Szu-Wei Cheng1,2, Jing-Xing Li1,2, Daniel Tzu-Li Chen2,3,4, Yu-Chuan Chien2,3, Jane Pei-Chen Chang1,2, Shih-Yi Huang5, Piotr Galecki6, Kuan-Pin Su1,2,3,7. 1. College of Medicine, China Medical University, Taichung 404, Taiwan. 2. Department of Psychiatry and Mind-Body Interface Laboratory (MBI-Lab), China Medical University Hospital, Taichung 404, Taiwan. 3. Graduate Institute of Biomedical Sciences, China Medical University, Taichung 404, Taiwan. 4. School of Chinese Medicine, China Medical University, Taichung 404, Taiwan. 5. School of Nutrition and Health Sciences, Taipei Medical University, Taipei 110, Taiwan. 6. Department of Adult Psychiatry, Medical University of Lodz, 90 Lodz, Poland. 7. An-Nan Hospital, China Medical University, Tainan 709, Taiwan.
Abstract
Importance: The high incidence of major depressive episodes during interferon-α (IFN-α) therapy is considered the most powerful supportive evidence for the inflammation theory of depression. As the kynurenine pathway plays an important role connecting inflammation and depression, it is plausible to investigate this pathway for predictive genetic markers for IFN-α-induced depression. Methods: In this prospective case-control study, we assessed 291 patients with chronic hepatitis C viral infection taking IFN-α therapy and analyzed the single nucleotide polymorphisms (SNPs) in genes in the kynurenine pathway. Our case group contained patients who developed IFN-α-induced depression during the treatment, and others were defined as the control group. Genomic DNA was extracted from leukocytes in the peripheral blood and analyzed by Affymetrix TWB array. We first tested allelic, dominant, and recessive models on each of our SNPs using Fisher's exact test. We then conducted 5000 gene-wide max(T) permutations based on the best model of each SNP to provide strong gene-wide family-wise error rate control. Finally, we preformed logistic regression for the significant SNPs acquired in previous procedures, with sex and education level as covariates to build predictive models. Additional haplotype analyses were conducted with Haploview 4.2 to investigate the combining effect of multiple significant SNPs within a gene. Results: With sex and education level as covariates, rs8082252 (p = 0.0015, odds ratio = 2.716), rs8082142 (p = 0.0031, odds ratio = 2.499) in arylformamidase (AFMID), and rs12477181 (p = 0.0004, odds ratio = 0.3478) in kynureninase (KYNU) were significant in logistic regression models with dominant modes of inheritance. Haplotype analyses showed the two significant SNPs in AFMID to be in the same haploblock and highly correlated (r2 = 0.99). There were two significant haplotypes (by the sequence of rs8082252, rs8082142): AT (χ2 = 7.734, p = 0.0054) and GC (χ2 = 6.874, p = 0.0087). Conclusions: This study provided supportive evidence of the involvement of the kynurenine pathway in IFN-α-induced depression. SNPs in this pathway were also predictive of this disease.
Importance: The high incidence of major depressive episodes during interferon-α (IFN-α) therapy is considered the most powerful supportive evidence for the inflammation theory of depression. As the kynurenine pathway plays an important role connecting inflammation and depression, it is plausible to investigate this pathway for predictive genetic markers for IFN-α-induced depression. Methods: In this prospective case-control study, we assessed 291 patients with chronic hepatitis C viral infection taking IFN-α therapy and analyzed the single nucleotide polymorphisms (SNPs) in genes in the kynurenine pathway. Our case group contained patients who developed IFN-α-induced depression during the treatment, and others were defined as the control group. Genomic DNA was extracted from leukocytes in the peripheral blood and analyzed by Affymetrix TWB array. We first tested allelic, dominant, and recessive models on each of our SNPs using Fisher's exact test. We then conducted 5000 gene-wide max(T) permutations based on the best model of each SNP to provide strong gene-wide family-wise error rate control. Finally, we preformed logistic regression for the significant SNPs acquired in previous procedures, with sex and education level as covariates to build predictive models. Additional haplotype analyses were conducted with Haploview 4.2 to investigate the combining effect of multiple significant SNPs within a gene. Results: With sex and education level as covariates, rs8082252 (p = 0.0015, odds ratio = 2.716), rs8082142 (p = 0.0031, odds ratio = 2.499) in arylformamidase (AFMID), and rs12477181 (p = 0.0004, odds ratio = 0.3478) in kynureninase (KYNU) were significant in logistic regression models with dominant modes of inheritance. Haplotype analyses showed the two significant SNPs in AFMID to be in the same haploblock and highly correlated (r2 = 0.99). There were two significant haplotypes (by the sequence of rs8082252, rs8082142): AT (χ2 = 7.734, p = 0.0054) and GC (χ2 = 6.874, p = 0.0087). Conclusions: This study provided supportive evidence of the involvement of the kynurenine pathway in IFN-α-induced depression. SNPs in this pathway were also predictive of this disease.
Authors: A R Currier; M H Ziegler; M M Riley; T A Babcock; V P Telbis; J M Carlin Journal: J Interferon Cytokine Res Date: 2000-04 Impact factor: 2.607
Authors: Robert Dantzer; Jason C O'Connor; Gregory G Freund; Rodney W Johnson; Keith W Kelley Journal: Nat Rev Neurosci Date: 2008-01 Impact factor: 34.870
Authors: Linn Fagerberg; Björn M Hallström; Per Oksvold; Caroline Kampf; Dijana Djureinovic; Jacob Odeberg; Masato Habuka; Simin Tahmasebpoor; Angelika Danielsson; Karolina Edlund; Anna Asplund; Evelina Sjöstedt; Emma Lundberg; Cristina Al-Khalili Szigyarto; Marie Skogs; Jenny Ottosson Takanen; Holger Berling; Hanna Tegel; Jan Mulder; Peter Nilsson; Jochen M Schwenk; Cecilia Lindskog; Frida Danielsson; Adil Mardinoglu; Asa Sivertsson; Kalle von Feilitzen; Mattias Forsberg; Martin Zwahlen; IngMarie Olsson; Sanjay Navani; Mikael Huss; Jens Nielsen; Fredrik Ponten; Mathias Uhlén Journal: Mol Cell Proteomics Date: 2013-12-05 Impact factor: 5.911