Integrated clinical and metabolomic analysis of dengue infection shows molecular signatures associated with host-pathogen interaction in different phases of the disease.

PURPOSE: Dengue is a mosquito vector-borne disease caused by the dengue virus, which affects 125 million people globally. The disease causes considerable morbidity. The disease, based on symptoms, is classified into three characteristic phases, which can further lead to complications in the second phase. Molecular signatures that are associated with the three phases have not been well characterized. We performed an integrated clinical and metabolomic analysis of our patient cohort and compared it with omics data from the literature to identify signatures unique to the different phases. METHODS: The dengue patients are recruited by clinicians after standard-of-care diagnostic tests and evaluation of symptoms. Blood from the patients was collected. NS1 antigen, IgM, IgG antibodies, and cytokines in serum were analyzed using ELISA. Targeted metabolomics was performed using LC-MS triple quad. The results were compared with analyzed transcriptomic data from the GEO database and metabolomic data sets from the literature. RESULTS: The dengue patients displayed characteristic features of the disease, including elevated NS1 levels. TNF-α was found to be elevated in all three phases compared to healthy controls. The metabolic pathways were found to be deregulated compared to healthy controls only in phases I and II of dengue patients. The pathways represent viral replication and host response mediated pathways. The major pathways include nucleotide metabolism of various amino acids and fatty acids, biotin, etc. CONCLUSION: The results show elevated TNF-α and metabolites that are characteristic of viral infection and host response. IL10 and IFN-γ were not significant, consistent with the absence of any complications.

Identification of clinical and psychosocial characteristics associated with perinatal depression in the south Indian population.

BACKGROUND: Longitudinal perinatal depression (PND) data is sparsely available in the Indian population. We have employed Edinburgh Postnatal Depression Scale (EPDS) to assess the prevalence and identify characteristics associated with PND in the south Indian population. PND was assessed longitudinally using EPDS scores with traditional cut-off approach as well as a novel method of latent class mixture modeling (LCMM). The LCMM method, to the best of our knowledge, has been used for the first time in the Indian population. METHODS: Three hundred and forty seven women, predominantly from economically-weaker sections of rural and urban South India were longitudinally assessed for antenatal depression (AD) and postnatal depression (PD) using EPDS cutoff-scores ≥13 and ≥10, respectively. Uni/multivariable analyses were used to identify PND associated characteristics. LCMM was then implemented, followed by risk characteristics identification. RESULTS: PND prevalence from traditional approach was 24.50 % (12.68 % AD; 18.16% PD). Characteristics associated with PND were urban-site and recent adverse life events. Irregular menstrual history and chronic health issues were associated with AD and PD, respectively. Three distinct PND trajectories were observed from LCMM-analysis: low-risk (76.08%), medium-risk (19.89%) and high-risk (4.04%). Urban-site, recent adverse life events, irregular menstrual history and pregnancy complications were associated with medium-risk/high-risk trajectories. LIMITATIONS: EPDS is a screening tool and not a diagnostic tool for depression. Since the study population included women from economically-weaker sections, the results need verification in other socio-economic groups. CONCLUSIONS: Both the traditional cut-off-based approach and LCMM provided very similar conclusions regarding the prevalence of PND and characteristics associated with it. Higher PND prevalence was observed in urban women compared to rural women. In low-income countries, identifying risk characteristics associated with PND is a critical component in designing prevention strategies for PND related conditions because of the limited access to mental health resources.

The role of Lp-PLA2 and biochemistry parameters as potential biomarkers of coronary artery disease in Asian South-Indians: a case-control study.

BACKGROUND: Coronary artery disease (CAD) is the leading cause of death and disability worldwide. Lipoprotein associated phospholipase A2 (Lp-PLA2) is an emerging biomarker for inflammation that has shown association with CAD. Its significance in the Asian Indian population is not clearly known. We sought to compare the possible association of various biomarkers of atherosclerosis along with Lp-PLA2, in symptomatic individuals with CAD vs. healthy controls in Asian South-Indians. METHODS: We conducted a cross-sectional case control study at three centers in a South Indian population. A total of 100 CAD patients with acute coronary syndrome (ACS), 100 age and gender matched healthy controls participated, of which, 166 subjects or 83 case-control pairs with complete data for both participants were identified for the statistical analysis. Lp-PLA2 concentration and activity were measured using PLAC test and PLAC activity assay respectively (diaDexus Inc., San Francisco, CA, USA), while all other parameters were measured using standard commercially available kits. RESULTS: We enrolled a total of 200 subjects (mean age 50.7±9.6 years, 87.5% males). A total of 83 subjects completed the study in the CAD group (mean age 51 ±8.9 years, 85% males) and 83 subjects in the control group (mean age 50±8.9 years, 86.5% males). In the CAD group, Lp-PLA2 concentration positively correlated with TC (ρ=0.19, P=0.02), non-HDL-C (ρ=0.20, P=0.02), Lp-PLA2 activity (ρ=0.27, P=0.001) and Lp(a) (r=0.25, P=0.02). Lp-PLA2 activity correlated positively with TC (ρ=0.28, P=0.001), LDL-C (ρ=0.30, P<0.001), non-HDL-C (ρ=0.35, P<0.001), ApoB (ρ=0.35, P<0.001) and negatively correlated to HDL-C (ρ=-0.24, P=0.004). Cox proportionality hazards model revealed Lp-PLA2 concentration (ß=0.006, SE =0.002, P=0.009) to have positive association with the event of CAD, while negative association was observed for ApoA1 (ß=-0.06, SE =0.02, P=0.001). ROC analysis revealed that the highest quartile of Lp-PLA2 concentration to have area under curve (AUC) of 0.80 (95% CI, 0.65-0.9; P<0.001) with cut off value of >427 ng/mL and ApoA1 with AUC of 0.78 (95% CI, 0.70-0.85; P<0.001) with cut off value of ≤129.6 mg/dL with the optimum balance of sensitivity and specificity. CONCLUSIONS: In this study population, circulating plasma Lp-PLA2 was found to be elevated in CAD group. ApoA1 showed negative association and Lp-PLA2 concentration showed positive association with risk for CAD. In the highest quartile, Lp-PLA2 concentration had the best diagnostic utility. Our results support the hypothesis that Lp-PLA2 may be a potential risk marker for CAD in Asian Indians.