Scientific Program

Conference Series Ltd invites all the participants across the globe to attend 11th Diabetologists Conference & Drug Market Summit New York, USA.

Day 2 :

OMICS International Diabetologists 2018 International Conference Keynote Speaker Irina Kurnikova photo

Irina Kurnikova - MD, PhD, Professor of Medicine, RUDN University, Moscow, Russia She has become Doctor of Medical Sciences (PhD) in 2010, the first academic degree (MD) received at the age of 28 years. Dealing with Problems of Endocrinology for over 20 years. She had led a course of Endocrinology at the Medical Academy (Izhevsk, Russia), was the Head of Endocrinology  department at the Russian Scientific Center of Medical  Rehabilitation and Health Resort (Moscow, Russia). Currently she teaches at Peoples' Friendship University of Russia, curator of the Scientific Direction Endocrinology. She has published more than 30 articles in well-known journals, the author of 25 books and tutorials in Russian language. Author of 10 patents for inventions.


Statement of the Problem: Study of heart rate variability indices allows not only to identify already existing disorders with the system of regulation and adaptation, but also to predict the risk of developing diseases by measuring the overall stress of regulatory mechanisms, neurohumoral regulation of the heart and the  relationship between sympathetic and parasympathetic parts of the autonomic nervous system.
Purpose: Is to assess the impact of diabetes mellitus on mechanisms of autonomic regulatory at the different stages of carbohydrate metabolism disturbance.
Methodology & Theoretical Orientation: At the first stage of this study, patients were divided into several groups. The group of patients without metabolic disorders as the primary cause of the disease - group 1 (n=27); patients with abdominal obesity, hypertension, dyslipidemia - metabolic syndrome - group 2 (n=33); group with symptomatic of DT 2 - group 3b (n=62) at the stage of clinically expressed disorders. Group 3a (n=39) - patients with DT 2 and HTN with normal body weight (endogenous insulin at the lower limit of the norm or below). At the second stage patients with DT 2 (101 people) were divided in four age group: 20-30 years, 31-40 years, 41-50 years,51-60 years of age. All patients were evaluated autonomic regulation by the method of spectral analysis of daily variability of the heart rhythm power spectrum of oscillation in three frequency bands: 0,004-0,08 Hz (very low frequency – VLF), 0,09-0,16 Hz (low frequency – LF), 0,17-0,5 Hz (high frequency – HF). The selection of three frequency ranges is due to differences in their formation. The low frequency range reflects the activity of the sympathetic system on the segmental level, the high-frequency range, the activity of parasympathetic nervous system at the segmental level.
Findings: Simultaneous progressive increase in the power spectra of low-frequency and high-frequency waves at the stages of the progression of metabolic disturbances indicates the transition of the mechanisms of vegetative regulation to a higher energy-consuming level, and the decrease in VLF is about the centralization of regulation and depletion of body resources. Evaluation of spectral analysis revealed a significant increase in the power of ULF% waves in patients with type 2 diabetes, which indicates disruption in adaptation and violation of autonomic regulation of heart rhythm. The revealed significant difference in the analysis of the centralization index in groups with metabolic syndrome and type 2 diabetes with obesity and hypertension emphasizes the importance of the stages of carbohydrate metabolism disorders. Changing the IC towards the increase at the stages of the progression of the violations of the carbohydrate metabolism testifies to the activation of the central contour of regulation and the gradual transition of systemic vegetative regulation from the control level to the management level. Patients with diabetes at the age of 30-40 years we have seen a decrease in parasympathetic activity, which is more typical for patients the next decade of life. Since the age of 41, there was considerable centralization on mechanism of regulation (increase VLF), which usually starts 10-15 years later. The decrease in the total power spectrum on the background of inadequate compensator of diabetes showed decrease of reserve opportunities of the organism.

Keynote Forum

Sarah H Elsea

Baylor College of Medicine, USA

Keynote: A multi-omics precision medicine approach to diagnosis of inborn errors of metabolism

Time : 11:00-11:35

OMICS International Diabetologists 2018 International Conference Keynote Speaker Sarah H Elsea photo

Sarah H Elsea is a Professor of Molecular and Human Genetics at Baylor College of Medicine and the Senior Director of Biochemical Genetics at Baylor Genetics. She has received her BS in Chemistry with a minor in Biology from Missouri State University and a PhD in Biochemistry from Vanderbilt University. She has completed her Postdoctoral Fellowships in Molecular and Biochemical Genetics at the Baylor College of Medicine and is a Board-Certified Geneticist through the American Board of Medical Genetics and Genomics. She held Faculty appointments at Michigan State University and the Medical College of Virginia at Virginia Commonwealth University prior to returning to Baylor College of Medicine. Her research is focused on the discovery, pathomechanisms, diagnosis, and treatment of rare disease, particularly neurodevelopmental and neurometabolic disorders. She is a Member of several professional societies and has authored more than 90 scientific and lay articles.


