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Zhong Z, Hu Z, Zhou W, Qin X, Tan S. The bone marrow lipidomics of mice reveal sex-related differences. Biomed Chromatogr 2024; 38:e5875. [PMID: 38643980 DOI: 10.1002/bmc.5875] [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: 01/12/2024] [Revised: 02/25/2024] [Accepted: 03/17/2024] [Indexed: 04/23/2024]
Abstract
Osteoporosis is a common skeletal disorder characterized by an imbalance between bone resorption and formation, exhibiting a higher prevalence in women compared with men. While previous studies have primarily focused on genomics and genetics in osteoporosis susceptibility, there is a lack of systematic exploration of sex-specific differences in lipid levels in mouse bone marrow. Multiple reaction monitoring-based liquid chromatography-trandem mass spectrometry (LC-MS/MS) was used to quantify lipidomic profiles in bone marrow samples from three female mice and three male mice. The LC-MS/MS technique based on the multiple reaction monitoring method identified and quantified 184 lipids from 15 lipid classes. The contents of most lipids in the bone marrow cells of female mice were higher than those in male mice, including four polyunsaturated fatty acids, three phospholipids and four sphingolipids. Among all the lipid molecules, lactosylceramide (d18:0/16:0) showed the highest fold change in female mice, while its precursor lipid, glucosylceramide, was the most up-regulated in male mice. This study, focusing on bone marrow lipidomics, elucidates significant sexual dimorphism in lipid levels within bone marrow cells. It provides novel evidence supporting the higher prevalence of osteoporosis in women and enhances our understanding of the connection between sex-specific lipid levels and the risk of osteoporosis.
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Affiliation(s)
- Ziqing Zhong
- Department of Orthopaedic Surgery, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Zuojian Hu
- Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Wei Zhou
- Department of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Xue Qin
- Department of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Shaolin Tan
- Department of Orthopaedic Surgery, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China
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Menassa M, Franco OH, Galenkamp H, Moll van Charante EP, van den Born BJH, Vriend EMC, Vidal PM, Stronks K. Healthy ageing in a multi-ethnic population: A descriptive cross-sectional analysis from the HELIUS study. Maturitas 2024; 184:107972. [PMID: 38507885 DOI: 10.1016/j.maturitas.2024.107972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 02/29/2024] [Accepted: 03/12/2024] [Indexed: 03/22/2024]
Abstract
OBJECTIVE We investigated ethnic health disparities in the Healthy Life in an Urban Setting multi-ethnic cohort using the multidimensional Healthy Ageing Score. STUDY DESIGN We conducted a cross-sectional analysis of the study baseline data (2011-2015) collected through questionnaires/physical examinations for 17,091 participants (54.8 % women, mean (SD) age = 44.5 (12.8) years) from South-Asian Surinamese (14.8 %), African Surinamese (20.5 %), Dutch (24.3 %), Moroccan (15.5 %), Turkish (14.9 %), and Ghanaian (10.1 %) origins, living in Amsterdam, the Netherlands. MAIN OUTCOME MEASURES We computed the Healthy Ageing Score developed in the Rotterdam Study, which has seven biopsychosocial domains: chronic diseases, mental health, cognitive function, physical function, pain, social support, and quality of life. That score was used to discern between healthy, moderate, and poor ageing. We explored differences in healthy ageing by ethnicity, sex, and age group using multinomial logistic regression. RESULTS The Healthy Ageing Score [overall: poor (69.0 %), moderate (24.8 %), and healthy (6.2 %)] differed between ethnicities and was poorer in women and after midlife (cut-off 45 years) across ethnicities (all p < 0.001). In the fully adjusted models in men and women, poor ageing (vs. healthy ageing) was highest in the South-Asian Surinamese [adjusted odds ratios (95 % confidence intervals)] [2.96 (2.24-3.90) and 6.88 (3.29-14.40), respectively] and Turkish [2.80 (2.11-3.73) and 7.10 (3.31-15.24), respectively] vs. Dutch, in the oldest [5.89 (3.62-9.60) and 13.17 (1.77-98.01), respectively] vs. youngest, and in the divorced [1.48 (1.10-2.01) and 2.83 (1.39-5.77), respectively] vs. married. Poor ageing was inversely associated with educational and occupational levels, mainly in men. CONCLUSIONS Compared with those of Dutch ethnic origin, ethnic minorities displayed less healthy ageing, which was more pronounced in women, before and after midlife, and was associated with sociodemographic factors.
