1
|
Zheng G, Cheng Y, Wang C, Wang B, Zou X, Zhou J, Peng L, Zeng T. Elucidating the causal nexus and immune mediation between frailty and chronic kidney disease: integrative multi-omics analysis. Ren Fail 2024; 46:2367028. [PMID: 39010723 PMCID: PMC11265307 DOI: 10.1080/0886022x.2024.2367028] [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] [Received: 04/30/2024] [Accepted: 06/06/2024] [Indexed: 07/17/2024] Open
Abstract
BACKGROUND Empirical research has consistently documented the concurrent manifestation of frailty and chronic kidney disease (CKD). However, the existence of a reverse causal association or the influence of confounding variables on these correlations remains ambiguous. METHODS Our analysis of 7,078 participants from National Health and Nutrition Examination Survey(NHANES) (1999-2018) applied weighted logistic regression and Mendelian Randomization (MR) to investigate the correlation between the frailty index (FI) and renal function. The multivariate MR analysis was specifically adjusted for type 2 diabetes and hypertension. Further analysis explored 3282 plasma proteins to link FI to CKD. A two-step network MR highlighted immune cells' mediating roles in the FI-CKD relationship. RESULT Genetically inferred FI and various renal function markers are significantly correlated, as supported by NHANES analyses. Multivariate MR analysis revealed a direct causal association between the FI and CKD. Additionally, our investigation into plasma proteins identified Tmprss11D and MICB correlated with FI and CKD, respectively. A two-step network MR to reveal 15 immune cell types, notably Central Memory CD4+ T cells and Lymphocytes, as crucial mediators between FI and CKD. CONCLUSION Our work establishes a causal connection between frailty and CKD, mediated by specific immune cell profiles. These findings highlight the importance of immune mechanisms in the frailty-CKD interplay and suggest that targeting shared risk factors and immune pathways could improve management strategies for these conditions. Our research contributes to a more nuanced understanding of frailty and CKD, offering new avenues for intervention and patient care in an aging population.
Collapse
Affiliation(s)
- Guanghao Zheng
- Department of Medicine, Graduate School of Nanchang University, Nanchang, China
| | - Yu Cheng
- Department of Medicine, Graduate School of Nanchang University, Nanchang, China
| | - Chenlong Wang
- Department of Central Laboratory, The Affiliated Huaian No.1 Peopele’s Hospital, Nanjing Medical University, Huai’an, China
| | - Bin Wang
- Department of Medicine, Graduate School of Nanchang University, Nanchang, China
| | - Xinchang Zou
- Department of Medicine, Graduate School of Nanchang University, Nanchang, China
| | - Jie Zhou
- Department of Medicine, Graduate School of Nanchang University, Nanchang, China
| | - Lifen Peng
- Molecular Experiment Center, Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, Nanchang, China
| | - Tao Zeng
- Department of Urology, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| |
Collapse
|
2
|
Jansen PR, Vos N, van Uhm J, Dekkers IA, van der Meer R, Mannens MMAM, van Haelst MM. The utility of obesity polygenic risk scores from research to clinical practice: A review. Obes Rev 2024; 25:e13810. [PMID: 39075585 DOI: 10.1111/obr.13810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Revised: 06/13/2024] [Accepted: 07/10/2024] [Indexed: 07/31/2024]
Abstract
Obesity represents a major public health emergency worldwide, and its etiology is shaped by a complex interplay of environmental and genetic factors. Over the last decade, polygenic risk scores (PRS) have emerged as a promising tool to quantify an individual's genetic risk of obesity. The field of PRS in obesity genetics is rapidly evolving, shedding new lights on obesity mechanisms and holding promise for contributing to personalized prevention and treatment. Challenges persist in terms of its clinical integration, including the need for further validation in large-scale prospective cohorts, ethical considerations, and implications for health disparities. In this review, we provide a comprehensive overview of PRS for studying the genetics of obesity, spanning from methodological nuances to clinical applications and challenges. We summarize the latest developments in the generation and refinement of PRS for obesity, including advances in methodologies for aggregating genome-wide association study data and improving PRS predictive accuracy, and discuss limitations that need to be overcome to fully realize its potential benefits of PRS in both medicine and public health.
Collapse
Affiliation(s)
- Philip R Jansen
- Amsterdam UMC, Department of Human Genetics, University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Reproduction and Development Research Institute, Amsterdam, Netherlands
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, VU University, Amsterdam, Netherlands
- Netherlands Institute for Neuroscience, Amsterdam, Netherlands
| | - Niels Vos
- Amsterdam UMC, Department of Human Genetics, University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Reproduction and Development Research Institute, Amsterdam, Netherlands
| | - Jorrit van Uhm
- Amsterdam UMC, Department of Human Genetics, University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Reproduction and Development Research Institute, Amsterdam, Netherlands
| | - Ilona A Dekkers
- Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
| | - Rieneke van der Meer
- Netherlands Obesity Clinic, Huis ter Heide, Netherlands
- Amsterdam UMC, Department of Endocrinology and Metabolism, University of Amsterdam, Amsterdam, Netherlands
| | - Marcel M A M Mannens
- Amsterdam UMC, Department of Human Genetics, University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Reproduction and Development Research Institute, Amsterdam, Netherlands
| | - Mieke M van Haelst
- Amsterdam UMC, Department of Human Genetics, University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Reproduction and Development Research Institute, Amsterdam, Netherlands
- Amsterdam UMC, Emma Center for Personalized Medicine, University of Amsterdam, Amsterdam, Netherlands
| |
Collapse
|
3
|
Peng L, Shen J, Li L, Liu J, Jiang X, Zhang G, Li Y. Birthweight influences liver structure, function and disease risk: Evidence of a causal association. Diabetes Obes Metab 2024; 26:4976-4988. [PMID: 39228281 DOI: 10.1111/dom.15910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Revised: 08/16/2024] [Accepted: 08/16/2024] [Indexed: 09/05/2024]
Abstract
AIM Low birthweight is an issue during pregnancy associated with an increased risk of developing liver disease later in life. Previous Mendelian randomisation (MR) studies which explored this issue have not isolated the direct impact of the foetus on birthweight. In the present study, MR was used to assess whether direct foetal effects on birthweight were causally associated with liver structure, function and disease risk independent of intrauterine effects. MATERIALS AND METHODS We extracted single nucleotide polymorphisms (SNPs) from genome-wide association studies (GWAS) about direct foetal-affected birthweight (321 223 cases) to conduct univariable and multivariable MR analyses to explore the relationships between birthweight and 4 liver structure measures, 9 liver function measures and 18 liver diseases. A two-step MR analysis was used to further assess and quantify the mediating effects of the mediators. RESULTS When isolating direct foetal effects, genetically predicted lower birthweight was associated with a higher risk of non-alcoholic fatty liver disease (NAFLD) (odds ratios [OR], 95% confidence interval [CI]: 1.61, 1.29-2.02, p < 0.001), higher magnetic resonance imaging [MRI] proton density fat fraction (PDFF) and higher serum gamma glutamyltransferase (GGT). Two-step MR identified two candidate mediators that partially mediate the direct foetal effect of lower birthweight on NAFLD, including fasting insulin (proportion mediated: 22.29%) and triglycerides (6.50%). CONCLUSIONS Our MR analysis reveals a direct causal association between lower birthweight and liver MRI PDFF, as well as the development of NAFLD, which persisted even after accounting for the potential influence of maternal factors. In addition, we identified fasting insulin and triglycerides as mediators linking birthweight and hepatic outcomes, providing insights for early clinical interventions.
Collapse
Affiliation(s)
- Lei Peng
- Department of Gastroenterology, First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jiajia Shen
- Department of General Surgery, First Affiliated Hospital, Nanjing Medical University, Nanjing, China
| | - Lurong Li
- Department of Gastroenterology, First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jiahao Liu
- Department of Gastroenterology, First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xingzhou Jiang
- Department of Gastroenterology, First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Guoxin Zhang
- Department of Gastroenterology, First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yuanyuan Li
- Department of Endocrinology, Children's Hospital of Nanjing Medical University, Nanjing, China
| |
Collapse
|
4
|
Wei X, Iao WC, Zhang Y, Lin Z, Lin H. Retinal Microvasculature Causally Affects the Brain Cortical Structure: A Mendelian Randomization Study. OPHTHALMOLOGY SCIENCE 2024; 4:100465. [PMID: 39149712 PMCID: PMC11324828 DOI: 10.1016/j.xops.2024.100465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 01/05/2024] [Accepted: 01/08/2024] [Indexed: 08/17/2024]
Abstract
Purpose To reveal the causality between retinal vascular density (VD), fractal dimension (FD), and brain cortex structure using Mendelian randomization (MR). Design Cross-sectional study. Participants Genome-wide association studies of VD and FD involving 54 813 participants from the United Kingdom Biobank were used. The brain cortical features, including the cortical thickness (TH) and surface area (SA), were extracted from 51 665 patients across 60 cohorts. Surface area and TH were measured globally and in 34 functional regions using magnetic resonance imaging. Methods Bidirectional univariable MR (UVMR) was used to detect the causality between FD, VD, and brain cortex structure. Multivariable MR (MVMR) was used to adjust for confounding factors, including body mass index and blood pressure. Main Outcome Measures The global and regional measurements of brain cortical SA and TH. Results At the global level, higher VD is related to decreased TH (β = -0.0140 mm, 95% confidence interval: -0.0269 mm to -0.0011 mm, P = 0.0339). At the functional level, retinal FD is related to the TH of banks of the superior temporal sulcus and transverse temporal region without global weighted, as well as the SA of the posterior cingulate after adjustment. Vascular density is correlated with the SA of subregions of the frontal lobe and temporal lobe, in addition to the TH of the inferior temporal, entorhinal, and pars opercularis regions in both UVMR and MVMR. Bidirectional MR studies showed a causation between the SA of the parahippocampal and cauda middle frontal gyrus and retinal VD. No pleiotropy was detected. Conclusions Fractal dimension and VD causally influence the cortical structure and vice versa, indicating that the retinal microvasculature may serve as a biomarker for cortex structural changes. Our study provides insights into utilizing noninvasive fundus images to predict cortical structural deteriorations and neuropsychiatric disorders. Financial Disclosures The author(s) have no proprietary or commercial interest in any materials discussed in this article.
Collapse
Affiliation(s)
- Xiaoyue Wei
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Vision Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong, China
- Center for Precision Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Wai Cheng Iao
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Vision Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong, China
- Center for Precision Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yi Zhang
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Zijie Lin
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Haotian Lin
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Vision Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong, China
- Center for Precision Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China
- Hainan Eye Hospital and Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Haikou, Hainan, China
| |
Collapse
|
5
|
Ling H, Raraigh KS, Pugh EW, Aksit MA, Zhang P, Pace RG, Faino AV, Bamshad MJ, Gibson RL, O'Neal W, Knowles MR, Blackman SM, Cutting GR. Genetic modifiers of body mass index in individuals with cystic fibrosis. Am J Hum Genet 2024; 111:2203-2218. [PMID: 39260370 DOI: 10.1016/j.ajhg.2024.08.004] [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] [Received: 12/12/2023] [Revised: 08/07/2024] [Accepted: 08/07/2024] [Indexed: 09/13/2024] Open
Abstract
To identify modifier loci underlying variation in body mass index (BMI) in persons with cystic fibrosis (pwCF), we performed a genome-wide association study (GWAS). Utilizing longitudinal height and weight data, along with demographic information and covariates from 4,393 pwCF, we calculated AvgBMIz representing the average of per-quarter BMI Z scores. The GWAS incorporated 9.8M single nucleotide polymorphisms (SNPs) with a minor allele frequency (MAF) > 0.005 extracted from whole-genome sequencing (WGS) of each study subject. We observed genome-wide significant association with a variant in FTO (FaT mass and Obesity-associated gene; rs28567725; p value = 1.21e-08; MAF = 0.41, β = 0.106; n = 4,393 individuals) and a variant within ADAMTS5 (A Disintegrin And Metalloproteinase with ThromboSpondin motifs 5; rs162500; p value = 2.11e-10; MAF = 0.005, β = -0.768; n = 4,085 pancreatic-insufficient individuals). Notably, BMI-associated variants in ADAMTS5 occur on a haplotype that is much more common in African (AFR, MAF = 0.183) than European (EUR, MAF = 0.006) populations (1000 Genomes project). A polygenic risk score (PRS) calculated using 924 SNPs (excluding 17 in FTO) showed significant association with AvgBMIz (p value = 2.2e-16; r2 = 0.03). Association between variants in FTO and the PRS correlation reveals similarities in the genetic architecture of BMI in CF and the general population. Inclusion of Black individuals in whom the single-gene disorder CF is much less common but genomic diversity is greater facilitated detection of association with variants that are in LD with functional SNPs in ADAMTS5. Our results illustrate the importance of population diversity, particularly when attempting to identify variants that manifest only under certain physiologic conditions.
Collapse
Affiliation(s)
- Hua Ling
- Center for Inherited Disease Research, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Karen S Raraigh
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Elizabeth W Pugh
- Center for Inherited Disease Research, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Melis A Aksit
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Peng Zhang
- Center for Inherited Disease Research, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Rhonda G Pace
- Marsico Lung Institute/UNC CF Research Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Anna V Faino
- Children's Core for Biostatistics, Epidemiology and Analytics in Research, Seattle Children's Research Institute, Seattle, WA 98101, USA
| | - Michael J Bamshad
- Brotman Baty Institute for Precision Medicine, Seattle, WA 98195, USA; Department of Pediatrics, Division of Genetic Medicine, University of Washington, Seattle, WA 98195, USA; Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA; Center for Clinical and Translational Research, Seattle Children's Hospital, Seattle, WA 98105, USA
| | - Ronald L Gibson
- Center for Clinical and Translational Research, Seattle Children's Hospital, Seattle, WA 98105, USA; Department of Pediatrics, Division of Pulmonary & Sleep Medicine, University of Washington School of Medicine/Seattle Children's Hospital, Seattle, WA, USA
| | - Wanda O'Neal
- Marsico Lung Institute/UNC CF Research Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Michael R Knowles
- Marsico Lung Institute/UNC CF Research Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Scott M Blackman
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Division of Pediatric Endocrinology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Garry R Cutting
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
| |
Collapse
|
6
|
Xiao P, Li C, Wu J, Dai J. Unravel the distinct effects of adiposity at different life stages on COVID-19 susceptibility and severity: A life-course Mendelian randomization study. J Med Virol 2024; 96:e29943. [PMID: 39360640 DOI: 10.1002/jmv.29943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Revised: 09/09/2024] [Accepted: 09/20/2024] [Indexed: 10/04/2024]
Abstract
Childhood obesity is widely recognized as a risk factor for numerous health conditions, particularly cardiovascular disease. However, it remains unclear whether childhood adiposity directly affects the risk of COVID-19 in later life. We aimed to investigate the causal effects of early life adiposity on COVID-19 susceptibility and severity. We used genetic instruments from large-scale genome-wide association studies to examine the relationships between birth weight, childhood and adulthood adiposity indicators (including body mass index [BMI], obesity, and body size), and COVID-19 outcomes. Univariable and multivariable Mendelian randomization (MR) analyses were used to obtain the causal estimates. Univariable MR analyses found that childhood BMI and obesity were positively associated with COVID-19 risk and severity in adulthood, however, the significant associations were attenuated to null after further adjusting for adulthood adiposity indicators in multivariable MR analyses. In contrast, our analysis revealed strong evidence of a genetically predicted effect of childhood obesity on COVID-19 hospitalization (OR 1.08, 95% CI: 1.01-1.15, p = 2.12E-2), which remained robust even after adjusting for adulthood obesity and potential lifestyle confounders. Our results highlight the importance of promoting healthy weight management throughout life to reduce the risk of COVID-19.
Collapse
Affiliation(s)
- Pei Xiao
- Center for Non-communicable Disease Management, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Chi Li
- Department of AIDS/STD Control and Prevention, Shijingshan District Center for Disease Control and Prevention, Beijing, China
| | - Jinyi Wu
- Department of Public Health, Wuhan Fourth Hospital, Wuhan, China
- School of public health, Fudan university, Shanghai, China
| | - Jiayuan Dai
- Department of Rare Diseases, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| |
Collapse
|
7
|
Jian S, Liu J, He M, Liu B, Liu K, Zang C, Su X, Zhang Y, Yi M. Crosstalk between gastrointestinal tract disorders and obstructive sleep apnea. Sleep Breath 2024; 28:2045-2053. [PMID: 39031245 DOI: 10.1007/s11325-024-03082-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 06/05/2024] [Accepted: 06/10/2024] [Indexed: 07/22/2024]
Abstract
PURPOSE Clinical studies suggested associations between obstructive sleep apnea (OSA) and gastrointestinal tract disorders. This study aims to investigate the genetic causal relationship between OSA and gastrointestinal tract disorders, specifically gastroesophageal reflux disease (GERD) and inflammatory bowel disease (IBD). METHODS In this study, we employed two-sample Mendelian Randomization (MR) analysis to investigate the potential relationships between OSA and GERD, and between OSA and IBD. More specifically, the primary analysis utilized inverse variance weighting (IVW). Weighted median, MR Egger, and MR PRESSO were applied to complicate potential violations of MR assumptions. Also, sensitivity analysis was evaluated and similar analysis was performed again after outliers were removed. Additionally, multivariable MR (MVMR) was conducted for associated pairs to adjust for obesity. RESULTS Genetically predicted risk of GERD increased OSA risk by approximately 60% (ORIVW = 1.62, 95%CI = [1.43,1.84]) which was also stable by other complicated approaches, and even with BMI adjusted by MVMR (ORadjBMI[95%CI] = 1.26 [1.15,1.37]). Besides, OSA showed a mild causal effect on increased GERD risk after adjusting for obesity (ORadjBMI[95%CI] = 1.05 [1.02,1.08]). Additionally, OSA increased the risks for IBD (ORIVW[95%CI] = 1.36 [1.12,1.65]), including a higher risk of CD (ORIVW[95%CI] = 1.41 [1.08,1.83]), and a trend for increasing UC risk (ORIVW[95%CI] = 1.29 [0.99,1.67]). CONCLUSION GERD exerts a substantial causality on increasing the risk of OSA. Conversely, the potential for a causal relationship that OSA contributes to the development of GERD or IBD remains probable. These findings support the crosstalk between gastrointestinal tract disorders and OSA.
