DESCRIPTION: State the application's broad,
long-term objectives and specific aims, making reference to the health relatedness
of the project. Describe concisely the research design and methods for achieving
these goals. Avoid summaries of past accomplishments and the use of the first
person. This abstract is meant to serve as a succinct and accurate description
of the proposed work when separated from the application. If the application
is funded, this description, as is, will become public information. Therefore,
do not include proprietary/confidential information. DO NOT EXCEED THE
SPACE PROVIDED.
_____ is a pediatric cardiologist and Assistant Professor
in Pediatrics at the University of _____. The candidate's long-term goal
is to develop an independent career combining clinical research with clinical
medicine. The candidate is interested in the prevention of cardiovascular
disease by investigating risk factors in children and adolescents and mechanisms
that influence their progress to adult atherosclerotic heart disease. _____
interests in this field developed during fellowship when _____ became interested
in the relations among obesity, left ventricular mass (LVM) insulin resistance,
and lipids. The proposed career development plan incorporates a multi-disciplinary
program designed to provide an intense, closely mentored, patient-oriented
research experience in association with a comprehensively structured didactic
curriculum in epidemiology. Under the mentorship of _____ and _____, the
candidate will investigate the effect of cardiovascular risk factors in
adolescence on establishment of cardiovascular risk in young adulthood,
while enrolled in a master's degree program in the Division of Epidemiology.
This research will examine epidemiologic associations of body fatness, insulin
resistance, lipids, and LVM and will test the hypothesis that body fatness
and insulin resistance during adolescence predict levels of adiposity, insulin
resistance, lipids, left ventricular mass, and systolic blood pressure in
young adulthood. The study will be conducted in a cohort of 200 subjects
recruited at mean age 13 years from the top 15% of the blood pressure distribution
in a general population, and reevaluated at age 17 years. Previous studies
in this cohort at age 13 have shown a difference between males and females
in the response of LVM to increases in body size; and a segregation analysis
in the cohort at age 17 and their parents has inferred the presence of a
major gene influencing the levels of fasting insulin. Therefore, a second
objective of this research will be to define gender differences in the association
of left entricular mass in young adulthood with cardiovascular risk factors
in adolescence; and a third objective is to confirm the genetic results
when the participants are young adults and share less of the childhood familial
environment with their parents. |
PERFORMANCE SITE(S) (organization, city, state)
University of _____
Department of _____
_____, _____
_____________________________________________________________________________________________________________
KEY PERSONNEL. See instructions on Page 11. Use continuation pages as needed
to provide the required information in
the format shown below.
Name
Organization
Role on Project
_____
University of _____
Candidate
_____
University of _____
Sponsor (mentor)
_____
University of _____
Additional Mentor
Name
Organization
Role on Project
_____
University of _____
Consultant
_____
University of _____
Consultant
_____
University of _____
Consultant
Advisory Committee:
_____
University of _____
Advisory Committee
_____
University of _____
Advisory Committee
_____
University of _____
Advisory Committee
_____
University of _____
Advisory Committee
Use this substitute page for the Table of Contents of Research Career Awards
Type to name of candidate at the top of each printed page and continuation page
RESEARCH CAREER AWARD
TABLE OF CONTENTS
(Substitute Page)
Page Numbers
Section I: Basic Administrative Data
1-3. Face Page, Description and Key Personnel, Table of Contents (Form pages
AA, BB, and this substitution page)....................................... ___
4. Detailed Budget for Initial Budget Period (Form page DD)..............................................................................................................................
___
5. Budget for Entire Proposed Period of Support (Form page EE) ......................................................................................................................
___
6. Biographical Sketches (Candidate and Sponsor(s)* - Form page FF)..............................................................................................................
___
7. Other Support (Candidate and Sponsor(s)* - Form page GG) ........................................................................................................................
___
8. Resources (Form page HH) .............................................................................................................................................................................
___
Section II: Specialized Information
1. The Candidate
a. Letters of Reference (Attach to Face Page) ....................................................................................................................................................
___
b. Candidate’s Background................................................................................................................................................................................
___
c. Career Goals and Objectives: Scientific Biography..........................................................................................................................................
___
d. Career Development Activities during Award Period................................(Not
to exceed 5 pages)..................................................................
___
2. Statements by Sponsor(s), Consultant(s), and Collaborators(s)*
.............................................................................
___
3. Environment and Institutional Commitment to Candidate..............................................................................................
___
a. Description of Institutional Environment .................................................................................................................................................................
___
b. Institutional Commitment to Candidate’s Research Career Development.................................................................................................................
___
4. Research Plan
(Introduction for Revised Application and General Comments)
a. Statement of Hypothesis and Specific Aims.............................................................................................................................................................
___
b. Background, Significance, and Rationale.................................................................................................................................................................
___
c. Preliminary Studies and Any Results...............................................(Not
to exceed 20 pages)..................................................................................
___
d. Research Design and Methods .............................................................................................................................................................................
___
5. Career Development Plan..........................................................................................................................................
___
Section III: Other Information
1. Research Plan Continued (see pages 17-19)
a. Minorities and Women* .........................................................................................................................................................................................
___
b. Human Subjects* ..................................................................................................................................................................................................
___
c. Vertebrate Animals*..............................................................................................................................................................................................
___
d. Literature Cited .....................................................................................................................................................................................................
___
e. Consortium/Contractual Arrangements* .................................................................................................................................................................
___
2. Checklist (Include form pages II-KK)
...................................................................................................................................................................___
3. Appendix
(Five collated sets. No page numbering necessary.)
Number of publications (not to exceed six): 1
List of key items
3 forms
Proof of U.S. Residency
Note: Type density and size for the entire
application must conform to the instructions on page 6 of the general instructions.
*Include these items only when applicable.
CITIZENSHIP statement is included with the application
RESOURCES
FACILITIES: Specify the facilities to be used for the conduct of the proposed
research. Indicate the performance sites and describe capacities, pertinent capabilities,
relative proximity, and extent of availability to the project. Under “Other,”
identify support services such as machine shop, electronics shop, and specify
the extent to which they will be available to the project. Use continuation pages
if necessary.
Laboratory: x, N/A
Clinical: The clinic consists of 2200 sq. ft. of recently renovated space. Included
are a reception area, clerical area, examination rooms, offices for interventionists,
conference room, lavatory, laboratory and storage area for files and equipment.
Free parking is available adjacent to the building.
Animal: x, N/A
Computer: x, N/A
Office: Office space for the principal investigator is provided by the Department
of _____and is located in the _____. It consists of two adjacent offices, of which
one is occupied by equipment related to tracing and digitizing echocardiograms.
Other: x, N/A
____________________________________________________________________________________________________
MAJOR EQUIPMENT: List the most important equipment
items already available for this project, noting the location and pertinent
capabilities of each.
Macintosh IIci computer with laserwriter
IBM PC AT with printer.