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Affiliation(s)
- Marilyne Menassa
- Institute of Social and Preventive Medicine, University of Bern, Mittelstrasse, 43 3012 Bern, Switzerland; Graduate School for Health Sciences, University of Bern, Mittelstrasse, 43 3012 Bern, Switzerland; Department of Global Public Health & Bioethics, Julius Center for Health Science and Primary Care, UMC Utrecht, Utrecht University, P.O. Box 85500, 3508 GA Utrecht, the Netherlands.
| | - Oscar H Franco
- Institute of Social and Preventive Medicine, University of Bern, Mittelstrasse, 43 3012 Bern, Switzerland; Department of Global Public Health & Bioethics, Julius Center for Health Science and Primary Care, UMC Utrecht, Utrecht University, P.O. Box 85500, 3508 GA Utrecht, the Netherlands.
| | - Henrike Galenkamp
- Department of Public and Occupational Health, Amsterdam University Medical Centers, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands.
| | - Eric P Moll van Charante
- Department of Public and Occupational Health, Amsterdam University Medical Centers, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands.
| | - Bert-Jan H van den Born
- Department of Public and Occupational Health, Amsterdam University Medical Centers, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands.
| | - Esther M C Vriend
- Department of Public and Occupational Health, Amsterdam University Medical Centers, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands.
| | - Pedro Marques Vidal
- Department of Medicine, Internal Medicine, Lausanne University Hospital, University of Lausanne, Rue du Bugnon 46, CH-1011 Lausanne, Switzerland.
| | - Karien Stronks
- Department of Public and Occupational Health, Amsterdam University Medical Centers, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands.
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Barranco-Altirriba M, Alonso N, Weber RJM, Lloyd GR, Hernandez M, Yanes O, Capellades J, Jankevics A, Winder C, Falguera M, Franch-Nadal J, Dunn WB, Perera-Lluna A, Castelblanco E, Mauricio D. Lipidome characterisation and sex-specific differences in type 1 and type 2 diabetes mellitus. Cardiovasc Diabetol 2024; 23:109. [PMID: 38553758 PMCID: PMC10981308 DOI: 10.1186/s12933-024-02202-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 03/14/2024] [Indexed: 04/01/2024] Open
Abstract
BACKGROUND In this study, we evaluated the lipidome alterations caused by type 1 diabetes (T1D) and type 2 diabetes (T2D), by determining lipids significantly associated with diabetes overall and in both sexes, and lipids associated with the glycaemic state. METHODS An untargeted lipidomic analysis was performed to measure the lipid profiles of 360 subjects (91 T1D, 91 T2D, 74 with prediabetes and 104 controls (CT)) without cardiovascular and/or chronic kidney disease. Ultra-high performance liquid chromatography-electrospray ionization mass spectrometry (UHPLC-ESI-MS) was conducted in two ion modes (positive and negative). We used multiple linear regression models to (1) assess the association between each lipid feature and each condition, (2) determine sex-specific differences related to diabetes, and (3) identify lipids associated with the glycaemic state by considering the prediabetes stage. The models were adjusted by sex, age, hypertension, dyslipidaemia, body mass index, glucose, smoking, systolic blood pressure, triglycerides, HDL cholesterol, LDL cholesterol, alternate Mediterranean diet score (aMED) and estimated glomerular filtration rate (eGFR); diabetes duration and glycated haemoglobin (HbA1c) were also included in the comparison between T1D and T2D. RESULTS A total of 54 unique lipid subspecies from 15 unique lipid classes were annotated. Lysophosphatidylcholines (LPC) and ceramides (Cer) showed opposite effects in subjects with T1D and subjects with T2D, LPCs being mainly up-regulated in T1D and down-regulated in T2D, and Cer being up-regulated in T2D and down-regulated in T1D. Also, Phosphatidylcholines were clearly down-regulated in subjects with T1D. Regarding sex-specific differences, ceramides and phosphatidylcholines exhibited important diabetes-associated differences due to sex. Concerning the glycaemic state, we found a gradual increase of a panel of 1-deoxyceramides from normoglycemia to prediabetes to T2D. CONCLUSIONS Our findings revealed an extensive disruption of lipid metabolism in both T1D and T2D. Additionally, we found sex-specific lipidome changes associated with diabetes, and lipids associated with the glycaemic state that can be linked to previously described molecular mechanisms in diabetes.
