Metabolic Characteristics of Lean Diabetes in Rural and Semi-urban India and in the United States
Conditions: Malnutrition; Diabetes, Diabetes
Sponsor: Albert Einstein College of Medicine

PI: Meredith Hawkins, MD
1
Revised on 6/8/2016
2013-2191: METABOLIC CHARACTERISTICS OF LEAN DIABETES IN RURAL 
AND SEMI-URBAN INDIA AND IN THE UNITED STATES. 
From
THE DEPARTMENT OF ENDOCRINOLOGY DIABETES AND METABOLISM
CHRISTIAN MEDICAL COLLEGE
VELLORE -632004, INDIA.
  
                                       And
ALBERT EINSTEIN COLLEGE OF MEDICINE /MONTEFIORE MEDICAL CENTER
Bronx, NY 10461.USA.
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PI: Meredith Hawkins, MD
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INDEX
1 INTRODUCTION
1.1THERAPEUTIC AREA:
1.2 BACKGROUND AND SIGNIFICANCE:
1.3 SIGNIFICANCE:
1.4 PRELIMINARY DATA
1.5 Relevance to Project
2.0 OBJECTIVES:
2.1 OBJECTIVE 1
2.2 OBJECTIVE 2
2.3 OBJECTIVE 3
2.4 OBJECTIVE 4
2.5 OBJECTIVE 5
2.6OBJECTIVE 6
3.0 RATIONALE
3.1 RATIONALE FOR THE TRIAL FOR OBJECTIVE 1:
3.2 RATIONALE FOR THE TRIAL FOR OBJECTIVE 2:
3.3 RATIONALE FOR THE TRIAL FOR OBJECTIVE 3:
3.4 RATIONALE FOR THE TRIAL FOR OBJECTIVE 4:
4.0 OUTCOME
4.1 OUTCOME OF OBJECTIVE 1:
4.2 OUTCOME OF OBJECTIVE 2:
4.3 OUTCOME OF OBJECTIVE 3:
4.4 OUTCOME OF OBJECTIVE 4:
5.0 STUDY POPULATION AND RECRUITMENT: 
6.0 SUBJECT ELGIBLITY CRITERIA
6.1 INCLUSION CRITERIA:                                                                                                                               
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6.2 EXCLUSION CRITERIA: 
7.0 TREATMENT OF SUBJECTS:
7.1 VISIT PROCEDURE:
 TIMELINE Strengths of this proposal: 
8.0 ASSESMENTS
8.1PHYSICAL ASSESMENT;
8.2LABORATORY ASSESMENT:
8.3 In vivo clamp studies – General Conditions (Figure 6) 
8.4 Plasma measurements:
8.5 Analytical procedures
8.6 Substrate determination:
8.7 Measurement of insulin secretory response to meal challenge:
8.8 Fat  and Muscle Biopsies and Analysis:
9. STATISTICAL ANALYSIS 
10. STUDY TEAM
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PI: Meredith Hawkins, MD
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METABOLIC CHARACTERISTICS OF LEAN DIABETES IN RURAL AND SEMI-URBAN 
INDIA AND IN THE UNITED STATES. 
1 INTRODUCTION
BASIC INFORMATION:
1.1 THERAPEUTIC AREA:
India has the world’s highest prevalence of diabetes, expected to rise to 80 million by 
2030. This includes many patients with lean diabetes, with low body mass index (BMI) and 
severe complications of diabetes. Despite its prevalence in India and other countries and 
its dire health consequences to individuals with the disease, little is known about the 
aetiopathogenesis and the genotype-phenotype relationship, lean diabetes being a cluster 
of low birth weight individuals, MODY, lipododystrophic disease, type 1 diabetes and 
fibrocalcific disease. While rudimentary tests have suggested defects in both insulin 
secretion and action, no comprehensive metabolic studies have been performed. It is 
therefore unclear as to how these patients should be treated. The optimal therapeutic 
adjunct whether a suitable oralantidiabetic agent or insulin is not yet determined. Defining 
the metabolic defects of ‘lean’ diabetes should have tremendous therapeutic benefit for 
millions of patients with this elusive condition.
1.2 BACKGROUND AND SIGNIFICANCE:
1.2. Significance of Diabetes in Indian population and South Asians living in the 
United States:
Diabetes is rapidly becoming a global epidemic. India has the world’s highest prevalence 
of diabetes, expected to rise to 80 million by 2030 (1). As a consequence of rapid 
Westernization, many Indians are developing type 2 diabetes (T2DM). Of note, T2DM 
incidence in Indians rises sharply when body mass index (BMI) rises above 22 kg/m2 (2). 
Additionally, the diabetes population in India and other LMICs includes many patients with 
low BMI and severe complications of diabetes. Various reports suggest that these patients 
are surprisingly insulin resistant considering their lean body habitus. Some of these 
individuals have Fibrocalculous Pancreatic Diabetes (FCPD), in whom pancreatic calculi 
and/or ductal dilatation may contribute to the etiology of their disease (3). Many, however, 
are classified as Lean Diabetes, identified clinically by early onset, high insulin 
requirements, absence of pancreatic calculi or ductal dilation, and low BMI (typically 
<17kg/m2 at presentation). The majority of young adults with diabetes in India are likely to 
have FCPD or lean diabetes (3). Both conditions differ from type 1 diabetes by persistent 
C-peptide response to nutrient stimuli, and absence of ketosis and pancreatic beta cell 
autoimmunity markers (4). Lean diabetes tends to present in young adults between the 
ages of 20 and 40 and afflicts men and women at a 2:1 ratio. Despite its sizeable 
prevalence, lean diabetes remains a relatively unknown disease that stirs conflicting 
opinions regarding its classification, diagnostic criteria, and pathogenesis (5).  Of note, 
patients with lean diabetes appear to have elevated VLDL and triglycerides as well as 
insulin resistance based on insulin tolerance tests (6).
It has increasingly become apparent that marked ethnic variability in the clinical features of 
diabetes exists. Variability in the prevalence and pattern of disease among ethnic groups 
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can be secondary to both genetic and environmental modifying factors. South Asians  in 
the United States have a higher prevalence of diabetes than non-Hispanic whites, despite 
lower BMI and being younger in age (7). Studies in the United Kingdom have shown that 
migrant Indians have increased insulin resistance and hyperinsulinemia compared to 
Europeans (8). However, comprehensive metabolic studies of these individuals are 
lacking in the United States.  Careful metabolic ‘phenotyping’ and genotyping of South 
Asian individuals with lean diabetes would be very helpful to better understand this 
condition and develop appropriate therapeutic approaches. Our study aims to define the 
ethnic variability in clinical and metabolic characteristics of diabetes in South Asian 
population living in United States.
Insulin resistance in individuals with lean diabetes: There are currently very few 
publications on the entity known as ‘lean’ or ‘malnutrition’ diabetes. Numerous case 
reports, however have described a high degree of insulin resistance in some of these 
individuals (7, 8). Nonetheless, there is a debate to whether the mechanisms are 
attributable to the pancreatic beta-cell, skeletal muscle, adipose tissue, or other tissues.
1.2.2 Significance of fat mass in the etiology of insulin resistance:
It is a well-recognized yet intriguing concept that individuals at both ends of the weight 
spectrum have abnormal fat metabolism impacting insulin sensitivity. In obesity, increased 
fat mass promotes fatty acid flux to nonadipose tissues (9). In apparent contradiction, 
similar metabolic features are observed in lipodystrophy, including insulin resistance, 
hepatic steatosis, hyperlipidemia and diabetes (10). In both obesity and lipodystrophy, a 
storage defect within adipocytes (due either to engorgement with lipid or a paucity of 
adipocytes) leads to excess accumulation of triglyceride in non-adipose tissues. Increased 
free fatty acid (FFA) availability in both conditions inhibits the effects of insulin on hepatic 
and peripheral glucose metabolism (11,12). Indeed, systemic insulin resistance is 
associated with increased adipose tissue lipolysis and resistance to the anti-lipolytic 
effects of insulin (13,14). Increased hepatic fat content is receiving particular attention as a 
potential causative factor of insulin resistance (15). In addition to the well-established 
associations between IHTG and hepatic insulin resistance (16), our preliminary data 
(below) demonstrate an intriguing association with peripheral insulin resistance. Based 
upon the relationships described above, we hypothesize that deficient fat stores in 
individuals with lean diabetes may promote hepatic triglyceride storage, leading to 
elevated circulating fatty acids and insulin resistance.
