Molecular Mechanism Biomarkers Predict Diagnosis in Schizophrenia and Schizoaffective Psychosis, with Implications for Treatment

Author:

Fryar-Williams Stephanie1234ORCID,Tucker Graeme5,Strobel Jörg6,Huang Yichao7,Clements Peter78ORCID

Affiliation:

1. Youth in Mind Research Institute, Unley, SA 5061, Australia

2. The Queen Elizabeth Hospital, Woodville, SA 5011, Australia

3. Basil Hetzel Institute for Translational Health Research, Woodville, SA 5011, Australia

4. Department of Nanoscale BioPhotonics, Faculty of Health and Medical Sciences, School of Biomedicine, The University of Adelaide, Adelaide, SA 5000, Australia

5. Department of Public Health, Faculty of Health and Medical Sciences, Adelaide Medical School, The University of Adelaide, Adelaide, SA 5000, Australia

6. Department of Psychiatry, Faculty of Health and Medical Sciences, Adelaide Medical School, The University of Adelaide, Adelaide, SA 5000, Australia

7. Waite Research Institute, The University of Adelaide, Urrbrae, SA 5064, Australia

8. Department of Paediatrics, Faculty of Health and Medical Sciences, Adelaide Medical School, The University of Adelaide, Adelaide, SA 5000, Australia

Abstract

Diagnostic uncertainty and relapse rates in schizophrenia and schizoaffective disorder are relatively high, indicating the potential involvement of other pathological mechanisms that could serve as diagnostic indicators to be targeted for adjunctive treatment. This study aimed to seek objective evidence of methylenetetrahydrofolate reductase MTHFR C677T genotype-related bio markers in blood and urine. Vitamin and mineral cofactors related to methylation and indolamine-catecholamine metabolism were investigated. Biomarker status for 67 symptomatically well-defined cases and 67 asymptomatic control participants was determined using receiver operating characteristics, Spearman’s correlation, and logistic regression. The 5.2%-prevalent MTHFR 677 TT genotype demonstrated a 100% sensitive and specific case-predictive biomarkers of increased riboflavin (vitamin B2) excretion. This was accompanied by low plasma zinc and indicators of a shift from low methylation to high methylation state. The 48.5% prevalent MTHFR 677 CC genotype model demonstrated a low-methylation phenotype with 93% sensitivity and 92% specificity and a negative predictive value of 100%. This model related to lower vitamin cofactors, high histamine, and HPLC urine indicators of lower vitamin B2 and restricted indole-catecholamine metabolism. The 46.3%-prevalent CT genotype achieved high predictive strength for a mixed methylation phenotype. Determination of MTHFR C677T genotype dependent functional biomarker phenotypes can advance diagnostic certainty and inform therapeutic intervention.

Funder

Queen Elizabeth Hospital Research Foundation

Australian Government Department of Industry Innovation and Science, Research and Development, Tax Incentive Grant

Publisher

MDPI AG

Subject

Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Spectroscopy,Molecular Biology,General Medicine,Catalysis

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