Disease Studies

Schizophrenia

Schizophrenia is a neuropsychiatric disease affecting 20 million people globally. Patients present with a wide variety of symptoms and severities. Most patients are treated with standard antipsychotic drugs, but given the disease’s heterogeneity, it’s not surprising that as many as 30% of patients are classified as treatment-resistant.

We clustered a schizophrenia population dataset to identify five different patient communities. These contain distinct combinations of genes with shared biological mechanisms, providing further insights into their role in underlying disease pathology and patient phenotype.

Of the 85 significant genes we identified, most have not previously been implicated in the disease. They nonetheless have strong mechanistic links to several pathways associated with schizophrenia pathogenesis, including altered neurotransmission, inflammation, and regulation of neuronal development and synaptic plasticity.



Methodology

Existing GWAS studies have identified a large number of loci and genes associated with the disease. These however have proved challenging to translate into novel therapies and useful prediction tools that demonstrate clinical benefit. In large part this is due to the complexity of the disease with the non-linear effects of interaction between multiple variants contributing to the patient’s phenotype.

We analysed genotype data from 823 patients diagnosed with schizophrenia found in the UK Biobank. Combinatorial analysis with the PrecisionLife® platform generated 186 strongly disease-associated combinations of SNPs.


Findings/Results

We identified 85 significant genes associated with schizophrenia patients. Although most have not previously been implicated in the disease, they have a strong mechanistic link to several pathways that are associated with schizophrenia pathogenesis, including altered neurotransmission, inflammation, and regulation of neuronal development and synaptic plasticity.

The disease signatures clustered to identify five different patient sub-cohorts. These sub-groups contain distinct combinations of genes that appear to have shared biological mechanisms, providing further insights into their impact on underlying disease pathology and patient phenotype. This high resolution patient stratification based on distinct biological mechanisms presents significant opportunities in improving diagnosis and treatment of schizophrenia.

In addition, mapping existing drug options for key targets identified as being significant in subpopulations of schizophrenia patients, allows us to rapidly identify potential repurposing opportunities. Our results included a gene that is targeted by a statin that has already been shown to reduce the negative symptoms of schizophrenia, providing validation for our methodology.

Disease architecture of schizophrenia. Each color identifies a distinct patient sub-group. Functional enrichment analysis of the five genes mapping to SNPs in Sub-group 3 indicate that they are all involved in neurotransmission pathways.


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