The clinic has a modem and computer for direct communication with the Division
of _____ computing service. Freezer (-20 and -70). Refrigerator.
_____________________________________________________________________________________________________
Section II: Specialized Information
1. Candidate
a. Letters of Reference
b. Candidate's Background
c. Career Goals and Objectives: Scientific Biography
My long-term goal is to develop an independent career combining clinical research
with clinical medicine. I am interested in the prevention of cardiovascular disease
and believe that important scientific information in this research area can be
developed by investigating risk factors in children and adolescents and mechanisms
that influence their progress to adult atherosclerotic/ischemic heart disease.
My research interests started during my fellowship in Pediatric Cardiology when
I studied a diverse group of topics within pediatric cardiology. These resulted
in primarily descriptive reports including: 1) post-mortem evaluation of coronary
artery abnormalities in sudden unexpected death in the young; 2) long-term outcome
in patients with pulmonary atresia and intact ventricular septum; 3) long term
cardiac effects of anthracyclines in childhood cancer survivors, including evaluation
of left ventricular performance and wall stress at baseline and peak exercise;
4) echocardiographic and MRI analysis conducted in the clinical research center,
directed at long term outcome of individuals after surgical repair of coarctation
of the aorta.
It was also at this time that I was introduced to questions about the relations
between obesity, left ventricular mass, insulin resistance, and lipids in children.
As a cardiologist I am aware of the epidemic proportions reached by cardiovascular
disease in the adult population. As a pediatrician, I strongly believe that any
effective measure against the conditions causing this disease must begin with
identification and quantification of risk factors early in life and design of
preventive measures during the periods of early development. It has become clear
to me through participation at national and international meetings that there
is much to learn about the developing heart and how early interactions with the
classical risk factors for adult cardiovascular disease influence cardiac development.
I
am committed to making this the focus of my research.
My clinical expertise is concentrated on evaluation, diagnosis and management
of children with cardiac disease. I have a strong interest and am highly skilled
in echocardiography. I also have been active in the area of pediatric lipid disorders
and initiated a pediatric lipid clinic at the University of _____ of which I am
the Director; I envision this clinic as having great potential for patient-oriented
research.
The Mentored Patient-Oriented Research Career Development Award will provide the
support and time I need to develop the skills and expertise necessary to become
a successful independent investigator. My work with _____, and, in particular,
observing his collaborations with the Division of _____ has led me to realize
that I lack some skills that are critical to a successful clinical research career.
While I have gained valuable experience during the past few years on these projects,
the opportunity to concentrate on developing these skills in an intense research
environment will be invaluable to my progress toward an independent clinical research
career.
d. Career Development/Training Activities During Award Period
Although I have a background in clinical research, my training and expertise in
biostatistics and epidemiologic methodology are limited. Through my work with
_____and _____ the importance of this became very clear to me. In order to become
proficient in studies of disease prevention it is crucial that I acquire the skills
to understand and analyze public health problems; design, implement and analyze
studies; and correctly interpret study results. The Master's in Clinical Research
offered in the Division of _____, School of Public Health, is ideal for these
purposes, and I look forward to beginning this curriculum.
The academic environment at the University of _____ is excellent. _____, who is
nationally and internationally recognized for his studies in blood pressure and
has vast experience in large cohort studies, will be one of my mentors during
this award period. He has been an excellent mentor for me in the past and helped
guide my first steps in this field. _____ will also serve as a mentor. _____ is
also nationally and internationally recognized for his studies and is expert in
epidemiologic and biostatistical methodology and in conduct and analysis of large
observational studies. I feel that he and _____complement each other well with
regard to the mentorship I will need in carrying out my career development plan.
Both have been very generous with their time in answering my questions
and I will be able to meet with them as often as necessary. In addition, I will
have the opportunity to work with _____ and _____. _____is a statistical geneticist
and expert in segregation analysis methodology. _____ is expert in clinical trials
and cohort studies and has great experience in studies such as the one I propose.
At the University of _____, there are multiple opportunities to attend seminars,
lectures and journal club meetings that either have direct relevance or will contribute
to my understanding of epidemiology, cardiovascular risk factors and their interrelations.
In addition, I will participate on a regular basis at meetings of the executive
committee of the project "_____" directed by _____ and will meet bi-weekly
with the cardiovascular risk group assembled by _____. These sessions provide
an interactive forum that facilitates free exchange of ideas. They are extremely
educational and they provide me with insights into and suggestions for my research.
The _____ (_____) at the University of _____ provides an ideal environment for
patient-oriented research and allows the close collaboration of the researchers
from several disciplines. Work on this research project in the _____will help
me in developing the skills necessary for leadership through coordination of multiple
research team members.
The resources of the Department of _____and School of Public Health will be available
to me throughout the proposed project. I will be able to devote at least _____
of my time to the research efforts proposed in this grant. This is a unique opportunity
because the faculty in the Division of _____ have heavy clinical demands. This
protected time will allow me to immerse myself in the complexities of epidemiology
and public health, and to interdigitate my clinical skills with these disciplines.
My clinical, administrative and teaching responsibilities will not exceed _____
of time and effort. This amount of time in clinical medicine is important for
me to maintain my skills and to stay abreast of the current literature. The Mentored
Patient-Oriented Research Career Development Award will facilitate my acquisition
of technical and academic skills necessary to achieve my ultimate goal, that of
becoming a competent independent clinical investigator in the field of preventive
cardiology.
2. Statements
a. Sponsor/Mentor: _____.
Co-Mentor: _____.
b. Consultants:
1) _____
2) _____
3) _____
3. Environmental and Institutional Commitment to Candidate:
a. Description of Institutional Environment
b. Institutional Commitment to Candidate's Research Career
Development
4. Research Plan
a. Specific Aims
This research is intended to examine
epidemiologic associations pertaining to body fatness, insulin resistance, and
other cardiovascular risk factors during adolescence and young adulthood. The
primary objective is to test the hypothesis that body fatness and insulin resistance
during adolescence predict levels of cardiovascular risk factors (adiposity, insulin
resistance, lipids, left ventricular mass, systolic blood pressure) in adulthood.
The study will be conducted in a cohort of 200 participants recruited at mean
age 13 years (range, 11-14) from the top 15% of the blood pressure distribution
in a general population, and reevaluated at age 17 years. Previous studies in
this cohort at age 13 have shown a difference between males and females in the
response of left ventricular mass to increases in body size; and a segregation
analysis in the cohort at age 17 and their parents has inferred the presence of
a major gene influencing the level of fasting insulin. Consequently, a second
objective of this research will be to define gender differences in the association
of left ventricular mass in young adulthood with cardiovascular risk factors in
adolescence. The third objective is to confirm the genetic results when the participants
are young adults and share less of the childhood familial environment with their
parents.
