Aug
13
Tue
2013
Invited Talk: Applying Machine learning for Automated Identification of Patient Cohorts @ Sathyam Hall
Aug 13 @ 2:40 pm – 3:05 pm

SriSairamSrisairam Achuthan, Ph.D.
Senior Scientific Programmer, Research Informatics Division, Department of Information Sciences, City of Hope, CA, USA


Applying Machine learning for Automated Identification of Patient Cohorts

Srisairam Achuthan, Mike Chang, Ajay Shah, Joyce Niland

Patient cohorts for a clinical study are typically identified based on specific selection criteria. In most cases considerable time and effort are spent in finding the most relevant criteria that could potentially lead to a successful study. For complex diseases, this process can be more difficult and error prone since relevant features may not be easily identifiable. Additionally, the information captured in clinical notes is in non-coded text format. Our goal is to discover patterns within the coded and non-coded fields and thereby reveal complex relationships between clinical characteristics across different patients that would be difficult to accomplish manually. Towards this, we have applied machine learning techniques such as artificial neural networks and decision trees to determine patients sharing similar characteristics from available medical records. For this proof of concept study, we used coded and non-coded (i.e., clinical notes) patient data from a clinical database. Coded clinical information such as diagnoses, labs, medications and demographics recorded within the database were pooled together with non-coded information from clinical notes including, smoking status, life style (active / inactive) status derived from clinical notes. The non-coded textual information was identified and interpreted using a Natural Language Processing (NLP) tool I2E from Linguamatics.

Delegate Talk: Inefficient NETosis: Cause for Predisposition to Recurrent Infections in Type 2 Diabetes @ Acharya Hall
Aug 13 @ 6:18 pm – 6:25 pm
Delegate Talk: Inefficient NETosis: Cause for Predisposition to Recurrent Infections in Type 2 Diabetes @ Acharya Hall | Vallikavu | Kerala | India

Manjunath Joshi, Apoorva Lad, Bharat Prasad Alevoor, Aswath Balakrishnan, Lingadakai Ramachandra and Kapaettu Satyamoorthy


 

Pathological conditions during Type 2 Diabetes (T2D) are associated with elevated risk for common community acquired infections due to poor glycemic control. Multiple studies have indicated specific defects in innate and adaptive immune function in diabetic subjects. Neutrophils play an important role in eliminating pathogens as an active constituent of innate immune system. Apart from canonically known phagocytosis mechanism, neutrophils are endowed with a unique ability to produce extracellular traps (NETs) to kill pathogens by expelling DNA coated with bactericidal proteins and histone. NETosis is stimulated by diverse bacteria and their products, fungi, protozoans, cytokines, phorbol esters and by activated platelets. Considering deregulation of metabolic and immune response pathways during pathological state of diabetes and NETosis as a potential mechanism for killing bacteria, we therefore, investigated whether hyperglycemic conditions modulate formation of neutrophil NETs and attempted to identify underlying immunoregulatory mechanisms. Freshly isolated neutrophils from normal individuals were cultured in absence or presence of high glucose (different concentrations) for 24 hours and activated with either LPS (2 mg/ml) or PMA (20 ng/ml) or IL-6 (20 ng/ml) for 3 hours. NETs were visualized and quantified by addition of DNA binding dye SYTOX green using fluorescence microscope and fluorimetry. NETs were quantified in Normal and diabetic subjects. Serum IL-6 levels were measured using ELISA technique. NETs bound elasatse were quantified in normal and diabetic subjects in presence or absence of DNase. Bacterial killing assays were performed upon infecting E.coli with activated neutrophils from normal and diabetic subjects. Microscopy and fluorimetry analysis suggested dramatic impairment in NETs formation under high glucose conditions. Extracellular DNA lattices formed in hyperglycemic conditions were short lived and unstable leading to rapid disintegration. Subsequent, time course experiments showed that NETs production was delayed in hyperglycemic conditions. To validate our findings more closely to clinical conditions, we investigated the neutrophil activation and NETs formation in diabetic patients. Upon stimulation with LPS for three hours, neutrophils from diabetic subjects responded weakly to LPS and lesser NETs were formed; whereas, neutrophils from normal individuals showed robust release of NETs. In few patients we found short and imperfect NETs in basal conditions suggesting constitutive activation of neutrophils in diabetic subjects. Interestingly, NETs bound elastase activity was reduced in diabetes subjects when compared to non-diabetic individuals, indicating a dysfunction of one of the important protein component of NETs during diabetes. Neutrophils from diabetic subjects released higher levels of IL-6 without any stimulation suggesting an existence of constitutively activated pro-inflammatory state. IL-6 induced NETs formation and was abrogated by high glucose. Weobserved that glycolysis inhibitor 2-DG resensitize the high glucose attenuated LPS and IL-6 induced NETs. a) NETs are influenced by glucose homeostasis, b) IL-6 as potent inducer of energy dependent NETs formation and c) hyperglycemia mimics a state of constitutively active pro-inflammatory condition in neutrophils leading to reduced response to external stimuli making diabetic subjects susceptible for infections.