Collapse
Affiliation(s)
- Shijie Jian
- Department of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- School of Life Sciences, Central South University, Changsha, China
| | - Jie Liu
- Department of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Xiangya Medical School, Central South University, Changsha, China
| | - Meng He
- Department of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Bin Liu
- Department of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Kun Liu
- School of Life Sciences, Central South University, Changsha, China
| | - Chenyang Zang
- Xiangya Medical School, Central South University, Changsha, China
| | - Xiaoli Su
- Department of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.
| | - Yuan Zhang
- Department of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.
| | - Minhan Yi
- School of Life Sciences, Central South University, Changsha, China.
| |
Collapse
|
8
|
He D, Cheng S, Wei W, Zhao Y, Cai Q, Chu X, Shi S, Zhang N, Qin X, Liu H, Jia Y, Cheng B, Wen Y, Zhang F. Body shape from birth to adulthood is associated with skeletal development: A Mendelian randomization study. Bone 2024; 187:117191. [PMID: 38969278 DOI: 10.1016/j.bone.2024.117191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 05/21/2024] [Accepted: 07/01/2024] [Indexed: 07/07/2024]
Abstract
BACKGROUND Observational studies have shown that childhood obesity is associated with adult bone health but yield inconsistent results. We aimed to explore the potential causal association between body shape and skeletal development. METHODS We used two-sample Mendelian randomization (MR) to estimate causal relationships between body shape from birth to adulthood and skeletal phenotypes, with exposures including placental weight, birth weight, childhood obesity, BMI, lean mass, fat mass, waist circumference, and hip circumference. Independent genetic instruments associated with the exposures at the genome-wide significance level (P < 5 × 10-8) were selected from corresponding large-scale genome-wide association studies. The inverse-variance weighted analysis was chosen as the primary method, and complementary MR analyses included the weighted median, MR-Egger, weighted mode, and simple mode. RESULTS The MR analysis shows strong evidence that childhood (β = -1.29 × 10-3, P = 8.61 × 10-5) and adulthood BMI (β = -1.28 × 10-3, P = 1.45 × 10-10) were associated with humerus length. Tibiofemoral angle was negatively associated with childhood BMI (β = -3.60 × 10-1, P = 3.00 × 10-5) and adolescent BMI (β = -3.62 × 10-1, P = 2.68 × 10-3). In addition, genetically predicted levels of appendicular lean mass (β = 1.16 × 10-3, P = 1.49 × 10-13), whole body fat mass (β = 1.66 × 10-3, P = 1.35 × 10-9), waist circumference (β = 1.72 × 10-3, P = 6.93 × 10-8) and hip circumference (β =1.28 × 10-3, P = 4.34 × 10-6) were all associated with tibia length. However, we found no causal association between placental weight, birth weight and bone length/width. CONCLUSIONS This large-scale MR analysis explores changes in growth patterns in the length/width of major bone sites, highlighting the important role of childhood body shape in bone development and providing insights into factors that may drive bone maturation.
Collapse
Affiliation(s)
- Dan He
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Shiqiang Cheng
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Wenming Wei
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yijing Zhao
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Qingqing Cai
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Xiaoge Chu
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Sirong Shi
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Na Zhang
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Xiaoyue Qin
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Huan Liu
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yumeng Jia
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Bolun Cheng
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yan Wen
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China.
| | - Feng Zhang
- NHC Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China.
| |
Collapse
|
9
|
Johnson EC, Austin-Zimmerman I, Thorpe HHA, Levey DF, Baranger DAA, Colbert SMC, Demontis D, Khokhar JY, Davis LK, Edenberg HJ, Di Forti M, Sanchez-Roige S, Gelernter J, Agrawal A. Cross-ancestry genetic investigation of schizophrenia, cannabis use disorder, and tobacco smoking. Neuropsychopharmacology 2024; 49:1655-1665. [PMID: 38906991 PMCID: PMC11399264 DOI: 10.1038/s41386-024-01886-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 04/22/2024] [Accepted: 05/06/2024] [Indexed: 06/23/2024]
Abstract
Individuals with schizophrenia frequently experience co-occurring substance use, including tobacco smoking and heavy cannabis use, and substance use disorders. There is interest in understanding the extent to which these relationships are causal, and to what extent shared genetic factors play a role. We explored the relationships between schizophrenia (Scz; European ancestry N = 161,405; African ancestry N = 15,846), cannabis use disorder (CanUD; European ancestry N = 886,025; African ancestry N = 120,208), and ever-regular tobacco smoking (Smk; European ancestry N = 805,431; African ancestry N = 24,278) using the largest available genome-wide studies of these phenotypes in individuals of African and European ancestries. All three phenotypes were positively genetically correlated (rgs = 0.17-0.62). Genetic instrumental variable analyses suggested the presence of shared heritable factors, but evidence for bidirectional causal relationships was also found between all three phenotypes even after correcting for these shared genetic factors. We identified 327 pleiotropic loci with 439 lead SNPs in the European ancestry data, 150 of which were novel (i.e., not genome-wide significant in the original studies). Of these pleiotropic loci, 202 had lead variants which showed convergent effects (i.e., same direction of effect) on Scz, CanUD, and Smk. Genetic variants convergent across all three phenotypes showed strong genetic correlations with risk-taking, executive function, and several mental health conditions. Our results suggest that both shared genetic factors and causal mechanisms may play a role in the relationship between CanUD, Smk, and Scz, but longitudinal, prospective studies are needed to confirm a causal relationship.
Collapse
Affiliation(s)
- Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.
| | - Isabelle Austin-Zimmerman
- Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Hayley H A Thorpe
- Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Daniel F Levey
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - David A A Baranger
- Department of Psychological and Brain Sciences, Washington University in Saint Louis, St. Louis, MO, USA
| | - Sarah M C Colbert
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ditte Demontis
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Department of Biomedicine and Centre for Integrative Sequencing (iSEQ), Aarhus University, Aarhus, Denmark
| | - Jibran Y Khokhar
- Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Lea K Davis
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Howard J Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Marta Di Forti
- Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Sandra Sanchez-Roige
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, USA
- Department of Psychiatry, UC San Diego School of Medicine, La Jolla, CA, USA
| | - Joel Gelernter
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| |
Collapse
|
10
|
Sung HL, Lin WY. Causal effects of cardiovascular health on five epigenetic clocks. Clin Epigenetics 2024; 16:134. [PMID: 39334501 PMCID: PMC11438310 DOI: 10.1186/s13148-024-01752-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2024] [Accepted: 09/25/2024] [Indexed: 09/30/2024] Open
Abstract
BACKGROUND This work delves into the relationship between cardiovascular health (CVH) and aging. Previous studies have shown an association of ideal CVH with a slower aging rate, measured by epigenetic age acceleration (EAA). However, the causal relationship between CVH and EAA has remained unexplored. METHODS AND RESULTS We performed genome-wide association studies (GWAS) on the (12-point) CVH score and its components using the Taiwan Biobank data, in which weighted genetic risk scores were treated as instrumental variables. Subsequently, we conducted a one-sample Mendelian Randomization (MR) analysis with the two-stage least-squares method on 2383 participants to examine the causal relationship between the (12-point) CVH score and EAA. As a result, we observed a significant causal effect of the CVH score on GrimAge acceleration (GrimEAA) (β [SE]: - 0.993 [0.363] year; p = 0.0063) and DNA methylation-based plasminogen activator inhibitor-1 (DNAmPAI-1) (β [SE]: - 0.294 [0.099] standard deviation (sd) of DNAmPAI-1; p = 0.0030). Digging individual CVH components in depth, the ideal total cholesterol score (0 [poor], 1 [intermediate], or 2 [ideal]) was causally associated with DNAmPAI-1 (β [SE]: - 0.452 [0.150] sd of DNAmPAI-1; false discovery rate [FDR] q = 0.0102). The ideal body mass index (BMI) score was causally associated with GrimEAA (β [SE]: - 2.382 [0.952] years; FDR q = 0.0498) and DunedinPACE (β [SE]: - 0.097 [0.030]; FDR q = 0.0044). We also performed a two-sample MR analysis using the summary statistics from European GWAS. We observed that the (12-point) CVH score exhibits a significant causal effect on Horvath's intrinsic epigenetic age acceleration (β [SE]: - 0.389 [0.186] years; p = 0.036) and GrimEAA (β [SE]: - 0.526 [0.244] years; p = 0.031). Furthermore, we detected causal effects of BMI (β [SE]: 0.599 [0.081] years; q = 2.91E-12), never smoking (β [SE]: - 2.981 [0.524] years; q = 1.63E-7), walking (β [SE]: - 4.313 [1.236] years; q = 0.004), and dried fruit intake (β [SE]: - 1.523 [0.504] years; q = 0.013) on GrimEAA in the European population. CONCLUSIONS Our research confirms the causal link between maintaining an ideal CVH and epigenetic age. It provides a tangible pathway for individuals to improve their health and potentially slow aging.
Collapse
Affiliation(s)
- Hsien-Liang Sung
- Institute of Health Data Analytics and Statistics, College of Public Health, National Taiwan University, Room 501, No. 17, Xu-Zhou Road, Taipei, 100, Taiwan
| | - Wan-Yu Lin
- Institute of Health Data Analytics and Statistics, College of Public Health, National Taiwan University, Room 501, No. 17, Xu-Zhou Road, Taipei, 100, Taiwan.
- Master of Public Health Degree Program, College of Public Health, National Taiwan University, Taipei, Taiwan.
| |
Collapse
|
11
|
Adams MJ, Thorp JG, Jermy BS, Kwong ASF, Kõiv K, Grotzinger AD, Nivard MG, Marshall S, Milaneschi Y, Baune BT, Müller-Myhsok B, Penninx BWJH, Boomsma DI, Levinson DF, Breen G, Pistis G, Grabe HJ, Tiemeier H, Berger K, Rietschel M, Magnusson PK, Uher R, Hamilton SP, Lucae S, Lehto K, Li QS, Byrne EM, Hickie IB, Martin NG, Medland SE, Wray NR, Tucker-Drob EM, Lewis CM, McIntosh AM, Derks EM. Genome-wide meta-analysis of ascertainment and symptom structures of major depression in case-enriched and community cohorts. Psychol Med 2024:1-10. [PMID: 39324397 DOI: 10.1017/s0033291724001880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/27/2024]
Abstract
BACKGROUND Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and etiological subtypes. There are several challenges to integrating symptom data from genetically informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data. METHODS We conducted genome-wide association studies of major depressive symptoms in three cohorts that were enriched for participants with a diagnosis of depression (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts who were not recruited on the basis of diagnosis (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors. RESULTS The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for the skip-structure in community cohorts (use of Depression and Anhedonia as gating symptoms). CONCLUSION The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analyzing genetic association data.
Collapse
Affiliation(s)
- Mark J Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Jackson G Thorp
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Bradley S Jermy
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Alex S F Kwong
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Kadri Kõiv
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Andrew D Grotzinger
- Department of Psychology and Neuroscience, University of Colorado at Boulder, Boulder, CO, USA
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | - Michel G Nivard
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Sally Marshall
- Centre for Genomic & Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Bernhard T Baune
- Department of Psychiatry, University of Melbourne, Melbourne, VIC, Australia
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia
- Department of Psychiatry, University of Münster, Münster, NRW, Germany
| | - Bertram Müller-Myhsok
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, BY, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, BY, Germany
- Institute of Population Health, University of Liverpool, Liverpool, UK
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology & Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Douglas F Levinson
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, King's College London, London, UK
| | - Giorgio Pistis
- Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, VD, Switzerland
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, MV, Germany
| | - Henning Tiemeier
- Child and Adolescent Psychiatry, Erasmus University Medical Center Rotterdam, Rotterdam, Netherlands
- Social and Behavioral Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, NRW, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, BW, Germany
| | - Patrik K Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Rudolf Uher
- Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Steven P Hamilton
- Psychiatry, Kaiser Permanente Northern California, San Francisco, CA, USA
| | - Susanne Lucae
- Max Planck Institute of Psychiatry, Munich, BY, Germany
| | - Kelli Lehto
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Qingqin S Li
- Neuroscience Therapeutic Area, Janssen Research and Development, LLC, Titusville, NJ, USA
| | - Enda M Byrne
- Child Health Research Centre, University of Queensland, Brisbane, QLD, Australia
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | - Nicholas G Martin
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Sarah E Medland
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Naomi R Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - Elliot M Tucker-Drob
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
- Population Research Center, University of Texas at Austin, Austin, TX, USA
| | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
- Department of Medical & Molecular Genetics, King's College London, London, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
- Institute for Genomics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Eske M Derks
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| |
Collapse
|
12
|
Solmi M, Miola A, Capone F, Pallottino S, Højlund M, Firth J, Siskind D, Holt RIG, Corbeil O, Cortese S, Dragioti E, Du Rietz E, Nielsen RE, Nordentoft M, Fusar-Poli P, Hartman CA, Høye A, Koyanagi A, Larsson H, Lehto K, Lindgren P, Manchia M, Skonieczna-Żydecka K, Stubbs B, Vancampfort D, Vieta E, Taipale H, Correll CU. Risk factors, prevention and treatment of weight gain associated with the use of antidepressants and antipsychotics: a state-of-the-art clinical review. Expert Opin Drug Saf 2024:1-21. [PMID: 39225182 DOI: 10.1080/14740338.2024.2396396] [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: 01/05/2023] [Revised: 06/12/2024] [Accepted: 08/14/2024] [Indexed: 09/04/2024]
Abstract
INTRODUCTION People with severe mental illness have poor cardiometabolic health. Commonly used antidepressants and antipsychotics frequently lead to weight gain, which may further contribute to adverse cardiovascular outcomes. AREAS COVERED We searched MEDLINE up to April 2023 for umbrella reviews, (network-)meta-analyses, trials and cohort studies on risk factors, prevention and treatment strategies of weight gain associated with antidepressants/antipsychotics. We developed 10 clinical recommendations. EXPERT OPINION To prevent, manage, and treat antidepressant/antipsychotic-related weight gain, we recommend i) assessing risk factors for obesity before treatment, ii) monitoring metabolic health at baseline and regularly during follow-up, iii) offering lifestyle interventions including regular exercise and healthy diet based on patient preference to optimize motivation, iv) considering first-line psychotherapy for mild-moderate depression and anxiety disorders, v)choosing medications based on medications' and patient's weight gain risk, vi) choosing medications based on acute vs long-term treatment, vii) using effective, tolerated medications, viii) switching to less weight-inducing antipsychotics/antidepressants where possible, ix) using early weight gain as a predictor of further weight gain to inform the timing of intervention/switch options, and x) considering adding metformin or glucagon-like peptide-1 receptor agonists, or topiramate(second-line due to potential adverse cognitive effects) to antipsychotics, or aripiprazole to clozapine or olanzapine.
