The framework, called PGS-TRI, analyzes “case-parent trios”: a child diagnosed with autism or another condition together with both biological parents. This family-based design gives researchers information that is not available when only the child’s DNA is studied. By comparing the genetic variants a child inherited with the variants present in the parents but not passed down, investigators can estimate whether an association is more likely to reflect a child’s direct genetic susceptibility or an indirect parental influence.

“Traditionally, genetic studies focus on the direct effects of genes passed from parent to child,” Wang said. “However, a child’s health is also shaped by indirect effects—how a parent’s own genetic makeup influences the environment they provide for their child.” A parent’s genetic predisposition to a trait can affect physiology, behavior, health, diet, stress exposure or other aspects of family life, even when the relevant genetic variants are not inherited by the child. These pathways are difficult to measure directly, but family genetic data can provide a statistical route for studying them.

The method builds on polygenic scores, which combine the small effects of many genetic variants across the genome into an estimate of an individual’s inherited predisposition to a disease or trait. Unlike a single-gene test, a polygenic score usually reflects thousands or millions of DNA variants, each contributing a very small amount to overall risk. PGS-TRI extends this approach by modeling the scores of children and both parents simultaneously. This enables researchers to distinguish inherited genetic effects from parental genetic effects that may operate through the prenatal or postnatal environment.

That distinction is especially important in autism research, where risk is influenced by a complex mixture of rare genetic changes, common variants, developmental biology and environmental conditions. No single factor determines whether a child will be autistic, and a polygenic score cannot diagnose autism or predict an individual child’s future with certainty. Instead, such scores are research instruments that can reveal patterns across large populations. By embedding them in a trio-based framework, investigators can ask more precise questions about how risk is transmitted and how family circumstances may interact with inherited biology.

For their initial analysis, the researchers examined more than 18,000 autism case-parent trios drawn from the Simons Foundation Powering Autism Research for Knowledge consortium and the Genes and Environment Autism Research Study. The datasets included families from multiple ancestral backgrounds, allowing the team to test how consistently polygenic scores captured genetic associations across populations. The analysis provided generally reassuring evidence that autism-related polygenic scores reflected direct genetic contributions, while also revealing important differences in their performance among ancestry groups.

Scores were more accurate for families with ancestry from the Americas, Europe and South Asia than for families of African or East Asian ancestry. The researchers attribute much of this gap to the populations historically represented in the large genome-wide association studies used to construct the scores. When discovery datasets contain more individuals from some populations than others, the resulting statistical signals may transfer unevenly across groups. This limitation is not evidence that genetics is inherently more informative for one population; rather, it highlights how unequal representation can reduce the accuracy and usefulness of genomic tools for underrepresented communities.

The findings also generated clues about indirect parental effects. Maternal genetic susceptibility to certain traits, including obesity and some neurocognitive characteristics, was associated with autism risk in children in the study’s analyses. Such results should not be interpreted as proof that a mother’s genes or lifestyle causes autism. Genetic correlations can arise through multiple biological and social pathways, and observational analyses cannot establish that a specific diet, behavior or prenatal exposure is responsible. The value of PGS-TRI is that it offers a framework for testing these possibilities more rigorously in future studies that combine genetic data with detailed clinical and environmental measurements.

The researchers also used the framework to identify the CADM2 gene as a promising target for further investigation. CADM2 has been linked in previous research to behavioral and neurocognitive traits, and the new analysis suggests that it may warrant closer study in relation to autism biology. The finding does not mean that CADM2 is an established cause of autism or that targeting the gene could immediately prevent the condition. Instead, it provides a lead for laboratory and clinical researchers seeking to understand the molecular networks involved in neurodevelopment. Additional studies will be needed to determine whether the association is reproducible, biologically meaningful and therapeutically relevant.

Wang developed PGS-TRI during her postdoctoral training at Johns Hopkins under the supervision of Nilanjan Chatterjee, PhD, whose appointments include the Department of Biostatistics at the Bloomberg School of Public Health and the School of Medicine. The team’s work, published in Nature Genetics, demonstrates how family-based genetic analysis can move beyond a simple comparison of DNA variants and disease status. By combining inherited and non-inherited genetic information, the approach may help clarify the relationship between nature and nurture in autism, developmental disabilities and other complex childhood conditions. The software is publicly available, offering researchers a way to apply the method to new cohorts and improve the representation of diverse populations in genetic studies.

