Publications by authors named "Anindya Bhadra"

18 Publications

  • Page 1 of 1

Association of food insecurity with dietary intakes and nutritional biomarkers among US children, National Health and Nutrition Examination Survey (NHANES) 2011-2016.

Am J Clin Nutr 2021 May 8. Epub 2021 May 8.

Department of Nutrition Science, Purdue University, West Lafayette, IN, USA.

Background: Food insecurity is associated with poorer nutrient intakes from food sources and lower dietary supplement use. However, its association with total usual nutrient intakes, inclusive of dietary supplements, and biomarkers of nutritional status among US children remains unknown.

Objective: The objective was to assess total usual nutrient intakes, Healthy Eating Index-2015 (HEI-2015) scores, and nutritional biomarkers by food security status, sex, and age among US children.

Methods: Cross-sectional data from 9147 children aged 1-18 y from the 2011-2016 NHANES were analyzed. Usual energy and total nutrient intakes and HEI-2015 scores were estimated using the National Cancer Institute method from 24-h dietary recalls.

Results: Overall diet quality was poor, and intakes of sodium, added sugars, and saturated fat were higher than recommended limits, regardless of food security status. Food-insecure girls and boys were at higher risk of inadequate intakes for vitamin D and magnesium, and girls also had higher risk for inadequate calcium intakes compared with their food-secure counterparts, when total intakes were examined. Choline intakes of food-insecure children were less likely to meet the adequate intake than those of their food-secure peers. No differences by food security status were noted for folate, vitamin C, iron, zinc, potassium, and sodium intakes. Food-insecure adolescent girls aged 14-18 y were at higher risk of micronutrient inadequacies than any other subgroup, with 92.8% (SE: 3.6%) at risk of inadequate intakes for vitamin D. No differences in biomarkers for vitamin D, folate, iron, and zinc were observed by food security status. The prevalence of iron deficiency was 12.7% in food-secure and 12.0% in food-insecure adolescent girls.

Conclusions: Food insecurity was associated with compromised intake of some micronutrients, especially among adolescent girls. These results highlight a need for targeted interventions to improve children's overall diet quality, including the reduction of specific nutrient inadequacies, especially among food-insecure children. This study was registered at clinicaltrials.gov as NCT03400436.
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http://dx.doi.org/10.1093/ajcn/nqab113DOI Listing
May 2021

Temporal physical activity patterns are associated with obesity in U.S. adults.

Prev Med 2021 Jul 30;148:106538. Epub 2021 Mar 30.

Department of Nutrition Science, Purdue University, West Lafayette, IN 47907, USA. Electronic address:

Few attempts have been made to incorporate multiple aspects of physical activity (PA) to classify patterns linked with health. Temporal PA patterns integrating time and activity counts were created to determine their association with health status. Accelerometry data from the National Health and Nutrition Examination Survey 2003-2006 was used to pattern PA counts and time of activity from 1999 adults with one weekday of activity. Dynamic time warping and kernel k-means clustering partitioned 4 participant clusters representing temporal PA patterns. Multivariate regression models determined associations between clusters and health status indicators and obesity, type 2 diabetes, and metabolic syndrome. Cluster 1 with a temporal PA pattern of the lowest activity counts reaching 4.8e cph from 6:00-23:00 was associated with higher body mass index (BMI) (β = 2.5 ± 0.6 kg/m, 95% CI: 1.0, 4.1), higher waist circumference (WC) (β = 6.4 ± 1.3 cm, 95% CI: 2.8, 10.0), and higher odds of obesity (OR: 2.4; 95% CI: 1.3, 4.4) compared with Cluster 3 with activity counts reaching 9.6e-1.2e cph between 16:00-21:00. Cluster 1 was also associated with higher BMI (β = 1.5 ± 0.5 kg/m, 95% CI: 0.1, 2.8) and WC (β = 3.6 ± 1.3 cm, 95% CI: 0.1, 7.0) compared to Cluster 4 with activity counts reaching 9.6e cph between 8:00-11:00. A Temporal PA pattern with the lowest PA counts had significantly higher mean BMI and WC compared to temporal PA patterns of higher activity counts performed early (8:00-11:00) or late (16:00-21:00) throughout the day. Temporal PA patterns appear to meaningfully link to health status.
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http://dx.doi.org/10.1016/j.ypmed.2021.106538DOI Listing
July 2021

Temporal Dietary Patterns Are Associated with Obesity in US Adults.

