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Transgender and Gender-Diverse Autistic Adolescents Are at Elevated Risk of Depression

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Title: Transgender and Gender-Diverse Autistic Adolescents Are at Elevated Risk of Depression
Language: English
Authors: Joseph Pereira, Natalia Ramos (ORCID 0000-0001-8688-9426), LeeAnne Green Snyder, Jeremy Veenstra-VanderWeele, Amandeep Jutla (ORCID 0000-0001-5973-9940)
Source: Autism: The International Journal of Research and Practice. 2026 30(2):316-328.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 13
Publication Date: 2026
Sponsoring Agency: National Institute of Mental Health (NIMH) (DHHS/NIH)
Contract Number: 2T32MH0164344
5K23MH13287402
Document Type: Journal Articles
Reports - Research
Descriptors: Autism Spectrum Disorders, Transgender People, Adolescents, LGBTQ People, At Risk Persons, Depression (Psychology), Correlation, Mental Disorders, Individual Characteristics
DOI: 10.1177/13623613251396712
ISSN: 1362-3613
1461-7005
Abstract: Autistic people are more likely to be transgender and gender diverse than the general population. Furthermore, co-occurring trait-level autism and transgender and gender-diverse identity are associated with symptoms of depression and anxiety, and autistic adolescents who identify as transgender and gender diverse have more internalizing behaviors than both non-transgender and gender-diverse autistic adolescents and non-autistic transgender and gender-diverse adolescents. However, no study has yet examined the extent to which transgender and gender-diverse identity predicts specific co-occurring mental health diagnoses in autistic adolescents. In a sample of 9027 autistic adolescents aged 13 to 17 drawn from the Simons Powering Autism Research for Knowledge cohort, 36 of whom we identified as transgender and gender diverse, we estimated univariate models of transgender and gender-diverse identity as a predictor of individual diagnoses. Depression, but no other diagnosis, remained statistically significant after adjustment for multiple comparisons. In a multiple regression model that incorporated known risk factors for adolescent depression (e.g. language impairment and disturbed sleep), transgender and gender-diverse identity remained a significant predictor (odds ratio: 4.01, 95% confidence interval: 1.87-8.67, p = 5.94 × 10[superscript -4]) with an effect size at least as strong as that of a depression family history. This suggests transgender and gender-diverse autistic adolescents, who often face stigma and discrimination, are particularly vulnerable to depression.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1494733
Database: ERIC
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  Value: <anid>AN0190905316;f9d01feb.26;2026Jan19.05:34;v2.2.500</anid> <title id="AN0190905316-1">Transgender and gender-diverse autistic adolescents are at elevated risk of depression </title> <p>Autistic people are more likely to be transgender and gender diverse than the general population. Furthermore, co-occurring trait-level autism and transgender and gender-diverse identity are associated with symptoms of depression and anxiety, and autistic adolescents who identify as transgender and gender diverse have more internalizing behaviors than both non-transgender and gender-diverse autistic adolescents and non-autistic transgender and gender-diverse adolescents. However, no study has yet examined the extent to which transgender and gender-diverse identity predicts specific co-occurring mental health diagnoses in autistic adolescents. In a sample of 9027 autistic adolescents aged 13 to 17 drawn from the Simons Powering Autism Research for Knowledge cohort, 36 of whom we identified as transgender and gender diverse, we estimated univariate models of transgender and gender-diverse identity as a predictor of individual diagnoses. Depression, but no other diagnosis, remained statistically significant after adjustment for multiple comparisons. In a multiple regression model that incorporated known risk factors for adolescent depression (e.g. language impairment and disturbed sleep), transgender and gender-diverse identity remained a significant predictor (odds ratio: 4.01, 95% confidence interval: 1.87–8.67, p = 5.94 × 10<sup>−4</sup>) with an effect size at least as strong as that of a depression family history. This suggests transgender and gender-diverse autistic adolescents, who often face stigma and discrimination, are particularly vulnerable to depression. "Transgender and gender diverse" (TGD) people have gender identities that differ from the sex they were assigned at birth. Many autistic people have a TGD identity. Autistic adolescents who are TGD have more "internalizing symptoms," which include symptoms of depression and anxiety, than autistic adolescents who are not TGD. In this study, we examined a group of 9027 autistic adolescents, 36 of whom had a TGD identity, to determine which, if any, mental health diagnoses would be associated with TGD identity, and whether those associations would remain even after accounting for known risk factors for a diagnosis. We found that depression, but no other diagnosis, was associated with TGD identity. This association remained even when accounting for known risk factors for depression, and in fact, TGD identity was associated with depression at least as strongly as a family history of that diagnosis. This strong association is perhaps not surprising. TGD adolescents often face stigma, social rejection, and discrimination, which can lead to depression. Autistic adolescents can face similar difficulties. Autistic youth who also have a TGD identity may therefore be at particular risk of developing depression. Our study highlights that providers who work with autistic youth in the community should be aware of this risk so they can identify and treat depression when it is present. Future studies should investigate the relationship between depression and TGD identity in autism further, to determine how providers and caregivers can support these youth.</p> <p>Keywords: autism; clinical; diagnoses; gender; topics</p> <hd id="AN0190905316-2">Introduction</hd> <p>"Transgender and gender diverse" (TGD) describes individuals with gender identities that differ from that socially attributed to their sex assigned at birth (see [<reflink idref="bib7" id="ref1">7</reflink>], for a detailed discussion). Research in recent years has established that autism and TGD identity may co-occur at higher-than-expected rates.</p> <p>Parents of autistic children, for example, are more likely than parents of typically developing controls to endorse a Child Behavior Checklist (CBCL) item indicating that their child "wishes to be the opposite gender" ([<reflink idref="bib50" id="ref2">50</reflink>]). Children with autism diagnoses are more likely than typically developing children to have a "gender dysphoria" diagnosis ([<reflink idref="bib19" id="ref3">19</reflink>]). Autistic adults are more likely than the general population to have trait-level gender dysphoria ([<reflink idref="bib16" id="ref4">16</reflink>]). Finally, several studies of TGD individuals have reported that trait- and diagnosis-level autism are both overrepresented ([<reflink idref="bib8" id="ref5">8</reflink>]; [<reflink idref="bib11" id="ref6">11</reflink>]; [<reflink idref="bib21" id="ref7">21</reflink>]; [<reflink idref="bib38" id="ref8">38</reflink>]; [<reflink idref="bib39" id="ref9">39</reflink>]; [<reflink idref="bib49" id="ref10">49</reflink>]; [<reflink idref="bib58" id="ref11">58</reflink>]), although methodological heterogeneity across studies make prevalence difficult to estimate ([<reflink idref="bib32" id="ref12">32</reflink>]).