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Affiliation(s)
- Maria Barranco-Altirriba
- Department of Endocrinology & Nutrition, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, B2SLab, Barcelona, Spain
- Networking Biomedical Research Centre in the subject area of Bioengineering, Biomaterials and Nanomedicine, CIBER-BBN), Madrid, Spain
- Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
| | - Núria Alonso
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Barcelona, Spain
- Servicio de Endocrinología y Nutrición, Hospital Universitario e Instituto de Investigación en Ciencias de la Salud Germans Trias i Pujol, Badalona, Barcelona, Spain
- Departament de Medicina, Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
| | - Ralf J M Weber
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Institute of Metabolism and Systems Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Gavin R Lloyd
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Institute of Metabolism and Systems Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Marta Hernandez
- Department of Endocrinology & Nutrition, Hospital Universitari Arnau de Vilanova, Institut de Recerca Biomèdica de Lleida (IRBLleida), Lleida, Spain
| | - Oscar Yanes
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Barcelona, Spain
- Department of Electronic Engineering, Universitat Rovira i Virgili, IISPV, Tarragona, Spain
| | - Jordi Capellades
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Barcelona, Spain
- Institut Investigació Sanitària Pere Virgili (IISPV), Tarragona, Spain
| | - Andris Jankevics
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research, Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands
- Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Catherine Winder
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Centre for Metabolomics Research, Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L69 7ZB, Liverpool, UK
| | - Mireia Falguera
- Institut d'Investigació Biomèdica, Centre Atenció Primària Cervera, Gerència d'Atenció Primària, Universitat de Lleida, Institut Català de la Salut, Lleida, Spain
| | - Josep Franch-Nadal
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Barcelona, Spain
- DAP-Cat Group, Unitat de Suport a La Recerca Barcelona Ciutat, Institut Universitari d'Investigació en Atenció Primària Jordi Gol, Barcelona, Spain
| | - Warwick B Dunn
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Centre for Metabolomics Research, Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L69 7ZB, Liverpool, UK
| | - Alexandre Perera-Lluna
- Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, B2SLab, Barcelona, Spain
- Networking Biomedical Research Centre in the subject area of Bioengineering, Biomaterials and Nanomedicine, CIBER-BBN), Madrid, Spain
- Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
| | - Esmeralda Castelblanco
- Division of Endocrinology, Metabolism and Lipid Research, Department of Internal Medicine, Washington University School of Medicine, 63110, St. Louis, MO, USA.
- Unitat de Suport a la Recerca Barcelona, Institut Universitari d'Investigació en Atenció Primària Jordi Gol i Gurina, 08007, Barcelona, Spain.
| | - Didac Mauricio
- Department of Endocrinology & Nutrition, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain.
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Barcelona, Spain.
- Institut d'Investigació Biomèdica Sant Pau (IR Sant Pau), 08041, Barcelona, Spain.
- Faculty of Medicine, University of Vic, Vic, Spain.
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Tabassum R, Widén E, Ripatti S. Effect of biological sex on human circulating lipidome: An overview of the literature. Atherosclerosis 2023; 384:117274. [PMID: 37743161 DOI: 10.1016/j.atherosclerosis.2023.117274] [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: 02/28/2023] [Revised: 04/28/2023] [Accepted: 09/01/2023] [Indexed: 09/26/2023]
Abstract
Cardiovascular diseases (CVD) are the leading cause of death worldwide for both men and women, but their prevalence and burden show marked sex differences. The existing knowledge gaps in research, prevention, and treatment for women emphasize the need for understanding the biological mechanisms contributing to the sex differences in CVD. Sex differences in the plasma lipids that are well-known risk factors and predictors of CVD events have been recognized and are believed to contribute to the known disparities in CVD manifestations in men and women. However, the current understanding of sex differences in lipids has mainly come from the studies on routinely measured standard lipids- low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total triglycerides, and total cholesterol, which have been the mainstay of the lipid profiling. Sex differences in individual lipid species, collectively called the lipidome, have until recently been less explored due to the technological challenges and analytic costs. With the technological advancements in the last decade and growing interest in understanding mechanisms of sexual dimorphism in metabolic disorders, many investigators utilized metabolomics and lipidomics based platforms to examine the effect of biological sex on detailed lipidomic profiles and individual lipid species. This review presents an overview of the research on sex differences in the concentrations of circulating lipid species, focusing on findings from the metabolome- and lipidome-wide studies. We also discuss the potential contribution of genetic factors including sex chromosomes and sex-specific physiological factors such as menopause and sex hormones to the sex differences in lipidomic profiles.
