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Nacis JS, Labrador JPH, Ronquillo DGD, Rodriguez MP, Dablo AMFD, Frane RD, Madrid ML, Santos NLC, Carrillo JJV, Fernandez MG, Gonzales GBL. A study protocol for a pilot randomized controlled trial to evaluate the effectiveness of a gene-based nutrition and lifestyle recommendation for weight management among adults: the MyGeneMyDiet ® study. Front Nutr 2023; 10:1238234. [PMID: 37674889 PMCID: PMC10477364 DOI: 10.3389/fnut.2023.1238234] [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: 06/11/2023] [Accepted: 08/09/2023] [Indexed: 09/08/2023] Open
Abstract
Introduction Managing nutrition and lifestyle practices, nutrition phenotypes, and the genome forms the foundation of precision nutrition. Precision nutrition focuses on metabolic variability among individuals, and one approach to achieving its goals is to integrate gene-based nutrition and lifestyle recommendations in nutrition practice. However, scientific evidence proving the effectiveness of such recommendations is limited. This study will examine whether providing nutrition and lifestyle recommendations based on individual genotype can lead to better weight loss, along with reduction in body mass index (BMI), waist circumference, and body fat percentage among overweight and obese adults. Methods and analysis A parallel group, single-blind, randomized controlled trial will be conducted. Sixty-two overweight/obese individuals aged 19-59 years old will be recruited. Participants will be randomly allocated to either the intervention (n = 31) or the control arm (n = 31). Participants in the intervention group will receive the MyGeneMyDiet® Recommendation for Weight Management, a gene-based nutrition and lifestyle recommendation that was developed based on existing evidence of the effects of FTO rs9939609 on body weight, BMI, and physical activity; UCP1 rs1800592 on calorie intake; and TCF7L2 rs7903146 on dietary fat intake. Participants in the control group will receive the standard recommendations for weight management. The primary outcomes will be the differences in weight, BMI, waist circumference, and body fat percentage between arms in both the active phase (6 months) and inactive phase (last 6 months) of the trial. Participants in both arms will be evaluated at baseline and in months 3, 6, 9, and 12. Discussion To the best of our knowledge, this will be the first gene-based intervention that will adopt a phase of intensive nutrition counseling, followed by a simulation of a free-living state to determine adherence to a gene-based recommendation. This study will contribute to the future implementation of precision nutrition interventions by providing evidence on the effectiveness of a gene-based nutrition and lifestyle recommendation for weight loss. Clinical trial registration clinicaltrials.gov, identifier [NCT05098899].
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Affiliation(s)
- Jacus S. Nacis
- Department of Science and Technology – Food and Nutrition Research Institute (DOST-FNRI), Taguig, Philippines
- Division of Human Nutrition and Health, Wageningen University & Research, Wageningen, Netherlands
| | - Jason Paolo H. Labrador
- Department of Science and Technology – Food and Nutrition Research Institute (DOST-FNRI), Taguig, Philippines
| | - Diana Glades D. Ronquillo
- Department of Science and Technology – Food and Nutrition Research Institute (DOST-FNRI), Taguig, Philippines
| | - Marietta P. Rodriguez
- Department of Science and Technology – Food and Nutrition Research Institute (DOST-FNRI), Taguig, Philippines
| | | | - Ruby D. Frane
- Department of Science and Technology – Food and Nutrition Research Institute (DOST-FNRI), Taguig, Philippines
| | - Marilou L. Madrid
- Department of Science and Technology – Food and Nutrition Research Institute (DOST-FNRI), Taguig, Philippines
| | - Noelle Lyn C. Santos
- Department of Science and Technology – Food and Nutrition Research Institute (DOST-FNRI), Taguig, Philippines
| | - Julianne Janine V. Carrillo
- Department of Science and Technology – Food and Nutrition Research Institute (DOST-FNRI), Taguig, Philippines
| | - Mikko Glen Fernandez
- Department of Science and Technology – Food and Nutrition Research Institute (DOST-FNRI), Taguig, Philippines
| | - Gerard Bryan L. Gonzales
- Division of Human Nutrition and Health, Wageningen University & Research, Wageningen, Netherlands
- Department of Public Health and Primary Care, Faculty of Medicine and Health Science, Ghent University, Ghent, Belgium
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Saftner DM, Bacon SN, Arienzo MM, Robtoy E, Schlauch K, Neveux I, Grzymski JJ, Carbone M. Predictions of Arsenic in Domestic Well Water Sourced from Alluvial Aquifers of the Western Great Basin, USA. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:3124-3133. [PMID: 36795051 PMCID: PMC11587882 DOI: 10.1021/acs.est.2c07948] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Chronic exposure to high levels of arsenic in drinking water can have wide-ranging health effects and is a global health concern. The domestic well population of the western Great Basin (WGB) is at increased risk of exposure to arsenic due to the hydrologic, geologic, and climatic setting of the region. A logistic regression (LR) model was developed to predict the probability of elevated arsenic (≥5 μg/L) in alluvial aquifers and assess the potential geologic hazard level posed to domestic well populations. Alluvial aquifers are susceptible to arsenic contamination, which is a concern because they are the primary source of water for domestic well users of the WGB. The probability of elevated arsenic at a domestic well is strongly influenced by tectonic and geothermal variables, including the total Quaternary fault length in the hydrographic basin and the distance between the sampled well and a geothermal system. The model had an overall accuracy of 81%, sensitivity of 92%, and specificity of 55%. Results show a >50% probability of elevated arsenic in untreated well water for approximately 49 thousand (64%) alluvial-aquifer domestic well users in northern Nevada, northeastern California, and western Utah.
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Affiliation(s)
- Daniel M Saftner
- Division of Hydrologic Sciences, Desert Research Institute, 2215 Raggio Parkway, Reno, Nevada 89512, United States
| | - Steven N Bacon
- Division of Hydrologic Sciences, Desert Research Institute, 2215 Raggio Parkway, Reno, Nevada 89512, United States
| | - Monica M Arienzo
- Division of Hydrologic Sciences, Desert Research Institute, 2215 Raggio Parkway, Reno, Nevada 89512, United States
| | - Erika Robtoy
- Division of Hydrologic Sciences, Desert Research Institute, 2215 Raggio Parkway, Reno, Nevada 89512, United States
| | - Karen Schlauch
- Center for Genomic Medicine, Desert Research Institute, 2215 Raggio Parkway, Reno, Nevada 89512, United States
| | - Iva Neveux
- Center for Genomic Medicine, Desert Research Institute, 2215 Raggio Parkway, Reno, Nevada 89512, United States
| | - Joseph J Grzymski
- Center for Genomic Medicine, Desert Research Institute, 2215 Raggio Parkway, Reno, Nevada 89512, United States
| | - Michele Carbone
- University of Hawai'i Cancer Center, 701 Ilalo Street, Honolulu, Hawaii 96813, United States
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Association of common genetic variants with body mass index in Russian population. Eur J Clin Nutr 2023; 77:574-578. [PMID: 36690773 DOI: 10.1038/s41430-023-01265-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 01/09/2023] [Accepted: 01/12/2023] [Indexed: 01/24/2023]
Abstract
BACKGROUND Overweight is the scourge of modern society and a major risk factor for many diseases. For this reason, understanding the genetic component predisposing to high body mass index (BMI) seems to be an important task along with preventive measures aimed at improving eating behavior and increasing physical activity. METHODS We analyzed genetic data of a European cohort (n = 21,080, 47.25% women, East Slavs ancestry >80%) for 5 frequently found genes in the context of association with obesity: IPX3 (rs3751723), MC4R (rs17782313), TMEM18 (rs6548238), PPARG (rs1801282) and FTO (rs9939609). RESULTS Our study revealed significant associations of FTO (rs9939609) (β = 0.37 (kg/m2)/allele, p = <2 × 10-16), MC4R (rs17782313) (β = 0.28 (kg/m2)/allele, p = 5.79 × 10-9), TMEM18 (rs6548238) (β = 0.29 (kg/m2)/allele, p = 2.43 × 10-8) with BMI and risk of obesity. CONCLUSIONS The results confirm the contribution of FTO, M4CR, and TMEM18 genes to the mechanism of body weight regulation and control.
