Back

Intelligence as proxy phenotype providing insight into the heterogeneity of schizophrenia

Ren, H.; Yin, M.; Wang, Q.; Ma, X.; Zhao, L.; Li, X.; Sham, P.; Li, M.; Li, S.; Li, T.

2023-02-14 psychiatry and clinical psychology
10.1101/2023.02.04.23285470 medRxiv
Show abstract

Schizophrenia is a mental disorder constituting different symptom clusters. Its high heterogeneity in both pathophysiology and clinical manifestations hampered effective prevention and treatment. It has long been recognized that one of the core features of schizophrenia is its intellectual decline. Using the proxy-phenotype method (PPM), we tried to identify core genes, the expression of which in the dorsal lateral prefrontal cortex (DLPFC) showed a genetic dependence between intelligence (IT) and schizophrenia (SCZ). The result revealed ten genes of genetic dependence in their genetic expression in DLPFC between IT and schizophrenia. Further, a clustering analysis using the expression matrix of these ten genes identified four biotypes in our patient group. Subsequent phenotypic profiling of these four biotypes indicated a significant difference in working memory capacity, the gray matter volume (GMV) of five brain regions (lLimbicA_TempPole_2, rLimbicA_TempPole_2 rLimbicB_OFC_1, rContA_IPS_1 and rContB_PFClv_1), structural network and psychopathology. An in-vitro investigation of the biological functions of these core genes indicated their potentially critical role in neuronal growth, especially in dendritic spines. Our current study employed a novel statistical approach to identify the core genes associated with IT and explore the possibility of using the expression knowledge of these core genes to reduce the heterogeneity of schizophrenia. The results pinpointed one biotype that exhibited significant deficits in working memory, GMV in limbic and prefrontal areas, and also showed psychopathology of core negative symptom and worse outcomes.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.