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Lariviere D, Craig SJC, Paul IM, Hohman EE, Savage JS, Wright RO, Chiaromonte F, Makova KD, Reimherr ML. Methylation profiles at birth linked to early childhood obesity. J Dev Orig Health Dis 2024; 15:e7. [PMID: 38660759 PMCID: PMC11268442 DOI: 10.1017/s2040174424000060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Childhood obesity represents a significant global health concern and identifying its risk factors is crucial for developing intervention programs. Many "omics" factors associated with the risk of developing obesity have been identified, including genomic, microbiomic, and epigenomic factors. Here, using a sample of 48 infants, we investigated how the methylation profiles in cord blood and placenta at birth were associated with weight outcomes (specifically, conditional weight gain, body mass index, and weight-for-length ratio) at age six months. We characterized genome-wide DNA methylation profiles using the Illumina Infinium MethylationEpic chip, and incorporated information on child and maternal health, and various environmental factors into the analysis. We used regression analysis to identify genes with methylation profiles most predictive of infant weight outcomes, finding a total of 23 relevant genes in cord blood and 10 in placenta. Notably, in cord blood, the methylation profiles of three genes (PLIN4, UBE2F, and PPP1R16B) were associated with all three weight outcomes, which are also associated with weight outcomes in an independent cohort suggesting a strong relationship with weight trajectories in the first six months after birth. Additionally, we developed a Methylation Risk Score (MRS) that could be used to identify children most at risk for developing childhood obesity. While many of the genes identified by our analysis have been associated with weight-related traits (e.g., glucose metabolism, BMI, or hip-to-waist ratio) in previous genome-wide association and variant studies, our analysis implicated several others, whose involvement in the obesity phenotype should be evaluated in future functional investigations.
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Affiliation(s)
- Delphine Lariviere
- Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA, USA
| | - Sarah J C Craig
- Department of Biology, Penn State University, University Park, PA, USA
- Center for Medical Genomics, Penn State University, University Park, PA, USA
| | - Ian M Paul
- Center for Medical Genomics, Penn State University, University Park, PA, USA
- Department of Pediatrics, Penn State College of Medicine, Hershey, PA, USA
| | - Emily E Hohman
- Center for Childhood Obesity Research, Penn State University, University Park, PA, USA
| | - Jennifer S Savage
- Center for Childhood Obesity Research, Penn State University, University Park, PA, USA
- Nutrition Department, Penn State University, University Park, PA, USA
| | | | - Francesca Chiaromonte
- Center for Medical Genomics, Penn State University, University Park, PA, USA
- Department of Statistics, Penn State University, University Park, PA, USA
- L'EMbeDS, Sant'Anna School of Advanced Studies, Piazza Martiri della Libertà, Pisa, Italy
| | - Kateryna D Makova
- Department of Biology, Penn State University, University Park, PA, USA
- Center for Medical Genomics, Penn State University, University Park, PA, USA
| | - Matthew L Reimherr
- Center for Medical Genomics, Penn State University, University Park, PA, USA
- Department of Statistics, Penn State University, University Park, PA, USA
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Brown V, Tran H, Jacobs J, Ananthapavan J, Strugnell C, Backholer K, Sultana M, Alsubhi M, Allender S, Novotny R, Nichols M. Spillover effects of childhood obesity prevention interventions: A systematic review. Obes Rev 2024; 25:e13692. [PMID: 38156507 DOI: 10.1111/obr.13692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 10/10/2023] [Accepted: 12/02/2023] [Indexed: 12/30/2023]
Abstract
BACKGROUND Childhood obesity prevention initiatives are complex interventions that aim to improve children's obesity-related behaviors and provide health promoting environments. These interventions often impact individuals, communities, and outcomes not primarily targeted by the intervention or policy. To accurately capture the effectiveness and cost-effectiveness of childhood obesity prevention interventions, an understanding of the broader impacts (or spillover effects) is required. This systematic review aims to assess the spillover effects of childhood obesity prevention interventions. METHODS Six academic databases and two trial registries were searched (2007-2023) to identify studies reporting quantifiable obesity-related and other outcomes in individuals or communities not primarily targeted by an obesity prevention intervention. Critical appraisal was undertaken for studies that reported statistically significant findings, and a narrative synthesis of the data was undertaken. RESULTS Twenty academic studies and 41 trial records were included in the synthesis. The most commonly reported spillovers were diet or nutrition-related, followed by BMI and physical activity/sedentary behavior. Spillovers were mostly reported in parents/caregivers followed by other family members. Nine of the 20 academic studies reported statistically significant spillover effects. CONCLUSION Limited evidence indicates that positive spillover effects of childhood obesity prevention interventions can be observed in parents/caregivers and families of targeted participants.