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Arienzo MM, Saftner D, Bacon SN, Robtoy E, Neveux I, Schlauch K, Carbone M, Grzymski J. Naturally occurring metals in unregulated domestic wells in Nevada, USA. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 851:158277. [PMID: 36029812 PMCID: PMC9588670 DOI: 10.1016/j.scitotenv.2022.158277] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Revised: 08/18/2022] [Accepted: 08/21/2022] [Indexed: 05/26/2023]
Abstract
The dominant source of drinking water in rural Nevada, United States, is privately-owned domestic wells. Because the water from these wells is unregulated with respect to government guidelines, it is the owner's responsibility to test their groundwater for heavy metals and other contaminants. Arsenic, lead, cadmium, and uranium have been previously measured at concentrations above Environmental Protection Agency (EPA) guidelines in Nevada groundwater. This is a public health concern because elevated levels of these metals are known to have negative health effects. We recruited individuals through a population health study, the Healthy Nevada Project, to submit drinking water samples from domestic wells for testing. Water samples were returned from 174 households with private wells. We found 22 % had arsenic concentrations exceeding the EPA maximum contaminant level (MCL) of 10 μg/L. Additionally, federal, state, or health-based guidelines were exceeded for 8 % of the households for uranium and iron, 6 % for lithium and manganese, 4 % for molybdenum, and 1 % for lead. The maximum observed concentrations of arsenic, uranium, and lead were ∼80, ∼5, and ∼1.5 times the EPA guideline values, respectively. 41 % of households had a treatment system and submitted both pre- and post-treatment water samples from their well. The household treatments were shown to reduce metal concentrations, but concentrations above guideline values were still observed. Many treatment systems cannot reduce the concentration below guideline values because of water chemistry, treatment failure, or improper treatment techniques. These results show the pressing need for continued education and outreach on regular testing of domestic well waters, proper treatment types, and health effects of metal contamination. These findings are potentially applicable to other arid areas where groundwater contamination of naturally occurring heavy metals occurs.
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Affiliation(s)
- Monica M Arienzo
- Division of Hydrologic Sciences, Desert Research Institute, Reno, NV, USA.
| | - Daniel Saftner
- Division of Hydrologic Sciences, Desert Research Institute, Reno, NV, USA
| | - Steven N Bacon
- Division of Hydrologic Sciences, Desert Research Institute, Reno, NV, USA
| | - Erika Robtoy
- Division of Hydrologic Sciences, Desert Research Institute, Reno, NV, USA
| | - Iva Neveux
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, USA
| | - Karen Schlauch
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, USA
| | | | - Joseph Grzymski
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, USA; Renown Health, Reno, NV, USA
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Xu J, Johnson JS, Signer R, Birgegård A, Jordan J, Kennedy MA, Landén M, Maguire SL, Martin NG, Mortensen PB, Petersen LV, Thornton LM, Bulik CM, Huckins LM. Exploring the clinical and genetic associations of adult weight trajectories using electronic health records in a racially diverse biobank: a phenome-wide and polygenic risk study. Lancet Digit Health 2022; 4:e604-e614. [PMID: 35780037 PMCID: PMC9612590 DOI: 10.1016/s2589-7500(22)00099-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 04/19/2022] [Accepted: 05/06/2022] [Indexed: 11/10/2022]
Abstract
BACKGROUND Weight trajectories might reflect individual health status. In this study, we aimed to examine the clinical and genetic associations of adult weight trajectories using electronic health records (EHRs) in the BioMe Biobank. METHODS We constructed four weight trajectories based on a-priori definitions of weight changes (5% or 10%) using annual weight in EHRs (stable weight, weight gain, weight loss, and weight cycle); the final weight dataset included 21 487 participants with 162 783 annual weight measures. To confirm accurate assignment of weight trajectories, we manually reviewed weight trajectory plots for 100 random individuals. We then did a hypothesis-free phenome-wide association study (PheWAS) to identify diseases associated with each weight trajectory. Next, we estimated the single-nucleotide polymorphism-based heritability (hSNP2) of weight trajectories using GCTA-GREML, and we did a hypothesis-driven analysis of anorexia nervosa and depression polygenic risk scores (PRS) on these weight trajectories, given both diseases are associated with weight changes. We extended our analyses to the UK Biobank to replicate findings from a patient population to a generally healthy population. FINDINGS We found high concordance between manually assigned weight trajectories and those assigned by the algorithm (accuracy ≥98%). Stable weight was consistently associated with lower disease risks among those passing Bonferroni-corrected p value in our PheWAS (p≤4·4 × 10-5). Additionally, we identified an association between depression and weight cycle (odds ratio [OR] 1·42, 95% CI 1·31-1·55, p≤7·7 × 10-16). The adult weight trajectories were heritable (using 5% weight change as the cutoff: hSNP2 of 2·1%, 95% CI 0·9-3·3, for stable weight; 4·1%, 1·4-6·8, for weight gain; 5·5%, 2·8-8·2, for weight loss; and 4·7%, 2·3-7·1%, for weight cycle). Anorexia nervosa PRS was positively associated with weight loss trajectory among individuals without eating disorder diagnoses (OR1SD 1·16, 95% CI 1·07-1·26, per 1 SD higher PRS, p=0·011), and the association was not attenuated by obesity PRS. No association was found between depression PRS and weight trajectories after permutation tests. All main findings were replicated in the UK Biobank (p<0·05). INTERPRETATION Our findings suggest the importance of considering weight from a longitudinal aspect for its association with health and highlight a crucial role of weight management during disease development and progression. FUNDING Klarman Family Foundation, US National Institute of Mental Health (NIMH).
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Affiliation(s)
- Jiayi Xu
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jessica S Johnson
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rebecca Signer
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andreas Birgegård
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jennifer Jordan
- Department of Psychological Medicine, University of Otago, Christchurch, New Zealand; Canterbury District Health Board, Christchurch, New Zealand
| | - Martin A Kennedy
- Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
| | - Mikael Landén
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Sarah L Maguire
- InsideOut Institute, Charles Perkins Centre, The University of Sydney, Camperdown, Sydney, NSW, Australia
| | - Nicholas G Martin
- Genetics & Computational Biology Department, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Preben Bo Mortensen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark; National Centre for Register-Based Research, Aarhus BSS, and Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
| | - Liselotte V Petersen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark; National Centre for Register-Based Research, Aarhus BSS, and Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
| | - Laura M Thornton
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Cynthia M Bulik
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Laura M Huckins
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Mental Illness Research, Education and Clinical Centers, James J Peters Department of Veterans Affairs Medical Center, Bronx, NY, USA.