J Nutr 2020 12;150(12):3259-3268

Department of Nutrition Science, Purdue University, West Lafayette, IN, USA.

Background: The integration of time with dietary patterns throughout a day, or temporal dietary patterns (TDPs), have been linked with dietary quality but relations to health are unknown.

Objective: The association between TDPs and selected health status indicators and obesity, type 2 diabetes (T2D), and metabolic syndrome (MetS) was determined.

Methods: The first-day 24-h dietary recall from 1627 nonpregnant US adult participants aged 20-65 y from the NHANES 2003-2006 was used to determine timing, amount of energy intake, and sequence of eating occasions (EOs). Modified dynamic time warping (MDTW) and kernel k-means algorithm clustered participants into 4 groups representing distinct TDPs. Multivariate regression models determined associations between TDPs and health status, controlling for potential confounders, and adjusting for the survey design and multiple comparisons (P <0.05/6).

Results: A cluster representing a TDP with evenly spaced, energy balanced EOs reaching ≤1200 kcal between 06:00 to 10:00, 12:00 to 15:00, and 18:00 to 22:00, had statistically significant and clinically meaningful lower mean BMI (P <0.0001), waist circumference (WC) (P <0.0001), and 75% lower odds of obesity compared with 3 other clusters representing patterns with much higher peaks of energy: 1000-2400 kcal between 15:00 and 18:00 (OR: 5.3; 95% CI: 2.8, 10.1), 800-2400 kcal between 11:00 and 15:00 (OR: 4.4; 95% CI: 2.5, 7.9), and 1000-2600 kcal between 18:00 and 23:00 (OR: 6.7; 95% CI: 3.9, 11.6).

Conclusions: Individuals with a TDP characterized by evenly spaced, energy balanced EOs had significantly lower mean BMI, WC, and odds of obesity compared with the other patterns with higher energy intake peaks at different times throughout the day, providing evidence that incorporating time with other aspects of a dietary pattern may be important to health status.
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http://dx.doi.org/10.1093/jn/nxaa287DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7726125PMC
December 2020

Older adults with obesity have higher risks of some micronutrient inadequacies and lower overall dietary quality compared to peers with a healthy weight, National Health and Nutrition Examination Surveys (NHANES), 2011-2014.

Public Health Nutr 2020 09 29;23(13):2268-2279. Epub 2020 May 29.

Department of Nutrition Science, Purdue University, West Lafayette, IN47907, USA.

Objective: To evaluate total usual intakes and biomarkers of micronutrients, overall dietary quality and related health characteristics of US older adults who were overweight or obese compared with a healthy weight.

Design: Cross-sectional study.

Setting: Two 24-h dietary recalls, nutritional biomarkers and objective and subjective health characteristic data were analysed from the National Health and Nutrition Examination Survey 2011-2014. We used the National Cancer Institute method to estimate distributions of total usual intakes from foods and dietary supplements for eleven micronutrients of potential concern and the Healthy Eating Index (HEI)-2015 score.

Participants: Older adults aged ≥60 years (n 2969) were categorised by sex and body weight status, using standard BMI categories. Underweight individuals (n 47) were excluded due to small sample size.

