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Li T, Yin L, Huang Y, Wang X, Wei Y, Wang Y, Yang S, Cunha GBDG, Liu F. Efficacy and safety of remimazolam versus propofol for intraoperative sedation during regional anesthesia: A phase II, multicenter, randomized, active-controlled, single-blind clinical trial. IBRAIN 2024; 10:134-145. [PMID: 38915947 PMCID: PMC11193864 DOI: 10.1002/ibra.12163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 05/19/2024] [Accepted: 05/19/2024] [Indexed: 06/26/2024]
Abstract
This study aimed to evaluate the efficacy and safety of remimazolam for intraoperative sedation during regional anesthesia. It was a phase II-multicenter, randomized, single-blind, parallel-group, active-controlled clinical trial (No. ChiCTR2100054956). From May 6, 2021 to July 4, 2021, patients were randomly enrolled from 17 hospitals in China. A total of 105 patients aged 18-65 years who underwent selective surgery under regional anesthesia were included. Patients received different sedatives with different dosages: 0.1 mg/kg remimazolam (HR), 0.05 mg/kg remimazolam (LR), or 1.0 mg/kg propofol (P) group, followed by a maintenance infusion. Main outcome measures included the efficacy of sedation measured by Modified Observer's Assessment of Alertness/Sedation Scale (MOAA/S) levels (1-4, 1-3, 2-3, 3, and 2-4) during the sedation procedure (the duration percentage) and incidence of adverse reactions. It showed that the duration percentage of MOAA/S levels 1-4 was 100.0 [8.1]% (median [interquartile range]), 89.9 [20.2]%, 100.0 [7.7]% in the HR, LR, and P groups, respectively. The percentage of patients in the HR, LR, and P groups who achieved MOAA/S levels 1-4 within 3 min after administration was 85.7%, 58.8%, and 82.9%, respectively. However, the time to recovery from anesthesia after withdrawal of sedatives (7.9 ± 5.7 min), incidence of anterograde amnesia (75%), and adverse effects were not statistically significant among the three groups. These findings suggest that a loading dose of remimazolam 0.1 mg/kg followed by a maintenance infusion of 0-3 mg/kg/h provides adequate sedation for patients under regional anesthesia without increasing adverse reactions.
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Affiliation(s)
- Ting‐Ting Li
- Department of AnesthesiologyWest China Hospital, Sichuan UniversityChengduSichuanChina
| | - Lu Yin
- Department of AnesthesiologyWest China Hospital, Sichuan UniversityChengduSichuanChina
- West China School of NursingSichuan UniversityChengduSichuanChina
| | - Yue‐Xin Huang
- Department of AnesthesiologyWest China Hospital, Sichuan UniversityChengduSichuanChina
| | - Xiu‐Hong Wang
- Department of AnesthesiologyWest China Hospital, Sichuan UniversityChengduSichuanChina
| | - Yan‐Huan Wei
- Graduate School of EducationBeijing Foreign Studies UniversityBeijingChina
| | - Yong Wang
- Division of Gastrointestinal Surgery, Department of General SurgeryWest China Hospital, Sichuan UniversityChengduSichuanChina
| | - Shi‐Wei Yang
- Division of Gastrointestinal Surgery, Department of General SurgeryWest China Hospital, Sichuan UniversityChengduSichuanChina
| | | | - Fei Liu
- Department of AnesthesiologyWest China Hospital, Sichuan UniversityChengduSichuanChina
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Hughes DA, Li-Gao R, Bull CJ, de Mutsert R, Rosendaal FR, Mook-Kanamori DO, Willems van Dijk K, Timpson NJ. The association between body mass index and metabolite response to a liquid mixed meal challenge: a Mendelian randomization study. Am J Clin Nutr 2024; 119:1354-1370. [PMID: 38494119 PMCID: PMC11130664 DOI: 10.1016/j.ajcnut.2024.03.009] [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: 10/09/2023] [Revised: 01/30/2024] [Accepted: 03/12/2024] [Indexed: 03/19/2024] Open
Abstract
BACKGROUND Metabolite abundance is a dynamic trait that varies in response to environmental stimuli and phenotypic traits, such as food consumption and body mass index (BMI, kg/m2). OBJECTIVES In this study, we used the Netherlands Epidemiology of Obesity (NEO) study data to identify observational and causal associations between BMI and metabolite response to a liquid meal. METHODS A liquid meal challenge was performed, and Nightingale Health metabolite profiles were collected in 5744 NEO participants. Observational and one-sample Mendelian randomization (MR) analysis were conducted to estimate the effect of BMI on metabolites (n = 229) in the fasting, postprandial, and response (or change in abundance) states. RESULTS We observed 473 associations with BMI (175 fasting, 188 postprandial, and 110 response) in observational analyses. In MR analyses, we observed 20 metabolite traits (5 fasting, 12 postprandial, and 3 response) to be associated with BMI. MR associations included the glucogenic amino acid alanine, which was inversely associated with BMI in the response state (β: -0.081; SE: 0.023; P = 5.91 × 10-4), suggesting that as alanine increased in postprandial abundance, that increase was attenuated with increasing BMI. CONCLUSIONS Overall, this study showed that MR estimates were strongly correlated with observational effect estimates, suggesting that the broad associations seen between BMI and metabolite variation has a causal underpinning. Specific effects in previously unassessed postprandial and response states are detected, and these may likely mark novel life course risk exposures driven by regular nutrition.
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Affiliation(s)
- David A Hughes
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Caroline J Bull
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands; Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands; Division of Endocrinology, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
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van der Ark-Vonk EM, Puijk MV, Pasterkamp G, van der Laan SW. The Effects of FABP4 on Cardiovascular Disease in the Aging Population. Curr Atheroscler Rep 2024; 26:163-175. [PMID: 38698167 PMCID: PMC11087245 DOI: 10.1007/s11883-024-01196-5] [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] [Accepted: 03/05/2024] [Indexed: 05/05/2024]
Abstract
PURPOSE OF REVIEW Fatty acid-binding protein 4 (FABP4) plays a role in lipid metabolism and cardiovascular health. In this paper, we cover FABP4 biology, its implications in atherosclerosis from observational studies, genetic factors affecting FABP4 serum levels, and ongoing drug development to target FABP4 and offer insights into future FABP4 research. RECENT FINDINGS FABP4 impacts cells through JAK2/STAT2 and c-kit pathways, increasing inflammatory and adhesion-related proteins. In addition, FABP4 induces angiogenesis and vascular smooth muscle cell proliferation and migration. FABP4 is established as a reliable predictive biomarker for cardiovascular disease in specific at-risk groups. Genetic studies robustly link PPARG and FABP4 variants to FABP4 serum levels. Considering the potential effects on atherosclerotic lesion development, drug discovery programs have been initiated in search for potent inhibitors of FABP4. Elevated FABP4 levels indicate an increased cardiovascular risk and is causally related to acceleration of atherosclerotic disease, However, clinical trials for FABP4 inhibition are lacking, possibly due to concerns about available compounds' side effects. Further research on FABP4 genetics and its putative causal role in cardiovascular disease is needed, particularly in aging subgroups.
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Affiliation(s)
- Ellen M van der Ark-Vonk
- Central Diagnostics Laboratory, Division Laboratory, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - Mike V Puijk
- Central Diagnostics Laboratory, Division Laboratory, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - Gerard Pasterkamp
- Central Diagnostics Laboratory, Division Laboratory, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - Sander W van der Laan
- Central Diagnostics Laboratory, Division Laboratory, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands.
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Sathyan S, Milman S, Ayers E, Gao T, Verghese J, Barzilai N. Plasma proteomic profile of abdominal obesity in older adults. Obesity (Silver Spring) 2024; 32:938-948. [PMID: 38439214 PMCID: PMC11039368 DOI: 10.1002/oby.24000] [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: 08/17/2023] [Revised: 12/30/2023] [Accepted: 01/07/2024] [Indexed: 03/06/2024]
Abstract
OBJECTIVE This study examines the plasma proteomic profile of abdominal obesity in older adults. METHODS The association of abdominal obesity (waist circumference [WC]) with 4265 plasma proteins identified using the SomaScan Assay was examined in 969 Ashkenazi Jewish participants (LonGenity cohort), aged 65 years and older (mean [SD] age 75.7 [6.7] years, 55.4% women), using regression models. Pathway analysis, as well as weighted correlation network analysis, was performed. WC was determined from the proteome using elastic net regression. RESULTS A total of 480 out of 4265 proteins were associated with WC in the linear regression model. Leptin (β [SE] = 12.363 [0.490]), inhibin β C chain (INHBC; β [SE] = 24.324 [1.448]), insulin-like growth factor-binding protein 2 (IGFBP-2; β [SE] = -12.782 [0.841]), heparan-sulfate 6-O-sulfotransferase 3 (H6ST3; β [SE] = -39.995 [2.729]), and matrix-remodeling-associated protein 8 (MXRA8; β [SE] = -27.101 [1.850]) were the top proteins associated with WC. Cell adhesion, extracellular matrix remodeling, and IGF transport pathways were the top enriched pathways associated with WC. WC signature determined from plasma proteins was highly correlated with measured WC (r = 0.80) and was associated with various metabolic and physical traits. CONCLUSIONS The study unveiled a multifaceted plasma proteomic profile of abdominal obesity in older adults, offering insights into its wide-ranging impact on the proteome. It also elucidated novel proteins, clusters of correlated proteins, and pathways that are intricately associated with abdominal obesity.