Collapse
Affiliation(s)
- Marco Solmi
- Department of Psychiatry, University of Ottawa, Ottawa, Ontario, Canada
- Department of Mental Health, The Ottawa Hospital, Ottawa, Ontario, Canada
- Ottawa Hospital Research Institute (OHRI) Clinical Epidemiology Program, University of Ottawa, Ottawa, Ontario, Canada
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
| | | | - Federico Capone
- Department of Medicine (DIMED), Unit of Internal Medicine III, Padua University Hospital, University of Padua, Padova, Italy
- Department of Biomedical Sciences, University of Padova, Padova, Italy
| | | | - Mikkel Højlund
- Department of Psychiatry Aabenraa, Mental Health Services in the Region of Southern Denmark, Aabenraa, Denmark
- Clinical Pharmacology, Pharmacy, and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Joseph Firth
- Division of Psychology and Mental Health, University of Manchester, Manchester, UK
- Greater Manchester Mental Health NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Dan Siskind
- Metro South Addiction and Mental Health Service, Princess Alexandra Hospital, Brisbane, Qld, Australia
- Physical and Mental Health Research Stream, Queensland Centre for Mental Health Research, School of Clinical Medicine, Brisbane, Qld, Australia
| | - Richard I G Holt
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK
- Southampton National Institute for Health Research Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Olivier Corbeil
- Faculty of Pharmacy, Université Laval, Québec, Canada
- Department of Pharmacy, Quebec Mental Health University Institute, Québec, Canada
| | - Samuele Cortese
- Developmental EPI (Evidence synthesis, Prediction, Implementation) lab, Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK
- Child and Adolescent Mental Health Service, Solent NHS Trust, Southampton, UK
- Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, Southampton, UK
- Hassenfeld Children's Hospital at NYU Langone, New York University Child Study Center, New York, NY, USA
- DiMePRe-J-Department of Precision and Regenerative Medicine-Jonic Area, University of Bari 'Aldo Moro', Bari, Italy
| | - Elena Dragioti
- Pain and Rehabilitation Centre, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Research Laboratory Psychology of Patients, Families & Health Professionals, Department of Nursing, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | - Ebba Du Rietz
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - René Ernst Nielsen
- Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
- Department of Psychiatry, Aalborg University Hospital, Aalborg, Denmark
| | - Merete Nordentoft
- Mental Health Centre Copenhagen, Department of Clinical Medicine, Copenhagen University Hospital, Glostrup, Denmark
| | - Paolo Fusar-Poli
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Early Psychosis: Interventions and Clinical-Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Outreach and Support in South-London (OASIS) service, South London and Maudlsey (SLaM) NHS Foundation Trust, London, UK
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian-University (LMU), Munich, Germany
| | - Catharina A Hartman
- Interdisciplinary Centre Psychopathology and Emotion regulation, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Anne Høye
- Department of Clinical Medicine, UiT The Arctic University of Norway, Tromsø, Norway
- Department of Mental Health and Substance Abuse, University Hospital of North Norway, Tromsø, Norway
| | - Ai Koyanagi
- Research and Development Unit, Parc Sanitari Sant Joan de Déu, Barcelona, Spain
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Kelli Lehto
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Peter Lindgren
- Department of Learning, Informatics, Management and Ethics, Karolinska Institutet, Stockholm, Sweden
- The Swedish Institute for Health Economics, Lund, Sweden
| | - Mirko Manchia
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
- Department of Pharmacology, Dalhousie University, Halifax, Nova Scotia, Canada
| | | | - Brendon Stubbs
- Physiotherapy Department, South London and Maudsley NHS Foundation Trust, London, UK
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
| | - Davy Vancampfort
- Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium
- University Psychiatric Centre KU Leuven, Leuven, Belgium
| | - Eduard Vieta
- Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia, Spain
| | - Heidi Taipale
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Center for Psychiatry Research, Stockholm City Council, Stockholm, Sweden
- Department of Forensic Psychiatry, University of Eastern Finland, Niuvanniemi Hospital, Kuopio, Finland
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Christoph U Correll
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
- Department of Psychiatry, Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
- Department of Psychiatry and Molecular Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| |
Collapse
|
13
|
Luo X, Ruan Z, Liu L. The association between overweight and varying degrees of obesity with subjective well-being and depressive symptoms: A two sample Mendelian randomization study. J Psychosom Res 2024; 187:111940. [PMID: 39317092 DOI: 10.1016/j.jpsychores.2024.111940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 08/25/2024] [Accepted: 09/18/2024] [Indexed: 09/26/2024]
Abstract
OBJECTIVE This study utilized the Mendelian randomization (MR) method to elucidate the causal relationship between genetically predicted overweight and various degrees of obesity with depressive symptoms and subjective well-being (SWB). METHODS Pooled genome-wide association studies (GWAS) data for overweight (BMI ≥ 25 kg/m2), class 1 obesity (BMI ≥ 30 kg/m2), and class 2 obesity (BMI ≥ 35 kg/m2) were used as exposures. Summary GWAS data for depressive symptoms and SWB were used as outcomes. Multiple MR methods, primarily inverse-variance weighted (IVW), were applied, and sensitivity analyses were conducted to assess heterogeneity and pleiotropy. RESULTS The MR analysis provided evidence that genetically predicted overweight(IVW β = 0.033; 95 %CI 0.008-0.057; P = 0.010) and class 1 obesity(IVW β = -0.033; 95 %CI -0.047 - -0.020; P < 0.001) were causally associated with increased depressive symptoms. Genetically predicted class 2 obesity(IVW β = 1.428; 95 %CI 1.193-1.710; P < 0.001) were associated with reduced SWB. There was no strong evidence of a causal association between genetically predicted overweight and class 1 obesity with SWB. Similarly, genetically predicted class 2 and class 3 obesity did not show strong evidence of a causal association with depressive symptoms. Sensitivity analysis revealed relationships of a similar magnitude. CONCLUSION This genetically informed MR study suggests that Overweight and class 1 obesity may causally increased depressive symptoms but not decrease SWB. In contrast, class 2 obesity may causally decrease SWB but not increase depressive symptoms.
Collapse
Affiliation(s)
- Xinxin Luo
- Department of Pharmacy, Jiangxi Provincial People's Hospital & The First Affiliated Hospital of Nanchang Medical College, Nanchang, China
| | - Zhichao Ruan
- First School of Clinical Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Ling Liu
- Department of Pharmacy, Jiangxi Provincial People's Hospital & The First Affiliated Hospital of Nanchang Medical College, Nanchang, China.
| |
Collapse
|
14
|
Flowers E, Stroebel B, Lewis KA, Aouizerat BE, Gadgil M, Kanaya AM, Zhang L, Gong X. Longitudinal associations between microRNAs and weight in the diabetes prevention program. Front Endocrinol (Lausanne) 2024; 15:1419812. [PMID: 39359416 PMCID: PMC11445047 DOI: 10.3389/fendo.2024.1419812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Accepted: 08/26/2024] [Indexed: 10/04/2024] Open
Abstract
Objective Circulating microRNAs show cross-sectional associations with overweight and obesity. Few studies provided data to differentiate between a snapshot perspective on these associations versus how microRNAs characterize prodromal risk from disease pathology and complications. This study assessed longitudinal relationships between circulating microRNAs and weight at multiple time-points in the Diabetes Prevention Program trial. Research design and methods A subset of participants (n=150) from the Diabetes Prevention Program were included. MicroRNAs were measured from banked plasma using a Fireplex Assay. We used generalized linear mixed models to evaluate relationships between microRNAs and changes in weight at baseline, year-1, and year-2. Logistic regression was used to evaluate whether microRNAs at baseline were associated with weight change after 2 years. Results In fully adjusted models that included relevant covariates, seven miRs (i.e., miR-126, miR-15a, miR-192, miR-23a, and miR-27a) were statistically associated with weight over 2 years. MiR-197 and miR-320a remained significant after adjustment for multiple comparisons. Baseline levels of let-7f, miR-17, and miR-320c were significantly associated with 3% weight loss after 2 years in fully adjusted models. Discussion This study provided evidence for longitudinal relationships between circulating microRNAs and weight. Because microRNAs characterize the combined effects of genetic determinants and responses to behavioral determinants, they may provide insights about the etiology of overweight and obesity in the context or risk for common, complex diseases. Additional studies are needed to validate the potential genes and biological pathways that might be targeted by these microRNA biomarkers and have mechanistic implications for weight loss and disease prevention.
Collapse
Affiliation(s)
- Elena Flowers
- Department of Physiological Nursing, University of California, San Francisco, San Francisco, CA, United States
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, United States
| | - Benjamin Stroebel
- Department of Physiological Nursing, University of California, San Francisco, San Francisco, CA, United States
| | - Kimberly A. Lewis
- Department of Physiological Nursing, University of California, San Francisco, San Francisco, CA, United States
| | - Bradley E. Aouizerat
- Bluestone Center for Clinical Research, New York University, New York, NY, United States
- Department of Oral and Maxillofacial Surgery, New York University, New York, NY, United States
| | - Meghana Gadgil
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Alka M. Kanaya
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, United States
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States
| | - Li Zhang
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States
- Division of Hematology and Oncology, Department of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Xingyue Gong
- Department of Physiological Nursing, University of California, San Francisco, San Francisco, CA, United States
| |
Collapse
|
15
|
Wolford BN, Åsvold BO. Bidirectional Mendelian Randomization to Elucidate the Relationship Between Healthy Sleep, Brains, and Hearts. J Am Heart Assoc 2024; 13:e037394. [PMID: 39258560 DOI: 10.1161/jaha.124.037394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2024] [Accepted: 08/12/2024] [Indexed: 09/12/2024]
Affiliation(s)
- Brooke N Wolford
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing Norwegian University of Science and Technology Trondheim Norway
| | - Bjørn O Åsvold
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing Norwegian University of Science and Technology Trondheim Norway
- Department of Endocrinology, Clinic of Medicine, St. Olav's Hospital Trondheim University Hospital Trondheim Norway
| |
Collapse
|
16
|
Cavaillès C, Andrews SJ, Leng Y, Chatterjee A, Daghlas I, Yaffe K. Causal Associations of Sleep Apnea With Alzheimer Disease and Cardiovascular Disease: A Bidirectional Mendelian Randomization Analysis. J Am Heart Assoc 2024; 13:e033850. [PMID: 39258525 DOI: 10.1161/jaha.123.033850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 06/26/2024] [Indexed: 09/12/2024]
Abstract
BACKGROUND Sleep apnea (SA) has been linked to an increased risk of dementia in numerous observational studies; whether this is driven by neurodegenerative, vascular, or other mechanisms is not clear. We sought to examine the bidirectional causal relationships between SA, Alzheimer disease (AD), coronary artery disease (CAD), and ischemic stroke using Mendelian randomization. METHODS AND RESULTS Using summary statistics from 4 recent, large genome-wide association studies of SA (n=523 366), AD (n=94 437), CAD (n=1 165 690), and stroke (n=1 308 460), we conducted bidirectional 2-sample Mendelian randomization analyses. Our primary analytic method was fixed-effects inverse variance-weighted (IVW) Mendelian randomization; diagnostics tests and sensitivity analyses were conducted to verify the robustness of the results. We identified a significant causal effect of SA on the risk of CAD (odds ratio [ORIVW]=1.35 per log-odds increase in SA liability [95% CI=1.25-1.47]) and stroke (ORIVW=1.13 [95% CI=1.01-1.25]). These associations were somewhat attenuated after excluding single-nucleotide polymorphisms associated with body mass index (ORIVW=1.26 [95% CI=1.15-1.39] for CAD risk; ORIVW=1.08 [95% CI=0.96-1.22] for stroke risk). SA was not causally associated with a higher risk of AD (ORIVW=1.14 [95% CI=0.91-1.43]). We did not find causal effects of AD, CAD, or stroke on risk of SA. CONCLUSIONS These results suggest that SA increased the risk of CAD, and the identified causal association with stroke risk may be confounded by body mass index. Moreover, no causal effect of SA on AD risk was found. Future studies are warranted to investigate cardiovascular pathways between sleep disorders, including SA, and dementia.
Collapse
Affiliation(s)
- Clémence Cavaillès
- Department of Psychiatry and Behavioral Sciences University of California San Francisco San Francisco CA
| | - Shea J Andrews
- Department of Psychiatry and Behavioral Sciences University of California San Francisco San Francisco CA
| | - Yue Leng
- Department of Psychiatry and Behavioral Sciences University of California San Francisco San Francisco CA
| | | | - Iyas Daghlas
- Department of Neurology University of California San Francisco San Francisco CA
| | - Kristine Yaffe
- Department of Psychiatry and Behavioral Sciences University of California San Francisco San Francisco CA
- San Francisco Veterans Affairs Health Care System San Francisco CA
- Department of Neurology University of California San Francisco San Francisco CA
- Department of Epidemiology University of California San Francisco San Francisco CA
| |
Collapse
|
17
|
Xiao P, Li C, Mi J, Wu J. Evaluating the distinct effects of body mass index at childhood and adulthood on adult major psychiatric disorders. SCIENCE ADVANCES 2024; 10:eadq2452. [PMID: 39270013 PMCID: PMC11397431 DOI: 10.1126/sciadv.adq2452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2024] [Accepted: 08/06/2024] [Indexed: 09/15/2024]
Abstract
Children with high body mass index (BMI) are at heightened risk of developing health issues in adulthood, yet the causality between childhood BMI and adult psychiatric disorders remains unclear. Using a life course Mendelian randomization (MR) framework, we investigated the causal effects of childhood and adulthood BMI on adult psychiatric disorders, including Alzheimer's disease, anxiety, major depressive disorder, obsessive-compulsive disorder (OCD), and schizophrenia, using data from the Psychiatric Genomics Consortium and FinnGen study. Childhood BMI was significantly associated with an increased risk of schizophrenia, while adulthood BMI was associated with a decreased risk of OCD and schizophrenia. Multivariable MR analyses indicated a direct causal effect of childhood BMI on schizophrenia, independent of adulthood BMI and lifestyle factors. No evidence of causal associations was found between childhood BMI and other psychiatric outcomes. The sensitivity analyses yielded broadly consistent findings. These findings highlight the critical importance of early-life interventions to mitigate the long-term consequences of childhood adiposity.
Collapse
Affiliation(s)
- Pei Xiao
- Center for Non-communicable Disease Management, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Chi Li
- Department of AIDS/STD Control and Prevention, Shijingshan District Center for Disease Control and Prevention, Beijing 100043, China
| | - Jie Mi
- Center for Non-communicable Disease Management, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Jinyi Wu
- Department of Public Health, Wuhan Fourth Hospital, Wuhan 430000, China
- School of Public Health, Fudan University, Shanghai 210000, China
| |
Collapse
|
18
|
Zhang W, Lan F, Zhou Q, Gu S, Li X, Wen C, Yang N, Sun C. Host genetics and gut microbiota synergistically regulate feed utilization in egg-type chickens. J Anim Sci Biotechnol 2024; 15:123. [PMID: 39245742 PMCID: PMC11382517 DOI: 10.1186/s40104-024-01076-7] [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: 04/03/2024] [Accepted: 07/14/2024] [Indexed: 09/10/2024] Open
Abstract
BACKGROUND Feed efficiency is a crucial economic trait in poultry industry. Both host genetics and gut microbiota influence feed efficiency. However, the associations between gut microbiota and host genetics, as well as their combined contributions to feed efficiency in laying hens during the late laying period, remain largely unclear. METHODS In total, 686 laying hens were used for whole-genome resequencing and liver transcriptome sequencing. 16S rRNA gene sequencing was conducted on gut chyme (duodenum, jejunum, ileum, and cecum) and fecal samples from 705 individuals. Bioinformatic analysis was performed by integrating the genome, transcriptome, and microbiome to screen for key genetic variations, genes, and gut microbiota associated with feed efficiency. RESULTS The heritability of feed conversion ratio (FCR) and residual feed intake (RFI) was determined to be 0.28 and 0.48, respectively. The ileal and fecal microbiota accounted for 15% and 10% of the FCR variance, while the jejunal, cecal, and fecal microbiota accounted for 20%, 11%, and 10% of the RFI variance. Through SMR analysis based on summary data from liver eQTL mapping and GWAS, we further identified four protein-coding genes, SUCLA2, TNFSF13B, SERTM1, and MARVELD3, that influence feed efficiency in laying hens. The SUCLA2 and TNFSF13B genes were significantly associated with SNP 1:25664581 and SNP rs312433097, respectively. SERTM1 showed significant associations with rs730958360 and 1:33542680 and is a potential causal gene associated with the abundance of Corynebacteriaceae in feces. MARVELD3 was significantly associated with the 1:135348198 and was significantly correlated with the abundance of Enterococcus in ileum. Specifically, a lower abundance of Enterococcus in ileum and a higher abundance of Corynebacteriaceae in feces were associated with better feed efficiency. CONCLUSIONS This study confirms that both host genetics and gut microbiota can drive variations in feed efficiency. A small portion of the gut microbiota often interacts with host genes, collectively enhancing feed efficiency. Therefore, targeting both the gut microbiota and host genetic variation by supporting more efficient taxa and selective breeding could improve feed efficiency in laying hens during the late laying period.
Collapse
Affiliation(s)
- Wenxin Zhang
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China
| | - Fangren Lan
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China
| | - Qianqian Zhou
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China
| | - Shuang Gu
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China
| | - Xiaochang Li
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China
| | - Chaoliang Wen
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China
| | - Ning Yang
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China
| | - Congjiao Sun
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China.
| |
Collapse
|
19
|
Wang Y, Bi Y, Wang Y, Ji F, Zhang L. Genetic estimation of causalities between educational attainment with common digestive tract diseases and the mediating pathways. BMC Gastroenterol 2024; 24:304. [PMID: 39251923 PMCID: PMC11386375 DOI: 10.1186/s12876-024-03400-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Accepted: 09/03/2024] [Indexed: 09/11/2024] Open
Abstract
BACKGROUND The association between education, intelligence, and cognition with digestive tract diseases has been established. However, the specific contribution of each factor in the pathogenesis of these diseases are still uncertain. METHOD This study employed multivariable Mendelian randomization (MR) to assess the independent effects of education, intelligence, and cognition on gastrointestinal conditions in the FinnGen and UK Biobank European-ancestry populations. A two-step MR approach was employed to assess the mediating effects of the association. RESULTS Meta-analysis of MR estimates from FinnGen and UK Biobank showed that 1- SD (4.2 years) higher education was causally associated with lower risks of gastroesophageal reflux (OR: 0.58; 95% CI: 0.50, 0.66), peptic ulcer (OR: 0.57; 95% CI: 0.47, 0.69), irritable bowel syndrome (OR: 0.70; 95% CI: 0.56, 0.87), diverticular disease (OR: 0.69; 95% CI: 0.61, 0.78), cholelithiasis (OR: 0.68; 95% CI: 0.59, 0.79) and acute pancreatitis (OR: 0.54; 95% CI: 0.41, 0.72), independently of intelligence and cognition. These causal associations were mediating by body mass index (3.7-22.3%), waist-to-hip ratio (8.3-11.9%), body fat percentage (4.1-39.8%), fasting insulin (1.4-5.5%) and major depression (6.0-12.4%). CONCLUSION Our findings demonstrate a causal and independent association between education and six common digestive tract diseases. Additionally, our study highlights five mediators as crucial targets for preventing digestive tract diseases associated with lower education levels.