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Affiliation(s)
- Vicki Brown
- Deakin Health Economics, Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Victoria, Australia
- Global Centre for Preventive Health and Nutrition (GLOBE) Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Victoria, Australia
| | - Huong Tran
- Deakin Health Economics, Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Victoria, Australia
- Global Centre for Preventive Health and Nutrition (GLOBE) Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Victoria, Australia
| | - Jane Jacobs
- Global Centre for Preventive Health and Nutrition (GLOBE) Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Victoria, Australia
| | - Jaithri Ananthapavan
- Deakin Health Economics, Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Victoria, Australia
- Global Centre for Preventive Health and Nutrition (GLOBE) Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Victoria, Australia
| | - Claudia Strugnell
- Global Centre for Preventive Health and Nutrition (GLOBE) Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Victoria, Australia
| | - Kathryn Backholer
- Global Centre for Preventive Health and Nutrition (GLOBE) Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Victoria, Australia
| | - Marufa Sultana
- Deakin Health Economics, Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Victoria, Australia
- Global Centre for Preventive Health and Nutrition (GLOBE) Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Victoria, Australia
| | - Moosa Alsubhi
- Deakin Health Economics, Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Victoria, Australia
- Global Centre for Preventive Health and Nutrition (GLOBE) Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Victoria, Australia
| | - Steve Allender
- Global Centre for Preventive Health and Nutrition (GLOBE) Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Victoria, Australia
| | | | - Melanie Nichols
- Global Centre for Preventive Health and Nutrition (GLOBE) Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Victoria, Australia
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Lariviere D, Craig SJC, Paul IM, Hohman EE, Savage JS, Wright RO, Chiaromonte F, Makova KD, Reimherr ML. Methylation profiles at birth linked to early childhood obesity. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.12.24301172. [PMID: 38260407 PMCID: PMC10802761 DOI: 10.1101/2024.01.12.24301172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Childhood obesity represents a significant global health concern and identifying risk factors is crucial for developing intervention programs. Many 'omics' factors associated with the risk of developing obesity have been identified, including genomic, microbiomic, and epigenomic factors. Here, using a sample of 48 infants, we investigated how the methylation profiles in cord blood and placenta at birth were associated with weight outcomes (specifically, conditional weight gain, body mass index, and weight-for-length ratio) at age six months. We characterized genome-wide DNA methylation profiles using the Illumina Infinium MethylationEpic chip, and incorporated information on child and maternal health, and various environmental factors into the analysis. We used regression analysis to identify genes with methylation profiles most predictive of infant weight outcomes, finding a total of 23 relevant genes in cord blood and 10 in placenta. Notably, in cord blood, the methylation profiles of three genes (PLIN4, UBE2F, and PPP1R16B) were associated with all three weight outcomes, which are also associated with weight outcomes in an independent cohort suggesting a strong relationship with weight trajectories in the first six months after birth. Additionally, we developed a Methylation Risk Score (MRS) that could be used to identify children most at risk for developing childhood obesity. While many of the genes identified by our analysis have been associated with weight-related traits (e.g., glucose metabolism, BMI, or hip-to-waist ratio) in previous genome-wide association and variant studies, our analysis implicated several others, whose involvement in the obesity phenotype should be evaluated in future functional investigations.
