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The successful therapeutic use of anti-TNF biological agents in patients with ankylosing spondylitis (AS) indicates that tumor necrosis factor-α (TNF-α) and tumor necrosis factor receptor (TNFR) genes are involved in the pathogenesis of AS. TNF-α exerts its biological activity by binding to its cell surface receptors (p55 TNF-α receptor [TNFRI, encoded by the Tumor Necrosis Factor Receptor Superfamily Member 1A (TNFRSF1A)] and p75 receptor [TNFRII, encoded by the Tumor Necrosis Factor Receptor Superfamily Member 1B (TNFRSF1B)]. TNFRSF1A and TNFRSF1B may be related to AS, but the relevant studies are still limited. Therefore, we aim to explore the association between TNFRSF1A and TNFRSF1B polymorphisms and susceptibility and short- and long-term response to anti-TNF treatment in human leukocyte antigen-B27 (HLA-B27)-positive Chinese Han patients with AS. A total of 215 HLA-B27-positive patients with AS and 216 HLA-B27-positive matched controls were enrolled and genotyped for rs767455, rs2234649, and rs1061622. A subset of 50 AS patients was also studied for the association of these polymorphisms with the short- and long-term response to etanercept assessed by Assessment in Ankylosing Spondylitis 20 (ASAS20) and Assessment in Ankylosing Spondylitis 40 (ASAS40). Our data showed that rs767455 was associated with the susceptibility of AS, G allele of rs767455 exhibited an association with the risk of developing AS (OR = 1.63 (1.04–2.55), P = .032). Rs1061622 polymorphism was associated with total back pain and chest expansion. Only rs1061622 was significantly associated with long-term efficacy of etanercept: the TG genotype of rs1061622 worsened ASAS20 and ASAS40 responses at 12 months (P = .021 and .041, respectively). The results suggest that TNFRSF1A and TNFRSF1B polymorphisms were associated with susceptibility, severity, and the long-term therapeutic efficacy of etanercept of patients with AS.

First-principles, all-electron, ab initio calculations have been performed to construct an equivalent water potential for the electronic structure of serine (Ser) in solution. The calculation is composed of three steps. The first step is to search for the configuration of the Ser + nH2O system with a minimum energy. The second step is to calculate the electronic structure of Ser with the water molecule potential via the self-consistent cluster-embedding method (SCCE), based on the result obtained in the first step. The last step is to calculate the electronic structure of Ser with the dipole potential after replacing the water molecules with dipoles. The results show that the occupied states of Ser are raised by about 0.017 Ry on average due to the effect of water. The water effect can be successfully simulated by using the dipole potential. The obtained equivalent potential can be applied directly to the electronic structure calculation of protein in solution by using the SCCE method.