Specific Aim #1: longitudinal analyses
To obtain measurements at mean age
26 of height, weight, waist and hip circumference, skinfold thickness, body mass
index, and blood pressure; blood samples for fasting insulin, glucose, and lipids;
insulin clamp studies for insulin resistance; and echocardiographic measurements
of left ventricular size in 200 (98 males and 102 females) normal young adults
who have been followed since mean age 13, and to compare them with measurements
of body size, lipids,
fasting insulin and left ventricular size previously obtained in adolescence.
Hypothesis #1
Weight and body fatness at mean age
13 and changes through mean age 17 will predict degree of adiposity and levels
of insulin resistance, lipids, blood pressure and left ventricular mass at mean
age 26.
Hypothesis #2
Fasting insulin at mean age 17 and
changes in fasting insulin from age 17-26 will predict insulin resistance, lipids,
blood pressure, and left ventricular mass independent of body size in young adulthood.
Specific Aim #2: gender differences
To compare changes in cardiovascular risk between males and females from adolescence
to young adulthood.
Hypothesis #3
With increasing adiposity, the increase
in left ventricular mass between mean ages 13 and 26 will be proportionately larger
in females than in males, conforming to cross-sectional findings at mean age 13.
Hypothesis #4
Insulin resistance in young adults
will be greater in females than in males, due to greater body fat in females.
This will be independent of differences in other risk factors between males and
females.
Specific Aim #3: genetics of insulin resistance
To perform segregation analysis of adult child and parent fasting insulin levels
and to carry out a mixture decomposition of adult child (age 26) M (insulin resistance)
values.
Hypothesis #5
In segregation analysis, the environmental
effect will be smaller and the genetic effect larger in the analysis which uses
fasting insulin at age 26 than in the analysis (already performed) which uses
fasting insulin at age 17.
Hypothesis #6
The statistical distribution of young
adult M value will be composed of the sum of three separate distributions, consistent
with the existence of a single Mendelian gene.
b. Background, Significance and Rationale
Research studies of the etiology of atherosclerotic cardiovascular disease support
an association with insulin resistance which, in turn, is linked with obesity,
hypertension and hyperlipidemia (1-4 ). The biologic effects of insulin, e.g.,
renal sodium retention (5), increased sympathetic tone (6), stimulation of vascular
smooth muscle growth (7), and altered lipid metabolism (1) suggest an essential,
possibly primary, role for insulin in these relations. However, it is not yet
possible to entirely dissociate the influence of any one of these factors from
the others in the development of cardiovascular disease.
The relation between insulin resistance and weight may be particularly relevant
to the proposed associations between insulin resistance and cardiovascular risk.
Obese adults have been shown to be insulin resistant when compared to normal control
subjects (8), and obesity has been strongly correlated with cardiovascular risk
(9). Data from the Framingham study have established an increased incidence of
cardiovascular events in both men and women with increasing weight (10); body
weight and mortality were directly related in the Harvard Alumni Health Study
(11); and weight gain was a significant risk factor for development of diabetes
mellitus in women (12). Other studies have shown sustained improvement in cardiovascular
risk in association with a 10-15% weight loss maintained over time (13). A direct
association between adiposity and insulin resistance has been reported in children
(14, 15), as has the association between insulin resistance and both lipids (16)
and blood pressure (17, 18). Weight loss is associated with a decrease in insulin
concentration and an increase in insulin sensitivity in adults (19) and adolescents
(20).
Increased left ventricular mass (LVM) is a powerful predictor of adverse cardiovascular
events such as ischemic heart disease, dysrhythmias, and congestive heart failure
(21,22). Although cardiovascular events are rarely seen during childhood, it is
important to study markers such as increaseed cardiac mass in adolescence and
young adulthood, because the pathologic processes associated with cardiovascular
events appear to be in their early stages of activity. Framingham (23) and other
studies in adults (24,25) have shown that an important cause of increased LVM
is obesity. Moreover, studies performed in 475 adults showed that the effect of
obesity on LVM appears to be greater in women than men (26, 27), especially in
the presence of hypertension (26). Studies at mean age 13 in the subjects included
in the present research proposal have suggested a greater effect of obesity on
left ventricular mass in females than males (see Preliminary Studies). However,
other studies in children and adolescents have reported a positive correlation
between LVM and body size, that is associated with male gender (26, 28-31). In
pediatric studies, in general, boys tend to have larger LV measurements and LVM
than girls (28, 32,33). Although this is felt to be related to a greater muscle
mass in boys (29), specific studies have not explored the independent influence
of adiposity versus muscularity on LV size in males vs. females. Thus, neither
the relation between obesity and cardiac size, the influence of gender on this
relation, nor the impact of these on adult cardiovascular disease has been well
defined.
The abnormal lipid profile associated with atherogenesis (elevated total cholesterol,
LDL-cholesterol and triglycerides, and low HDL-cholesterol) is related to obesity
and insulin resistance. The Beaver County Lipid Study in young adults (mean age
22 years) has reported positive and significant correlations between BMI and LDL-C
and triglycerides (34). Weight loss was associated with improvements in lipids,
blood pressure, and fasting insulin (13). The relation between weight and abnormal
lipids is also present during childhood. Waist-hip ratio has been positively correlated
with serum cholesterol and LDL-C in four year old children (35); and body size
has been shown to be a significant correlate of blood pressure and lipids in older
children and adolescents (17, 36,38). An increase in obesity during childhood
is related to changes in lipids and lipoproteins that are consistent with a more
atherogenic lipid profile. Children examined at age 5-12 in the Bogalusa Study
and re-examined five years later had significant correlations between change in
triceps skinfold thickness and change in cholesterol, triglycerides, LDL-C, HDL-C,
and VLDL-C (39); and in two separate Bogalusa cohorts evaluated after an eight
year period of observation increases in weight were accompanied by adverse changes
in lipids and lipoproteins (40). Similarly, in subjects examined initially at
8-18 years in the Muscatine study and again during their third decade a direct
association was found between development of obesity and adult cholesterol levels
(41). Insulin influences lipid metabolism via regulation of very low density lipoprotein
(VLDL) production by the liver (42). Hyperinsulinemia is associated with hypertriglyceridemia
not only in obesity (1,43,44) but also in individuals with normal weight (45),
and it is inversely correlated with HDL-cholesterol (1). Hyperinsulinemia and
insulin resistance are characterized by an atherogenic lipoprotein profile (46,47)
and insulin resistance is associated with asymptomatic atherosclerosis (48) independent
of obesity or hypertension. The CARDIA study of 4576 young adults reported a weight-independent
association between insulin and lipids (49). While it is currently impossible
to entirely dissociate the influence of insulin from obesity on lipid levels,
it is clear that an association exists between insulin and lipids that is independent
of the association with obesity.