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Affiliation(s)
- Rubina Tabassum
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland.
| | - Elisabeth Widén
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland; Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA.
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5
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Verhaar BJH, Mosterd CM, Collard D, Galenkamp H, Muller M, Rampanelli E, van Raalte DH, Nieuwdorp M, van den Born BJH. Sex differences in associations of plasma metabolites with blood pressure and heart rate variability: The HELIUS study. Atherosclerosis 2023; 384:117147. [PMID: 37286456 DOI: 10.1016/j.atherosclerosis.2023.05.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 04/27/2023] [Accepted: 05/17/2023] [Indexed: 06/09/2023]
Abstract
BACKGROUND AND AIMS Since plasma metabolites can modulate blood pressure (BP) and vary between men and women, we examined sex differences in plasma metabolite profiles associated with BP and sympathicovagal balance. Our secondary aim was to investigate associations between gut microbiota composition and plasma metabolites predictive of BP and heart rate variability (HRV). METHODS From the HELIUS cohort, we included 196 women and 173 men. Office systolic BP and diastolic BP were recorded, and heart rate variability (HRV) and baroreceptor sensitivity (BRS) were calculated using finger photoplethysmography. Plasma metabolomics was measured using untargeted LC-MS/MS. Gut microbiota composition was determined using 16S sequencing. We used machine learning models to predict BP and HRV from metabolite profiles, and to predict metabolite levels from gut microbiota composition. RESULTS In women, best predicting metabolites for systolic BP included dihomo-lineoylcarnitine, 4-hydroxyphenylacetateglutamine and vanillactate. In men, top predictors included sphingomyelins, N-formylmethionine and conjugated bile acids. Best predictors for HRV in men included phenylacetate and gentisate, which were associated with lower HRV in men but not in women. Several of these metabolites were associated with gut microbiota composition, including phenylacetate, multiple sphingomyelins and gentisate. CONCLUSIONS Plasma metabolite profiles are associated with BP in a sex-specific manner. Catecholamine derivatives were more important predictors for BP in women, while sphingomyelins were more important in men. Several metabolites were associated with gut microbiota composition, providing potential targets for intervention.
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Affiliation(s)
- Barbara J H Verhaar
- Department of Internal and Vascular Medicine, Amsterdam UMC, Location AMC, Amsterdam, the Netherlands; Department of Internal Medicine - Geriatrics, Amsterdam UMC, Location VUmc, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands.
| | - Charlotte M Mosterd
- Department of Internal and Vascular Medicine, Amsterdam UMC, Location AMC, Amsterdam, the Netherlands; Diabetes Center, Department of Internal Medicine, Amsterdam UMC, Location VUmc, Amsterdam, the Netherlands
| | - Didier Collard
- Department of Internal and Vascular Medicine, Amsterdam UMC, Location AMC, Amsterdam, the Netherlands
| | - Henrike Galenkamp
- Department of Public and Occupational Health, Amsterdam UMC, Location AMC, Amsterdam, the Netherlands; Amsterdam Public Health Research Institute, Health Behaviors and Chronic Diseases, Amsterdam, the Netherlands
| | - Majon Muller
- Department of Internal Medicine - Geriatrics, Amsterdam UMC, Location VUmc, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Elena Rampanelli
- Department of Internal and Vascular Medicine, Amsterdam UMC, Location AMC, Amsterdam, the Netherlands
| | - Daniël H van Raalte
