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Jo J, Ha N, Ji Y, Do A, Seo JH, Oh B, Choi S, Choe EK, Lee W, Son JW, Won S. Genetic determinants of obesity in Korean populations: exploring genome-wide associations and polygenic risk scores. Brief Bioinform 2024; 25:bbae389. [PMID: 39207728 PMCID: PMC11359806 DOI: 10.1093/bib/bbae389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 06/24/2024] [Indexed: 09/04/2024] Open
Abstract
East Asian populations exhibit a genetic predisposition to obesity, yet comprehensive research on these traits is limited. We conducted a genome-wide association study (GWAS) with 93,673 Korean subjects to uncover novel genetic loci linked to obesity, examining metrics such as body mass index, waist circumference, body fat ratio, and abdominal fat ratio. Participants were categorized into non-obese, metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO) groups. Using advanced computational methods, we developed a multifaceted polygenic risk scores (PRS) model to predict obesity. Our GWAS identified significant genetic effects with distinct sizes and directions within the MHO and MUO groups compared with the non-obese group. Gene-based and gene-set analyses, along with cluster analysis, revealed heterogeneous patterns of significant genes on chromosomes 3 (MUO group) and 11 (MHO group). In analyses targeting genetic predisposition differences based on metabolic health, odds ratios of high PRS compared with medium PRS showed significant differences between non-obese and MUO, and non-obese and MHO. Similar patterns were seen for low PRS compared with medium PRS. These findings were supported by the estimated genetic correlation (0.89 from bivariate GREML). Regional analyses highlighted significant local genetic correlations on chromosome 11, while single variant approaches suggested widespread pleiotropic effects, especially on chromosome 11. In conclusion, our study identifies specific genetic loci and risks associated with obesity in the Korean population, emphasizing the heterogeneous genetic factors contributing to MHO and MUO.
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Affiliation(s)
- Jinyeon Jo
- Department of Public Health Sciences, Graduate school of Public Health, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea
| | - Nayoung Ha
- Department of Public Health Sciences, Graduate school of Public Health, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea
| | - Yunmi Ji
- Interdisciplinary Program in Bioinformatics, College of Natural Sciences, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea
| | - Ahra Do
- Interdisciplinary Program in Bioinformatics, College of Natural Sciences, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea
| | - Je Hyun Seo
- Veterans Health Service Medical Center, Veterans Medical Research Institute, 53, Jinhwangdo-ro 61-gil, Gangdong-gu, Seoul, 05368, South Korea
| | - Bumjo Oh
- Department of Family Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, 20, Boramae-ro 5-gil, Dongjak-gu, Seoul, 07061, South Korea
| | - Sungkyoung Choi
- Department of Applied Mathematics, Hanyang University (ERICA), 55, Hanyang-deahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, South Korea
| | - Eun Kyung Choe
- Division of Colorectal Surgery, Department of Surgery, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, South Korea
- Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, 39FL, 152, Teheran-ro, Gangnam-gu, Seoul, 06236, South Korea
| | - Woojoo Lee
- Department of Public Health Sciences, Graduate school of Public Health, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea
- Institute of Health and Environment, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea
| | - Jang Won Son
- Division of Endocrinology, Department of Internal Medicine, Bucheon St. Mary's hospital, The Catholic University of Korea, 327, Sosa-ro, Bucheon-si, Gyeonggi-do, Bucheon, 14647, South Korea
| | - Sungho Won
- Department of Public Health Sciences, Graduate school of Public Health, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea
- Interdisciplinary Program in Bioinformatics, College of Natural Sciences, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea
- Institute of Health and Environment, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea
- RexSoft Corps, Seoul National University Administration Building, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea
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Xu H, Gupta S, Dinsmore I, Kollu A, Cawley AM, Anwar MY, Chen HH, Petty LE, Seshadri S, Graff M, Below P, Brody JA, Chittoor G, Fisher-Hoch SP, Heard-Costa NL, Levy D, Lin H, Loos RJF, Mccormick JB, Rotter JI, Mirshahi T, Still CD, Destefano A, Cupples LA, Mohlke KL, North KE, Justice AE, Liu CT. Integrating Genetic and Transcriptomic Data to Identify Genes Underlying Obesity Risk Loci. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.11.24308730. [PMID: 38903089 PMCID: PMC11188121 DOI: 10.1101/2024.06.11.24308730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/22/2024]
Abstract
Genome-wide association studies (GWAS) have identified numerous body mass index (BMI) loci. However, most underlying mechanisms from risk locus to BMI remain unknown. Leveraging omics data through integrative analyses could provide more comprehensive views of biological pathways on BMI. We analyzed genotype and blood gene expression data in up to 5,619 samples from the Framingham Heart Study (FHS). Using 3,992 single nucleotide polymorphisms (SNPs) at 97 BMI loci and 20,692 transcripts within 1 Mb, we performed separate association analyses of transcript with BMI and SNP with transcript (PBMI and PSNP, respectively) and then a correlated meta-analysis between the full summary data sets (PMETA). We identified transcripts that met Bonferroni-corrected significance for each omic, were more significant in the correlated meta-analysis than each omic, and were at least nominally associated with BMI in FHS data. Among 308 significant SNP-transcript-BMI associations, we identified seven genes (NT5C2, GSTM3, SNAPC3, SPNS1, TMEM245, YPEL3, and ZNF646) in five association regions. Using an independent sample of blood gene expression data, we validated results for SNAPC3 and YPEL3. We tested for generalization of these associations in hypothalamus, nucleus accumbens, and liver and observed significant (PMETA<0.05 & PMETA