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Wright KM, Deighan AG, Di Francesco A, Freund A, Jojic V, Churchill GA, Raj A. Age and diet shape the genetic architecture of body weight in diversity outbred mice. eLife 2022; 11:64329. [PMID: 35838135 PMCID: PMC9286741 DOI: 10.7554/elife.64329] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 05/20/2022] [Indexed: 12/26/2022] Open
Abstract
Understanding how genetic variation shapes a complex trait relies on accurately quantifying both the additive genetic and genotype–environment interaction effects in an age-dependent manner. We used a linear mixed model to quantify diet-dependent genetic contributions to body weight measured through adulthood in diversity outbred female mice under five diets. We observed that heritability of body weight declined with age under all diets, except the 40% calorie restriction diet. We identified 14 loci with age-dependent associations and 19 loci with age- and diet-dependent associations, with many diet-dependent loci previously linked to neurological function and behavior in mice or humans. We found their allelic effects to be dynamic with respect to genomic background, age, and diet, identifying several loci where distinct alleles affect body weight at different ages. These results enable us to more fully understand and predict the effectiveness of dietary intervention on overall health throughout age in distinct genetic backgrounds. Body weight is one trait influenced by genes, age and environmental factors. Both internal and external environmental pressures are known to affect genetic variation over time. However, it is largely unknown how all factors – including age – interact to shape metabolism and bodyweight. Wright et al. set out to quantify the interactions between genes and diet in ageing mice and found that the effect of genetics on mouse body weight changes with age. In the experiments, Wright et al. weighed 960 female mice with diverse genetic backgrounds, starting at two months of age into adulthood. The animals were randomized to different diets at six months of age. Some mice had unlimited food access, others received 20% or 40% less calories than a typical mouse diet, and some fasted one or two days per week. Variations in their genetic background explained about 80% of differences in mice’s weight, but the influence of genetics relative to non-genetic factors decreased as they aged. Mice on the 40% calorie restriction diet were an exception to this rule and genetics accounted for 80% of their weight throughout adulthood, likely due to reduced influence from diet and reduced interactions between diet and genes. Several genes involved in metabolism, neurological function, or behavior, were associated with mouse weight. The experiments highlight the importance of considering interactions between genetics, environment, and age in determining complex traits like body weight. The results and the approaches used by Wright et al. may help other scientists learn more about how the genetic predisposition to disease changes with environmental stimuli and age.
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Affiliation(s)
- Kevin M Wright
- Calico Life Sciences LLC, South San Francisco, United States
| | | | | | - Adam Freund
- Calico Life Sciences LLC, South San Francisco, United States
| | - Vladimir Jojic
- Calico Life Sciences LLC, South San Francisco, United States
| | | | - Anil Raj
- Calico Life Sciences LLC, South San Francisco, United States
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Carreras-Gallo N, Cáceres A, Balagué-Dobón L, Ruiz-Arenas C, Andrusaityte S, Carracedo Á, Casas M, Chatzi L, Grazuleviciene R, Gutzkow KB, Lepeule J, Maitre L, Nieuwenhuijsen M, Slama R, Stratakis N, Thomsen C, Urquiza J, Wright J, Yang T, Escaramís G, Bustamante M, Vrijheid M, Pérez-Jurado LA, González JR. The early-life exposome modulates the effect of polymorphic inversions on DNA methylation. Commun Biol 2022; 5:455. [PMID: 35550596 PMCID: PMC9098634 DOI: 10.1038/s42003-022-03380-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 04/19/2022] [Indexed: 11/14/2022] Open
Abstract
Polymorphic genomic inversions are chromosomal variants with intrinsic variability that play important roles in evolution, environmental adaptation, and complex traits. We investigated the DNA methylation patterns of three common human inversions, at 8p23.1, 16p11.2, and 17q21.31 in 1,009 blood samples from children from the Human Early Life Exposome (HELIX) project and in 39 prenatal heart tissue samples. We found inversion-state specific methylation patterns within and nearby flanking each inversion region in both datasets. Additionally, numerous inversion-exposure interactions on methylation levels were identified from early-life exposome data comprising 64 exposures. For instance, children homozygous at inv-8p23.1 and higher meat intake were more susceptible to TDH hypermethylation (P = 3.8 × 10−22); being the inversion, exposure, and gene known risk factors for adult obesity. Inv-8p23.1 associated hypermethylation of GATA4 was also detected across numerous exposures. Our data suggests that the pleiotropic influence of inversions during development and lifetime could be substantially mediated by allele-specific methylation patterns which can be modulated by the exposome. Analysis of the relationship between presence of common DNA sequence inversions and DNA methylation patterns suggests a role for environmental exposures (such as food intake) in mediating inversion state-specific methylation patterns.
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Affiliation(s)
| | - Alejandro Cáceres
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.,Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.,Department of Mathematics, Escola d'Enginyeria de Barcelona Est (EEBE), Universitat Politècnica de Catalunya, Barcelona, 08019, Spain
| | | | - Carlos Ruiz-Arenas
- Institut Hospital del Mar d'Investigacions Mediques (IMIM), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Madrid, Spain.,Department of Health and Experimental Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Sandra Andrusaityte
- Department of Environmental Science, Vytautas Magnus University, 44248, Kaunas, Lithuania
| | - Ángel Carracedo
- Medicine Genomics Group, Centro de Investigación Biomédica en Red Enfermedades Raras (CIBERER), University of Santiago de Compostela, CEGEN-PRB3, Santiago de Compostela, Spain.,Galician Foundation of Genomic Medicine, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Servicio Gallego de Salud (SERGAS), Santiago de Compostela, Galicia, Spain
| | - Maribel Casas
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.,Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.,Department of Health and Experimental Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Leda Chatzi
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Regina Grazuleviciene
- Department of Environmental Science, Vytautas Magnus University, 44248, Kaunas, Lithuania
| | - Kristine Bjerve Gutzkow
- Department of Environmental Health, Norwegian Institute of Public Health, 0456, Oslo, Norway
| | - Johanna Lepeule
- Institut national de la santé et de la recherche médicale (Inserm) and Université Grenoble-Alpes, Institute for Advanced Biosciences (IAB), Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Grenoble, France
| | - Léa Maitre
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.,Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.,Department of Health and Experimental Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Mark Nieuwenhuijsen
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.,Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.,Department of Health and Experimental Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Remy Slama
- Institut national de la santé et de la recherche médicale (Inserm) and Université Grenoble-Alpes, Institute for Advanced Biosciences (IAB), Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Grenoble, France
| | - Nikos Stratakis
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
| | - Cathrine Thomsen
- Department of Environmental Health, Norwegian Institute of Public Health, 0456, Oslo, Norway
| | - Jose Urquiza
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.,Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.,Department of Health and Experimental Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Tiffany Yang
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Geòrgia Escaramís
- Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.,Department of Biomedical Science, Faculty of Medicine and Health Science, University of Barcelona, Barcelona, Spain.,Research Group on Statistics, Econometrics and Health (GRECS), UdG, Girona, Spain
| | - Mariona Bustamante
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.,Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.,Department of Health and Experimental Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain.,Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
| | - Martine Vrijheid
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.,Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.,Department of Health and Experimental Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Luis A Pérez-Jurado
- Institut Hospital del Mar d'Investigacions Mediques (IMIM), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Madrid, Spain.,Department of Health and Experimental Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain.,Genetics Service, Hospital del Mar, Barcelona, Spain
| | - Juan R González
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain. .,Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP), Madrid, Spain. .,Department of Mathematics, Universitat Autònoma de Barcelona, Bellaterra, Spain.