Collapse
Affiliation(s)
- Yudan Wang
- Department of Traditional Chinese medicine, Xi'an NO.3 Hospital, the Affiliated Hospital of Northwest University, 710018, Xi'an, Shaanxi, P.R. China
- Department of Life Sciences and Medicine, Northwest University, 710069, Xi'an, Shaanxi, P.R. China
| | - Yanping Bi
- Department of Radiation Oncology, the Affiliated Hospital of Northwest University, Xi'an No.3 Hospital, 710018, Xi'an, Shaanxi, China
| | - Yilin Wang
- Department of Clinical Medicine, Medical College, Northwest University, 710018, Xi'an, Shaanxi, P.R. China
| | - Fuqing Ji
- Xi'an NO.3 Hospital, The Affiliated Hospital of Northwest University, 710018, Xi'an, Shaanxi, P.R. China
| | - Lanhui Zhang
- Department of Traditional Chinese medicine, Xi'an NO.3 Hospital, the Affiliated Hospital of Northwest University, 710018, Xi'an, Shaanxi, P.R. China.
| |
Collapse
|
20
|
Lin B, Pan L, He H, Hu Y, Tu J, Zhang L, Cui Z, Ren X, Wang X, Nai J, Shan G. Heritability and genetic correlations of obesity indices and cardiometabolic traits in the Northern Chinese families. Ann Hum Genet 2024. [PMID: 39239922 DOI: 10.1111/ahg.12578] [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: 05/23/2024] [Revised: 08/11/2024] [Accepted: 08/21/2024] [Indexed: 09/07/2024]
Abstract
OBJECTIVE This study aimed to investigate the heritability of various obesity indices and their shared genetic factors with cardiometabolic traits in the Chinese nuclear family. METHODS A total of 1270 individuals from 538 nuclear families were included in this cross-sectional study. Different indices were used to quantify fat mass and distribution, including body index mass (BMI), visceral fat index (VFI), and body fat percent (BFP). Heritability and genetic correlations for all quantitative traits were estimated using variance component models. The susceptibility-threshold model was utilized to estimate the heritability for binary traits. RESULTS Heritability estimates for obesity indices were highest for BMI (59%), followed by BFP (49%), and VFI (40%). Heritability estimates for continuous cardiometabolic traits varied from 24% to 50%. All obesity measures exhibited consistently significant positive genetic correlations with blood pressure, fasting blood glucose, and uric acid (rG range: 0.26-0.57). However, diverse genetic correlations between various obesity indices and lipid profiles were observed. Significant genetic correlations were limited to specific pairs: BFP and total cholesterol (rG = 0.24), BFP and low-density lipoprotein cholesterol (rG = 0.25), and VFI and triglyceride (rG = 0.33). CONCLUSION The genetic overlap between various obesity indices and cardiometabolic traits underscores the importance of pleiotropic genes. Further studies are warranted to investigate specific shared genetic and environmental factors between obesity and cardiometabolic diseases.
Collapse
Affiliation(s)
- Binbin Lin
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, China
- State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
| | - Li Pan
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, China
- State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
| | - Huijing He
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, China
- State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
| | - Yaoda Hu
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, China
- State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
| | - Ji Tu
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, China
- State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
| | - Ling Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Ze Cui
- Department of Chronic and Noncommunicable Disease Prevention and Control, Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hebei, China
| | - Xiaolan Ren
- Department of Chronic and Noncommunicable Disease Prevention and Control, Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China
| | - Xianghua Wang
- Institute of Biomedical Engineering, Chinese Academy of Medical Sciences, Tianjin, China
| | - Jing Nai
- Clinical Laboratory, Beijing Hepingli Hospital, Beijing, China
| | - Guangliang Shan
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, China
- State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| |
Collapse
|
21
|
Wachowski NA, Pippin JA, Boehm K, Lu S, Leonard ME, Manduchi E, Parlin UW, Wabitsch M, Chesi A, Wells AD, Grant SFA, Pahl MC. Implicating type 2 diabetes effector genes in relevant metabolic cellular models using promoter-focused Capture-C. Diabetologia 2024:10.1007/s00125-024-06261-x. [PMID: 39240351 DOI: 10.1007/s00125-024-06261-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Accepted: 07/04/2024] [Indexed: 09/07/2024]
Abstract
AIMS/HYPOTHESIS Genome-wide association studies (GWAS) have identified hundreds of type 2 diabetes loci, with the vast majority of signals located in non-coding regions; as a consequence, it remains largely unclear which 'effector' genes these variants influence. Determining these effector genes has been hampered by the relatively challenging cellular settings in which they are hypothesised to confer their effects. METHODS To implicate such effector genes, we elected to generate and integrate high-resolution promoter-focused Capture-C, assay for transposase-accessible chromatin with sequencing (ATAC-seq) and RNA-seq datasets to characterise chromatin and expression profiles in multiple cell lines relevant to type 2 diabetes for subsequent functional follow-up analyses: EndoC-BH1 (pancreatic beta cell), HepG2 (hepatocyte) and Simpson-Golabi-Behmel syndrome (SGBS; adipocyte). RESULTS The subsequent variant-to-gene analysis implicated 810 candidate effector genes at 370 type 2 diabetes risk loci. Using partitioned linkage disequilibrium score regression, we observed enrichment for type 2 diabetes and fasting glucose GWAS loci in promoter-connected putative cis-regulatory elements in EndoC-BH1 cells as well as fasting insulin GWAS loci in SGBS cells. Moreover, as a proof of principle, when we knocked down expression of the SMCO4 gene in EndoC-BH1 cells, we observed a statistically significant increase in insulin secretion. CONCLUSIONS/INTERPRETATION These results provide a resource for comparing tissue-specific data in tractable cellular models as opposed to relatively challenging primary cell settings. DATA AVAILABILITY Raw and processed next-generation sequencing data for EndoC-BH1, HepG2, SGBS_undiff and SGBS_diff cells are deposited in GEO under the Superseries accession GSE262484. Promoter-focused Capture-C data are deposited under accession GSE262496. Hi-C data are deposited under accession GSE262481. Bulk ATAC-seq data are deposited under accession GSE262479. Bulk RNA-seq data are deposited under accession GSE262480.
Collapse
Affiliation(s)
- Nicholas A Wachowski
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - James A Pippin
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Keith Boehm
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Sumei Lu
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Michelle E Leonard
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Elisabetta Manduchi
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ursula W Parlin
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Martin Wabitsch
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics and Adolescent Medicine, University Medical Center Ulm, Ulm, Germany
| | - Alessandra Chesi
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew D Wells
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Struan F A Grant
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Division of Diabetes and Endocrinology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
| | - Matthew C Pahl
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| |
Collapse
|
22
|
Saeed S, Bonnefond A, Froguel P. Obesity: exploring its connection to brain function through genetic and genomic perspectives. Mol Psychiatry 2024:10.1038/s41380-024-02737-9. [PMID: 39237720 DOI: 10.1038/s41380-024-02737-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 08/27/2024] [Accepted: 08/29/2024] [Indexed: 09/07/2024]
Abstract
Obesity represents an escalating global health burden with profound medical and economic impacts. The conventional perspective on obesity revolves around its classification as a "pure" metabolic disorder, marked by an imbalance between calorie consumption and energy expenditure. Present knowledge, however, recognizes the intricate interaction of rare or frequent genetic factors that favor the development of obesity, together with the emergence of neurodevelopmental and mental abnormalities, phenotypes that are modulated by environmental factors such as lifestyle. Thirty years of human genetic research has unveiled >20 genes, causing severe early-onset monogenic obesity and ~1000 loci associated with common polygenic obesity, most of those expressed in the brain, depicting obesity as a neurological and mental condition. Therefore, obesity's association with brain function should be better recognized. In this context, this review seeks to broaden the current perspective by elucidating the genetic determinants that contribute to both obesity and neurodevelopmental and mental dysfunctions. We conduct a detailed examination of recent genetic findings, correlating them with clinical and behavioral phenotypes associated with obesity. This includes how polygenic obesity, influenced by a myriad of genetic variants, impacts brain regions associated with addiction and reward, differentiating it from monogenic forms. The continuum between non-syndromic and syndromic monogenic obesity, with evidence from neurodevelopmental and cognitive assessments, is also addressed. Current therapeutic approaches that target these genetic mechanisms, yielding improved clinical outcomes and cognitive advantages, are discussed. To sum up, this review corroborates the genetic underpinnings of obesity, affirming its classification as a neurological disorder that may have broader implications for neurodevelopmental and mental conditions. It highlights the promising intersection of genetics, genomics, and neurobiology as a foundation for developing tailored medical approaches to treat obesity and its related neurological aspects.
Collapse
Affiliation(s)
- Sadia Saeed
- INSERM UMR 1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Lille, France
- University of Lille, Lille University Hospital, Lille, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Amélie Bonnefond
- INSERM UMR 1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Lille, France
- University of Lille, Lille University Hospital, Lille, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Philippe Froguel
- INSERM UMR 1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Lille, France.
- University of Lille, Lille University Hospital, Lille, France.
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.
| |
Collapse
|
23
|
Broadaway KA, Brotman SM, Rosen JD, Currin KW, Alkhawaja AA, Etheridge AS, Wright F, Gallins P, Jima D, Zhou YH, Love MI, Innocenti F, Mohlke KL. Liver eQTL meta-analysis illuminates potential molecular mechanisms of cardiometabolic traits. Am J Hum Genet 2024; 111:1899-1913. [PMID: 39173627 PMCID: PMC11393674 DOI: 10.1016/j.ajhg.2024.07.017] [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] [Received: 01/04/2024] [Revised: 07/24/2024] [Accepted: 07/25/2024] [Indexed: 08/24/2024] Open
Abstract
Understanding the molecular mechanisms of complex traits is essential for developing targeted interventions. We analyzed liver expression quantitative-trait locus (eQTL) meta-analysis data on 1,183 participants to identify conditionally distinct signals. We found 9,013 eQTL signals for 6,564 genes; 23% of eGenes had two signals, and 6% had three or more signals. We then integrated the eQTL results with data from 29 cardiometabolic genome-wide association study (GWAS) traits and identified 1,582 GWAS-eQTL colocalizations for 747 eGenes. Non-primary eQTL signals accounted for 17% of all colocalizations. Isolating signals by conditional analysis prior to coloc resulted in 37% more colocalizations than using marginal eQTL and GWAS data, highlighting the importance of signal isolation. Isolating signals also led to stronger evidence of colocalization: among 343 eQTL-GWAS signal pairs in multi-signal regions, analyses that isolated the signals of interest resulted in higher posterior probability of colocalization for 41% of tests. Leveraging allelic heterogeneity, we predicted causal effects of gene expression on liver traits for four genes. To predict functional variants and regulatory elements, we colocalized eQTL with liver chromatin accessibility QTL (caQTL) and found 391 colocalizations, including 73 with non-primary eQTL signals and 60 eQTL signals that colocalized with both a caQTL and a GWAS signal. Finally, we used publicly available massively parallel reporter assays in HepG2 to highlight 14 eQTL signals that include at least one expression-modulating variant. This multi-faceted approach to unraveling the genetic underpinnings of liver-related traits could lead to therapeutic development.
Collapse
Affiliation(s)
- K Alaine Broadaway
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Sarah M Brotman
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Jonathan D Rosen
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Kevin W Currin
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Abdalla A Alkhawaja
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Amy S Etheridge
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Fred Wright
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA; Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA; Department of Statistics, North Carolina State University, Raleigh, NC 27695, USA
| | - Paul Gallins
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA
| | - Dereje Jima
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA
| | - Yi-Hui Zhou
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA; Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA
| | - Michael I Love
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Federico Innocenti
- Eshelman School of Pharmacy, Division of Pharmacotherapy and Experimental Therapeutics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
| |
Collapse
|
24
|
Li WD, Zhang X, Yu K, Zhu Y, Du N, Song Z, Fan Q. A genome-wide association study of occupational creativity and its relations with well-being and career success. Commun Biol 2024; 7:1092. [PMID: 39237691 PMCID: PMC11377709 DOI: 10.1038/s42003-024-06686-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 08/06/2024] [Indexed: 09/07/2024] Open
Abstract
Creativity is one defining characteristic of human species. There have been mixed findings on how creativity relates to well-being, and little is known about its relationship with career success. We conduct a large-scale genome-wide association study to examine the genetic architecture of occupational creativity, and its genetic correlations with well-being and career success. The SNP-h2 estimates range from 0.08 (for managerial creativity) to 0.22 (for artistic creativity). We record positive genetic correlations between occupational creativity with autism, and positive traits and well-being variables (e.g., physical height, and low levels of neuroticism, BMI, and non-cancer illness). While creativity share positive genetic overlaps with indicators of high career success (i.e., income, occupational status, and job satisfaction), it also has a positive genetic correlation with age at first birth and a negative genetic correlation with number of children, indicating creativity-related genes may reduce reproductive success.
Collapse
Affiliation(s)
- Wen-Dong Li
- Department of Management, CUHK Business School, The Chinese University of Hong Kong, Hong Kong, China.
| | - Xin Zhang
- Department of Human Resource Management, School of Business, Shanghai University of Finance and Economics, Shanghai, China.
| | - Kaili Yu
- Department of Management, CUHK Business School, The Chinese University of Hong Kong, Hong Kong, China
| | - Yimo Zhu
- Department of Management and Organization, National University of Singapore, Singapore, Singapore
| | - Nianyao Du
- Department of Statistics and Data Science, National University of Singapore, Singapore, Singapore
| | - Zhaoli Song
- Department of Management and Organization, National University of Singapore, Singapore, Singapore.
| | - Qiao Fan
- Centre for Quantitative Medicine, Duke-NUS Medical School, National University of Singapore, Singapore, Singapore.
| |
Collapse
|
25
|
Tume CE, Chick SL, Holmans PA, Rees E, O’Donovan MC, Cameron D, Bray NJ. Genetic Implication of Specific Glutamatergic Neurons of the Prefrontal Cortex in the Pathophysiology of Schizophrenia. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:100345. [PMID: 39099730 PMCID: PMC11295574 DOI: 10.1016/j.bpsgos.2024.100345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Revised: 05/03/2024] [Accepted: 05/19/2024] [Indexed: 08/06/2024] Open
Abstract
Background The prefrontal cortex (PFC) has been strongly implicated in the pathophysiology of schizophrenia. Here, we combined high-resolution single-nuclei RNA sequencing data from the human PFC with large-scale genomic data for schizophrenia to identify constituent cell populations likely to mediate genetic liability to the disorder. Methods Gene expression specificity values were calculated from a single-nuclei RNA sequencing dataset comprising 84 cell populations from the human PFC, spanning gestation to adulthood. Enrichment of schizophrenia common variant liability and burden of rare protein-truncating coding variants were tested in genes with high expression specificity for each cell type. We also explored schizophrenia common variant associations in relation to gene expression across the developmental trajectory of implicated neurons. Results Common risk variation for schizophrenia was prominently enriched in genes with high expression specificity for a population of mature layer 4 glutamatergic neurons emerging in infancy. Common variant liability to schizophrenia increased along the developmental trajectory of this neuronal population. Fine-mapped genes at schizophrenia genome-wide association study risk loci had significantly higher expression specificity than other genes in these neurons and in a population of layer 5/6 glutamatergic neurons. People with schizophrenia had a higher rate of rare protein-truncating coding variants in genes expressed by cells of the PFC than control individuals, but no cell population was significantly enriched above this background rate. Conclusions We identified a population of layer 4 glutamatergic PFC neurons likely to be particularly affected by common variant genetic risk for schizophrenia, which may contribute to disturbances in thalamocortical connectivity in the condition.
Collapse
Affiliation(s)
- Claire E. Tume
- Centre for Neuropsychiatric Genetics & Genomics, Division of Psychological Medicine & Clinical Neurosciences, Cardiff University, Cardiff, Wales, United Kingdom
| | - Sophie L. Chick
- Centre for Neuropsychiatric Genetics & Genomics, Division of Psychological Medicine & Clinical Neurosciences, Cardiff University, Cardiff, Wales, United Kingdom
| | - Peter A. Holmans
- Centre for Neuropsychiatric Genetics & Genomics, Division of Psychological Medicine & Clinical Neurosciences, Cardiff University, Cardiff, Wales, United Kingdom
| | - Elliott Rees
- Centre for Neuropsychiatric Genetics & Genomics, Division of Psychological Medicine & Clinical Neurosciences, Cardiff University, Cardiff, Wales, United Kingdom
| | - Michael C. O’Donovan
- Centre for Neuropsychiatric Genetics & Genomics, Division of Psychological Medicine & Clinical Neurosciences, Cardiff University, Cardiff, Wales, United Kingdom
| | - Darren Cameron
- Centre for Neuropsychiatric Genetics & Genomics, Division of Psychological Medicine & Clinical Neurosciences, Cardiff University, Cardiff, Wales, United Kingdom
| | - Nicholas J. Bray
- Centre for Neuropsychiatric Genetics & Genomics, Division of Psychological Medicine & Clinical Neurosciences, Cardiff University, Cardiff, Wales, United Kingdom
- Neuroscience & Mental Health Innovation Institute, Cardiff University, Cardiff, Wales, United Kingdom
| |
Collapse
|
26
|
Fu H, Song S, Du B, Zhou T, Cai M, Jiang S, Chen Y, Zang X, Huang Y, Wang W, Xie Q. Causal effects of female reproductive features on nonalcoholic fatty liver disease: A mendelian randomization study. J Gene Med 2024; 26:e3738. [PMID: 39245705 DOI: 10.1002/jgm.3738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 08/08/2024] [Accepted: 08/31/2024] [Indexed: 09/10/2024] Open
Abstract
BACKGROUND AND AIMS Epidemiological evidence on the associations between female reproductive features and nonalcoholic fatty liver disease (NAFLD) is conflicting. To explore their causalities, we conducted a Mendelian randomization (MR) study. METHODS Summary-level data were obtained, and univariable MR was performed to explore the causalities between female reproductive features and NAFLD. And we performed multivariable MR and MR mediation analysis to explore the mediation effects of educational attainment (EA) and body mass index (BMI) for these associations. Sensitivity analyses were performed to evaluate pleiotropy and heterogeneity. RESULTS There were causal effects of age at menarche (AAMA) (odds ratio [OR]: 0.817, 95% confidence interval [CI]: 0.736-0.907, per year-increase), age at first birth (AFB) (OR: 0.851, 95%CI: 0.791-0.926, per year-increase) and age at first sexual intercourse (AFS) (OR: 0.676, 95%CI: 0.511-0.896, per standard deviation-increase) on NAFLD risk. Besides, the causal effects were also observed on NAFLD phenotypes including liver fat content (LFC) and alanine aminotransferase (ALT). Further mediation analysis showed that BMI mediated partial proportion of effects of AAMA and AFS on NAFLD/ALT, AFB on NAFLD/LFC/ALT, while EA mediated partial proportion of effects of AFB on NAFLD/LFC/ALT, and AFS on NAFLD/ALT. CONCLUSIONS This study provided convincing evidence that early AAMA, AFB, and AFS were risk factors for NAFLD. Reproductive health education, obesity management, and education spread might be the beneficial strategies for NAFLD prevention.