- Department of Internal and Vascular Medicine, Amsterdam UMC, Location AMC, Amsterdam, the Netherlands; Diabetes Center, Department of Internal Medicine, Amsterdam UMC, Location VUmc, Amsterdam, the Netherlands
| | - Max Nieuwdorp
- Department of Internal and Vascular Medicine, Amsterdam UMC, Location AMC, Amsterdam, the Netherlands; Wallenberg Laboratory, Department of Molecular and Clinical Medicine, Sahlgrenska Academy, Goteborgs Universitet, Gothenburg, Sweden
| | - Bert-Jan H van den Born
- Department of Internal and Vascular Medicine, Amsterdam UMC, Location AMC, Amsterdam, the Netherlands; Department of Public and Occupational Health, Amsterdam UMC, Location AMC, Amsterdam, the Netherlands
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Bockus LB, Jensen PN, Fretts AM, Hoofnagle AN, McKnight B, Sitlani CM, Siscovick DS, King IB, Psaty BM, Sotoodehnia N, Lemaitre RN. Plasma Ceramides and Sphingomyelins and Sudden Cardiac Death in the Cardiovascular Health Study. JAMA Netw Open 2023; 6:e2343854. [PMID: 37976059 PMCID: PMC10656644 DOI: 10.1001/jamanetworkopen.2023.43854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 10/09/2023] [Indexed: 11/19/2023] Open
Abstract
Importance Sphingolipids, including ceramides and sphingomyelins, may influence the pathophysiology and risk of sudden cardiac death (SCD) through multiple biological activities. Whether the length of the fatty acid acylated to plasma sphingolipid species is associated with SCD risk is not known. Objective To determine whether the saturated fatty acid length of plasma ceramides and sphingomyelins influences the association with SCD risk. Design, Setting, and Participants In this cohort study, multivariable Cox proportional hazards regression models were used to examine the association of sphingolipid species with SCD risk. The study population included 4612 participants in the Cardiovascular Health Study followed up prospectively for a median of 10.2 (IQR, 5.5-11.6) years. Baseline data were collected from January 1992 to December 1995 during annual examinations. Data were analyzed from February 11, 2020, to September 9, 2023. Exposures Eight plasma sphingolipid species (4 ceramides and 4 sphingomyelins) with saturated fatty acids of 16, 20, 22, and 24 carbons. Main Outcome and Measure Association of plasma ceramides and sphingomyelins with saturated fatty acids of different lengths with SCD risk. Results Among the 4612 CHS participants included in the analysis (mean [SD] age, 77 [5] years; 2724 [59.1%] women; 6 [0.1%] American Indian; 4 [0.1%] Asian; 718 [15.6%] Black; 3869 [83.9%] White, and 15 [0.3%] Other), 215 SCD cases were identified. In adjusted Cox proportional hazards regression analyses, plasma ceramides and sphingomyelins with palmitic acid (Cer-16 and SM-16) were associated with higher SCD risk per higher SD of log sphingolipid levels (hazard ratio [HR] for Cer-16, 1.34 [95% CI, 1.12-1.59]; HR for SM-16, 1.37 [95% CI, 1.12-1.67]). Associations did not differ by baseline age, sex, race, or body mass index. No significant association of SCD with sphingolipids with very-long-chain saturated fatty acids was observed after correction for multiple testing (HR for ceramide with arachidic acid, 1.06 [95% CI, 0.90-1.24]; HR for ceramide with behenic acid, 0.92 [95% CI, 0.77-1.10]; HR for ceramide with lignoceric acid, 0.92 [95% CI, 0.77-1.09]; HR for sphingomyelin with arachidic acid, 0.83 [95% CI, 0.71-0.98]; HR for sphingomyelin with behenic acid, 0.84 [95% CI, 0.70-1.00]; HR for sphingomyelin with lignoceric acid, 0.86 [95% CI, 0.72-1.03]). Conclusions and Relevance The findings of this large, population-based cohort study of SCD identified that higher plasma levels of Cer-16 and SM-16 were associated with higher risk of SCD. Future studies are needed to examine the underlying mechanism of these associations.