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Affiliation(s)
- Hanfei Xu
- Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
| | - Shreyash Gupta
- Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
| | - Ian Dinsmore
- Department of Genomic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
| | - Abbey Kollu
- Department of Psychology and Neuroscience, University of North Carolina, 235 E. Cameron Avenue, Chapel Hill, NC, 27599, USA
| | - Anne Marie Cawley
- Marsico Lung Institute, University of North Carolina, 125 Mason Farm Rd, Chapel Hill, NC, 27599, USA
| | - Mohammad Y. Anwar
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
| | - Hung-Hsin Chen
- Institute of Biomedical Sciences, Academia Sinica, No. 128, Section 2, Academia Rd., Taipei, Nangang District, 115201, Taiwan
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
| | - Lauren E. Petty
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
| | - Sudha Seshadri
- Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
- Department of Neurology, School of Medicine, Boston University, 85 East Concord Street, Boston, MA, 02118, USA
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, UT Health San Antonio, 8300 Floyd Curl Drive, San Antonio, TX, 78229, USA
| | - Misa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
| | - Piper Below
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
| | - Jennifer A. Brody
- Department of Medicine, Cardiovascular Health Research Unit, University of Washington, 1730 Minor Ave, Seattle, WA, 98101, USA
| | - Geetha Chittoor
- Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
| | - Susan P. Fisher-Hoch
- Department of Epidemiology, School of Public Health, UT Health Houston, Regional Academic Health Center, One West University Blvd, Brownsville, TX, 78520, USA
| | - Nancy L. Heard-Costa
- Framingham Heart Study, 73 Mt Wayte Ave, Framingham, MA, 01702, USA
- Department of Neurology, Chobanian & Avedisian School of Medicine, Boston University, 72 E Concord St, Boston, MA, 02118, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute of the National Institutes of Health, 6701 Rockledge Drive, Bethesda, MD, 20892, USA
| | - Honghuang Lin
- Department of Medicine, University of Massachusetts Chan Medical School, 55 N Lake Ave, Worcester, MA, 01655, USA
| | - Ruth JF. Loos
- Charles Bronfman Institute for Personalized Medicine at Mount Sinai, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY, 10029, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3A, 2200, Copenhagen, Denmark
| | - Joseph B. Mccormick
- Department of Epidemiology, School of Public Health, UT Health Houston, Regional Academic Health Center, One West University Blvd, Brownsville, TX, 78520, USA
| | - Jerome I. Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, 1124 West Carson Street, Torrance, CA, 90502, USA
| | - Tooraj Mirshahi
- Department of Genomic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
| | - Christopher D. Still
- Center for Obesity and Metabolic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
| | - Anita Destefano
- Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
- Department of Neurology, School of Medicine, Boston University, 85 East Concord Street, Boston, MA, 02118, USA
| | - L. Adrienne Cupples
- Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
| | - Karen L Mohlke
- Department of Genetics, School of Medicine, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Kari E. North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
| | - Anne E. Justice
- Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
| | - Ching-Ti Liu
- Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
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Kim J, Baek Y, Lee S. Consumption of dietary fiber and APOA5 genetic variants in metabolic syndrome: baseline data from the Korean Medicine Daejeon Citizen Cohort Study. Nutr Metab (Lond) 2024; 21:19. [PMID: 38581036 PMCID: PMC10998362 DOI: 10.1186/s12986-024-00793-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 03/13/2024] [Indexed: 04/07/2024] Open
Abstract
BACKGROUND Consumption of dietary fiber has been suggested as an important aspect of a healthy diet to reduce the risk of metabolic syndrome (MetS), including cardiovascular disease. The role of fiber intake in MetS might differ by individual genetic susceptibility. APOA5 encodes a regulator of plasma triglyceride levels, which impacts the related mechanisms of MetS. This study investigated the association between dietary fiber and the risk of MetS, assessing their associations according to APOA5 genetic variants. METHODS A total of 1985 participants aged 30-55 years were included from a cross-sectional study based on the Korean Medicine Daejeon Citizen Cohort study at baseline (2017-2019). Dietary fiber intake was measured using a semiquantitative food frequency questionnaire. The APOA5 polymorphisms (rs2266788 A > G, rs662799 A > G, and rs651821 T > C) were genotyped using the Asia Precision Medicine Research Array. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs). RESULTS A higher consumption of dietary fiber was associated with a lower prevalence of MetS (P = 0.025). Among the components of MetS, an inverse association with dietary fiber was observed in increased waist circumference (OR, 95% CI = 0.60, 0.41-0.88, P for trend = 0.009) and elevated triglycerides (OR, 95% CI = 0.69, 0.50-0.96, P for trend = 0.012). Regarding the interaction with APOA5 genetic variants, a stronger association with dietary fiber intake was shown in G allele carriers of rs662799 than in A/A carriers (OR, 95% CI = 2.34, 1.59-3.44, P for interaction = 0.024) and in C allele carriers of rs651821 than in T/T carriers (OR, 95% CI = 2.35, 1.59-3.46, P for interaction = 0.027). CONCLUSIONS The findings of this study suggest that the benefits of dietary fiber on the risk of MetS could be modified by genetic variants of the APOA5 gene, providing a more effective strategy for preventing MetS.
