Leveraging mathematical modeling to analyze nonadherence for hydroxyurea therapy in sickle cell disease.

Nonadherence is common in individuals with sickle cell disease (SCD) on hydroxyurea therapy and can be observed with waning improvements in hematologic parameters or biomarkers like mean cell volume and fetal hemoglobin level over time. We modeled the impact of hydroxyurea nonadherence on longitudinal biomarker profiles. We estimated the potential nonadherent days in individuals exhibiting a drop in biomarker levels by modifying the dosing profile using a probabilistic approach. Incorporating additional nonadherence using our approach besides existing ones in the dosing profile improves the model fits. We also studied how different patterns in adherence give rise to various physiological profiles of biomarkers. The key finding is consecutive days of nonadherence are less favorable than when nonadherence is interspersed. These findings improve our understanding of nonadherence and how appropriate intervention strategies can be applied for individuals with SCD susceptible to the severe impacts of nonadherence.

Mathematical Modeling of Hydroxyurea Therapy in Individuals with Sickle Cell Disease.

Sickle cell disease (SCD) is a chronic hemolytic anemia affecting millions worldwide with acute and chronic clinical manifestations and early mortality. While hydroxyurea (HU) and other treatment strategies managed to ameliorate disease severity, high inter-individual variability in clinical response and a lack of an ability to predict those variations need to be addressed to maximize the clinical efficacy of HU. We developed pharmacokinetics (PK) and pharmacodynamics (PD) models to study the dosing, efficacy, toxicity, and clinical response of HU treatment in more than eighty children with SCD. The clinical PK parameters were used to model the HU plasma concentration for a 24 h period, and the estimated daily average HU plasma concentration was used as an input to our PD models with approximately 1 to 9 years of data connecting drug exposure with drug response. We modeled the biomarkers mean cell volume and fetal hemoglobin to study treatment efficacy. For myelosuppression, we modeled red blood cells and absolute neutrophil count. Our models provided excellent fits for individuals with known or correctly inferred adherence. Our models can be used to determine the optimal dosing regimens and study the effect of non-adherence on HU-treated individuals.

Effect of Clinical, Biochemical, and Genetic Variations on Medical Management in Filarial Chyluria: A Prospective Study at a Tertiary Care Centre in North India.

Objective To analyze the effect of clinical, biochemical factors, and Mannose Binding Lectin 2 (MBL2) gene variations on medical management in filarial chyluria (FC) patients. Material and methods We conducted a study between March 2013 and April 2016. MBL2polymorphisms were genotyped in confirmed 101 medically-treated cases of FC. Demographic, clinical, and biochemical variables were compared between remission and failure groups. Genotyping of MBL2 codon 54 and promoter -221 were undertaken by polymerase chain reaction. Genotype frequencies were compared with clinical and biochemical variables and medical treatment outcomes (remission/failure). The association between genotypes and treatment response was estimated by OR and 95% CI and generated by the chi-square test. Results The mean age was 36.9±10.28-years and the male-female ratio was 3:1.2. Sixty-six patients had remission (Group-A) while 35 had recurrence (Group-B) at a mean follow-up of 21 months. The success rate for medical therapy was 65.35%. There was no statistical difference observed in the demographic profile of the two groups. On multivariate analysis, patients in Group-B had a higher grade of chyluria (p=0.005), had experienced greater number of disease attacks in the past (p=0.022), and had higher urinary triglyceride levels (TG) (p<0.001) as compared to Group-A patients. A significant association of MBL2 codon 54 genotypes was observed with the recurrent presentation of chyluria (p=0.044), grade of chyluria (p=0.028), and urinary TGs (p=0.001). However, genotype distribution at -221 did not show association with clinical and biochemical parameters of FC patients. The distribution of genotypes at codon 54 differed significantly between remission and failure/recurrence group; the variant genotype BB was significantly higher in the recurrence or failure group (OR:6.00; 95%CI, 1.00-35.91; p=0.050). However, frequencies of variant genotype YX and recessive group YX+XX of MBL2 -221 promoter was higher in remission group (OR:2.97;95%CI, 1.23-7.13; p=0.018 and OR:2.76; 95%CI, 1.80-6.50; p=0.020), respectively, showing that genetic variant may be associated with response to medical therapy. Conclusion Higher grade of chyluria, a higher number of disease attacks in the past, and higher urinary TGs levels were clinical predictors of poor response to medical treatment. Our results showed that the variants of MBL2 genes have an impact on treatment outcomes in FC patients. These observations may be limited by sample size.