</p> <p>While there is a known increase of mental health conditions in TGD young people ([<reflink idref="bib52" id="ref13">52</reflink>]) as well as autistic individuals ([<reflink idref="bib34" id="ref14">34</reflink>]) independently, the implications of the TGD/autism intersection are just beginning to be understood. TGD individuals, like other sexual minorities, must contend with minority stress, a constellation of interrelated social and cultural factors that stigma, prejudice, discrimination, and rejection, and that can give rise to mental health problems ([<reflink idref="bib31" id="ref15">31</reflink>]). Intuitively, the social and communication difficulties associated with autism could exacerbate this stress ([<reflink idref="bib15" id="ref16">15</reflink>]). Given this, a full understanding of the risk of developing mental health conditions in individuals with autism spectrum disorder who identify as TGD is imperative. Characterization of risk can lead to increased awareness, fewer missed psychiatric diagnoses, and increased access to treatment and support.</p> <p>However, few studies to date have focused on capturing the prevalence or risk of developing psychiatric symptoms in the TGD autistic population. A 2020 study published results of an online survey suggesting anxiety and depression rates were higher in TGD-identifying individuals who were also autistic compared to TGD-identifying individuals who were not autistic or autistic individuals who did not identify as TGD ([<reflink idref="bib37" id="ref17">37</reflink>]). However, the data were self-reported and a professional diagnosis of autism was not required, which may have contributed to an inaccurate rate of autistic traits in the study group. Nevertheless, a subsequent study in 2021 with a robust procedure of ascertaining and confirming autism diagnoses found higher rates of internalizing symptoms in TGD autistic adolescents compared to non-TGD autistic and non-autistic TGD groups ([<reflink idref="bib48" id="ref18">48</reflink>]). While this article examined the association of autism and transgender status with internalizing symptoms and suicidality, it did not capture the prevalence of mental health conditions (e.g. depression, anxiety, psychosis) in TGD autistic individuals. Similarly, a case-control study in 2018 found that individuals with autism who also identified as TGD had higher rates of symptoms associated with disorder in the <emph>Diagnostic and Statistical Manual of Mental Disorders</emph> (5th ed.; DSM-5), but did not present the rate of any specific disorder compared to non-TGD autistic individuals ([<reflink idref="bib55" id="ref19">55</reflink>]).</p> <p>No study has yet confirmed the relationship between TGD identity and mental health diagnoses among autistic adolescents, nor has any study yet examined the relative effect of TGD identity on depression, anxiety, or other mental health diagnoses in autistic adolescents as compared to other known risk factors. This is a significant gap in the literature given that adolescence is a critical developmental period in both the formation of gender identity and in the development of mental health problems ([<reflink idref="bib23" id="ref20">23</reflink>]; [<reflink idref="bib46" id="ref21">46</reflink>]). In the work reported here, we saw an opportunity to simultaneously address both of these gaps in the literature by examining data from the nationwide Simons Powering Autism Research for Knowledge (SPARK) cohort. We reasoned that if associations reported in existing studies were also seen in SPARK despite its size and heterogeneity, then this would more strongly establish their robustness. The size of SPARK would also give us the statistical power to examine TGD identity in the context of known risk factors for mental health diagnoses.</p> <p>Given the existing findings described above, we hypothesized that (<reflink idref="bib1" id="ref22">1</reflink>) depression and anxiety, the two major "internalizing" mental health diagnosis, would both be significantly more common in TGD autistic adolescents than their non-TGD counterparts, and that (<reflink idref="bib2" id="ref23">2</reflink>) TGD identity would be at least as strong a predictor of depression and anxiety as established risk factors such as family history.</p> <hd id="AN0190905316-3">Method</hd> <p></p> <hd id="AN0190905316-4">Study sample</hd> <p>Our study leveraged the SPARK study cohort ([<reflink idref="bib12" id="ref24">12</reflink>]). SPARK has recruited, and continues to recruit, participants from across the United States with a professional diagnosis of autism spectrum disorder. This includes anyone with a DSM-5 diagnosis of autism spectrum disorder and/or a <emph>Diagnostic and Statistical Manual of Mental Disorders</emph> (4th ed.; DSM-IV) diagnosis of Asperger disorder, autistic disorder, Rett syndrome, childhood disintegrative disorder, or pervasive developmental disorder not otherwise specified. Clinical sites are the principal recruitment arm for SPARK, alongside a supplemental social media strategy. All SPARK sites have oversight by, and approval from, a central institutional review board. Clinical information for SPARK is collected via an online survey completed by caregivers (for minors and non-independent adults) or participants (for independent adults). All participants (or, for minors, their parents) provide informed written consent.</p> <p>We analyzed SPARK's version 8.1 data release from 3 June 2022, which included 117,203 individuals reporting a professional diagnosis of autism spectrum disorder ([<reflink idref="bib45" id="ref25">45</reflink>]) who enrolled in SPARK between SPARK's 2016 launch and 2022. Given our focus on adolescents and given systematic differences in how SPARK data were collected for minors and for most adults (i.e. parent report vs self-report), we focused our primary analysis on SPARK participants who were at least 13 but less than 18 years of age, with a separate secondary analysis conducted in young adult participants aged 18 to 25. We also excluded participants with missing data for any of the following key covariates we planned to include in all analyses: age at registration, language ability, or level of cognition. This yielded final sample sizes of 9027 autistic adolescents in the primary group and 9326 autistic young adults in the secondary group. We conducted a series of logistic regressions in both the adolescent and young adult groups to examine whether missingness in age, language ability, or level of cognition were associated with any observed variables included in our analyses. We did not find any significant associations. This supports the assumption that there is no systematic difference between participants with and without complete data, justifying our complete-case analysis approach.</p> <hd id="AN0190905316-5">Ascertainment of transgender and gender-diverse identity</hd> <p>All study participants had data for both sex assigned at birth and gender. "Sex assigned at birth" was a variable with two possible values: "male" and "female." "Gender" had three possible values: "male," "female," and "other." These values were parent-reported for all individuals in the adolescent group and for about 40% of individuals (<emph>n</emph> = 3748) in the young adult group. We defined TGD participants as those in whom reported gender at the time of evaluation did not match reported sex assigned at birth. Under this definition, we ascertained that 36 individuals in the primary sample were TGD.</p> <hd id="AN0190905316-6">Notable variables of interest</hd> <p>We included the following notable variables of interest in our analyses:</p> <p></p> <ulist> <item> <bold> Mental health diagnoses: </bold> Depression, anxiety, obsessive-compulsive disorder (OCD), tic disorder, attention-deficit hyperactivity disorder (ADHD), bipolar disorder, and psychotic disorder were each assigned a value indicating either the presence or absence of a history of that condition. No participant in the study sample had a diagnosis of a substance use disorder, personality disorder, or eating disorder. Diagnoses were parent- or self-reported and were elicited with the question "please select all medical conditions that your child has been diagnosed with by a professional" ("that you have" for participants self-reporting).</item> <p></p> <item> <bold> Family history of mental health diagnoses: </bold> For each participant, we derived variables indicating the presence or absence of a family history of individual mental health diagnoses by ascertaining whether at least one parent, sibling, or half-sibling reported a history of that diagnosis.