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Affiliation(s)
- Jimi Kim
- Department of Food and Nutrition, Changwon National University, 20 Changwondaehak-ro, Uichang-gu, 51140, Changwon, Gyeongnam, South Korea
| | - Younghwa Baek
- Korean Medicine Data Division, Korea Institute of Oriental Medicine, 1672 Yuseong-daero, Yuseong-gu, 34054, Daejeon, South Korea
| | - Siwoo Lee
- Korean Medicine Data Division, Korea Institute of Oriental Medicine, 1672 Yuseong-daero, Yuseong-gu, 34054, Daejeon, South Korea.
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Park JM, Lee HS, Yang J, Jung DH, Lee JW. Metabolic Obesity Phenotypes and Incident Cardiovascular Outcomes in Middle-Aged and Older Korean Adults: A Longitudinal 10-Year Analysis of the Korean Genome and Epidemiology Study. Metab Syndr Relat Disord 2024; 22:232-239. [PMID: 38603765 DOI: 10.1089/met.2023.0170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/13/2024] Open
Abstract
Background: This study investigated the association of four metabolic obesity phenotypes with incident coronary artery disease and stroke in a large-scale, community population-based, prospective Korean cohort observed for over 10 years. Methods: The study participants included 7374 adults aged 40-69 years, drawn from the Korean Genome and Epidemiology Study. Participants with different metabolic obesity phenotypes were categorized according to body weight and metabolic health status into four groups: metabolically healthy nonobese (MHNO), metabolically healthy obese (MHO), metabolically unhealthy nonobese (MUHNO), and metabolically unhealthy obese (MUHO). Combined cardiovascular events were defined as coronary artery disease and stroke. We used multivariate Cox proportional hazards regression models to prospectively assess hazard ratios (HRs) with 95% confidence intervals (CIs) for incident coronary artery disease or stroke over 10 years after the baseline survey. Results: During the follow-up period, newly developed coronary artery disease, stroke, and combined cardiovascular events were diagnosed in 151 (2.0%), 137 (1.9%), and 283 (3.8%) participants, respectively. After adjusting for confounding variables, the HRs (95% CIs) for incident combined cardiovascular events were 1.81 (1.34-2.46) in the MUHO group, 1.29 (0.92-1.81) in the MUHNO group, and 1.21 (0.81-1.79) in the MHO group compared with those in the MHNO group. Conclusions: This study revealed distinct risks associated with four metabolic obesity phenotypes concerning incident coronary artery disease and stroke. After adjusting for potential confounding variables, the results indicated that MUHO, but not MUHNO or MHO, showed a higher risk of developing coronary artery disease and stroke than MHNO.
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Affiliation(s)
- Jae-Min Park
- Department of Family Medicine, Uijeongbu Eulji Medical Center, Eulji University, Uijeongbu, Korea
- Department of Medicine, Graduate School of Medicine, Yonsei University, Seoul, Republic of Korea
| | - Hye Sun Lee
- Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Juyeon Yang
- Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Dong-Hyuk Jung
- Department of Family Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Gyeonggi-do, Republic of Korea
| | - Ji-Won Lee
- Department of Family Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
- Institute for Innovation in Digital Healthcare, Yonsei University, Seoul, Republic of Korea
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5
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Romero-Becera R, Santamans AM, Arcones AC, Sabio G. From Beats to Metabolism: the Heart at the Core of Interorgan Metabolic Cross Talk. Physiology (Bethesda) 2024; 39:98-125. [PMID: 38051123 DOI: 10.1152/physiol.00018.2023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 10/26/2023] [Accepted: 12/01/2023] [Indexed: 12/07/2023] Open
Abstract
The heart, once considered a mere blood pump, is now recognized as a multifunctional metabolic and endocrine organ. Its function is tightly regulated by various metabolic processes, at the same time it serves as an endocrine organ, secreting bioactive molecules that impact systemic metabolism. In recent years, research has shed light on the intricate interplay between the heart and other metabolic organs, such as adipose tissue, liver, and skeletal muscle. The metabolic flexibility of the heart and its ability to switch between different energy substrates play a crucial role in maintaining cardiac function and overall metabolic homeostasis. Gaining a comprehensive understanding of how metabolic disorders disrupt cardiac metabolism is crucial, as it plays a pivotal role in the development and progression of cardiac diseases. The emerging understanding of the heart as a metabolic and endocrine organ highlights its essential contribution to whole body metabolic regulation and offers new insights into the pathogenesis of metabolic diseases, such as obesity, diabetes, and cardiovascular disorders. In this review, we provide an in-depth exploration of the heart's metabolic and endocrine functions, emphasizing its role in systemic metabolism and the interplay between the heart and other metabolic organs. Furthermore, emerging evidence suggests a correlation between heart disease and other conditions such as aging and cancer, indicating that the metabolic dysfunction observed in these conditions may share common underlying mechanisms. By unraveling the complex mechanisms underlying cardiac metabolism, we aim to contribute to the development of novel therapeutic strategies for metabolic diseases and improve overall cardiovascular health.