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Affiliation(s)
- Lee B Bockus
- Department of Medicine, University of Washington, Seattle
| | - Paul N Jensen
- Department of Medicine, University of Washington, Seattle
| | - Amanda M Fretts
- Department of Epidemiology, University of Washington, Seattle
| | - Andrew N Hoofnagle
- Departments of Laboratory Medicine and Pathology, University of Washington, Seattle
| | | | | | | | - Irena B King
- Department of Internal Medicine, University of New Mexico, Albuquerque
| | - Bruce M Psaty
- Department of Medicine, University of Washington, Seattle
- Department of Epidemiology, University of Washington, Seattle
- Department of Health Systems and Population Health, University of Washington, Seattle
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7
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van Kruining D, Losen M, Crivelli SM, de Jong JJA, Jansen JFA, Backes WH, Monereo‐Sánchez J, van Boxtel MPJ, Köhler S, Linden DEJ, Schram MT, Mielke MM, Martinez‐Martinez P. Plasma ceramides relate to mild cognitive impairment in middle-aged men: The Maastricht Study. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12459. [PMID: 37675435 PMCID: PMC10478166 DOI: 10.1002/dad2.12459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 06/29/2023] [Accepted: 07/01/2023] [Indexed: 09/08/2023]
Abstract
Introduction There is an urgent need for biomarkers identifying individuals at risk of early-stage cognitive impairment. Using cross-sectional data from The Maastricht Study, this study included 197 individuals with mild cognitive impairment (MCI) and 200 cognitively unimpaired individuals aged 40 to 75, matched by age, sex, and educational level. Methods We assessed the association of plasma sphingolipid and ceramide transfer protein (CERT) levels with MCI and adjusted for potentially confounding risk factors. Furthermore, the relationship of plasma sphingolipids and CERTs with magnetic resonance imaging brain volumes was assessed and age- and sex-stratified analyses were performed. Results Associations of plasma ceramide species C18:0 and C24:1 and combined plasma ceramide chain lengths (ceramide risk score) with MCI were moderated by sex, but not by age, and higher levels were associated with MCI in men. No associations were found among women. In addition, higher levels of ceramide C20:0, C22:0, and C24:1, but not the ceramide risk score, were associated with larger volume of the hippocampus after controlling for covariates, independent of MCI. Although higher plasma ceramide C18:0 was related to higher plasma CERT levels, no association of CERT levels was found with MCI or brain volumes. Discussion Our results warrant further analysis of plasma ceramides as potential markers for MCI in middle-aged men. In contrast to previous studies, no associations of plasma sphingolipids with MCI or brain volumes were found in women, independent of age. These results highlight the importance of accounting for sex- and age-related factors when examining sphingolipid and CERT metabolism related to cognitive function.
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Affiliation(s)
- Daan van Kruining
- School for Mental Health and NeuroscienceFaculty of HealthMedicine, and Life SciencesMaastricht UniversityMaastrichtthe Netherlands
- Department of Psychiatry and NeuropsychologyMaastricht UniversityMaastrichtthe Netherlands
| | - Mario Losen
- School for Mental Health and NeuroscienceFaculty of HealthMedicine, and Life SciencesMaastricht UniversityMaastrichtthe Netherlands
- Department of Psychiatry and NeuropsychologyMaastricht UniversityMaastrichtthe Netherlands
| | - Simone M. Crivelli
- Department of PhysiologyUniversity of Kentucky College of MedicineLexingtonKentuckyUSA
| | - Joost J. A. de Jong
- School for Mental Health and NeuroscienceFaculty of HealthMedicine, and Life SciencesMaastricht UniversityMaastrichtthe Netherlands
- Department of Radiology and Nuclear MedicineMaastricht University Medical Center+ (MUMC+)Maastrichtthe Netherlands
| | - Jacobus F. A. Jansen
- School for Mental Health and NeuroscienceFaculty of HealthMedicine, and Life SciencesMaastricht UniversityMaastrichtthe Netherlands
- Department of Radiology and Nuclear MedicineMaastricht University Medical Center+ (MUMC+)Maastrichtthe Netherlands
- Department of Electrical EngineeringEindhoven University of TechnologyEindhoventhe Netherlands
| | - Walter H. Backes
- School for Mental Health and NeuroscienceFaculty of HealthMedicine, and Life SciencesMaastricht UniversityMaastrichtthe Netherlands