Collapse
Affiliation(s)
- Haoshuang Fu
- Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shuying Song
- Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bingying Du
- Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianhui Zhou
- Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Minghao Cai
- Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shaowen Jiang
- Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yaoxing Chen
- Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xinya Zang
- Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yan Huang
- Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weijing Wang
- Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qing Xie
- Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| |
Collapse
|
27
|
Peña E, Mas-Bermejo P, Lecube A, Ciudin A, Arenas C, Simó R, Rigla M, Caixàs A, Rosa A. Use of polygenic risk scores to assess weight loss after bariatric surgery: a 5-year follow-up study. J Gastrointest Surg 2024; 28:1400-1405. [PMID: 38821212 DOI: 10.1016/j.gassur.2024.05.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 05/19/2024] [Accepted: 05/27/2024] [Indexed: 06/02/2024]
Abstract
BACKGROUND Bariatric surgery (BS) is currently the most effective long-term treatment of severe obesity. However, the interindividual variability observed in surgical outcomes suggests a moderating effect of several factors, including individual genetic background. This study aimed to investigate the contribution of the genetic architecture of body mass index (BMI) to the variability in weight loss outcomes after BS. METHODS A total of 106 patients with severe obesity who underwent Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy were followed up for 5 years. Changes in BMI (BMIchange) and percentage of total weight loss (%TWL) were evaluated during the postoperative period. Polygenic risk scores (PRSs), including 50 genetic variants, were calculated for each participant to determine their genetic risk of high BMI based on a previous genome-wide association study. Generalized estimating equation models were used to study the role of the individual's polygenic score and other factors on BMIchange and %TWL in the long term after surgery. RESULTS This study found an effect of the polygenic score on %TWL and BMIchange, in which patients with lower scores had better outcomes after surgery than those with higher scores. Furthermore, when analyzing only patients who underwent RYGB, the results were replicated, showing greater weight loss after surgery for patients with lower polygenic scores. DISCUSSION Our results indicate that genetic background assessed with PRSs, along with other individual factors, such as biological sex, age, and preoperative BMI, has an effect on BS outcomes and could represent a useful tool for estimating surgical outcomes in advance.
Collapse
Affiliation(s)
- Elionora Peña
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark; Secció de Zoologia i Antropologia Biòlogica, Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona, Barcelona, Spain
| | - Patricia Mas-Bermejo
- Secció de Zoologia i Antropologia Biòlogica, Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona, Barcelona, Spain; Institut de Biomedicina de la Universitat de Barcelona, Barcelona, Spain
| | - Albert Lecube
- Department of Endocrinology and Nutrition, Arnau de Vilanova University Hospital, Institut de Recerca Biomèdica de Lleida, Universitat de Lleida, Lleida, Spain
| | - Andreea Ciudin
- Diabetes and Metabolism Research Unit, Department of Endocrinology and Nutrition, Hospital Universitari Vall d'Hebron, Vall d'Hebron Institut de Recerca, Universitat Autònoma de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Madrid, Spain
| | - Concepción Arenas
- Statistics Section of the Department of Genetics, Microbiology and Statistics, Universitat de Barcelona, Barcelona, Spain
| | - Rafael Simó
- Diabetes and Metabolism Research Unit, Department of Endocrinology and Nutrition, Hospital Universitari Vall d'Hebron, Vall d'Hebron Institut de Recerca, Universitat Autònoma de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Madrid, Spain
| | - Mercedes Rigla
- Department of Endocrinology and Nutrition, Institut d'Investigació i Innovació, Parc Taulí Hospital Universitari, Sabadell, Spain; Departament de Medicina, Universitat Autònoma de Barcelona, Sabadell, Spain
| | - Assumpta Caixàs
- Department of Endocrinology and Nutrition, Institut d'Investigació i Innovació, Parc Taulí Hospital Universitari, Sabadell, Spain; Departament de Medicina, Universitat Autònoma de Barcelona, Sabadell, Spain
| | - Araceli Rosa
- Secció de Zoologia i Antropologia Biòlogica, Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona, Barcelona, Spain; Institut de Biomedicina de la Universitat de Barcelona, Barcelona, Spain; Centro de Investigación Biomédica En Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain.
| |
Collapse
|
28
|
Piazza GG, Allegrini AG, Eley TC, Epskamp S, Fried E, Isvoranu AM, Roiser JP, Pingault JB. Polygenic Scores and Networks of Psychopathology Symptoms. JAMA Psychiatry 2024; 81:902-910. [PMID: 38865107 PMCID: PMC11170456 DOI: 10.1001/jamapsychiatry.2024.1403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 03/19/2024] [Indexed: 06/13/2024]
Abstract
Importance Studies on polygenic risk for psychiatric traits commonly use a disorder-level approach to phenotyping, implicitly considering disorders as homogeneous constructs; however, symptom heterogeneity is ubiquitous, with many possible combinations of symptoms falling under the same disorder umbrella. Focusing on individual symptoms may shed light on the role of polygenic risk in psychopathology. Objective To determine whether polygenic scores are associated with all symptoms of psychiatric disorders or with a subset of indicators and whether polygenic scores are associated with comorbid phenotypes via specific sets of relevant symptoms. Design, Setting, and Participants Data from 2 population-based cohort studies were used in this cross-sectional study. Data from children in the Avon Longitudinal Study of Parents and Children (ALSPAC) were included in the primary analysis, and data from children in the Twins Early Development Study (TEDS) were included in confirmatory analyses. Data analysis was conducted from October 2021 to January 2024. Pregnant women based in the Southwest of England due to deliver in 1991 to 1992 were recruited in ALSPAC. Twins born in 1994 to 1996 were recruited in TEDS from population-based records. Participants with available genetic data and whose mothers completed the Short Mood and Feelings Questionnaire and the Strength and Difficulties Questionnaire when children were 11 years of age were included. Main Outcomes and Measures Psychopathology relevant symptoms, such as hyperactivity, prosociality, depression, anxiety, and peer and conduct problems at age 11 years. Psychological networks were constructed including individual symptoms and polygenic scores for depression, anxiety, attention-deficit/hyperactivity disorder (ADHD), body mass index (BMI), and educational attainment in ALSPAC. Following a preregistered confirmatory analysis, network models were cross-validated in TEDS. Results Included were 5521 participants from ALSPAC (mean [SD] age, 11.8 [0.14] years; 2777 [50.3%] female) and 4625 participants from TEDS (mean [SD] age, 11.27 [0.69] years; 2460 [53.2%] female). Polygenic scores were preferentially associated with restricted subsets of core symptoms and indirectly associated with other, more distal symptoms of psychopathology (network edges ranged between r = -0.074 and r = 0.073). Psychiatric polygenic scores were associated with specific cross-disorder symptoms, and nonpsychiatric polygenic scores were associated with a variety of indicators across disorders, suggesting a potential contribution of nonpsychiatric traits to comorbidity. For example, the polygenic score for ADHD was associated with a core ADHD symptom, being easily distracted (r = 0.07), and the polygenic score for BMI was associated with symptoms across disorders, including being bullied (r = 0.053) and not thinking things out (r = 0.041). Conclusions and Relevance Genetic associations observed at the disorder level may hide symptom-level heterogeneity. A symptom-level approach may enable a better understanding of the role of polygenic risk in shaping psychopathology and comorbidity.
Collapse
Affiliation(s)
- Giulia G. Piazza
- Department of Clinical, Educational and Health Psychology, University College London, London, United Kingdom
| | - Andrea G. Allegrini
- Department of Clinical, Educational and Health Psychology, University College London, London, United Kingdom
- Social Genetic and Developmental Psychiatry, King’s College London, London, United Kingdom
| | - Thalia C. Eley
- Social Genetic and Developmental Psychiatry, King’s College London, London, United Kingdom
| | - Sacha Epskamp
- Department of Psychology, National University of Singapore, Singapore
| | - Eiko Fried
- Department of Clinical Psychology, Leiden University, Leiden, the Netherlands
| | | | - Jonathan P. Roiser
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
| | - Jean-Baptiste Pingault
- Department of Clinical, Educational and Health Psychology, University College London, London, United Kingdom
- Social Genetic and Developmental Psychiatry, King’s College London, London, United Kingdom
| |
Collapse
|
29
|
Gustavson DE, Morrison CL, Mallard TT, Jennings MV, Fontanillas P, Elson SL, Palmer AA, Friedman NP, Sanchez-Roige S. Executive Function and Impulsivity Predict Distinct Genetic Variance in Internalizing Problems, Externalizing Problems, Thought Disorders, and Compulsive Disorders: A Genomic Structural Equation Modeling Study. Clin Psychol Sci 2024; 12:865-881. [PMID: 39323941 PMCID: PMC11423426 DOI: 10.1177/21677026231207845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/27/2024]
Abstract
Individual differences in self-control predict many health and life outcomes. Building on twin literature, we used genomic structural equation modeling to test the hypothesis that genetic influences on executive function and impulsivity predict independent variance in mental health and other outcomes. The impulsivity factor (comprising urgency, lack of premeditation, and other facets) was only modestly genetically correlated with low executive function (rg =.13). Controlling for impulsivity, low executive function was genetically associated with increased internalizing (βg =.15), externalizing (βg =.13), thought disorders (βg =.38), compulsive disorders (βg =.22), and chronotype (βg =.11). Controlling for executive function, impulsivity was positively genetically associated with internalizing (βg =.36), externalizing (βg =.55), body mass index (βg =.26), and insomnia (βg =.35), and negatively genetically associated with compulsive disorders (βg = -.17). Executive function and impulsivity were both genetically correlated with general cognitive ability and educational attainment. This work suggests that executive function and impulsivity are genetically separable and show independent associations with mental health.
Collapse
Affiliation(s)
- Daniel E Gustavson
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO
| | - Claire L Morrison
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO
| | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Psychiatry, Harvard Medical School, Boston, MA
| | - Mariela V Jennings
- Department of Psychiatry, University of California San Diego, La Jolla CA, USA
| | | | | | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Naomi P Friedman
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| |
Collapse
|
30
|
Lahousse L. Overweight and dysanapsis in childhood asthma. Eur Respir J 2024; 64:2401164. [PMID: 39237315 DOI: 10.1183/13993003.01164-2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2024] [Accepted: 06/17/2024] [Indexed: 09/07/2024]
Affiliation(s)
- Lies Lahousse
- Department of Bioanalysis, Ghent University, Ghent, Belgium
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| |
Collapse
|
31
|
Fitch AK, Malhotra S, Conroy R. Differentiating monogenic and syndromic obesities from polygenic obesity: Assessment, diagnosis, and management. OBESITY PILLARS 2024; 11:100110. [PMID: 38766314 PMCID: PMC11101890 DOI: 10.1016/j.obpill.2024.100110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 04/18/2024] [Accepted: 04/18/2024] [Indexed: 05/22/2024]
Abstract
Background Obesity is a multifactorial neurohormonal disease that results from dysfunction within energy regulation pathways and is associated with increased morbidity, mortality, and reduced quality of life. The most common form is polygenic obesity, which results from interactions between multiple gene variants and environmental factors. Highly penetrant monogenic and syndromic obesities result from rare genetic variants with minimal environmental influence and can be differentiated from polygenic obesity depending on key symptoms, including hyperphagia; early-onset, severe obesity; and suboptimal responses to nontargeted therapies. Timely diagnosis of monogenic or syndromic obesity is critical to inform management strategies and reduce disease burden. We outline the physiology of weight regulation, role of genetics in obesity, and differentiating characteristics between polygenic and rare genetic obesity to facilitate diagnosis and transition toward targeted therapies. Methods In this narrative review, we focused on case reports, case studies, and natural history studies of patients with monogenic and syndromic obesities and clinical trials examining the efficacy, safety, and quality of life impact of nontargeted and targeted therapies in these populations. We also provide comprehensive algorithms for diagnosis of patients with suspected rare genetic causes of obesity. Results Patients with monogenic and syndromic obesities commonly present with hyperphagia (ie, pathologic, insatiable hunger) and early-onset, severe obesity, and the presence of hallmark characteristics can inform genetic testing and diagnostic approach. Following diagnosis, specialized care teams can address complex symptoms, and hyperphagia is managed behaviorally. Various pharmacotherapies show promise in these patient populations, including setmelanotide and glucagon-like peptide-1 receptor agonists. Conclusion Understanding the pathophysiology and differentiating characteristics of monogenic and syndromic obesities can facilitate diagnosis and management and has led to development of targeted pharmacotherapies with demonstrated efficacy for reducing body weight and hunger in the affected populations.
Collapse
Affiliation(s)
| | - Sonali Malhotra
- Harvard Medical School, Boston, MA, USA
- Rhythm Pharmaceuticals, Inc., Boston, MA, USA
- Massachussetts General Hospital, Boston, MA, USA
| | | |
Collapse
|
32
|
Jensen SK, Pedersen CET, Fischer-Rasmussen K, Melgaard ME, Brustad N, Kyvsgaard JN, Vahman N, Schoos AMM, Stokholm J, Chawes B, Eliasen A, Bønnelykke K. Genetic predisposition to high BMI increases risk of early life respiratory infections and episodes of severe wheeze and asthma. Eur Respir J 2024; 64:2400169. [PMID: 38811044 DOI: 10.1183/13993003.00169-2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 05/20/2024] [Indexed: 05/31/2024]
Abstract
BACKGROUND High body mass index (BMI) is an established risk factor for asthma, but the underlying mechanisms remain unclear. OBJECTIVE To increase understanding of the BMI-asthma relationship by studying the association between genetic predisposition to higher BMI and asthma, infections and other asthma traits during childhood. METHODS Data were obtained from the two ongoing Copenhagen Prospective Studies on Asthma in Childhood (COPSAC) mother-child cohorts. Polygenic risk scores for adult BMI were calculated for each child. Replication was done in the large-scale register-based Integrative Psychiatric Research (iPSYCH) cohort using data on hospitalisation for asthma and infections. RESULTS In the COPSAC cohorts (n=974), the adult BMI polygenic risk score was significantly associated with lower respiratory tract infections (incidence rate ratio (IRR) 1.20, 95% CI 1.08-1.33, false discovery rate p-value (pFDR)=0.005) at age 0-3 years and episodes of severe wheeze (IRR 1.30, 95% CI 1.06-1.60, pFDR=0.04) at age 0-6 years. Lower respiratory tract infections partly mediated the association between the adult BMI polygenic risk score and severe wheeze (proportion mediated: 0.59, 95% CI 0.28-2.24, p-value associated with the average causal mediation effect (pACME)=2e-16). In contrast, these associations were not mediated through the child's current BMI and the polygenic risk score was not associated with an asthma diagnosis or reduced lung function up to age 18 years. The associations were replicated in iPSYCH (n=114 283), where the adult BMI polygenic risk score significantly increased the risk of hospitalisations for lower respiratory tract infections and wheeze or asthma throughout childhood to age 18 years. CONCLUSION Children with genetic predisposition to higher BMI had increased risk of lower respiratory tract infections and severe wheeze, independent of the child's current BMI. These results shed further light on the complex relationship between body mass BMI and asthma.
Collapse
Affiliation(s)
- Signe Kjeldgaard Jensen
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Casper-Emil Tingskov Pedersen
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Kasper Fischer-Rasmussen
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Mathias Elsner Melgaard
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Nicklas Brustad
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Julie Nyholm Kyvsgaard
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
- Department of Pediatrics, Slagelse Hospital, Slagelse, Denmark
| | - Nilo Vahman
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Ann-Marie Malby Schoos
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
- Department of Pediatrics, Slagelse Hospital, Slagelse, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jakob Stokholm
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
- Department of Pediatrics, Slagelse Hospital, Slagelse, Denmark
- Section of Microbiology and Fermentation, Department of Food Science, University of Copenhagen, Copenhagen, Denmark
| | - Bo Chawes
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Anders Eliasen
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
- Department of Pediatrics, Division of Endocrinology, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Shared senior author
| | - Klaus Bønnelykke
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Department of Pediatrics, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Shared senior author
| |
Collapse
|
33
|
Zhou Y, Ye R, Guo X. Modifiable risk factors mediating the impact of educational inequality on heart failure: A Mendelian randomization study. Prev Med 2024; 186:108098. [PMID: 39127305 DOI: 10.1016/j.ypmed.2024.108098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Revised: 08/07/2024] [Accepted: 08/07/2024] [Indexed: 08/12/2024]
Abstract
BACKGROUND Heart failure (HF) is a rapidly growing global disease burden with high mortality rates. We aimed to utilize mendelian randomization (MR) analyses to investigate the association between educational attainment (EA) and HF, and to evaluate the contribution of modifiable risk factors as mediators. METHODS We applied a two-sample MR approach based on the largest genome-wide association studies (GWAS) to investigate the causal relationship between EA and HF. Data collection was conducted in July 2023. We then conducted mediation analyses to explore whether body mass index (BMI), blood pressure, and type 2 diabetes mellitus (T2DM) mediate the effect of EA on HF, and utilized multivariable MR to estimate the proportion of mediation attributed to these factors. RESULTS Genetically predicted 3.4 years of additional education was associated with a decrease in the risk of HF (OR 0.76 for each 3.4 years of schooling; 95% CI 0.72, 0.81). BMI, T2DM, systolic blood pressure, and diastolic blood pressure mediated 40.82% (95% CI: 28.86%, 52.77%), 18.00% (95% CI: 12.10%, 23.90%), 11.60% (95% CI: 7.63%, 15.56%), and 7.80% (95% CI: 4.63%, 10.96%) of the EA-HF association, respectively. All risk factors combined were estimated to mediate 63.81% (95% CI: 45.91%, 81.71%) of the effect of EA on HF. CONCLUSION Higher EA has a protective effect against the risk of HF, and potential mechanisms may include regulation of BMI, blood pressure, and blood glucose. Further research is needed to understand whether interventions targeting these factors could influence the association between EA and HF risk.