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Affiliation(s)
| | | | - Alba C Arcones
- Centro Nacional de Investigaciones Cardiovasculares, Madrid, Spain
- Centro Nacional de Investigaciones Oncológicas, Madrid, Spain
| | - Guadalupe Sabio
- Centro Nacional de Investigaciones Cardiovasculares, Madrid, Spain
- Centro Nacional de Investigaciones Oncológicas, Madrid, Spain
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Piko P, Llanaj E, Nagy K, Adany R. Genetic Background of Metabolically Healthy and Unhealthy Obesity Phenotypes in Hungarian Adult Sample Population. Int J Mol Sci 2023; 24:ijms24065209. [PMID: 36982283 PMCID: PMC10049500 DOI: 10.3390/ijms24065209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 03/06/2023] [Accepted: 03/07/2023] [Indexed: 03/30/2023] Open
Abstract
A specific phenotypic variant of obesity is metabolically healthy (MHO), which is characterized by normal blood pressure and lipid and glucose profiles, in contrast to the metabolically unhealthy variant (MUO). The genetic causes underlying the differences between these phenotypes are not yet clear. This study aims to explore the differences between MHO and MUO and the contribution of genetic factors (single nucleotide polymorphisms-SNPs) in 398 Hungarian adults (81 MHO and 317 MUO). For this investigation, an optimized genetic risk score (oGRS) was calculated using 67 SNPs (related to obesity and to lipid and glucose metabolism). Nineteen SNPs were identified whose combined effect was strongly associated with an increased risk of MUO (OR = 1.77, p < 0.001). Four of them (rs10838687 in MADD, rs693 in APOB, rs1111875 in HHEX, and rs2000813 in LIPG) significantly increased the risk of MUO (OR = 1.76, p < 0.001). Genetic risk groups based on oGRS were significantly associated with the risk of developing MUO at a younger age. We have identified a cluster of SNPs that contribute to the development of the metabolically unhealthy phenotype among Hungarian adults suffering from obesity. Our findings emphasize the significance of considering the combined effect(s) of multiple genes and SNPs in ascertaining cardiometabolic risk in obesity in future genetic screening programs.
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Affiliation(s)
- Peter Piko
- ELKH-DE Public Health Research Group, Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary
- Epidemiology and Surveillance Centre, Semmelweis University, 1085 Budapest, Hungary
| | - Erand Llanaj
- ELKH-DE Public Health Research Group, Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary
| | - Karoly Nagy
- Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary
| | - Roza Adany
- ELKH-DE Public Health Research Group, Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary
- Epidemiology and Surveillance Centre, Semmelweis University, 1085 Budapest, Hungary
- Department of Public Health, Semmelweis University, 1089 Budapest, Hungary
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Valderrábano RJ, Badour S, Ferri-Guerra J, Barb D, Garg R. Body Fat Distribution in Lean Individuals with Metabolic Abnormalities. Metab Syndr Relat Disord 2023; 21:79-84. [PMID: 36448994 DOI: 10.1089/met.2022.0026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Objective: Obesity, defined as body mass index (BMI) >30 kilogram/m2 is associated with metabolic derangements, but lean individuals with BMI <25 kilogram/m2 may also have metabolic abnormalities. This study was conducted to evaluate fat distribution in metabolically unhealthy lean (MUL) individuals. Methods: Adults with BMI 18.5-24.9 kilogram/m2 had their body composition evaluated with dual-energy X-ray absorptiometry. Metabolic data were obtained from their medical records. Patients with ≥2 components of the metabolic syndrome (MetS) were considered MUL and those with ≤1 component metabolically healthy lean (MHL). Multivariable logistic regression was used to analyze the association between metabolic abnormalities and anthropometric indexes. Results: The study includes 119 subjects; 69 in MHL and 50 in the MUL group. Two groups had comparable total body fat, fat mass index, and appendicular lean mass. Indices of visceral fat were associated with increased odds of being MUL (odds ratio with 95% confidence interval): visceral adipose tissue 1.75 (1.13-2.73), trunk-to-legs fat ratio 2.28 (1.30-4.00), trunk-to-limb fat ratio 2.43 (1.37-4.32), android-to-gynoid fat ratio 1.80 (1.07-3.03), and visceral-to-total fat percentage 1.80 (1.07-3.05). Conclusion: Metabolically unhealthy subjects had increased truncal distribution of body fat without an increase in total body fat. Body morphometry in MUL was similar to that of obese individuals with MetS.