The insulin resistance (or multiple metabolic) syndrome (insulin resistance, non
insulin dependent diabetes, dyslipidemia, obesity, and hypertension) is determined,
at least in part, by genetic determinants (50-52) and there is evidence for a
genetic influence on individual components of the syndrome. A strong genetic influence
on blood pressure has been demonstrated in early childhood (53) with intensification
in the presence of other risk factors (54). Fasting insulin, blood pressure and
lipids are closely related in young adult offspring of hypertensive parents (55),
and a parental history of NIDDM and hypertension is associated with increased
levels of insulin resistance in their children (56). The aggregation of lipid
levels within families has been previously recognized (57) and forms the basis
for current lipid screening recommendations in children (57). Data obtained from
this study cohort in adolescence showed a significant relation between insulin,
lipids and blood pressure, as well as a significant relation for these factors
between adolescents and their parents (see Preliminary Studies). Also in this
cohort at age 17 a segregation analysis of fasting insulin in children and their
parents strongly suggests the presence of a major gene (see Preliminary Studies).
1) Significance of the Research
Extensive anthropometric, blood pressure, and echocardiographic measurements on
this population are available to us from age 13, and fasting insulin and lipid
levels are available in most subjects from age 17. With these previous data, the
proposed research provides an opportunity to determine the relationships among
cardiovascular risk factors at the childhood-adolescent-adult transition, i.e.,
the putative earliest point in the development of cardiovascular risk, and to
assess etiologic relations between early indicators of insulin resistance and
establishment of risk in young adulthood. Specific gender-related and genetic
analyses will further define the role of these risk factors. It is reasonable
to suggest that understanding these epidemiologic relationships at earliest development
and prior to the onset of overt disease may lead to strategies for reducing cardiovascular
risk.
c. Preliminary Studies and Results
1) Results from a different study sample:
The relationship between insulin resistance and abnormal lipid profile in
obese adolescents
Studies utilizing the euglycemic insulin clamp technique in
normoglycemic individuals have suggested that insulin resistance can be linked
with lipid and lipoprotein abnormalities. Insulin resistance has been associated
with elevated fasting and post prandial insulin levels, and has been hypothesized
to play a major role in dyslipidemia in individuals with normal glucose tolerance
as well as those with impaired glucose tolerance, and non insulin dependent diabetes.
In a collaborative study with _____, Division of _____, University of _____,
we examined whether lipid abnormalities occur in normoglycemic, obese adolescents
and are associated with insulin resistance (reference number - manuscript appended).
The relationship between lipid levels and insulin resistance was assessed in
82 obese adolescents (mean weight = 69.9±2.5 kg, mean % fat = 37.4±1.1%), by
comparing fasting insulin and sum of the insulin values after an oral glucose
tolerance test to those from 40 nonobese adolescents (mean weight = 44.3±2.9
kg, mean % fat = 20.1±1.0%). Whole body glucose uptake during euglycemic hyperinsulinemia
(M value) was performed in a subset of 19 of the obese adolescents and compared
with another control group, 24 nonobese young adults. The obese adolescents
had significantly elevated LDL-cholesterol and triglycerides and lower HDL-cholesterol
when compared with the nonobese subjects. M values were significantly depressed
(i.e., increased degree of insulin resistance) in the obese compared with the
nonobese subjects (see Figure 1).
Among the variables representing insulin resistance (fasting
insulin, sum of insulin during oral glucose tolerance test, and M), the strongest
correlation with the abnormal lipid profile was found for the M value. In stepwise
multiple regression analysis, the M value was the only variable entered into
the relationship for the dependent variables triglycerides and LDL-cholesterol,
while both M value and fasting insulin entered for HDL-cholesterol.
Thus, in this small sample, the degree of insulin resistance in obese adolescents
is correlated with the levels of triglycerides, LDL-cholesterol and HDL-cholesterol.
2) Results from the cohort proposed for this study
a) Obesity and female sex influence left ventricular size
in children
Echocardiographic measurements of left ventricular posterior wall thickness,
chamber size (left ventricular internal dimension) and mass were performed in
210 children aged 11-14 yrs. Children were stratified into quintiles of body
mass index. Comparisons were made between the highest (obese) and lowest (nonobese)
quintiles (BMI (mean ± standard error): 29.4±0.7 v 17.2±0.1 p=0.0001). Systolic
blood pressure differed significantly between quintiles (males:
131±2 v 119±2 p=0.0001; females: 123±2 v 118±2 p=0.03). Echocardiographic measurements
were made using the American Society of Echocardiography criteria. Comparisons
of left ventricular size and mass between obese (highest quintile of BMI) and
nonobese (lowest quintile of BMI) in the table below were adjusted for height,
systolic blood pressure and sexual maturity (Tanner score).
In this study, obesity in children, independent of height, systolic blood pressure,
and sexual maturity, was associated with increased left ventricular (LV) size
and mass. These findings are consistent with previous reports showing a direct
relationship between body size and LV size in children and a larger LV size
in males than females. However, it was found that LV mass was significantly
greater in boys than in girls only in the lowest (non obese) quintile of BMI,
whereas in the highest (obese) quintile LV mass was similar in males and females;
this is depicted in the graph below.
The results were similar when waist circumference was substituted for BMI in
the analyses. Thus, these data suggest that body fatness has a particularly
adverse effect on cardiac size in females.
It is not clear why these gender differences exist between children of the upper
and lower BMI quintiles. It is possible that the greater LV mass/BMI relation
in non obese males is due to a greater muscle mass, whereas in obese children
the equalization of the LV mass/BMI relation between males and females may be
due to a disproportionate increase in fatness in females as they gain weight.
The relative importance of the differences in changes in LV mass and body fatness
in males versus females as they mature from adolescence to young adulthood is
not known.
b) Adiposity at age 13 is a predictor of adiposity, insulin resistance and
abnormal lipids at age 22
The purpose of this study was to determine whether adiposity in children predicts
insulin resistance and abnormal lipids in young adults. The children had blood
pressure, weight and height measured at age 13.3 ± 0.3 years. 24 of them (7 males
and 17 females) were reevaluated at age 21.8 ± 0.3 years, at which time the measurements
were repeated, a euglycemic insulin clamp was performed, and fasting lipids were
measured. All values are expressed in mean ± SEM. Data were analyzed by linear
regression analysis. Body mass index (BMI) in childhood (22.8 ± 0.8) was highly
correlated with BMI in young adulthood (28.3 ± 1.02) (r = 0.72; p = 0.0001). As
shown in Figure 3, although only 2 of the 24 subjects at age 13 had a BMI>27,
at age 22, eleven subjects had a BMI>27.
The Figures below show the regression analyses of the M value on BMI at age
22 (Figure 4), and of M value at age 22 (Figure 5) on BMI at age 13.
These data suggest that: despite the low frequency of obesity at age 13, higher
BMI at age 13 predicted obesity at age 22; at age 22 insulin resistance was
directly correlated with adiposity; and in the relatively nonobese population
higher BMI at age 13 was predictive of insulin resistance at age 22.