Pesticide Risk and Recurrent Pregnancy Loss in Females of Subhumid Region of India.

OBJECTIVE: The objective of this study is to determine the level of pesticides and their role in cases of recurrent pregnancy loss (RPL). MATERIALS AND METHODS: This was designed as a case-control study. Gas chromatography was used to characterize the pesticide level in 70 cases and 70 controls. Case refers to women with RPL, whereas controls refer to women with full-term delivery. RESULTS: A higher level of pesticide, namely beta-hexachlorocyclohexane, malathion, chlorpyrifos, and fenvalerate was found in the case group as compared to control group (P < 0.05). CONCLUSIONS: The present study suggests that high exposure of pesticide (organochlorine and organophosphates) may increase the risk of RPL in females of the subhumid region of India.

Duplication mutation in CHIT1 gene is associated with poor response to medical therapy in patients affected with filarial chyluria.

We explore the impact of CHIT1 gene mutation on clinical, biochemical parameters and response to outcome (remission/failure) of medical treatment in North Indian filarial chyluria (FC) patients. Data of 101 subjects of FC treated medically between March 2013 and April 2016 in whom CHIT1 gene polymorphism was determined were analyzed. Filarial etiology was confirmed by DEC-provocative test, immuno-chromatographic test and IgG/IgM-combo rapid antibody test. CHIT1 gene polymorphism was genotyped by polymerase chain reaction. Of 101 patients (mean age, 36.9±10.28 years; male: female, 3:1.2), 66 experienced remission (Group-A) while 35 experienced relapse or failed to respond (Group-B). A significant association was observed between CHIT1 genotypes and higher grade of disease (p= 0.001). Wild-type, heterozygous and homozygous mutant frequencies of CHIT1 genotypes were 78.6%, 72.5% and 27.8% in remission and 21.4%, 27.5% and 72.2%, in recurrence/failure, respectively. Our results showed that patients with mutant genotype (TT) of CHIT1 gene showed significantly higher rate of recurrence or failure to medical therapy than wild type (HH) genotypes [OR (95% CI) = 9.53 (1.84-49.21), p=0.011]. This preliminary study showed the impact of CHIT1 gene variants on treatment outcome in FC patients. This observation needs to be confirmed using studies with larger numbers of FC patients.

The two-component signalling networks of Mycobacterium tuberculosis display extensive cross-talk in vitro.

Two-component systems (TCSs), which contain paired sensor kinase and response regulator proteins, form the primary apparatus for sensing and responding to environmental cues in bacteria. TCSs are thought to be highly specific, displaying minimal cross-talk, primarily due to the co-evolution of the participating proteins. To assess the level of cross-talk between the TCSs of Mycobacterium tuberculosis, we mapped the complete interactome of the M. tuberculosis TCSs using phosphotransfer profiling. Surprisingly, we found extensive cross-talk among the M. tuberculosis TCSs, significantly more than that in the TCSs in Escherichia coli or Caulobacter crescentus, thereby offering an alternate to specificity paradigm in TCS signalling. Nearly half of the interactions we detected were significant novel cross-interactions, unravelling a potentially complex signalling landscape. We classified the TCSs into specific 'one-to-one' and promiscuous 'one-to-many' and 'many-to-one' circuits. Using mathematical modelling, we deduced that the promiscuous signalling observed can explain several currently confounding observations about M. tuberculosis TCSs. Our findings suggest an alternative paradigm of bacterial signalling with significant cross-talk between TCSs yielding potentially complex signalling landscapes.