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Affiliation(s)
- Rodrigo J Valderrábano
- Section in Men's Health and Aging, Clinical Research Unit, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Sanaa Badour
- Division of Endocrinology, Diabetes and Metabolism, University of Florida, Gainesville, Florida, USA
| | - Juliana Ferri-Guerra
- Department of Internal Medicine, Mount Sinai Medical Center, Miami Beach, Florida, USA
| | - Diana Barb
- Division of Endocrinology, Diabetes and Metabolism, University of Florida, Gainesville, Florida, USA
| | - Rajesh Garg
- Division of Endocrinology, University of Miami, Miller School of Medicine, Miami, Florida, USA
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Rouland A, Masson D, Lagrost L, Vergès B, Gautier T, Bouillet B. Role of apolipoprotein C1 in lipoprotein metabolism, atherosclerosis and diabetes: a systematic review. Cardiovasc Diabetol 2022; 21:272. [PMID: 36471375 PMCID: PMC9724408 DOI: 10.1186/s12933-022-01703-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 11/21/2022] [Indexed: 12/12/2022] Open
Abstract
Apolipoprotein C1 (apoC1) is a small size apolipoprotein whose exact role is not totally clarified but which seems to modulate significantly the metabolism of lipoproteins. ApoC1 is involved in the metabolism of triglyceride-rich lipoproteins by inhibiting the binding of very low density lipoproteins (VLDL) to VLDL-receptor (VLDL-R), to low density lipoprotein receptor (LDL-R) and to LDL receptor related protein (LRP), by reducing the activity of lipoprotein lipase (LPL) and by stimulating VLDL production, all these effects leading to increase plasma triglycerides. ApoC1 takes also part in the metabolism of high density lipoproteins (HDL) by inhibiting Cholesterol Ester Transfer Protein (CETP). The functionality of apoC1 on CETP activity is impaired in diabetes that might account, at least in part, for the increased plasma CETP activity observed in patients with diabetes. Its different effects on lipoprotein metabolism with a possible role in the modulation of inflammation makes the net impact of apoC1 on cardiometabolic risk difficult to figure out and apoC1 might be considered as pro-atherogenic or anti-atherogenic depending on the overall metabolic context. Making the link between total plasma apoC1 levels and the risk of cardio-metabolic diseases is difficult due to the high exchangeability of this small protein whose biological effects might depend essentially on its association with VLDL or HDL. The role of apoC1 in humans is not entirely elucidated and further studies are needed to determine its precise role in lipid metabolism and its possible pleiotropic effects on inflammation and vascular wall biology. In this review, we will present data on apoC1 structure and distribution among lipoproteins, on the effects of apoC1 on VLDL metabolism and HDL metabolism and we will discuss the possible links between apoC1, atherosclerosis and diabetes.
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Affiliation(s)
- Alexia Rouland
- grid.31151.37Endocrinology and Diabetology Unit, University Hospital, Dijon, France ,grid.493090.70000 0004 4910 6615INSERM/University of Bourgogne Franche-Comté, LNC UMR1231, Dijon, France
| | - David Masson
- grid.493090.70000 0004 4910 6615INSERM/University of Bourgogne Franche-Comté, LNC UMR1231, Dijon, France ,LipSTIC LabEx, UFR Sciences de Santé, Dijon, France
| | - Laurent Lagrost
- grid.493090.70000 0004 4910 6615INSERM/University of Bourgogne Franche-Comté, LNC UMR1231, Dijon, France ,LipSTIC LabEx, UFR Sciences de Santé, Dijon, France
| | - Bruno Vergès
- grid.31151.37Endocrinology and Diabetology Unit, University Hospital, Dijon, France ,grid.493090.70000 0004 4910 6615INSERM/University of Bourgogne Franche-Comté, LNC UMR1231, Dijon, France
| | - Thomas Gautier
- grid.493090.70000 0004 4910 6615INSERM/University of Bourgogne Franche-Comté, LNC UMR1231, Dijon, France ,LipSTIC LabEx, UFR Sciences de Santé, Dijon, France
| | - Benjamin Bouillet
- grid.31151.37Endocrinology and Diabetology Unit, University Hospital, Dijon, France ,grid.493090.70000 0004 4910 6615INSERM/University of Bourgogne Franche-Comté, LNC UMR1231, Dijon, France ,grid.31151.37Service Endocrinologie, Diabétologie et Maladies Métaboliques, Hôpital François Mitterrand, CHU Dijon, BP 77908, 21079 Dijon, France
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Sex-related differences in single nucleotide polymorphisms associated with dyslipidemia in a Korean population. Lipids Health Dis 2022; 21:124. [PMID: 36419087 PMCID: PMC9685854 DOI: 10.1186/s12944-022-01736-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 11/14/2022] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND The prevalence of dyslipidemia has increased steadily in Korea, and the incidence of dyslipidemia differs by sex. In this study, we identified single nucleotide polymorphisms (SNPs) related to dyslipidemia in Korean cohorts through genome-wide association study (GWAS) analysis. METHODS Genotyping was conducted to determine the genotypes of 72,298 participants and investigate genotypes for 7,079,946 SNPs. Sex, age, and BMI were set as covariates for GWAS, and significant SNPs were identified in the discovery and replication stages using logistic regression. RESULTS GWAS of the entire cohort revealed a total of five significant SNPs: rs117026536 (LPL), rs651821 (APOA5), rs9804646 (APOA5), rs9926440 (CETP), and rs429358 (APOE). GWAS of the male subjects revealed a total of four significant SNPs. While rs9804646 (APOA5) and rs429358 (APOE) were significant for all the subjects, rs662799 (APOA5) and rs56156922 (CETP) were significant only for the male subjects. GWAS of the female subjects revealed two significant SNPs, rs651821 (APOA5) and rs9804646 (APOA5), both of which were significant in all the subjects. CONCLUSION This is the first study to identify sex-related differences in genetic polymorphisms in Korean populations with dyslipidemia. Further studies considering environmental variables will be needed to elucidate these sex-related genetic differences in dyslipidemia.