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Affiliation(s)
- Delphine Lariviere
- Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA
| | - Sarah J C Craig
- Department of Biology, Penn State University, University Park, PA
- Center for Medical Genomics, Penn State University, University Park, PA
| | - Ian M Paul
- Center for Medical Genomics, Penn State University, University Park, PA
- Department of Pediatrics, Penn State College of Medicine, Hershey, PA
| | - Emily E Hohman
- Center for Childhood Obesity Research, Penn State University, University Park, PA
| | - Jennifer S Savage
- Center for Childhood Obesity Research, Penn State University, University Park, PA
- Nutrition Department, Penn State University, University Park, PA
| | | | - Francesca Chiaromonte
- Center for Medical Genomics, Penn State University, University Park, PA
- Department of Statistics, Penn State University, University Park, PA
- EMbeDS, Sant'Anna School of Advanced Studies, Piazza Martiri della Libertà, Pisa, Italy
| | - Kateryna D Makova
- Department of Biology, Penn State University, University Park, PA
- Center for Medical Genomics, Penn State University, University Park, PA
| | - Matthew L Reimherr
- Center for Medical Genomics, Penn State University, University Park, PA
- Department of Statistics, Penn State University, University Park, PA
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Jeong J, Domonko V, Mendile T, Yousafzai AK. Effects of a Parenting and Nutrition Intervention on Siblings: A Cluster-RCT. Pediatrics 2023; 152:e2023061383. [PMID: 37777643 DOI: 10.1542/peds.2023-061383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/26/2023] [Indexed: 10/02/2023] Open
Abstract
OBJECTIVES The majority of the evidence about the effectiveness of early parenting and nutrition interventions pertains to 1 targeted index child in a given household. We evaluated whether nontargeted sibling children benefited from a bundled parenting and nutrition intervention. METHODS We designed a sub-study within a broader cluster-randomized trial that evaluated the effects of engaging both mothers and fathers and bundling parenting and nutrition interventions in Mara, Tanzania. Trained community health workers delivered interventions to parents through peer groups and home visits. Interventions encompassed various content including responsive parenting, infant and young child feeding, and positive couples' relationships. The main trial enrolled mothers and fathers and 1-index children <18 months of age in 80 clusters. Between June and July 2021, in 32 clusters (16 intervention, 16 control), we reenrolled 222 households (118 intervention, 104 control) from the main trial that had another child <6 years of age (ie, sibling to the index child). We compared caregiving practices and child development and nutrition outcomes among siblings in intervention versus control households. RESULTS Compared with control siblings, intervention siblings had improved expressive language development (β = 0.33 [95% confidence interval: 0.03 to 0.62]) and dietary intake (β = 0.52 [0.10 to 0.93]) and reduced internalizing behaviors (β = -0.56 [-1.07 to -0.06]). Intervention caregivers reported greater maternal stimulation (β = 0.31 [0.00 to 0.61]) and paternal stimulation (β = 0.33 [0.02 to 0.65]) and displayed more responsive caregiving behaviors (β = 0.40 [0.09 to 0.72]) with sibling children. CONCLUSIONS A father-inclusive, bundled parenting and nutrition intervention can achieve positive spillover effects on sibling children's developmental and nutritional outcomes.
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Affiliation(s)
- Joshua Jeong
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | | | | | - Aisha K Yousafzai
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
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Ayre SK, White MJ, Harris HA, Byrne RA. 'I'm having jelly because you've been bad!': A grounded theory study of mealtimes with siblings in Australian families. MATERNAL & CHILD NUTRITION 2023; 19:e13484. [PMID: 36808876 PMCID: PMC10019066 DOI: 10.1111/mcn.13484] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 01/11/2023] [Accepted: 01/23/2023] [Indexed: 02/22/2023]
Abstract
Obesity prevention interventions have been designed to promote responsive feeding in early childhood. However, existing interventions primarily target first-time mothers without considering the complexities of feeding multiple children within a family unit. By applying principles of Constructivist Grounded Theory (CGT), this study aimed to explore how mealtimes are enacted in families with more than one child. A mixed-methods study was conducted with parent-sibling triads (n = 18 families) in South East Queensland, Australia. Data included direct mealtime observations, semistructured interviews, field notes, and memos. Data were analysed using open and focused coding, during which constant comparative analysis was applied. The sample comprised of two-parent families with children ranging in age from 12 to 70 months (median sibling age difference = 24 months). A conceptual model was developed to map sibling-related processes integral to the enactment of mealtimes in families. Notably, this model captured feeding practices used by siblings, such as pressure to eat and overt restriction, that previously had only been described in parents. It also documented feeding practices used by parents that may occur only in the presence of a sibling, such as leveraging sibling competitiveness and rewarding a child to vicariously condition their sibling's behaviour. The conceptual model demonstrates complexities in feeding that give shape to the overall family food environment. Findings from this study can inform the design of early feeding interventions that support parents to remain responsive, particularly when their perceptions and expectations of siblings differ.