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Affiliation(s)
- Sanish Sathyan
- Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Sofiya Milman
- Institute for Aging Research, Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Emmeline Ayers
- Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Tina Gao
- Institute for Aging Research, Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Joe Verghese
- Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, USA
- Institute for Aging Research, Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Nir Barzilai
- Institute for Aging Research, Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
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Cao M, Cui B. Clinically relevant plasma proteome for adiposity depots: evidence from systematic mendelian randomization and colocalization analyses. Cardiovasc Diabetol 2024; 23:126. [PMID: 38614964 PMCID: PMC11016216 DOI: 10.1186/s12933-024-02222-1] [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: 01/31/2024] [Accepted: 03/31/2024] [Indexed: 04/15/2024] Open
Abstract
BACKGROUND The accumulation of visceral and ectopic fat comprise a major cause of cardiometabolic diseases. However, novel drug targets for reducing unnecessary visceral and ectopic fat are still limited. Our study aims to provide a comprehensive investigation of the causal effects of the plasma proteome on visceral and ectopic fat using Mendelian randomization (MR) approach. METHODS We performed two-sample MR analyses based on five large genome-wide association study (GWAS) summary statistics of 2656 plasma proteins, to screen for causal associations of these proteins with traits of visceral and ectopic fat in over 30,000 participants of European ancestry, as well as to assess mediation effects by risk factors of outcomes. The colocalization analysis was conducted to examine whether the identified proteins and outcomes shared casual variants. RESULTS Genetically predicted levels of 14 circulating proteins were associated with visceral and ectopic fat (P < 4.99 × 10- 5, at a Bonferroni-corrected threshold). Colocalization analysis prioritized ten protein targets that showed effect on outcomes, including FST, SIRT2, DNAJB9, IL6R, CTSA, RGMB, PNLIPRP1, FLT4, PPY and IL6ST. MR analyses revealed seven risk factors for visceral and ectopic fat (P < 0.0024). Furthermore, the associations of CTSA, DNAJB9 and IGFBP1 with primary outcomes were mediated by HDL-C and SHBG. Sensitivity analyses showed little evidence of pleiotropy. CONCLUSIONS Our study identified candidate proteins showing putative causal effects as potential therapeutic targets for visceral and ectopic fat accumulation and outlined causal pathways for further prevention of downstream cardiometabolic diseases.
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Affiliation(s)
- Min 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.
| | - Bin Cui
- 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
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Ponomarenko I, Pasenov K, Churnosova M, Sorokina I, Aristova I, Churnosov V, Ponomarenko M, Reshetnikova Y, Reshetnikov E, Churnosov M. Obesity-Dependent Association of the rs10454142 PPP1R21 with Breast Cancer. Biomedicines 2024; 12:818. [PMID: 38672173 PMCID: PMC11048332 DOI: 10.3390/biomedicines12040818] [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: 03/05/2024] [Revised: 03/30/2024] [Accepted: 04/02/2024] [Indexed: 04/28/2024] Open
Abstract
The purpose of this work was to find a link between the breast cancer (BC)-risk effects of sex hormone-binding globulin (SHBG)-associated polymorphisms and obesity. The study was conducted on a sample of 1498 women (358 BC; 1140 controls) who, depending on the presence/absence of obesity, were divided into two groups: obese (119 BC; 253 controls) and non-obese (239 BC; 887 controls). Genotyping of nine SHBG-associated single nucleotide polymorphisms (SNP)-rs17496332 PRMT6, rs780093 GCKR, rs10454142 PPP1R21, rs3779195 BAIAP2L1, rs440837 ZBTB10, rs7910927 JMJD1C, rs4149056 SLCO1B1, rs8023580 NR2F2, and rs12150660 SHBG-was executed, and the BC-risk impact of these loci was analyzed by logistic regression separately in each group of obese/non-obese women. We found that the BC-risk effect correlated by GWAS with the SHBG-level polymorphism rs10454142 PPP1R21 depends on the presence/absence of obesity. The SHBG-lowering allele C rs10454142 PPP1R21 has a risk value for BC in obese women (allelic model: CvsT, OR = 1.52, 95%CI = 1.10-2.11, and pperm = 0.013; additive model: CCvsTCvsTT, OR = 1.71, 95%CI = 1.15-2.62, and pperm = 0.011; dominant model: CC + TCvsTT, OR = 1.95, 95%CI = 1.13-3.37, and pperm = 0.017) and is not associated with the disease in women without obesity. SNP rs10454142 PPP1R21 and 10 proxy SNPs have adipose-specific regulatory effects (epigenetic modifications of promoters/enhancers, DNA interaction with 51 transcription factors, eQTL/sQTL effects on five genes (PPP1R21, RP11-460M2.1, GTF2A1L, STON1-GTF2A1L, and STON1), etc.), can be "likely cancer driver" SNPs, and are involved in cancer-significant pathways. In conclusion, our study detected an obesity-dependent association of the rs10454142 PPP1R21 with BC in women.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (I.P.); (K.P.); (M.C.); (I.S.); (I.A.); (V.C.); (M.P.); (Y.R.); (E.R.)
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Watts EL, Moore SC, Gunter MJ, Chatterjee N. Adiposity and cancer: meta-analysis, mechanisms, and future perspectives. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.16.24302944. [PMID: 38405761 PMCID: PMC10889047 DOI: 10.1101/2024.02.16.24302944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Obesity is a recognised risk factor for many cancers and with rising global prevalence, has become a leading cause of cancer. Here we summarise the current evidence from both population-based epidemiologic investigations and experimental studies on the role of obesity in cancer development. This review presents a new meta-analysis using data from 40 million individuals and reports positive associations with 19 cancer types. Utilising major new data from East Asia, the meta-analysis also shows that the strength of obesity and cancer associations varies regionally, with stronger relative risks for several cancers in East Asia. This review also presents current evidence on the mechanisms linking obesity and cancer and identifies promising future research directions. These include the use of new imaging data to circumvent the methodological issues involved with body mass index and the use of omics technologies to resolve biologic mechanisms with greater precision and clarity.
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Affiliation(s)
- Eleanor L Watts
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Shady Grove, MD, USA
| | - Steven C Moore
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Shady Grove, MD, USA
| | - Marc J Gunter
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Nilanjan Chatterjee
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA
- Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, USA
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Bull CJ, Hazelwood E, Legge DN, Corbin LJ, Richardson TG, Lee M, Yarmolinsky J, Smith-Byrne K, Hughes DA, Johansson M, Peters U, Berndt SI, Brenner H, Burnett-Hartman A, Cheng I, Kweon SS, Le Marchand L, Li L, Newcomb PA, Pearlman R, McConnachie A, Welsh P, Taylor R, Lean MEJ, Sattar N, Murphy N, Gunter MJ, Timpson NJ, Vincent EE. Impact of weight loss on cancer-related proteins in serum: results from a cluster randomised controlled trial of individuals with type 2 diabetes. EBioMedicine 2024; 100:104977. [PMID: 38290287 PMCID: PMC10844806 DOI: 10.1016/j.ebiom.2024.104977] [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: 07/19/2023] [Revised: 01/03/2024] [Accepted: 01/06/2024] [Indexed: 02/01/2024] Open
Abstract
BACKGROUND Type 2 diabetes is associated with higher risk of several cancer types. However, the biological intermediates driving this relationship are not fully understood. As novel interventions for treating and managing type 2 diabetes become increasingly available, whether they also disrupt the pathways leading to increased cancer risk is currently unknown. We investigated the effect of a type 2 diabetes intervention, in the form of intentional weight loss, on circulating proteins associated with cancer risk to gain insight into potential mechanisms linking type 2 diabetes and adiposity with cancer development. METHODS Fasting serum samples from participants with diabetes enrolled in the Diabetes Remission Clinical Trial (DiRECT) receiving the Counterweight-Plus weight-loss programme (intervention, N = 117, mean weight-loss 10 kg, 46% diabetes remission) or best-practice care by guidelines (control, N = 143, mean weight-loss 1 kg, 4% diabetes remission) were subject to proteomic analysis using the Olink Oncology-II platform (48% of participants were female; 52% male). To identify proteins which may be altered by the weight-loss intervention, the difference in protein levels between groups at baseline and 1 year was examined using linear regression. Mendelian randomization (MR) was performed to extend these results to evaluate cancer risk and elucidate possible biological mechanisms linking type 2 diabetes and cancer development. MR analyses were conducted using independent datasets, including large cancer meta-analyses, UK Biobank, and FinnGen, to estimate potential causal relationships between proteins modified during intentional weight loss and the risk of colorectal, breast, endometrial, gallbladder, liver, and pancreatic cancers. FINDINGS Nine proteins were modified by the intervention: glycoprotein Nmb; furin; Wnt inhibitory factor 1; toll-like receptor 3; pancreatic prohormone; erb-b2 receptor tyrosine kinase 2; hepatocyte growth factor; endothelial cell specific molecule 1 and Ret proto-oncogene (Holm corrected P-value <0.05). Mendelian randomization analyses indicated a causal relationship between predicted circulating furin and glycoprotein Nmb on breast cancer risk (odds ratio (OR) = 0.81, 95% confidence interval (CI) = 0.67-0.99, P-value = 0.03; and OR = 0.88, 95% CI = 0.78-0.99, P-value = 0.04 respectively), though these results were not supported in sensitivity analyses examining violations of MR assumptions. INTERPRETATION Intentional weight loss among individuals with recently diagnosed diabetes may modify levels of cancer-related proteins in serum. Further evaluation of the proteins identified in this analysis could reveal molecular pathways that mediate the effect of adiposity and type 2 diabetes on cancer risk. FUNDING The main sources of funding for this work were Diabetes UK, Cancer Research UK, World Cancer Research Fund, and Wellcome.
