D.
      • Liewald D.C.M.
      • Ritchie S.J.
      • et al.
      Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (N=112 151) and 24 GWAS consortia.
      ). Inclusion of only simplex families from the SFARI (Simons Foundation Autism Research Initiative) Base SSC may additionally explain the lack of findings, with theorized additive genetic risk more commonly occurring in multiplex versus simplex families (
      • St Pourcain B.
      • Skuse D.H.
      • Mandy W.P.
      • Wang K.
      • Hakonarson H.
      • Timpson N.J.
      • et al.
      Variability in the common genetic architecture of social-communication spectrum phenotypes during childhood and adolescence.
      ). Furthermore, the SSC excluded families in which ASD was suspected in parents, potentially reducing the variance of BAP features in the sample and reducing the ability to find associations with BAP features. A final explanation may be linked to the differential genetic architectures underlying ASD traits more broadly and social communication traits more specifically (
      • Hagenaars S.P.
      • Harris S.E.
      • Davies G.
      • Hill W.D.
      • Liewald D.C.M.
      • Ritchie S.J.
      • et al.
      Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (N=112 151) and 24 GWAS consortia.
      ,
      • Klei L.
      • Sanders S.J.
      • Murtha M.T.
      • Hus V.
      • Lowe J.K.
      • Willsey A.J.
      • et al.
      Common genetic variants, acting additively, are a major source of risk for autism.
      ,
      • Constantino J.N.
      Deconstructing autism: from unitary syndrome to contributory developmental endophenotypes.
      ,
      • Ronald A.
      • Happé F.
      • Plomin R.
      The genetic relationship between individual differences in social and nonsocial behaviours characteristic of autism.
      ), which diminishes the likelihood of associations between ASD-risk genes and communication phenotypic traits. As such, future studies should consider the inclusion of multiplex families and may also benefit from the inclusion of additional BAP assessments in analyses, as questionnaires may limit the sensitivity of BAP trait detection given potential reporting biases in self-report measures of BAP traits (
      • Sasson N.J.
      • Nowlin R.B.
      • Pinkham A.E.
      Social cognition, social skill, and the broad autism phenotype.
      ).
      In sum, this study revealed key associations of ASD-related features in probands with ASD and the parental BAP, with effects on mothers emerging in the language-related social communication domain, and paternal phenotypic effects in the rigid/RRB domain. Additionally, ASD-PGS associations with the BAP emerged only in mothers, highlighting the potential for a female protective factor that may also be expressed among first-degree relatives of individuals with ASD. Together, findings from this study underscore the significance of the BAP in parents, which may reflect more influences from common genetic variation and polygenic risk rather than rare variation that contributes to aggregate and heterogeneous ASD (
      • Gottesman II,
      • Gould T.D.
      The endophenotype concept in psychiatry: Etymology and strategic intentions.
      ).

      Acknowledgments and Disclosures

      This work was supported by grants from the National Institutes of Health (Grant Nos. R01DC010191 and R01MH091131 [to principal investigator ML; KN, LB] and Grant Nos. U54MD010722-04, R01NS102371, R01MH113362, U01HG009086, R01MH118223, DP2HD98859, R01DC16977, R01NS105746, R56MH120736, R21HG010652, and RM1HG009034 [to LKD]) and the National Institutes of Health National Institute of General Medical Sciences (Grant No. 5T32GM080178–12 [JMS; principal investigator, Nancy J. Cox]). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
      ML, LKD, and EHC conceived and designed the study and oversaw all analyses and writing of the manuscript. KN and JMS led data processing, analysis, and manuscript preparation. NM and LB contributed to data processing and analysis. NM also contributed to manuscript preparation. All authors read and approved the final manuscript.
      We are grateful to all of the families at the participating SSC sites, as well as the principal investigators (A. Beaudet, R. Bernier, J. Constantino, E. Cook, E. Fombonne, D. Geschwind, R. Goin-Kochel, E. Hanson, D. Grice, A. Klin, D. Ledbetter, C. Lord, C. Martin, D. Martin, R. Maxim, J. Miles, O. Ousley, K. Pelphrey, B. Peterson, J. Piggot, C. Saulnier, M. State, W. Stone, J. Sutcliffe, C. Walsh, Z. Warren, E. Wijsman). We appreciate obtaining access to phenotypic and genetic data on SFARI Base. Approved researchers can obtain the SSC population dataset described in this study (https://www.sfari.org/resource/simons-simplex-collection/) by applying at https://base.sfari.org. We also thank Dr. Richard Anney for providing the summary statistics from the ASD working group of the Psychiatric Genomics Consortium excluding the SSC samples.