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8
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Kühnapfel A, Ahnert P, Horn K, Kirsten H, Loeffler M, Scholz M. First genome-wide association study of 99 body measures derived from 3-dimensional body scans. Genes Dis 2022; 9:777-788. [PMID: 35782980 PMCID: PMC9243350 DOI: 10.1016/j.gendis.2021.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 01/26/2021] [Accepted: 02/05/2021] [Indexed: 11/23/2022] Open
Abstract
Body height, body mass index, hip and waist circumference are important risk factors or outcome variables in clinical and epidemiological research with complex underlying genetics. However, these classical anthropometric traits represent only a very limited view on the human body and other traits with potentially higher functional specificity are not yet studied to a larger extent. Participants of LIFE-Adult were assessed by three-dimensional body scanner VITUS XXL determining 99 high-quality anthropometric traits in parallel. Genotyping was performed by Axiom Genome-Wide CEU 1 Array Plate microarray technology and imputation was done using 1000 Genomes phase 3 reference panel. Combined phenotype and genetic information are available for a total of 7,562 participants. Largest heritabilities were estimated for height traits (maximum heritability with h2 = 44% for neck height) and 61 traits achieved values larger than 20%. By genome-wide analyses, we identified 16 loci associated with at least one of the 99 traits. Ten of these loci were not described for association with classical anthropometric traits so far. The strongest novel association was observed for 7p14.3 (rs11979006, P = 2.12 × 10−9) for the trait Back Width with ZNRF2 as the most plausible candidate gene. Loci established for association with classical anthropometric traits were subjected to anthropometric phenome-wide association analysis. From the reported 709 loci, 211 are co-associated with body scanner traits (enrichment: OR = 1.96, P = 1.08 × 10−61). We conclude that genetics of 3D laser-based anthropometry is promising to identify novel loci and to improve the functional understanding of established ones.
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9
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Schlauch KA, Read RW, Neveux I, Lipp B, Slonim A, Grzymski JJ. The Impact of ACEs on BMI: An Investigation of the Genotype-Environment Effects of BMI. Front Genet 2022; 13:816660. [PMID: 35342390 PMCID: PMC8942770 DOI: 10.3389/fgene.2022.816660] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 02/04/2022] [Indexed: 12/31/2022] Open
Abstract
Adverse Childhood Experiences are stressful and traumatic events occurring before the age of eighteen shown to cause mental and physical health problems, including increased risk of obesity. Obesity remains an ongoing national challenge with no predicted solution. We examine a subset of the Healthy Nevada Project, focusing on a multi-ethnic cohort of 15,886 sequenced participants with recalled adverse childhood events, to study how ACEs and their genotype-environment interactions affect BMI. Specifically, the Healthy Nevada Project participants sequenced by the Helix Exome+ platform were cross-referenced to their electronic medical records and social health determinants questionnaire to identify: 1) the effect of ACEs on BMI in the absence of genetics; 2) the effect of genotype-environment interactions on BMI; 3) how these gene-environment interactions differ from standard genetic associations of BMI. The study found very strong significant associations between the number of adverse childhood experiences and adult obesity. Additionally, we identified fifty-five common and rare variants that exhibited gene-interaction effects including three variants in the CAMK1D gene and four variants in LHPP; both genes are linked to schizophrenia. Surprisingly, none of the variants identified with interactive effects were in canonical obesity-related genes. Here we show the delicate balance between genes and environment, and how the two strongly influence each other.
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Affiliation(s)
- Karen A Schlauch
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, United States
| | - Robert W Read
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, United States
| | - Iva Neveux
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, United States
| | - Bruce Lipp
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, United States
| | | | - Joseph J Grzymski
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, United States.,Renown Health, Reno, NV, United States
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10
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Dashti HS, Miranda N, Cade BE, Huang T, Redline S, Karlson EW, Saxena R. Interaction of obesity polygenic score with lifestyle risk factors in an electronic health record biobank. BMC Med 2022; 20:5. [PMID: 35016652 PMCID: PMC8753909 DOI: 10.1186/s12916-021-02198-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 11/23/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Genetic and lifestyle factors have considerable effects on obesity and related diseases, yet their effects in a clinical cohort are unknown. This study in a patient biobank examined associations of a BMI polygenic risk score (PRS), and its interactions with lifestyle risk factors, with clinically measured BMI and clinical phenotypes. METHODS The Mass General Brigham (MGB) Biobank is a hospital-based cohort with electronic health record, genetic, and lifestyle data. A PRS for obesity was generated using 97 genetic variants for BMI. An obesity lifestyle risk index using survey responses to obesogenic lifestyle risk factors (alcohol, education, exercise, sleep, smoking, and shift work) was used to dichotomize the cohort into high and low obesogenic index based on the population median. Height and weight were measured at a clinical visit. Multivariable linear cross-sectional associations of the PRS with BMI and interactions with the obesity lifestyle risk index were conducted. In phenome-wide association analyses (PheWAS), similar logistic models were conducted for 675 disease outcomes derived from billing codes. RESULTS Thirty-three thousand five hundred eleven patients were analyzed (53.1% female; age 60.0 years; BMI 28.3 kg/m2), of which 17,040 completed the lifestyle survey (57.5% female; age: 60.2; BMI: 28.1 (6.2) kg/m2). Each standard deviation increment in the PRS was associated with 0.83 kg/m2 unit increase in BMI (95% confidence interval (CI) =0.76, 0.90). There was an interaction between the obesity PRS and obesity lifestyle risk index on BMI. The difference in BMI between those with a high and low obesogenic index was 3.18 kg/m2 in patients in the highest decile of PRS, whereas that difference was only 1.55 kg/m2 in patients in the lowest decile of PRS. In PheWAS, the obesity PRS was associated with 40 diseases spanning endocrine/metabolic, circulatory, and 8 other disease groups. No interactions were evident between the PRS and the index on disease outcomes. CONCLUSIONS In this hospital-based clinical biobank, obesity risk conferred by common genetic variants was associated with elevated BMI and this risk was attenuated by a healthier patient lifestyle. Continued consideration of the role of lifestyle in the context of genetic predisposition in healthcare settings is necessary to quantify the extent to which modifiable lifestyle risk factors may moderate genetic predisposition and inform clinical action to achieve personalized medicine.