Childhood BMI was not only highly correlated with young adult insulin resistance
(r=0.55, p=0.006), but also with total cholesterol (r=0.68, p=0.0006), and LDL-cholesterol
(r=0.70, p=0.0003). These data confirm that adiposity in childhood is a strong
predictor of young adult adiposity and that cardiovascular risk factors such
as insulin resistance and hyperlipidemia in young adulthood are related to the
degree of adiposity established as early as age 13.
c) Relation of Fasting Insulin to Blood Pressure and Lipids in Adolescents
and Parents
The children were 16.7 ± 0.1 years (range: 14-18 years) at the time of this study.
A fasting early morning blood sample was obtained from 183 of the 210 children
(87 boys, 96 girls) and 241 of their parents (143 mothers, 98 fathers) for fasting
insulin and lipids. Fasting insulin was significantly correlated with systolic
blood pressure in the adolescents (r=0.29, p=0.00001) and also in the parents
(r=0.20, p=0.0076) before and after adjustment for BMI. Fasting insulin was correlated
significantly with cholesterol, triglycerides, HDL-C, and LDL-C in the adolescents.
It was correlated only with triglycerides and HDL-C in mothers and fathers. After
adjustment for BMI, the correlations between fasting insulin and lipids in the
children were not significant. Associations between
parents’ and children’s values are shown in the table below.
Pearson Correlation Coefficients (r) Between Parents' and Children’s Fasting
Insulin, Lipids, and Systolic Blood Pressure Before and After Adjustment for BMI
Significant correlations were found between the children
and fathers fasting insulin, triglycerides and HDL-C, whereas significant correlations
were found for fasting insulin and all lipids between mothers and children,
and these remained significant after adjustment for BMI (except for children’s
and father’s triglycerides - see table). A significant relation was shown
for children's systolic blood pressure (dependent variable) regressed on mother’s
fasting insulin and systolic blood pressure. These results show 1) a significant
relation between fasting insulin and both lipids and systolic blood pressure
in adolescents and 2) a significant relation for these factors between adolescents
and their parents. Although weight appears to play an important role in this
relation during adolescence, genetic and environmental factors other than those
mediated via weight appear to be operative in the control of insulin metabolism
within families.
d) Genetic Studies:
A segregation analysis (58) of fasting insulin was performed
on this cohort (16.7 ± 0.1 years) and their parents by _____, Division of _____,
______. Using maximum likelihood methods a model allowing Mendelian transmission
only and a model allowing environmental transmission only was tested against a
general model that incorporated both sets of variables. The Mendelian model was
accepted (p=0.51) and the environmental model was rejected (p=0.00002), leading
to the inference of a major gene. The frequency of the low (L) allele was estimated
to be 0.75 and the frequency of the high (H) allele was 0.25, the mean fasting
insulin value of the LL genotype was 13.7, of the LH genotype was 20.0, and of
the HH genotype was 32.5. The model simulataneously adjusted for the effects of
sex, age, and BMI. As maximum likelihood methods are sensitive to outliers, they
were removed. The major gene accounted for 46% of the total variation, the covariates
accounted for 20% of the total variation and 34% was due to noise.
d. Research Design and Methods
1) Participants
a) Young Adults
The cohort of participants consists of approximately 200 subjects who will be
aged 25-27 years in 1999. These participants originally were recruited in 1985-1986
(at ages 11-14 years) as participants in the "Sodium -Potassium Blood Pressure
Trial in Children" (59). Blood pressure screening was conducted in 19,452
(93% of all enrolled) 5-8th grade students in the _____ and _____ public schools
during regular school days. Blood pressure was measured twice on the right arm
with students in the seated position by trained personnel using a standard clinical
sphygmomanometer and following a standardized protocol (60). All children whose
systolic blood pressure (mean of two measurements) equaled or exceeded the 70th
percentile of the sex and age-specific blood pressure distribution, as derived
from the screening, had their blood pressure measured a second time under identical
conditions. After rescreening of all black, white and Hispanic children, the top
15 percent of the blood pressure distribution (n=3,223) were further screened
for eligibility and willingness to participate; 231 were enrolled, in a four year
blood pressure intervention trial. Blacks represented 17.6% and Hispanics 2.8%
of the total children screened, and their representation in the group of 231 was
12.8% and 1.6%, respectively. The participants were seen in clinic four times
each year for 4 years. At each of the clinic visits, data were obtained for height,
weight and blood pressure. Once each year a complete set of anthropometric data
were obtained, including height and weight, waist and hip circumferences, and
triceps and subscapular skinfold measurements. At the end of four school years,
fasting blood samples were obtained for insulin, glucose and lipids; in addition,
body size measurements and fasting blood samples for glucose, insulin and lipids
were obtained from the parents of the participants. Of the 231 initial participants
we have maintained contact by telephone and postcards with approximately 200 who
are now young adults and have expressed willingness to participate in this study.
b) Parents of the Young Adults
Parents will be seen once in the clinic for anthropometric and blood pressure
measurements, and in the Clinical Research Center for fasting insulin, lipids
and glucose.
2) Clinic and General Clinical Research Center (GCRC) Protocol for Young Adults
For logistic reasons, the protocol requires 2 separate visits, one to a clinic,
the other to the GCRC. The two visits are usually several days apart. This protocol
has been pilot tested in 24 participants as detailed in the preliminary studies
section. Visit contents are summarized in the table below.
Schedule of measurements at the clinic and at the _____ Research Center (_____RC)
______________________________________________________________________________
Clinic
RC
Blood pressure
X
-
Anthropometry (weight, height, X
-
triceps and subscapular skinfold,
waist and hip circumference)
Questionnaires
X
-
(participant past medical history,
family social history, family medical history)
Euglycemic insulin clamp
-
X
Serum lipids
-
X
Echocardiogram
-
X
_________________________________________________________________________________
a) Blood pressure and Anthropometry
After arriving at the clinic, participants will have their seated blood pressure
measured twice, using a random zero sphygmomanometer. Anthropometric measurements
(height, weight, waist and hip circumferences, and subscapular and triceps skinfold
thickness) then will be obtained.
b) Questionnaires
These forms were developed for prior studies at the University of _____ and have
undergone extensive evaluation and use. They include: participant past medical
history, family social history, family medical history, and exercise and diet.
c) Echocardiogram
Echocardiography will be obtained using 2D-Echo guided M-mode imaging with Doppler
to evaluate cardiac mass, cardiac output and cardiac function. Analyses will be
conducted to determine if changes in these measurements can be correlated with
changes in insulin resistance, or blood pressure. All studies will be performed
in the Echocardiography Laboratory of the University of _____ utilizing Hewlett-Packard
echocardiographic equipment by _____, a technician with over _____ years experience.
Measurements will be made by _____. Accuracy will be determined by random selection
of five percent of echocardiograms for evaluation by a second reader and for a
second blinded reading by the applicant. All measurements will be made in accordance
with the recommendations of the American Society of Echocardiography using leading
edge to leading edge methodology (61). The transverse dimensions of the left ventricle
at end diastole and at end systole will be obtained with the ultrasound beam passing
through the left ventricle slightly below the tips of the mitral valve leaflets.
