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258 Pages·2015·9.1 MB·English

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This document contains a collection of the 2015 NYCEF abstracts.

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HGNChelper: Identification and correction of invalid
human gene symbols

Background

Gene symbols are intuitively appealing and popular identifiers, but prone to error. Aliases for
the same gene occur across different disciplines, and descriptive symbols change over time as
gene function is identified. Worse, most spreadsheet programs can introduce mislabeling as
certain gene symbols are converted to date formats. Many bioinformaticians incorrectly assume
that by using annotations directly from public databases, and avoiding Excel, these problems
can be avoided. The Human Gene Nomenclature Committee (HGNC) maintains the official
database gene symbols and their aliases; however it cannot be accessed programmatically and
does not correct symbols that have been mogrified by spreadsheet programs.
Results
We present the HGNChelper R package and website, which identifies and corrects known
aliases and outdated gene symbols, as well as date modifications introduced by spreadsheets.
We used HGNChelper to analyze the annotations of all 4,161 Homo Sapiens microarray
platforms in the Gene Expression Omnibus (GEO). Platform annotations contained large
fractions of invalid symbols, most of which could be corrected by HGNChelper.
Conclusions
HGNChelper is implemented as an R package for high-throughput programmatic correction, and
as a web page for simple interactive usage. HGNChelper improves the mapping of genomic
platform annotations, published gene signatures, and can prevent the embarrassment of
publishing “DEC-1” as a candidate disease-associated gene.
Title: Validation of self-rated overall diet quality by Healthy Eating Index 2010 score among New
York City adults, 2013
Authors: Tamar Adjoian*, Melanie J. Firestone, Donna Eisenhower, Stella S. Yi
Presenter email address: [email protected]
Affiliation: New York City Department of Health and Mental Hygiene, Bureau of Chronic Disease
Prevention and Tobacco Control
Word Count: 354

Background: Chronic conditions such as cardiovascular disease and cancer can result from a number of
environmental and behavioral factors; an important contributor to the incidence or prevention of such
conditions is dietary intake. Screening for poor diet is helpful in developing interventions to prevent
chronic disease, but measuring dietary behavior can be costly and time-consuming. The purpose of this
study was to determine if the single-item measure of self-rated diet could serve as an adequate proxy for
evaluating diet quality for population surveillance.

Methods: A 24-hour dietary recall and self-rated diet quality were collected for 485 adult (18 years and
older) New York City residents. Dietary recalls were obtained using the ASA24 Automated Self-
administered 24-hour Recall online system developed by the National Cancer Institute, Bethesda, MD.
From dietary recall output, Healthy Eating Index (HEI) 2010 scores were computed (from 0-100 possible
points) and compared with self-rated diet responses, which were reported as part of a 5-point Likert scale
(5 = “excellent,” 4 = “very good,” 3 = “good,” 2 = “fair,” 1 = “poor”).

Results: The study sample was 57% female, 47% white, 56% college educated, and 45% in the highest
income tertile. The mean HEI-2010 score was 56.5 out of a possible 100. Women averaged higher HEI
scores than men (58.1 vs 54.3). There was a modest yet significant correlation between HEI scores and
self-rated diet (ρ = 0.282, p <.01). The average HEI score for those rating their diet quality as “fair” or
“poor” was below 50, which is the USDA’s threshold for poor diet quality using HEI-2010 scores (“fair”:
48.6, “poor”: 48.2). Overall, mean HEI score increased as self-rated diet improved (from 48.2 for “poor”
to 63.0 for “excellent”).

Conclusions: Diet quality was relatively low, even among those with “excellent” self-ratings. However,
those who rated their diet as fair or poor had HEI scores below 50, which corresponds to the USDA
classification of “poor diet.” Thus, though not a flawless proxy, the single-item measure of self-rated diet
may provide a simple method of ranking by diet quality and may serve to identify those individuals and
populations with the lowest diet quality.
The impact of obesity on prostate cancer recurrence observed after exclusion of diabetics.