Collapse
Affiliation(s)
- Yijiang Zhou
- Department of Cardiology, The First Affiliated Hospital, School of Medicine, Zhejiang University, 79 Qingchun Road, Hangzhou 310003, Zhejiang, China.
| | - Runze Ye
- Department of Cardiology, The First Affiliated Hospital, School of Medicine, Zhejiang University, 79 Qingchun Road, Hangzhou 310003, Zhejiang, China.
| | - Xiaogang Guo
- Department of Cardiology, The First Affiliated Hospital, School of Medicine, Zhejiang University, 79 Qingchun Road, Hangzhou 310003, Zhejiang, China.
| |
Collapse
|
34
|
Dash S. Opportunities to optimize lifestyle interventions in combination with glucagon-like peptide-1-based therapy. Diabetes Obes Metab 2024; 26 Suppl 4:3-15. [PMID: 39157881 DOI: 10.1111/dom.15829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Revised: 06/28/2024] [Accepted: 07/10/2024] [Indexed: 08/20/2024]
Abstract
Obesity is a chronic multi-system disease and major driver of type 2 diabetes and cardiometabolic disease. Nutritional interventions form the cornerstone of obesity and type 2 diabetes management. Some interventions such as Mediterranean diet can reduce incident cardiovascular disease, probably independently of weight loss. Weight loss of 5% or greater can improve many adiposity-related comorbidities. Although this can be achieved with lifestyle intervention, it is often difficult to sustain in the longer term due to adaptive endocrine changes. In recent years glucagon-like-peptide-1 receptor agonists (GLP-1RAs) have emerged as effective treatments for both type 2 diabetes and obesity. Newer GLP-1RAs can achieve average weight loss of 15% or greater and improve cardiometabolic health. There is heterogeneity in the weight loss response to GLP-1RAs, with a substantial number of patients unable to achieve 5% or greater weight. Weight loss, on average, is lower in older adults, male patients and people with type 2 diabetes. Mechanistic studies are needed to understand the aetiology of this variable response. Gastrointestinal side effects leading to medication discontinuation are a concern with GLP-1RA treatment, based on real-world data. With weight loss of 20% or higher with newer GLP-1RAs, nutritional deficiency and sarcopenia are also potential concerns. Lifestyle interventions that may potentially mitigate the side effects of GLP-1RA treatment and enhance weight loss are discussed here. The efficacy of such interventions awaits confirmation with well-designed randomized controlled trials.
Collapse
Affiliation(s)
- Satya Dash
- Division of Endocrinology, University Health Network & University of Toronto, Toronto General Hospital, Toronto, Ontario, Canada
| |
Collapse
|
35
|
Fan S, Jiang H, Shen J, Lin H, Yu D, Yang L, Zheng N, Chen L. Association between educational attainment and thyroid cancer: evidence from a univariable and multivariable Mendelian randomization study. Endocrine 2024; 85:1238-1243. [PMID: 38565797 DOI: 10.1007/s12020-024-03796-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 03/14/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND Thyroid cancer and educational attainment have been related in observational studies. It is unclear if these correlations indicate causative relationships. METHODS Using large-scale genome-wide association studies (GWAS) datasets, we conducted an univariable and multivariable Mendelian randomization (MR) study to assess a potential connection between educational attainment and thyroid cancer. The inverse-variance weighted (IVW) analysis method is used as our primary outcome. Additionally, we carry out several sensitivity analyses to evaluate the pleiotropy and robustness of the causal estimates. RESULTS Univariate MR study shows 4.2 years of additional education is associated with a 41.4% reduction in thyroid cancer risk (OR = 0.586; 95% CI: 0.378-0.909; P = 0.017). Further multivariable MR analysis revealed that body mass index (BMI) acted as a partial mediating factor in the protective impact of higher educational attainment against thyroid cancer. CONCLUSION This MR study provided genetic evidence that longer education attainment is related to a lower risk of thyroid cancer. Strategies of expanding education may reduce the burden of thyroid cancer in the world.
Collapse
Affiliation(s)
- Siyue Fan
- Nursing College, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Hongzhan Jiang
- Nursing College, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Jiali Shen
- Nursing College, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Huihui Lin
- Nursing College, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Doudou Yu
- Nursing College, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Liping Yang
- Nursing College, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Nengtong Zheng
- Nursing College, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Lijuan Chen
- Nursing College, Fujian University of Traditional Chinese Medicine, Fuzhou, China.
- Department of General Surgery, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen, China.
| |
Collapse
|
36
|
Jiang Y, Shen J, Chen P, Cai J, Zhao Y, Liang J, Cai J, Cheng S, Zhang Y. Association of triglyceride glucose index with stroke: from two large cohort studies and Mendelian randomization analysis. Int J Surg 2024; 110:5409-5416. [PMID: 38896856 PMCID: PMC11392123 DOI: 10.1097/js9.0000000000001795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Accepted: 05/30/2024] [Indexed: 06/21/2024]
Abstract
INTRODUCTION The triglyceride glucose index (TyG) is associated with cardiovascular diseases; however, its association with stroke remains unclear. This study aimed to elucidate this relationship by examining two extensive cohort studies using two-sample Mendelian randomization (MR). METHODS Using data from the 1999-2018 National Health and Nutrition Examination Survey (NHANES) and the Medical Information Mart for Intensive Care (MIMIC)-IV, the correlation between TyG (continuous and quartile) and stroke was examined using multivariate Cox regression models and sensitivity analyses. Two-sample MR was employed to establish causality between TyG and stroke using the inverse variance weighting method. Genome-wide association study catalog queries were performed for single nucleotide polymorphism-mapped genes, and the STRING platform used to assess protein interactions. Functional annotation and enrichment analyses were also conducted. RESULTS From the NHANES and MIMIC-IV cohorts, we included 740 and 589 participants with stroke, respectively. After adjusting for covariates, TyG was linearly associated with the risk of stroke death (NHANES: hazard ratio [HR] 0.64, 95% CI: 0.41-0.99, P =0.047; Q3 vs. Q1, HR 0.62, 95% CI: 0.40-0.96, P =0.033; MIMIC-IV: HR 0.46, 95% CI: 0.27-0.80, P =0.006; Q3 vs. Q1, HR 0.32, 95% CI: 0.12-0.86; Q4 vs. Q1, HR 0.30, 95% CI: 0.10-0.89, P =0.030, P for trend=0.017). Two-sample MR analysis showed genetic prediction supported a causal association between a higher TyG and a reduced risk of stroke (odds ratio 0.711, 95% CI: 0.641-0.788, P =7.64e -11 ). CONCLUSIONS TyG was causally associated with a reduced risk of stroke. TyG is a critical factor for stroke risk management.
Collapse
Affiliation(s)
- Yong'An Jiang
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University
| | - Jing Shen
- Institute of Geriatrics, Jiangxi Provincial People's Hospital and The First Affiliated Hospital of Nanchang Medical College
- School of Public Health, Nanchang University
| | - Peng Chen
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University
| | - JiaHong Cai
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University
| | - YangYang Zhao
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University
| | - JiaWei Liang
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University
| | - JianHui Cai
- Department of Neurosurgery, Nanchang County People's Hospital, Nanchang
- Nanchang Cranio-Cerebral Trauma Laboratory Nanchang, Jiangxi, People's Republic of China
| | - ShiQi Cheng
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University
| | - Yan Zhang
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University
- Nanchang Cranio-Cerebral Trauma Laboratory Nanchang, Jiangxi, People's Republic of China
| |
Collapse
|
37
|
Norton SA, Gorelik AJ, Paul SE, Johnson EC, Baranger DA, Siudzinski JL, Li ZA, Bondy E, Modi H, Karcher NR, Hershey T, Hatoum AS, Agrawal A, Bogdan R. A Phenome-Wide Association Study (PheWAS) of Genetic Risk for C-Reactive Protein in Children of European Ancestry: Results From the ABCD Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.30.24312857. [PMID: 39252928 PMCID: PMC11383484 DOI: 10.1101/2024.08.30.24312857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/11/2024]
Abstract
BACKGROUND C-reactive protein (CRP) is a moderately heritable marker of systemic inflammation that is associated with adverse physical and mental health outcomes. Identifying factors associated with genetic liability to elevated CRP in childhood may inform our understanding of variability in CRP that could be targeted to prevent and/or delay the onset of related health outcomes. METHODS We conducted a phenome-wide association study (PheWAS) of genetic risk for elevated CRP (i.e. CRP polygenic risk score [PRS]) among children genetically similar to European ancestry reference populations (median analytic n = 5,509) from the Adolescent Brain and Cognitive Development℠ (ABCD) Study. Associations between CRP PRS and 2,377 psychosocial and neuroimaging phenotypes were estimated using independent mixed effects models. Post hoc analyses examined whether: (1) covarying for measured body mass index (BMI) or removing the shared genetic architecture between CRP and BMI altered phenotypic associations, (2) sex moderated CRP PRS associations, and (3) associations are unconfounded by assortative mating or passive gene-environment correlations (using a within-family analyses). Multiple testing was adjusted for using Bonferroni and false discovery rate (FDR) correction. RESULTS Nine phenotypes were positively associated with CRP PRS after multiple testing correction: five weight- and eating-related phenotypes (e.g. BMI, overeating), three phenotypes related to caregiver somatic problems (e.g. caregiver somatic complaints), as well as weekday video watching (all ps = 1.2 × 10-7 - 2.5 × 10-4, all p FDR s = 0.0002 - 0.05). No neuroimaging phenotypes were associated with CRP PRS (all ps = 0.0003 - 0.998; all p FDR s = 0.08 - 0.998) after correction for multiple testing. Eating and weight-related phenotypes remained associated with CRP PRS in within-family analyses. Covarying for BMI resulted in largely consistent results, and sex did not moderate any CRP PRS associations. Removing the shared genetic variance between CRP and BMI attenuated all relationships; associations with weekday video watching, caregiver somatic problems and caregiver report that the child is overweight remained significant while associations with waist circumference, weight, and caregiver report that child overeats did not. DISCUSSION Genetic liability to elevated CRP is associated with higher weight, eating, and weekday video watching during childhood as well as caregiver somatic problems. These associations were consistent with direct genetic effects (i.e., not solely due to confounding factors like passive gene-environment correlations) and were independent of measured BMI. The majority of associations with weight and eating phenotypes were attributable to shared genetic architecture between BMI and inflammation. The relationship between genetics and heightened inflammation in later life may be partially attributable to modifiable behaviors (e.g. weight and activity levels) that are expressed as early as childhood.
Collapse
Affiliation(s)
- Sara A Norton
- Washington University in St. Louis, Department of Psychological & Brain Sciences
| | - Aaron J Gorelik
- Washington University in St. Louis, Department of Psychological & Brain Sciences
| | - Sarah E Paul
- Washington University in St. Louis, Department of Psychological & Brain Sciences
| | - Emma C Johnson
- Washington University School of Medicine in St. Louis, Department of Psychiatry
| | - David Aa Baranger
- Washington University in St. Louis, Department of Psychological & Brain Sciences
| | - Jayne L Siudzinski
- Washington University in St. Louis, Department of Psychological & Brain Sciences
| | - Zhaolong Adrian Li
- Washington University School of Medicine in St. Louis, Department of Psychiatry
| | - Erin Bondy
- University of North Carolina School of Medicine, Department of Psychiatry
| | - Hailey Modi
- Washington University School of Medicine in St. Louis, Division of Biological and Biomedical Sciences
| | - Nicole R Karcher
- Washington University School of Medicine in St. Louis, Department of Psychiatry
| | - Tamara Hershey
- Washington University School of Medicine in St. Louis, Department of Psychiatry
- Washington University School of Medicine, Department of Radiology
| | - Alexander S Hatoum
- Washington University School of Medicine in St. Louis, Department of Psychiatry
| | - Arpana Agrawal
- Washington University School of Medicine in St. Louis, Department of Psychiatry
| | - Ryan Bogdan
- Washington University in St. Louis, Department of Psychological & Brain Sciences
| |
Collapse
|
38
|
Li Z, Hao J, Wang T, Guo C, Liu L. Branched-chain amino acids and risk of lung cancer: insights from mendelian randomization and NHANES III. J Thorac Dis 2024; 16:5248-5261. [PMID: 39268127 PMCID: PMC11388241 DOI: 10.21037/jtd-24-420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 07/12/2024] [Indexed: 09/15/2024]
Abstract
Background Recent studies have observed the relationships of circulatory and dietary intake of branched-chain amino acids (BCAAs) with long-term risk of certain cancers. However, the exact causality of BCAA with lung cancer (LUCA) and its pathological subtypes remains obscure. The aim of this study is to investigate the association between BCAA metabolism and risk of LUCA. Methods Here we conducted Mendelian randomization (MR) and observational epidemiological analyses to investigate the association between BCAA and risk of LUCA. With single nucleotide polymorphism (SNP)-phenotype association data extracted from genome-wide association studies (GWAS), we performed univariate and multivariate MR analyses to infer the causal effect of circulatory BCAA concentrations on LUCA. We further investigated the effects of several potential mediators and quantified the mediation effects. Population-level analyses were performed in the National Health and Nutrition Examination Survey (NHANES) III. Results Our results demonstrated that genetically predicted circulatory valine concentrations causally increased the risk of overall LUCA [odds ratio (OR) =1.324, 95% confidence interval (CI): 1.058-1.658, P=0.01]. For pathological subgroups, elevated levels of leucine, isoleucine, valine, and total BCAA were founded to be significantly associated with a higher risk of squamous cell lung cancer (LUSC); however, they did not significantly affect lung adenocarcinoma (LUAD). Moreover, body mass index (BMI) mediated approximately 3.91% (95% CI: 1.22-7.18%) of the total effect of leucine on LUSC. In the NHANES III population, dietary total BCAA intake was significantly associated with BMI ≥30 kg/m2, while no non-linear relationships were observed. Conclusions This study provides genetic evidence for the histology-specific causality of BCAA on LUCA and implies the mediation role of BMI in this relationship. Further studies are needed to confirm these findings and elucidate the underlying mechanisms.
Collapse
Affiliation(s)
- Zongyuan Li
- Department of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, Chengdu, China
- West China School of Medicine, Sichuan University, Chengdu, China
| | - Jianqi Hao
- Department of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, Chengdu, China
- Western China Collaborative Innovation Center for Early Diagnosis and Multidisciplinary Therapy of Lung Cancer, Sichuan University, Chengdu, China
| | - Tengyong Wang
- Department of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, Chengdu, China
- West China School of Medicine, Sichuan University, Chengdu, China
| | - Chenglin Guo
- Department of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, Chengdu, China
- Western China Collaborative Innovation Center for Early Diagnosis and Multidisciplinary Therapy of Lung Cancer, Sichuan University, Chengdu, China
| | - Lunxu Liu
- Department of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, Chengdu, China
- Western China Collaborative Innovation Center for Early Diagnosis and Multidisciplinary Therapy of Lung Cancer, Sichuan University, Chengdu, China
| |
Collapse
|
39
|
Zhang W, Song X, Song T, Zeng D. Association between common chronic pulmonary diseases and lung cancer: Mendelian randomization analysis. Discov Oncol 2024; 15:387. [PMID: 39212755 PMCID: PMC11364834 DOI: 10.1007/s12672-024-01274-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2024] [Accepted: 08/26/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND Lung cancer is a leading public health concern worldwide. Previous evidence suggests that chronic obstructive pulmonary disease (COPD) and asthma may contribute to its development. However, whether these common chronic pulmonary diseases are causal factors of lung cancer remained unclear. METHODS Summary statistics from genome-wide association studies (GWAS) were used for Mendelian randomization (MR) analysis. Genetic data for COPD were obtained from the Global Biobank Meta-Analysis Initiative, and asthma data were retrieved from the UK Biobank cohort. Suitable instrumental variables were selected based on quality control measures. GWAS summary data for lung cancer were obtained from a large study involved 85,716 participants. MR analysis was performed using various methods, and sensitivity analyses were conducted. Multivariable MR (MVMR) analysis was employed to account for potential confounding factors. RESULTS Our MR analysis revealed a significant causal association between COPD and lung cancer, including its subtypes such as lung squamous cell carcinoma, lung adenocarcinoma, and small cell lung carcinoma. Genetically predicted COPD was associated with a 64% increased risk of lung cancer and a 2.3 to 2.8-fold increased risk of the different subtypes. However, in the MVMR analysis adjusting for smoking, alcohol drinking, and body mass index, the association between COPD and lung cancer became non-significant. No significant association was observed between asthma (childhood-onset and adult-onset) and lung cancer and its histological subtypes. CONCLUSIONS Our study suggests a potential causal association between COPD and lung cancer. However, this association became non-significant after adjusting for smoking in the multivariable analysis.
Collapse
Affiliation(s)
- Wenbin Zhang
- The Fifth clinical medical college, Guilin Medical University, Guilin, 541002, Guangxi, People's Republic of China.
| | - Xinnan Song
- The Fifth clinical medical college, Guilin Medical University, Guilin, 541002, Guangxi, People's Republic of China
| | - Tianjun Song
- Department of Medicine II, University Hospital, LMU Munich, 81377, Munich, Germany
| | - Dongyun Zeng
- Clinicopathological Diagnosis & Research Center, the Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, 533000, People's Republic of China.