The end-diastolic dimensions of the left ventricular cavity (LVID), posterior
wall (LVPW) and interventricular septum (IVS) will be taken at the onset of the
QRS complex. Left ventricular systolic dimension will be measured at the nadir
of septal motion. Left ventricular cycle length for heart rate calculation also
will be measured at the onset of the QRS complex. The measurements for five consecutive
beats will be averaged for each participant. Left ventricular mass (LVM) will
be calculated utilizing the formula LVM = 0.80 (1.04x(IVS+LVID+LVPW)3-LVID3))+0.6,
as previously recommended by Devereaux et.al. (62). Systolic function will be
estimated by calculating the fractional shortening of the left ventricle (the
difference between the LVID at end diastole and end systole/ LVID at end diastole).
Left ventricular peak systolic wall stress (PSWS) will be estimated utilizing
the formula recommended by Grossmann et.al (63) based on left ventricular end-systolic
(ES) dimensions : PSWS = [(1.35)(systolic BP)(LVID systole)] /[(4)(LVPW systole)(1+LVPW
systole/LVID systole)].
d) Euglycemic Insulin Clamp
The euglycemic clamp studies will be performed in the _____ of the University
of _____. All participants will be admitted to the Center the morning of the study
after fasting from 8:00 p.m. The study will begin at 7:00 a.m. With the participant
in a semi-supine position, a polyethylene cannula will be placed into an antecubital
vein in one arm. A scalp vein needle will be inserted into a dorsal vein of the
other hand, after which that hand will be placed in a warming box at 60 degrees
C to obtain arterialized venous blood samples. The participants will remain semi-supine
(45 degree elevation) throughout the study. Blood will be drawn for sodium, potassium,
glucose, insulin, cholesterol, triglycerides and HDL-C. After the blood samples
are obtained, a constant infusion of insulin will be administered at a dose of
1mU/kg/min for 180 minutes. Concomitantly with the insulin, an intravenous infusion
of 20 percent glucose will be administered by a variable infusion syringe pump
(Harvard Apparatus, Holliston, Mass). Blood samples will be obtained at five minute
intervals for determination of blood glucose concentration. The plasma glucose
concentration will be held constant at baseline by varying the glucose infusion
rate every five minutes. Since at these insulin infusion rates hepatic glucose
output should be nearly completely suppressed, the amount of glucose required
to maintain euglycemia will be used as the index of whole-body glucose uptake.
3) Data Processing and Management
The _____ and_____ (_____) center of the Division of _____ at the University of
_____ available for use by the candidate. This center has experience over decades
in data processing of large epidemiological studies. It has developed a modern
data processing system of national reputation, and its use will assure quality
and completeness of data. Use of the _____ simplifies creating, editing and merging
clean data files. A process to accomplish these tasks has been already in place
for several studies conducted by our group.
Data collected at the clinic will be visually edited, batched and sent to _____
for entry. Data from a particular form are entered and then appended to the entire
data set on a VAX mainframe. The _____ and _____ (_____) in the Department of
_____ at the University of _____ builds in edit and consistency checks for data
entry, so all data are verified and edited and a study data file is created.
4) Quality Control
All personnel participate in training sessions prior to the study and undergo
training in all measurement techniques every six months. Personnel involved in
measurements are compared using Z-scores for each observer (standardized deviates
comparing each observer to the average of all others) and those with significant
Z-scores are retrained and retested.
Forms to be used in this study have been carefully pretested and have been used
previously. All forms are precoded and are reviewed using a clinic checklist before
the participant leaves the clinic.
Laboratory variability will be assessed by a 5 to 10% sample of blind duplicates
sent to each lab to determine the technical error of the measurement, which is
computed as (∑d2/2n)1/2, where d is the difference
between duplicate samples and n is the number of duplicates.
For echocardiograms, a 5% random sample will be selected for a second (blinded)
reading by the candidate and for reading by a second echocardiographer. Inter
and intra-observer measures of agreement will be computed using statistics such
as Kappa and intraclass correlation coefficients.
5) Analysis Plans
a) Analyses of hypothesis #1 and #2
We will initially assess whether anticipated associations hold in cross-sectional
data at age 26, following completion of studies performed in the clinic and in
the Clinical Research Center. In these analyses, relations of insulin resistance
to body fatness and other variables of interest will be characterized, and useful
insights will be provided for subsequent longitudinal analyses. The expectation
is that: 1. body weight and body mass index will be positively correlated with
blood pressure, insulin resistance, dyslipidemia, and left ventricular size; 2.
insulin resistance will be positively correlated with blood pressure,total cholesterol,
triglycerides, LDL-cholesterol and left ventricular size, and negatively correlated
with HDL-cholesterol, and will explain the association of body size to these factors.
Insulin resistance will be defined either as fasting insulin or as the glucose
uptake during the euglycemic insulin clamp. It is expected that relations will
be stronger with the more specific insulin resistance measure, glucose infused
in the euglycemic insulin clamp than with fasting insulin. In each case, for descriptive
purposes, correlation coefficients will be examined, and means and standard errors
of blood pressure, body size, serum lipids, and left ventricular wall thickness
will be examined according to categories of insulin resistance. Multiple regression
analysis with insulin resistance as the dependent variable and body size as the
independent variable of interest will be used to assess whether observed relations
are independent of age, race, sex and blood pressure. General body fatness will
be assessed using the body mass index (wt/ht2), while central fatness
will use waist circumference. Body fatness will also be assessed using triceps
and subscapular skinfolds. Our expectation is that insulin resistance/ body fatness
relations will be found to be independent of all other factors examined. Parallel
analyses will be carried out for other dependent variables: blood pressure, serum
lipids, and left ventricular wall thickness.
Further analyses will be carried out with each of these latter variables as dependent
variables and body size and insulin resistance both as independent variables.
Because we hypothesize that the effect of obesity on these dependent variables
is mediated by insulin resistance, our expectation is that, in these multiple
regression analyses, insulin resistance will be predictive, but body size will
not.
We will specifically assess whether the observed relations are different in race,
sex, serum lipid or blood pressure strata (the latter two for left ventricular
mass). Goodness of fit of regression analyses will be assessed by examining mean
levels of dependent variables according to categories of independent variables.
Hypotheses #1 and #2 are that adolescent levels and changes in body size and insulin
resistance are predictive of the development of adiposity and cardiovascular risk
factors at age 26. The associations are predicted to parallel those seen in the
cross-sectional analyses, that is, that body fatness and insulin resistance in
adolescence will predict young adult obesity and insulin resistance, as well as
changes from adolescence in blood pressure, serum lipids, and left ventricular
wall thickness.
