The results leading to this publication have received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 777394 for the project AIMS-2-TRIALS. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA and AUTISM SPEAKS, Autistica, SFARI. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Any views expressed are those of the author(s) and not necessarily those of the funders.
Individuals affected by autism spectrum conditions (ASC) are considerably heterogeneous. Novel approaches are needed to parse this heterogeneity to enhance precision in clinical and translational research. Applying a clustering approach taken from genomics and systems biology on two large independent cognitive datasets of adults with and without ASC (n = 694; n = 249), we find replicable evidence for 5 discrete ASC subgroups that are highly differentiated in item-level performance on an explicit mentalizing task tapping ability to read complex emotion and mental states from the eye region of the face (Reading the Mind in the Eyes Test; RMET). Three subgroups comprising 45–62% of ASC adults show evidence for large impairments (Cohen's d = −1.03 to −11.21), while other subgroups are effectively unimpaired. These findings delineate robust natural subdivisions within the ASC population that may allow for more individualized inferences and accelerate research towards precision medicine goals. ; This study was supported by the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) East of England at Cambridgeshire and Peterborough NHS Foundation Trust. This study was also conducted in association with the European Autism Interventions—A Multicentre Study for Developing New Medications (EU-AIMS) consortium; EU-AIMS receives support from the Innovative Medicines Initiative Joint Undertaking under grant agreement number 115300, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007–2013), EFPIA companies, and Autism Speaks. This study was also supported by grants from the UK Medical Research Council (MRC) (G0600977), the Wellcome Trust (091774/Z/10/Z), and the Autism Research Trust (ART). M-CL and AR received support from the William Binks Autism Neuroscience Fellowship at the University of Cambridge. M-CL received support from the O'Brien Scholars Program within the Child and Youth Mental Health Collaborative at the Centre for Addiction and Mental Health and The Hospital for Sick Children, Toronto. ; This is the final version of the article. It first appeared from Nature Publishing Group via https://doi.org/10.1038/srep35333
Individuals affected by autism spectrum conditions (ASC) are considerably heterogeneous. Novel approaches are needed to parse this heterogeneity to enhance precision in clinical and translational research. Applying a clustering approach taken from genomics and systems biology on two large independent cognitive datasets of adults with and without ASC (n = 694; n = 249), we find replicable evidence for 5 discrete ASC subgroups that are highly differentiated in item-level performance on an explicit mentalizing task tapping ability to read complex emotion and mental states from the eye region of the face (Reading the Mind in the Eyes Test; RMET). Three subgroups comprising 45-62% of ASC adults show evidence for large impairments (Cohen's d = -1.03 to -11.21), while other subgroups are effectively unimpaired. These findings delineate robust natural subdivisions within the ASC population that may allow for more individualized inferences and accelerate research towards precision medicine goals. ; This study was supported by the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) East of England at Cambridgeshire and Peterborough NHS Foundation Trust. This study was also conducted in association with the European Autism Interventions—A Multicentre Study for Developing New Medications (EU-AIMS) consortium; EU-AIMS receives support from the Innovative Medicines Initiative Joint Undertaking under grant agreement number 115300, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007–2013), EFPIA companies, and Autism Speaks. This study was also supported by grants from the UK Medical Research Council (MRC) (G0600977), the Wellcome Trust (091774/Z/10/Z), and the Autism Research Trust (ART). M-CL and AR received support from the William Binks Autism Neuroscience Fellowship at the University of Cambridge. M-CL received support from the O'Brien Scholars Program within the Child and Youth Mental Health Collaborative at the Centre for Addiction and Mental Health and The Hospital for Sick Children, Toronto. ; This is the final version of the article. It first appeared from Nature Publishing Group via https://doi.org/10.1038/srep35333