1.3 SIGNIFICANCE:
It is highly intriguing, in the twenty-first century, to encounter a condition as prevalent as 
lean diabetes yet about which so much remains to be learned. The diabetes literature is 
dominated by studies conducted in high income countries, where this condition is never 
encountered. These would be the first truly comprehensive studies defining the body 
composition and metabolic features of lean diabetes. Scientifically, this application will 
explore a novel frontier in the intriguing dynamic between fat metabolism and insulin 
sensitivity. 
Clinical relevance: Given India’s high prevalence of diabetes, of which a substantial yet 
poorly defined proportion is likely to have lean diabetes, this proposal would have 
considerable clinical relevance for India and many other countries. In the absence of 
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sufficient information about this condition and its management, many lean diabetes 
patients are labeled as type 1 diabetes and are prescribed insulin. Unfortunately, 
inconsistent food availability among poor patients results in many insulin-induced 
hypoglycemic deaths. A better understanding of the metabolic defects of this condition 
should be very helpful in pointing towards more appropriate therapeutic approaches. 
Specifically, being able to clearly demonstrate that these subjects are insulin resistant 
would favor the use of safer, cheaper oral insulin sensitizing agents. This application 
therefore seeks to shift current clinical practice paradigms for underweight patients with 
diabetes, by studying a novel hypothesis concerning the pathophysiology of lean 
diabetes. Defining the metabolic defects of lean diabetes could therefore have 
tremendous therapeutic benefit for millions of patients with this elusive condition.
1.4 PRELIMINARY STUDIES  
Moderate elevations in FFA levels characteristic of T2DM impair glucose 
effectiveness: These studies were performed at Einstein, and highlight the impact of 
abnormal fatty acid flux on glucose metabolism. In previously reported studies, FFA levels 
were elevated in poorly controlled T2DM subjects (377±46 mM) during glucose clamp 
studies, relative to age- and BMI-matched nondiabetic subjects (167±12 mM)(17). To 
determine the extent to which the ~2-fold elevations in FFA characteristic of poorly 
controlled T2DM contribute to defects in glucose metabolism, we infused nicotinic acid at 
0.015 mg/kg.min to lower FFA to nondiabetic levels in n=9 poorly controlled T2DM subjects 
(HbA1C = 10±1%, age = 49±3yr; BMI = 27±1 kg/m2)(18). We established steady state 
hormone and tracer conditions over the first four hours at normoglycemic glucose levels 
(90 mg/dl) and then abruptly raised glucose levels to 180 mg/dl for the final 2 hours of the 
studies. Normalizing FFA levels essentially restored the endogenous glucose production 
(EGP) response to hyperglycemia. Indeed, EGP was reduced by 41±8% with the onset of 
hyperglycemia when FFA were lowered with nicotinic acid (p<0.001), which was 
comparable to the response in nondiabetic individuals. These data indicate that moderately 
increased FFA levels could contribute substantially to abnormal glucose metabolism in 
T2DM. 
Increased Intrahepatic Triglyceride (IHTG) Is Associated with Peripheral Insulin 
Resistance: These studies were performed at Einstein. A total of 56 nondiabetic subjects 
(49 M) ranging in age from 19 to 78 yrs underwent five hour hyperinsulinemic (40 
mU/m2.min), euglycemic (90 mg/dl) ‘clamp’ studies, using 3-3H-glucose to quantify insulin-
mediated glucose uptake. Mean glucose uptake was 10.2+0.4 mg/kg.min among normal 
weight subjects (BMI<25; n=15) vs. 8.0+0.8 mg/kg.min in overweight-to-obese subjects 
(BMI>25; n=41; ~22% reduction, p<0.001), with a significant, inverse correlation between 
BMI and glucose uptake (r=-0.386, p=0.004). As noted above, altered fat deposition may 
contribute to insulin resistance in humans. Since visceral (VF) and deep subcutaneous fat 
(SF) depots may contribute to IHTG via hepatic delivery of free fatty acids (FFA), we 
simultaneously measured intramyocellular lipid (IMCL), IHTG, VF and abdominal SF in a 
subgroup of n=12 nondiabetic, nonobese individuals using noninvasive 1H magnetic 
resonance spectroscopy (MRS) and magnetic resonance imaging (MRI). Positive 
correlations were observed among IMCL, IHTG and VF. There were remarkably tight 
correlations between IHTG and peripheral (non-hepatic) insulin sensitivity (r = -0.87, p 
<0.001).  Intriguingly, however, there was a lack of correlation of insulin-stimulated 
glucose uptake with IMCL or other fat depots. These observations are consistent with 
studies in rodents in which decreasing IHTG levels improved muscle insulin action (19). 
Although the IHTG levels in these nonobese subjects were substantially lower than levels 
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reported in obesity and T2DM, the inverse correlation of IHTG with insulin sensitivity was 
exceptionally tight. This was presumably aided by the sensitive measures generated by in 
vivo 1H MRS and insulin ‘clamps’. This association between IHTG and insulin resistance 
at normal body weights demonstrates that fatty acid flux and tissue triglyceride content 
are important determinants of insulin sensitivity, even in the absence of obesity.
Deleterious Metabolic Effects of Low Birth Weight: These studies were performed at 
Christian Medical College India (CMC) in collaboration with University of Copenhagen. 
Nutrition in rural areas of India is still less than satisfactory. Hence, pregnant women often 
have insufficient protein intake, and the prevalence of low birth weight in India is endemic 
(26% of the babies born in rural India). These babies are more prone to diabetes in 
adulthood. A population-based cohort of 60 low birth weight (LBW) subjects and 60 normal 
birth weight (NBW) subjects, aged 18 to 22 years, was recruited from a rural area near 
Vellore. Insulin resistance was assessed by HOMA and by the glucose infusion rate 
required during hyperinsulinemic euglycaemic clamp studies (M-value). Body composition 
was measured by DEXA, and liver triglyceride content by MRS. Among these young 
subjects, with comparable BMI’s in both groups (~18 kg/m2), LBW was associated with a 
reduction 
in 
insulin 
sensitivity 
as 
assessed 
by 
HOMA 
(LBW=1.02+0.13 
vs. 
NBW=0.75+0.10, p<0.05) and lower total body fat content (LBW=7654+642 vs. 8559+542 
g, p<0.05). However, the M-value with this clamp technique was highly variable, and did 
not show a difference between groups. IHTG analysis is pending. While these studies only 
included nondiabetic subjects, these data suggested a relationship between LBW and 
insulin resistance, consistent with the increased propensity for diabetes in malnourished 
individuals later in life.
1.5 Relevance to Project: 
These data indicate that moderately increased FFA levels could contribute substantially to 
abnormal glucose metabolism in T2DM. The association between IHTG and insulin 
resistance at normal body weights demonstrates that fatty acid flux and tissue triglyceride 
content are important determinants of insulin sensitivity, even in the absence of obesity. 
While these studies only included nondiabetic subjects, these data suggested a 
relationship between LBW and insulin resistance, consistent with the increased propensity 
for diabetes in malnourished individuals later in life.
2.0 OBJECTIVES:
                2.1 Objective 1
(i)
To characterize body composition and hepatic lipid deposition in individuals 
with lean diabetes.
                2.2 Objective 2
(ii)
To characterize insulin’s ability to regulate glucose fluxes and inhibit lipolysis in 
individuals with lean diabetes.
                2.3 Objective 3
(iii)
To assess the insulin secretory response to meal challenge in individuals with 
lean diabetes
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          2.4 Objective 4  
    
(iv)
To characterize and study the gene expression profile of adipose tissue and 
skeletal muscle in individuals with lean diabetes.
       2.5 Objective 5
(v)
To understand the immunologic determinants of diabetes in the lean. 
       2.6 Objective 6
(vi)
To sequence the genes involved in monogenic forms of diabetes to identify the 
genetic variants and their association with lean diabetes
3.0 RATIONALE
3.1 RATIONALE FOR THE TRIAL FOR OBJECTIVE 1:
Of note, these studies aim to carefully characterize a condition about which little is known. 