- Department of Radiology and Nuclear MedicineMaastricht University Medical Center+ (MUMC+)Maastrichtthe Netherlands
| | - Jennifer Monereo‐Sánchez
- School for Mental Health and NeuroscienceFaculty of HealthMedicine, and Life SciencesMaastricht UniversityMaastrichtthe Netherlands
- Department of Radiology and Nuclear MedicineMaastricht University Medical Center+ (MUMC+)Maastrichtthe Netherlands
| | - Martin P. J. van Boxtel
- School for Mental Health and NeuroscienceFaculty of HealthMedicine, and Life SciencesMaastricht UniversityMaastrichtthe Netherlands
- Department of Psychiatry and NeuropsychologyMaastricht UniversityMaastrichtthe Netherlands
| | - Sebastian Köhler
- School for Mental Health and NeuroscienceFaculty of HealthMedicine, and Life SciencesMaastricht UniversityMaastrichtthe Netherlands
- Department of Psychiatry and NeuropsychologyMaastricht UniversityMaastrichtthe Netherlands
| | - David E. J. Linden
- School for Mental Health and NeuroscienceFaculty of HealthMedicine, and Life SciencesMaastricht UniversityMaastrichtthe Netherlands
- Department of Psychiatry and NeuropsychologyMaastricht UniversityMaastrichtthe Netherlands
| | - Miranda T. Schram
- School for Mental Health and NeuroscienceFaculty of HealthMedicine, and Life SciencesMaastricht UniversityMaastrichtthe Netherlands
- Department of Internal MedicineMaastricht University Medical Center+ (MUMC+)Maastrichtthe Netherlands
- Heart and Vascular CenterMaastricht University Medical Center+ (MUMC+)Maastrichtthe Netherlands
- School for Cardiovascular Diseases (CARIM)Faculty of HealthMedicine, and Life SciencesMaastricht UniversityMaastrichtthe Netherlands
| | - Michelle M. Mielke
- Department of Epidemiology and PreventionWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Pilar Martinez‐Martinez
- School for Mental Health and NeuroscienceFaculty of HealthMedicine, and Life SciencesMaastricht UniversityMaastrichtthe Netherlands
- Department of Psychiatry and NeuropsychologyMaastricht UniversityMaastrichtthe Netherlands
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8
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Medina J, Borreggine R, Teav T, Gao L, Ji S, Carrard J, Jones C, Blomberg N, Jech M, Atkins A, Martins C, Schmidt-Trucksass A, Giera M, Cazenave-Gassiot A, Gallart-Ayala H, Ivanisevic J. Omic-Scale High-Throughput Quantitative LC-MS/MS Approach for Circulatory Lipid Phenotyping in Clinical Research. Anal Chem 2023; 95:3168-3179. [PMID: 36716250 DOI: 10.1021/acs.analchem.2c02598] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Lipid analysis at the molecular species level represents a valuable opportunity for clinical applications due to the essential roles that lipids play in metabolic health. However, a comprehensive and high-throughput lipid profiling remains challenging given the lipid structural complexity and exceptional diversity. Herein, we present an 'omic-scale targeted LC-MS/MS approach for the straightforward and high-throughput quantification of a broad panel of complex lipid species across 26 lipid (sub)classes. The workflow involves an automated single-step extraction with 2-propanol, followed by lipid analysis using hydrophilic interaction liquid chromatography in a dual-column setup coupled to tandem mass spectrometry with data acquisition in the timed-selective reaction monitoring mode (12 min total run time). The analysis pipeline consists of an initial screen of 1903 lipid species, followed by high-throughput quantification of robustly detected species. Lipid quantification is achieved by a single-point calibration with 75 isotopically labeled standards representative of different lipid classes, covering lipid species with diverse acyl/alkyl chain lengths and unsaturation degrees. When applied to human plasma, 795 lipid species were measured with median intra- and inter-day precisions of 8.5 and 10.9%, respectively, evaluated within a single and across multiple batches. The concentration ranges measured in NIST plasma were in accordance with the consensus intervals determined in previous ring-trials. Finally, to benchmark our workflow, we characterized NIST plasma materials with different clinical and ethnic backgrounds and analyzed a sub-set of sera (n = 81) from a clinically healthy elderly population. Our quantitative lipidomic platform allowed for a clear distinction between different NIST materials and revealed the sex-specificity of the serum lipidome, highlighting numerous statistically significant sex differences.