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Affiliation(s)
- Susannah K. Ayre
- Woolworths Centre for Childhood Nutrition Research, Faculty of HealthQueensland University of TechnologySouth BrisbaneQueenslandAustralia
- School of Exercise and Nutrition Sciences, Faculty of HealthQueensland University of TechnologyKelvin GroveQueenslandAustralia
| | - Melanie J. White
- School of Psychology & Counselling, Faculty of HealthQueensland University of TechnologyKelvin GroveQueenslandAustralia
| | - Holly A. Harris
- Department of Psychology, Education and Child StudiesErasmus University RotterdamRotterdamThe Netherlands
| | - Rebecca A. Byrne
- Woolworths Centre for Childhood Nutrition Research, Faculty of HealthQueensland University of TechnologySouth BrisbaneQueenslandAustralia
- School of Exercise and Nutrition Sciences, Faculty of HealthQueensland University of TechnologyKelvin GroveQueenslandAustralia
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Food-related parenting practices and styles in households with sibling children: A scoping review. Appetite 2022; 174:106045. [DOI: 10.1016/j.appet.2022.106045] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 03/30/2022] [Accepted: 04/08/2022] [Indexed: 11/23/2022]
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Hohman EE, Savage JS, Marini ME, Anzman-Frasca S, Buxton OM, Loken E, Paul IM. Effect of the INSIGHT Firstborn Parenting Intervention on Secondborn Sleep. Pediatrics 2022; 150:188273. [PMID: 35703026 PMCID: PMC9893513 DOI: 10.1542/peds.2021-055244] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/18/2022] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND AND OBJECTIVES The Intervention Nurses Start Infants Growing on Healthy Trajectories (INSIGHT) responsive parenting (RP) intervention for first-time mothers improved firstborn infant sleep compared with controls. The goals of this analysis were to test intervention spillover effects on secondborn siblings and examine birth order differences in infant sleep. METHODS Secondborns (n = 117) of INSIGHT mothers were enrolled in an observational cohort, SIBSIGHT. The Brief Infant Sleep Questionnaire was collected at 3, 16, and 52 weeks. Generalized linear mixed models assessed differences among secondborns by firstborn randomization, as well as birth order differences at 16 and 52 weeks. RESULTS The RP group secondborns slept 42 minutes longer at night (95% confidence interval [95% CI]: 19-64) and 53 minutes longer total (95% CI: 17-90) than control secondborns. RP secondborns were more likely to self-soothe to sleep (odds ratio [OR] = 2.0, 95% CI: 1.1-3.7) and less likely to be fed back to sleep after waking (OR = 0.5, 95% CI: 0.3-0.9) than secondborns of control mothers. RP secondborns were more likely to have a bedtime ≤8 pm at 3 (OR = 2.9, 95% CI: 1.1-7.7) and 16 weeks (OR = 4.7, 95% CI: 2.0-11.0). Few differences in sleep parenting practices were observed when comparing siblings within families. Secondborns slept 37 minutes longer than firstborns at 16 weeks (CI: 7-67, P = .03). CONCLUSIONS The INSIGHT RP intervention for first-time mothers had a spillover effect to secondborns, positively impacting sleep duration and behaviors. Intervening with first-time mothers benefits both firstborns and subsequent children.