Since there are no rigorous definitions differentiating lean diabetes from T2DM, we will 
classify the DM subject groups based upon their BMI ranges. To further increase the 
likelihood of correctly identifying lean diabetes, we will elicit a history of low birth weight 
and documented malnutrition in the lean diabetes subjects. We will also carefully exclude 
subjects with features of type 1 diabetes, excluding individuals who test positive for anti-
CAD, insulin and/or IC2 antibodies. 
The lack of weight matching between the two DM groups is an inevitable feature of the 
different pathophysiology of these conditions. To minimize the impact of a sizeable 
difference in BMI, we will select a T2DM group at the lower BMI range for this condition. 
As noted above, risk of T2DM among ethnic Indians begins to increase sharply above a 
BMI of 22 kg/m2. 
To increase the likelihood that the “nondiabetic comparators” will have a normal metabolic 
profile, we will select subjects with normal birth weight and no documented history of 
malnutrition, despite having a BMI in the target range. Of note, it is possible that these 
individuals will also demonstrate some metabolic consequences of decreased fat mass. If 
we document insulin resistance in the underweight nondiabetic group, we will consider 
adding a fourth group of normal weight, nondiabetic subjects that would be BMI-matched 
to the T2DM group (BMI 22-25 kg/m2).
DEXA scanning will quantify truncal fat and total body fat. If significant relationships are 
discovered between truncal fat content and metabolic endpoints, future studies will include 
a more comprehensive analysis of visceral vs. subcutaneous abdominal fat using CT 
scanning. 
3.2 RATIONALE FOR THE TRIAL FOR OBJECTIVE 2:
Dr. Hawkins and her research group have now performed more than eight hundred clamp 
studies in human subjects, and thus have considerable experience both in the execution 
of the studies and in data analysis. Indeed, the human liver is known to be exquisitely 
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sensitive to small changes in plasma insulin levels, such that small increases in insulin 
rapidly decrease glucose production yet have little effect on peripheral glucose uptake. 
Particular benefits of the proposed study design include the proposed stepped insulin 
clamp studies for measuring both hepatic and peripheral insulin action, and the pancreatic 
clamp study design to maintain stable hormone levels. The latter is particularly relevant to 
the low insulin phase of the study in which hepatic insulin action is determined. 
Insulin will be infused overnight prior to the studies in both DM groups, to correct the 
confounding effects of glucose-induced insulin resistance. A variable low-dose infusion of 
insulin will be initiated at 10 pm, and will be adjusted overnight based upon hourly glucose 
measurements to attain plasma glucose concentrations of 100 - 120 mg/dl prior to the 
start of the clamp study. This will ensure that all subjects will be studied under 
normoglycemic conditions. This gradual lowering of plasma glucose is intended to avoid 
activation of counter-regulatory responses. Indeed, the phenomenon of ‘glucose toxicity’ is 
recognized to cause reversible resistance to insulin at the level of the liver, muscle and 
adipocyte (20).
To what extent do increased FFA contribute to insulin resistance in the DM groups? As 
described above, there is substantial evidence that increased FFA levels in T2DM and 
obesity contribute to insulin resistance. Response to insulin’s anti-lipolytic effects will be 
explored in this proposal by following FFA levels during the stepped insulin clamp studies, 
with the hypothesis that defective fat storage in lean diabetes will increase FFA levels and 
contribute to insulin resistance. 
It could be argued that the proposed measures of body composition and insulin sensitivity, 
while highly sensitive and ‘state-of-the-art’, will be observational and will not prove 
causality. However, given the tremendous need for more knowledge about lean diabetes, 
it is essential to first do a thorough ‘metabolic phenotyping’ of individuals with lean 
diabetes. 
3.3 RATIONALE FOR THE TRIAL FOR OBJECTIVE 3:
While rudimentary tests in individuals with lean diabetes have suggested defects in both 
insulin secretion and action, no comprehensive metabolic studies have been performed. It 
is therefore unclear as to how these patients should be treated. 
3.4 RATIONALE FOR THE TRIAL FOR OBJECTIVE 4:
It is a well-recognized yet intriguing concept that individuals at both ends of the weight 
spectrum have abnormal fat metabolism impacting insulin sensitivity. In obesity, increased 
fat mass promotes fatty acid flux to nonadipose tissues (21). In apparent contradiction, 
similar metabolic features are observed in lipodystrophy, including insulin resistance, 
hepatic steatosis, hyperlipidemia and diabetes (22). In both obesity and lipodystrophy, a 
storage defect within adipocytes (due either to engorgement with lipid or a paucity of 
adipocytes) leads to excess accumulation of triglyceride in non-adipose tissues. Increased 
free fatty acid (FFA) availability in both conditions inhibits the effects of insulin on hepatic 
and peripheral glucose metabolism (23,24). Indeed, systemic insulin resistance is 
associated with increased adipose tissue lipolysis and resistance to the anti-lipolytic 
effects of insulin (25,26). Increased hepatic fat content is receiving particular attention as a 
potential causative factor of insulin resistance (27). In addition to the well-established 
associations between IHTG and hepatic insulin resistance (28), our preliminary data 
(below) demonstrate an intriguing association with peripheral insulin resistance. Based 
upon the relationships described above, we hypothesize that deficient fat stores in 
individuals with lean diabetes may promote hepatic triglyceride storage, leading to 
elevated circulating fatty acids and insulin resistance.
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4.0 OUTCOME
4.1 OUTCOME OF OBJECTIVE 1:
To define body composition (DEXA) and liver triglyceride content (MRI) as well as 
determine the presence of fibrocalcific pancreatic disease,  in young adults who have lean 
diabetes, based upon a history of established diabetes and malnutrition, without features 
of type 1 diabetes.
4.2 OUTCOME OF OBJECTIVE 2:
Hepatic insulin action: this will be determined as the ability of low infusion rates of insulin 
(20 mU/m2.min above basal requirements) to suppress glucose production during the “low 
insulin phase” of the clamp studies. 
Peripheral insulin action: this will be determined as the ability of high infusion rates of 
insulin to stimulate glucose uptake during the “high insulin phase” of the clamp studies. 
For the final two hours of the study, insulin infusion rates will be raised by a larger 
increment (80 mU/m2.min) above basal insulin requirements, to determine peripheral 
insulin sensitivity under maximally stimulated conditions.
Glucose kinetics: Rates of glucose appearance (Ra) and disappearance (Rd) and other 
indices of glucose turnover will be estimated using Steele equations (29). Endogenous 
glucose production will be determined by subtracting the rates of glucose infusion from 
the tracer-derived Ra.
Plasma hormone and substrate determinations: plasma insulin, free-insulin, C-
peptide, and glucagon concentrations will be measured by Core Analytical Lab at Albert 
Einstein College of Medicine (30). Plasma lactate, FFA and glycerol concentrations will be 
measured using spectrophotometric or colorimetric techniques (31,32,33).
6-6 D-glucose determinations: Initially, it is likely that these determinations will be 
performed at Einstein. Plasma samples for Gas Chromatography-Mass Spectroscopy 
(GC-MS) will be derivatized after protein precipitation to the aldonitrile pentacetate with 
hydroxylamine hydrochloride-acetic anhydride. GC/electron impact-mass spectrometry 
analysis will be performed on an Agilent model 6890/5973 with a 7673 Agilent 
autosampler (34).
4.3 OUTCOME OF OBJECTIVE 3:
Mixed meal tests have been proposed to have similar sensitivity and reproducibility to oral 
glucose tolerance testing (OGTT) for the detection of hyperglycemia and diagnosis of 
glucose intolerance (35,36) and we have substantial experience in performing these tests in 
older subjects.  Indeed, a standard mixed meal challenge, rather than an oral glucose 
challenge, represents a more physiologically relevant stimulus in that it may more closely 
mimic the metabolic changes experienced by individuals in daily life, and is better 
tolerated than an OGTT. It also represents a more integrated measure of nutrient 
metabolism than intravenous challenge tests, since it includes the contribution of the 
incretin hormones.  
We will study subjects following an overnight fast and after a test meal of 100 g CHO, 20 g 
protein, and 20 g fat.  Blood sampling will be performed through an indwelling intravenous 
catheter, fasting and 15, 30, 45, 60, 90, 120 and 180 minutes following the meal, for 
measurement of glucose, insulin and C-peptide levels. Plasma triglycerides and FFA 
levels will be measured fasting and at 60, 120 and 180 minutes. Subjects will be provided 
with a standard meal and snack to consume at home the night prior to the SMT and will 
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fast after 10 pm, in order to minimize metabolic variability between tests. Glucose and 
insulin levels will be used to calculate the area under the curve (AUC) using the 
trapezoidal method.  