      The authors report no biomedical financial interests or potential conflicts of interest.

      Supplementary Material

      References

        • Baio J.
        • Wiggins L.
        • Christensen D.L.
        • Maenner M.J.
        • Daniels J.
        • Warren Z.
        • et al.
        Prevalence of autism spectrum disorder among children aged 8 years—Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2014.
        MMWR Surveill Summ. 2018; 67: 1-23
        • Folstein S.
        • Rutter M.
        Genetic influences and infantile autism.
        Nature. 1977; 265: 726-728
        • Bailey A.
        • Le Couteur A.
        • Gottesman I.
        • Bolton P.
        • Simonoff E.
        • Yuzda E.
        • Rutter M.
        Autism as a strongly genetic disorder: Evidence from a British twin study.
        Psychol Med. 1995; 25: 63-77
        • Tick B.
        • Bolton P.
        • Happé F.
        • Rutter M.
        • Rijsdijk F.
        Heritability of autism spectrum disorders: A meta-analysis of twin studies.
        J Child Psychol Psychiatry. 2016; 57: 585-595
        • Wong E.H.F.
        • Fox J.C.
        • Ng M.Y.M.
        • Lee C.-M.
        Toward personalized medicine in the neuropsychiatric field.
        Int Rev Neurobiol. 2011; 101: 329-349
        • Beauchaine T.P.
        • Constantino J.N.
        Redefining the endophenotype concept to accommodate transdiagnostic vulnerabilities and etiological complexity.
        Biomark Med. 2017; 11: 769-780
        • Woodbury-Smith M.
        • Nicolson R.
        • Zarrei M.
        • Yuen R.K.C.
        • Walker S.
        • Howe J.
        • et al.
        Variable phenotype expression in a family segregating microdeletions of the NRXN1 and MBD5 autism spectrum disorder susceptibility genes.
        NPJ Genomic Med. 2017; 2: 17
        • Bishop D.V.M.
        • Maybery M.
        • Wong D.
        • Maley A.
        • Hill W.
        • Hallmayer J.
        Are phonological processing deficits part of the broad autism phenotype?.
        Am J Med Genet. 2004; 128B: 54-60
        • Frazier T.W.
        • Youngstrom E.A.
        • Hardan A.Y.
        • Georgiades S.
        • Constantino J.N.
        • Eng C.
        Quantitative autism symptom patterns recapitulate differential mechanisms of genetic transmission in single and multiple incidence families.
        Mol Autism. 2015; 6: 58
        • Hurley R.S.E.
        • Losh M.
        • Parlier M.
        • Reznick J.S.
        • Piven J.
        The Broad Autism Phenotype Questionnaire.
        J Autism Dev Disord. 2007; 37: 1679-1690
        • Sasson N.J.
        • Lam K.S.L.
        • Parlier M.
        • Daniels J.L.
        • Piven J.
        Autism and the broad autism phenotype: Familial patterns and intergenerational transmission.
        J Neurodev Disord. 2013; 5: 11
        • Losh M.
        • Esserman D.
        • Piven J.
        Rapid automatized naming as an index of genetic liability to autism.
        J Neurodev Disord. 2010; 2: 109-116
        • Gerdts J.A.
        • Bernier R.
        • Dawson G.
        • Estes A.
        The broader autism phenotype in simplex and multiplex families.
        J Autism Dev Disord. 2013; 43: 1597-1605
        • Stern Y.S.
        • Maltman N.
        • Roberts M.Y.
        The influence of maternal pragmatics on the language skills of children with autism.
        J Dev Behav Pediatr. 2017; 38: 339-344
        • Klusek J.
        • Martin G.E.
        • Losh M.
        Consistency between research and clinical diagnoses of autism among boys and girls with fragile X syndrome.
        J Intellect Disabil Res. 2014; 58: 940-952
        • Levin-Decanini T.
        • Maltman N.
        • Francis S.M.
        • Guter S.
        • Anderson G.M.
        • Cook E.H.
        • Jacob S.
        Parental broader autism subphenotypes in ASD affected families: Relationship to gender, child’s symptoms, SSRI treatment, and platelet serotonin.
        Autism Res. 2013; 6: 621-630
        • Losh M.
        • Martin G.E.
        • Lee M.
        • Klusek J.
        • Sideris J.
        • Barron S.
        • Wassink T.
        Developmental markers of genetic liability to autism in parents: A longitudinal, multigenerational study.
        J Autism Dev Disord. 2017; 47: 834-845
        • Losh M.