Results: A greater percentage of obese older adults compared with their healthy-weight counterparts was at risk of inadequate Mg (both sexes), Ca, vitamin B6 and vitamin D (women only) intakes. The proportion of those with serum 25-hydroxyvitamin D < 40 nmol/l was higher in obese (12 %) than in healthy-weight older women (6 %). Mean overall HEI-2015 scores were 8·6 (men) and 7·1 (women) points lower in obese than in healthy-weight older adults. In addition, compared with healthy-weight counterparts, obese older adults were more likely to self-report fair/poor health, use ≥ 5 medications and have limitations in activities of daily living and cardio-metabolic risk factors; and obese older women were more likely to be food-insecure and have depression.

Conclusions: Our findings suggest that obesity may coexist with micronutrient inadequacy in older adults, especially among women.
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http://dx.doi.org/10.1017/S1368980020000257DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7429309PMC
September 2020

Correction: Marah Aqeel et al. "The Effect of Timing of Exercise and Eating on Postprandial Response in Adults: A Systematic Review". Nutrients 2020, 12, 221.

Nutrients 2020 Apr 29;12(5). Epub 2020 Apr 29.

Department of Nutrition Science, Purdue University, West Lafayette, IN 47907, USA.

In the original paper, the total number of included studies was = 20 and is = 17 in the revised version. Also, in the original paper, the total number of participants was = 352, while it is = 332 in the revised paper.
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http://dx.doi.org/10.3390/nu12051263DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7281960PMC
April 2020

The Effect of Timing of Exercise and Eating on Postprandial Response in Adults: A Systematic Review.

Nutrients 2020 Jan 15;12(1). Epub 2020 Jan 15.

Department of Nutrition Science, Purdue University, West Lafayette, IN 47907, USA.

Type 2 diabetes is a major public health concern. Management of this condition has focused on behavior modification through diet and exercise interventions. A growing body of evidence has focused on temporality of dietary intake and exercise and potential effects on health. This review summarizes current literature that investigates the question "how does the timing of exercise relative to eating throughout the day effect postprandial response in adults?" Databases PubMed, Scopus, Cochrane Library, CINAHL, and SPORTDiscus were searched between March-May 2019. Experimental studies conducted in healthy adults (≥18 y) and those with type 2 diabetes were included. Full texts were examined by at least two independent reviewers. Twenty studies with a total of 352 participants met the inclusion criteria. The primary finding supports that exercise performed post-meal regardless of time of day had a beneficial impact on postprandial glycemia. There was insufficient evidence regarding whether timing of exercise performed pre- vs. post-meal or vice versa in a day is related to improved postprandial glycemic response due to inherent differences between studies. Future studies focusing on the investigation of timing and occurrence of meal intake and exercise throughout the day are needed to inform whether there is, and what is, an optimal time for these behaviors regarding long-term health outcomes.
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http://dx.doi.org/10.3390/nu12010221DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7019516PMC
January 2020

Total Usual Micronutrient Intakes Compared to the Dietary Reference Intakes among U.S. Adults by Food Security Status.

Nutrients 2019 Dec 22;12(1). Epub 2019 Dec 22.

Interdepartmental Nutrition Program, Purdue University, 700 W. State Street, West Lafayette, IN 47907, USA.

This study examined total usual micronutrient intakes from foods, beverages, and dietary supplements (DS) compared to the Dietary Reference Intakes among U.S. adults (≥19 years) by sex and food security status using NHANES 2011-2014 data ( = 9954). DS data were collected via an in-home interview; the NCI method was used to estimate distributions of total usual intakes from two 24 h recalls for food and beverages, after which DS were added. Food security status was categorized using the USDA Household Food Security Survey Module. Adults living in food insecure households had a higher prevalence of risk of inadequacy among both men and women for magnesium, potassium, vitamins A, B6, B12, C, D, E, and K; similar findings were apparent for phosphorous, selenium, and zinc in men alone. Meanwhile, no differences in the prevalence of risk for inadequacy were observed for calcium, iron (examined in men only), choline, or folate by food security status. Some DS users, especially food secure adults, had total usual intakes that exceeded the Tolerable Upper Intake Level (UL) for folic acid, vitamin D, calcium, and iron. In conclusion, while DS can be helpful in meeting nutrient requirements for adults for some micronutrients, potential excess may also be of concern for certain micronutrients among supplement users. In general, food insecure adults have higher risk for micronutrient inadequacy than food secure adults.
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http://dx.doi.org/10.3390/nu12010038DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7019721PMC
December 2019