Glucose-stimulated insulin secretion can be assessed using a variety of techniques, 
including hyperglycemic “clamp” studies and the frequently sampled intravenous glucose 
tolerance test.  However, these procedures could be considered to be less physiologic, as 
they do not capture the contribution of incretin hormones, and may be more burdensome 
for older subjects. Standard mixed-meal tests with frequent blood sampling and 
application of mathematical modeling have been used to evaluate insulin secretion, and 
have been reported to produce results comparable to more invasive and less physiologic 
tests (37,38). 
In collaboration with our colleague, Dr. Daniel Stein, indices of β-cell function will be 
estimated from plasma glucose and C-peptide concentrations using the oral minimal 
model of C-peptide secretion, with kinetics calculated from deconvolution of plasma C-
peptide concentrations measured during the standard mixed meal (39) and using 
parameters for C-peptide kinetics and volume of distribution as measured by Van Cauter 
et al (40). Insulin secretory dynamics can be broken down into dynamic and static 
components of β-cell responsivity to glucose. The dynamic responsivity index, termed 
Ψdynamic, measures the β-cell secretory response to the rate of change of glucose 
concentration. This measure approximates the first phase of insulin release and defines 
the response to a given increment in glucose. Conversely, the static responsivity index  
(Ψstatic) measures the beta cell secretory response to a given glucose concentration.  This 
static measure is believed to represent the provision of new insulin into the secretory pool. 
The two Phi factors can be combined into a Ψtotal.  The appropriateness of the insulin 
secretion for the prevailing degree of insulin resistance will be determined by the 
disposition index (DI) calculated as the Ψdynamic, Ψstatic and Ψtotal times the insulin sensitivity 
(41), which will be determined by the method of MatsudaError! Bookmark not defined., allowing 
calculation of a DI for subjects who do not undergo the euglycemic clamp. 
4.4 OUTCOME OF OBJECTIVE 4:
Biopsies: Participants will have fat biopsies performed in the periumbilical region 
approximately one month following the clamp study. A small ~1-2 cm cutaneous incision 
will be performed under local anaesthesia (Lidocaine 1%) and 1-2 g of adipose tissue will 
be obtained by open biopsy technique. A skeletal muscle biopsy of ~50-100 g will be 
obtained with a spring-loaded biopsy needle (Bard Instruments) in the mid-thigh region 
following local anesthesia extending into the muscle area. 
Adipose tissue specimens- Whole adipose tissue for analysis by rt-PCR will be 
immediately homogenized in Trizol (Life Technologies, Bethesda, MD) with a Tissumizer 
homogenizer. Remaining fresh adipose biopsy specimens will be immediately digested 
with collagenase type 1. Adipocytes will be subsequently separated from stromal cells by 
centrifugation and filtration. Macrophages will be separated from stromal cells by CD14+ 
specific antibody coated beads. Subsequent mRNA extraction and analysis of gene 
expression by real-time QPCR of each adipose tissue fraction will be performed..
Gene expression profile of following array of genes would be studied in adipose tissue and 
muscle.  
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1.
Carbohydrate Metabolism
2.
Lipid Metabolism
3.
Insulin signaling pathway
4.
Adipogenesis
5.
Energy metabolism
6.
Inflammation 
We will quantify adipose tissue macrophages with immunohistochemistry. To measure 
macrophage content in adipose tissue by immunohistochemistry, samples will be fixed 
and embedded in paraffin (42). For immunofluorescence, tissue sections will be stained 
with primary antibodies to human CD68 and PAI-1 followed by fluorescent secondary 
antibodies, and images quantified.
FACS analysis: After digestion with collagenase, the pellet of stromal cells will be treated 
with red blood cell lysing buffer followed by incubation with saturating amounts of FITC-
labeled human CD14+ or CD163+ antibody, then washed and analyzed immediately by 
using a FACS calibur flow cytometer (Becton Dickinson, San Jose, CA). Intracellular 
cytokine staining will involve a modification of basic flow cytometry that will be used for 
the simultaneous analysis of surface molecules and intracellular antigens at the single-cell 
level. Cells will be stained for surface antigens, then fixed to stabilize the cell membrane, 
and then permeabilized with the detergent saponin to allow anti-cytokine antibodies to 
stain intracellularly. 
Muscle tissue specimens: The muscle biopsy specimens will be obtained as described 
above, immediately homogenized in Trizol at the bedside, to inhibit any RNAase activity, 
and will subsequently be stored at –80 ˚ C. They will be analyzed for the following:

gene expression of GLUT-4 

gene expression of PPAR-y
This will be done in the endocrine molecular laboratory. 
Epigenomics: The field of epigenomics can be defined as the study of heritable 
changes in gene expression that occur without a change in DNA sequence, principally 
through DNA methylation, histone post-translational modifications and chromatin 
organization. These processes provide an important additional layer of transcriptional 
control that regulates how genes are expressed under various physiological and 
environmental conditions. We anticipate that variable nutritional intake during development 
will induce specific metabolic changes in adipose tissue not only resulting from changes in 
substrate flux and availability but also due to changes in protein expression regulating 
metabolism. 
To determine changes in DNA methylation patterns in fat biopsies from the human 
subjects, we will use a modify and updated protocol of previously established HELP assay 
system namely HELP-tagging assay, which involved the sequencing of the short tag 
adjacent to the digestion site, fundamentally a similar approach to the recently-described 
MSCC assay. HELP-tagging is a more quantitative assay than those previously available 
and is more sensitive to hypomethylated loci. In addition, the HELP-tag assay has 
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demonstrated that polymorphic HpaII sites occur at higher frequencies in the human 
genome than was previously thought based upon less sensitive DNA methylation assays. 
Briefly, DNA is digested with HpaII and ligated to a customised Illumina adapter with a 
complementary cohesive end.  The adapter also contains an EcoP15I site that cuts into 
the adjacent sequence 27 bp away, allowing us to polish that end and ligate the other 
Illumina adapter for library generation by PCR. The presence of the CCGG and EcoP15I 
sequences at the end of the reads obtained is a useful quality metric and allows us to 
remove spurious sequences.  Prior to sequencing, we perform quantitative real time PCR 
with primers that measure the proportion of adapter dimer complexes in the library, usually 
a very small proportion (<5%) of the total library. Following sequencing, we remove low 
quality or unmapped reads, pile up reads on each locus and create an output for each 
locus in terms of read frequency. We find some heterogeneity in the MspI representation, 
requiring that, as for microarray-based HELP, we normalize the HpaII signal with that of 
the deep sequenced MspI profiles we have generated to date. Co-investigator Dr. John 
Greally at Einstein will lead the continued development of the analytical pipelines 
supporting the use of HELP-tagging studies.
OUTCOME OF OBJECTIVE 5: 
To screen for type 1 diabetes using auto-antibody testing. We will perform specific 
immunologic (radiobinding) assays to detect islet autoantibodies including: Islet Antigen-2 
autoantibodies (IA-2A), Glutamic acid decarboxylase autoantibodies (GAD65A), and 
Insulin autoantibodies (IAA). In addition, auto-antibodies to Zink transporter 8 (ZnT8A) 
were recently identified as novel markers for type 1 diabetes diagnosis and prediction (43, 44)
. Therefore, using dried blood spot samples (see attached protocol), we will evaluate for 
Zinc Transporter 8 (ZnT8) autoantibody variants: Arginine (ZnT8-RA), Tryptophan (ZnT8-
WA) and Glutamine (ZnT8-QA) (45, 46). Importantly, measuring ZnT8A, GADA, IA-2A, and 
IAA has been shown to raise autoimmunity detection rates to 98% at disease onset (43). 
Considering that measurements of these novel auto-antibodies are currently not available 
in India, these determinations will initially be done at Lund University in Sweden. 
Moreover, to better characterize these lean diabetic individuals we plan to examine 
maturity-onset diabetes of the young (MODY) genes 1-6 and the neonatal diabetes genes 
ABCC-8 and KCNJ-2.
