探討宿主基因與腸胃道菌相的交互作用與憂鬱症之關聯性

Abstract

Background Among the mental disorder, major depressive disorder (MDD) is a common and highly prevalent disease that affects millions of people worldwide. The complex mechanisms and multi-factorial factors such as biological, psychological, social factors, genetic factors and even microbiota composition for MDD were the reasons that the pace of finding robust genetic variants has been slow and difficult. Although the heritability has been confirmed in MDD, the genetic variants associated with the illness were still inconsistent across studies. After discovering the pathway “gut-brain axis,” the potential association between brain and gut was directly implicated. The huge amounts of gut microbiota have their unique function and also promote human health. Besides several factors such as the lifestyle and medical practice that may influence our gut microbiota composition, previous studies have demonstrated that host genetics may also play an important role in shaping both the overall microbiota composition and individual bacteria taxa among humans and mice. In addition to the physiological change such as obesity, inflammatory bowel disease, and liver disease that were associated with the dysbiosis of the microbiota, more and more studies have focused on the mental health that also may be affected by the composition of microbiota. The above findings showing the link between MDD and microbiota via host genetic, but the interaction between host genetic variants and the composition of microbiota need further investigate. Materials and Methods To conducted GWAS analysis, we recruited 455 MDD patients from 5 Taipei hospitals with a clinical diagnosis of DSM-IV MDD, and 18,000 general population from Taiwan Biobank. General population were defined as MDD patients with self-report as MDD in past history and removed due to the high scores of PHQ-4. After quality controls, 1057 MDD patients and 16349 controls with 163451 genotyped and well-imputed SNPs were retained for analysis. To analyze the microbiota composition, we recruited 36 patients from 5 Taipei hospitals with a clinical diagnosis of DSM-IV MDD, 37 controls were from community and random volunteers. Stool samples were collected of each of the participants. Microbiota information will be done by DNA extraction and 16s rRNA sequencing. We performed genetic association test using logistic regression for MDD with adjustment for age and sex. To discover the specific microbiota targets, we use linear regression and adjustment for age, sex and the sequence order. Finally, to performed the interaction analysis between host genetic and microbiota, we used logistic regression as grouping the microbiota as high and low abundance group, the genetic variants were presented as additive, dominant and recessive model. Results There were 4 loci showed suggestive signals with p-value<5×10-6, 13 loci showed signals with p-value<5×10-5. The top three significant markers were rs2075244 (P=3.09×10-6) which mapped to gene PTPRO, rs337170 (P=4.41×10-6) which mapped to C1orf115 and MARC2 and rs9455527 (P=4.82×10-6) which did not mapped to any gene. There were 5 specific microbiota targets Bacteroides, SMB53, Dialister, Turicibacter, Phascolarctobacterium showing significant different compare MDD and controls, while Prevotella reached the borderline of the significant threshold. After the interaction analysis within different genetic model, Phascolarctobacterium showed significant interaction with rs337170, rs1909153 in both additive and dominant model, and also showed significant interaction with SNP rs7517824, rs1494373 and rs2075244 in recessive model. While Dialister showed significant interaction with rs337170 in dominant model, SMB53 showed significant interaction with rs337170 in additive model and rs1909153 in both additive and dominant model. Conclusion: We found several genetic loci that may influence the composition of gut microbiota, which showing the interaction among different genetic model. Future studies are needed to replicate the genetic loci and microbiota targets in MDD patients in Chinese population and further investigate their biological function.