Comparison of 4 Methods to Assess the Prevalence of Use and Estimates of Nutrient Intakes from Dietary Supplements among US Adults.

J Nutr 2020 04;150(4):884-893

Department of Nutrition Science, Purdue University, West Lafayette, IN, USA.

Background: Accurate and reliable methods to assess prevalence of use of and nutrient intakes from dietary supplements (DSs) are critical for research, clinical practice, and public health monitoring. NHANES has been the primary source of DS usage patterns using an in-home inventory with a frequency-based DS and Prescription Medicine Questionnaire (DSMQ), but little is known regarding DS information obtained from 24-h dietary recalls (24HRs).

Methods: The objectives of this analysis were to compare results from 4 different methods for measuring DS use constructed from two data collection instruments (i.e., DSMQ and 24HR) and to determine the most comprehensive method for measuring the prevalence of use and estimating nutrient intakes from DS for selected nutrients. NHANES 2011-2014 data from US adults (aged ≥19 y; n = 11,451) were used to examine the 4 combinations of methods constructed for measuring the prevalence of use of and amount of selected nutrients from DSs (i.e., riboflavin, vitamin D, folate, magnesium, calcium): 1) DSMQ, 2) 24HR day 1, 3) two 24HRs (i.e., mean), and 4) DSMQ or at least one 24HR.

Results: Half of US adults reported DS use on the DSMQ (52%) and on two 24HRs (mean of 49%), as compared with a lower prevalence of DS use when using a single 24HR (43%) and a higher (57%) prevalence when combining the DSMQ with at least one 24HR. Mean nutrient intake estimates were highest using 24HR day 1. Mean supplemental calcium from the DSMQ or at least one 24HR was 372 mg/d, but 464 mg/d on the 24HR only. For vitamin D, the estimated intakes per consumption day were higher on the DSMQ (46 μg) and the DSMQ or at least one 24HR (44 μg) than those on the 24HR day 1 (32 μg) or the mean 24HR (31 μg). Fewer products were also classed as a default or reasonable match on the DSMQ than on the 24HR.

Conclusions: A higher prevalence of use of DSs is obtained using frequency-based methods, whereas higher amounts of nutrients are reported from a 24HR. The home inventory results in greater accuracy for products reported. Collectively, these findings suggest that combining the DSMQ with at least one 24HR (i.e., DSMQ or at least one 24HR) is the most comprehensive method for assessing the prevalence of and estimating usual intake from DSs in US adults.This trial was registered at clinicaltrials.gov as NCT03400436.
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http://dx.doi.org/10.1093/jn/nxz306DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7138661PMC
April 2020

Distance metrics optimized for clustering temporal dietary patterning among U.S. adults.

Appetite 2020 01 12;144:104451. Epub 2019 Sep 12.

School of Electrical and Computer Engineering, 465 Northwestern Avenue, Purdue University, West Lafayette, IN, 47907, USA. Electronic address:

Objective: Few attempts to determine dietary patterns have incorporated concepts of time, specifically time and proportion of energy intake consumed throughout a day. A type of modified dynamic time warping (MDTW) was previously developed using an appropriate distance metric for patterning these aspects to determine temporal dietary patterns (TDP). This study further explores dynamic time warping (DTW) distance metrics including unconstrained DTW (UDTW), constrained DTW (CDTW), and MDTW with modern spectral clustering methods to optimize TDP related to dietary quality. MDTW was expected to create TDP with the strongest relationships to dietary quality and distinct visualization among U.S. adults 20-65y of the National Health and Nutrition Examination Survey 1999-2004.