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TrustGWAS: A full-process workflow for encrypted GWAS using multi-key homomorphic encryption and pseudorandom number perturbation. Cell Syst 2022; 13:752-767.e6. [PMID: 36041458 DOI: 10.1016/j.cels.2022.08.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 04/21/2022] [Accepted: 08/04/2022] [Indexed: 01/26/2023]
Abstract
The statistical power of genome-wide association studies (GWASs) is affected by the effective sample size. However, the privacy and security concerns associated with individual-level genotype data pose great challenges for cross-institutional cooperation. The full-process cryptographic solutions are in demand but have not been covered, especially the essential principal-component analysis (PCA). Here, we present TrustGWAS, a complete solution for secure, large-scale GWAS, recapitulating gold standard results against PLINK without compromising privacy and supporting basic PLINK steps including quality control, linkage disequilibrium pruning, PCA, chi-square test, Cochran-Armitage trend test, covariate-supported logistic regression and linear regression, and their sequential combinations. TrustGWAS leverages pseudorandom number perturbations for PCA and multiparty scheme of multi-key homomorphic encryption for all other modules. TrustGWAS can evaluate 100,000 individuals with 1 million variants and complete QC-LD-PCA-regression workflow within 50 h. We further successfully discover gene loci associated with fasting blood glucose, consistent with the findings of the ChinaMAP project.
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Factors of Obesity and Metabolically Healthy Obesity in Asia. Medicina (B Aires) 2022; 58:medicina58091271. [PMID: 36143948 PMCID: PMC9500686 DOI: 10.3390/medicina58091271] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 08/14/2022] [Accepted: 09/06/2022] [Indexed: 11/17/2022] Open
Abstract
The East Asian region (China, Japan, and South Korea) is comprised of almost 1.5 billion people and recent industrialization has brought with it a pandemic of rising obesity, even in children. As these countries are rapidly aging and functioning at sub-replacement birthrates, the burgeoning costs of obesity-related care may threaten socialized healthcare systems and quality of life. However, a condition called metabolically healthy obesity (MHO) has been found to be without immediate cardiopulmonary or diabetic risk. Thus, maintenance of the MHO condition for the obese in East Asia could buffer the burden of long-term obesity care on medical systems and knowledge of the biochemical, genetic, and physiological milieu associated with it could also provide new targets for intervention. Diverse physiological, psychological, environmental, and social factors play a role in obesogenesis and the transition of MHO to a metabolically unhealthy obesity. This review will give a broad survey of the various causes of obesity and MHO, with special emphasis on the East Asian population and studies from that region.
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Choe EK, Shivakumar M, Lee SM, Verma A, Kim D. Dissecting the clinical relevance of polygenic risk score for obesity-a cross-sectional, longitudinal analysis. Int J Obes (Lond) 2022; 46:1686-1693. [PMID: 35752651 PMCID: PMC10362905 DOI: 10.1038/s41366-022-01168-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 06/07/2022] [Accepted: 06/07/2022] [Indexed: 12/15/2022]
Abstract
BACKGROUND Obesity is a global pandemic disease whose prevalence is increasing worldwide. The clinical relevance of a polygenic risk score (PRS) for obesity has not been fully elucidated in Asian populations. METHOD We utilized a comprehensive health check-up database from the Korean population in conjunction with genotyping to generate PRS for BMI (PRS-BMI). We conducted a phenome-wide association (PheWAS) analysis and observed the longitudinal association of BMI with PRS-BMI. RESULTS PRS-BMI was generated by PRS-CS. Adding PRS-BMI to a model predicting ten-year BMI based on age, sex, and baseline BMI improved the model's accuracy (p = 0.003). In a linear mixed model of longitudinal change in BMI with aging, higher deciles of PRS were directly associated with changes in BMI. In the PheWAS, significant associations were observed for metabolic syndrome, bone density, and fatty liver. In the lean body population, those having the top 20% PRS-BMI had higher BMI and body fat mass along with better metabolic trait profiles compared to the bottom 20%. A bottom-20% PRS-BMI was a risk factor for metabolically unhealthy lean body (odds ratio 3.092, 95% confidence interval 1.707-6.018, p < 0.001), with adjustment for age, sex and BMI. CONCLUSIONS Genetic predisposition to obesity as defined by PRS-BMI was significantly associated with obesity-related disease or trajectory of obesity. Low PRS-BMI might be a risk factor associated with a metabolically unhealthy lean body. Better understanding the mechanisms of these relationships may allow tailored intervention in obesity or early selection of populations at risk of metabolic disease.