</item> <p></p> <item> <bold> Language ability </bold> : For each participant, we derived a binary variable indicating whether they were nonverbal or had any verbal ability (i.e. able to use single words meaningfully or higher).</item> <p></p> <item> <bold> Level of cognition: </bold> For each participant, we derived a binary variable indicating whether they had likely cognitive impairment as predicted by a machine learning model using several parent-reported datapoints. The development and features of this machine learning model have been described elsewhere ([<reflink idref="bib44" id="ref26">44</reflink>]), but briefly the model has a sensitivity of 0.772 and specificity of 0.803 to predict a full-scale IQ of less than 80.</item> <p></p> <item> <bold> Race and ethnicity: </bold> Most participants in the primary study sample were white (71%) with a substantial Black (6.9%) minority, so we represented race with two binary variables to indicate white versus non-white and Black versus non-Black. An additional binary variable indicated Hispanic versus non-Hispanic ethnicity.</item> <p></p> <item> <bold> Area deprivation index: </bold> The SPARK dataset contains national and state percentile rankings of socioeconomic disadvantage by neighborhood that are generated based on self-report of physical address and the publicly available area deprivation index (ADI) ([<reflink idref="bib25" id="ref27">25</reflink>]). However, in the primary sample examined for this study, ADI percentiles were absent or not calculable for 5297 participants due to low population, minimal housing, or other key missing variables. Thus, although we provide summary ADI statistics here, we did not include the ADI as a covariate in our regression models.</item> </ulist> <hd id="AN0190905316-7">Analytic approach</hd> <p>We devised the following a priori statistical approach: First, we planned to identify mental health diagnoses that were more common in TGD autistic adolescents than non-TGD autistic adolescents. To do this, we estimated a series of univariate binomial logistic regression models in which TGD identity predicted each of the following diagnoses: depression, anxiety, OCD, tic disorder, ADHD, bipolar disorder, and psychotic disorder. Given the multiple simultaneous comparisons made, we adjusted <emph>p</emph> values for all models using the Benjamini–Hochberg method.</p> <p>Next, for each diagnosis that TGD identity significantly predicted after adjustment, we planned to estimate a multiple logistic regression model that would include TGD identity along with covariates and known risk factors for that diagnosis as predictors. These known risk factors would be chosen in advance based on availability in the SPARK dataset and clinical relevance. We planned to include these variables using a simultaneous forced-entry strategy ([<reflink idref="bib36" id="ref28">36</reflink>]). To ascertain the robustness of these multiple regression models, we planned to rule out collinearity using the variance inflation factor metric.</p> <p>We rescaled age, the only continuous non-binary variable included in our models, by dividing it by two standard deviations. This method of scaling has been recommended when including continuous variables alongside binary variables in regression models, as the magnitude of the transformed coefficients can be compared directly with the coefficients for binary predictors ([<reflink idref="bib14" id="ref29">14</reflink>]; [<reflink idref="bib43" id="ref30">43</reflink>]).</p> <p>We examined the same diagnoses, covariates, and risk factors in both the study's primary sample of adolescents and the secondary sample of young adults.</p> <hd id="AN0190905316-8">Software and data</hd> <p>We conducted analyses in R 4.4.1. Scripts to reproduce the results reported here are available from the authors at https://github.com/amandeepjutla/2023-tgd-asd.</p> <p>The SPARK dataset is available to interested researchers through the Simons Foundation at https://<ulink href="http://www.sfari.org/resource/sfari-base/">www.sfari.org/resource/sfari-base/</ulink>.</p> <hd id="AN0190905316-9">Results</hd> <p></p> <hd id="AN0190905316-10">Basic characteristics of the primary study sample of autistic adolescents</hd> <p>Table 1 summarizes basic characteristics of the study's primary sample of 9027 autistic adolescents, and the mean age was 15.08 (<emph>SD</emph> = 1.38). Consistent with the demographics of autism, most participants (<emph>n</emph> = 7072, 78%) were assigned male at birth. Most (<emph>n</emph> = 6396, <emph>n</emph> = 71%) participants were white, though the sample also included many Black (<emph>n</emph> = 623, 6.9%) and Hispanic (<emph>n</emph> = 1058, 12%) participants. For the 3730 participants with ADI data, the mean ADI (national percentile) was 47.30 (<emph>SD</emph> = 25.83). A minority of participants (<emph>n</emph> = 479, 5.3%) were nonverbal. A majority (<emph>n</emph> = 5396, 60%) had likely cognitive impairment (IQ < 80), which is essentially consistent with the known demographics of autism, in which 61.4% of affected US youth have an IQ < 85 ([<reflink idref="bib27" id="ref31">27</reflink>]). ADHD (<emph>n</emph> = 4676, 52%), anxiety (<emph>n</emph> = 3139, 35%), depression (<emph>n</emph> = 1689, 19%) and OCD (<emph>n</emph> = 1394; 15%) were the most common mental health diagnoses in the study sample, with psychotic disorder (<emph>n</emph> = 177, 2.0%), bipolar disorder (<emph>n</emph> = 398, 4.4%), and tic disorder (<emph>n</emph> = 506, 5.6%) relatively less prevalent. All variables were compared between TGD and non-TGD patients with unadjusted and adjusted <emph>p</emph> values presented. The Wilcoxon rank-sum test was used for continuous variables. Pearson's chi-square test was used for binary variables, unless a frequency in any cell of a contingency table was less than 5, in which case Fisher's exact test was used.</p> <p>Table 1. Characteristics of autistic adolescents in SPARK aged 13 to 17.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left" rowspan="2">Characteristic</th><th align="left" rowspan="2">Overall, <italic>N</italic> = 9027<xref ref-type="table-fn" rid="tfn1">a</xref></th><th align="left" colspan="2">Transgender and gender diverse</th><th align="left" rowspan="2"><italic>p</italic><xref ref-type="table-fn" rid="tfn1">b</xref></th><th align="left" rowspan="2">BH adjusted <italic>p</italic><xref ref-type="table-fn" rid="tfn1">c</xref></th></tr><tr><th align="left">No, <italic>N</italic> = 8991<xref ref-type="table-fn" rid="tfn1">a</xref></th><th align="left">Yes, <italic>N</italic> = 36<xref ref-type="table-fn" rid="tfn1">a</xref></th></tr></thead><tbody><tr><td colspan="6">Demographics</td></tr><tr><td> Age (in years)</td><td>15.08 (1.38)</td><td>15.08 (1.38)</td><td>15.22 (1.36)</td><td>0.53</td><td>>0.99</td></tr><tr><td> Male sex at birth</td><td>7072 (78%)</td><td>7062 (79%)</td><td>10 (28%)</td><td><0.001</td><td><0.001</td></tr><tr><td> White race</td><td>6396 (71%)</td><td>6365 (71%)</td><td>31 (86%)</td><td>0.044</td><td>0.16</td></tr><tr><td> Black race</td><td>623 (6.9%)</td><td>621 (6.9%)</td><td>2 (5.6%)</td><td>>0.99</td><td>>0.99</td></tr><tr><td> Asian race</td><td>267 (3.0%)</td><td>267 (3.0%)</td><td>0 (0%)</td><td>0.63</td><td>>0.99</td></tr><tr><td> Native American race</td><td>290 (3.2%)</td><td>288 (3.2%)</td><td>2 (5.6%)</td><td>0.32</td><td>0.72</td></tr><tr><td> Native Hawaiian race</td><td>57 (0.6%)</td><td>57 (0.6%)</td><td>0 (0%)</td><td>>0.99</td><td>>0.99</td></tr><tr><td> Other race</td><td>380 (4.2%)</td><td>377 (4.2%)</td><td>3 (8.3%)</td><td>0.19</td><td>0.48</td></tr><tr><td> More than one race</td><td>664 (7.4%)</td><td>662 (7.4%)</td><td>2 (5.6%)</td><td>>0.99</td><td>>0.99</td></tr><tr><td> Hispanic ethnicity</td><td>1058 (12%)</td><td>1051 (12%)</td><td>7 (19%)</td><td>0.19</td><td>0.40</td></tr><tr><td> Area Deprivation Index<xref ref-type="table-fn" rid="tfn1">d</xref></td><td>47.30 (25.83)</td><td>47.29 (25.83)</td><td>48.85 (26.59)</td><td>0.81</td><td>>0.99</td></tr><tr><td colspan="6">Cognitive characteristics</td></tr><tr><td> Nonverbal</td><td>479 (5.3%)</td><td>478 (5.3%)</td><td>1 (2.8%)</td><td>>0.99</td><td>>0.99</td></tr><tr><td> Cognitive impairment<xref ref-type="table-fn" rid="tfn1">e</xref></td><td>5396 (60%)</td><td>5373 (60%)</td><td>23 (64%)</td><td>0.61</td><td>>0.99</td></tr><tr><td colspan="6">Comorbid psychiatric condition</td></tr><tr><td> Anxiety</td><td>3139 (35%)</td><td>3120 (35%)</td><td>19 (53%)</td><td>0.023</td><td>0.12</td></tr><tr><td> Depression</td><td>1689 (19%)</td><td>1670 (19%)</td><td>19 (53%)</td><td><0.001</td><td><0.001</td></tr><tr><td> OCD</td><td>1394 (15%)</td><td>1385 (15%)</td><td>9 (25%)</td><td>0.11</td><td>0.34</td></tr><tr><td> Psychotic disorder</td><td>177 (2.0%)</td><td>175 (1.9%)</td><td>2 (5.6%)</td><td>0.16</td><td>0.39</td></tr><tr><td> Bipolar disorder</td><td>398 (4.4%)</td><td>397 (4.4%)</td><td>1 (2.8%)</td><td>>0.99</td><td>>0.99</td></tr><tr><td> Tic disorders</td><td>506 (5.6%)</td><td>504 (5.6%)</td><td>2 (5.6%)</td><td>>0.99</td><td>>0.99</td></tr><tr><td> ADHD</td><td>4676 (52%)</td><td>4658 (52%)</td><td>18 (50%)</td><td>0.83</td><td>>0.99</td></tr></tbody></table> </ephtml> </p> <p>1 Mean (<emph>SD</emph>); <emph>n</emph> (%). <sups>b</sups> Wilcoxon rank sum test used for continuous variables. Pearson's chi-square test or Fisher's exact test for binary variables. <sups>c</sups> Benjamini and Hochberg correction for multiple testing. <sups>d</sups> National percentile. Number of non-numerical values excluded: 5297. Non-numerical values included: "NA": not applicable; "PH": suppression due to low population and/or housing; "GQ": suppression due to a high group quarters population; "PH-GQ": suppression due to both types of suppression criteria and "KVM": designates block groups without an ADI due to Key Missing Variables, stemming from missing data in the source ACS data. <sups>e</sups> As predicted by machine learning.</p> <p>Basic characteristics of the 36 TGD participants were similar to the 9027 non-TGD participants, with one notable exception: only 28% (<emph>n</emph> = 10) of TGD participants were assigned male sex at birth, as compared with 79% (<emph>n</emph> = 7062, adjusted <emph>p</emph> < 0.001) of non-TGD participants. Of the 36 TGD adolescents, 14 (39%) had a gender identity of "other," 15% were transmasculine (i.e. their gender identity was male and their sex assignment at birth was female), and 7 (19%) were transfeminine (their gender identity was female and their sex assignment at birth was male).</p> <hd id="AN0190905316-11">Univariate models examining TGD identity as a predictor of mental health diagnoses in autisti...</hd> <p>In univariate models estimated across mental health diagnoses (Table 2), TGD identity was a significant predictor of depression (odds ratio (OR) = 4.90, 95% confidence interval (CI) = 2.54–9.54, <emph>p</emph> = 2.09 × 10<sups>−6</sups>) and anxiety (OR: 2.10, 95% CI: 1.09–4.09, <emph>p</emph> = 0.026). After correction for multiple comparisons, depression (adjusted <emph>p</emph> = 1.46 × 10<sups>−5</sups>) but not anxiety (adjusted <emph>p</emph> = 0.092) remained significant. TGD identity did not significantly predict any other mental health diagnoses.</p> <p>Table 2. TGD identity as predictor of co-occurring psychiatric disorders in autistic adolescents in SPARK aged 13 to 17.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left">Model</th><th align="left">Odds ratio</th><th align="left">95% CI</th><th align="left"><italic>p</italic></th><th align="left">BH adjusted <italic>p</italic></th></tr></thead><tbody><tr><td><bold>Depression</bold></td><td><bold>4.90</bold></td><td><bold>[2.54, 9.54]</bold></td><td><bold>2.09 × 10</bold>−6</td><td><bold>1.46 × 10</bold>−5<xref ref-type="table-fn" rid="tfn3">***</xref></td></tr><tr><td>Anxiety</td><td>2.10</td><td>[1.09, 4.09]</td><td>0.026</td><td>0.092</td></tr><tr><td>OCD</td><td>1.83</td><td>[0.81, 3.75]</td><td>0.117</td><td>0.241</td></tr><tr><td>Psychotic disorders</td><td>2.96</td><td>[0.48, 9.83]</td><td>0.138</td><td>0.241</td></tr><tr><td>Bipolar disorder</td><td>0.62</td><td>[0.03, 2.87]</td><td>0.636</td><td>0.891</td></tr><tr><td>ADHD</td><td>0.93</td><td>[0.48, 1.8]</td><td>0.829</td><td>0.967</td></tr><tr><td>Tic disorders</td><td>0.99</td><td>[0.16, 3.26]</td><td>0.99</td><td>0.99</td></tr></tbody></table> </ephtml> </p> <ulist> <item>2 BH: Benjamini–Hochberg; CI: confidence interval; OCD: obsessive-compulsive disorder; ADHD: attention-deficit/hyperactivity disorder. Bold indicates any <emph>p</emph> value below the 0.05 threshold.</item> <item>3 <emph>p</emph> < 0.05. **<emph>p</emph> < 0.01. **<emph>p</emph> < 0.001.</item> </ulist> <hd id="AN0190905316-12">Multiple regression model comparing TGD identity in autistic adolescents with other known pre...</hd> <p>Our multiple regression model (Table 3, Figure 1) included several known depression risk factors. These included the presence of anxiety, oppositional defiant disorder (ODD), sleep disturbances, ADHD, cognitive impairment, lack of verbal language ability (i.e. nonverbal), learning disability, family history of depression, family history of anxiety, TGD identity, as well as demographic factors known to influence the presentation of depression, including sex assigned at birth, age, race, and ethnicity ([<reflink idref="bib2" id="ref32">2</reflink>]; [<reflink idref="bib4" id="ref33">4</reflink>]; [<reflink idref="bib13" id="ref34">13</reflink>]; [<reflink idref="bib18" id="ref35">18</reflink>]; [<reflink idref="bib24" id="ref36">24</reflink>]; [<reflink idref="bib26" id="ref37">26</reflink>]; [<reflink idref="bib29" id="ref38">29</reflink>]; [<reflink idref="bib30" id="ref39">30</reflink>]; [<reflink idref="bib33" id="ref40">33</reflink>]; [<reflink idref="bib37" id="ref41">37</reflink>]; [<reflink idref="bib53" id="ref42">53</reflink>]).</p> <p>Table 3. Predictors of depression in autistic adolescents in SPARK aged 13 to 17.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left">Predictor</th><th align="left">Odds ratio</th><th align="left">95% CI</th><th align="left"><italic>p</italic></th><th align="left">BH adjusted <italic>p</italic></th></tr></thead><tbody><tr><td><bold>Anxiety</bold></td><td>4.68</td><td>[4.13, 5.32]</td><td>1.02 × 10−125</td><td>1.53 × 10−124<xref ref-type="table-fn" rid="tfn5">***</xref></td></tr><tr><td><bold>Transgender and gender diverse</bold></td><td>4.01</td><td>[1.87, 8.67]</td><td>3.57 × 10−4</td><td>5.94 × 10−4<xref ref-type="table-fn" rid="tfn5">***</xref></td></tr><tr><td><bold>Depression family history</bold></td><td>2.77</td><td>[2.44, 3.15]</td><td>3.43 × 10−54</td><td>2.57 × 10−53<xref ref-type="table-fn" rid="tfn5">***</xref></td></tr><tr><td><bold>ODD</bold></td><td>2.26</td><td>[1.93, 2.64]</td><td>1.71 × 10−24</td><td>8.57 × 10−24<xref ref-type="table-fn" rid="tfn5">***</xref></td></tr><tr><td><bold>Sleep disturbance</bold></td><td>1.62</td><td>[1.44, 1.84]</td><td>1.23 × 10−14</td><td>4.63 × 10−14<xref ref-type="table-fn" rid="tfn5">***</xref></td></tr><tr><td><bold>Female sex at birth</bold></td><td>1.57</td><td>[1.37, 1.80]</td><td>7.73 × 10−11</td><td>2.32 × 10−10<xref ref-type="table-fn" rid="tfn5">***</xref></td></tr><tr><td><bold>ADHD</bold></td><td>1.34</td><td>[1.18, 1.53]</td><td>1.22 × 10−5</td><td>2.29 × 10−5<xref ref-type="table-fn" rid="tfn5">***</xref></td></tr><tr><td><bold>Age (in years)</bold></td><td>1.33</td><td>[1.18, 1.5]</td><td>2.10 × 10−6</td><td>4.50 × 10−6<xref ref-type="table-fn" rid="tfn5">***</xref></td></tr><tr><td>White race</td><td>1.03</td><td>[0.89, 1.19]</td><td>0.698</td><td>0.698</td></tr><tr><td>Anxiety family history</td><td>0.95</td><td>[0.83, 1.09]</td><td>0.458</td><td>0.522</td></tr><tr><td>Black race</td><td>0.91</td><td>[0.7, 1.17]</td><td>0.487</td><td>0.522</td></tr><tr><td>Hispanic ethnicity</td><td>0.91</td><td>[0.74, 1.1]</td><td>0.319</td><td>0.399</td></tr><tr><td>Cognitive impairment</td><td>0.89</td><td>[0.79, 1]</td><td>0.0576</td><td>0.0785</td></tr><tr><td><bold>Learning disability</bold></td><td><bold>0.81</bold></td><td><bold>[0.71, 0.93]</bold></td><td><bold>0.00176</bold></td><td>0.00264<xref ref-type="table-fn" rid="tfn5">**</xref></td></tr><tr><td><bold>Nonverbal</bold></td><td><bold>0.30</bold></td><td><bold>[0.17, 0.47]</bold></td><td><bold>1.58 × 10</bold>−6</td><td><bold>3.96 × 10</bold>−6<xref ref-type="table-fn" rid="tfn5">***</xref></td></tr></tbody></table> </ephtml> </p> <ulist> <item>4 BH: Benjamini–Hochberg; CI: confidence interval; OCD: obsessive-compulsive disorder; ADHD: attention-deficit/hyperactivity disorder. Bold indicates any <emph>p</emph> value below the 0.05 threshold.