- Key Laboratory of Tumor Molecular Pathology of Guangxi Higher Education Institutes, Baise, 533000, People's Republic of China.
| |
Collapse
|
40
|
Solé-Navais P, Juodakis J, Ytterberg K, Wu X, Bradfield JP, Vaudel M, LaBella AL, Helgeland Ø, Flatley C, Geller F, Finel M, Zhao M, Lazarus P, Hakonarson H, Magnus P, Andreassen OA, Njølstad PR, Grant SFA, Feenstra B, Muglia LJ, Johansson S, Zhang G, Jacobsson B. Genome-wide analyses of neonatal jaundice reveal a marked departure from adult bilirubin metabolism. Nat Commun 2024; 15:7550. [PMID: 39214992 PMCID: PMC11364559 DOI: 10.1038/s41467-024-51947-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 08/20/2024] [Indexed: 09/04/2024] Open
Abstract
Jaundice affects almost all neonates in their first days of life and is caused by the accumulation of bilirubin. Although the core biochemistry of bilirubin metabolism is well understood, it is not clear why some neonates experience more severe jaundice and require treatment with phototherapy. Here, we present the first genome-wide association study of neonatal jaundice to date in nearly 30,000 parent-offspring trios from Norway (cases ≈ 2000). The alternate allele of a common missense variant affecting the sequence of UGT1A4 reduces the susceptibility to jaundice five-fold, which replicated in separate cohorts of neonates of African American and European ancestries. eQTL colocalization analyses indicate that the association may be driven by regulation of UGT1A1 in the intestines, but not in the liver. Our results reveal marked differences in the genetic variants involved in neonatal jaundice compared to those regulating bilirubin levels in adults, suggesting distinct genetic mechanisms for the same biological pathways.
Collapse
Affiliation(s)
- Pol Solé-Navais
- Department of Obstetrics and Gynaecology, Sahlgrenska Academy, Institute of Clinical Sciences, University of Gothenburg, Gothenburg, Sweden.
| | - Julius Juodakis
- Department of Obstetrics and Gynaecology, Sahlgrenska Academy, Institute of Clinical Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Karin Ytterberg
- Department of Obstetrics and Gynaecology, Sahlgrenska Academy, Institute of Clinical Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Xiaoping Wu
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
- Copenhagen University Hospital Biobank Unit, Department of Clinical Immunology, Rigshospitalet, Copenhagen, Denmark
| | - Jonathan P Bradfield
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Quantinuum Research LLC, Wayne, PA, USA
| | - Marc Vaudel
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Abigail L LaBella
- Department of Bioinformatics and Genomics, College of Computing and Informatics, North Carolina Research Campus, University of North Carolina at Charlotte, Kannapolis, NC, USA
| | - Øyvind Helgeland
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Christopher Flatley
- Department of Obstetrics and Gynaecology, Sahlgrenska Academy, Institute of Clinical Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Frank Geller
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
- Copenhagen University Hospital Biobank Unit, Department of Clinical Immunology, Rigshospitalet, Copenhagen, Denmark
| | - Moshe Finel
- Division of Pharmaceutical Chemistry and Technology, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland
| | - Mengqi Zhao
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, WA, USA
| | - Philip Lazarus
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, WA, USA
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, Buffalo, NY, USA
| | - Hakon Hakonarson
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Pulmonary Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Per Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, University of Oslo, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Pål R Njølstad
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway
| | - Struan F A Grant
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Endocrinology and Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
- Copenhagen University Hospital Biobank Unit, Department of Clinical Immunology, Rigshospitalet, Copenhagen, Denmark
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Louis J Muglia
- Office of the President, Burroughs Wellcome Fund, Research Triangle Park, NC, USA
- Division of Human Genetics, Center for the Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Stefan Johansson
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Ge Zhang
- Division of Human Genetics, Center for the Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Bo Jacobsson
- Department of Obstetrics and Gynaecology, Sahlgrenska Academy, Institute of Clinical Sciences, University of Gothenburg, Gothenburg, Sweden.
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway.
| |
Collapse
|
41
|
Takahashi I, Ohseto H, Ueno F, Oonuma T, Narita A, Obara T, Ishikuro M, Murakami K, Noda A, Hozawa A, Sugawara J, Tamiya G, Kuriyama S. Genome-wide association study based on clustering by obesity-related variables uncovers a genetic architecture of obesity in the Japanese and the UK populations. Heliyon 2024; 10:e36023. [PMID: 39247266 PMCID: PMC11379603 DOI: 10.1016/j.heliyon.2024.e36023] [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: 06/08/2023] [Revised: 08/06/2024] [Accepted: 08/08/2024] [Indexed: 09/10/2024] Open
Abstract
Whether all obesity-related variants contribute to the onset of obesity or one or a few variants cause obesity in genetically heterogeneous populations remains obscure. Here, we investigated the genetic architecture of obesity by clustering the Japanese and British populations with obesity using obesity-related factors. In Step-1, we conducted a genome-wide association study (GWAS) with body mass index (BMI) as the outcome for eligible participants. In Step-2, we assigned participants with obesity (BMI ≥25 kg/m2) to five clusters based on obesity-related factors. Subsequently, participants from each cluster and those with a BMI <25 kg/m2 were combined. A GWAS was conducted for each cluster. Several previously identified obesity-related genes were verified in Step-1. Of the genes detected in Step-1, unique obesity-related genes were detected separately for each cluster in Step-2. Our novel findings suggest that a smaller sample size with increased homogeneity may provide insights into the genetic architecture of obesity.
Collapse
Affiliation(s)
- Ippei Takahashi
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Hisashi Ohseto
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Fumihiko Ueno
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Tomomi Oonuma
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Akira Narita
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Taku Obara
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Tohoku University Hospital, Sendai, Japan
| | - Mami Ishikuro
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Keiko Murakami
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Aoi Noda
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Tohoku University Hospital, Sendai, Japan
| | - Atsushi Hozawa
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Junichi Sugawara
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Gen Tamiya
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
| | - Shinichi Kuriyama
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| |
Collapse
|
42
|
Mao T, Chen J, Su T, Xie L, Qu X, Feng R, Pan Y, Wan J, Cui X, Jia W, Gao Q, Lin Q. Causal relationships between GLP1 receptor agonists, blood lipids, and heart failure: a drug-target mendelian randomization and mediation analysis. Diabetol Metab Syndr 2024; 16:208. [PMID: 39198854 PMCID: PMC11360323 DOI: 10.1186/s13098-024-01448-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2024] [Accepted: 08/19/2024] [Indexed: 09/01/2024] Open
Abstract
BACKGROUND Glucagon-like peptide-1 receptor (GLP1R) agonists have been shown to reduce major cardiovascular events in diabetic patients, but their role in heart failure (HF) remains controversial. Recent evidence implies their potential benefits on cardiometabolism such as lipid metabolism, which may contribute to lowering the risk of HF. Consequently, we designed a Mendelian randomization (MR) study to investigate the causal relationships of circulating lipids mediating GLP1R agonists in HF. METHODS The available cis-eQTLs for GLP1R target gene were selected as instrumental variables (IVs) of GLP1R agonism. Positive control analyses of type 2 diabetes mellitus (T2DM) and body mass index (BMI) were conducted to validate the enrolled IVs. Two-sample MR was performed to evaluate the associations between GLP1R agonism and HF as well as left ventricular ejection fraction (LVEF). Summary data for HF and LVEF were obtained from two genome-wide association studies (GWASs), which included 977,323 and 40,000 individuals of European ancestry, respectively. The primary method employed was the random-effects inverse variance weighted, with several other methods used for sensitivity analyses, including MR-Egger, MR PRESSO, and weighted median. Additionally, multivariable MR and mediation MR were applied to identify potentially causal lipid as mediator. RESULTS A total of 18 independent IVs were included. The positive control analyses showed that GLP1R agonism significantly reduced the risk of T2DM (OR = 0.79, 95% CI = 0.75-0.85, p < 0.0001) and decreased BMI (OR = 0.95, 95% CI = 0.93-0.96, p < 0.0001), ensuring the effectiveness of selected IVs. We found favorable evidence to support the protective effect of GLP1R agonism on HF (OR = 0.75, 95% CI = 0.71-0.79, p < 0.0001), but there was no obvious correlation with increased LVEF (OR = 1.01, 95% CI = 0.95-1.06, p = 0.8332). Among the six blood lipids, only low-density lipoprotein cholesterol (LDL-C) was both associated with GLP1R agonism and HF. The causal effect of GLP1R agonism on HF was partially mediated through LDL-C by 4.23% of the total effect (95% CI = 1.04-7.42%, p = 0.0093). CONCLUSIONS This study supported the causal relationships of GLP1R agonists with a reduced risk of HF. LDL-C might be the mediator in this association, highlighting the cardiometabolic benefit of GLP1R agonists on HF.
Collapse
Affiliation(s)
- Tianshi Mao
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, 100700, China
| | - Jie Chen
- The First Affiliated Hospital of Anhui Medical University, Hefei, 230032, China
| | - Tong Su
- Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, 100078, China
| | - Long Xie
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, 100700, China
| | - Xinyan Qu
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, 100700, China
| | - Ruli Feng
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, 100700, China
| | - Yi Pan
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, 100700, China
| | - Jie Wan
- Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, 100078, China
| | - Xiaoyun Cui
- Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, 100078, China
| | - Wenhao Jia
- Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, 100029, China
| | - Qun Gao
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, 100700, China.
| | - Qian Lin
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, 100700, China.
| |
Collapse
|
43
|
Ma X, Chang L, Li S, Gu Y, Wan J, Sang H, Ding L, Liu M, He Q. Genetic associations of birthweight, childhood, and adult BMI with metabolic dysfunction-associated steatotic liver disease: a Mendelian randomization. BMC Gastroenterol 2024; 24:291. [PMID: 39198755 PMCID: PMC11351507 DOI: 10.1186/s12876-024-03383-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2024] [Accepted: 08/23/2024] [Indexed: 09/01/2024] Open
Abstract
PURPOSE The causal relationship between life course adiposity with metabolic dysfunction-associated steatotic liver disease (MASLD) is ambiguous. We aimed to investigate whether there is an independent genetic causal relationship between body size at various life course and MASLD. METHODS We performed univariable and multivariable Mendelian randomization (MR) to estimate the causal effect of body size at different life stages on MASLD (i.e., defined by the clinical comprehensive diagnosis from the electronic health record [HER] codes [ICD9/ICD10] or diagnostic phrases), including birthweight, childhood body mass index (BMI), adult BMI, waist circumference (WC), waist-to-hip ratio (WHR), body fat percentage (BFP). RESULTS In univariate analyses, higher genetically predicted lower birthweight (ORIVW = 0.61, 95%CI, 0.52 to 0.74), Childhood BMI ( ORIVW = 1.37, 95%CI, 1.12 to 1.64), and adult BMI (ORIVW = 1.41, 95%CI, 1.27 to 1.57) was significantly associated with subsequent risk of MASLD after Bonferroni correction. The MVMR analysis demonstrated compelling proof that birthweight and adult BMI had a direct causal relationship with MASLD. However, after adjusting for birthweight and adult BMI, the direct causal relationship between childhood BMI and MASLD disappeared. CONCLUSION For the first time, this MR elucidated new evidence for the effect of life course adiposity on MASLD risk, providing lower birthweight and duration of obesity are independent risk factors for MASLD. Our findings indicated that weight management during distinct time periods plays a significant role in the prevention and treatment of MASLD.
Collapse
Affiliation(s)
- Xiaohui Ma
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China
| | - Lina Chang
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China
| | - Shuo Li
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China
| | - Yian Gu
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China
| | - Jieying Wan
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China
| | - Hequn Sang
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China
| | - Li Ding
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China.
| | - Ming Liu
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China.
| | - Qing He
- Department of Endocrinology and Metabolism, Tianjin Medical University Genaral Hospital, 154 Anshan Road, Heping District, 300052, Tianjin, Tianjin, China.
| |
Collapse
|
44
|
Cameron D, Vinh NN, Prapaiwongs P, Perry EA, Walters JTR, Li M, O’Donovan MC, Bray NJ. Genetic Implication of Prenatal GABAergic and Cholinergic Neuron Development in Susceptibility to Schizophrenia. Schizophr Bull 2024; 50:1171-1184. [PMID: 38869145 PMCID: PMC11349020 DOI: 10.1093/schbul/sbae083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/14/2024]
Abstract
BACKGROUND The ganglionic eminences (GE) are fetal-specific structures that give rise to gamma-aminobutyric acid (GABA)- and acetylcholine-releasing neurons of the forebrain. Given the evidence for GABAergic, cholinergic, and neurodevelopmental disturbances in schizophrenia, we tested the potential involvement of GE neuron development in mediating genetic risk for the condition. STUDY DESIGN We combined data from a recent large-scale genome-wide association study of schizophrenia with single-cell RNA sequencing data from the human GE to test the enrichment of schizophrenia risk variation in genes with high expression specificity for developing GE cell populations. We additionally performed the single nuclei Assay for Transposase-Accessible Chromatin with Sequencing (snATAC-Seq) to map potential regulatory genomic regions operating in individual cell populations of the human GE, using these to test for enrichment of schizophrenia common genetic variant liability and to functionally annotate non-coding variants-associated with the disorder. STUDY RESULTS Schizophrenia common variant liability was enriched in genes with high expression specificity for developing neuron populations that are predicted to form dopamine D1 and D2 receptor-expressing GABAergic medium spiny neurons of the striatum, cortical somatostatin-positive GABAergic interneurons, calretinin-positive GABAergic neurons, and cholinergic neurons. Consistent with these findings, schizophrenia genetic risk was concentrated in predicted regulatory genomic sequence mapped in developing neuronal populations of the GE. CONCLUSIONS Our study implicates prenatal development of specific populations of GABAergic and cholinergic neurons in later susceptibility to schizophrenia, and provides a map of predicted regulatory genomic elements operating in cells of the GE.
Collapse
Affiliation(s)
- Darren Cameron
- Division of Psychological Medicine and Clinical Neurosciences, Centre for Neuropsychiatric Genetics & Genomics, Cardiff University, Cardiff, UK
| | - Ngoc-Nga Vinh
- Division of Psychological Medicine and Clinical Neurosciences, Centre for Neuropsychiatric Genetics & Genomics, Cardiff University, Cardiff, UK
| | - Parinda Prapaiwongs
- Neuroscience and Mental Health Innovation Institute, Cardiff University, Cardiff, UK
| | - Elizabeth A Perry
- Division of Psychological Medicine and Clinical Neurosciences, Centre for Neuropsychiatric Genetics & Genomics, Cardiff University, Cardiff, UK
| | - James T R Walters
- Division of Psychological Medicine and Clinical Neurosciences, Centre for Neuropsychiatric Genetics & Genomics, Cardiff University, Cardiff, UK
| | - Meng Li
- Division of Psychological Medicine and Clinical Neurosciences, Centre for Neuropsychiatric Genetics & Genomics, Cardiff University, Cardiff, UK
- Neuroscience and Mental Health Innovation Institute, Cardiff University, Cardiff, UK
| | - Michael C O’Donovan
- Division of Psychological Medicine and Clinical Neurosciences, Centre for Neuropsychiatric Genetics & Genomics, Cardiff University, Cardiff, UK
| | - Nicholas J Bray
- Division of Psychological Medicine and Clinical Neurosciences, Centre for Neuropsychiatric Genetics & Genomics, Cardiff University, Cardiff, UK
- Neuroscience and Mental Health Innovation Institute, Cardiff University, Cardiff, UK
| |
Collapse
|
45
|
Saliba-Gustafsson P, Justesen JM, Ranta A, Sharma D, Bielczyk-Maczynska E, Li J, Najmi LA, Apodaka M, Aspichueta P, Björck HM, Eriksson P, Schurr TM, Franco-Cereceda A, Gloudemans M, Mujica E, den Hoed M, Assimes TL, Quertermous T, Carcamo-Orive I, Park CY, Knowles JW. A functional genomic framework to elucidate novel causal metabolic dysfunction-associated fatty liver disease genes. Hepatology 2024:01515467-990000000-01007. [PMID: 39190705 DOI: 10.1097/hep.0000000000001066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Accepted: 07/28/2024] [Indexed: 08/29/2024]
Abstract
BACKGROUND AND AIMS Metabolic dysfunction-associated fatty liver disease (MASLD) is the most prevalent chronic liver pathology in western countries, with serious public health consequences. Efforts to identify causal genes for MASLD have been hampered by the relative paucity of human data from gold standard magnetic resonance quantification of hepatic fat. To overcome insufficient sample size, genome-wide association studies using MASLD surrogate phenotypes have been used, but only a small number of loci have been identified to date. In this study, we combined genome-wide association studies of MASLD composite surrogate phenotypes with genetic colocalization studies followed by functional in vitro screens to identify bona fide causal genes for MASLD. APPROACH AND RESULTS We used the UK Biobank to explore the associations of our novel MASLD score, and genetic colocalization to prioritize putative causal genes for in vitro validation. We created a functional genomic framework to study MASLD genes in vitro using CRISPRi. Our data identify VKORC1 , TNKS , LYPLAL1 , and GPAM as regulators of lipid accumulation in hepatocytes and suggest the involvement of VKORC1 in the lipid storage related to the development of MASLD. CONCLUSIONS Complementary genetic and genomic approaches are useful for the identification of MASLD genes. Our data supports VKORC1 as a bona fide MASLD gene. We have established a functional genomic framework to study at scale putative novel MASLD genes from human genetic association studies.