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Affiliation(s)
- Caroline J Bull
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; School of Translational Health Sciences, Dorothy Hodgkin Building, University of Bristol, Bristol, UK
| | - Emma Hazelwood
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Danny N Legge
- School of Translational Health Sciences, Dorothy Hodgkin Building, University of Bristol, Bristol, UK
| | - Laura J Corbin
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tom G Richardson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Matthew Lee
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, WHO, Lyon, France
| | - James Yarmolinsky
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Karl Smith-Byrne
- Cancer Epidemiology Unit, Oxford Population Health, University of Oxford, UK
| | - David A Hughes
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Mattias Johansson
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, WHO, Lyon, France
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany; German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Iona Cheng
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Sun-Seog Kweon
- Department of Preventive Medicine, Chonnam National University Medical School, Gwangju, Korea; Jeonnam Regional Cancer Center, Chonnam National University Hwasun Hospital, Hwasun, Korea
| | | | - Li Li
- Department of Family Medicine, University of Virginia, Charlottesville, VA, USA
| | - Polly A Newcomb
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA; School of Public Health, University of Washington, Seattle, WA, USA
| | - Rachel Pearlman
- Division of Human Genetics, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Alex McConnachie
- Robertson Centre for Biostatistics, Institute of Health and Wellbeing, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Paul Welsh
- School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
| | - Roy Taylor
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Mike E J Lean
- Human Nutrition, School of Medicine, Dentistry and Nursing, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, UK
| | - Naveed Sattar
- School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
| | - Neil Murphy
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, WHO, Lyon, France
| | - Marc J Gunter
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, WHO, Lyon, France; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Emma E Vincent
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; School of Translational Health Sciences, Dorothy Hodgkin Building, University of Bristol, Bristol, UK.
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9
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Drouard G, Hagenbeek FA, Whipp AM, Pool R, Hottenga JJ, Jansen R, Hubers N, Afonin A, Willemsen G, de Geus EJC, Ripatti S, Pirinen M, Kanninen KM, Boomsma DI, van Dongen J, Kaprio J. Longitudinal multi-omics study reveals common etiology underlying association between plasma proteome and BMI trajectories in adolescent and young adult twins. BMC Med 2023; 21:508. [PMID: 38129841 PMCID: PMC10740308 DOI: 10.1186/s12916-023-03198-7] [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: 07/03/2023] [Accepted: 11/27/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND The influence of genetics and environment on the association of the plasma proteome with body mass index (BMI) and changes in BMI remains underexplored, and the links to other omics in these associations remain to be investigated. We characterized protein-BMI trajectory associations in adolescents and adults and how these connect to other omics layers. METHODS Our study included two cohorts of longitudinally followed twins: FinnTwin12 (N = 651) and the Netherlands Twin Register (NTR) (N = 665). Follow-up comprised 4 BMI measurements over approximately 6 (NTR: 23-27 years old) to 10 years (FinnTwin12: 12-22 years old), with omics data collected at the last BMI measurement. BMI changes were calculated in latent growth curve models. Mixed-effects models were used to quantify the associations between the abundance of 439 plasma proteins with BMI at blood sampling and changes in BMI. In FinnTwin12, the sources of genetic and environmental variation underlying the protein abundances were quantified by twin models, as were the associations of proteins with BMI and BMI changes. In NTR, we investigated the association of gene expression of genes encoding proteins identified in FinnTwin12 with BMI and changes in BMI. We linked identified proteins and their coding genes to plasma metabolites and polygenic risk scores (PRS) applying mixed-effects models and correlation networks. RESULTS We identified 66 and 14 proteins associated with BMI at blood sampling and changes in BMI, respectively. The average heritability of these proteins was 35%. Of the 66 BMI-protein associations, 43 and 12 showed genetic and environmental correlations, respectively, including 8 proteins showing both. Similarly, we observed 7 and 3 genetic and environmental correlations between changes in BMI and protein abundance, respectively. S100A8 gene expression was associated with BMI at blood sampling, and the PRG4 and CFI genes were associated with BMI changes. Proteins showed strong connections with metabolites and PRSs, but we observed no multi-omics connections among gene expression and other omics layers. CONCLUSIONS Associations between the proteome and BMI trajectories are characterized by shared genetic, environmental, and metabolic etiologies. We observed few gene-protein pairs associated with BMI or changes in BMI at the proteome and transcriptome levels.
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Affiliation(s)
- Gabin Drouard
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
| | - Fiona A Hagenbeek
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Alyce M Whipp
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Rick Jansen
- Department of Psychiatry, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, The Netherlands
| | - Nikki Hubers
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, The Netherlands
| | - Aleksei Afonin
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Katja M Kanninen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, The Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, The Netherlands
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
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10
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Goudswaard LJ, Smith ML, Hughes DA, Taylor R, Lean M, Sattar N, Welsh P, McConnachie A, Blazeby JM, Rogers CA, Suhre K, Zaghlool SB, Hers I, Timpson NJ, Corbin LJ. Using trials of caloric restriction and bariatric surgery to explore the effects of body mass index on the circulating proteome. Sci Rep 2023; 13:21077. [PMID: 38030643 PMCID: PMC10686974 DOI: 10.1038/s41598-023-47030-x] [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: 07/11/2023] [Accepted: 11/08/2023] [Indexed: 12/01/2023] Open
Abstract
Thousands of proteins circulate in the bloodstream; identifying those which associate with weight and intervention-induced weight loss may help explain mechanisms of diseases associated with adiposity. We aimed to identify consistent protein signatures of weight loss across independent studies capturing changes in body mass index (BMI). We analysed proteomic data from studies implementing caloric restriction (Diabetes Remission Clinical trial) and bariatric surgery (By-Band-Sleeve), using SomaLogic and Olink Explore1536 technologies, respectively. Linear mixed models were used to estimate the effect of the interventions on circulating proteins. Twenty-three proteins were altered in a consistent direction after both bariatric surgery and caloric restriction, suggesting that these proteins are modulated by weight change, independent of intervention type. We also integrated Mendelian randomisation (MR) estimates of the effect of BMI on proteins measured by SomaLogic from a UK blood donor cohort as a third line of causal evidence. These MR estimates provided further corroborative evidence for a role of BMI in regulating the levels of six proteins including alcohol dehydrogenase-4, nogo receptor and interleukin-1 receptor antagonist protein. These results indicate the importance of triangulation in interrogating causal relationships; further study into the role of proteins modulated by weight in disease is now warranted.
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Affiliation(s)
- Lucy J Goudswaard
- Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
- MRC Integrative Epidemiology Unit, Bristol, UK.
- Physiology, Pharmacology & Neuroscience, University of Bristol, Biomedical Sciences Building, University Walk, Bristol, BS8 1TD, UK.
| | - Madeleine L Smith
- Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- MRC Integrative Epidemiology Unit, Bristol, UK
| | - David A Hughes
- Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- MRC Integrative Epidemiology Unit, Bristol, UK
| | - Roy Taylor
- Newcastle Magnetic Resonance Centre, Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, NE4 5PL, UK
| | - Michael Lean
- Human Nutrition, School of Medicine, Dentistry and Nursing, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, G31 2ER, UK
| | - Naveed Sattar
- School of Cardiovascular and Medical Science, University of Glasgow, Glasgow, G12 8TA, UK
| | - Paul Welsh
- School of Cardiovascular and Medical Science, University of Glasgow, Glasgow, G12 8TA, UK
| | - Alex McConnachie
- Robertson Centre for Biostatistics, School of Health and Wellbeing, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Jane M Blazeby
- Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Chris A Rogers
- Bristol Medical School, Bristol Trials Centre, University of Bristol, Bristol, BS8 1NU, UK
| | - Karsten Suhre
- Department of Biophysics and Physiology, Weill Cornell Medicine - Qatar, Doha, Qatar
| | - Shaza B Zaghlool
- Department of Biophysics and Physiology, Weill Cornell Medicine - Qatar, Doha, Qatar
| | - Ingeborg Hers
- Physiology, Pharmacology & Neuroscience, University of Bristol, Biomedical Sciences Building, University Walk, Bristol, BS8 1TD, UK
| | - Nicholas J Timpson
- Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- MRC Integrative Epidemiology Unit, Bristol, UK
| | - Laura J Corbin
- Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- MRC Integrative Epidemiology Unit, Bristol, UK
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11
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Constantinescu AE, Bull CJ, Goudswaard LJ, Zheng J, Elsworth B, Timpson NJ, Moore SF, Hers I, Vincent EE. A phenome-wide approach to identify causal risk factors for deep vein thrombosis. BMC Med Genomics 2023; 16:284. [PMID: 37951941 PMCID: PMC10640748 DOI: 10.1186/s12920-023-01710-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 10/20/2023] [Indexed: 11/14/2023] Open
Abstract
Deep vein thrombosis (DVT) is the formation of a blood clot in a deep vein. DVT can lead to a venous thromboembolism (VTE), the combined term for DVT and pulmonary embolism, a leading cause of death and disability worldwide. Despite the prevalence and associated morbidity of DVT, the underlying causes are not well understood. Our aim was to leverage publicly available genetic summary association statistics to identify causal risk factors for DVT. We conducted a Mendelian randomization phenome-wide association study (MR-PheWAS) using genetic summary association statistics for 973 exposures and DVT (6,767 cases and 330,392 controls in UK Biobank). There was evidence for a causal effect of 57 exposures on DVT risk, including previously reported risk factors (e.g. body mass index-BMI and height) and novel risk factors (e.g. hyperthyroidism and varicose veins). As the majority of identified risk factors were adiposity-related, we explored the molecular link with DVT by undertaking a two-sample MR mediation analysis of BMI-associated circulating proteins on DVT risk. Our results indicate that circulating neurogenic locus notch homolog protein 1 (NOTCH1), inhibin beta C chain (INHBC) and plasminogen activator inhibitor 1 (PAI-1) influence DVT risk, with PAI-1 mediating the BMI-DVT relationship. Using a phenome-wide approach, we provide putative causal evidence that hyperthyroidism, varicose veins and BMI enhance the risk of DVT. Furthermore, the circulating protein PAI-1 has a causal role in DVT aetiology and is involved in mediating the BMI-DVT relationship.