Methods: Proportional energy intake by time of day metrics were optimized to create TDP from complete day-one 24-h dietary recalls using MDTW, UDTW with only a standard local constraint, and CDTW with standard local and global banding constraints, then clustered using spectral clustering. The association between each TDP distance metric clustering and mean dietary quality, as indicated by the 2005 Healthy Eating Index (HEI-2005), were determined using multiple linear regression controlled for potential confounders. Strength of association for each model was compared using adjusted R-squared. The results were also visualized to make qualitative comparisons.

Results: Four clusters representing distinct TDP for each distance metric by spectral clustering were generated among participants. MDTW exhibited TDP clusters with strongest associations to HEI compared with the TDP clusters generated from unconstrained and constrained DTW, and visualization of the TDP clusters from MDTW supported the association.

Implication: MDTW paired with spectral clustering is a useful tool for dimension reduction and uncovering temporal patterns with dietary data.
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http://dx.doi.org/10.1016/j.appet.2019.104451DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6875636PMC
January 2020

Best Practices for Dietary Supplement Assessment and Estimation of Total Usual Nutrient Intakes in Population-Level Research and Monitoring.

J Nutr 2019 02;149(2):181-197

School of Medicine, Wake Forest, Winston-Salem, NC.

The use of dietary supplements (DS) is pervasive and can provide substantial amounts of micronutrients to those who use them. Therefore when characterizing dietary intakes, describing the prevalence of inadequacy or excess, or assessing relations between nutrients and health outcomes, it is critical to incorporate DS intakes to improve exposure estimates. Unfortunately, little is known about the best methods to assess DS, and the structure of measurement error in DS reporting. Several characteristics of nutrients from DS are salient to understand when comparing to those in foods. First, DS can be consumed daily or episodically, in bolus form and can deliver discrete and often very high doses of nutrients that are not limited by energy intakes. These characteristics contribute to bimodal distributions and distributions severely skewed to the right. Labels on DS often provide nutrient forms that differ from those found in conventional foods, and underestimate analytically derived values. Finally, the bioavailability of many nutrient-containing DS is not known and it may not be the same as the nutrients in a food matrix. Current methods to estimate usual intakes are not designed specifically to handle DS. Two temporal procedures are described to refer to the order that nutrient intakes are combined relative to usual intake procedures, referred to as a "shrinking" the distribution to remove random error. The "shrink then add" approach is preferable to the "add then shrink" approach when users and nonusers are combined for most research questions. Stratifying by DS before usual intake methods is another defensible option. This review describes how to incorporate nutrient intakes from DS to usual intakes from foods, and describes the available methods and fit-for-purpose of different analytical strategies to address research questions where total usual intakes are of interest at the group level for use in nutrition research and to inform policy decisions. Clinical Trial Registry: NCT03400436.
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http://dx.doi.org/10.1093/jn/nxy264DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6374152PMC
February 2019

Dietary Supplement Use among U.S. Children by Family Income, Food Security Level, and Nutrition Assistance Program Participation Status in 2011⁻2014.

Nutrients 2018 Sep 1;10(9). Epub 2018 Sep 1.

Department of Nutrition Science, Purdue University, West Lafayette, IN 47907, USA.