</item> <item>5 <emph>p</emph> < 0.05. **<emph>p</emph> < 0.01. ***<emph>p</emph> < 0.001.</item> </ulist> <p>Graph: Figure 1. Predictors of depression in autistic adolescents aged 13 to 17.</p> <p>TGD identity (OR: 4.01, 95% CI: 1.87–8.67, <emph>p</emph> = 5.94 × 10<sups>−4</sups>) predicted depression at least as strongly as anxiety (OR: 4.68, 95% CI: 4.13–5.32, <emph>p</emph> = 1.53 × 10<sups>−124</sups>), family history of depression (OR: 2.77, 95% CI: 2.44–3.15, <emph>p</emph> = 2.57 × 10<sups>−53</sups>) or ODD (OR: 2.26, 95% CI: 1.93–2.64, <emph>p</emph> = 8.57 × 10<sups>−24</sups>), and more strongly than sleep disturbance (OR: 1.62, 95% CI: 1.44–1.84, <emph>p</emph> = 4.63 × 10<sups>−14</sups>), female sex assigned at birth (OR: 1.57, 95% CI: 1.37–1.80, 2.32 × 10<sups>−10</sups>), age (OR: 1.33, 95% CI: 1.18–1.50, <emph>p</emph> = 4.50 × 10<sups>−6</sups>), or ADHD (OR: 1.34, 95% CI: 1.18–1.53, <emph>p</emph> = 2.29 × 10<sups>−5</sups>).</p> <p>All variance inflation factor (VIF) values in this model were less than 1.25, suggesting that predictors were not strongly intercorrelated. Family history of anxiety (1.21), family history of depression (1.17), and ADHD history (1.13) were associated with the highest VIF values. In follow-up sensitivity analyses that excluded these predictors, as well as analyses that excluded cognitive impairment, which despite VIF metrics could logically have overlapped with lack of verbal language ability, TGD remained a strong predictor of depression.</p> <hd id="AN0190905316-13">Exploratory analysis of female sex assigned at birth as predictor of depression within TGD au...</hd> <p>As TGD identity and female sex assigned at birth were both significant positive predictors of a depression diagnosis in the multiple regression model described above, and as a substantial number of TGD adolescents in our sample were assigned female at birth (<emph>n</emph> = 26, 72%), we conducted an exploratory post hoc analysis to investigate whether female sex assigned at birth could be driving the increased risk of depression seen in the TGD group. We did this by estimating a regression model within the primary 13- to 17-year-old group. In this model, TGD identity, female sex assigned at birth, and the interaction of these predictors were included in the model. While TGD identity (OR: 5.00, 95% CI: 1.39–18.00, adjusted <emph>p</emph> = 0.0166) and female sex assigned at birth (OR: 1.72, 95% CI: 1.52–1.93, <emph>p</emph> = 3.13 × 10<sups>−18</sups>) were significant, the interaction term was not (OR: 0.68, 95% CI: 0.15–3.02, <emph>p</emph> = 0.605). This suggests that female assigned sex at birth is not underlying the association of TGD identity with depression.</p> <hd id="AN0190905316-14">Subsample analysis of adolescents matched by age and sex assigned at birth</hd> <p>Uneven sample sizes between comparator groups can lead to issues with power, increase the risk of committing a Type II statistical error, and create challenges with interpretability of results. We therefore conducted a separate secondary analysis to mitigate potential imbalance in our dataset, as there is a far greater number of non-TGD individuals (<emph>n</emph> = 8991) compared to TGD individuals (<emph>n</emph> = 36) in our primary analysis. We repeated the methods of our primary analysis using a subsample of non-TGD individuals who were randomly selected and matched by age and sex assigned at birth to TGD individuals using the nearest neighbor method. TGD to non-TGD participants were matched in a 1:4 ratio, as no additional power is theoretically gained by a higher ratio when matching. After matching, the standardized mean difference for age and sex assigned at birth were both below 0.1, indicating adequate balancing.</p> <p>The resulting non-TGD subsample included 144 participants as well as the 36 TGD participants also included in the primary analysis. Summary statistics are highlighted in Supplemental Table 1, with the average age being 15.22 years (<emph>SD</emph> = 1.35 in non-TGD group and 1.36 in TGD group) and percentage of males being 28% in both groups. Similar to our primary analysis, TGD identity only predicted depression when included in univariate models of mental health diagnoses (Supplemental Table 2). In a multiple regression model comparing TGD identity with other known predictors of depression, TGD identity (OR: 4.99, 95% CI: 1.99–13.27, adjusted <emph>p</emph> = 8.35 × 10<sups>−3</sups>) predicted depression at least as strongly as anxiety (OR: 4.05, 95% CI: 1.77–9.71, adjusted <emph>p</emph> = 1.53 × 10<sups>−124</sups>), similar to our primary findings. No other predictor remained significant after adjusting for multiple comparisons (Supplemental Table 3).</p> <hd id="AN0190905316-15">Secondary analysis of autistic young adults</hd> <p>For our primary analysis, we chose an age range of 13 to 17, as all data for participants from this age group comes from parent report. In contrast, data from SPARK participants aged 18 or older may come from either self- or parent-report, depending on the level of functioning. Given this, we conducted a separate secondary analysis of young adults, defined as those aged 18 to 25. Demographics of this group (Supplemental Table 4) were similar to those of the primary sample. Of 9326 young adult participants, 13 (0.14%) identified as TGD. Of these 13 TGD young adults, 5 (38%) reported a gender identity of "other," 3 (24%) were transmasculine (male gender identity, assigned female at birth), and 5 (38%) were transfeminine (female gender identity, assigned male at birth).</p> <p>Univariate regression models (Supplemental Table 5) suggested that TGD identification continued to be a strong predictor of depression in young adults (OR = 15.16, 95% CI: 4.63–67.65, adjusted <emph>p</emph> = 2.21 × 10<sups>−4</sups>). A follow-up multiple regression model (Supplemental Table 6) included the same predictors as the multiple regression analysis estimated in the primary analysis with the exceptions of cognitive impairment and language level, as data were not available for these variables for those older than 18 years and 21 years, respectively. TGD identification remained a strong predictor of depression in this model (OR = 8.42, 95% CI: 1.84–50.01, adjusted <emph>p</emph> = 0.0133).</p> <p>As with our main sample, we matched TGD individuals by age and sex assigned at birth to a randomly selected subset of non-TGD individuals in a 1:4 ratio, verifying that balancing was adequate by examining the standardized mean differences for age and sex assigned at birth. The matched sample comprised 65 individuals (the 13 TGD young adults and 52 non-TGD comparators) (Supplemental Table 7). The direction and magnitude of results in this matched analysis were consistent with those seen in the full sample. TGD identity significantly predicted depression (OR = 21.4, 95% CI = 5.2–115.64, <emph>p</emph> < 0.001), anxiety (OR = 4.80, 95% CI = 1.37–18.48, <emph>p</emph> < 0.02), and bipolar disorder (OR = 7.5, 95% CI = 1.11–62.88, <emph>p</emph> = 0.04), with depression surviving adjustment for multiple comparisons (Supplemental Table 8). In a multiple regression model comparing known predictors of depression, TGD identity (OR = 20.4, 95% CI = 1.89–457.26, <emph>p</emph> = 0.025) and anxiety were significant (OR = 13.6, 95% CI = 1.92–173.18, <emph>p</emph> = 0.017), though neither survived adjustment for multiple comparisons (Supplemental Table 9).</p> <hd id="AN0190905316-16">Discussion</hd> <p>Our study found an association between TGD identity and a depression diagnosis in a sample of autistic adolescents aged 13 to 17. TGD identity as a predictor was at least as strong as other known risk factors such as anxiety or a family history of depression. Findings were similar in an analysis of a secondary sample of young adults aged 18 to 25.</p> <p>These results are consistent with previous studies that found a greater burden of internalizing symptoms in TGD autistic adolescents than in either non-TGD autistic adolescents or non-autistic TGD adolescents ([<reflink idref="bib48" id="ref43">48</reflink>]; [<reflink idref="bib55" id="ref44">55</reflink>]).