        • Adolphs R.
        • Piven J.
        The broad autism phenotype.
        in: Dawson G. Amaral D. Geschwind D. Autism Spectrum Disorders. Oxford University Press, Oxford2011: 457-476
        • Nayar K.
        • Gordon P.C.
        • Martin G.E.
        • Hogan A.L.
        • La Valle C.
        • McKinney W.
        • et al.
        Links between looking and speaking in autism and first-degree relatives: Insights into the expression of genetic liability to autism.
        Mol Autism. 2018; 9: 51
        • Hogan-Brown A.L.
        • Hoedemaker R.S.
        • Gordon P.C.
        • Losh M.
        Eye-voice span during rapid automatized naming: Evidence of reduced automaticity in individuals with autism spectrum disorder and their siblings.
        J Neurodev Disord. 2014; 6: 33
        • Losh M.
        • Adolphs R.
        • Poe M.D.
        • Couture S.
        • Penn D.
        • Baranek G.T.
        • Piven J.
        Neuropsychological profile of autism and the broad autism phenotype.
        Arch Gen Psychiatry. 2009; 66: 518-526
        • Losh M.
        • Childress D.
        • Lam K.
        • Piven J.
        Defining key features of the broad autism phenotype: A comparison across parents of multiple- and single-incidence autism families.
        Am J Med Genet B Neuropsychiatr Genet. 2008; 147: 424-433
        • Constantino J.N.
        • Todd R.D.
        Autistic traits in the general population: A twin study.
        Arch Gen Psychiatry. 2003; 60: 524-530
        • Piven J.
        • Wzorek M.
        • Landa R.
        • Lainhart J.
        • Bolton P.
        • Chase G.
        • Folstein S.
        Personality characteristics of the parents of autistic individuals.
        Psychol Med. 1994; 24: 783-795
        • Happé F.
        • Ronald A.
        • Plomin R.
        Time to give up on a single explanation for autism.
        Nat Neurosci. 2006; 9: 1218-1220
        • Gottesman II,
        • Gould T.D.
        The endophenotype concept in psychiatry: Etymology and strategic intentions.
        Am J Psychiatry. 2003; 160: 636-645
        • Davidson J.
        • Goin-Kochel R.P.
        • Green-Snyder L.A.
        Expression of the broad autism phenotype in simplex autism families from the Simons Simplex Collection.
        J Autism Dev Disord. 2014; 44: 2392-2399
        • Woodbury-Smith M.
        • Paterson A.D.
        • O’Connor I.
        • Zarrei M.
        • Yuen R.K.C.
        • Howe J.L.
        • et al.
        A genome-wide linkage study of autism spectrum disorder and the broad autism phenotype in extended pedigrees.
        J Neurodev Disord. 2018; 10: 20
        • De La Torre-Ubieta L.
        • Won H.
        • Stein J.L.
        • Geschwind D.H.
        Advancing the understanding of autism disease mechanisms through genetics.
        Nat Med. 2016; 22: 345-361
        • Sandin S.
        • Lichtenstein P.
        • Kuja-Halkola R.
        • Larsson H.
        • Hultman C.M.
        • Reichenberg A.
        The familial risk of autism.
        JAMA. 2014; 311: 1770-1777
        • Vorstman J.A.S.
        • Parr J.R.
        • Moreno-De-Luca D.
        • Anney R.J.L.
        • Nurnberger J.I.
        • Hallmayer J.F.
        Autism genetics: Opportunities and challenges for clinical translation.
        Nat Rev Genet. 2017; 18: 362-376
        • Gaugler T.
        • Klei L.
        • Sanders S.J.
        • Bodea C.A.
        • Goldberg A.P.
        • Lee A.B.
        • et al.
        Most genetic risk for autism resides with common variation.
        Nat Genet. 2014; 46: 881-885
        • Robinson E.B.
        • St Pourcain B.
        • Anttila V.
        • Kosmicki J.A.
        • Bulik-Sullivan B.
        • Grove J.
        • et al.
        Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population.
        Nat Genet. 2016; 48: 552-555
        • Anney R.
        • Klei L.
        • Pinto D.
        • Almeida J.
        • Bacchelli E.
        • Baird G.
        • et al.
        Individual common variants exert weak effects on the risk for autism spectrum disorders.
        Hum Mol Genet. 2012; 21: 4781-4792
        • Grove J.
        • Ripke S.
        • Als T.D.
        • Mattheisen M.
        • Walters R.K.
        • Won H.
        • et al.