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Affiliation(s)
- Andrei-Emil Constantinescu
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK.
- Bristol Medical School, Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK.
- School of Translational Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK.
| | - Caroline J Bull
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- School of Translational Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Health Data Research UK. Registered Office, 215 Euston Road, London, NW1 2BE, UK
| | - Lucy J Goudswaard
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK
| | - Jie Zheng
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- 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 National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Benjamin Elsworth
- Our Future Health Ltd. Registered office: 2 New Bailey, 6 Stanley Street, Manchester, M3 5GS, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Samantha F Moore
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK
- UKRI Medical Research Council, Swindon, UK
| | - Ingeborg Hers
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK
| | - Emma E Vincent
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- School of Translational Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
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12
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Titova OE, Brunius C, Warensjö Lemming E, Stattin K, Baron JA, Byberg L, Michaëlsson K, Larsson SC. Comprehensive analyses of circulating cardiometabolic proteins and objective measures of fat mass. Int J Obes (Lond) 2023; 47:1043-1049. [PMID: 37550405 PMCID: PMC10599989 DOI: 10.1038/s41366-023-01351-z] [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: 03/07/2023] [Revised: 07/03/2023] [Accepted: 07/14/2023] [Indexed: 08/09/2023]
Abstract
BACKGROUND The underlying molecular pathways for the effect of excess fat mass on cardiometabolic diseases is not well understood. Since body mass index is a suboptimal measure of body fat content, we investigated the relationship of fat mass measured by dual-energy X-ray absorptiometry with circulating cardiometabolic proteins. METHODS We used data from a population-based cohort of 4950 Swedish women (55-85 years), divided into discovery and replication samples; 276 proteins were assessed with three Olink Proseek Multiplex panels. We used random forest to identify the most relevant biomarker candidates related to fat mass index (FMI), multivariable linear regression to further investigate the associations between FMI characteristics and circulating proteins adjusted for potential confounders, and principal component analysis (PCA) for the detection of common covariance patterns among the proteins. RESULTS Total FMI was associated with 66 proteins following adjustment for multiple testing in discovery and replication multivariable analyses. Five proteins not previously associated with body size were associated with either lower FMI (calsyntenin-2 (CLSTN2), kallikrein-10 (KLK10)), or higher FMI (scavenger receptor cysteine-rich domain-containing group B protein (SSC4D), trem-like transcript 2 protein (TLT-2), and interleukin-6 receptor subunit alpha (IL-6RA)). PCA provided an efficient summary of the main variation in FMI-related circulating proteins involved in glucose and lipid metabolism, appetite regulation, adipocyte differentiation, immune response and inflammation. Similar patterns were observed for regional fat mass measures. CONCLUSIONS This is the first large study showing associations between fat mass and circulating cardiometabolic proteins. Proteins not previously linked to body size are implicated in modulation of postsynaptic signals, inflammation, and carcinogenesis.
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Affiliation(s)
- Olga E Titova
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
| | - Carl Brunius
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
- Department of Biology and Biological Engineering, Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
| | - Eva Warensjö Lemming
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
- Department of Food studies, nutrition and dietetics, Uppsala University, Uppsala, Sweden
| | - Karl Stattin
- Department of Surgical Sciences, Anaesthesiology and Intensive Care, Uppsala University, Uppsala, Sweden
| | - John A Baron
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
- Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Liisa Byberg
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Karl Michaëlsson
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Susanna C Larsson
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
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13
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Nimptsch K, Aleksandrova K, Pham TT, Papadimitriou N, Janke J, Christakoudi S, Heath A, Olsen A, Tjønneland A, Schulze MB, Katzke V, Kaaks R, van Guelpen B, Harbs J, Palli D, Macciotta A, Pasanisi F, Yohar SMC, Guevara M, Amiano P, Grioni S, Jakszyn PG, Figueiredo JC, Samadder NJ, Li CI, Moreno V, Potter JD, Schoen RE, Um CY, Weiderpass E, Jenab M, Gunter MJ, Pischon T. Prospective and Mendelian randomization analyses on the association of circulating fatty acid binding protein 4 (FABP-4) and risk of colorectal cancer. BMC Med 2023; 21:391. [PMID: 37833736 PMCID: PMC10576353 DOI: 10.1186/s12916-023-03104-1] [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: 03/06/2023] [Accepted: 10/04/2023] [Indexed: 10/15/2023] Open
Abstract
BACKGROUND Fatty acid binding protein 4 (FABP-4) is a lipid-binding adipokine upregulated in obesity, which may facilitate fatty acid supply for tumor growth and promote insulin resistance and inflammation and may thus play a role in colorectal cancer (CRC) development. We aimed to investigate the association between circulating FABP-4 and CRC and to assess potential causality using a Mendelian randomization (MR) approach. METHODS The association between pre-diagnostic plasma measurements of FABP-4 and CRC risk was investigated in a nested case-control study in 1324 CRC cases and the same number of matched controls within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. A two-sample Mendelian randomization study was conducted based on three genetic variants (1 cis, 2 trans) associated with circulating FABP-4 identified in a published genome-wide association study (discovery n = 20,436) and data from 58,131 CRC cases and 67,347 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium, Colorectal Cancer Transdisciplinary Study, and Colon Cancer Family Registry. RESULTS In conditional logistic regression models adjusted for potential confounders including body size, the estimated relative risk, RR (95% confidence interval, CI) per one standard deviation, SD (8.9 ng/mL) higher FABP-4 concentration was 1.01 (0.92, 1.12) overall, 0.95 (0.80, 1.13) in men and 1.09 (0.95, 1.25) in women. Genetically determined higher FABP-4 was not associated with colorectal cancer risk (RR per FABP-4 SD was 1.10 (0.95, 1.27) overall, 1.03 (0.84, 1.26) in men and 1.21 (0.98, 1.48) in women). However, in a cis-MR approach, a statistically significant association was observed in women (RR 1.56, 1.09, 2.23) but not overall (RR 1.23, 0.97, 1.57) or in men (0.99, 0.71, 1.37). CONCLUSIONS Taken together, these analyses provide no support for a causal role of circulating FABP-4 in the development of CRC, although the cis-MR provides some evidence for a positive association in women, which may deserve to be investigated further.
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Affiliation(s)
- Katharina Nimptsch
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine (MDC), Berlin, Germany.
