Neurotransmitter-specific polygenic scores dissect clinical heterogeneity in schizophrenia
- 1IRBCatSud
Abstract
Schizophrenia (SCZ) is a highly heritable psychiatric disorder characterised by substantial clinical heterogeneity. While global polygenic scores (gPGS) capture genetic liability to SCZ, their ability to explain clinical variability remains limited. Pathway-stratified polygenic scores (sPGS) offer a biologically informed approach to patient stratification. In this study, common genetic variants were annotated across five neurotransmitter (NT) signalling pathways - acetylcholine (ACh), dopamine, gamma-aminobutyric acid (GABA), glutamate (Glu), and serotonin. sPGS adjusted for sex and ancestry principal components, were calculated in two independent cohorts with different available clinical data (N=3,044 and N=645). By clustering top-decile individuals across the five sPGS dimensions, we classified patients into five mutually exclusive patient profiles, which were then evaluated for their associations with Positive and Negative Syndrome Scale (PANSS) symptom dimensions, age at disease onset (AAO), and three-year clinical remission and treatment response. Although gPGS showed no significant association with clinical outcomes, some sPGS-derived profiles captured clinically relevant heterogeneity across cohorts. Patients assigned to the Ach profile exhibited higher overall symptom severity, particularly negative symptoms and general psychopathology. Patients within the Glu profile were characterised by more severe negative symptoms, earlier AAO, reduced three-year remission, and poorer treatment response. Similarly, the GABA risk profile was also associated with three-year remission rates. These findings suggest that NT pathway-specific polygenic profiling may capture clinically relevant variation overlooked by genome-wide approaches. By identifying genetic profiles associated with symptom severity, disease onset, and longitudinal outcomes, this framework could contribute to biologically informed patient stratification and inform future precision psychiatry approaches in SCZ.
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BibTeX
@misc{ramoncanellas2026neurotransmitterspecific,
title = {{Neurotransmitter-specific polygenic scores dissect clinical heterogeneity in schizophrenia}},
author = {P. Ramon-Canellas and J. Vazquez-Bourgon and B. Crespo-Facorro and D. Molto and M. J. Escarti and J. Gonzalez-Penas and C. Arango and A. M. Gonzalez-Pinto and L. Fananas and B. Arias and J. Bobes and J. Costas and L. Martorell and E. Vilella and G. Santpere and G. Muntane},
howpublished = {medRxiv},
year = {2026},
month = nov,
doi = {10.64898/2026.11.05.26367352},
url = {https://www.medrxiv.org/content/10.64898/2026.11.05.26367352v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Neurotransmitter-specific polygenic scores dissect clinical heterogeneity in schizophrenia
AU - P. Ramon-Canellas
AU - J. Vazquez-Bourgon
AU - B. Crespo-Facorro
AU - D. Molto
AU - M. J. Escarti
AU - J. Gonzalez-Penas
AU - C. Arango
AU - A. M. Gonzalez-Pinto
AU - L. Fananas
AU - B. Arias
AU - J. Bobes
AU - J. Costas
AU - L. Martorell
AU - E. Vilella
AU - G. Santpere
AU - G. Muntane
PY - 2026
DA - 2026/11/05
PB - medRxiv
DO - 10.64898/2026.11.05.26367352
UR - https://www.medrxiv.org/content/10.64898/2026.11.05.26367352v1
AB - Schizophrenia (SCZ) is a highly heritable psychiatric disorder characterised by substantial clinical heterogeneity. While global polygenic scores (gPGS) capture genetic liability to SCZ, their ability to explain clinical variability remains limited. Pathway-stratified polygenic scores (sPGS) offer a biologically informed approach to patient stratification. In this study, common genetic variants were annotated across five neurotransmitter (NT) signalling pathways - acetylcholine (ACh), dopamine, gamma-aminobutyric acid (GABA), glutamate (Glu), and serotonin. sPGS adjusted for sex and ancestry principal components, were calculated in two independent cohorts with different available clinical data (N=3,044 and N=645). By clustering top-decile individuals across the five sPGS dimensions, we classified patients into five mutually exclusive patient profiles, which were then evaluated for their associations with Positive and Negative Syndrome Scale (PANSS) symptom dimensions, age at disease onset (AAO), and three-year clinical remission and treatment response. Although gPGS showed no significant association with clinical outcomes, some sPGS-derived profiles captured clinically relevant heterogeneity across cohorts. Patients assigned to the Ach profile exhibited higher overall symptom severity, particularly negative symptoms and general psychopathology. Patients within the Glu profile were characterised by more severe negative symptoms, earlier AAO, reduced three-year remission, and poorer treatment response. Similarly, the GABA risk profile was also associated with three-year remission rates. These findings suggest that NT pathway-specific polygenic profiling may capture clinically relevant variation overlooked by genome-wide approaches. By identifying genetic profiles associated with symptom severity, disease onset, and longitudinal outcomes, this framework could contribute to biologically informed patient stratification and inform future precision psychiatry approaches in SCZ.
ER -