Progress and Challenges in GxE Research on Depression

Gut microbial diversity moderates polygenic risk of schizophrenia

Background

Schizophrenia (SCZ) is a heritable disorder with a polygenic architecture, and the gut microbiota seems to be involved in its development and outcome. In this study, we investigate the interplay between genetic risk and gut microbial markers.

Methods

We included 159 first-episode, drug-naïve SCZ patients and 86 healthy controls. The microbial composition of feces was characterized using the 16S rRNA sequencing platform, and five microbial α-diversity indices were estimated [Shannon, Simpson, Chao1, the Abundance-based Eoverage Estimator (ACE), and a phylogenetic diversity-based estimate (PD)]. Polygenic risk scores (PRS) for SCZ were constructed using data from large-scale genome-wide association studies. Effects of microbial α-diversity, microbial abundance, and PRS on SCZ were evaluated via generalized linear models.

Results

We confirmed that PRS was associated with SCZ (OR = 2.08, p = 1.22×10-5) and that scores on the Shannon (OR = 0.29, p = 1.15×10-8) and Simpson (OR = 0.29, p = 1.25×10-8) indices were inversely associated with SCZ risk. We found significant interactions (p < 0.05) between PRS and α-diversity indices (Shannon, Simpson, and PD), with the effects of PRS being larger in those exhibiting higher diversity compared to those with lower diversity. Moreover, the PRS effects were larger in individuals with a high abundance of the genera Romboutsia, Streptococcus, and Anaerostipes than in those with low abundance (p < 0.05). All three of these genera showed protective effects against SCZ.

Conclusion

The current findings suggest an interplay between the gut microbiota and polygenic risk of SCZ that warrants replication in independent samples. Experimental studies are needed to determine the underpinning mechanisms.

A person-centered data analytic approach to dopaminergic polygenic moderation of child maltreatment exposure

The present study illustrates the utility of latent class analysis, a person-centered data analytic approach, as an innovative method for identifying naturally occurring patterns of polygenic risk, specifically within the dopaminergic system. Moreover, this study tests whether latent classes of polygenic variation moderate the effect of child maltreatment exposure on internalizing symptoms among African ancestry youth. African ancestry youth were selected for this study because youth of color are overrepresented in the child welfare system and because African ancestry individuals are significantly underrepresented in genomics research. Results identified three latent classes of dopaminergic gene variation. Class 1 was marked predominately by homozygous minor alleles, Class 2 was characterized by homozygous major and heterozygous presentations, and Class 3 was marked by heterozygous alleles on the DAT-1 single-nucleotide polymorphisms (SNPs) and a combination of homozygous major and minor alleles on the other SNPs. Results indicated that a greater number of maltreatment subtypes experienced were associated with higher internalizing symptoms only for children with the latent polygenic Class 2 pattern. This latent class was distinctly characterized by more homozygous major or heterozygous allelic presentations along all three DAT-1 SNPs. This significant latent polygenic class by environment interaction was replicated in an independent replication sample. Together, findings suggest that African ancestry children with a pattern of dopaminergic variation characterized by this specific combination of polygenic variation are more vulnerable to developing internalizing symptoms following maltreatment exposure, relative to their peers with other dopamine-related polygenic patterns.