This analysis characterizes use of dietary supplements (DS) and motivations for DS use among U.S. children (≤18 years) by family income level, food security status, and federal nutrition assistance program participation using the 2011⁻2014 National Health and Nutrition Examination Survey data. About one-third (32%) of children used DS, mostly multivitamin-minerals (MVM; 24%). DS and MVM use were associated with higher family income and higher household food security level. DS use was lowest among children in households participating in the Supplemental Nutrition Assistance Program (SNAP; 20%) and those participating in the Special Supplemental Nutrition Assistance Program for Women, Infants, and Children (WIC; 26%) compared to both income-eligible and income-ineligible nonparticipants. Most children who used DS took only one (83%) or two (12%) products; although children in low-income families took fewer products than those in higher income families. The most common motivations for DS and MVM use were to "improve (42% or 46%)" or "maintain (34 or 38%)" health, followed by "to supplement the diet (23 or 24%)" for DS or MVM, respectively. High-income children were more likely to use DS and MVM "to supplement the diet" than middle- or low-income children. Only 18% of child DS users took DS based on a health practitioner's recommendation. In conclusion, DS use was lower among children who were in low-income or food-insecure families, or families participating in nutrition assistance programs.
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http://dx.doi.org/10.3390/nu10091212DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6163871PMC
September 2018

Dietary Supplement Use Differs by Socioeconomic and Health-Related Characteristics among U.S. Adults, NHANES 2011⁻2014.

Nutrients 2018 Aug 17;10(8). Epub 2018 Aug 17.

Department of Nutrition Science, Purdue University, 700 W. State St., West Lafayette, IN 47907, USA.

The objective of this study was to estimate the prevalence of use and types of dietary supplements (DS) used by U.S. adults (≥19 years) by sociodemographic characteristics: family income-to-poverty ratio (PIR), food security status, and Supplemental Nutrition Assistance Program (SNAP) participation using NHANES 2011⁻2014 data ( = 11,024). DS use was ascertained via a home inventory and a retrospective 30-day questionnaire. Demographic and socioeconomic differences related to DS use were evaluated using a univariate statistic. Half of U.S. adults (52%) took at least one DS during a 30-day period; multivitamin-mineral (MVM) products were the most commonly used (31%). DS and MVM use was significantly higher among those with a household income of ≥ 350% of the poverty level, those who were food secure, and SNAP income-ineligible nonparticipants across all sex, age, and race/ethnic groups. Among women, prevalence of use significantly differed between SNAP participants (39%) and SNAP income-eligible nonparticipants (54%). Older adults (71+ years) remained the highest consumers of DS, specifically among the highest income group (82%), while younger adults (19⁻30 years), predominantly in the lowest income group (28%), were the lowest consumers. Among U.S. adults, DS use and the types of products consumed varied with income, food security, and SNAP participation.
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http://dx.doi.org/10.3390/nu10081114DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6116059PMC
August 2018

High-dimensional regression analysis links magnetic resonance imaging features and protein expression and signaling pathway alterations in breast invasive carcinoma.

Oncoscience 2018 Jan 26;5(1-2):39-48. Epub 2018 Feb 26.

Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Background: Imaging features derived from MRI scans can be used for not only breast cancer detection and measuring disease extent, but can also determine gene expression and patient outcomes. The relationships between imaging features, gene/protein expression, and response to therapy hold potential to guide personalized medicine. We aim to characterize the relationship between radiologist-annotated tumor phenotypic features (based on MRI) and the underlying biological processes (based on proteomic profiling) in the tumor.

Methods: Multiple-response regression of the image-derived, radiologist-scored features with reverse-phase protein array expression levels generated association coefficients for each combination of image-feature and protein in the RPPA dataset. Significantly-associated proteins for features were analyzed with Ingenuity Pathway Analysis software. Hierarchical clustering of the results of the pathway analysis determined which features were most strongly correlated with pathway activity and cellular functions.

Results: Each of the twenty-nine imaging features was found to have a set of significantly correlated molecules, associated biological functions, and pathways.

Conclusions: We interrogated the pathway alterations represented by the protein expression associated with each imaging feature. Our study demonstrates the relationships between biological processes (via proteomic measurements) and MRI features within breast tumors.
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http://dx.doi.org/10.18632/oncoscience.397DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5854291PMC
January 2018

Multiple-response regression analysis links magnetic resonance imaging features to de-regulated protein expression and pathway activity in lower grade glioma.