Subject of Research: Genetic and environmental influences on autism risk, polygenic scores, and parent-child genetic effects.

Web References: https://ziqiaow.github.io/PGS.TRI/ ; https://zenodo.org/records/19339894

References: Nature Genetics, DOI: https://doi.org/10.1038/s41588-026-02601-2

Image Credits: Courtesy Wang lab

Keywords: Autism, autism spectrum disorder, genetics, polygenic risk scores, PGS-TRI, parent-child trios, indirect genetic effects, developmental disorders, medical genetics, neurodevelopment, CADM2, personalized medicine, genetic diversity, Nature Genetics

The researchers employed a comprehensive approach, utilizing a substantial dataset that allowed them to analyze various environmental correlates that might influence the lives of autistic individuals. The use of data analytics provided insights that are rarely accessible through traditional qualitative methods, thereby spotlighting previously uncharted territory concerning the intersection of environmental context and autism. This methodological innovation not only sheds light on the issues at hand but also establishes a framework for future research.

One of the key findings of the study highlights the intricate relationship between environmental factors and social interactions among autistic individuals. The researchers discovered that certain environmental conditions, such as the design of community spaces and availability of sensory-friendly environments, significantly affected social engagement. This insight underscores the pressing need for urban planners and community developers to consider the unique sensory and social needs of autistic individuals when designing public spaces.

Moreover, the investigation revealed that access to natural environments contributed positively to the mental well-being of autistic people. Green spaces appear to reduce anxiety levels and promote happier dispositions. This finding presents a strong argument for enhancing access to parks and natural settings, suggesting that even small changes in urban infrastructure can yield substantial benefits for the autistic community. It serves as both a call to action for policymakers and an invitation for communities to take a stand in support of inclusivity.

Another essential aspect of the study was its examination of safe spaces. The research determined that places designated for quiet reflection or retreat could dramatically impact the experiences of autistic individuals in public settings. These results advocate for a systematic incorporation of designated quiet zones in various environments, from schools to shopping centers, allowing for moments of respite that are critical for regulating sensory overload.

The research also emphasizes the importance of community engagement and support systems as vital environmental correlates. The study found that elements of community cohesion contribute significantly to the quality of life for autistic individuals. Positive social networks, whether familial or communal, foster an environment of acceptance and support that can greatly enhance the lived experiences of those on the autism spectrum. Cultivating these networks can lead to more inclusive communities where autistic people feel valued and understood.

Furthermore, the work of de Wit and colleagues raises questions regarding the role of policy in shaping these environments. Legislative measures that prioritize sensory-friendly designs and increased community support for autistic individuals could transform how societies perceive and accommodate neurodiversity. The findings compel stakeholders at all levels to rethink their strategies for fostering environments that genuinely reflect inclusivity.

This research does not exist in a vacuum; it aligns with a broader movement toward recognizing the significance of the environments in which people live. As global awareness of autism continues to grow, the potential for change in public perception and policy is immense. The study contributes a wealth of knowledge to this ongoing dialogue, providing concrete data to support calls for change in both social and physical environments.

Additionally, the research advocates for a multidisciplinary approach in addressing the complexities of autism and environmental impact. By involving experts from various fields—urban planning, psychology, sociology, and public health—future initiatives can be better informed, ensuring comprehensive solutions are proposed and implemented. Integrating diverse perspectives could lead to innovative strategies that enhance the quality of life for autistic individuals on multiple fronts.

Looking ahead, the implications of this research are profound. It not only nurtures the understanding of autism but also promotes a vision of society where neurodiversity is embraced rather than merely tolerated. Each finding serves as an invitation for community members, researchers, and policymakers to engage with the vital goal of creating spaces that celebrate inclusivity. This may lead to a ripple effect, encouraging deeper investigations into other marginalized groups and their environmental needs.

In the realm of academia, this study sets a new standard for future research methodologies. The researchers’ commitment to leveraging data analytics raises the bar for how inquiries into subjective experiences should be conducted. The innovative use of data-driven approaches signals a shift that could reshape research practices across multiple disciplines, ensuring more nuanced understandings of human experiences.

As this vital research fuels further exploration, it calls for continued engagement and dialogue among those impacted by its findings. Researchers, non-profit organizations, and community advocates must work collaboratively to ensure that the data and insights generated through studies like these translate into real-world applications. This collective responsibility will motivate genuine change, benefitting not only autistic individuals but society as a whole.