        Identification of common genetic risk variants for autism spectrum disorder.
        Nat Genet. 2019; 51: 431-444
        • Clarke T.K.
        • Lupton M.K.
        • Fernandez-Pujals A.M.
        • Starr J.
        • Davies G.
        • Cox S.
        • et al.
        Common polygenic risk for autism spectrum disorder (ASD) is associated with cognitive ability in the general population.
        Mol Psychiatry. 2016; 21: 419-425
        • Fischbach G.D.
        • Lord C.
        The Simons Simplex Collection: A resource for identification of autism genetic risk factors.
        Neuron. 2010; 68: 192-195
        • Sasson N.J.
        • Nowlin R.B.
        • Pinkham A.E.
        Social cognition, social skill, and the broad autism phenotype.
        Autism. 2013; 17: 655-667
        • Lord C.
        • Risi S.
        • Lambrect L.
        • Cook Jr., E.H.
        • Leventhal B.L.
        • DiLavore P.C.
        • et al.
        The Autism Diagnostic Observation Schedule–Generic: A standard measure of social and communication deficits associated with the spectrum of autism.
        J Autism Dev Disord. 2000; 30: 205-223
        • Gotham K.
        • Risi S.
        • Pickles A.
        • Lord C.
        The autism diagnostic observation schedule: Revised algorithms for improved diagnostic validity.
        J Autism Dev Disord. 2007; 37: 613-627
        • Lord C.
        • Rutter M.
        • Le couteur A.
        Autism Diagnostic Interview-Revised: A revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders.
        J Autism Dev Disord. 1994; 24: 1-27
        • Lam K.S.L.
        • Aman M.G.
        The Repetitive Behavior Scale-Revised: Independent validation in individuals with autism spectrum disorders.
        J Autism Dev Disord. 2007; 37: 855-866
        • Constantino J.N.
        Social Responsiveness Scale.
        in: Volkmar F.R. Encyclopedia of Autism Spectrum Disorders. Springer, New York, NY2013: 2919-2929
        • Constantino J.N.
        • Todd R.D.
        Intergenerational transmission of subthreshold autistic traits in the general population.
        Biol Psychiatry. 2005; 57: 655-660
        • Rutter M.
        • Bailey A.
        • Lord C.
        The Social Communication Questionnaire.
        Western Psychological Services, Los Angeles, CA2003
        • Aman M.G.
        Aberrant Behavior Checklist.
        in: Volkmar F.R. Encyclopedia of Autism Spectrum Disorders. Springer, New York, NY2013: 10-17
        • Achenbach T.M.
        • Rescorla L.A.
        Manual for the ASEBA School-Age Forms and Profile.
        University of Vermont, Research Center for Children, Youth, and Families, Burlington, VT2001
        • Sparrow S.S.
        • Cicchetti D.V.
        The Vineland Adaptive Behavior Scales.
        in: Newmark C.S. Major Psychological Assessment Instruments, vol 2. Allyn and Bacon, Boston, MA1989: 199-231
        • Purcell S.
        • Neale B.
        • Todd-Brown K.
        • Thomas L.
        • Ferreira M.A.R.
        • Bender D.
        • et al.
        PLINK: A tool set for whole-genome association and population-based linkage analyses.
        Am J Hum Genet. 2007; 81: 559-575
        • Ge T.
        • Chen C.Y.
        • Ni Y.
        • Feng Y.C.A.
        • Smoller J.W.
        Polygenic prediction via Bayesian regression and continuous shrinkage priors.
        Nat Commun. 2019; 10: 1776
        • Dennis M.
        • Francis D.
        • Cirino P.
        • Schachar R.
        • Barnes M.
        • Fletcher J.
        Why IQ is not a covariate in cognitive studies of neurodevelopmental disorders.
        J Int Neuropsychol Soc. 2009; 15: 331-343
        • Weiner D.J.
        • Wigdor E.M.
        • Ripke S.
        • Walters R.K.
        • Kosmicki J.A.
        • Grove J.
        • et al.
        Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders.
        Nat Genet. 2017; 49: 978-985
        • Rubenstein E.
        • Chawla D.
        Broader autism phenotype in parents of children with autism: A systematic review of percentage estimates.
        J Child Fam Stud. 2018; 27: 1705-1720
        • Sasson N.J.
        • Faso D.J.
        • Parlier M.
        • Daniels J.L.
        • Piven J.
        When father doesn’t know best: Selective disagreement between self-report and informant report of the broad autism phenotype in parents of a child with autism.
        Autism Res. 2014; 7: 731-739
        • Flippin M.