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Affiliation(s)
- Eun Kyung Choe
- Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Department of Surgery, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, 06236, South Korea
| | - Manu Shivakumar
- Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Seung Mi Lee
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, 03080, South Korea
| | - Anurag Verma
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA. .,Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
| | - Dokyoon Kim
- Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA. .,Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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Wu S, Hsu LA, Teng MS, Chou HH, Ko YL. Differential Genetic and Epigenetic Effects of the KLF14 Gene on Body Shape Indices and Metabolic Traits. Int J Mol Sci 2022; 23:ijms23084165. [PMID: 35456983 PMCID: PMC9032945 DOI: 10.3390/ijms23084165] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 04/03/2022] [Accepted: 04/06/2022] [Indexed: 02/06/2023] Open
Abstract
The KLF14 gene is a key metabolic transcriptional transregulator with monoallelic maternal expression. KLF14 variants are only associated with adipose tissue gene expression, and KLF14 promoter methylation is strongly associated with age. This study investigated whether age, sex, and obesity mediate the effects of KLF14 variants and DNA methylation status on body shape indices and metabolic traits. In total, the data of 78,742 and 1636 participants from the Taiwan Biobank were included in the regional plot association analysis for KLF14 variants and KLF14 methylation, respectively. Regional plot association studies revealed that the KLF14 rs4731702 variant and the nearby strong linkage disequilibrium polymorphisms were the lead variants for lipid profiles, blood pressure status, insulin resistance surrogate markers, and metabolic syndrome mainly in female participants and for body shape indices mainly in obese women. Significant age-dependent associations between KLF14 promoter methylation levels and body shape indices, and metabolic traits were also noted predominantly in female participants. KLF14 variants and KLF14 hypermethylation status were associated with metabolically healthy and unhealthy phenotypes, respectively, in obese individuals, and only the KLF14 variants demonstrated a significant association with both higher adiposity and lower cardiometabolic risk in the same allele, revealing uncoupled excessive adiposity from its cardiometabolic comorbidities, especially in obese women. Variations of KLF14 are associated with body shape indices, metabolic traits, insulin resistance, and metabolically healthy status. Differential genetic and epigenetic effects of KLF14 are age-, sex- and obesity-dependent. These results provided a personalized reference for the management of cardiometabolic diseases in precision medicine.
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Affiliation(s)
- Semon Wu
- Department of Life Science, Chinese Culture University, Taipei 11114, Taiwan;
| | - Lung-An Hsu
- The First Cardiovascular Division, Department of Internal Medicine, Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Taoyuan 33305, Taiwan;
| | - Ming-Sheng Teng
- Department of Research, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City 23142, Taiwan;
| | - Hsin-Hua Chou
- The Division of Cardiology, Department of Internal Medicine and Cardiovascular Center, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City 23142, Taiwan;
- School of Medicine, Tzu Chi University, Hualien 97004, Taiwan
| | - Yu-Lin Ko
- Department of Research, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City 23142, Taiwan;
- The Division of Cardiology, Department of Internal Medicine and Cardiovascular Center, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City 23142, Taiwan;
- School of Medicine, Tzu Chi University, Hualien 97004, Taiwan
- Correspondence: ; Tel.: +886-2-6628-9779 (ext. 5355); Fax: +886-2-6628-9009
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Genetic variations in adiponectin levels and dietary patterns on metabolic health among children with normal weight versus obesity: the BCAMS study. Int J Obes (Lond) 2022; 46:325-332. [PMID: 34716426 PMCID: PMC9131437 DOI: 10.1038/s41366-021-01004-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 10/13/2021] [Accepted: 10/15/2021] [Indexed: 11/08/2022]
Abstract
BACKGROUND/OBJECTIVES Adiponectin represents an important link between adipose tissue dysfunction and cardiometabolic risk in obesity; however, there is a lack of data on the effects of adiponectin-related genetic variations and gene-diet interactions on metabolic disorders in children. We aimed to investigate possible interactions between adiponectin-related genetic variants and habitual dietary patterns on metabolic health among children with normal weight versus overweight/obesity, and whether these effects in childhood longitudinally contribute to metabolic risk at follow-up. SUBJECTS/METHODS In total, 3,317 Chinese children aged 6-18 at baseline and 339 participants at 10-year follow-up from the Beijing Child and Adolescent Metabolic Syndrome study cohort were included. Baseline lifestyle factors, plasma adiponectin levels, and six adiponectin-related genetic variants resulting from GWAS in East Asians (loci in/near ADIPOQ, CDH13, WDR11FGF, CMIP, and PEPD) were