The overarching theme of this groundbreaking study is clear: environments play a crucial role in shaping the experiences of autistic individuals. By recognizing and acting upon the correlations identified through this research, we can propel society closer to an inclusive future. The journey begins with understanding, followed by action—a mission that requires dedication from all sectors of society.

In conclusion, this extensive investigation by de Wit, Sant’Anna Barbosa Ferriera, and Begeer illuminates the profound impact of environmental factors on the lived experiences of autistic individuals. Through a detailed analysis and data-driven methodologies, the study articulates a compelling narrative advocating for change across community landscapes. It is a clarion call for humanity to build environments where all individuals, irrespective of neurological differences, can thrive.

Subject of Research: Environmental correlates impacting the lived experiences of autistic individuals.

Article Title: A Data-Driven Investigation of Environmental Correlates Associated With the Lived Experience of Autistic People.

Article References:

de Wit, M.M., Sant’Anna Barbosa Ferriera, P., Begeer, S. et al. A Data-Driven Investigation of Environmental Correlates Associated With the Lived Experience of Autistic People.
J Autism Dev Disord (2025). https://doi.org/10.1007/s10803-025-07127-w

Image Credits: AI Generated

DOI: https://doi.org/10.1007/s10803-025-07127-w

Keywords: Autism, Environmental Factors, Neurodiversity, Community Support, Data-Driven Research, Inclusive Design.

Autism spectrum disorder, characterized by challenges in social interaction, communication, and repetitive behaviors, has witnessed a striking surge in diagnosed cases over the past few decades. The newly published research analyzed data spanning multiple continents, encompassing various demographic groups to elucidate how ASD’s prevalence and burden differ regionally and globally. Such a broad and integrative approach is vital to understanding not only the raw numbers but also the underlying causes and disparities linked to this complex neurodevelopmental condition.

What sets this study apart is its utilization of advanced statistical models and epidemiological methodologies that incorporate both genetic predispositions and environmental exposures. By synthesizing data from health registries, surveys, and genetic databases, the researchers were able to highlight significant risk factors that may exacerbate the likelihood of ASD. These factors range from prenatal exposures, such as maternal health and toxin contact, to broader societal influences like urbanization and healthcare accessibility.

One of the most poignant revelations from the study is the interplay between socioeconomic status and ASD diagnosis rates. The research suggests that wealthier regions, often with better healthcare infrastructure and heightened awareness, report higher incidence rates due to improved diagnosis and reporting mechanisms. Conversely, under-resourced regions may face underdiagnosis, leading to underestimated prevalence and unmet care needs. This diagnostic disparity calls for global adjustments in healthcare policy and resource allocation.

Moreover, the study provided compelling evidence supporting the role of environmental pollutants in increasing ASD risk. Exposure to air pollution, heavy metals, and endocrine-disrupting chemicals during critical periods of fetal development appeared strongly correlated with the development of autism spectrum traits. These findings emphasize the urgent need for environmental regulations and public health initiatives targeting pollutant reduction to mitigate ASD incidence.

In addition to environmental factors, the researchers delved into genetic and epigenetic contributions to ASD. While genetic mutations and hereditary susceptibilities are well-established in ASD pathophysiology, this study added nuanced perspectives on how gene-environment interactions shape disease risk. Epigenetic modifications, influenced by maternal nutrition, stress, and toxin exposure, emerged as pivotal modulators that could either amplify or buffer genetic vulnerabilities.

The global scope of this study also underscored significant differences in ASD prevalence across age groups and sexes. Consistent with prior research, males were more frequently diagnosed than females, but the gender gap differed according to geography and diagnostic practices. The variability in early childhood screening programs worldwide further complicated adult ASD prevalence estimates, highlighting a dire need for standardized diagnostic criteria and inclusive screening protocols.

From a societal impact perspective, the research highlighted the substantial economic and caregiving burdens borne by families affected by ASD. In many countries, lack of early intervention programs and educational support limited individuals’ potential for social integration and economic independence. The study advocates for comprehensive public health frameworks that not only facilitate early diagnosis but also incorporate lifelong support services to enhance quality of life.

Technological advancements were also examined as a double-edged sword: while improved neuroimaging and genetic testing technologies have enriched understanding of ASD heterogeneity, disparities in technology access have widened gaps between high- and low-income settings. Bridging this technological divide remains an imperative goal to ensure equitable health outcomes globally.