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Affiliation(s)
- Hassan S Dashti
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. .,Broad Institute, Cambridge, MA, USA. .,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
| | - Nicole Miranda
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Brian E Cade
- Broad Institute, Cambridge, MA, USA.,Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Tianyi Huang
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.,Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Elizabeth W Karlson
- Mass General Brigham Personalized Medicine, Mass General Brigham HealthCare, Boston, MA, USA.,Department of Medicines, Brigham and Women's Hospital and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.,Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Boston, MA, USA
| | - Richa Saxena
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.,Broad Institute, Cambridge, MA, USA.,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
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11
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Schlauch KA, Read RW, Koning SM, Neveux I, Grzymski JJ. Using phenome-wide association studies and the SF-12 quality of life metric to identify profound consequences of adverse childhood experiences on adult mental and physical health in a Northern Nevadan population. Front Psychiatry 2022; 13:984366. [PMID: 36276335 PMCID: PMC9583677 DOI: 10.3389/fpsyt.2022.984366] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 09/15/2022] [Indexed: 11/13/2022] Open
Abstract
In this research, we examine and identify the implications of Adverse Childhood Experiences (ACEs) on a range of health outcomes, with particular focus on a number of mental health disorders. Many previous studies observed that traumatic childhood events are linked to long-term adult diseases using the standard Adverse Childhood Experience Questionnaire. The study cohort was derived from the Healthy Nevada Project, a volunteer-based population health study in which each adult participant is invited to take a retrospective questionnaire that includes the Adverse Childhood Experience Questionnaire, the 12-item Short Form Survey measuring quality of life, and self-reported incidence of nine mental disorders. Using participant's cross-referenced electronic health records, a phenome-wide association analysis of 1,703 phenotypes and the incidence of ACEs examined links between traumatic events in childhood and adult disease. These analyses showed that many mental disorders were significantly associated with ACEs in a dose-response manner. Similarly, a dose response between ACEs and obesity, chronic pain, migraine, and other physical phenotypes was identified. An examination of the prevalence of self-reported mental disorders and incidence of ACEs showed a positive relationship. Furthermore, participants with less adverse childhood events experienced a higher quality of life, both physically and mentally. The whole-phenotype approach confirms that ACEs are linked with many negative adult physical and mental health outcomes. With the nationwide prevalence of ACEs as high as 67%, these findings suggest a need for new public health resources: ACE-specific interventions and early childhood screenings.
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Affiliation(s)
- Karen A Schlauch
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, United States
| | - Robert W Read
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, United States
| | | | - Iva Neveux
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, United States
| | - Joseph J Grzymski
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, United States.,Renown Health, Reno, NV, United States
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12
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Abstract
Obesity is a chronic, relapsing, and multifactorial disease, with a rising prevalence and an associated high economic burden. Achieving successful and sustained weight loss outcomes with current interventions is challenging. This is due, at least in part, to the disease's heterogenous pathophysiology that is yet to be completely understood. Technological advances and greater capabilities for the extraction and storage of information have facilitated the application of precision medicine. Several precision medicine initiatives have been proposed to improve obesity outcomes. Most of these initiatives are based on -omics technologies. Although the data generated from these technologies have led to developing hypotheses that may explain the underpinnings of obesity, their applicability to the clinical practice is yet to be determined. There are other initiatives that have identified quantitative or qualitative physiologic traits that can be targeted and that could have a more immediate clinical impact. This review aims to provide a perspective of current initiatives for precision medicine for obesity.
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13
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Blum K, Thanos PK, Wang GJ, Bowirrat A, Gomez LL, Baron D, Jalali R, Gondré-Lewis MC, Gold MS. Dopaminergic and other genes related to reward induced overeating, Bulimia, Anorexia Nervosa, and Binge eating. EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2021. [DOI: 10.1080/23808993.2021.1994186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Kenneth Blum
- Division of Addiction Research & Education, Center for Psychiatry, Medicine & Primary Care (Office of the Provost), Western University Health Sciences Graduate School of Biomedical Sciences, Pomona, CA, USA
- Department of Precision Behavioral Management, The Kenneth Blum Behavioral Neurogenetic Institute (Division of Ivitalize Inc.), Austin, TX, USA
- Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
- Department of Psychiatry, University of Vermont, Burlington, VM, USA
- Centre for Genomics and Applied Gene Technology, Institute of Integrative Omics and Applied Biotechnology, Nonakuri, India
| | - Panayotis K. Thanos
- Behavioral Neuropharmacology and Neuroimaging Laboratory on Addictions, Research Institute on Addictions, University at Buffalo, Buffalo, NY, USA
| | - Gene -Jack Wang
- Laboratory of Neuroimaging, National Institute of Alcohol Abuse and Alcoholism, Bethesda, MD, USA
| | - Abdalla Bowirrat
- Department of Molecular Biology and Adelson School of Medicine, Ariel University, Ariel, Israel
| | - Luis Llanos Gomez
- Department of Precision Behavioral Management, The Kenneth Blum Behavioral Neurogenetic Institute (Division of Ivitalize Inc.), Austin, TX, USA
| | - David Baron
- Division of Addiction Research & Education, Center for Psychiatry, Medicine & Primary Care (Office of the Provost), Western University Health Sciences Graduate School of Biomedical Sciences, Pomona, CA, USA
| | - Rehan Jalali
- Department of Precision Behavioral Management, The Kenneth Blum Behavioral Neurogenetic Institute (Division of Ivitalize Inc.), Austin, TX, USA
| | - Marjorie C Gondré-Lewis
- Neuropsychopharmacology Laboratory, Department of Anatomy, Howard University College of Medicine, Washington, Washington, DC, USA
| | - Mark S Gold
- Department of Psychiatry, School of Medicine, Washington University, St. Louis, MO, USA
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14
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Hanscombe KB, Persyn E, Traylor M, Glanville KP, Hamer M, Coleman JRI, Lewis CM. The genetic case for cardiorespiratory fitness as a clinical vital sign and the routine prescription of physical activity in healthcare. Genome Med 2021; 13:180. [PMID: 34753499 PMCID: PMC8579601 DOI: 10.1186/s13073-021-00994-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 10/19/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Cardiorespiratory fitness (CRF) and physical activity (PA) are well-established predictors of morbidity and all-cause mortality. However, CRF is not routinely measured and PA not routinely prescribed as part of standard healthcare. The American Heart Association (AHA) recently presented a scientific case for the inclusion of CRF as a clinical vital sign based on epidemiological and clinical observation. Here, we leverage genetic data in the UK Biobank (UKB) to strengthen the case for CRF as a vital sign and make a case for the prescription of PA. METHODS We derived two CRF measures from the heart rate data collected during a submaximal cycle ramp test: CRF-vo2max, an estimate of the participants' maximum volume of oxygen uptake, per kilogram of body weight, per minute; and CRF-slope, an estimate of the rate of increase of heart rate during exercise. Average PA over a 7-day period was derived from a wrist-worn activity tracker. After quality control, 70,783 participants had data on the two derived CRF measures, and 89,683 had PA data. We performed genome-wide association study (GWAS) analyses by sex, and post-GWAS techniques to understand genetic architecture of the traits and prioritise functional genes for follow-up. RESULTS We found strong evidence that genetic variants associated with CRF and PA influenced genetic expression in a relatively small set of genes in the heart, artery, lung, skeletal muscle and adipose tissue. These functionally relevant genes were enriched among genes known to be associated with coronary artery disease (CAD), type 2 diabetes (T2D) and Alzheimer's disease (three of the top 10 causes of death in high-income countries) as well as Parkinson's disease, pulmonary fibrosis, and blood pressure, heart rate, and respiratory phenotypes. Genetic variation associated with lower CRF and PA was also correlated with several disease risk factors (including greater body mass index, body fat and multiple obesity phenotypes); a typical T2D profile (including higher insulin resistance, higher fasting glucose, impaired beta-cell function, hyperglycaemia, hypertriglyceridemia); increased risk for CAD and T2D; and a shorter lifespan. CONCLUSIONS Genetics supports three decades of evidence for the inclusion of CRF as a clinical vital sign. Given the genetic, clinical and epidemiological evidence linking CRF and PA to increased morbidity and mortality, regular measurement of CRF as a marker of health and routine prescription of PA could be a prudent strategy to support public health.