Ilir Agalliu 1,2 * , Steve Williams 2, Brandon Adler 1, Lagu Androga 2, Michael Siev 2, Juan Lin 1, Xiaonan Xue 1,
Gloria Huang 3, Howard D. Strickler 1, Reza Ghavamian 2

1. Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY.
2. Department of Urology, Albert Einstein College of Medicine and Montefiore Medical Center Bronx, NY
3. Department of Obstetrics, Gynecology and Women’s Health, Albert Einstein College of Medicine, Bronx, NY.
*Ilir Agalliu: [email protected]

Abstract
Background: The association between obesity and risk of prostate cancer (PrCa) recurrence is uncertain,
following conflicting reports. While the summary effect estimate from a recent meta-analyses suggested a relative
risk (RR) of 1.16 (95% CI: 1.08–1.24) for PrCa recurrence per 5 kg/m2 increase in body mass index (BMI), only 11
of 26 studies included in this analysis reported statistically significant positive associations. We investigated
whether the failure to exclude diabetics in prior studies could have increased the likelihood of null results.
Methods: A total of N=610 racially and ethnically diverse PrCa patients (36% African-American and 38%
Hispoanic) who underwent radical prostatectomy for their cancer between 2005 and 2012 at Montefiore Medical
Center in the Bronx were followed for recurrence, defined as a rise in serum PSA ≥0.2 ng/ml following surgery.
Patients’ BMI and history of type 2 diabetes were documented prior to surgery. The analysis was conducted using
Cox proportional hazard models, adjusted for age and clinical/pathological variables that were associated with PrCa
recurrence such as pre-operative PSA, pathological Gleason score, tumor stage, and positive surgical tumor
margins.
Results: Obesity (25.6%) and diabetes (18.7%) were common in this cohort. There were 87 (14.3%)
recurrence events during a median follow-up of 30.8 months after surgery among the 610 patients. When analyzed
among all PrCa patients, no association was observed between BMI/obesity and PrCa recurrence. However, when
analysis was limited to non-diabetics, there was 38% increased risk of PrCa recurrence (95% CI 1.05 – 1.82) per 5
kg/m2 in BMI increase. In particular obese men had a 2.27-fold increased risk (95% CI 1.17-4.41) of PrCa
recurrence relative to normal weight men, after adjusting for age and clinical / pathological tumor characteristics.
Conclusions: This study found a greater than two-fold association between obesity/BMI and PrCa recurrence
in non-diabetics. We predicted these results because the relationship between BMI/obesity and the biologic factors
that may underlie the PrCa recurrence – BMI/obesity association, such as insulin, may be altered by the use of anti-
diabetes medication or diminished beta-cell insulin production in advanced diabetes. Studies to further assess the
molecular factors that explain the BMI/obesity – PrCa recurrence relationship are warranted.

1
Title: Bronchiolitis in first 2 years of life as a predictor of Wheezing and Asthma development later
in childhood
Authors: Muhammad Waseem, MD. Anyelina Delacruz, MD. Wendy Henriquez, MD. Mark Leber, MD.
*Seleipiri Iboroma Akobo, RN, BSN, MPH.
Affiliation: Department of Pediatrics, Lincoln Medical and Mental Health Center and Weill Cornell
Medical College, Bronx NY. [email protected]
Background: Viral bronchiolitis (mainly RSV, adenovirus, parainfluenza and influenza) remains a major
cause of childhood morbidity, hospital admissions and a huge financial burden on the economy. These
diseases once acquired will complete its natural course and severity varies from person to person
depending upon age, immunological status and comorbidities. Treatment is mainly supportive. Evidence
from a large number of studies suggest that bronchiolitis in infancy is often associated with recurrent
wheezing and asthma during subsequent years. Due to high incidence, it is imperative to establish a
relationship between the incidence of viral bronchiolitis and its sequelae, mainly the future episodes of
wheezing and eventual diagnosis of asthma.
Method: A retrospective cohort study design was used and medical records of 1991 patients <2years of
age presenting to the emergency department for viral bronchiolitis from January 2000 to December 2010
reviewed. In addition to demographic information, the number of bronchiolitis episodes and information
regarding the presence of atopy were also obtained. These children were followed for a year to determine
whether they received a diagnosis of airway hyperactivity manifesting as wheezing and asthma via the
pediatric clinic records. A stepwide logistic regression was then performed to determine the factors
predicting asthma.
Result: The medical records of 1991 children with the diagnosis of bronchiolitis were reviewed. Of these,
832 (41.8%) were female and 1159 (58.3%) were male. 1374 (69.0%) were Hispanic, 501 (25.2%) were
African Americans and 116 (5.8%) were others. 259 (13.0%) children were discharged from the ED, 1443
(72.5%) had one hospitalization, 252 (12.7%) had 2 hospitalizations, 33 (1.7%) had 3 hospitalizations and
4 (0.2%) children had 4 hospitalizations. Over a period of one year, 817 (41.0%) children received a
diagnosis of asthma, while 1174 (59.0%) children were not diagnosed with asthma. Of 817 children with
the diagnosis of asthma, 319 (39.0%) were female and 498 (60.94%) were male. 647 had one prior
episode, 150 had 2 episodes, 17 of these children had 3 episodes, and 3 had 4 episodes of bronchiolitis.
Using logistic regression, the following variables were the best predictors of asthma: Male gender (OR
1.3; 95% CI 1.05-1.55), family history of asthma (OR 1.6; 95% CI 1.33-1.95), atopy (OR 1.4; 95% CI
1.12-1.83), age more than 5 months (OR 1.4 95% CI 1.13-1.66), more than 2 episodes of bronchiolitis
(OR 2.4; 95% CI 1.79-3.07) and allergies (OR1.6; 95% CI 1.14-2.14) The model had a 60.1% positive
predictive value, sensitivity of 31.2% and a specificity of 84.9%.
Conclusion: Being an older male greater than or equal to 5 months of age, with a history of at least 2
episodes of bronchiolitis evaluated in the ED, a history of atopy and allergies predicted the development
of asthma in later years.
Title:

 Simulating
 confidential
 epidemiological
 datasets

Authors
 and
 affiliations:

Ragheed
 F.
 Al-­‐Dulaimi,
 MPH
 1
 *
 <[email protected]>

Rebekkah
 Robbins,
 MPH2

Stephanie
 Chamberlin,
 MPH2

Mckaylee
 M
 Robertson,
 MPH1,
 2
 ,
 3

Sarah
 G.
 Kulkarni,
 MPH1

Mary
 Irvine,
 DrPH
 2

Denis
 Nash,
 PhD
 1,
 3

Levi
 Waldron,
 PhD
 1,
 3
 *
 <[email protected]>

(1) Hunter
 College-­‐
 CUNY
 School
 of
 Public
 Health

(2) NYC
 Department
 of
 Health
 and
 Mental
 Hygiene

(3) CUNY
 Graduate
 Center

Abstract:

Epidemiological
 datasets
 containing
 personally
 identifiable
 information
 often
 must
 be
 stored
 in
 secure,

tightly
 controlled
 environments
 to
 project
 subject
 confidentiality.

 These
 datasets
 may
 be
 complex
 in

structure,
 and
 may
 not
 be
 fully
 available
 until
 final
 collection
 and
 cleaning,
 delaying
 code
 development

and
 data
 analysis.
 Furthermore,
 collaboration
 across
 multiple
 research
 centers
 may
 make
 development

of
 a
 detailed
 data
 analysis
 plan
 difficult,
 especially
 when
 data
 access
 is
 limited
 to
 one
 site.

 We
 present
 an
 R
 package
 “episim”
 generate
 simulations
 of
 such
 complex
 datasets,
 while
 mimicking

their
 summary
 statistics
 and
 idiosyncrasies.

 The
 package
 generates
 categorical
 variables
 with
 matching

prevalences,
 continuous
 variables
 with
 matching
 quantiles,
 missing
 data,
 transformed
 variables
 such
 as

discretized
 versions
 of
 continuous
 variables
 and
 categorical
 variables
 with
 re-­‐aggregated
 bins.

 Using
 a

simple
 Excel
 spreadsheet
 as
 input,
 it
 facilitates
 simulation
 of
 a
 wide
 range
 of
 study
 designs
 and
 variable

types
 by
 users
 with
 minimal
 programming
 skills
Erin M. Andrews, DrPH(c), MPH*
SUNY Downstate Medical Center School of Public Health
[email protected]

Title: The Impact of Health Insurance Coverage on Obesity in Young Adults in the U.S. (in progress)

