Good effort.This will lead to  lot of new knowledge on Urology and kidney related diseases

Dear Jakhongir,

It is a very interesting project. I suggest that you take a look on the recent advances in this field. For example, H-NMR has been utilized for profiling of urinary tract infection.

Ekaterina Nevedomskaya et al. have published an article entitled " 1H NMR-based metabolic profiling of urinary tract infection: combining multiple statistical models and clinical data" and the conclusions emerged from their study:

"In the current paper we used a metabolomics approach to profile UTI, which is on the one hand one of the most common infectious diseases among the adults, and on the other hand a disease that still lacks markers of morbidity. Using 1H NMR profiles of urine we generated various statistical models: (a) discriminating UTI patients and control subjects, (b) following the recovery process of UTI patients and (c) associating urine metabolic content with bacterial contamination. The discriminative model was able to classify most of the independent samples correctly according to their diagnosis, which indicates its high predictive ability. Comparing the sets of molecules derived from different analyses, we concluded that some of the compounds (e.g. trimethylamine and acetate) can be attributed to the effect of bacterial contamination of urine; others (e.g. para-aminohippuric acid, scyllo-inositol) can be considered markers of morbidity."

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3483096/

https://www.researchgate.net/publication/233336554_1H_NMR-Based_Metabolic_Profiling_of_Urinary_Tract_Infection_Combining_Multiple_Statistical_Models_and_Clinical_Data

On the other hand, Haitao Lv et al. have used LC-MS as an Integrated Metabolomic Profiling Approach for Infectious Diseases Research. The following is the publication abstract for quick view:

Metabolomic profiling offers direct insights into the chemical environment and metabolic pathway activities at sites of human disease. During infection, this environment may receive important contributions from both host and pathogen. Here we apply untargeted metabolomics approach to identify compounds associated with an E. coli urinary tract infection population. Correlative and structural data from minimally processed samples were obtained using an optimized LC-MS platform capable of resolving ∼2300 molecular features. Principal components analysis readily distinguished patient groups and multiple supervised chemometric analyses resolved robust metabolomic shifts between groups. These analyses revealed nine compounds whose provisional structures suggest candidate infection-associated endocrine, catabolic, and lipid pathways. Several of these metabolite signatures may derive from microbial processing of host metabolites. Overall, this study highlights the ability of metabolomic approaches to directly identify compounds encountered by, and produced from, bacterial pathogens within human hosts.

http://europepmc.org/articles/PMC3746514/

Other important publications which may be helpful are contained in the following links:

http://jac.oxfordjournals.org/content/65/suppl_3/iii25.full

https://www.hindawi.com/journals/ab/2014/543974/

Hoping this will be helpful,

Rafik

Article 1H NMR-Based Metabolic Profiling of Urinary Tract Infection:...

Dear Dr. Karman,

Thank you for your detailed and clear answer. I appreciate your support.