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Affiliation(s)
- Ken B Hanscombe
- Department of Medical & Molecular Genetics, King's College London, London, UK. .,Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK.
| | - Elodie Persyn
- Department of Medical & Molecular Genetics, King's College London, London, UK
| | | | - Kylie P Glanville
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
| | - Mark Hamer
- Institute of Sport Exercise & Health, Division of Surgery and Interventional Science, University College London, London, UK
| | - Jonathan R I Coleman
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
| | - Cathryn M Lewis
- Department of Medical & Molecular Genetics, King's College London, London, UK.,Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
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15
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Vimaleswaran KS. GeNuIne (gene-nutrient interactions) Collaboration: towards implementing multi-ethnic population-based nutrigenetic studies of vitamin B 12 and D deficiencies and metabolic diseases. Proc Nutr Soc 2021; 80:1-11. [PMID: 34548115 DOI: 10.1017/s0029665121002822] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Gene-nutrient interactions (GeNuIne) collaboration, a large-scale collaborative project, has been initiated to investigate the impact of gene-nutrient interactions on cardiometabolic diseases using population-based studies from ethnically diverse populations. In this project, the relationship between deficiencies of vitamins B12 and D, and metabolic diseases was explored using a nutrigenetic approach. A genetic risk score (GRS) analysis was used to examine the combined effect of several genetic variations that have been shown to be associated with metabolic diseases and vitamin B12 and D deficiencies, respectively. In Sri Lankan, Indonesian and Brazilian populations, those carrying a high B12-GRS had an increased risk of metabolic diseases under the influence of dietary protein, fibre and carbohydrate intakes, respectively; however, in Asian Indians, genetically instrumented metabolic disease risk showed a significant association with low vitamin B12 status. With regards to nutrigenetic studies on vitamin D status, although high metabolic-GRS showed an interaction with dietary carbohydrate intake on vitamin D status, the study in Indonesian women demonstrated a vitamin D GRS-carbohydrate interaction on body fat percentage. In summary, these nutrigenetic studies from multiple ethnic groups have provided evidence for the influence of the dietary factors on the relationship between vitamin B12/D deficiency and metabolic outcomes. Furthermore, these studies highlight the existence of genetic heterogeneity in gene-diet interactions across ethnically diverse populations, which further implicates the significance of personalised dietary approaches for the prevention of these micronutrient deficiencies and metabolic diseases.
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Affiliation(s)
- Karani S Vimaleswaran
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences, University of Reading, Reading, UK
- The Institute for Food, Nutrition, and Health (IFNH), University of Reading, Reading, UK
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16
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Kaare M, Mikheim K, Lilleväli K, Kilk K, Jagomäe T, Leidmaa E, Piirsalu M, Porosk R, Singh K, Reimets R, Taalberg E, Schäfer MKE, Plaas M, Vasar E, Philips MA. High-Fat Diet Induces Pre-Diabetes and Distinct Sex-Specific Metabolic Alterations in Negr1-Deficient Mice. Biomedicines 2021; 9:1148. [PMID: 34572334 PMCID: PMC8466019 DOI: 10.3390/biomedicines9091148] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 08/27/2021] [Accepted: 08/28/2021] [Indexed: 11/16/2022] Open
Abstract
In the large GWAS studies, NEGR1 gene has been one of the most significant gene loci for body mass phenotype. The purpose of the current study was to clarify the role of NEGR1 in the maintenance of systemic metabolism, including glucose homeostasis, by using both male and female Negr1-/- mice receiving a standard or high fat diet (HFD). We found that 6 weeks of HFD leads to higher levels of blood glucose in Negr1-/- mice. In the glucose tolerance test, HFD induced phenotype difference only in male mice; Negr1-/- male mice displayed altered glucose tolerance, accompanied with upregulation of circulatory branched-chain amino acids (BCAA). The general metabolomic profile indicates that Negr1-/- mice are biased towards glyconeogenesis, fatty acid synthesis, and higher protein catabolism, all of which are amplified by HFD. Negr1 deficiency appears to induce alterations in the efficiency of energy storage; reduced food intake could be an attempt to compensate for the metabolic challenge present in the Negr1-/- males, particularly during the HFD exposure. Our results suggest that the presence of functional Negr1 allows male mice to consume more HFD and prevents the development of glucose intolerance, liver steatosis, and excessive weight gain.
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Affiliation(s)
- Maria Kaare
- Institute of Biomedicine and Translational Medicine, Department of Physiology, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia; (K.M.); (K.L.); (T.J.); (M.P.); (K.S.); (E.V.); (M.-A.P.)
- Center of Excellence in Genomics and Translational Medicine, University of Tartu, 50411 Tartu, Estonia; (K.K.); (R.P.); (E.T.)
| | - Kaie Mikheim
- Institute of Biomedicine and Translational Medicine, Department of Physiology, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia; (K.M.); (K.L.); (T.J.); (M.P.); (K.S.); (E.V.); (M.-A.P.)
- Center of Excellence in Genomics and Translational Medicine, University of Tartu, 50411 Tartu, Estonia; (K.K.); (R.P.); (E.T.)
| | - Kersti Lilleväli
- Institute of Biomedicine and Translational Medicine, Department of Physiology, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia; (K.M.); (K.L.); (T.J.); (M.P.); (K.S.); (E.V.); (M.-A.P.)
- Center of Excellence in Genomics and Translational Medicine, University of Tartu, 50411 Tartu, Estonia; (K.K.); (R.P.); (E.T.)
| | - Kalle Kilk
- Center of Excellence in Genomics and Translational Medicine, University of Tartu, 50411 Tartu, Estonia; (K.K.); (R.P.); (E.T.)
- Institute of Biomedicine and Translational Medicine, Department of Biochemistry, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia
| | - Toomas Jagomäe
- Institute of Biomedicine and Translational Medicine, Department of Physiology, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia; (K.M.); (K.L.); (T.J.); (M.P.); (K.S.); (E.V.); (M.-A.P.)
- Center of Excellence in Genomics and Translational Medicine, University of Tartu, 50411 Tartu, Estonia; (K.K.); (R.P.); (E.T.)
- Institute of Biomedicine and Translational Medicine, Laboratory Animal Center, University of Tartu, 14B Ravila Street, 50411 Tartu, Estonia; (R.R.); (M.P.)
| | - Este Leidmaa
- Institute of Molecular Psychiatry, Medical Faculty, University of Bonn, 53129 Bonn, Germany;
| | - Maria Piirsalu
- Institute of Biomedicine and Translational Medicine, Department of Physiology, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia; (K.M.); (K.L.); (T.J.); (M.P.); (K.S.); (E.V.); (M.-A.P.)
- Center of Excellence in Genomics and Translational Medicine, University of Tartu, 50411 Tartu, Estonia; (K.K.); (R.P.); (E.T.)
| | - Rando Porosk
- Center of Excellence in Genomics and Translational Medicine, University of Tartu, 50411 Tartu, Estonia; (K.K.); (R.P.); (E.T.)
- Institute of Biomedicine and Translational Medicine, Department of Biochemistry, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia
| | - Katyayani Singh
- Institute of Biomedicine and Translational Medicine, Department of Physiology, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia; (K.M.); (K.L.); (T.J.); (M.P.); (K.S.); (E.V.); (M.-A.P.)