| | - Krasimira Aleksandrova
- Department Epidemiological Methods and Etiological Research, Leibniz Institute for Prevention Research and Epidemiology, Bremen, Germany
- Faculty of Human and Health Sciences, University of Bremen, Bremen, Germany
| | - Thu Thi Pham
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine (MDC), Berlin, Germany
- Charité - Universitaetsmedizin Berlin, Corporate Member of Freie Universitaet Berlin, Humboldt-Universitaet zu Berlin, Berlin, Germany
| | - Nikos Papadimitriou
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Jürgen Janke
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine (MDC), Berlin, Germany
- Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), Biobank Technology Platform, Berlin, Germany
| | - Sofia Christakoudi
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Inflammation Biology, School of Immunology and Microbial Sciences, King's College London, London, UK
| | - Alicia Heath
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Anja Olsen
- Danish Cancer Society Research Center, Copenhagen, Denmark
- Department of Public Health, University of Århus, Århus, Denmark
| | - Anne Tjønneland
- Danish Cancer Society Research Center, Copenhagen, Denmark
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nutehtal, Germany
- Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany
| | - Verena Katzke
- Department of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rudolf Kaaks
- Department of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Bethany van Guelpen
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
- Wallenberg Centre for Molecular Medicine, Umeå University, Umeå, Sweden
| | - Justin Harbs
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
| | - Domenico Palli
- Cancer Risk Factors and Life-Style Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Alessandra Macciotta
- Department of Clinical and Biological Sciences, University of Turin, Turin, Italy
| | - Fabrizio Pasanisi
- Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy
| | - Sandra Milena Colorado Yohar
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Research Group on Demography and Health, National Faculty of Public Health, University of Antioquia, Medellín, Colombia
| | - Marcela Guevara
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Instituto de Salud Pública de Navarra, Pamplona, 31003, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, 31008, Spain
| | - Pilar Amiano
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Ministry of Health of the Basque Government, Sub Directorate for Public Health and Addictions of Gipuzkoa, San Sebastian, Spain
- Epidemiology of Chronic and Communicable Diseases Group, Biodonostia Health Research Institute, San Sebastián, Spain
| | - Sara Grioni
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, 20133, Italy
| | - Paula Gabriela Jakszyn
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology (ICO-IDIBELL), Barcelona, Spain
- Blanquerna School of Health Sciences, Ramon Llull University, Barcelona, Spain
| | - Jane C Figueiredo
- Cedars-Sinai Medical Center Samuel Oschin Comprehensive Cancer Institute, Los Angeles, CA, USA
| | - N Jewel Samadder
- Division of Gastroenterology and Hepatology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Phoenix, AZ, USA
| | - Christopher I Li
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Victor Moreno
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Oncology Data Analytics Program, Catalan Institute of Oncology-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain
- Department of Clinical Sciences, Faculty of Medicine and Health Sciences and Universitat de Barcelona Institute of Complex Systems (UBICS), University of Barcelona (UB), L'Hospitalet de Llobregat, Barcelona, Spain
| | - John D Potter
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Research Centre for Hauora and Health, Massey University, Wellington, New Zealand
| | - Robert E Schoen
- Department of Medicine and Epidemiology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Caroline Y Um
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Elisabete Weiderpass
- International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Mazda Jenab
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Marc J Gunter
- Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Tobias Pischon
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine (MDC), Berlin, Germany
- Charité - Universitaetsmedizin Berlin, Corporate Member of Freie Universitaet Berlin, Humboldt-Universitaet zu Berlin, Berlin, Germany
- Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), Biobank Technology Platform, Berlin, Germany
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14
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Nieman DC, Sakaguchi CA, Pelleigrini M, Thompson MJ, Sumner S, Zhang Q. Healthy lifestyle linked to innate immunity and lipoprotein metabolism: a cross-sectional comparison using untargeted proteomics. Sci Rep 2023; 13:16728. [PMID: 37794065 PMCID: PMC10550951 DOI: 10.1038/s41598-023-44068-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 10/03/2023] [Indexed: 10/06/2023] Open
Abstract
This study used untargeted proteomics to compare blood proteomic profiles in two groups of adults that differed widely in lifestyle habits. A total of 52 subjects in the lifestyle group (LIFE) (28 males, 24 females) and 52 in the control group (CON) (27 males, 25 females) participated in this cross-sectional study. Age, education level, marital status, and height did not differ significantly between LIFE and CON groups. The LIFE and CON groups differed markedly in body composition, physical activity patterns, dietary intake patterns, disease risk factor prevalence, blood measures of inflammation, triglycerides, HDL-cholesterol, glucose, and insulin, weight-adjusted leg/back and handgrip strength, and mood states. The proteomics analysis showed strong group differences for 39 of 725 proteins identified in dried blood spot samples. Of these, 18 were downregulated in the LIFE group and collectively indicated a lower innate immune activation signature. A total of 21 proteins were upregulated in the LIFE group and supported greater lipoprotein metabolism and HDL remodeling. Lifestyle-related habits and biomarkers were probed and the variance (> 50%) in proteomic profiles was best explained by group contrasts in indicators of adiposity. This cross-sectional study established that a relatively small number of proteins are associated with good lifestyle habits.
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Affiliation(s)
- David C Nieman
- Human Performance Laboratory, Biology Department, Appalachian State University, North Carolina Research Campus, Kannapolis, NC, USA.
| | - Camila A Sakaguchi
- Human Performance Laboratory, Biology Department, Appalachian State University, North Carolina Research Campus, Kannapolis, NC, USA
| | - Matteo Pelleigrini
- Department of Molecular, Cell, and Developmental Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Michael J Thompson
- Department of Molecular, Cell, and Developmental Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Susan Sumner
- Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, 28081, USA
| | - Qibin Zhang
- UNCG Center for Translational Biomedical Research, University of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, NC, USA
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15
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Yao P, Iona A, Kartsonaki C, Said S, Wright N, Lin K, Pozarickij A, Millwood I, Fry H, Mazidi M, Chen Y, Du H, Bennett D, Avery D, Schmidt D, Pei P, Lv J, Yu C, Hill M, Chen J, Peto R, Walters R, Collins R, Li L, Clarke R, Chen Z. Conventional and genetic associations of adiposity with 1463 proteins in relatively lean Chinese adults. Eur J Epidemiol 2023; 38:1089-1103. [PMID: 37676424 PMCID: PMC10570181 DOI: 10.1007/s10654-023-01038-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 07/28/2023] [Indexed: 09/08/2023]
Abstract
Adiposity is associated with multiple diseases and traits, but little is known about the causal relevance and mechanisms underlying these associations. Large-scale proteomic profiling, especially when integrated with genetic data, can clarify mechanisms linking adiposity with disease outcomes. We examined the associations of adiposity with plasma levels of 1463 proteins in 3977 Chinese adults, using measured and genetically-instrumented BMI. We further used two-sample bi-directional MR analyses to assess if certain proteins influenced adiposity, along with other (e.g. enrichment) analyses to clarify possible mechanisms underlying the observed associations. Overall, the mean (SD) baseline BMI was 23.9 (3.3) kg/m2, with only 6% being obese (i.e. BMI ≥ 30 kg/m2). Measured and genetically-instrumented BMI was significantly associated at FDR < 0.05 with levels of 1096 (positive/inverse: 826/270) and 307 (positive/inverse: 270/37) proteins, respectively, with FABP4, LEP, IL1RN, LSP1, GOLM2, TNFRSF6B, and ADAMTS15 showing the strongest positive and PON3, NCAN, LEPR, IGFBP2 and MOG showing the strongest inverse genetic associations. These associations were largely linear, in adiposity-to-protein direction, and replicated (> 90%) in Europeans of UKB (mean BMI 27.4 kg/m2). Enrichment analyses of the top > 50 BMI-associated proteins demonstrated their involvement in atherosclerosis, lipid metabolism, tumour progression and inflammation. Two-sample bi-directional MR analyses using cis-pQTLs identified in CKB GWAS found eight proteins (ITIH3, LRP11, SCAMP3, NUDT5, OGN, EFEMP1, TXNDC15, PRDX6) significantly affect levels of BMI, with NUDT5 also showing bi-directional association. The findings among relatively lean Chinese adults identified novel pathways by which adiposity may increase disease risks and novel potential targets for treatment of obesity and obesity-related diseases.
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Affiliation(s)
- Pang Yao
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Andri Iona
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Christiana Kartsonaki
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Saredo Said
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Neil Wright
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Kuang Lin
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Alfred Pozarickij
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Iona Millwood
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Hannah Fry
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Mohsen Mazidi
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Yiping Chen
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Derrick Bennett
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Daniel Avery
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Dan Schmidt
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Jun Lv
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Canqing Yu
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Michael Hill
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Richard Peto
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Robin Walters
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Rory Collins
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Liming Li
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Robert Clarke
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK.
| | - Zhengming Chen
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK.
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
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16
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Drouard G, Hagenbeek FA, Whipp A, Pool R, Hottenga JJ, Jansen R, Hubers N, Afonin A, Willemsen G, de Geus EJC, Ripatti S, Pirinen M, Kanninen KM, Boomsma DI, van Dongen J, Kaprio J. Longitudinal multi-omics study reveals common etiology underlying association between plasma proteome and BMI trajectories in adolescent and young adult twins. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.28.23291995. [PMID: 37425750 PMCID: PMC10327285 DOI: 10.1101/2023.06.28.23291995] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Background The influence of genetics and environment on the association of the plasma proteome with body mass index (BMI) and changes in BMI remain underexplored, and the links to other omics in these associations remain to be investigated. We characterized protein-BMI trajectory associations in adolescents and adults and how these connect to other omics layers. Methods Our study included two cohorts of longitudinally followed twins: FinnTwin12 (N=651) and the Netherlands Twin Register (NTR) (N=665). Follow-up comprised four BMI measurements over approximately 6 (NTR: 23-27 years old) to 10 years (FinnTwin12: 12-22 years old), with omics data collected at the last BMI measurement. BMI changes were calculated using latent growth curve models. Mixed-effects models were used to quantify the associations between the abundance of 439 plasma proteins with BMI at blood sampling and changes in BMI. The sources of genetic and environmental variation underlying the protein abundances were quantified using twin models, as were the associations of proteins with BMI and BMI changes. In NTR, we investigated the association of gene expression of genes encoding proteins identified in FinnTwin12 with BMI and changes in BMI. We linked identified proteins and their coding genes to plasma metabolites and polygenic risk scores (PRS) using mixed-effect models and correlation networks. Results We identified 66 and 14 proteins associated with BMI at blood sampling and changes in BMI, respectively. The average heritability of these proteins was 35%. Of the 66 BMI-protein associations, 43 and 12 showed genetic and environmental correlations, respectively, including 8 proteins showing both. Similarly, we observed 6 and 4 genetic and environmental correlations between changes in BMI and protein abundance, respectively. S100A8 gene expression was associated with BMI at blood sampling, and the PRG4 and CFI genes were associated with BMI changes. Proteins showed strong connections with many metabolites and PRSs, but we observed no multi-omics connections among gene expression and other omics layers. Conclusions Associations between the proteome and BMI trajectories are characterized by shared genetic, environmental, and metabolic etiologies. We observed few gene-protein pairs associated with BMI or changes in BMI at the proteome and transcriptome levels.