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Affiliation(s)
- Emily E. Hohman
- Center for Childhood Obesity Research, Pennsylvania State University, University Park, PA
| | - Jennifer S. Savage
- Center for Childhood Obesity Research, Pennsylvania State University, University Park, PA,Nutritional Sciences, Pennsylvania State University, University Park, PA
| | - Michele E. Marini
- Center for Childhood Obesity Research, Pennsylvania State University, University Park, PA
| | | | - Orfeu M. Buxton
- Biobehavioral Health, Pennsylvania State University, University Park, PA
| | - Eric Loken
- Educational Psychology, University of Connecticut, Storrs, CT
| | - Ian M. Paul
- Pediatrics and Public Health Sciences, Penn State College of Medicine, Hershey PA
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Nandy D, Craig SJC, Cai J, Tian Y, Paul IM, Savage JS, Marini ME, Hohman EE, Reimherr ML, Patterson AD, Makova KD, Chiaromonte F. Metabolomic profiling of stool of two-year old children from the INSIGHT study reveals links between butyrate and child weight outcomes. Pediatr Obes 2022; 17:e12833. [PMID: 34327846 PMCID: PMC8647636 DOI: 10.1111/ijpo.12833] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 05/11/2021] [Accepted: 06/09/2021] [Indexed: 12/19/2022]
Abstract
BACKGROUND Metabolomic analysis is commonly used to understand the biological underpinning of diseases such as obesity. However, our knowledge of gut metabolites related to weight outcomes in young children is currently limited. OBJECTIVES To (1) explore the relationships between metabolites and child weight outcomes, (2) determine the potential effect of covariates (e.g., child's diet, maternal health/habits during pregnancy, etc.) in the relationship between metabolites and child weight outcomes, and (3) explore the relationship between selected gut metabolites and gut microbiota abundance. METHODS Using 1 H-NMR, we quantified 30 metabolites from stool samples of 170 two-year-old children. To identify metabolites and covariates associated with children's weight outcomes (BMI [weight/height2 ], BMI z-score [BMI adjusted for age and sex], and growth index [weight/height]), we analysed the 1 H-NMR data, along with 20 covariates recorded on children and mothers, using LASSO and best subset selection regression techniques. Previously characterized microbiota community information from the same stool samples was used to determine associations between selected gut metabolites and gut microbiota. RESULTS At age 2 years, stool butyrate concentration had a significant positive association with child BMI (p-value = 3.58 × 10-4 ), BMI z-score (p-value = 3.47 × 10-4 ), and growth index (p-value = 7.73 × 10-4 ). Covariates such as maternal smoking during pregnancy are important to consider. Butyrate concentration was positively associated with the abundance of the bacterial genus Faecalibacterium (p-value = 9.61 × 10-3 ). CONCLUSIONS Stool butyrate concentration is positively associated with increased child weight outcomes and should be investigated further as a factor affecting childhood obesity.
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Affiliation(s)
- Debmalya Nandy
- Department of StatisticsPenn State UniversityUniversity ParkPAUSA,Present address:
Department of Biostatistics and Informatics, Colorado School of Public HealthUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Sarah J. C. Craig
- Department of BiologyPenn State UniversityUniversity ParkPAUSA,Center for Medical GenomicsPenn State UniversityUniversity ParkPAUSA
| | - Jingwei Cai
- Department of Molecular ToxicologyPenn State UniversityUniversity ParkPAUSA,Present address:
Department of Drug Metabolism and PharmacokineticsGenentech Inc.South San FranciscoCaliforniaUSA
| | - Yuan Tian
- Department of Molecular ToxicologyPenn State UniversityUniversity ParkPAUSA
| | - Ian M. Paul
- Center for Medical GenomicsPenn State UniversityUniversity ParkPAUSA,Department of PediatricsPenn State College of MedicineHersheyPAUSA
| | - Jennifer S. Savage
- Department of Nutritional SciencesPenn State UniversityUniversity ParkPAUSA,Center for Childhood Obesity ResearchPenn State UniversityUniversity ParkPAUSA
| | - Michele E. Marini
- Center for Childhood Obesity ResearchPenn State UniversityUniversity ParkPAUSA
| | - Emily E. Hohman
- Center for Childhood Obesity ResearchPenn State UniversityUniversity ParkPAUSA
| | - Matthew L. Reimherr
- Department of StatisticsPenn State UniversityUniversity ParkPAUSA,Center for Medical GenomicsPenn State UniversityUniversity ParkPAUSA
| | - Andrew D. Patterson
- Department of Molecular ToxicologyPenn State UniversityUniversity ParkPAUSA,Department of Biochemistry & Molecular BiologyPenn State UniversityUniversity ParkPAUSA
| | - Kateryna D. Makova
- Department of BiologyPenn State UniversityUniversity ParkPAUSA,Center for Medical GenomicsPenn State UniversityUniversity ParkPAUSA
| | - Francesca Chiaromonte
- Department of StatisticsPenn State UniversityUniversity ParkPAUSA,Center for Medical GenomicsPenn State UniversityUniversity ParkPAUSA,Institute of EconomicsEMbeDS, Sant'Anna School of Advanced StudiesPisaItaly
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