Despite recent progress in deciphering the genomic basis of schizophrenia, treatment options remain limited, and approximately 30% of patients do not respond adequately to current first-line medications. Understanding the molecular basis of treatment resistance in schizophrenia is therefore essential for improving care and developing novel treatment options. Toward that goal, we leveraged the Massachusetts General Hospital NeuroBank to comprehensively profile patient-derived disease-relevant cells from individuals with schizophrenia as well as neurotypical controls. Individuals with schizophrenia--defined as antipsychotic-responsive and antipsychotic-resistant based upon structured clinical interview and high-throughput phenotyping using electronic health records--provided a fibroblast sample via dermal punch biopsy. Neural progenitor cell lines (NPCs) were then generated from fibroblast-reprogrammed iPSCs using small molecule differentiation, and treated with clozapine and DMSO (vehicle control). Transcriptomic, metabolomic, and imaging profiles were collected from cultured NPCs. DNA was extracted from peripheral blood samples and subjected to whole genome sequencing. Single nucleotide variants (SNVs) were identified using the Genome Analysis Toolkit’s HaplotypeCaller. Variants with minor allele frequency (MAF)>1% in general population datasets (e.g. ExAC, excluding subjects with psychiatric diseases) and those identified in healthy controls were removed. Focusing on SNVs shared by at least three individuals of the same group and none in the other group revealed 37 SNVs in the treatment resistant group, and 2 in the treatment responsive one. Of those, a nonsynonymous ENTPD1 gene variant (rs192954755) was identified in three resistant individuals; the reported MAF in ExAC is ~0.001. ENTPD1 is involved in adenosine metabolism, and its dysregulation had been previously found to significantly impact neuromodulatory function. ENTPD1 was also downregulated in NPCs from treatment resistant individuals, irrespective of their rs192954755 genotype. Overall, NPC expression profiles accurately distinguished treatment resistant from treatment responsive individuals. The strongest single gene predictors of treatment resistance in patient-derived NPCs were downregulation of ASTN1 (log fold change (logFC)=-7.45, P=4.96x10-11), HOXB9 (logFC=-8.00 , P=9.09x10-10), and HOXC9 (logFC=-7.90, P=2.27x10-10). Such homeobox transcription factors were among the most dysregulated genes between treatment resistant and responsive NPCs (P=7.7x10-13). These results provide a next step in elucidating the molecular mechanisms underlying individual treatment response in schizophrenia, and may facilitate development of tools for stratifying risk and identifying rescue treatments in this chronic disease.
Multidimensional profiling of treatment response in schizophrenia
Sanavia T;
2018-01-01
Abstract
Despite recent progress in deciphering the genomic basis of schizophrenia, treatment options remain limited, and approximately 30% of patients do not respond adequately to current first-line medications. Understanding the molecular basis of treatment resistance in schizophrenia is therefore essential for improving care and developing novel treatment options. Toward that goal, we leveraged the Massachusetts General Hospital NeuroBank to comprehensively profile patient-derived disease-relevant cells from individuals with schizophrenia as well as neurotypical controls. Individuals with schizophrenia--defined as antipsychotic-responsive and antipsychotic-resistant based upon structured clinical interview and high-throughput phenotyping using electronic health records--provided a fibroblast sample via dermal punch biopsy. Neural progenitor cell lines (NPCs) were then generated from fibroblast-reprogrammed iPSCs using small molecule differentiation, and treated with clozapine and DMSO (vehicle control). Transcriptomic, metabolomic, and imaging profiles were collected from cultured NPCs. DNA was extracted from peripheral blood samples and subjected to whole genome sequencing. Single nucleotide variants (SNVs) were identified using the Genome Analysis Toolkit’s HaplotypeCaller. Variants with minor allele frequency (MAF)>1% in general population datasets (e.g. ExAC, excluding subjects with psychiatric diseases) and those identified in healthy controls were removed. Focusing on SNVs shared by at least three individuals of the same group and none in the other group revealed 37 SNVs in the treatment resistant group, and 2 in the treatment responsive one. Of those, a nonsynonymous ENTPD1 gene variant (rs192954755) was identified in three resistant individuals; the reported MAF in ExAC is ~0.001. ENTPD1 is involved in adenosine metabolism, and its dysregulation had been previously found to significantly impact neuromodulatory function. ENTPD1 was also downregulated in NPCs from treatment resistant individuals, irrespective of their rs192954755 genotype. Overall, NPC expression profiles accurately distinguished treatment resistant from treatment responsive individuals. The strongest single gene predictors of treatment resistance in patient-derived NPCs were downregulation of ASTN1 (log fold change (logFC)=-7.45, P=4.96x10-11), HOXB9 (logFC=-8.00 , P=9.09x10-10), and HOXC9 (logFC=-7.90, P=2.27x10-10). Such homeobox transcription factors were among the most dysregulated genes between treatment resistant and responsive NPCs (P=7.7x10-13). These results provide a next step in elucidating the molecular mechanisms underlying individual treatment response in schizophrenia, and may facilitate development of tools for stratifying risk and identifying rescue treatments in this chronic disease.
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