Background: Heart disease is the leading cause of death and although cardiovascular disease mortality
among young adults has declined recently, the morbidity of related diseases, specifically obesity, has
increased. The explanation for the increase is complex but may be attributed to individual behavior (diet
and exercise) and extrinsic properties (access to care). Health insurance is designed to provide access to
health care and emphasize disease prevention. The purpose of this analysis is to determine the
importance and role of health insurance in overweight and obesity in adolescents and young adults.
Objective: Does the absence of health insurance coverage increase the likelihood of overweight and
obesity among young adults? Methods: The National Longitudinal Survey of Youth (NLSY) 1997 is a
nationally representative longitudinal sample of 8,984 young Americans between 12 and 17 years old in
1997 and follows the respondents until 2011. The predictor, health insurance status, was measured
annually and was dichotomized as yes (had some form of health insurance) or no (did not have health
insurance). The respondents’ health insurance status will be noted annually from 2002 to 2010.
Respondents will be divided up into a control group: Insured (had health insurance for 5 or more years)
and a treatment group: Uninsured (did not have health insurance for 5 or more years). The outcome,
overweight/obesity, defined as a Body Mass Index (BMI) ≥ 25, will be measured in 2011. Statistical
analyses will include descriptive statistics and bivariate analyses of health insurance status and all control
variables. The analyses will be conducted to test for associations between the control variables and health
insurance status, but also to detect any differences between the control and treatment groups using a t-test
or Wilcoxon test when appropriate. Logistic regression will be conducted to determine which control
variables predict overweight and obesity (BMI≥ 25). Propensity score matching will be used to match
the control (health insurance) and treatment group (no health insurance) on necessary variables. Adjusted
logistic regression models will determine if the absence of health insurance is a predictor for excess
weight. All analyses will be performed at the 95% confidence level in Stata 13.1. Implications: Results
from these analyses will bridge an important gap in literature by addressing the causal impact of health
insurance on overweight and obesity in young adults. This research will determine if health insurance,
which has now been expanded to all eligible Americans under the Affordable Care Act, is an effective
preventative measure against the growing prevalence of obesity. Recommendations will include obesity
and cardiovascular disease prevention methods among young adults that is not addressed in current health
care legislation.
Incident (Injury) surveillance and associations with socioeconomic status indicators
among youth/young workers in New Jersey secondary schools

*Alexsandra A. Apostolico, MPH, BS1,2 and Derek G. Shendell, D.Env, MPH1,3,4
1 Rutgers School of Public Health (SPH), Center for School and Community-Based Research and
Education (NJ Safe Schools Program), New Brunswick, NJ
2 Department of Epidemiology, Rutgers SPH, Piscataway, NJ
3 Department of Environmental and Occupational, Rutgers SPH, Piscataway, NJ
4 Exposure Measures and Assessment Division, Environmental and Occupational Health Sciences
Institute, Rutgers Robert Wood Johnson Medical School, Piscataway, NJ
*Email address of presenter: [email protected]

Background: New Jersey Department of Education requires by law for accidents/incidents (injury or
illness) involving career-technical-vocational education (CTE) students, and/or staff to be reported to the
Commissioner of Education within five business days. These incidents get directly reported to New
Jersey Safe Schools Program (NJSS) online surveillance system (via Psychdata) for aggregate analyses.
Methods: To explore associations between socioeconomic status (SES) indicators and injuries reported to
NJSS, District Factor Groups (DFGs) were used as a proxy indicator for SES of a reporting school/school
district. Reporting schools were classified by DFG status as either a ‘high’ or ‘low’ scoring school,
depending on the SES of the county in which they are located. Data were analyzed from NJSS injury
surveillance database between 12/1998-12/2013. Chi square tests (X2) for independence were conducted
to examine associations between DFG and various variables, including gender, injury treatment (hospital
versus doctor), injury location on body, injury type, injury cause, severity of injury, and use of personal
protective equipment (PPE). To assess potential associations between DFG scores and personal protective
equipment, data were stratified by years, 2003-2008 and 2008-2013 given mandatory payment by
employers for PPE determined necessary for employees in 2008 (NJ 2/2008-, U.S. 10/1/2008-).
Results: Statistically significant associations were found between DFG scores and injury cause [X2= (7,
14.74), p=0.039] as well as DFG scores and injury treatment [X2= (1, 4.76), p=0.029]. Logistic regression
was performed to better understand potential associations between treatment and DFG score. Adjusted
odds ratio comparing injured students of low DFG scoring schools being treated at a hospital to injured
students of high DFG scoring schools being treated at a hospital was 2.4 (95% CI = 1.3-4.3).