Oncoscience 2017 May 23;4(5-6):57-66. Epub 2017 Jun 23.

Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Background And Purpose: Lower grade gliomas (LGGs), lesions of WHO grades II and III, comprise 10-15% of primary brain tumors. In this study, we aim to carry out a radioproteomic characterization of LGGs using proteomics data from the TCGA and imaging data from the TCIA cohorts, to obtain an association between tumor MRI characteristics and protein measurements. The availability of linked imaging and molecular data permits the assessment of relationships between tumor genomic/proteomic measurements with phenotypic features.

Materials And Methods: Multiple-response regression of the image-derived, radiologist scored features with reverse-phase protein array (RPPA) expression levels generated correlation coefficients for each combination of image-feature and protein or phospho-protein in the RPPA dataset. Significantly-associated proteins for VASARI features were analyzed with Ingenuity Pathway Analysis software. Hierarchical clustering of the results of the pathway analysis was used to determine which feature groups were most strongly correlated with pathway activity and cellular functions.

Results: The multiple-response regression approach identified multiple proteins associated with each VASARI imaging feature. VASARI features were found to be correlated with expression of IL8, PTEN, PI3K/Akt, Neuregulin, ERK/MAPK, p70S6K and EGF signaling pathways.

Conclusion: Radioproteomics analysis might enable an insight into the phenotypic consequences of molecular aberrations in LGGs.
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http://dx.doi.org/10.18632/oncoscience.353DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5538849PMC
May 2017

Inferring network structure in non-normal and mixed discrete-continuous genomic data.

Biometrics 2018 03 24;74(1):185-195. Epub 2017 Apr 24.

Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 1400 Pressler Dr., Houston,Texas 77030, U.S.A.

Inferring dependence structure through undirected graphs is crucial for uncovering the major modes of multivariate interaction among high-dimensional genomic markers that are potentially associated with cancer. Traditionally, conditional independence has been studied using sparse Gaussian graphical models for continuous data and sparse Ising models for discrete data. However, there are two clear situations when these approaches are inadequate. The first occurs when the data are continuous but display non-normal marginal behavior such as heavy tails or skewness, rendering an assumption of normality inappropriate. The second occurs when a part of the data is ordinal or discrete (e.g., presence or absence of a mutation) and the other part is continuous (e.g., expression levels of genes or proteins). In this case, the existing Bayesian approaches typically employ a latent variable framework for the discrete part that precludes inferring conditional independence among the data that are actually observed. The current article overcomes these two challenges in a unified framework using Gaussian scale mixtures. Our framework is able to handle continuous data that are not normal and data that are of mixed continuous and discrete nature, while still being able to infer a sparse conditional sign independence structure among the observed data. Extensive performance comparison in simulations with alternative techniques and an analysis of a real cancer genomics data set demonstrate the effectiveness of the proposed approach.
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http://dx.doi.org/10.1111/biom.12711DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5654714PMC
March 2018

Exact sampling of the unobserved covariates in Bayesian spline models for measurement error problems.

Stat Comput 2016 Jul 14;26(4):827-840. Epub 2015 Jun 14.

Department of Statistics, Texas A&M University, 3143 TAMU, College Station, TX 77843-3143, USA.

In truncated polynomial spline or B-spline models where the covariates are measured with error, a fully Bayesian approach to model fitting requires the covariates and model parameters to be sampled at every Markov chain Monte Carlo iteration. Sampling the unobserved covariates poses a major computational problem and usually Gibbs sampling is not possible. This forces the practitioner to use a Metropolis-Hastings step which might suffer from unacceptable performance due to poor mixing and might require careful tuning. In this article we show for the cases of truncated polynomial spline or B-spline models of degree equal to one, the complete conditional distribution of the covariates measured with error is available explicitly as a mixture of double-truncated normals, thereby enabling a Gibbs sampling scheme. We demonstrate via a simulation study that our technique performs favorably in terms of computational efficiency and statistical performance. Our results indicate up to 62 and 54 % increase in mean integrated squared error efficiency when compared to existing alternatives while using truncated polynomial splines and B-splines respectively. Furthermore, there is evidence that the gain in efficiency increases with the measurement error variance, indicating the proposed method is a particularly valuable tool for challenging applications that present high measurement error. We conclude with a demonstration on a nutritional epidemiology data set from the NIH-AARP study and by pointing out some possible extensions of the current work.
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http://dx.doi.org/10.1007/s11222-015-9572-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4941830PMC
July 2016