</p> <p>It is also consistent with adult findings, including one study that identified a greater prevalence of depression in TGD-identifying adults who are also autistic as compared with both non-autistic TGD-identifying adults and non-TGD autistic adults ([<reflink idref="bib35" id="ref45">35</reflink>]), and a study that found greater anxiety and mood disorders among adults in SPARK ([<reflink idref="bib6" id="ref46">6</reflink>]).</p> <p>The higher rate of depression we identified among TGD autistic adolescents than their non-TGD autistic counterparts may not be surprising. TGD adolescents are known to face inequities across peer and family settings, including pervasive stigma, rejection, and discrimination. These experiences contribute to and perpetuate internalizing symptoms, including those of depression and social marginalization ([<reflink idref="bib7" id="ref47">7</reflink>]). Furthermore, gender dysphoria, or the significant distress stemming from an incongruence between gender identity and physical sex characteristics ([<reflink idref="bib1" id="ref48">1</reflink>]), may itself contribute to psychological distress and symptoms of depression. However, it is important to note that we did not assess gender dysphoria in this study and that an individual with TGD does not necessarily meet the criteria for a gender dysphoria diagnosis.</p> <p>A majority (23 of 36, 64%) of the TGD autistic adolescents we identified also had likely cognitive impairment. Although this proportion is not significantly different from that we observed in the overall sample, it is potentially higher than expected. Cognition and depression in autism are thought to have a complex relationship, and cognitive impairment may be associated with particular clinical profiles of depression ([<reflink idref="bib20" id="ref49">20</reflink>]). Our work therefore raises questions for future studies about possible interrelationships among cognitive impairment and depressive symptoms in the context of TGD identity in autism.</p> <p>We did not find that TGD identity predicted a higher rate of anxiety in our sample. This is somewhat surprising, as it is odds both with the findings of previous research ([<reflink idref="bib48" id="ref50">48</reflink>]), and contrary to our expectation that internalizing symptoms would be increased in TGD autistic adolescents: if depressive symptoms are increased, then why not anxiety? It may be that our inability to detect a relationship is a function of the relatively small sample size of TGD adolescents in our study. The substantial degree of cognitive impairment we observed may also be a partial explanation. Cognitive impairment is notably also thought to potentially overshadow or complicate the ascertainment of anxiety in autistic youth ([<reflink idref="bib22" id="ref51">22</reflink>]), and it may either go undiagnosed or unnoticed by the parent reporting diagnoses.</p> <p>Many more TGD autistic adolescents in our sample were assigned female rather than male at birth. This is consistent with reports in recent years of an overall shift in the assigned sex ratio of TGD adolescents from predominantly male to predominantly female ([<reflink idref="bib10" id="ref52">10</reflink>]; [<reflink idref="bib59" id="ref53">59</reflink>]). This is interesting given that, in our exploratory analysis (see Results, "Exploratory analysis of female sex assigned at birth as predictor of depression within TGD adolescents"), female sex assigned at birth did not explain the association we identified between TGD identity and depression (i.e. both female sex and TGD identity independently predicted depression but the interaction between them was not significant). That we did not find such an association even though trajectories of depressive symptoms in autistic adolescents differ between natal males and natal females ([<reflink idref="bib17" id="ref54">17</reflink>]) underscores the significance of TGD, independent of other factors, as a predictor of depression. The finding is also interesting given evidence that gender expression may differ across autistic girls and autistic boys in nuanced ways, with autistic girls more likely to show diversity in gender expression, with preferences and mannerisms that fall outside typical gender norms ([<reflink idref="bib5" id="ref55">5</reflink>]; [<reflink idref="bib9" id="ref56">9</reflink>]). Autistic boys, however, may be more likely to self-report gender discontent and interest in having another gender identity ([<reflink idref="bib54" id="ref57">54</reflink>]). Future studies may be able to investigate whether autistic TGD individuals are particularly more likely to have been assigned female at birth.</p> <p>We found a much lower rate of TGD identity among autistic adolescents (0.4%) in our sample than might be expected from the literature. Other studies have found that autistic individuals are more than four times as likely as their typically developing counterparts to identify as TGD ([<reflink idref="bib19" id="ref58">19</reflink>]), and that the prevalence of trait or diagnosis-level autism in TGD individuals ranges from 8% to 23% ([<reflink idref="bib8" id="ref59">8</reflink>]; [<reflink idref="bib11" id="ref60">11</reflink>]; [<reflink idref="bib39" id="ref61">39</reflink>]).</p> <p>One possible reason for this discrepancy is that the survey methods used to characterize gender in our sample may have led to under-ascertainment. We inferred TGD identity based on whether reported sex assigned at birth and reported gender were discrepant, but the parent of a TGD adolescent quickly filling out a form could plausibly not have realized what was being asked without a question explicitly asking whether their child has a TGD identity. The "two-step" approach taken in SPARK of asking separately about sex assigned at birth and gender ([<reflink idref="bib3" id="ref62">3</reflink>]; [<reflink idref="bib40" id="ref63">40</reflink>]) alone does not capture the full gender spectrum. Current best practices in gender ascertainment are to use terminology more nuanced and dimensional than "male, "female," and "other." In future studies, including a more robust measure of gender identity could allow more respondents to accurately report their or their child's gender identity, also leading to a higher rate of identification ([<reflink idref="bib41" id="ref64">41</reflink>]; [<reflink idref="bib47" id="ref65">47</reflink>]). The incorporation of items from instruments validated in the autistic population, such as the Gender Self-Report ([<reflink idref="bib51" id="ref66">51</reflink>]), could also be valuable.</p> <p>Another, perhaps even more significant, reason for this discrepancy is that participant gender was parent-reported rather than self-reported for all individuals in our primary sample of adolescents and for many individuals in the sample of young adults we examined in our secondary analysis. This limitation is reflected by the difference between the TGD prevalence we identified and the much higher (16.1%) prevalence identified by Bungert et al. in their study of self-reported data from an older SPARK sample who received a gender-specific survey. Our reliance on both parent report prevented us from identifying TGD adolescents who have not disclosed their gender identity to their parents, or whose parents do not accept or understand their identity, leading to systematic under-ascertainment. Even parents who accept their child's identity may feel wary of disclosing it in the context of a research study given the widespread societal and cultural prejudice and discrimination that TGD individuals face.</p> <p>This limitation of our data may actually serve to highlight the importance of our finding, as it means we found an association with depression even in a group of TGD adolescents with parents who were, by definition, supportive and understanding enough of their identity to report it. It is possible that future studies making use of self-report and more survey options for gender identity could find even higher rates. Such studies might also identify associations with anxiety that we did not: given our reliance on parent report, TGD adolescents in our study by definition are not closeted and have parents at least supportive enough to respect their gender identity, which may make them less likely to be anxious. Study designs that allow autistic youth to self-report their gender identity could help identify the needs and vulnerabilities of TGD adolescents who are largely invisible to studies such as ours.