{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,31]],"date-time":"2026-10-31T12:29:06Z","timestamp":1793449746851,"version":"4.5.0"},"reference-count":41,"publisher":"Cambridge University Press (CUP)","license":[{"start":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T00:00:00Z","timestamp":1750118400000},"content-version":"unspecified","delay-in-days":167,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["cambridge.org"],"crossmark-restriction":true},"short-container-title":["Psychol. Med."],"published-print":{"date-parts":[[2025]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec id=\"S0033291725000765_sec1\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Psychiatric symptoms are typically highly inter-correlated at the group level. Collectively, these correlations define the architecture of psychopathology \u2013 informing taxonomic and mechanistic models in psychiatry. However, to date, it remains unclear if this architecture differs between etiologically distinct subgroups, despite the core relevance of this understanding for personalized medicine. Here, we introduce a new analytic pipeline to probe group differences in the psychopathology architecture \u2013 demonstrated through the comparison of two distinct neurogenetic disorders.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S0033291725000765_sec2\" sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We use a large questionnaire battery in 300 individuals aged 5\u201325\u00a0years (\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a0102 XXY\/KS,\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a064 XYY,\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a0134 age-matched XY) to characterize the structure of correlations among 53 diverse measures of psychopathology in XXY\/KS and XYY syndrome \u2013 enabling us to compare the effects of X- versus Y-chromosome dosage on the architecture of psychopathology at multiple, distinctly informative levels.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S0033291725000765_sec3\" sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Behavior correlation matrices describe the architecture of psychopathology in each syndrome. A comparison of matrix rows reveals that social problems and externalizing symptoms are most differentially coupled to other aspects of psychopathology in XXY\/KS versus XYY. Clustering the difference between matrices captures coordinated group differences in pairwise coupling between measures of psychopathology: XXY\/KS shows greater coherence among externalizing, internalizing, and autism-related features, while XYY syndrome shows greater coherence in dissociality and early neurodevelopmental impairment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S0033291725000765_sec4\" sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>These methods offer new insights into X- and Y-chromosome dosage effects on behavior, and our shared code can now be applied to other clinical groups of interest \u2013 helping to hone mechanistic models and inform the tailoring of care.<\/jats:p>\n                  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