We recognize that, compared to longitudinal analyses, the cross-sectional analyses
are in some ways stronger, and in some ways weaker estimates of the strength of
relations between insulin resistance, body fatness and the cardiovascular risk
factors. The great strength of the cross-sectional analyses is that they pertain
to long term relations in the sense that they represent the cumulative (26 year)
lifetime experience of insulin and body size. However, the cross-sectional analyses
have several weaknesses. They do not assess temporality (for example, does increased
insulin resistance precede or coincide with body size increase) and they do not
take advantage of increased statistical power due to reduced variance of within
person analyses. Longitudinal analyses are more powerful in these respects.
Preliminary analyses will examine means and standard deviations of longitudinal
variables, and correlations between variables. Multiple regression analyses will
use change in each of blood pressure, serum lipids, and left ventricular mass
as dependent variables, and assess their associations with the independent variables
baseline levels of body size and of insulin resistance. In longitudinal as in
cross-sectional analyses we expect stronger relations with the euglycemic clamp
measure than with fasting insulin, and we anticipate that associations with body
size will be explained by insulin resistance.
We will also model change in cardiovascular risk factors (dependent variables)
according to body size and insulin resistance simultaneously a) as level at age
13/17 and b) change until age 26, to examine whether adolescent levels of body
size and insulin resistance are predictive of changes in the cardiovascular risk
factors, independent of their changes during adolescence.
b) Analyses of hypothesis #3, #4
These analyses pertain to gender differences in the development of higher levels
of insulin resistance and left ventricular mass.
Specifically, it is our expectation that the slope of change in left ventricular
mass on body mass index and waist circumference will be steeper in females than
in males. This analysis will be carried out by examining a regression analysis
of change in left ventricular mass on body mass index and waist circumference,
gender and their interactions.
We also anticipate that insulin resistance will be greater in females than in
males, and that this association will be explained in multiple regression by adjustment
for body fatness.
c) Analyses of hypothesis #5
Complex segregation analysis (64) will be performed on the phenotype using the
computer program REGC in SAGE (58). We will compare a set of restricted models
to an unrestricted model. For a single locus with two alleles, the unrestricted
model assumes that up to three unobservable types exist in the data and that these
types may correspond to any genetic inheritance. The three types can be denoted
as AA, Aa, and aa. Corresponding to each type will be a mean value of that type.
This mean is assumed to be the mean of a normal distribution. This mean will be
estimated for each type along with a common standard deviation for the associated
distributions. Three transmission parameters denoting the probability that an
individual with a given type (AA, Aa, or aa) transmits A to an offspring, will
be estimated in the unrestricted model. Different patterns among these transmission
parameters will indicate whether an environmental effect or a single gene explains
the data. These two possibilities, environmental (cardiovascular risk factor)
or genetic, form the two subclasses of restricted models. These classes of restricted
models will be tested against the unrestricted model using the unified approach
of Lalouel et al. (65). The first class of models allows only random environmental
effects. The value of the transmission parameters are all equal in this model,
i.e. the types have no effect on the data. Variations on this model allow for
polygenic inheritance and heterogeneity between generations. The second class
of models assumes Mendelian transmission is the major cause of phenotypic variation.
The three Mendelian transmission parameters are (1,1/2,0), i.e. the probability
that AA transmits A to his offspring is 1, the probability that Aa transmits A
to his offspring is 1/2, and the probability that aa transmits A to his offspring
is 0. Variations on this model include restrictions on the means that represent
dominant and recessive effects. Residual non-independence among relatives is subsumed
into familial correlation parameters.
In humans, random mating is usually assumed. This implies that the frequencies
of the types follow Hardy-Weinberg proportions (p2: 2p(1-p): (1-p)
2), thus only one allele frequency, p, is required. In human populations
deviations from Hardy-Weinberg equilibrium are almost unknown (66).
Effects of covariates that have been shown to be significant in simpler models
or are suspected of having an effect based on prior information will be estimated
simultaneously. Each restricted model will be compared with the unrestricted model
using likelihood ratio statistics which are twice the difference between the natural
log-likelihoods of the unrestricted and restricted models. These test statistics
are approximately asymptotically distributed as a chi-square distribution with
degrees of freedom equal to the difference in the number of parameters between
the two models being compared. If there is no significant difference between the
models then the more parsimonious restricted model is preferred. A "major
gene" is said to exist when the Mendelian model is accepted and the environmental
model is rejected. Effects between the two age points will be evaluated with standard
statistical paired and longitudinal methods similar to those presented in the
previous section of this proposal.
d) Analyses of Hypothesis #6
This hypothesis states that the young adult (age 26) M values arise from 3 separate
distributions, each corresponding to one genetic type (AA, Aa, or aa) of a Mendelian
trait. Although parent M values from the euglycemic clamp will be be available,
it is still possible to deconvolute the histogram of young adult M values, to
estimate the 3 underlying probability distributions. The program REGC can be used
for this purpose. If the hypothesis is true, REGC will estimate that the observed
distribution of M is well described as the sum of 3 underlying normal distributions,
with varying means. such a deconvolution was shown to hold in an analysis preliminary
to the segregation analysis carried out using the fasting insulin values at age
17, and is expected to hold for M values, a more direct measure of insulin resistance.
e) Detectable differences
The detectable difference in change in left ventricular mass from adolescence
through young adulthood, according to level of fasting insulin at age 17 was estimated
based on the detectable linear regression coefficient, using variances based on
age 17 fasting insulin and pilot study left ventricular mass. The standard deviation
of change in left ventricular mass was 36 grams, and of fasting insulin at age
17 was 10 microU/ml. Assuming that we observe a sample of about 200, we estimated
the standard error of the regression coefficient of left ventricular mass on fasting
insulin to be 36/(10*√199) = 0.25 g/microU/ml. For alpha = 0.05 and power
= 0.85, the regression coefficient must be at least 3 times its standard error
(0.75 g/microU/ml) to be declared statistically significant. This corresponds
to 7.5 g per 10 microU/ml (one standard deviation) of baseline insulin. A difference
of this magnitude is of clinical interest, and the study is deemed to have adequate
power.
5. Career Development Plan
This career development plan incorporates a multi-disciplinary program designed
to provide an intense, closely mentored, patient-oriented research experience
in association with a comprehensively structured didactic curriculum in epidemiology.
The goal is to build on the Candidate's previous training and experience in clinical
Cardiology while providing the additional epidemiologic skills required to successfully
pursue a clinical research career. The Candidate’s record, to date, indicates
a strong commitment to an academic career. On completion of this plan she will
have the ability to compete on a national basis for patient-oriented research
funding, independent of her mentors.
This is a five year program in which the clinical research protocol will run concurrently
with the didactic course. Attempting to schedule the didactic sessions in a solid
block of time would require a two-year full time commitment by the Candidate and
eliminate the possibility of any meaningful work on the research protocol. The
nature of this type of patient-oriented research is such that it demands regular
attention over a multi-year time frame. Thus, the program will allow the Candidate
to enroll in classes spread over a four-year period and provide sufficient time
to organize and conduct the clinical research. In addition, attempting to concentrate
either component of this plan to a greater degree will not allow for the 25% time
allotted by this award for ongoing clinical activities.
a. Didactic Component
The didactic component will be conducted in the Division of _____, _____(_____).