The article underscores the importance of cross-disciplinary collaborations, merging neuroscience, epidemiology, environmental science, and social policy to tackle ASD comprehensively. This integrative approach is foundational for developing precision medicine strategies tailored to individual risk profiles, thereby optimizing preventive and therapeutic interventions.

Given the trajectory of rising ASD prevalence projected for the coming decades, the researchers emphasize the criticality of proactive investment in research and healthcare infrastructure. Expanding longitudinal cohorts and genetic biobanks, improving data sharing between countries, and enhancing public awareness campaigns are pivotal steps toward curbing this public health challenge.

Importantly, the study calls for heightened attention to prenatal and early-life care, advocating for policies that prioritize maternal health, reduce exposure to environmental toxins, and promote early developmental screening. These preventive measures could substantially diminish ASD risk and improve neurodevelopmental outcomes globally.

The implications of this research ripple beyond scientific communities, touching the lives of millions who navigate life with ASD. It prompts a renewed commitment from governments, healthcare providers, and societies to foster inclusivity, improve access to care, and support ongoing research aimed at unraveling ASD’s multifactorial etiology.

This landmark study stands as a clarion call underscoring that understanding and mitigating autism spectrum disorder requires a global, multifaceted response. As scientific frontiers expand, so too must our collective efforts to create environments where every individual, regardless of neurodevelopmental status, has the opportunity to thrive.

Subject of Research: Autism Spectrum Disorder (ASD), its global prevalence, risk factors, and societal burden.

Article Title: Burden and risk factors of autism spectrum disorder: global study and analysis.

Article References:
Lin, L., Zhang, Y., Zhou, D. et al. Burden and risk factors of autism spectrum disorder: global study and analysis. Pediatr Res (2025). https://doi.org/10.1038/s41390-025-04641-6

Image Credits: AI Generated

DOI: 14 December 2025

Keywords: Autism spectrum disorder, global prevalence, risk factors, environmental exposures, genetic susceptibility, socioeconomics, epidemiology, neurodevelopmental disorders.

Autism spectrum disorder has long been defined by a constellation of behavioral symptoms, including challenges in social communication and repetitive behaviors. However, the heterogeneity in ASD presentations has complicated efforts to pin down consistent biological markers or phenotypic patterns. Traditional studies often rely on relatively small or fragmented datasets, limiting the ability to detect subtle correlations that could reveal deeper insights into the disorder’s etiology. By leveraging a large-scale family-centered dataset, this study overcomes these barriers, enabling the identification of understudied correlations with enhanced statistical power and dimensionality.

At the heart of this research lies the analysis of extensive multigenerational family data, which includes detailed phenotypic records ranging from neurodevelopmental profiles to physical health measures. Such comprehensive data facilitate the disentanglement of heritable traits from environmental influences, allowing the scientists to map how specific phenotypic attributes cluster with autistic traits within familial lineages. The large cohort size further empowers the detection of rare but meaningful trait associations that smaller studies might miss, offering a richer portrait of ASD’s phenotypic landscape.

One of the study’s key revelations is the identification of correlations between autism and certain physical phenotypes often overlooked in diagnostic frameworks. These include subtle anatomical variations and physiological features, which may serve as biomarkers or endophenotypes for ASD. By integrating these phenotypic markers with behavioral assessments, the researchers advocate for a more multidimensional diagnostic approach that could improve early detection and tailor interventions according to individual phenotypic signatures.

Moreover, the integration of genetic data proxies with phenotypic traits was pivotal in their analytical approach. By examining family-based data, the researchers could infer genetic contributions to observed phenotypes, unearthing connections that may reflect underlying genetic architectures influencing both autism and associated traits. This offers fertile ground for future genetic studies aimed at pinpointing causal variants or gene networks implicated in ASD, with the potential to inspire novel therapeutic targets.

The methodology utilized in the study is noteworthy for its sophisticated use of statistical modeling and machine learning techniques. Employing hierarchical models and advanced clustering algorithms, the researchers captured complex, nonlinear relationships between autism phenotypes and additional traits. This cutting-edge analytical framework transcends traditional correlation analyses, facilitating the discovery of intricate phenotypic network patterns that correspond to different autism subtypes or severity levels.