- Center of Excellence in Genomics and Translational Medicine, University of Tartu, 50411 Tartu, Estonia; (K.K.); (R.P.); (E.T.)
| | - Riin Reimets
- Institute of Biomedicine and Translational Medicine, Laboratory Animal Center, University of Tartu, 14B Ravila Street, 50411 Tartu, Estonia; (R.R.); (M.P.)
| | - Egon Taalberg
- Center of Excellence in Genomics and Translational Medicine, University of Tartu, 50411 Tartu, Estonia; (K.K.); (R.P.); (E.T.)
- Institute of Biomedicine and Translational Medicine, Department of Biochemistry, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia
| | - Michael K. E. Schäfer
- Department of Anesthesiology, Focus Program Translational Neurosciences, Research Center for Immunotherapy, University Medical Center of the Johannes Gutenberg-University Mainz, 55131 Mainz, Germany;
| | - Mario Plaas
- Institute of Biomedicine and Translational Medicine, Laboratory Animal Center, University of Tartu, 14B Ravila Street, 50411 Tartu, Estonia; (R.R.); (M.P.)
| | - Eero Vasar
- Institute of Biomedicine and Translational Medicine, Department of Physiology, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia; (K.M.); (K.L.); (T.J.); (M.P.); (K.S.); (E.V.); (M.-A.P.)
- Center of Excellence in Genomics and Translational Medicine, University of Tartu, 50411 Tartu, Estonia; (K.K.); (R.P.); (E.T.)
| | - Mari-Anne Philips
- Institute of Biomedicine and Translational Medicine, Department of Physiology, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia; (K.M.); (K.L.); (T.J.); (M.P.); (K.S.); (E.V.); (M.-A.P.)
- Center of Excellence in Genomics and Translational Medicine, University of Tartu, 50411 Tartu, Estonia; (K.K.); (R.P.); (E.T.)
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17
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Fernandez-Luque L, Al Herbish A, Al Shammari R, Argente J, Bin-Abbas B, Deeb A, Dixon D, Zary N, Koledova E, Savage MO. Digital Health for Supporting Precision Medicine in Pediatric Endocrine Disorders: Opportunities for Improved Patient Care. Front Pediatr 2021; 9:715705. [PMID: 34395347 PMCID: PMC8358399 DOI: 10.3389/fped.2021.715705] [Citation(s) in RCA: 12] [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: 05/27/2021] [Accepted: 06/17/2021] [Indexed: 12/16/2022] Open
Abstract
Digitalization of healthcare delivery is rapidly fostering development of precision medicine. Multiple digital technologies, known as telehealth or eHealth tools, are guiding individualized diagnosis and treatment for patients, and can contribute significantly to the objectives of precision medicine. From a basis of "one-size-fits-all" healthcare, precision medicine provides a paradigm shift to deliver a more nuanced and personalized approach. Genomic medicine utilizing new technologies can provide precision analysis of causative mutations, with personalized understanding of mechanisms and effective therapy. Education is fundamental to the telehealth process, with artificial intelligence (AI) enhancing learning for healthcare professionals and empowering patients to contribute to their care. The Gulf Cooperation Council (GCC) region is rapidly implementing telehealth strategies at all levels and a workshop was convened to discuss aspirations of precision medicine in the context of pediatric endocrinology, including diabetes and growth disorders, with this paper based on those discussions. GCC regional investment in AI, bioinformatics and genomic medicine, is rapidly providing healthcare benefits. However, embracing precision medicine is presenting some major new design, installation and skills challenges. Genomic medicine is enabling precision and personalization of diagnosis and therapy of endocrine conditions. Digital education and communication tools in the field of endocrinology include chatbots, interactive robots and augmented reality. Obesity and diabetes are a major challenge in the GCC region and eHealth tools are increasingly being used for management of care. With regard to growth failure, digital technologies for growth hormone (GH) administration are being shown to enhance adherence and response outcomes. While technical innovations become more affordable with increasing adoption, we should be aware of sustainability, design and implementation costs, training of HCPs and prediction of overall healthcare benefits, which are essential for precision medicine to develop and for its objectives to be achieved.
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Affiliation(s)
| | | | - Riyad Al Shammari
- National Center for Artificial Intelligence, Saudi Data and Artificial Intelligence Authority, Riyadh, Saudi Arabia
| | - Jesús Argente
- Department of Pediatrics & Pediatric Endocrinology, Hospital Infantil Universitario Niño Jesús, Instituto de Investigación La Princesa, Universidad Autónoma de Madrid, Madrid, Spain
- Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- IMDEA Food Institute, CEIUAM+CSIC, Madrid, Spain
| | - Bassam Bin-Abbas
- King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | - Asma Deeb
- Paediatric Endocrine Division, Sheikh Shakhbout Medical City, Abu Dhabi, United Arab Emirates
| | - David Dixon
- Connected Health and Devices, Merck, Ares Trading SA, Aubonne, Switzerland
| | - Nabil Zary
- Institute for Excellence in Health Professions Education, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates
| | | | - Martin O. Savage
- Department of Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine & Dentistry, London, United Kingdom
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18
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Isgin-Atici K, Alsulami S, Turan-Demirci B, Surendran S, Sendur SN, Lay I, Karabulut E, Ellahi B, Lovegrove JA, Alikasifoglu M, Erbas T, Vimaleswaran KS, Buyuktuncer Z. FTO gene-lifestyle interactions on serum adiponectin concentrations and central obesity in a Turkish population. Int J Food Sci Nutr 2021; 72:375-385. [PMID: 32746650 DOI: 10.1080/09637486.2020.1802580] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 07/07/2020] [Accepted: 07/23/2020] [Indexed: 12/18/2022]
Abstract
The aim of the study was to investigate whether lifestyle factors modify the association between fat mass and obesity-associated (FTO) gene single nucleotide polymorphisms (SNPs) and obesity in a Turkish population. The study included 400 unrelated individuals, aged 24-50 years recruited in a hospital setting. Dietary intake and physical activity were assessed using 24-hour dietary recall and self-report questionnaire, respectively. A genetic risk score (GRS) was developed using FTO SNPs, rs9939609 and rs10163409. Body mass index and fat mass index were significantly associated with FTO SNP rs9939609 (p = 0.001 and p = 0.002, respectively) and GRS (p = 0.002 and p = 0.003, respectively). The interactions between SNP rs9939609 and physical activity on adiponectin concentrations, and SNP rs10163409 and dietary protein intake on increased waist circumference were statistically significant (Pinteraction = 0.027 and Pinteraction = 0.044, respectively). Our study has demonstrated that the association between FTO SNPs and central obesity might be modified by lifestyle factors in this Turkish population.