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Affiliation(s)
- Gabin Drouard
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Fiona A. Hagenbeek
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Alyce Whipp
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Rick Jansen
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, The Netherlands
| | - Nikki Hubers
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, The Netherlands
| | - Aleksei Afonin
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - BIOS Consortium
- Biobank-based Integrative Omics Study Consortium. Lists of authors and their affiliations appear in the supplementary material (see Additional file 1)
| | | | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Eco J. C. de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Katja M. Kanninen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, The Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, The Netherlands
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
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17
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Zhao Q, Han B, Xu Q, Wang T, Fang C, Li R, Zhang L, Pei Y. Proteome and genome integration analysis of obesity. Chin Med J (Engl) 2023; 136:910-921. [PMID: 37000968 PMCID: PMC10278747 DOI: 10.1097/cm9.0000000000002644] [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: 11/07/2022] [Indexed: 04/03/2023] Open
Abstract
ABSTRACT The prevalence of obesity has increased worldwide in recent decades. Genetic factors are now known to play a substantial role in the predisposition to obesity and may contribute up to 70% of the risk for obesity. Technological advancements during the last decades have allowed the identification of many hundreds of genetic markers associated with obesity. However, the transformation of current genetic variant-obesity associations into biological knowledge has been proven challenging. Genomics and proteomics are complementary fields, as proteomics extends functional analyses. Integrating genomic and proteomic data can help to bridge a gap in knowledge regarding genetic variant-obesity associations and to identify new drug targets for the treatment of obesity. We provide an overview of the published papers on the integrated analysis of proteomic and genomic data in obesity and summarize four mainstream strategies: overlap, colocalization, Mendelian randomization, and proteome-wide association studies. The integrated analyses identified many obesity-associated proteins, such as leptin, follistatin, and adenylate cyclase 3. Despite great progress, integrative studies focusing on obesity are still limited. There is an increased demand for large prospective cohort studies to identify and validate findings, and further apply these findings to the prevention, intervention, and treatment of obesity. In addition, we also discuss several other potential integration methods.
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Affiliation(s)
- Qigang Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215123, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215213, China
| | - Baixue Han
- Department of Epidemiology and Biostatistics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215123, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215213, China
| | - Qian Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215123, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215213, China
| | - Tao Wang
- Department of Endocrinology, The Second Affiliated Hospital, Soochow University, Suzhou, Jiangsu 215004, China
| | - Chen Fang
- Department of Endocrinology, The Second Affiliated Hospital, Soochow University, Suzhou, Jiangsu 215004, China
| | - Rui Li
- Department of Gastroenterology, The First Affiliated Hospital, Soochow University, Suzhou, Jiangsu 215006, China
| | - Lei Zhang
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215213, China
- Center for Genetic Epidemiology and Genomics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215123, China
| | - Yufang Pei
- Department of Epidemiology and Biostatistics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215123, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215213, China
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18
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Yoshiji S, Butler-Laporte G, Lu T, Willett JDS, Su CY, Nakanishi T, Morrison DR, Chen Y, Liang K, Hultström M, Ilboudo Y, Afrasiabi Z, Lan S, Duggan N, DeLuca C, Vaezi M, Tselios C, Xue X, Bouab M, Shi F, Laurent L, Münter HM, Afilalo M, Afilalo J, Mooser V, Timpson NJ, Zeberg H, Zhou S, Forgetta V, Farjoun Y, Richards JB. Proteome-wide Mendelian randomization implicates nephronectin as an actionable mediator of the effect of obesity on COVID-19 severity. Nat Metab 2023; 5:248-264. [PMID: 36805566 PMCID: PMC9940690 DOI: 10.1038/s42255-023-00742-w] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 01/10/2023] [Indexed: 02/22/2023]
Abstract
Obesity is a major risk factor for Coronavirus disease (COVID-19) severity; however, the mechanisms underlying this relationship are not fully understood. As obesity influences the plasma proteome, we sought to identify circulating proteins mediating the effects of obesity on COVID-19 severity in humans. Here, we screened 4,907 plasma proteins to identify proteins influenced by body mass index using Mendelian randomization. This yielded 1,216 proteins, whose effect on COVID-19 severity was assessed, again using Mendelian randomization. We found that an s.d. increase in nephronectin (NPNT) was associated with increased odds of critically ill COVID-19 (OR = 1.71, P = 1.63 × 10-10). The effect was driven by an NPNT splice isoform. Mediation analyses supported NPNT as a mediator. In single-cell RNA-sequencing, NPNT was expressed in alveolar cells and fibroblasts of the lung in individuals who died of COVID-19. Finally, decreasing body fat mass and increasing fat-free mass were found to lower NPNT levels. These findings provide actionable insights into how obesity influences COVID-19 severity.
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Grants
- C18281/A29019 Cancer Research UK
- 365825 CIHR
- 409511 CIHR
- 100558 CIHR
- 169303 CIHR
- The Richards research group is supported by the Canadian Institutes of Health Research (CIHR: 365825, 409511, 100558, 169303), the McGill Interdisciplinary Initiative in Infection and Immunity (MI4), the Lady Davis Institute of the Jewish General Hospital, the Jewish General Hospital Foundation, the Canadian Foundation for Innovation, the NIH Foundation, Cancer Research UK, Genome Québec, the Public Health Agency of Canada, McGill University, Cancer Research UK [grant number C18281/A29019] and the Fonds de Recherche Québec Santé (FRQS). J.B.R. is supported by an FRQS Mérite Clinical Research Scholarship. Support from Calcul Québec and Compute Canada is acknowledged. TwinsUK is funded by the Welcome Trust, Medical Research Council, European Union, the National Institute for Health Research (NIHR)-funded BioResource, Clinical Research Facility and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London. S.Y. is supported by the Japan Society for the Promotion of Science. T.L. has been supported by a Vanier Canada Graduate Scholarship, an FRQS doctoral training fellowship, and a McGill University Faculty of Medicine Studentship. These funding agencies mentioned above had no role in the design, implementation, or interpretation of this study.
- MEXT | Japan Society for the Promotion of Science (JSPS)
- Gouvernement du Canada | Instituts de Recherche en Santé du Canada | CIHR Skin Research Training Centre (Skin Research Training Centre)
- Fonds de Recherche du Québec-Société et Culture (FRQSC)
- Cancer Research UK (CRUK)
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Affiliation(s)
- Satoshi Yoshiji
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
- Department of Human Genetics, McGill University, Montréal, Quebec, Canada
- Kyoto-McGill International Collaborative Program in Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Japan Society for the Promotion of Science, Tokyo, Japan
| | - Guillaume Butler-Laporte
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Quebec, Canada
| | - Tianyuan Lu
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
- Quantitative Life Sciences Program, McGill University, Montréal, Quebec, Canada
- 5 Prime Sciences, Montréal, Quebec, Canada
| | - Julian Daniel Sunday Willett
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
- Quantitative Life Sciences Program, McGill University, Montréal, Quebec, Canada
| | - Chen-Yang Su
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
- Department of Computer Science, McGill University, Montréal, Quebec, Canada
| | - Tomoko Nakanishi
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
- Department of Human Genetics, McGill University, Montréal, Quebec, Canada
- Kyoto-McGill International Collaborative Program in Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Japan Society for the Promotion of Science, Tokyo, Japan
| | - David R Morrison
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
| | - Yiheng Chen
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
- Department of Human Genetics, McGill University, Montréal, Quebec, Canada
| | - Kevin Liang
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
- Quantitative Life Sciences Program, McGill University, Montréal, Quebec, Canada
| | - Michael Hultström
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Quebec, Canada
- Anaesthesiology and Intensive Care Medicine, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
- Integrative Physiology, Department of Medical Cell Biology, Uppsala University, Uppsala, Sweden
| | - Yann Ilboudo
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
| | - Zaman Afrasiabi
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
| | - Shanshan Lan
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
| | - Naomi Duggan
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
| | - Chantal DeLuca
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
| | - Mitra Vaezi
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
| | - Chris Tselios
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
| | - Xiaoqing Xue
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
| | - Meriem Bouab
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
| | - Fangyi Shi
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
| | - Laetitia Laurent
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
| | | | - Marc Afilalo
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
- Department of Emergency Medicine, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
| | - Jonathan Afilalo
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Quebec, Canada
- Division of Cardiology, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
| | - Vincent Mooser
- Department of Human Genetics, McGill University, Montréal, Quebec, Canada
- McGill Genome Centre, McGill University, Montréal, Quebec, Canada
| | | | - Hugo Zeberg
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Sirui Zhou
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
- Department of Human Genetics, McGill University, Montréal, Quebec, Canada
- McGill Genome Centre, McGill University, Montréal, Quebec, Canada
| | - Vincenzo Forgetta
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
- 5 Prime Sciences, Montréal, Quebec, Canada
| | - Yossi Farjoun
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada
| | - J Brent Richards
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Quebec, Canada.
- Department of Human Genetics, McGill University, Montréal, Quebec, Canada.
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Quebec, Canada.
- 5 Prime Sciences, Montréal, Quebec, Canada.
- Department of Twin Research, King's College London, London, UK.