Importantly, the researchers addressed a critical gap in the literature regarding phenotype diversity across familial samples. They found that certain phenotypic attributes associated with autism did not manifest uniformly among affected family members, highlighting the variable expressivity and penetrance of these traits. This variability emphasizes the necessity of personalized approaches in both clinical research and patient care, as one-size-fits-all models fail to capture the disorder’s heterogeneity.

Another crucial aspect uncovered by the study is the relationship between autism and phenotypes related to co-occurring conditions. Many individuals with autism exhibit comorbidities such as anxiety, gastrointestinal issues, or immune dysregulation, but these associations have been understudied in family-based contexts with integrative phenotyping. The findings suggest that these co-occurring phenotypes also aggregate within families, strengthening the hypothesis of shared genetic or environmental etiologies that span multiple domains of health beyond core autism symptoms.

This family dataset approach also facilitated unprecedented analyses of developmental trajectories. Tracking phenotypic changes across age groups within families, the study revealed patterns of phenotypic stability and evolution, illuminating critical windows during which certain traits emerge or intensify. Such longitudinal insights are invaluable for designing age-appropriate interventions and for understanding the dynamic nature of autism manifestations over the lifespan.

Equally notable is the attention paid to sex differences in phenotypic correlations. ASD is known to present differently between males and females, yet the phenotypic nuances underpinning these differences remain incompletely characterized. By dissecting sex-specific patterns of trait clustering within families, the study contributes to unraveling the biological and possibly social factors driving divergent expression of ASD, which could guide gender-sensitive diagnostic and treatment strategies.

The study’s implications extend into the realm of precision medicine. By detailing understudied correlations and complex phenotypic networks, it lays the groundwork for biomarker discovery and stratified patient profiling. These breakthroughs can pave the way for targeted therapies tailored to distinct autism subtypes, moving the field closer to interventions that address the specific needs of each individual rather than relying on broad-brush approaches.

Complex disorders like autism have always challenged researchers due to multifactorial etiologies that span genes, environment, and development. By capitalizing on a uniquely large and richly phenotyped family cohort, this research delivers a compelling model for future investigations into other neurodevelopmental and psychiatric conditions. The dataset and analytical strategies employed set a new gold standard for integrating phenotypic diversity within familial and genetic contexts.

Future research avenues emerging from these findings include deeper investigations into the molecular and cellular correlates of identified phenotypic traits. Integrating multi-omics data—such as genomics, transcriptomics, and proteomics—with the detailed family phenotyping could unveil mechanistic insights into how certain phenotypes arise in the context of autism. Additionally, expanding the dataset to include environmental exposure data may unravel gene-environment interplay in shaping phenotypic diversity.

Challenges remain, particularly related to data harmonization across diverse populations and phenotyping protocols. Expanding the representativeness of such family cohorts to include underrepresented ethnicities and socio-economic backgrounds is essential to ensure the generalizability of findings. Furthermore, ethical considerations around data privacy and the use of genetic and phenotypic data in families will require careful stewardship as research advances.

Overall, this innovative research marks a significant leap forward in autism science by highlighting the intricate and understudied correlations between autism and a broad spectrum of phenotypic attributes within families. Its comprehensive approach, integrating large-scale, multigenerational phenotypic data with advanced analytics, not only deepens our understanding of autism’s multifaceted nature but also charts a promising path toward more individualized and effective clinical care. As the field moves forward, such integrative family-based studies are poised to become indispensable tools in unraveling the complexities of neurodevelopmental disorders.

Subject of Research: Autism spectrum disorder and its understudied correlations with phenotypic attributes in a large family dataset

Article Title: Identifying understudied correlations between autism & phenotypic attributes in a large family dataset

Article References:
McNealis, M., Kent, J., Paskov, K. et al. Identifying understudied correlations between autism & phenotypic attributes in a large family dataset.
BMC Psychol 13, 561 (2025). https://doi.org/10.1186/s40359-025-02739-4

Image Credits: AI Generated

For more than three decades, the National Institutes of Health (NIH) and associated federal bodies have funneled considerable resources into autism spectrum disorder (ASD) research. This long-term investment has yielded profound insights into the genetic, neurological, and environmental factors contributing to autism, confirming the disorder’s complexity and heterogeneity. The coalition’s members highlight key milestones in scientific discovery, including identification of hundreds of genetic variants associated with autism risk, elucidation of neurodevelopmental pathways, and an increasingly nuanced understanding of how gene-environment interactions modulate expression.