</p> <p>We should note that the relatively small number of TGD participants in our study meant our multiple regression model had fewer than 10 events per variable. This approach aligns with recent methodological advice ([<reflink idref="bib56" id="ref67">56</reflink>]; [<reflink idref="bib57" id="ref68">57</reflink>]) but could nevertheless have created the potential for overfitting. The low VIF values across predictors, indicating limited multicollinearity, make this less likely. In addition, our finding of an association between TGD identity and depression was robust to sensitivity analyses, including an analysis in the adolescent group comparing TGD with matched non-TGD individuals to account for a potentially imbalanced dataset. The direction and magnitude of findings in a similar matched analysis in the young adult group were similarly consistent with the finding of an association between TGD identity and depression.</p> <p>Our study did not examine causality or longitudinal course. Depression and other mental health diagnoses were ascertained based on lifetime diagnoses and therefore could have preceded or followed the emergence or disclosure of TGD identity. TGD is a "predictor" of depression in a statistical, rather than chronological, sense.</p> <p>Finally, we were not able to explore every mental health diagnosis of interest. Notably, we did not have symptom or diagnosis-level data for post-traumatic stress disorder (PTSD). This is an unfortunate limitation given that both autistic individuals ([<reflink idref="bib42" id="ref69">42</reflink>]) and TGD-identifying individuals ([<reflink idref="bib28" id="ref70">28</reflink>]) are, separately, at increased risk of PTSD. We hope that future work will be able to investigate this diagnosis in individuals at the autism and TGD intersection.</p> <p>We also hope that future work can examine the temporal relationship between the onset of mental health diagnoses and the realization or formation of TGD identity. As we only had data for lifetime rather than current mental health diagnoses, we were unable to do this. Data about when diagnoses emerge would allow future studies to ask and answer questions about the extent to which stigma, and rejection mediate the relationship between TGD identity and depression. Our study is one of few to examine the relationship between TGD identity and autism diagnosis in a generally representative sample of autistic adolescents not enriched for gender diversity. Our findings shed light on the mental health challenges that TGD autistic youth may face and highlight the need for clinicians to ensure that they monitor for signs and symptoms of depression in the TGD autistic youth they see.</p> <p>Important questions, however, remain for our group and others to investigate. For example, we did not have data regarding the presence or absence of gender dysphoria, which can contribute to psychological distress among TGD adolescents navigating puberty-related physical changes and psychosocial challenges, but is not always present. In future work, we hope to characterize gender dysphoria and examine it as a mediator of the relationship between TGD identity and depression. We also hope to assess mental health in TGD autistic youth more dimensionally, examining symptoms and symptom clusters in additional to categorical diagnoses. This may help us understand whether TGD autistic youth with significant symptoms are under-diagnosed, or whether particular symptoms of depression or other mental health problems are particularly relevant to this population and worthy of special clinical attention in the context of early identification. Finally, we hope to expand on the cross-sectional analyses described here with longitudinal data so that we can compare trajectories and outcomes of depression in TGD compared to non-TGD autistic adolescents. Continued examination of how, when, and why depression and other mental health problems develop in TGD autistic youth will, we hope, provide the evidence base to catalyze societal and policy-level changes to improve the lives of adolescents who belong to this group.</p> <hd id="AN0190905316-17">Supplemental Material</hd> <p>Graph: Supplemental material, sj-docx-1-aut-10.1177_13623613251396712 for Transgender and gender-diverse autistic adolescents are at elevated risk of depression by Joseph Pereira, Natalia Ramos, LeeAnne Green Snyder, Jeremy Veenstra-VanderWeele and Amandeep Jutla in Autism</p> <p>We would like to thank and acknowledge the important contributions of all families and individuals participating in SPARK.</p> <ref id="AN0190905316-18"> <title> References </title> <blist> <bibl id="bib1" idref="ref22" type="bt">1</bibl> <bibtext> American Psychiatric Association. (2022). 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Archives of Sexual Behavior, 48(7), 1983–1992. https://doi.org/10.1007/s10508-019-01518-8</bibtext> </blist> </ref> <ref id="AN0190905316-19"> <title> Footnotes </title> <blist> <bibtext> Natalia Ramos</bibtext> </blist> <blist> <bibtext>Graph</bibtext> </blist> <blist> <bibtext>https://orcid.org/0000-0001-8688-9426 Amandeep Jutla</bibtext> </blist> <blist> <bibtext>Graph https://orcid.org/0000-0001-5973-9940</bibtext> </blist> <blist> <bibtext> Joseph Pereira: Conceptualization; Formal analysis; Investigation; Methodology; Writing – original draft; Writing – review & editing.Natalia Ramos: Investigation; Methodology; Writing – original draft; Writing – review & editing.LeeAnne Green Snyder: Data curation; Investigation; Methodology; Writing – original draft; Writing – review & editing.Jeremy Veenstra-VanderWeele: Investigation; Methodology; Supervision; Writing – original draft; Writing – review & editing.Amandeep Jutla: Conceptualization; Formal analysis; Investigation; Methodology; Supervision; Writing – original draft; Writing – review & editing.</bibtext> </blist> <blist> <bibtext> The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by National Institute of Mental Health (NIMH) grant #2T32MH016434-41 to Drs Jeremy Veenstra-VanderWeele and Rachel Marsh and by NIMH grant #5K23MH132874-02 to Dr Amandeep Jutla.</bibtext> </blist> <blist> <bibtext> The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Dr Veenstra-VanderWeele has consulted or served on an advisory board for Roche Pharmaceuticals, Novartis, and SynapDx; has received research funding from Roche Pharmaceuticals, Novartis, SynapDx, Seaside Therapeutics, and Forest; and has received an editorial stipend from Springer and Wiley. The other authors report no conflicts of interest.</bibtext> </blist> <blist> <bibtext> SPARK's Community Advisory Council comprises autistic individuals, parents of autistic children, and professionals who work in the autism community from across the United States. This Council provides feedback regarding recruitment, retention, and research conducted by SPARK. The Council was, however, not involved in the development of this analysis of SPARK data.</bibtext> </blist> <blist> <bibtext> The SPARK dataset is available to interested researchers through the Simons Foundation at https://<ulink href="http://www.sfari.org/resource/sfari-base/">www.sfari.org/resource/sfari-base/</ulink>. Scripts to reproduce the results reported here are available from the authors at https://github.com/amandeepjutla/2023-tgd-asd.</bibtext> </blist> <blist> <bibtext> Supplemental material for this article is available online.