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19
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Kardeby C, Evans A, Campos J, Al-Wahaibi AM, Smith CW, Slater A, Martin EM, Severin S, Brill A, Pejler G, Sun Y, Watson SP. Heparin and heparin proteoglycan-mimetics activate platelets via PEAR1 and PI3Kβ. J Thromb Haemost 2023; 21:101-116. [PMID: 36695374 DOI: 10.1016/j.jtha.2022.10.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 10/04/2022] [Accepted: 10/25/2022] [Indexed: 01/11/2023]
Abstract
BACKGROUND Platelet endothelial aggregation receptor 1 (PEAR1) is a single-transmembrane orphan receptor primarily expressed on platelets and endothelial cells. Genetic variants of PEAR1 have repeatedly and independently been identified to be associated with cardiovascular diseases, including coronary artery disease. OBJECTIVES We have identified sulfated fucoidans and their mimetics as ligands for PEAR1 and proposed that its endogenous ligand is a sulfated proteoglycan. The aim of this study was to test this hypothesis. METHODS A heparin proteoglycan-mimetic (HPGM) was created by linking unfractionated heparin (UFH) to albumin. The ability of the HPGM, UFH and selectively desulfated heparins to stimulate platelet aggregation and protein phosphorylation was investigated. Nanobodies against the 12th to 13th epidermal growth factor-like repeat of PEAR1 and phosphoinositide 3-kinase (PI3K) isoform-selective inhibitors were tested for the inhibition of platelet activation. RESULTS We show that HPGM, heparin conjugated to an albumin protein core, stimulates aggregation and phosphorylation of PEAR1 in washed platelets. Platelet aggregation was abolished by an anti-PEAR1 nanobody, Nb138. UFH stimulated platelet aggregation in washed platelets, but desulfated UFH did not. Furthermore, HPGM, but not UFH, stimulated maximal aggregation in platelet-rich plasma. However, both HPGM and UFH increased integrin αIIbβ3 activation in whole blood. By using PI3K isoform-selective inhibitors, we show that PEAR1 activates PI3Kβ, leading to Akt phosphorylation. CONCLUSION Our findings reveal that PEAR1 is a receptor for heparin and HPGM and that PI3Kβ is a key signaling molecule downstream of PEAR1 in platelets. These findings may have important implications for our understanding of the role of PEAR1 in cardiovascular disease.
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Affiliation(s)
- Caroline Kardeby
- Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK.
| | - Alice Evans
- Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Joana Campos
- Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Afraa Moosa Al-Wahaibi
- Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Christopher W Smith
- Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Alexandre Slater
- Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Eleyna M Martin
- Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Sonia Severin
- INSERM U1297 and Paul Sabatier University, Institute of Cardiovascular and Metabolic Diseases, Toulouse, France
| | - Alexander Brill
- Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Gunnar Pejler
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Yi Sun
- Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; Centre of Membrane Proteins and Receptors, Universities of Birmingham and Nottingham, Midlands, UK
| | - Steve P Watson
- Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; Centre of Membrane Proteins and Receptors, Universities of Birmingham and Nottingham, Midlands, UK
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20
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Gagliano-Jucá T, Alvarez M, Basaria S. The medicalization of testosterone: reinventing the elixir of life. Rev Endocr Metab Disord 2022; 23:1275-1284. [PMID: 35999482 DOI: 10.1007/s11154-022-09751-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/08/2022] [Indexed: 01/11/2023]
Abstract
The pursuit of longevity, which during the Renaissance era was limited to longing for miraculous ways of rejuvenation, such as bathing in the fountain of youth, took a scientific turn in 1889 with the publication of Brown-Sequard's self-experiments with an extract of animal testes, which apparently improved his vitality, physical strength and cognition. This extract, marketed then as the "Elixir of Life", was sold for decades throughout Europe and North America. However, recent replication of Brown-Sequard's experiments demonstrated that such an extract only contains homeopathic concentrations of testosterone that are insufficient to exert any biological effect. Thus, the birth of Andrology began with a placebo effect. Over the past few decades, the quest for compounds that might lead to rejuvenation has regained traction, with testosterone being at the forefront. Though clinical practice guidelines advocate testosterone therapy in men with organic hypogonadism-the only indication approved by the Food and Drug Administration-testosterone continues to be marketed as a wonder drug with rejuvenating effects on sexual function, vitality, and a host of other unproven benefits. Additionally, the epidemic of obesity and diabetes, conditions associated with low testosterone, has further brought testosterone into the limelight. Although the number of testosterone prescriptions written have increased several-fold in the past two decades, carefully conducted randomized trials suggest modest benefits of testosterone therapy. At the same time, safety concerns, particularly in older men, remain valid.
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Affiliation(s)
- Thiago Gagliano-Jucá
- Northwestern Medicine McHenry Hospital, Chicago Medical School, Rosalind Franklin University of Medicine and Science, McHenry, IL, United States
| | - Mauricio Alvarez
- Section of Endocrinology, Hospital Militar Central, Bogota, Colombia
| | - Shehzad Basaria
- Section On Men's Health, Endocrinology Division, Brigham and Women's Hospital, Harvard Medical School, 221 Longwood Ave, BLI 541, Boston, MA, 02115, United States.
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21
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Larsson SC, Spyrou N, Mantzoros CS. Body fatness associations with cancer: evidence from recent epidemiological studies and future directions. Metabolism 2022; 137:155326. [PMID: 36191637 DOI: 10.1016/j.metabol.2022.155326] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 09/27/2022] [Accepted: 09/27/2022] [Indexed: 12/12/2022]
Abstract
This narrative review highlights current evidence linking greater body fatness to risk of various cancers, with focus on evidence from recent large cohort studies and pooled analyses of cohort studies as well as Mendelian randomization studies (which utilized genetic variants associated with body mass index to debrief the causal effect of higher body fatness on cancer risk). This review also provides insights into the biological mechanisms underpinning the associations. Data from both observational and Mendelian randomization studies support the associations of higher body mass index with increased risk of many cancers with the strongest evidence for digestive system cancers, including esophageal, stomach, colorectal, liver, gallbladder, and pancreatic cancer, as well as kidney, endometrial, and ovarian (weak association) cancer. Evidence from observational studies suggests that greater body fatness has contrasting effects on breast cancer risk depending on menopausal status and on prostate cancer risk depending on disease stage. Experimental and Mendelian randomization studies indicate that adiponectin, insulin, and sex hormone pathways play an important role in mediating the link between body fatness and cancer risk. The possible role of specific factors and pathways, such as other adipocytokines and hormones and the gut microbiome in mediating the associations between greater body fatness and cancer risk is yet uncertain and needs investigation in future studies. With rising prevalence of overweight and obesity worldwide, the proportion of cancer caused by excess body fatness is expected to increase. There is thus an urgent need to identify efficient ways at the individual and societal level to improve diet and physical activity patterns to reduce the burden of obesity and accompanying comorbidities, including cancer.
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Affiliation(s)
- Susanna C Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
| | - Nikolaos Spyrou
- The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Christos S Mantzoros
- Department of Medicine, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA, USA; Section of Endocrinology, VA Boston Healthcare System, Harvard Medical School, Boston, MA, USA
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22
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Goulding NJ, Goudswaard LJ, Hughes DA, Corbin LJ, Groom A, Ring S, Timpson NJ, Fraser A, Northstone K, Suderman M. Inflammation proteomics datasets in the ALSPAC cohort. Wellcome Open Res 2022. [DOI: 10.12688/wellcomeopenres.18482.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
Proteomics is the identification, detection and quantification of proteins within a biological sample. The complete set of proteins expressed by an organism is known as the proteome. The availability of new high-throughput proteomic technologies, such as Olink Proteomic Proximity Extension Assay (PEA) technology has enabled detailed investigation of the circulating proteome in large-scale epidemiological studies. In particular, the Olink® Target 96 inflammatory panel allows the measurement of 92 circulating inflammatory proteins. The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prospective population-based cohort study which recruited pregnant women in 1991-1992 and has followed these women, their partners, and their offspring ever since. In this data note, we describe the proteomic data available in ALSPAC. Ninety-two proteins were analysed in 9000 blood plasma samples using the Olink® Target 96 inflammatory panel. Samples were derived from 2968 fasted mothers (mean age 47.5; Focus on Mothers 1 (FOM1)), 3005 non-fasted offspring at age 9 (Focus@9) and 3027 fasted offspring at age 24 (Focus@24). Post sample filtering, 1834 offspring have data at both timepoints and 1119 of those have data from their mother available. We performed quality control analyses using a standardised data processing workflow (metaboprep) to produce a filtered dataset of 8983 samples for researchers to use in future analyses. Initial validation analyses indicate that IL-6 measured using the Olink® Target 96 inflammatory panel is highly correlated with IL-6 previously measured by clinical chemistry (Pearson’s correlation = 0.77) and we are able to reproduce the reported positive correlation between body mass index (BMI) and IL-6. The pre-processing and validation analyses indicate a rich proteomic dataset to further characterise the role of inflammation in health and disease.
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23
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Jarmund AH, Madssen TS, Giskeødegård GF. ALASCA: An R package for longitudinal and cross-sectional analysis of multivariate data by ASCA-based methods. Front Mol Biosci 2022; 9:962431. [PMID: 36387276 PMCID: PMC9645785 DOI: 10.3389/fmolb.2022.962431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 09/20/2022] [Indexed: 01/24/2023] Open
Abstract
The increasing availability of multivariate data within biomedical research calls for appropriate statistical methods that can describe and model complex relationships between variables. The extended ANOVA simultaneous component analysis (ASCA+) framework combines general linear models and principal component analysis (PCA) to decompose and visualize the separate effects of experimental factors. It has recently been demonstrated how linear mixed models can be included in the framework to analyze data from longitudinal experimental designs with repeated measurements (RM-ASCA+). The ALASCA package for R makes the ASCA+ framework accessible for general use and includes multiple methods for validation and visualization. The package is especially useful for longitudinal data and the ability to easily adjust for covariates is an important strength. This paper demonstrates how the ALASCA package can be applied to gain insights into multivariate data from interventional as well as observational designs. Publicly available data sets from four studies are used to demonstrate the methods available (proteomics, metabolomics, and transcriptomics).