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Affiliation(s)
- Kubra Isgin-Atici
- Department of Nutrition and Dietetics, Faculty of Health Sciences, Hacettepe University, Ankara, Turkey
| | - Sooad Alsulami
- Department of Food and Nutritional Sciences, University of Reading, Whiteknights, Reading, UK
- Department of Clinical Nutrition, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Busra Turan-Demirci
- Department of Nutrition and Dietetics, Faculty of Health Sciences, Hacettepe University, Ankara, Turkey
| | - Shelini Surendran
- Department of Food and Nutritional Sciences, University of Reading, Whiteknights, Reading, UK
| | - Suleyman Nahit Sendur
- Department of Endocrinology and Metabolism, School of Medicine, Hacettepe University, Ankara, Turkey
| | - Incilay Lay
- Department of Medical Biochemistry, School of Medicine, Hacettepe University, Ankara, Turkey
- Clinical Pathology Laboratory, Hacettepe University Hospitals, Ankara, Turkey
| | - Erdem Karabulut
- Department of Biostatistics, School of Medicine, Hacettepe University, Ankara, Turkey
- Department of Bioinformatics, Hacettepe University, Ankara, Turkey
| | - Basma Ellahi
- Faculty of Health and Social Care, University of Chester, Chester, UK
| | - Julie A Lovegrove
- Department of Food and Nutritional Sciences, University of Reading, Whiteknights, Reading, UK
| | - Mehmet Alikasifoglu
- Department of Medical Genetics, School of Medicine, Hacettepe University Ankara, Turkey
- Genetics Diagnostic Centre, DAMAGEN, Ankara, Turkey
| | - Tomris Erbas
- Department of Endocrinology and Metabolism, School of Medicine, Hacettepe University, Ankara, Turkey
| | | | - Zehra Buyuktuncer
- Department of Nutrition and Dietetics, Faculty of Health Sciences, Hacettepe University, Ankara, Turkey
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19
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Secolin R, Gonsales MC, Rocha CS, Naslavsky M, De Marco L, Bicalho MAC, Vazquez VL, Zatz M, Silva WA, Lopes-Cendes I. Exploring a Region on Chromosome 8p23.1 Displaying Positive Selection Signals in Brazilian Admixed Populations: Additional Insights Into Predisposition to Obesity and Related Disorders. Front Genet 2021; 12:636542. [PMID: 33841501 PMCID: PMC8027303 DOI: 10.3389/fgene.2021.636542] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 03/04/2021] [Indexed: 11/13/2022] Open
Abstract
We recently reported a deviation of local ancestry on the chromosome (ch) 8p23.1, which led to positive selection signals in a Brazilian population sample. The deviation suggested that the genetic variability of candidate genes located on ch 8p23.1 may have been evolutionarily advantageous in the early stages of the admixture process. In the present work, we aim to extend the previous work by studying additional Brazilian admixed individuals and examining DNA sequencing data from the ch 8p23.1 candidate region. Thus, we inferred the local ancestry of 125 exomes from individuals born in five towns within the Southeast region of Brazil (São Paulo, Campinas, Barretos, and Ribeirão Preto located in the state of São Paulo and Belo Horizonte, the capital of the state of Minas Gerais), and compared to data from two public Brazilian reference genomic databases, BIPMed and ABraOM, and with information from the 1000 Genomes Project phase 3 and gnomAD databases. Our results revealed that ancestry is similar among individuals born in the five Brazilian towns assessed; however, an increased proportion of sub-Saharan African ancestry was observed in individuals from Belo Horizonte. In addition, individuals from the five towns considered, as well as those from the ABRAOM dataset, had the same overrepresentation of Native-American ancestry on the ch 8p23.1 locus that was previously reported for the BIPMed reference sample. Sequencing analysis of ch 8p23.1 revealed the presence of 442 non-synonymous variants, including frameshift, inframe deletion, start loss, stop gain, stop loss, and splicing site variants, which occurred in 24 genes. Among these genes, 13 were associated with obesity, type II diabetes, lipid levels, and waist circumference (PRAG1, MFHAS1, PPP1R3B, TNKS, MSRA, PRSS55, RP1L1, PINX1, MTMR9, FAM167A, BLK, GATA4, and CTSB). These results strengthen the hypothesis that a set of variants located on ch 8p23.1 that result from positive selection during early admixture events may influence obesity-related disease predisposition in admixed individuals of the Brazilian population. Furthermore, we present evidence that the exploration of local ancestry deviation in admixed individuals may provide information with the potential to be translated into health care improvement.
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Affiliation(s)
- Rodrigo Secolin
- Department of Medical Genetics and Genomic Medicine, Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas - UNICAMP, Campinas, Brazil
| | - Marina C Gonsales
- Department of Medical Genetics and Genomic Medicine, Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas - UNICAMP, Campinas, Brazil
| | - Cristiane S Rocha
- Department of Medical Genetics and Genomic Medicine, Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas - UNICAMP, Campinas, Brazil
| | - Michel Naslavsky
- Departament of Genetics and Evolutive Biology, Human Genome and Stem Cell Research Center, Institute of Bioscience, University of São Paulo (USP), São Paulo, Brazil
| | - Luiz De Marco
- Department of Surgery, Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Maria A C Bicalho
- Department of Clinical Medicine, Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Vinicius L Vazquez
- Molecular Oncology Research Center (CPOM) - Barretos Cancer Hospital, Barretos, Brazil
| | - Mayana Zatz
- Departament of Genetics and Evolutive Biology, Human Genome and Stem Cell Research Center, Institute of Bioscience, University of São Paulo (USP), São Paulo, Brazil
| | - Wilson A Silva
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo at Ribeirão Preto (USP), Ribeirão Preto, Brazil
| | - Iscia Lopes-Cendes
- Department of Medical Genetics and Genomic Medicine, Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas - UNICAMP, Campinas, Brazil
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20
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Read RW, Schlauch KA, Lombardi VC, Cirulli ET, Washington NL, Lu JT, Grzymski JJ. Genome-Wide Identification of Rare and Common Variants Driving Triglyceride Levels in a Nevada Population. Front Genet 2021; 12:639418. [PMID: 33763119 PMCID: PMC7982958 DOI: 10.3389/fgene.2021.639418] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Accepted: 02/12/2021] [Indexed: 01/08/2023] Open
Abstract
Clinical conditions correlated with elevated triglyceride levels are well-known: coronary heart disease, hypertension, and diabetes. Underlying genetic and phenotypic mechanisms are not fully understood, partially due to lack of coordinated genotypic-phenotypic data. Here we use a subset of the Healthy Nevada Project, a population of 9,183 sequenced participants with longitudinal electronic health records to examine consequences of altered triglyceride levels. Specifically, Healthy Nevada Project participants sequenced by the Helix Exome+ platform were cross-referenced to their electronic medical records to identify: (1) rare and common single-variant genome-wide associations; (2) gene-based associations using a Sequence Kernel Association Test; (3) phenome-wide associations with triglyceride levels; and (4) pleiotropic variants linked to triglyceride levels. The study identified 549 significant single-variant associations (p < 8.75 × 10-9), many in chromosome 11's triglyceride hotspot: ZPR1, BUD13, APOC3, APOA5. A well-known protective loss-of-function variant in APOC3 (R19X) was associated with a 51% decrease in triglyceride levels in the cohort. Sixteen gene-based triglyceride associations were identified; six of these genes surprisingly did not include a single variant with significant associations. Results at the variant and gene level were validated with the UK Biobank. The combination of a single-variant genome-wide association, a gene-based association method, and phenome wide-association studies identified rare and common variants, genes, and phenotypes associated with elevated triglyceride levels, some of which may have been overlooked with standard approaches.
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Affiliation(s)
- Robert W. Read
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, United States
| | - Karen A. Schlauch
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, United States
| | - Vincent C. Lombardi
- Department of Microbiology and Immunology, School of Medicine, University of Nevada, Reno, Reno, NV, United States
| | | | | | - James T. Lu
- Helix Opco, LLC., San Mateo, CA, United States
| | - Joseph J. Grzymski
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, United States
- Renown Health, Reno, NV, United States
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