assessed for their associations with the metabolic disorders. Being metabolically unhealthy was defined by exhibiting any metabolic syndrome component. RESULTS Among the six loci, ADIPOQ rs6773957 (OR 1.26, 95% CI:1.07-1.47, P = 0.004) and adiponectin receptor CDH13 rs4783244 (0.82, 0.69-0.96, P = 0.017) were correlated with metabolic risks independent of lifestyle factors in normal-weight children, but the associations were less obvious in those with overweight/obesity. A significant interaction between rs6773957 and diet (Pinteraction = 0.004) for metabolic health was observed in normal-weight children. The adiponectin-decreasing allele of rs6773957 was associated with greater metabolic risks in individuals with unfavorable diet patterns (P < 0.001), but not in those with healthy patterns (P > 0.1). A similar interaction effect was observed using longitudinal data (Pinteraction = 0.029). CONCLUSIONS These findings highlight a novel gene-diet interaction on the susceptibility to cardiometabolic disorders, which has a long-term impact from childhood onward, particularly in those with normal weight. Personalized dietary advice in these individuals may be recommended as an early possible therapeutic measure to improve metabolic health.
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Metabolic Obesity in People with Normal Body Weight (MONW)-Review of Diagnostic Criteria. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19020624. [PMID: 35055447 PMCID: PMC8776153 DOI: 10.3390/ijerph19020624] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 12/26/2021] [Accepted: 01/04/2022] [Indexed: 12/12/2022]
Abstract
Disorders of metabolic obesity with normal body weight (MONW) are widely recognized risk factors for the development of cardiovascular diseases and type 2 diabetes. Despite this, MONW is not diagnosed in clinical practice. There is no consensus on the definition of MONW, and measuring the degree of insulin resistance or obesity among apparently healthy, non-obese patients is not widely applicable. The awareness of the relationship between metabolic disorders such as MONW and a higher risk of mortality from cardiovascular causes and other related diseases prompts the need for action to be taken aimed at creating appropriate diagnostic models that will allow for the effective detection of those with metabolic abnormalities among people with normal body weight. Such actions are decisive in the prevention and treatment of diseases. Therefore, the purpose of this article is to review the MONW diagnostic criteria used over the years.
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Rasaei N, Hosseininasab D, Shiraseb F, Gholami F, Noori S, Ghaffarian-Ensaf R, Daneshzad E, Clark CCT, Mirzaei K. The Association between Healthy Beverage Index and Healthy and Unhealthy Obesity Phenotypes among Obese Women: A Cross-Sectional Study. Int J Clin Pract 2022; 2022:7753259. [PMID: 36660267 PMCID: PMC9815920 DOI: 10.1155/2022/7753259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 09/24/2022] [Accepted: 12/08/2022] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Metabolic phenotypes are new dimensions of obesity. Two important types of these phenotypes are metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO). Studies showed that the components of the healthy beverage index (HBI) such as sugar-sweetened beverages (SSBs), milk, and fruit juices might have an association with MHO and MUO phenotypes. METHODS This cross-sectional study was performed on 210 women with the age range of 18-65 years and a body mass index (BMI) ≥25 kg/m2. The age range of the study population was the main inclusion criterion. Dietary intakes were assessed using a 147-item food frequency questionnaire (FFQ), as well as biochemistry and anthropometric parameters, in all participants. Metabolic health phenotypes were considered using the Karelis score, whilst HBI was evaluated based on 8 categories of beverages consumed. Analysis was carried out using binary logistic regression. RESULT After controlling for a wide variety of confounding variables such as age, energy intake, BMI, education, physical activity, marriage, economic status, job, and supplementation, we found that the participants in the highest tertile of HBI had a lower risk of abnormal metabolic status than those in the lowest tertile (OR = 0.49; 95% CI: 0.07-3.21; P trend: 0.04), and it was not statistically significant, but we saw a significant trend. CONCLUSION In conclusion, it seems that higher adherence to HBI can minimize the risk of metabolic abnormality, based on a significant trend.
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Affiliation(s)
- Niloufar Rasaei
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Dorsa Hosseininasab
- Department of Nutrition, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Farideh Shiraseb
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Fatemeh Gholami
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Sahar Noori
- Department of Nutrition, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | | | - Elnaz Daneshzad
- Non-Communicable Diseases Research Center, Alborz University of Medical Sciences, Karaj, Iran
| | - Cain C. T. Clark
- Centre for Intelligent Healthcare, Coventry University, Coventry, CV1 5FB, UK
| | - Khadijeh Mirzaei
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, Iran
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