Collapse
Affiliation(s)
- Peter Saliba-Gustafsson
- Department of Medicine, Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, California, USA
- CardioMetabolic Unit, Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden
- Department of Medicine, Stanford Diabetes Research Center, Stanford University, California, USA
- Stanford Cardiovascular Institute, Stanford School of Medicine, Stanford University, California, USA
| | - Johanne M Justesen
- Department of Medicine, Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, California, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Denmark
| | - Amanda Ranta
- Department of Medicine, Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, California, USA
- Department of Medicine, Stanford Diabetes Research Center, Stanford University, California, USA
- Stanford Cardiovascular Institute, Stanford School of Medicine, Stanford University, California, USA
| | - Disha Sharma
- Department of Medicine, Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, California, USA
- Stanford Cardiovascular Institute, Stanford School of Medicine, Stanford University, California, USA
| | - Ewa Bielczyk-Maczynska
- Department of Medicine, Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, California, USA
- Department of Medicine, Stanford Diabetes Research Center, Stanford University, California, USA
- Stanford Cardiovascular Institute, Stanford School of Medicine, Stanford University, California, USA
- The Hormel Institute, University of Minnesota, Minneapolis, Minnesota, USA
| | - Jiehan Li
- Department of Medicine, Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, California, USA
- Department of Medicine, Stanford Diabetes Research Center, Stanford University, California, USA
- Stanford Cardiovascular Institute, Stanford School of Medicine, Stanford University, California, USA
| | - Laeya A Najmi
- Department of Medicine, Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, California, USA
- Department of Medicine, Stanford Diabetes Research Center, Stanford University, California, USA
- Stanford Cardiovascular Institute, Stanford School of Medicine, Stanford University, California, USA
| | - Maider Apodaka
- Department of Physiology, University of the Basque Country (UPV/EHU), Faculty of Medicine and Nursing, Leioa, Spain
| | - Patricia Aspichueta
- Department of Physiology, University of the Basque Country (UPV/EHU), Faculty of Medicine and Nursing, Leioa, Spain
- National Institute for the Study of Liver and Gastrointestinal Diseases (CIBERehd, Instituto de Salud Carlos III)
| | - Hanna M Björck
- Department of Medicine, Division of Cardiovascular Medicine, Centre for Molecular Medicine, Karolinska Inistitutet, Stockholm, Karolinska University Hospital, Solna, Sweden
| | - Per Eriksson
- Department of Medicine, Division of Cardiovascular Medicine, Centre for Molecular Medicine, Karolinska Inistitutet, Stockholm, Karolinska University Hospital, Solna, Sweden
| | - Theresia M Schurr
- Department of Medicine, Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, California, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Denmark
| | | | - Mike Gloudemans
- Department of Pathology, Stanford University School of Medicine, CA, USA
| | - Endrina Mujica
- Department of Immunology, Genetics and Pathology, Uppsala University, Sweden
| | - Marcel den Hoed
- Department of Immunology, Genetics and Pathology, Uppsala University, Sweden
| | - Themistocles L Assimes
- Department of Medicine, Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, California, USA
- VA Palo Alto Health Care System, Palo Alto, California, USA
| | - Thomas Quertermous
- Department of Medicine, Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, California, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Denmark
| | - Ivan Carcamo-Orive
- Department of Medicine, Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, California, USA
- Department of Endocrinology, Metabolism, Nutrition, and Kidney Disease, Biobizkaia Health Research Institute, Cruces, Spain
- IKERBASQUE, Basque Foundation for Science, Bilbao, Spain
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (UPV/EHU), Leioa, Spain
| | - Chong Y Park
- Department of Medicine, Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, California, USA
| | - Joshua W Knowles
- Department of Medicine, Division of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, Stanford, California, USA
- Department of Medicine, Stanford Diabetes Research Center, Stanford University, California, USA
- Stanford Cardiovascular Institute, Stanford School of Medicine, Stanford University, California, USA
- Stanford Prevention Research Center, Stanford, California, USA
| |
Collapse
|
46
|
Du Y, Qi L, Borné Y, Sonestedt E. Adulthood weight changes, body mass index in youth, genetic susceptibility and risk of atrial fibrillation: a population-based cohort study. BMC Med 2024; 22:345. [PMID: 39183287 PMCID: PMC11346199 DOI: 10.1186/s12916-024-03565-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Accepted: 08/15/2024] [Indexed: 08/27/2024] Open
Abstract
BACKGROUND Epidemiological evidence on weight change and atrial fibrillation (AF) remains limited and inconsistent. Previous studies on body mass index (BMI) in youth and AF rarely considered subsequent BMI. This study aimed to assess the associations of AF with weight change and BMI in youth, as well as modified effect by genetic susceptibility of AF. METHODS The study included 21,761 individuals (mean age 57.8 years) from the Malmö Diet and Cancer cohort. Weight information was obtained at three time points, including recalled weight at age 20 years, measured weight at baseline (middle adulthood), and reported weight at 5-year follow-up examination (late middle adulthood). A weighted genetic risk score of AF was created using 134 variants. RESULTS During a median follow-up of 23.2 years, a total of 4038 participants developed AF. The association between weight change from early to middle adulthood and AF risk was modified by sex (Pinteraction = 0.004); weight loss was associated with a lower AF risk in females, but not in males. Conversely, weight gain was positively associated with AF risk in a linear manner in females, whereas increased AF risk appeared only when weight gain exceeded a threshold in males. Participants with weight gain of > 5 kg from middle to late middle adulthood had a 19% higher risk of AF relative to those with stable weight, whereas weight loss showed a null association. Compared to individuals with a lower BMI at age 20 years, those with a BMI above 25 kg/m2 had an increased risk of AF (HR = 1.14; 95% CI: 1.02-1.28), after controlling for baseline BMI; this association was more pronounced in males or those with a lower genetic risk of AF. CONCLUSIONS Weight gain in middle adulthood was associated with higher AF risk. Weight loss from early to middle adulthood, but not from middle to late middle adulthood, was associated with a lower risk of AF only in females. Higher BMI in youth was associated with an increased risk of AF, particularly among males or those with a lower genetic risk of AF.
Collapse
Affiliation(s)
- Yufeng Du
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, Lanzhou, Gansu, China.
- Nutritional Epidemiology, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden.
| | - Lu Qi
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yan Borné
- Nutritional Epidemiology, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Emily Sonestedt
- Nutritional Epidemiology, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden.
- Department of Food and Meal Science and the Research Environment MEAL, Faculty of Natural Science, Kristianstad University, Kristianstad, Sweden.
| |
Collapse
|
47
|
Deng Z, Graff RE, Batai K, Chung BI, Langston ME, Kachuri L. Polygenic score for body mass index in relation to mortality among patients with renal cell cancer. Int J Obes (Lond) 2024:10.1038/s41366-024-01609-0. [PMID: 39152336 DOI: 10.1038/s41366-024-01609-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 08/02/2024] [Accepted: 08/08/2024] [Indexed: 08/19/2024]
Abstract
BACKGROUND The association between body mass index (BMI) and mortality among individuals with renal cell cancer (RCC) is debated, with some observational studies suggesting a lower mortality associated with higher BMI. However, methodological issues such as confounding and reverse causation may bias these findings. Using BMI-associated genetic variants can avoid these biases and generate more valid estimates. METHODS In this prospective cohort study, we included 1264 RCC patients (446 deaths) from the UK Biobank. We created a BMI polygenic score (PGS) based on 336 BMI-associated genetic variants. The association between the PGS and mortality (all-cause and RCC-specific) was evaluated by logistic regression (all RCC cases) and Cox regression (906 incident cases). For comparison, the associations of measured pre-diagnostic BMI and waist-to-hip ratio (WHR) with mortality were quantified by Cox regression among incident cases. We stratified these analyses by time between anthropometric measurement and RCC diagnosis to assess the influence of reverse causation. RESULTS We did not observe an association between the BMI PGS and all-cause mortality among RCC patients (hazard ratio (HR) per SD increase = 0.98, 95% CI: 0.88,1.10). No association was found for pre-diagnostic BMI (HR per 5 kg/m2 increase = 0.93, 95% CI: 0.83,1.04) or WHR (HR per 0.1 increase = 0.97, 95% CI: 0.83,1.13) with mortality. In patients with anthropometrics measured within 2 years before RCC diagnosis, we observed associations of higher BMI (HR per 5 kg/m2 = 0.76, 95% CI: 0.59,0.98) and WHR (HR = 0.67 per 0.1 increase, 95% CI: 0.45,0.98) with a lower risk of death. Similar patterns were observed for RCC-specific mortality. CONCLUSION We found no association between either genetic variants for high BMI or measured pre-diagnostic body adiposity and mortality among RCC patients, and our results suggested a role for reverse causation in the association of obesity with lower mortality. Future studies should be designed carefully to produce unbiased estimates that account for confounding and reverse causation.
Collapse
Affiliation(s)
- Zhengyi Deng
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA.
| | - Rebecca E Graff
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Ken Batai
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Benjamin I Chung
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
| | - Marvin E Langston
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
| | - Linda Kachuri
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
| |
Collapse
|
48
|
Wang F, Chen L, Nie M, Li Z. Integrative analysis of causal associations between neurodegenerative diseases and colorectal cancer. Heliyon 2024; 10:e35432. [PMID: 39170445 PMCID: PMC11336615 DOI: 10.1016/j.heliyon.2024.e35432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 07/24/2024] [Accepted: 07/29/2024] [Indexed: 08/23/2024] Open
Abstract
Background Observational studies have shown that the correlation between neurodegenerative diseases and colorectal cancer (CRC) remains controversial. Therefore, this study aimed to verify the causal association between these two diseases. Methods Mendelian randomization (MR) analysis was used to assess the causal relationships between five major neurodegenerative diseases and CRC. Multivariable MR (MVMR) analysis was conducted to assess the direct causal effect of neurodegenerative diseases on CRC. Colocalization and pathway enrichment analyses were conducted to further elucidate our results. Sensitivity analysis was conducted to assess the robustness of the results. Results Genetically predicted Alzheimer's disease (AD) nominally increased CRC risk (OR = 1.0620, 95%CI = 1.0127-1.1136, P = 0.013). There was no causal effect of genetically predicted CRC on neurodegenerative diseases. Furthermore, we demonstrated that genetically predicted AD marginally increased colon cancer risk (OR = 1.1621, 95%CI = 1.0267-1.3153, P = 0.017). Genetically predicted Lewy body dementia (LBD) had a significant causal effect on the increasing risk of colon cancer (IVW OR = 1.1779, 95%CI = 1.0694-1.2975, P = 0.001). MVMR indicated that effect of AD on colon cancer was driven by LBD, type 2 diabetes, body mass index, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglyceride, total cholesterol (TC), processed meat consumption, smoking, alcohol consumption, and educational attainment, whereas the effect of LBD on colon cancer was only influenced by TC. Colocalization and pathway enrichment analysis suggested that LBD and colon cancer possibly shared causal variants (nearby gene APOE), and ERBB4 signaling and lipid metabolism may mediate the causal association between LBD and colon cancer. Sensitivity analysis confirmed the reliability of our findings. Conclusions Our study demonstrated that genetic vulnerabilities to AD nominally increased the overall risk of CRC and colon cancer. Genetically predicted LBD indicated an elevated risk of colon cancer, potentially linked to ERBB4 signaling and lipid metabolism.
Collapse
Affiliation(s)
- Feifan Wang
- Gastrointestinal Disease Diagnosis and Treatment Center, The First Hospital of Hebei Medical University, Shijiazhuang, 050000, China
| | - Lu Chen
- Department of Medical Oncology and Radiation Sickness, Peking University Third Hospital, Beijing, 100191, China
| | - Mengke Nie
- Department of General Practice, Huaihe Hospital of Henan University, Kaifeng, 475000, China
| | - Zhongxin Li
- Gastrointestinal Disease Diagnosis and Treatment Center, The First Hospital of Hebei Medical University, Shijiazhuang, 050000, China
| |
Collapse
|
49
|
Wu C, Yang F, Zhong H, Hong J, Lin H, Zong M, Ren H, Zhao S, Chen Y, Shi Z, Wang X, Shen J, Wang Q, Ni M, Chen B, Cai Z, Zhang M, Cao Z, Wu K, Gao A, Li J, Liu C, Xiao M, Li Y, Shi J, Zhang Y, Xu X, Gu W, Bi Y, Ning G, Wang W, Wang J, Liu R. Obesity-enriched gut microbe degrades myo-inositol and promotes lipid absorption. Cell Host Microbe 2024; 32:1301-1314.e9. [PMID: 38996548 DOI: 10.1016/j.chom.2024.06.012] [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] [Received: 11/29/2023] [Revised: 04/29/2024] [Accepted: 06/14/2024] [Indexed: 07/14/2024]
Abstract
Numerous studies have reported critical roles for the gut microbiota in obesity. However, the specific microbes that causally contribute to obesity and the underlying mechanisms remain undetermined. Here, we conducted shotgun metagenomic sequencing in a Chinese cohort of 631 obese subjects and 374 normal-weight controls and identified a Megamonas-dominated, enterotype-like cluster enriched in obese subjects. Among this cohort, the presence of Megamonas and polygenic risk exhibited an additive impact on obesity. Megamonas rupellensis possessed genes for myo-inositol degradation, as demonstrated in vitro and in vivo, and the addition of myo-inositol effectively inhibited fatty acid absorption in intestinal organoids. Furthermore, mice colonized with M. rupellensis or E. coli heterologously expressing the myo-inositol-degrading iolG gene exhibited enhanced intestinal lipid absorption, thereby leading to obesity. Altogether, our findings uncover roles for M. rupellensis as a myo-inositol degrader that enhances lipid absorption and obesity, suggesting potential strategies for future obesity management.
Collapse
Affiliation(s)
- Chao Wu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Fangming Yang
- BGI Research, Shenzhen 518083, China; Institute of Intelligent Medical Research (IIMR), BGI Genomics, Shenzhen 518083, China
| | - Huanzi Zhong
- BGI Research, Shenzhen 518083, China; Institute of Intelligent Medical Research (IIMR), BGI Genomics, Shenzhen 518083, China
| | - Jie Hong
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huibin Lin
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Mingxi Zong
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huahui Ren
- BGI Research, Shenzhen 518083, China; Institute of Intelligent Medical Research (IIMR), BGI Genomics, Shenzhen 518083, China
| | - Shaoqian Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yufei Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhun Shi
- BGI Research, Shenzhen 518083, China; Institute of Intelligent Medical Research (IIMR), BGI Genomics, Shenzhen 518083, China
| | - Xingyu Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Juan Shen
- BGI Research, Shenzhen 518083, China
| | - Qiaoling Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Mengshan Ni
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Banru Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhongle Cai
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Minchun Zhang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhiwen Cao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Kui Wu
- BGI Research, Shenzhen 518083, China; Institute of Intelligent Medical Research (IIMR), BGI Genomics, Shenzhen 518083, China; Guangdong Provincial Key Laboratory of Human Disease Genomics, Shenzhen Key Laboratory of Genomics, BGI Research, Shenzhen 518083, China
| | - Aibo Gao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Junhua Li
- BGI Research, Shenzhen 518083, China
| | - Cong Liu
- BGI Research, Shenzhen 518083, China
| | | | - Yan Li
- BGI Research, Shenzhen 518083, China
| | - Juan Shi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yifei Zhang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xun Xu
- BGI Research, Shenzhen 518083, China
| | - Weiqiong Gu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yufang Bi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Jiqiu Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Ruixin Liu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| |
Collapse
|
50
|
Li K, Leng Y, Lei D, Zhang H, Ding M, Lo WLA. Causal link between metabolic related factors and osteoarthritis: a Mendelian randomization investigation. Front Nutr 2024; 11:1424286. [PMID: 39206315 PMCID: PMC11349640 DOI: 10.3389/fnut.2024.1424286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2024] [Accepted: 07/22/2024] [Indexed: 09/04/2024] Open
Abstract
Introduction Metabolic syndrome (MetS) is significantly associated with osteoarthritis (OA), especially in MetS patients with blood glucose abnormalities, such as elevated fasting blood glucose (FG), which may increase OA risk. Dietary modifications, especially the intake of polyunsaturated fatty acids (PUFAs), are regarded as a potential means of preventing MetS and its complications. However, regarding the effects of FG, Omega-3s, and Omega-6s on OA, the research conclusions are conflicting, which is attributed to the complexity of the pathogenesis of OA. Therefore, it is imperative to thoroughly evaluate multiple factors to fully understand their role in OA, which needs further exploration and clarification. Methods Two-sample univariable Mendelian randomization (UVMR) and multivariable Mendelian randomization (MVMR) were employed to examine the causal effect of metabolic related factors on hip OA (HOA) or knee OA (KOA). The exposure and outcome datasets were obtained from Open GWAS IEU. All cases were independent European ancestry data. Three MR methods were performed to estimate the causal effect: inverse-variance weighting (IVW), weighted median method (WMM), and MR-Egger regression. Additionally, the intercept analysis in MR-Egger regression is used to estimate pleiotropy, and the IVW method and MR-Egger regression are used to test the heterogeneity. Results The UVMR analysis revealed a causal relationship between FG and HOA. By MVMR analysis, the study discovered a significant link between FG (OR = 0.79, 95%CI: 0.64∼0.99, p = 0.036) and KOA after accounting for body mass index (BMI), age, and sex hormone-binding globulin (SHBG). However, no causal effects of FG on HOA were seen. Omega-3s and Omega-6s did not have a causal influence on HOA or KOA. No significant evidence of pleiotropy was identified. Discussion The MR investigation showed a protective effect of FG on KOA development but no causal relationship between FG and HOA. No causal effect of Omega-3s and Omega-6s on HOA and KOA was observed. Shared genetic overlaps might also exist between BMI and age, SHBG and PUFAs for OA development. This finding offers a novel insight into the treatment and prevention of KOA from glucose metabolism perspective. The FG cutoff value should be explored in the future, and consideration should be given to demonstrating the study in populations other than Europeans.
Collapse
Affiliation(s)
- Kai Li
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yan Leng
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Di Lei
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Haojie Zhang
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Minghui Ding
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Wai Leung Ambrose Lo
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Engineering and Technology Research Centre for Rehabilitation Medicine and Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| |
Collapse
|