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Affiliation(s)
- Anders Hagen Jarmund
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway,Centre of Molecular Inflammation Research (CEMIR), NTNU, Trondheim, Norway,*Correspondence: Anders Hagen Jarmund,
| | | | - Guro F. Giskeødegård
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Trondheim, Norway
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24
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Liao Z, Vosberg DE, Pausova Z, Paus T. A Shifting Relationship Between Sex Hormone-Binding Globulin and Total Testosterone Across Puberty in Boys. J Clin Endocrinol Metab 2022; 107:e4187-e4196. [PMID: 35965384 PMCID: PMC9516180 DOI: 10.1210/clinem/dgac484] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Indexed: 11/19/2022]
Abstract
CONTEXT Sex hormone-binding globulin (SHBG) is associated with levels of total testosterone (total-T), and both total-T and SHBG are associated with obesity. OBJECTIVE We aimed to clarify the nature of the relationship between testosterone and SHBG and improve our understanding of their relationships with obesity. We hypothesize that the hypothalamic-pituitary-gonadal axis contributes to the homeostasis of testosterone by increasing the production of gonadal testosterone through a feedback mechanism that might operate differently at different pubertal stages. METHODS We investigated the dynamics of the relationship between SHBG, total-T, and body mass index (BMI) throughout puberty (from age 9 to 17) using longitudinal data obtained in 507 males. The directionality of this relationship was explored using polygenic scores of SHBG and total-T, and a two-sample Mendelian Randomization (MR) in male adults. RESULTS Consistent with our hypothesis, we found positive relationships between SHBG and total-T at age 15 and 17 but either no relationship or a negative relationship during the earlier time points. Such shifting relationships explained age-related changes in the association between total-T and BMI. Polygenic scores of SHBG and total-T in mediation analyses and the two-sample MR in male adults suggested an effect of SHBG on total-T but also a somewhat weaker effect of total-T on SHBG. Two-sample MR also showed an effect of BMI on SHBG but no effect of SHBG on BMI. CONCLUSION These results clarify the nature of the relationship between testosterone and SHBG during puberty and adulthood and shed new light on their possible relationship with obesity.
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Affiliation(s)
- Zhijie Liao
- Department of Psychology, University of Toronto, Toronto, Ontario, M5S 3G3, Canada
| | - Daniel E Vosberg
- Centre Hospitalier Universitaire (CHU) Sainte-Justine, Montreal, Quebec, H3T 1C5, Canada
- Departments of Psychiatry and Neuroscience, University of Montreal, Montreal, Quebec, H3T 1J4, Canada
| | - Zdenka Pausova
- Research Institute of the Hospital for Sick Children, Toronto, Ontario, M5G 0A4, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, M5S 1A8, Canada
- Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, M5S 1A8, Canada
| | - Tomas Paus
- Department of Psychology, University of Toronto, Toronto, Ontario, M5S 3G3, Canada
- Centre Hospitalier Universitaire (CHU) Sainte-Justine, Montreal, Quebec, H3T 1C5, Canada
- Departments of Psychiatry and Neuroscience, University of Montreal, Montreal, Quebec, H3T 1J4, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario, M5T 1R8, Canada
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25
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Goudswaard LJ, Corbin LJ, Burley KL, Mumford A, Akbari P, Soranzo N, Butterworth AS, Watkins NA, Pournaras DJ, Harris J, Timpson NJ, Hers I. Higher body mass index raises immature platelet count: potential contribution to obesity-related thrombosis. Platelets 2022; 33:869-878. [PMID: 35068290 DOI: 10.1080/09537104.2021.2003317] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 10/08/2021] [Accepted: 10/21/2021] [Indexed: 02/02/2023]
Abstract
Higher body mass index (BMI) is a risk factor for thrombosis. Platelets are essential for hemostasis but contribute to thrombosis when activated pathologically. We hypothesized that higher BMI leads to changes in platelet characteristics, thereby increasing thrombotic risk. The effect of BMI on platelet traits (measured by Sysmex) was explored in 33 388 UK blood donors (INTERVAL study). Linear regression showed that higher BMI was positively associated with greater plateletcrit (PCT), platelet count (PLT), immature platelet count (IPC), and side fluorescence (SFL, a measure of mRNA content used to derive IPC). Mendelian randomization (MR), applied to estimate a causal effect with BMI proxied by a genetic risk score, provided causal estimates for a positive effect of BMI on both SFL and IPC, but there was little evidence for a causal effect of BMI on PCT or PLT. Follow-up analyses explored the functional relevance of platelet characteristics in a pre-operative cardiac cohort (COPTIC). Linear regression provided observational evidence for a positive association between IPC and agonist-induced whole blood platelet aggregation. Results indicate that higher BMI raises the number of immature platelets, which is associated with greater whole blood platelet aggregation in a cardiac cohort. Higher IPC could therefore contribute to obesity-related thrombosis.
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Affiliation(s)
- Lucy J Goudswaard
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK
- Bristol Heart Institute, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Laura J Corbin
- Medical Research Council (MRC) Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Kate L Burley
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK
| | - Andrew Mumford
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
| | - Parsa Akbari
- Department of Public Health and Primary Care, British Heart Foundation Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, UK
- National Institute for Health Research Blood and Transplant Research Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Human Genetics, Wellcome Sanger Institute, Hinxton, UK
| | - Nicole Soranzo
- National Institute for Health Research Blood and Transplant Research Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- Human Genetics, Wellcome Sanger Institute, Hinxton, UK
- Department of Haematology, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Adam S Butterworth
- Department of Public Health and Primary Care, British Heart Foundation Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, UK
- National Institute for Health Research Blood and Transplant Research Unit (NIHR BTRU) in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- NIHR Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
| | | | - Dimitri J Pournaras
- Department of Bariatric and Metabolic Surgery, Southmead Hospital, North Bristol NHS Trust, Bristol, UK
| | - Jessica Harris
- Bristol Trials Centre, Faculty of Health Sciences, University of Bristol, Bristol, UK
| | - Nicholas J Timpson
- Medical Research Council (MRC) Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ingeborg Hers
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK
- Bristol Heart Institute, Bristol, UK
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26
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Han BX, Yan SS, Xu Q, Ni JJ, Wei XT, Feng GJ, Zhang H, Li B, Zhang L, Pei YF. Mendelian Randomization Analysis Reveals Causal Effects of Plasma Proteome on Body Composition Traits. J Clin Endocrinol Metab 2022; 107:e2133-e2140. [PMID: 34922401 DOI: 10.1210/clinem/dgab911] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Indexed: 11/19/2022]
Abstract
CONTEXT Observational studies have demonstrated associations between plasma proteins and obesity, but evidence of causal relationship remains to be studied. OBJECTIVE We aimed to evaluate the causal relationship between plasma proteins and body composition. METHODS We conducted a 2-sample Mendelian randomization (MR) analysis based on the genome-wide association study (GWAS) summary statistics of 23 body composition traits and 2656 plasma proteins. We then performed hierarchical cluster analysis to evaluate the structure and pattern of the identified causal associations, and we performed gene ontology enrichment analysis to explore the functional relevance of the identified proteins. RESULTS We identified 430 putatively causal effects of 96 plasma proteins on 22 body composition traits (except obesity status) with strong MR evidence (P < 2.53 × 10 - 6, at a Bonferroni-corrected threshold). The top 3 causal associations are follistatin (FST) on trunk fat-free mass (Beta = -0.63, SE = 0.04, P = 2.00 × 10-63), insulin-like growth factor-binding protein 1 (IGFBP1) on trunk fat-free mass (Beta = -0.54, SE = 0.03, P = 1.79 × 10-57) and r-spondin-3 (RSPO3) on WHR (waist circumference/hip circumference) (Beta = 0.01, SE = 4.47 × 10-4, P = 5.45 × 10-60), respectively. Further clustering analysis and pathway analysis demonstrated that the pattern of causal effect to fat mass and fat-free mass may be different. CONCLUSION Our findings may provide evidence for causal relationships from plasma proteins to various body composition traits and provide basis for further targeted functional studies.
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Affiliation(s)
- Bai-Xue Han
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, Jiangsu, PR China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Jiangsu, PR China
| | - Shan-Shan Yan
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, Jiangsu, PR China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Jiangsu, PR China
| | - Qian Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, Jiangsu, PR China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Jiangsu, PR China
| | - Jing-Jing Ni
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Jiangsu, PR China
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Jiangsu, PR China
| | - Xin-Tong Wei
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, Jiangsu, PR China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Jiangsu, PR China
| | - Gui-Juan Feng
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, Jiangsu, PR China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Jiangsu, PR China
| | - Hong Zhang
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Jiangsu, PR China
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Jiangsu, PR China
| | - Bin Li
- Department of General Surgery, Suzhou Ninth Hospital Affiliated to Soochow University; Affiliated Wujiang Hospital of Nantong University; Suzhou Ninth People's Hospital, Suzhou, Jiangsu, PR China
| | - Lei Zhang
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Jiangsu, PR China
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Jiangsu, PR China
| | - Yu-Fang Pei
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, Jiangsu, PR China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Jiangsu, PR China
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