The Genetic Polymorphism of TNF-α Associated with the Anti-TNF-α Therapy Used for COVID-19 Patients – Another Possible Approach

Objective: This work aimed of to review the implications of anti-TNF-α therapy in COVID-19 patients associated with the genetic polymorphism (TNF-α polymorphisms in the region-308) of this pertinent cytokine Methodology: Electronic searches were carried out on PUBMED Central, BVS/BIREME, Web of Science and The Cochrane Library with the aid of key-words. Results: Twenty-six articles were collected. Anti-TNF-α therapy was interpreted and evaluated. Conclusions: Although scarce information is available in the current literature, anti- TNF-α therapy seems to be a viable clinical approach for hospitalized COVID-19 patients who do not need oxygen supply. The genetic polymorphisms, although relevant, may be useful for further researched to assess the clinical response in different research groups.

Ex Vivo Chemosensitivity Profiling of Acute Myeloid Leukemia and Its Correlation With Clinical Response and Outcome to Chemotherapy

We evaluated the predictive value of the ex-vivo PharmaFlow PM platform in measuring the pharmacological activity of drug combinations consisting of 20 different chemotherapy regimens (20 Tx) administered in 104 acute myeloid leukemia (AML) patients. The predicted sensitivities of alternative treatments for each patient were ranked in five 20% categories, from resistant to sensitive (Groups 1–5). The complete remission (CR) rates of the five groups were 0%, 12.5%, 38.5%, 50.0%, and 81.3%, respectively. The heat map showed a good relationship between drug sensitivity with CR (Group 4 + 5 vs. Group 1 + 2+3: 77.5% vs. 27.3%, p = 0.002) and the European Leukemia Net risk group (22.6% vs. 63.6%, p = 0.015). The predicted coincidence rate was 90.9% in Group 1 + 2 and 81.3% in Group 5. According to the recommendations of the PharmaFlow PM platform, the CR rate would have increased by about 16.3% in one cycle. The overall survival (OS) was shorter in patients predicted to be resistant (Group 1 + 2 vs. Group 3 + 4+5, p = 0.086). In multivariable analysis, CR after one cycle was an independent prognostic factor for OS [p = 0.001; 95% CI 0.202 (0.080–0.511)], and ex-vivo chemosensitivity was a potential predictive factor for OS [p = 0.078; 95% CI 0.696 (0.465–1.041)]. To conclude, the PharmaFlow PM platform is a rapid and valuable tool for predicting clinical response and outcomes in AML patients.

Development and Validation of a Novel Microbiome-Based Biomarker of Post-antibiotic Dysbiosis and Subsequent Restoration

Background: The human gut microbiota are important to health and wellness, and disrupted microbiota homeostasis, or “dysbiosis,” can cause or contribute to many gastrointestinal disease states. Dysbiosis can be caused by many factors, most notably antibiotic treatment. To correct dysbiosis and restore healthier microbiota, several investigational microbiota-based live biotherapeutic products (LBPs) are in formal clinical development. To better guide and refine LBP development and to better understand and manage the risks of antibiotic administration, biomarkers that distinguish post-antibiotic dysbiosis from healthy microbiota are needed. Here we report the development of a prototype Microbiome Health Index for post-Antibiotic dysbiosis (MHI-A).Methods: MHI-A was developed and validated using longitudinal gut microbiome data from participants in clinical trials of RBX2660 and RBX7455 – investigational LBPs in development for reducing recurrent Clostridioides difficile infections (rCDI). The MHI-A algorithm relates the relative abundances of microbiome taxonomic classes that changed the most after RBX2660 or RBX7455 treatment, that strongly correlated with clinical response, and that reflect biological mechanisms believed important to rCDI. The diagnostic utility of MHI-A was reinforced using publicly available microbiome data from healthy or antibiotic-treated populations.Results: MHI-A has high accuracy to distinguish post-antibiotic dysbiosis from healthy microbiota. MHI-A values were consistent across multiple healthy populations and were significantly shifted by antibiotic treatments known to alter microbiota compositions, shifted less by microbiota-sparing antibiotics. Clinical response to RBX2660 and RBX7455 correlated with a shift of MHI-A from dysbiotic to healthy values.Conclusion: MHI-A is a promising biomarker of post-antibiotic dysbiosis and subsequent restoration. MHI-A may be useful for rank-ordering the microbiota-disrupting effects of antibiotics and as a pharmacodynamic measure of microbiota restoration.

Unraveling heterogeneity within ACPA-negative rheumatoid arthritis: the subgroup of patients with a strong clinical and serological response to initiation of DMARD treatment favor disease resolution

Background Rheumatoid arthritis (RA) is a heterogeneous disease, as evidenced by the differences in long-term outcomes. This applies especially to anti-citrullinated protein antibodies (ACPA)-negative RA, where a proportion achieves sustained DMARD-free remission (SDFR; sustained absence of synovitis after DMARD cessation). Differentiation of RA patients who will achieve SDFR can guide personalized treatment/tapering strategies. Although this subgroup remains scarcely discerned, previous research demonstrated that these RA patients are characterized by an early clinical response (DAS remission after 4 months) after DMARD start. We studied whether, in addition to this clinical response, a specific biomarker response can further distinguish the subgroup of RA patients most likely to achieve SDFR. Methods In 266 RA patients, levels of 12 biomarkers (SAA/CRP/MMP-1/MMP-3/resistin/leptin/IL-6/TNF-R1/YKL-40/EGF/VEGF/VCAM-1), in the first 2 years after diagnosis, were studied in relation to SDFR, stratified for ACPA status. Subsequently, biomarkers associated with SDFR development were combined with early DAS remission to study its additional value in defining subgroups. Since most biomarker levels are not routinely measured in clinical practice, we explored how this subgroup can be clinically recognized. Results ACPA-negative RA patients achieving SDFR were characterized by high baseline levels and stronger decline in MMP-1/MMP-3/SAA/CRP after DMARD-start, respectively 1.30×/1.44×/2.12×/2.24× stronger. This effect was absent in ACPA-positive RA. In ACPA-negative RA, a strong biomarker decline is associated with early DAS remission. The combination of both declines (clinical, biomarker) was present in a subgroup of ACPA-negative RA patients achieving SDFR. This subgroup can be clinically recognized by the combination of high baseline CRP levels (≥ 3 times ULN), and early DAS remission (DAS4 months < 1.6). This latter was replicated in independent ACPA-negative RA patients. Conclusions ACPA-negative RA patients with early DAS remission and a strong biomarker response (or baseline CRP levels ≥ 3× ULN) are most likely to achieve SDFR later on. This could guide personalized decisions on DMARD tapering/cessation in ACPA-negative RA.