        • Watson L.R.
        Parental broad autism phenotype and the language skills of children with autism spectrum disorder.
        J Autism Dev Disord. 2018; 48: 1895-1907
        • Pohl A.
        • Jones W.R.
        • Marrus N.
        • Zhang Y.
        • Klin A.
        • Constantino J.N.
        Behavioral predictors of autism recurrence are genetically independent and influence social reciprocity: Evidence that polygenic ASD risk is mediated by separable elements of developmental liability.
        Transl Psychiatry. 2019; 9: 202
        • Lai M.C.
        • Lombardo M.V.
        • 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: 11-24
        • Young H.
        • Oreve M.J.
        • Speranza M.
        Clinical characteristics and problems diagnosing autism spectrum disorder in girls.
        Arch Pediatr. 2018; 25: 399-403
        • Tsai L.
        • Stewart M.A.
        • August G.
        Implication of sex differences in the familial transmission of infantile autism.
        J Autism Dev Disord. 1981; 11: 165-173
        • Mitra I.
        • Tsang K.
        • Ladd-Acosta C.
        • Croen L.A.
        • Aldinger K.A.
        • Hendren R.L.
        • et al.
        Pleiotropic mechanisms indicated for sex differences in autism [published correction appears in PLoS Genet 2017 13:e1006831].
        PLoS Genet. 2016; 12e1006425
        • Jacquemont S.
        • Coe B.P.
        • Hersch M.
        • Duyzend M.H.
        • Krumm N.
        • Bergmann S.
        • et al.
        A higher mutational burden in females supports a “female protective model” in neurodevelopmental disorders.
        Am J Hum Genet. 2014; 94: 415-425
        • Constantino J.N.
        Data from the Baby Siblings Research Consortium confirm and specify the nature of the female protective effect in autism: A commentary on Messinger et al.
        Mol Autism. 2016; 7: 32
        • Bulik-Sullivan B.
        • Finucane H.K.
        • Anttila V.
        • Gusev A.
        • Day F.R.
        • Loh P.R.
        • et al.
        An atlas of genetic correlations across human diseases and traits.
        Nat Genet. 2015; 47: 1236-1241
        • Okbay A.
        • Beauchamp J.P.
        • Fontana M.A.
        • Lee J.J.
        • Pers T.H.
        • Rietveld C.A.
        • et al.
        Genome-wide association study identifies 74 loci associated with educational attainment.
        Nature. 2016; 533: 539-542
        • Hagenaars S.P.
        • Harris S.E.
        • Davies G.
        • Hill W.D.
        • Liewald D.C.M.
        • Ritchie S.J.
        • et al.
        Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (N=112 151) and 24 GWAS consortia.
        Mol Psychiatry. 2016; 21: 1624-1632
        • St Pourcain B.
        • Skuse D.H.
        • Mandy W.P.
        • Wang K.
        • Hakonarson H.
        • Timpson N.J.
        • et al.
        Variability in the common genetic architecture of social-communication spectrum phenotypes during childhood and adolescence.
        Mol Autism. 2014; 5: 18
        • Klei L.
        • Sanders S.J.
        • Murtha M.T.
        • Hus V.
        • Lowe J.K.
        • Willsey A.J.
        • et al.
        Common genetic variants, acting additively, are a major source of risk for autism.
        Mol Autism. 2012; 3: 9
        • Constantino J.N.
        Deconstructing autism: from unitary syndrome to contributory developmental endophenotypes.
        Int Rev Psychiatry. 2018; 30: 18-24
        • Ronald A.
        • Happé F.
        • Plomin R.
        The genetic relationship between individual differences in social and nonsocial behaviours characteristic of autism.
        Dev Sci. 2005; 8: 444-458
        • Sasson N.J.
        • Lam K.S.L.
        • Childress D.
        • Parlier M.
        • Daniels J.L.
        • Piven J.
        The Broad Autism Phenotype Questionnaire: Prevalence and diagnostic classification.
        Autism Res. 2013; 6: 134-143

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        Biological PsychiatryVol. 89Issue 5
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          Genetic risk for autism spectrum disorder (ASD) is present, to some degree, in all of us. This is because ASDs are polygenic traits, meaning that they reflect the aggregate influence of many thousands of common, inherited variants across the genome. Individually, each of these common variants carry a small amount of ASD risk. This is by necessity, as any genetic difference that confers a large amount of risk for a fecundity-reducing outcome, like ASD, cannot be common in the population (1). Therefore, if a risk variant for ASD is common—present in many or most of us—its effect is small.
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