5.0 STUDY POPULATION AND RECRUITMENT: 
Diabetes Mellitus (DM) Subjects: The subjects with diabetes will be recruited from the 
community as well as from the outpatient diabetes practice at CMC India, Jacobi Medical 
Center and North Central Bronx hospital. Subjects with diabetes mellitus will meet the 
following criteria: ages 19-45 years, diabetes duration at least one year, negative GAD 
antibodies, present (>1.0 pmol/l) C-peptide response to Sustacal challenge, stable and 
moderate-to-poor glycemic control (HbA1c between 8 and 11%), with no pancreatic 
calcification on imaging, and not suffering from significant  complications. Diabetic 
subjects will be otherwise in good health. 
Lean Diabetes Subjects: N=20 subjects with BMI 16-22.5 kg/m2, with a history of 
low birth weight and malnutrition documented on at least one occasion.
T2DM Subjects: N=20 subjects with BMI 22.5-27 kg/m2
T1DM Subjects: N=20 subjects with BMI 16-22.5 kg/m2
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Nondiabetic Subjects: N=20 nondiabetic with BMI 16-22.5 kg/m2 subjects 19-45 
years of age and in general good health, taking no medications, with normal 
glucose tolerance and no family history of diabetes. These subjects will be similar 
in age, ethnicity and BMI with the lean DM group, and will be recruited through 
various means of community outreach, including notices in shops and 
newspapers. 
6.0 Subject Eligibility Criteria
6.1 Inclusion Criteria:
1.
 Age 19-45 yr 
2.
 Diabetes duration at least one year (for the diabetes groups)
3.
BMI range: 16-22.5 kg/m2 (individuals with lean and type 1 diabetes and non-
diabetic controls); 22.5-27 kg/m2 in individuals with type 2 diabetes
4.
 Negative GAD antibodies 
5.
 Present (>1.0pmol/l) C-peptide response to Sustacal challenge
6.
 Stable and moderate-to-poor glycemic control (HbA1c greater than 8%)
7.
 Able and willing to provide informed consent.
6.2 Exclusion Criteria: 
1.
Mentally disabled persons
2.
Major psychiatric disorder on medication (excluding successfully treated 
depression)  
3.
HIV/AIDS
4.
History of any cancer 
5.
Alcohol or substance abuse or toxin exposure which could be associated with 
neuropathy
6.
Cushing’s syndrome 
7.
Pregnancy or breast-feeding 
8.
Untreated or uncontrolled hypertension 
9.
Any Chronic illness requiring medication 
10. History of bleeding disorder or with a prolonged PT or PTT
11. Renal disease
12. Liver impairment
13. Prisoners
Prior to their enrollment in the study the purpose, nature, risks and benefits of the study 
will be explained to all subjects and their voluntary, informed, written consent will be 
obtained. All subjects will have a screening visit to allow for clinical evaluation, including 
history, physical examination and consent procedures. 
7.0 TREATMENT OF SUBJECTS:
7.1 VISIT PROCEDURE: 
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SCREENING VISIT (Visit 1). All subjects recruited in the United States will present to the 
Department of Endocrinology  fasting; consequently, visits will be scheduled in the 
morning. Before screening takes place subject will be provided with written information 
about the trial and the procedures involved in accordance with local requirements. 
Subjects will be fully informed, orally and in writing, of their responsibilities and rights while 
participating in the trial, as well as of possible advantages/disadvantages when being 
treated with the trial medication. Subjects will have the opportunity to ask questions and 
have ample time to consider participation.  
The informed consent process will take place at the screening visit (visit 1).
Subjects who wish to participate in the trial will sign and date the informed consent form 
for the trial before any trial related procedure.
All subjects will be provided with a copy of their own signed and dated informed consent 
form.
If the investigator is not the primary physician, the investigator will preferably notify the 
primary physician about the subjects trial participation. If required permission should be 
given by the subject.
The following will be performed and recorded during the screening visit
An initial screening visit will include a full history and physical examination, an oral glucose 
tolerance test and additional laboratory tests to determine eligibility, including testing for 
autoantibodies to Islet Antigen-2 autoantibodies (IA-2A), Glutamic acid decarboxylase 
autoantibodies (GAD65A), Zinc Transporter 8 (ZnT8) autoantibody variants: Arginine 
(ZnT8-RA), Tryptophan (ZnT8-WA) and Glutamine (ZnT8-QA), c-peptide, HbA1c, serum 
electrolytes, BUN and creatinine, PT/PTT, liver function tests, lipid profile, and urinalysis.
a)
Signed informed consents, date and time
b)
Demography ●Name,
                                   ● Date of Birth
                                         ● Sex
                                         ● Medical History.
                                         ● Concomitant Medications.
c)
full history and physical examination,
d)
laboratory tests to determine eligibility, 
i)
serum electrolytes,
ii)
serum BUN and creatinine
iii)
PT/PTT, 
iv)
liver function tests, 
v)
lipid profile,
vi)
 HbA1c, 
vii)
screening urinalysis 
.  
 The patients will be evaluated for fibrocalcific pancreatic disease by abdominal imaging 
such as abdominal X-ray, ultrasound or MRI scan. 
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This is an observational study and hence there will be no randomization.
Schedule of proposed clinical studies: 
TIMELINE:
Year 1
Year 2
Year 3
Recruitment efforts and screening visits
50
30
20
Body composition analysis
10
25
25
Clamp studies
10
25
25
Data analysis 
X
XX
XX
Manuscript preparation & presentations
X
XX
8.0 ASSESSMENTS
8.1 Physical Assessment:    
Physical examination will include a careful assessment of upper extremity veins, musculo-
skeletal exam as well as measurement of height, weight, waist circumference and percent 
body fat (by bio-impedance absorptiometry). 
8.2 Laboratory assessment: 
Laboratory assessment will tests to determine eligibility, including serum electrolytes, 
serum BUN and creatinine, PT/PTT, liver function tests, lipid profile, HbA1c, screening 
urinalysis, and blood pressure measurements.
8.3 In vivo clamp studies – General Conditions (Figure 6) 
All subjects will be admitted on the day of the study to the Endocrinology 
Department study room after an overnight fast. At 8:00 am 2 intravenous cannulae will be 
established, one for infusions and a second one to be inserted in a retrograde fashion in a 
dorsal vein of the opposite arm for blood sampling. To obtain arterialized venous blood 
samples, this hand will be maintained at 65°C in a heated blanket. 
A primed continuous infusion of D2G- Glucose will be initiated at t= 0 min (2 hours 
prior to the onset of the ‘clamp’ study).  A bolus of D2G 200 mg/m
2 over 3 min will be 
followed by continuous infusion of 2 mg/min/m
2  for the entire study in all subjects (for total 
duration of 6 hours) to quantify glucose turnover, specifically rates of peripheral glucose 
disposal and hepatic glucose production.  
These ‘pancreatic clamp’ experiments will consist of 360 min insulin/somatostatin 
(250 µg/hr) infusions with replacement of glucoregulatory hormones (glucagon 1 ng/kgmin; 
growth hormone 3 ng/kgmin). Throughout the entire 360 min the plasma glucose 
concentration will be maintained at basal levels (~90 mg/dl). 
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Basal phase: From t=0 min to t=120, optimal insulin infusion rates will be selected in each 
individual by making frequent (~ every 20-25 mins) adjustments to the insulin infusion 
rates in order to establish insulin infusion rates required to maintain euglycemia (90 mg/dl) 
without the requirement for exogenous glucose infusion. In our experience, this approach 
has resulted in our ability to detect small changes in insulin sensitivity (86) 
Low phase: Following establishment of basal insulin requirements during the basal 
phase, at T=0 the insulin infusion rate will be increased by ~20 mU/m
2/min, and it will be 
maintained at this rate for 2 hours (T=120-240 min). These rates are designed to optimally 
assess hepatic insulin sensitivity. Plasma glucose will be maintained at euglycemic 
concentrations (~90mg/dl) by a variable infusion of 20% dextrose for the entire study (96). 
High phase: At T=240 min, insulin infusion rate will be increased to 80 mU/m
2/min, and will 
be maintained at that rate for the final 2 hours of the study (T=240-360). These rates are 
designed to assess whole body insulin sensitivity. 
 All infusions will be stopped at t=360 min.  The subject will be given a standard meal and 
plasma glucose levels will be monitored at 15-30 min intervals for the next one hour. 