</bibtext> </blist> </ref> <aug> <p>By Joseph Pereira; Natalia Ramos; LeeAnne Green Snyder; Jeremy Veenstra-VanderWeele and Amandeep Jutla</p> <p>Reported by Author; Author; Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib50" firstref="ref2"></nolink> <nolink nlid="nl2" bibid="bib19" firstref="ref3"></nolink> <nolink nlid="nl3" bibid="bib16" firstref="ref4"></nolink> <nolink nlid="nl4" bibid="bib11" firstref="ref6"></nolink> <nolink nlid="nl5" bibid="bib21" firstref="ref7"></nolink> <nolink nlid="nl6" bibid="bib38" firstref="ref8"></nolink> <nolink nlid="nl7" bibid="bib39" firstref="ref9"></nolink> <nolink nlid="nl8" bibid="bib49" firstref="ref10"></nolink> <nolink nlid="nl9" bibid="bib58" firstref="ref11"></nolink> <nolink nlid="nl10" bibid="bib32" firstref="ref12"></nolink> <nolink nlid="nl11" bibid="bib52" firstref="ref13"></nolink> <nolink nlid="nl12" bibid="bib34" firstref="ref14"></nolink> <nolink nlid="nl13" bibid="bib31" firstref="ref15"></nolink> <nolink nlid="nl14" bibid="bib15" firstref="ref16"></nolink> <nolink nlid="nl15" bibid="bib37" firstref="ref17"></nolink> <nolink nlid="nl16" bibid="bib48" firstref="ref18"></nolink> <nolink nlid="nl17" bibid="bib55" firstref="ref19"></nolink> <nolink nlid="nl18" bibid="bib23" firstref="ref20"></nolink> <nolink nlid="nl19" bibid="bib46" firstref="ref21"></nolink> <nolink nlid="nl20" bibid="bib12" firstref="ref24"></nolink> <nolink nlid="nl21" bibid="bib45" firstref="ref25"></nolink> <nolink nlid="nl22" bibid="bib44" firstref="ref26"></nolink> <nolink nlid="nl23" bibid="bib25" firstref="ref27"></nolink> <nolink nlid="nl24" bibid="bib36" firstref="ref28"></nolink> <nolink nlid="nl25" bibid="bib14" firstref="ref29"></nolink> <nolink nlid="nl26" bibid="bib43" firstref="ref30"></nolink> <nolink nlid="nl27" bibid="bib27" firstref="ref31"></nolink> <nolink nlid="nl28" bibid="bib13" firstref="ref34"></nolink> <nolink nlid="nl29" bibid="bib18" firstref="ref35"></nolink> <nolink nlid="nl30" bibid="bib24" firstref="ref36"></nolink> <nolink nlid="nl31" bibid="bib26" firstref="ref37"></nolink> <nolink nlid="nl32" bibid="bib29" firstref="ref38"></nolink> <nolink nlid="nl33" bibid="bib30" firstref="ref39"></nolink> <nolink nlid="nl34" bibid="bib33" firstref="ref40"></nolink> <nolink nlid="nl35" bibid="bib53" firstref="ref42"></nolink> <nolink nlid="nl36" bibid="bib35" firstref="ref45"></nolink> <nolink nlid="nl37" bibid="bib20" firstref="ref49"></nolink> <nolink nlid="nl38" bibid="bib22" firstref="ref51"></nolink> <nolink nlid="nl39" bibid="bib10" firstref="ref52"></nolink> <nolink nlid="nl40" bibid="bib59" firstref="ref53"></nolink> <nolink nlid="nl41" bibid="bib17" firstref="ref54"></nolink> <nolink nlid="nl42" bibid="bib54" firstref="ref57"></nolink> <nolink nlid="nl43" bibid="bib40" firstref="ref63"></nolink> <nolink nlid="nl44" bibid="bib41" firstref="ref64"></nolink> <nolink nlid="nl45" bibid="bib47" firstref="ref65"></nolink> <nolink nlid="nl46" bibid="bib51" firstref="ref66"></nolink> <nolink nlid="nl47" bibid="bib56" firstref="ref67"></nolink> <nolink nlid="nl48" bibid="bib57" firstref="ref68"></nolink> <nolink nlid="nl49" bibid="bib42" firstref="ref69"></nolink> <nolink nlid="nl50" bibid="bib28" firstref="ref70"></nolink>
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  Data: Transgender and Gender-Diverse Autistic Adolescents Are at Elevated Risk of Depression
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  Data: English
– Name: Author
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  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Joseph+Pereira%22">Joseph Pereira</searchLink><br /><searchLink fieldCode="AR" term="%22Natalia+Ramos%22">Natalia Ramos</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-8688-9426">0000-0001-8688-9426</externalLink>)<br /><searchLink fieldCode="AR" term="%22LeeAnne+Green+Snyder%22">LeeAnne Green Snyder</searchLink><br /><searchLink fieldCode="AR" term="%22Jeremy+Veenstra-VanderWeele%22">Jeremy Veenstra-VanderWeele</searchLink><br /><searchLink fieldCode="AR" term="%22Amandeep+Jutla%22">Amandeep Jutla</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-5973-9940">0000-0001-5973-9940</externalLink>)
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  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Autism%3A+The+International+Journal+of+Research+and+Practice%22"><i>Autism: The International Journal of Research and Practice</i></searchLink>. 2026 30(2):316-328.
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  Label: Availability
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  Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
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  Data: Y
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  Data: 13
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  Label: Publication Date
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  Data: 2026
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  Data: National Institute of Mental Health (NIMH) (DHHS/NIH)
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  Data: 2T32MH0164344<br />5K23MH13287402
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  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Autism+Spectrum+Disorders%22">Autism Spectrum Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Transgender+People%22">Transgender People</searchLink><br /><searchLink fieldCode="DE" term="%22Adolescents%22">Adolescents</searchLink><br /><searchLink fieldCode="DE" term="%22LGBTQ+People%22">LGBTQ People</searchLink><br /><searchLink fieldCode="DE" term="%22At+Risk+Persons%22">At Risk Persons</searchLink><br /><searchLink fieldCode="DE" term="%22Depression+%28Psychology%29%22">Depression (Psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Correlation%22">Correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+Disorders%22">Mental Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Individual+Characteristics%22">Individual Characteristics</searchLink>
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  Label: DOI
  Group: ID
  Data: 10.1177/13623613251396712
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1362-3613<br />1461-7005
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Autistic people are more likely to be transgender and gender diverse than the general population. Furthermore, co-occurring trait-level autism and transgender and gender-diverse identity are associated with symptoms of depression and anxiety, and autistic adolescents who identify as transgender and gender diverse have more internalizing behaviors than both non-transgender and gender-diverse autistic adolescents and non-autistic transgender and gender-diverse adolescents. However, no study has yet examined the extent to which transgender and gender-diverse identity predicts specific co-occurring mental health diagnoses in autistic adolescents. In a sample of 9027 autistic adolescents aged 13 to 17 drawn from the Simons Powering Autism Research for Knowledge cohort, 36 of whom we identified as transgender and gender diverse, we estimated univariate models of transgender and gender-diverse identity as a predictor of individual diagnoses. Depression, but no other diagnosis, remained statistically significant after adjustment for multiple comparisons. In a multiple regression model that incorporated known risk factors for adolescent depression (e.g. language impairment and disturbed sleep), transgender and gender-diverse identity remained a significant predictor (odds ratio: 4.01, 95% confidence interval: 1.87-8.67, p = 5.94 × 10[superscript -4]) with an effect size at least as strong as that of a depression family history. This suggests transgender and gender-diverse autistic adolescents, who often face stigma and discrimination, are particularly vulnerable to depression.
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  Data: 2026
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  Data: EJ1494733
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        Value: 10.1177/13623613251396712
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      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 13
        StartPage: 316
    Subjects:
      – SubjectFull: Autism Spectrum Disorders
        Type: general
      – SubjectFull: Transgender People
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      – SubjectFull: Adolescents
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      – TitleFull: Transgender and Gender-Diverse Autistic Adolescents Are at Elevated Risk of Depression
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