A miR-137-related biological pathway of risk for Schizophrenia is associated with human brain emotion processing

Abstract

Genome-Wide-Association studies have involved miR-137 in schizophrenia. However, the biology underlying this statistical evidence is unclear. Statistical polygenic risk for schizophrenia is associated with working memory, while other biological evidence involves miR-137 in emotion processing. We investigated the function of miR-137 target schizophrenia risk genes in humans. We identified a prefrontal co-expression pathway of schizophrenia-associated miR-137 targets and validated the association with miR-137 expression in neuroblastoma cells. Alleles predicting greater co-expression of this pathway were associated with greater prefrontal activation during emotion processing in two independent cohorts of healthy volunteers (N1=222; N2=136). Statistical polygenic risk for schizophrenia was instead associated with prefrontal activation during working memory. A co-expression pathway links miR-137 and its target genes to emotion processing and risk for schizophrenia. Low prefrontal miR-137 expression may be related with SCZ risk via increased expression of target risk genes, itself associated with increased prefrontal activation during emotion processing.

Consensus molecular environment of schizophrenia risk genes in coexpression networks shifting across age and brain regions

“…Table 1 shows genes coexpressed in SCZ risk modules in at least two-thirds of the networks that had at least one module enriched with SCZ risk genes in (i) cortical fetal samples [the perinatal age period–parsed network and the networks published in ( 26 , 27 , 31 )] and (ii) postnatal networks [juvenile, adult, older adult DLPFC networks presented here, plus those reported by others ( 5 , 10 – 14 , 35 )] (Fig. 9A).…”

“…First, we performed a sensitivity analysis to establish the parameters used to identify SCZ risk modules based on enrichment for SCZ risk genes. To this aim, we used previously published networks ( 5 , 10 – 14 , 26 , 27 , 31 , 35 , 36 ). We then tested four hypotheses (each outlined in Fig.…”

“…In addition to hypergeometric tests, we also computed permutation statistics (creating for each module in each network a null distribution of 10,000 sets of randomly sampled genes using network-specific genes as the universe) to obtain an unbiased empirical P value. We performed these same analyses in networks from published reports to provide a benchmark ( 5 , 10 – 14 , 26 , 27 , 31 , 35 , 36 ). Moreover, we tested whether SCZ risk genes were significantly underrepresented in the gray module of nonclustered genes relative to a universe represented by all genes expressed in a network.…”

A polygenic score indexing a DRD2-related co-expression network is associated with striatal dopamine function

“…Gene co-expression networks have been instrumental in identifying gene sets associated with antipsychotic treatment response 30 , 35 , phenotypes associated with schizophrenia 25 , 28 , 35 , 85 , clinical state and risk for schizophrenia 31 , and changes in prefrontal function after D2R stimulation 39 . As reviewed previously, increased dopamine synthesis capacity represents a phenotype associated with schizophrenia 47 , 86 , 87 .…”

“…However, it is unlikely that genetic variations within a single gene explain the entire physiology related to specific brain phenotypes. In this regard, previous investigations have elucidated that genes involved in complex traits do not work in isolation but operate in networks of interacting genes 18 – 22 acting via molecular pathways 23 – 25 . Genetic networks can be investigated in detail using methods for the analysis of gene co-expression patterns 26 , 27 .…”