Dextrose infusion will be continued for approximately 45 minutes after the study in order to 
avoid hypoglycemia. The subject will be discharged provided that his or her condition 
remains stable. 
Measurements of plasma insulin, C-peptide, glucagon, and growth hormone are 
undertaken throughout the studies in order to evaluate the adequacy of the “pancreatic 
clamp” technique, i.e. the inhibitory effects of somatostatin on hormone secretion, and 
uniformity of hormone replacement. All samples will be kept on ice until centrifuged (within 
30 min). Plasma samples will then be sorted and handled by the Special Assay Core, and 
will be stored frozen at -20°C for later assays. 
8.4 Plasma measurements: 
From t=0 to t= 360 min., blood samples will be obtained at hourly intervals for 
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determination of plasma glucose, insulin, glucagon, C-peptide, and  Free fatty acids (FFA). 
Additional samples for D2G glucose determinations will also be obtained every 15 
minutes.
 Plasma glucose will be measured every 5-10 min to adjust the glucose infusion rate. 
Plasma lipids (LDL, HDL, VLDL, total Cholesterol and Triglycerides) will be measured at 
t=0). 
8.5 Analytical procedures: 
 Plasma glucose will be measured with a Beckman glucose analyzer (Fullerton, CA) by 
use of the glucose oxidase method (87). Plasma hormone determinations will be 
performed by radioimmunoassay as previously reported (98), and these determinations 
will be provided by the Radioimmunoassay Core of the Diabetes Research and Training 
Center (DRTC). 
8.6 Substrate determination: 
 Plasma FFA levels will be determined by using an acyl-CoA oxidase based colorimetric 
kit (Wako, Osaka, Japan) (99, 100). Plasma lactate will be measured by fluorometric 
enzyme techniques (101).  
Plasma for labeled glucose will be treated as previously described (102).Rates of glucose 
appearance (Ra) and disappearance (Rd) and other indices of glucose turnover will be 
estimated by using the steady-state equation of Steele (103). Endogenous glucose 
production (EGP) will be determined by subtracting the rates of glucose infusion from the 
tracer-derived rate of appearance of glucose. Data for glucose turnover represent the 
mean values during the final 60 min of the low insulin period (t=60-120 min), and during 
the final 60 min of the high insulin period (t=180-240 min). 
8.7 Measurement of insulin secretory response to meal challenge:
Mixed meal tests have been proposed to have similar sensitivity and reproducibility to oral 
glucose tolerance testing (OGTT) for the detection of hyperglycemia and diagnosis of 
glucose intolerance (47,48) and we have substantial experience in performing these tests in 
older subjects.  Indeed, a standard mixed meal challenge, rather than an oral glucose 
challenge, represents a more physiologically relevant stimulus in that it may more closely 
mimic the metabolic changes experienced by individuals in daily life, and is better 
tolerated than an OGTT. It also represents a more integrated measure of nutrient 
metabolism than intravenous challenge tests, since it includes the contribution of the 
incretin hormones.  
We will study subjects following an overnight fast and after a test meal of 100 g CHO, 20 g 
protein, and 20 g fat.  Blood sampling will be performed through an indwelling intravenous 
catheter, fasting and 15, 30, 45, 60, 90, 120 and 180 minutes following the meal, for 
measurement of glucose, insulin, C-peptide and glucagon levels. Plasma triglycerides and 
FFA levels will be measured fasting and at 60, 120 and 180 minutes. Subjects will be 
provided with a standard meal and snack to consume at home the night prior to the MMT 
and will fast after 10 pm, in order to minimize metabolic variability between tests. Glucose 
and insulin levels will be used to calculate the area under the curve (AUC) using the 
trapezoidal method.  
Glucose-stimulated insulin secretion can be assessed using a variety of techniques, 
including hyperglycemic “clamp” studies and the frequently sampled intravenous glucose 
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tolerance test.  However, these procedures could be considered to be less physiologic, as 
they do not capture the contribution of incretin hormones, and may be more burdensome 
for older subjects. Standard mixed-meal tests with frequent blood sampling and 
application of mathematical modeling have been used to evaluate insulin secretion, and 
have been reported to produce results comparable to more invasive and less physiologic 
tests (49,50). 
In collaboration with our colleague, Dr. Daniel Stein, indices of β-cell function will be 
estimated from plasma glucose and C-peptide concentrations using the oral minimal 
model of C-peptide secretion, with kinetics calculated from deconvolution of plasma C-
peptide concentrations measured during the standard mixed meal (51) and using 
parameters for C-peptide kinetics and volume of distribution as measured by Van Cauter 
et al (52). Insulin secretory dynamics can be broken down into dynamic and static 
components of β-cell responsivity to glucose. The dynamic responsivity index, termed 
Ψdynamic, measures the β-cell secretory response to the rate of change of glucose 
concentration. This measure approximates the first phase of insulin release and defines 
the response to a given increment in glucose. Conversely, the static responsivity index  
(Ψstatic) measures the beta cell secretory response to a given glucose concentration.  This 
static measure is believed to represent the provision of new insulin into the secretory pool. 
The two Phi factors can be combined into a Ψtotal.  The appropriateness of the insulin 
secretion for the prevailing degree of insulin resistance will be determined by the 
disposition index (DI) calculated as the Ψdynamic, Ψstatic and Ψtotal times the insulin sensitivity 
(53), which will be determined by the method of MatsudaError! Bookmark not defined., allowing 
calculation of a DI for subjects who do not undergo the euglycemic clamp. 
8.8 Fat Biopsies and Analysis:
Biopsies: Participants will have fat biopsies performed in the periumbilical region 
approximately one month following the clamp study. A small ~1-2 cm cutaneous incision 
will be performed under local anaesthesia (Lidocaine 1%) and 1-2 g of adipose tissue will 
be obtained by open biopsy technique.
Initially, the fat biopsies were planned to be obtained by aspiration technique. However, 
given the low BMI of the lean diabetic subjects, an aspiration biopsy is likely to be very 
difficult. We would therefore like to perform an open subcutaneous abdominal fat biopsy in 
each study participant. Moreover, given the complex nature of the clamp study we 
propose to perform the fat biopsy on a separate date approximately one month following 
the clamp study.
Adipose tissue specimens- Whole adipose tissue for analysis by rt-PCR will be 
immediately homogenized in Trizol (Life Technologies, Bethesda, MD) with a Tissumizer 
homogenizer. Remaining fresh adipose biopsy specimens will be immediately digested 
with collagenase type 1. Adipocytes will be subsequently separated from stromal cells by 
centrifugation and filtration. Macrophages will be separated from stromal cells by CD14+ 
specific antibody coated beads. Subsequent mRNA extraction and analysis of gene 
expression by real-time QPCR of each adipose tissue fraction will be performed .
We will quantify adipose tissue macrophages with immunohistochemistry. To measure 
macrophage content in adipose tissue by immunohistochemistry, samples will be fixed 
and embedded in paraffin (54). For immunofluorescence, tissue sections will be stained 
with primary antibodies to human CD68 and PAI-1 followed by fluorescent secondary 
antibodies, and images quantified.
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FACS analysis: After digestion with collagenase, the pellet of stromal cells will be treated 
with red blood cell lysing buffer followed by incubation with saturating amounts of FITC-
labeled human CD14+ or CD163+ antibody, then washed and analyzed immediately by 
using a FACScalibur flow cytometer (Becton Dickinson, San Jose, CA). Intracellular 
cytokine staining will involve a modification of basic flow cytometry that will be used for 
the simultaneous analysis of surface molecules and intracellular antigens at the single-cell 
level. Cells will be stained for surface antigens, then fixed to stabilize the cell membrane, 
and then permeabilized with the detergent saponin to allow anti-cytokine antibodies to 
stain intracellularly. 
9. STATISTICAL ANALYSIS 
Analysis of Variance (ANOVA): A one-way ANOVA will be used to compare the primary 
measures (eg. glucose uptake, glucose production, IHTG) among the three study groups. 
When the ANOVA indicates a significant difference, unpaired t-tests will be performed to 
distinguish which groups differ. The null hypothesis is that the primary measures will not 
differ between the three groups: the nondiabetic, lean diabetes and T2DM groups. These 
analyses will be performed in collaboration with Einstein’s biostatistician .