The Candidate will be enrolled in an Interdisciplinary Graduate Program in Clinical
Research. This program consists of 53 credits of course work (quarter basis) and
offers an MS degree in Public Health. As noted above, the Candidate will successfully
complete the course over four years. This course will provide a comprehensive
educational resource that will prepare the Candidate for all aspects of patient-oriented
research, including, but not limited to, the following :
1) Biostatistics: probability models, hypothesis testing, regression and correlation
techniques, analysis of variance, multiple regression analysis, model selection
and analysis, and others.
2) Epidemiologic Principles; general principles applicable to epidemiologic
studies.
3) Clinical Trials: methodology of randomized clinical trials, including design
issues, case examples, operational aspects and applications to follow-up studies.
4) Epidemiologic Methods: methods and techniques for collecting and managing
research data , including sampling, response rates, forms design, training interviewers,
and data preparation , entry, cleaning, and management.
5) Research Grant Writing: mechanics of grant development and writing, principles
of informed consent, budget development, grant-review process.
6) Statistical Computing: analyzing biomedical data.
7) Biomedical Ethics.
8) Genetic Epidemiology: disease within relatives, inherited disease in populations,
case-control family studies, twin studies, segregation analysis, gene mapping.
9) Electives.
10) Thesis.
In addition to the course work, _____ will participate in the Division of _____
graduate student research seminars.
b. Research Plan
The research plan will build on the Candidate's prior patient-oriented research
experience in which she has had the opportunity to observe methodologies for protocol
development, participant recruitment, and data gathering and has been trained
in the insulin clamp procedure for determining insulin resistance. The Candidate
will be the Principal Investigator on this grant. She will be responsible for
patient recruitment and scheduling and will conduct the insulin clamps in the
_____. She will ensure accurate data collection and entry and will be responsible
for data analysis.
It is anticipated that the proposed protocol will be completed over five years.
By balancing the didactic program with the research proposal, adequate time will
be provided for the significant patient-oriented activities required to successfully
complete the study.
c. Mentors
1)
_____.
_____ has been a member of the Division of _____, Department of _____ since 1974.
The Division has trained approximately 30 fellows during that time, and approximately
90% of them currently are in academic faculty positions.
_____ has been involved in patient-oriented research on cardiovascular risk factors
for over 20 years. He is nationally and internationally recognized for his studies
in blood pressure and cardiovascular risk in children and young adults. Specifically,
he has had ongoing NIH funding since 1985 for large cohort studies of the type
proposed in this application and currently is Principal Investigator of the study
“_____”. He has served on _____ and is a member of the _____ and the
_____.
2)
_____
_____ has been a member of the Division of _____ since 1974. Since 1988, he has
been advisor or co-advisor for 19 Ph.D. students, 17 of whom are currently in
academics or government research, and 8 postdoctoral fellows, all of whom are
still in research.
_____ is expert in epidemiologic and biostatistical methodology and in conduct
and analysis of large observational studies. He is nationally and internationally
recognized for his studies of determinants of cardiac and other chronic disease
and public health interventions and currently is Principal Investor on two NIH
funded studies. He and _____ have worked closely together for a number of years.
d. Group Support
_____ will meet weekly with her mentor, _____, and will participate in the activities
of the clinical research/epidemiology group associated with ongoing research of
cardiovascular risk. This group, consisting of _____, _____, _____, _____, and
_____ meets bi-weekly to review progress in current studies, review data analyses,
consider new questions and areas of research suggested by these data, plan for
submission of new grant proposals and funding, and plan and review manuscripts.
In addition, _____ will meet regularly with _____ to review data collection and
analysis questions and with _____, and _____ to discuss specialized areas of her
research and course work.
e. Instruction in Responsible Conduct of Research
_____ has completed a required course, "Responsible Conduct in Research"
given by the University of _____ on June 10-11, 1996. Subjects included: 1) The
role of the scientist in society; 2) Environmental health and safety issues; 3)
Responsibility and ethics regarding the role of the faculty member in mentoring;
4) The role of the institutional review board in ensuring appropriate participant
consent, risk-benefit balance, justice, advocacy for research subjects, adverse
event recording, modification of protocol; 5) Code of conduct regarding fabrication
of data, plagiarism, supervision of research and assignment of authorship, and
fiscal responsibility; 6) Conflict of interest.
During the period of the Award _____ will enroll in Philosophy 8320, “Ethical
Issues in Human Experimentation. This course will discuss ethical protection of
human subjects, definition of research, informed consent, competency, and ethics
of research on vulnerable subjects such as children, prisoners, and the mentally
ill.
Section III: Other Information
1. Research Plan Continued
a. Minorities and Women:
1) The subject population will be approximately
200 young adults, ages 25-27 years, equally divided between males and females,
approximately 13% African-American, 2% Hispanic and 85% white, and in excellent
health.
b. Human Subjects:
1) Research material obtained from
individuals will consist of blood specimens, urine specimens and information
recorded on a number of forms. These materials and data will be obtained specifically
for research purposes.
2) Recruitment will be by letter,
telephone call and personal interviews. The participants will sign informed
consent and a copy of the consent will be provided to all participants and/or
parents. Participants will be fully informed of all procedures to be performed
and how all information will be used. Consent will be documented by signature
of the participant and will be witnessed by clinic personnel. The Institutional
Review Board has not authorized any modifications or waiver of the elements
of consent.
3) The risks from this study are
minimal. There is the potential that a small amount of pain will occur during
the blood drawing. The measurements and form completion have been performed
in numerous studies by our group and have not been shown to be a risk. The potential
risk associated with the insulin clamp studies is minimized by performing these
studies in the _____ under close medical supervision.
4) Absolute confidentiality will
be maintained. All data are stored in locked compartments and are not released
without consent of the participants. If data are used in scientific presentations
or publications, individuals are never identified. All data will be monitored
by the applicant and Sponsor at their meetings.
5) Identification of physiologic
and/or biochemical factors that may be associated with the onset of cardiovascular
risk offers the opportunity to initiate intervention strategies early in development
in order to prevent onset of the disease. A number of basic and clinical studies
have suggested that insulin resistance may be etiologically related to cardiovascular
risk. Thus, determining the relation between insulin resistance, and other risk
factors during childhood and adolescence may help reduce the incidence of cardiovascular
disease. The very small risk involved with this study may result in great benefit,
if the findings lead to a greater understanding of factors that cause cardiovascular
disease.
c. Vertebrate Animals
Not applicable
d. Literature Cited
e. Consortium/Contractual Arrangements
Not applicable
2. Checklist
3. Appendix