Joint high-dimensional Bayesian variable and covariance selection with an application to eQTL analysis.

Biometrics 2013 Jun 22;69(2):447-57. Epub 2013 Apr 22.

Department of Statistics, Purdue University, West Lafayette, IN 47907-2066, USA.

We describe a Bayesian technique to (a) perform a sparse joint selection of significant predictor variables and significant inverse covariance matrix elements of the response variables in a high-dimensional linear Gaussian sparse seemingly unrelated regression (SSUR) setting and (b) perform an association analysis between the high-dimensional sets of predictors and responses in such a setting. To search the high-dimensional model space, where both the number of predictors and the number of possibly correlated responses can be larger than the sample size, we demonstrate that a marginalization-based collapsed Gibbs sampler, in combination with spike and slab type of priors, offers a computationally feasible and efficient solution. As an example, we apply our method to an expression quantitative trait loci (eQTL) analysis on publicly available single nucleotide polymorphism (SNP) and gene expression data for humans where the primary interest lies in finding the significant associations between the sets of SNPs and possibly correlated genetic transcripts. Our method also allows for inference on the sparse interaction network of the transcripts (response variables) after accounting for the effect of the SNPs (predictor variables). We exploit properties of Gaussian graphical models to make statements concerning conditional independence of the responses. Our method compares favorably to existing Bayesian approaches developed for this purpose.
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http://dx.doi.org/10.1111/biom.12021DOI Listing
June 2013

Forcing versus feedback: epidemic malaria and monsoon rains in northwest India.

PLoS Comput Biol 2010 Sep 2;6(9):e1000898. Epub 2010 Sep 2.

Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, USA.

Malaria epidemics in regions with seasonal windows of transmission can vary greatly in size from year to year. A central question has been whether these interannual cycles are driven by climate, are instead generated by the intrinsic dynamics of the disease, or result from the resonance of these two mechanisms. This corresponds to the more general inverse problem of identifying the respective roles of external forcings vs. internal feedbacks from time series for nonlinear and noisy systems. We propose here a quantitative approach to formally compare rival hypotheses on climate vs. disease dynamics, or external forcings vs. internal feedbacks, that combines dynamical models with recently developed, computational inference methods. The interannual patterns of epidemic malaria are investigated here for desert regions of northwest India, with extensive epidemiological records for Plasmodium falciparum malaria for the past two decades. We formulate a dynamical model of malaria transmission that explicitly incorporates rainfall, and we rely on recent advances on parameter estimation for nonlinear and stochastic dynamical systems based on sequential Monte Carlo methods. Results show a significant effect of rainfall in the inter-annual variability of epidemic malaria that involves a threshold in the disease response. The model exhibits high prediction skill for yearly cases in the malaria transmission season following the monsoonal rains. Consideration of a more complex model with clinical immunity demonstrates the robustness of the findings and suggests a role of infected individuals that lack clinical symptoms as a reservoir for transmission. Our results indicate that the nonlinear dynamics of the disease itself play a role at the seasonal, but not the interannual, time scales. They illustrate the feasibility of forecasting malaria epidemics in desert and semi-arid regions of India based on climate variability. This approach should be applicable to malaria in other locations, to other infectious diseases, and to other nonlinear systems under forcing.
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http://dx.doi.org/10.1371/journal.pcbi.1000898DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2932675PMC
September 2010