POWER ANALYSIS
It should be emphasized that the proposed comparisons represent ‘ground-breaking’ 
studies, as such measures have not yet been performed in individuals with lean diabetes. 
Based on our hypotheses, we predict that both DM groups will have similarly reduced 
rates of insulin-stimulated glucose uptake, while glucose uptake in the lean diabetes group 
will differ from matched nondiabetic controls to a similar extent as the difference observed 
between obese and lean subjects in our preliminary data. A sample size calculation was 
therefore performed based on an unpaired two-tailed t-test of between-group difference. 
Sample size analyses were performed, using NCSS/Pass software, to calculate the 
minimum sample size needed to achieve at least 80% power to detect a statistically 
significant difference in the primary outcomes of interest. Using our preliminary data in 
which mean glucose uptake was 8.0 mg/kg.min with SD of 2.0 mg/kg.min in the obese 
group, vs. mean glucose uptake of 10.2 mg/kg.min with SD of 2.5 mg/kg.min in the lean 
group, this calculation yielded a sample size of 20 per group.
Potential Risks: 
Potential risks to the subjects include the following:
1. Blood withdrawal: The total amount of blood sampled will not exceed 190 ml per study, 
less than half of that donated by a blood donor. 
2. 20% dextrose: The infusion of 20% dextrose may be associated with local venous 
irritation. This will be minimized by use of a large-bore antecubital vein in which the 
glucose will be infused. 
3. D2G: is a non-radioactive glucose tracer and is not associated with any known side 
effects at the doses used. 
4. Glucagon infusion in high doses can cause gastrointestinal symptoms such as cramps 
and nausea, and produce hyperglycemia in persons with glucose intolerance. The doses 
to be employed here are intended to maintain plasma glucagon at basal levels. 
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5. Growth Hormone: At higher doses and for prolonged periods of exposure, growth 
hormone (rhGH) has either insulin-like or insulin-antagonistic effects on carbohydrate and 
lipid metabolism, however the proposed infusion is for physiological replacement during 
SRIF infusion and is unlikely to have adverse effects. 
6. Hypoglycemia: is unlikely to develop in these subjects because of the desired plasma 
glucose targets (90 mg/dl during the normoglycemic studies), the low rates of insulin 
infusion, and the constant blood glucose monitoring. 
7. Somatostatin: At the proposed physiological replacement doses has no known side 
effects. 
8. Ocreotide: At the proposed physiological replacement doses has no known side effects.
Protection Against Risks:
Recruitment and Informed Consent Procedures:
Consent will be initially obtained during telephone screening performed by a research 
fellow or the study coordinator. Formal consent procedures which adhere to the 
Committee on Clinical Investigations of the Albert Einstein College of Medicine will be 
followed. Specifically, each subject will be verbally informed in layman's language of the 
purpose, benefits and possible risks of the studies.  They will then read the written consent 
form in the presence of a member of the research team and a physician who will answer 
any further questions. The subject and witness shall be asked to sign the consent form 
which will be kept in the patient’s chart. Each subject's potential participation in related 
experiments (for example, when each subject is asked to perform repeat studies) will be 
explicitly stated. 
All clinical data on the subjects will be confidential. Data generated in these studies will be 
considered only relevant for research purposes and will not be included in any clinical 
databases or the patient’s chart. Since the GCRC databases are coded, the study data will 
not be available on any clinical database system.
Procedures employed to protect subjects from undue risks include the following: 
1) Blood withdrawal: Blood withdrawal during any single study will be limited to less 
than 190cc and subsequent studies will be separated by at least, a four week 
interval.  The infusion and withdrawal catheters may produce infection or local 
hematoma, but strict aseptic technique will be observed by the experienced 
physician performing the procedure. 
2) 20% glucose: Vein irritation with 20% glucose infusion will be prevented by use of 
a large-bore antecubital vein.
3) Glucagon: Symptoms of mild nausea will be treated with antiemetic medications, if 
needed.
4) Hypoglycemia: All of these studies will be performed by a physician, hypoglycemia 
will be prevented by blood glucose sampling every 5-10 minutes and if inadvertent 
hypoglycemia develops can be rapidly treated by glucose infusion. 
Benefits 
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This study could be of direct benefit to you. It will help you gain a better understanding of 
your own metabolic processes, whole body glucose handling as well as insulin secretion in 
response to a standard meal.
The study can also be of benefit to others as would be very helpful to better understand 
this condition and develop appropriate therapeutic approaches. 
Data Storage/Confidentiality 
All data and records obtained in this study will be used for research purposes only. The 
protocol will be submitted for review and approval by the Institutional Review Board known 
as the Committee on Clinical Investigations of the Albert Einstein College of Medicine 
(CCI). The CCI is responsible to ensure human subject protections in compliance with 
institutional policies and federal regulations including the HIPAA privacy law.
All clinical data on the subjects will be confidential. Data generated in these studies will be 
considered only relevant for research purposes and will not be included in any clinical 
databases or the patient’s chart. Since the GCRC databases are coded, the study data will 
not be available on any clinical database system.
The research records will be kept private, in a secure manner, and subject names will not 
be used in any written or verbal reports. All computer records will be password protected 
in the Albert Einstein College of Medicine Clinical Research Center. Only the Clinical 
Research Center staff, as well as the research personnel authorized by the researcher will 
have access to these records.
Data Safety Monitoring Board
The data safety monitoring board will include:
Dr. Jill Crandall, Professor of Clinical Medicine in the Division of Endocrinology, Director of 
the Diabetes Clinical Trials Unit, and co-director of the DRTC Clinical Research 
Facilitation Core
Dr. Nir Barzilai, director of the Institute for Aging Research at the Albert Einstein College of 
Medicine and the Director of the Paul F. Glenn Center for the Biology of Human Aging 
Research and of the National Institutes of Health’s (NIH) Nathan Shock Centers of 
Excellence in the Basic Biology of Aging, as well as the Ingeborg and Ira Leon Rennert 
Chair of Aging Research, a professor in the Departments of Medicine and Genetics, and 
member of the Diabetes Research Center and of the Divisions of Endocrinology & 
Diabetes and Geriatrics.
Dr. Joel Zonszein, director of the Clinical Diabetes Center at the University Hospital of the 
Albert Einstein College of Medicine, a Division of Montefiore Medical Center, as well as a 
Professor of Clinical Medicine.
Selected Publications by Study Team:
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1.
Paul 
TV, 
Thomas 
N. 
The 
Clinical 
and 
Laboratory 
Profile 
of 
Primary 
Hyperparathyroidism in India. The Association of Physicians in India: Medicine Update, 
2009(Part-1) Eds: Agarwal AK, Jain DG, Yadav P. 493-499.
2.
Paul T V, Thomas N, Seshadri MS, Oommen R, Arun J, Mahendri NV. Prevalence of 
vitamin D insufficiency and osteoporosis in semi-urban South Indian population-
Endocrine Practice. 2008;14:665-671.
3.
Rao N, Jacob JJ, Paul TV, Thomas N, Rajarathinam S, Seshadri MS. Effects of 
Pioglitazone on Menstrual frequency, Hyperandrogenism and Insulin Resistance in 
Adolescents and Young adults with Polycystic Ovary Syndrome. J Pediatr Adolesc 
Gynecol. 2009 ; 22(2):91-5.
4.
Thomas N. Reversibility of neuronal damage in diabetes: the search for a newer 
therapeutic paradigm. Indian J Med Sci 2009, 63, 129-130. (Guest Editorial).
5.
Lau SL, Debarma R, Thomas N, Asha HS, Vasan KS, Alex RG, Gnanaraj J. 
Healthcare Planning in North-East India: A Survey on Diabetes Awareness, Risk 
Factors and Health Attitudes in a Rural Community. J Assoc Phys Ind.2009,57,305-
309.
6.
Koshy G, Thomas N, Rajaratnam S, Simha A, Thomas M, Viswabandya A, Nagaraj C. 
Proptosis and Polyuria- quiz and discussion. HKMed J 2009, 15,6.
7.
Thomas N. Gamma Glutamyl Transferase- a Novel marker of endothelial dysfunction? 
J Ind Assoc of Clin Med 2009. 
8.
Kannagai R, Vasan S, Danda D, Thomas N. Immune response to Epstein-Barr virus in 
individuals with systemic and organ specific autoimmune disorders. Ind J Med Micro. 