Metabolomics is the study of the distinctive chemical fingerprint produced by specific cellular processes. Untargeted mass spectrometry-based metabolomic profiling for small molecules in body fluids is an emerging technique used to produce and analyze this chemical fingerprint. This technology holds the promise of providing new insights into human disease states and serving as a primary diagnostic tool for novel and previously characterized inborn errors of metabolism (IEM), as well as for the identification of biomarkers of disease and treatment. Clinical metabolomic profiling allows for parallel screening of hundreds of metabolites in a single biological specimen. On average, ~900 small molecules are detected in a given plasma sample with a core group of ~350 analytes found in all specimens tested to date. The analytes detected encompass numerous classes of small molecule biomarkers including acylcarnitine’s, amino acids, bile acids, carbohydrates, lipids, and nucleotides. In addition, metabolomic data in many cases affords a much richer view of a patient's metabolic disturbance by identifying: (1) elevated metabolites located far upstream of the genetic defect, (2) treatment related compounds, including commonly tested therapeutic drug monitoring analytes, and (3) spectrally unique analytes that are not yet associated with a biochemical phenotype. In our clinical experience, the integration of whole exome sequencing data with the metabolomics profile has improved the interpretation of genetic variants, including ruling out the diagnosis of IEMs, as well as supporting a specific diagnosis, and for the identification of new disease and/or treatment biomarkers. For undifferentiated clinical phenotypes such as intellectual disability, hypotonia, autism, or seizures, many different tests involving different sample types are often needed for diagnosis. This can lead to prohibitive costs and ongoing diagnostic odysseys. Data will be presented on genomic and metabolomic profiling of previously non-diagnostic cases which pointed to genetic disorders such as aromatic amino acid decarboxylase deficiency, GABA transaminase  deficiency, adenylosuccinate lyase deficiency, and peroxisome biogenesisdisorders, illustrating the powerful synergy of genomic and metabolomic analysis in determining the pathogenicity of variants of uncertain significance. Ultimately, a clinical systems biology approach to the integration clinical data with genomic, transcriptomic, epigenomic, proteomic, and metabolomics data will provide a comprehensive precision medicine approach to improve understanding of natural biological variation and to improve diagnosis and management of disease.

Keynote Forum

Hui Feng

Boston University School of Medicine, USA

Keynote: Differential dependence of the TCA cycle in triple-negative breast cancer cells

Time : 11:35-12:10

OMICS International Diabetologists 2018 International Conference Keynote Speaker Hui Feng photo

Hui Feng has her expertise in Zebrafish Genetics and Cancer  Therapeutics. Her application of innovative Zebrafish model system led to uncovery of novel metabolic pathways important for survival and proliferation of MYC-dependent leukemic cells. She has expanded her studies of this metabolic pathway into multiple MYC-driven cancers, including triple-negative breast cancer.


Statement: Despite the demonstrated role of  glutamine in the growth and survival of Triple-Negative Breast Cancer (TNBC) cells, how glutamine is utilized in TNBC cells remains unclear. The tricarboxylic acid (TCA) cycle is a central route for oxidative phosphorylation in cells, and fulfills their bioenergetic, biosynthetic, and redox balance requirements. Our research aims to understand whether TNBC cells metabolize glutamine via the TCA cycle (i.e., glutamine anaplerosis). The key cycle intermediate α-ketoglutarate (α-KG) serves as the entry point for glutamine anaplerosis. α-KG can then be converted to succinyl-CoA by the α-KG dehydrogenase complex (KGDHC) through oxidative phosphorylation, or to isocitrate by isocitrate dehydrogenase (IDH2) through reductive carboxylation pathways.
Findings: Here, we show that glutamine anaplerosis is critical for survival and growth of human TNBC cells. However, the dependence of human TNBC cells on KGDHC and IDH2 varies. In our presentation, we will discuss the potential mechanisms underlying the differential dependence of glutamine anaplerosis in human TNBC cells.
Conclusion & Significance: Overall, our studies provide compelling evidence to support metabolic dependence of TNBC cells on the TCA cycle, and also reveal the various pathways they may utilize in the TCA cycle.