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Mood stabilizers are a category of medications used in the management of mood disorders. The mood stabilizing properties of lithium were first reported in 1949 by John Cade, and since then it has been considered the first line treatment for bipolar disorder. Despite presenting more differences than similarities, mood stabilizers are all characterized by high variability in response in treated patients. This feature has stimulated a vast body of research on potential predictive markers of clinical response, with promising but often inconclusive findings. Pharmacogenetics of mood stabilizers has provided valuable hints toward the involvement of genes and pathways in modulating response. However, with the exception of lithium, the number of studies is still too sparse to draw definite conclusions. Moreover, the mechanism of action of these drugs has yet to be completely elucidated. A growing body of research has explored the effect of mood stabilizers on a family of molecular players responsible for the regulation of gene expression without interfering with the DNA sequence. These processes belong to the epigenetic machinery and represent the mechanisms through which our biological systems interact with environmental factors, including drug treatments. In this review we focused on findings from preclinical and clinical studies suggesting that mood stabilizers may interfere with epigenetic mechanisms, providing an intriguing perspective that may help us filling the gap between molecular functions and clinical efficacy of mood stabilizers.

Lithium has been used for more than six decades for the management of bipolar disorder (BD). In a previous transcriptomic study, we showed that patients affected by either BD or cluster headache, both disorders characterized by circadian disturbances and response to lithium in a subgroup of patients, have higher expression of the RNA binding motif (RNP1, RRM) protein 3 (RBM3) gene compared to controls. To investigate whether RBM3 could represent a biomarker of lithium response, we screened raw microarray expression data from lymphoblastoid cell lines (LCLs) derived from 20 BD patients, responders or non-responders to lithium. RBM3 was the most significantly differentially expressed gene in the list, being overexpressed in responders compared to non-responders (fold change = 2.0; p = 1.5 × 10−16). We therefore sought to validate the microarray finding by quantitative reverse transcription polymerase chain reaction (RT-qPCR) and explore whether RBM3 expression was modulated by lithium treatment in vitro in LCLs as well as in human-derived neural progenitor cells (NPCs). Our findings confirmed the higher expression of RBM3 in responders compared to non-responders (fold change = 3.78; p = 0.0002). Lithium did not change RBM3 expression in LCLs in any of the groups, but it increased its expression in NPCs. While preliminary, our data suggest that higher levels of RBM3 might be required for better lithium response and that the expression of this gene could be modulated by lithium in a tissue-specific manner.

Lithium is the mainstay in the maintenance of bipolar disorder (BD) and the most efficacious pharmacological treatment in suicide prevention. Nevertheless, its use is hampered by a high interindividual variability and important side effects. Genetic and epigenetic factors have been suggested to modulate lithium response, but findings so far have not allowed identifying molecular targets with predictive value. In this study we used next generation sequencing to measure genome-wide miRNA expression in lymphoblastoid cell lines from BD patients excellent responders (ER, n = 12) and non-responders (NR, n = 12) to lithium. These data were integrated with microarray genome-wide expression data to identify pairs of miRNA/mRNA inversely and significantly correlated. Significant pairs were prioritized based on strength of association and in-silico miRNA target prediction analyses to select candidates for validation with qRT-PCR. Thirty-one miRNAs were differentially expressed in ER vs. NR and inversely correlated with 418 genes differentially expressed between the two groups. A total of 331 of these correlations were also predicted by in-silico algorithms. miR-320a and miR-155-3p, as well as three of their targeted genes (CAPNS1 (Calpain Small Subunit 1) and RGS16 (Regulator of G Protein Signaling 16) for miR-320, SP4 (Sp4 Transcription Factor) for miR-155-3p) were validated. These miRNAs and mRNAs were previously implicated in psychiatric disorders (miR-320a and SP4), key processes of the central nervous system (CAPNS1, RGS16, SP4) or pathways involved in mental illnesses (miR-155-3p). Using an integrated approach, we identified miRNAs and their targeted genes potentially involved in lithium response in BD.

We report the clinical description and genetic analyses of a Greek family with four individuals affected with a complicated form of hereditary spastic paraplegia (HSP) and a recessive pattern of inheritance. Exome sequencing of all affected individuals led to the identification of a homozygous 25 bp deletion predicted to lead to a frameshift and premature stop codon in the SPG7 gene, encoding paraplegin. This deletion, which is located in the first exon of the SPG7 gene, has not been previously reported and likely lead to the complete absence of the SPG7 protein. Interestingly, this family shows significant phenotypic heterogeneity further highlighting the clinical variability associated with SPG7 mutations. Our findings emphasize the clinical utility of whole exome sequencing for the molecular diagnosis of HSPs.

Schizophrenia is a severe disorder that significantly affects the quality of life and total functioning of patients and their caregivers. Clozapine is the first atypical antipsychotic with fewer adverse effects and established efficacy. As a rule of thumb, risperidone is one of the most reliable and effective antipsychotics for newly diagnosed and chronic schizophrenics. Pharmacogenetic studies have identified genomic variants of candidate genes that seem to be important in the way a patient responds to treatment. The recent progress made in pharmacogenomics will improve the quality of treatment, since drug doses will be tailored to the special needs of each patient. In this article, we review the available literature attempting to delineate the role of genomic variations in clozapine and risperidone response in schizophrenic patients of various ethnicities. We conclude that pharmacogenomics for these two drugs is still not ready for implementation in the clinic.