Importantly, the coalition expresses deep concern over the dismissal by the HHS secretary of this substantial body of work. His recent remarks reportedly minimize the causal influence of genetics in autism and propagate narratives that contradict both clinical and empirical observations. Such positions, they argue, trivialize decades of research and disrespect the autistic community by perpetuating stigmatizing misconceptions. The scientists emphasize that appreciating the multifactorial basis of autism is essential for formulating meaningful interventions and policies that genuinely support autistic individuals and their families.

The coalition’s statement also calls for transparency and scientific integrity in upcoming research initiatives announced by HHS. Of particular contention is the plan to swiftly execute a study aiming to identify a singular environmental toxin as causative for autism—a move criticized for potentially bypassing established protocols of peer review, open data access, and independent analysis. Since autism’s etiology involves complex gene-environment interplay rather than simple unifactorial causation, the coalition insists that any new study must be grounded in methodological rigor and inclusive scientific scrutiny to prevent misleading conclusions.

Autism research is grounded in decades of methodological evolution, employing a range of sophisticated techniques spanning genomics, neuroimaging, and longitudinal behavioral analyses. The coalition points out that advancements such as genome-wide association studies (GWAS), epigenetic profiling, and high-resolution brain connectivity mapping have collectively revolutionized the field. These technologies have not only illuminated underlying biology but also facilitated the development of targeted interventions that address core symptoms and comorbidities. It is within this framework that future research must progress, rather than circumventing established approaches in favor of expedient but scientifically dubious claims.

Helen Tager-Flusberg elaborates on the coalition’s unified vision, emphasizing that autism research must prioritize unresolved questions that hold translational potential. “Finite resources necessitate focusing on the unknowns rather than rehashing settled issues,” she states. Areas such as the neuroimmune interface, the developmental trajectory of social communication networks in the brain, and heterogeneity in response to interventions represent frontiers that, if effectively explored, could transform clinical practice and improve quality of life for autistic individuals.

Furthermore, the coalition underscores the importance of community engagement and mutual respect between scientists and the public. Trust in biomedical research is paramount, especially within vulnerable populations like those affected by autism. The spread of misinformation and politicization of science raises stakes for public confidence. The coalition advocates for adherence to transparent protocols, robust ethical standards, and participatory models that include autistic individuals and their advocates as stakeholders in research design and dissemination.

The planned HHS study’s expedited timeline raises additional alarms, as it risks oversimplifying complex etiological frameworks into narrow causal assertions. The coalition argues that such an approach could divert precious funding away from longitudinal, multifactorial investigations and marginalize the voices of diverse autism communities whose experiences reflect a broad spectrum of needs. They urge that rigorous peer review and open commentary from the research community and families should guide study protocols before implementation.

Autism spectrum disorder’s prevalence has been increasing globally, a fact extensively documented by epidemiological research. Understanding whether this trend reflects better diagnostic tools, increased awareness, or environmental changes requires meticulous, multi-layered analyses. The coalition points out that attributing rising prevalence rates to a solitary environmental factor, as suggested by the current HHS agenda, ignores years of sophisticated data synthesis and misleads policymakers and the public alike.

In conclusion, the Coalition of Autism Scientists articulates a call to action for the Department of Health and Human Services to reaffirm a commitment to evidence-based research principles. Scientific progress in autism has been hard-won through collaborative, transparent inquiry and must not be undermined by politicized or premature assertions. With collaborative effort and sustained funding, the field is poised to unravel autism’s intricate biological underpinnings and translate discoveries into compassionate, effective support mechanisms for autistic individuals and their families.

As this dialogue continues, the autism research community remains steadfast in upholding scientific rigor as the cornerstone of progress. The coalition’s forthcoming website promises to serve as a resource hub for researchers, practitioners, and the public, facilitating access to data, fostering connections, and promoting informed discourse. Their leadership under Dr. Tager-Flusberg represents a renewed dedication to advancing autism science responsibly, ethically, and inclusively in an era of both unprecedented challenge and opportunity.

Subject of Research: People

Article Title: Coalition of Autism Scientists Critiques U.S. Department of Health and Human Services Autism Research Initiative

News Publication Date: April 25, 2025

Web References: Coalition of Autism Scientists Signatories List

Keywords: Autism; Discovery research; Developmental disabilities; Health and medicine; Scientific approaches