2009.
9.
Jacob JJ, Chacko A, Selvan B, Thomas N. Primary hyperparathyroidism and chronic 
pancreatitis. J Gastroenterol Hepatol. 2008, 23:164. 
10. The ORIGIN Trial Investigators. Rational, Design and baseline characteristics for a 
large international trial of cardiovascular disease prevention in people with 
dysglycaemia: The ORIGIN trial (Outcome Reduction with an Initial Glargine 
Intervention). Am Heart Jr 2008, 155, 32e1-e6.
11. Hawkins M, Gabriely I, Wozniak R, Mevorach M, Rossetti L, Shamoon H: The Effect of 
Glycemic Control on Hepatic and Peripheral Glucose Effectiveness in Type 2 Diabetes 
Mellitus. Diabetes 51:2179-89, 2002. 
12. Hawkins M, Gabriely I, Wozniak R, Shamoon H, Rossetti L: Fructose Restores the 
Ability of Hyperglycemia Per Se to Regulate Hepatic Glucose Production (GP) in Type 
2 Diabetes Mellitus (DM2). Diabetes 51:606-614, 2002.
13. Gabriely, I., Wozniak, R., Hawkins, M., and H. Shamoon. Troglitazone Amplifies 
Counterregulatory Responses to Hypoglycemia in Nondiabetic Subjects. J. Clin. Endo. 
Metabol. 86: 521-8, 2001
14. Gabriely I., Hawkins M., Vilcu C., Rossetti L, and H. Shamoon. Fructose Amplifies 
Counterregulatory Responses to Hypoglycemia in Humans. Diabetes 51:893-900, 
2002.
15. Hawkins M, Tonelli J, Kishore P, Stein D, Ragucci E, Gitig A, Reddy K. Contribution of 
elevated free fatty acid levels to the lack of glucose effectiveness in type 2 diabetes. 
Diabetes. 2003 Nov;52 (11):2748-58.
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16. Tonelli J, Li W, Kishore P, Pajvani UB, Kwon E, Weaver C, Scherer PE, Hawkins M. 
Mechanisms of early insulin-sensitizing effects of thiazolidinediones in type 2 diabetes. 
Diabetes. 2004 Jun;53(6):1621-9. 
17. Hawkins MA. Markers of increased cardiovascular risk: are we measuring the most 
appropriate parameters? Review. Obesity Research 12 Suppl 2:107S-14S, 2004. 
18. Tonelli J, Kishore P, Lee DE, Hawkins M. The regulation of glucose effectiveness: how 
glucose modulates its own production. Curr Opin Clin Nutr Metab Care. 2005 
Jul;8(4):450-6.
19. Kishore P, J. Tonelli, A. Buse, C. Fratila, and M. Hawkins. Rapid time-dependent 
restoration of glucose effectiveness upon lowering free fatty acid levels in type 2 
diabetes mellitus. Diabetes 55:1761-8, 2006
20. Li W, J. Tonelli, P. Kishore, R.Owen, E. Goodman, P.E. Scherer and M. Hawkins. 
Insulin-sensitizing effects of thiazolidinediones are not linked to adiponectin receptor 
expression in human fat or muscle. Am J. Physiol. 292(5):E1301-7, 2007
21. Hwang J-H, Tonelli J, Stein D, Barzilai N, Hawkins M. Increased intrahepatic 
triglyceride is associated with peripheral insulin resistance: in vivo MR imaging and 
spectroscopy studies. Am J. Physiol. 293(6):E1663-9, 2007.
22. Schraw T, Wang ZV, Halberg N, Hawkins M, Scherer PE. Plasma adiponectin 
complexes have distinct biochemical characteristics.  Endocrinology 149(5):2270-82, 
2008.
23. S. Kehlenbrink, J. Tonelli, S. Koppaka, V. Chandramouli, M. Hawkins and P. Kishore. 
Inhibiting gluconeogenesis prevents fatty acid-induced increases in endogenous 
glucose production. Am J. Physiol. 2009 Jul;297(1):E165-73.
24. Lee D.-E., Kehlenbrink S., Lee H., Hawkins M.  and Yudkin J. Fat at the Crossroads: 
The central role of adipose tissue in the induction of insulin resistance. Am J. Physiol. 
(in press)
25. Kishore P, Li W, Tonelli J, Kehlenbrink S, Koppaka S, Lee H, Scherer PE, and 
Hawkins M. Adipocyte-derived factors potentiate nutritional activation of adipose tissue 
macrophages. (manuscript submitted)
10. STUDY TEAM:
Principal Investigator: Nihal Thomas, MBBS MD MNAMS DNB (Endo) FRACP (Endo) 
FRCP (Edin)
Professor in Endocrinology, Department of Endocrinology, Diabetes and Metabolism
Christian Medical College Hospital,
Vellore-632004, India.
Email: nihal_thomas@yahoo.com
Ph No: 91-416-2282528 / 2282491(work)
98431-11996(Mobile) / Fax No: 91-416-4200844
Einstein PI: Dr. Meredith Hawkins
1300 Morris Park Ave Belfer 709
Bronx, NY 10461
Email: Hawkins@aecom.yu.edu
Phone: 718-430-3186
Fax: 718-430-8557
Dr. Daniel Stein
IRB NUMBER: 2013-2191
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PI: Meredith Hawkins, MD
25
1300 Morris Park Avenue
Golding Building, Room G02A
Bronx, NY 10461
Email: daniel.stein@einstein.yu.edu
718-430-2446
Dr. Roshan Livingstone
Assistant Professor
Dept. of Radiodiagnostics
Christian Medical College
Vellore.
Ph:-0416-2282181.
Ph:-0416-4200844.
Mr. Aaron Chapla
Associate Research Officer
MSc Biochemistry
Dept of Endocrinology Diabetes and Metabolism
Christian Medical College
Vellore.
Ph:-0416-2282181.
Ph:-0416-4200844.
Email: aaronchapla@gmail.com
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3(3): 214-8.
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differences in the responsiveness of adipocyte lipolytic activity to insulin. Obes Res. 2000 
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27 Ryysy L, Hakkinen AM, Goto T, Vehkavaara S, Westerbacka J, Halavaara J, Yki-
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49: 749-758, 2000.
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46 Persson A, Becker C, Hansson I, Nilsson A, Torn C. Comparison of 
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palatability, and symptoms associated with a standardized mixed test meal versus 75 g 
oral glucose. Diabetes Care 21: 336-340, 1998 
48. Harano Y, Miyawaki T, Nabiki J, et al:  Development of cookie test for the 
simultaneous determination of glucose intolerance, hyperinsulinemia, insulin resistance 
and postprandial dyslipidemia. Endocr J 53:173-80, 2006
49. Dalla MC, Campioni M, Polonsky KS, et al: Two-hour seven-sample oral glucose 
tolerance test and meal protocol: minimal model assessment of beta-cell responsivity and 
insulin sensitivity in nondiabetic individuals. Diabetes 54: 3265-3273, 2005 
50. Aloulou I, Brun JF, Mercier J: Evaluation of insulin sensitivity and glucose 
effectiveness during a standardized breakfast test: comparison with the minimal model 
analysis of an intravenous glucose tolerance test. Metabolism 55: 676-690, 2006
51. Mari A, Schmitz O, Gastaldelli A, et al:  Meal and oral glucose tests for assessment of 
b-cell function: modeling analysis in normal subjects.  Am J Physiol Endocrinol Metab 283: 
E1159-1166, 2002
52. Van Cauter E, Mestrez F, Sturie J, Polonsky KS.  Estimation of insulin secretion rates 
from C-peptide levels: comparison of individual and standard kinetic parameters for C-
peptide clearance.  Diabetes 41: 368-77, 1992
53. Basu R, Breda E, Ober A, et al:  Mechanisms of the age-associated deterioration in 
glucose tolerance.  Contributions of alterations of insulin secretion, action and clearance.  
Diabetes 52:1738-48, 2003
54. Weisberg SP, Mc Cann D, Desai M, Rosenbaum M, Leibel RL, Ferrante Jr AW. 2003. 
Obesity is associated with macrophage accumulation in adipose tissue J Clin Invest, 
112:1796-1808.
IRB NUMBER: 2013-2191
IRB APPROVAL DATE: 01/20/2017