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Affiliation(s)
- Jessica Medina
- Metabolomics Platform, Faculty of Biology and Medicine, University of Lausanne, Quartier UNIL-CHUV, Rue du Bugnon 19, Lausanne CH-1005, Switzerland
| | - Rebecca Borreggine
- Metabolomics Platform, Faculty of Biology and Medicine, University of Lausanne, Quartier UNIL-CHUV, Rue du Bugnon 19, Lausanne CH-1005, Switzerland
| | - Tony Teav
- Metabolomics Platform, Faculty of Biology and Medicine, University of Lausanne, Quartier UNIL-CHUV, Rue du Bugnon 19, Lausanne CH-1005, Switzerland
| | - Liang Gao
- Department of Biochemistry and Precision Medicine TRP, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117456, Singapore.,Singapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore 117456, Singapore
| | - Shanshan Ji
- Singapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore 117456, Singapore
| | - Justin Carrard
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, Basel CH-4052, Switzerland
| | - Christina Jones
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, United States
| | - Niek Blomberg
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden 2333ZA, Netherlands
| | - Martin Jech
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States
| | - Alan Atkins
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States
| | - Claudia Martins
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States
| | - Arno Schmidt-Trucksass
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, Basel CH-4052, Switzerland
| | - Martin Giera
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden 2333ZA, Netherlands
| | - Amaury Cazenave-Gassiot
- Department of Biochemistry and Precision Medicine TRP, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117456, Singapore.,Singapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore 117456, Singapore
| | - Hector Gallart-Ayala
- Metabolomics Platform, Faculty of Biology and Medicine, University of Lausanne, Quartier UNIL-CHUV, Rue du Bugnon 19, Lausanne CH-1005, Switzerland
| | - Julijana Ivanisevic
- Metabolomics Platform, Faculty of Biology and Medicine, University of Lausanne, Quartier UNIL-CHUV, Rue du Bugnon 19, Lausanne CH-1005, Switzerland
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9
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Tabassum R, Ruotsalainen S, Ottensmann L, Gerl MJ, Klose C, Tukiainen T, Pirinen M, Simons K, Widén E, Ripatti S. Lipidome- and Genome-Wide Study to Understand Sex Differences in Circulatory Lipids. J Am Heart Assoc 2022; 11:e027103. [PMID: 36193934 PMCID: PMC9673737 DOI: 10.1161/jaha.122.027103] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background Despite well-recognized differences in the atherosclerotic cardiovascular disease risk between men and women, sex differences in risk factors and sex-specific mechanisms in the pathophysiology of atherosclerotic cardiovascular disease remain poorly understood. Lipid metabolism plays a central role in the development of atherosclerotic cardiovascular disease. Understanding sex differences in lipids and their genetic determinants could provide mechanistic insights into sex differences in atherosclerotic cardiovascular disease and aid in precise risk assessment. Herein, we examined sex differences in plasma lipidome and heterogeneity in genetic influences on lipidome in men and women through sex-stratified genome-wide association analyses. Methods and Results We used data consisting of 179 lipid species measured by shotgun lipidomics in 7266 individuals from the Finnish GeneRISK cohort and sought for replication using independent data from 2045 participants. Significant sex differences in the levels of 141 lipid species were observed (P<7.0×10-4). Interestingly, 121 lipid species showed significant age-sex interactions, with opposite age-related changes in 39 lipid species. In general, most of the cholesteryl esters, ceramides, lysophospholipids, and glycerides were higher in 45- to 50-year-old men compared with women of same age, but the sex differences narrowed down or reversed with age. We did not observe any major differences in genetic effect in the sex-stratified genome-wide association analyses, which suggests that common genetic variants do not have a major role in sex differences in lipidome. Conclusions Our study provides a comprehensive view of sex differences in circulatory lipids pointing to potential sex differences in lipid metabolism and highlights the need for sex- and age-specific prevention strategies.
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Affiliation(s)
- Rubina Tabassum
- Institute for Molecular Medicine Finland, HiLIFE University of Helsinki Finland
| | - Sanni Ruotsalainen
- Institute for Molecular Medicine Finland, HiLIFE University of Helsinki Finland
| | - Linda Ottensmann
- Institute for Molecular Medicine Finland, HiLIFE University of Helsinki Finland
| | | | | | - Taru Tukiainen
- Institute for Molecular Medicine Finland, HiLIFE University of Helsinki Finland
| | - Matti Pirinen
- Institute for Molecular Medicine Finland, HiLIFE University of Helsinki Finland.,Department of Public Health, Clinicum, Faculty of Medicine University of Helsinki Finland.,Department of Mathematics and Statistics University of Helsinki Finland
| | | | - Elisabeth Widén
- Institute for Molecular Medicine Finland, HiLIFE University of Helsinki Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, HiLIFE University of Helsinki Finland.,Department of Public Health, Clinicum, Faculty of Medicine University of Helsinki Finland.,Broad Institute of the Massachusetts Institute of Technology and Harvard University Cambridge MA USA
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10
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Sliz E, Shin J, Ahmad S, Williams DM, Frenzel S, Gauß F, Harris SE, Henning AK, Hernandez MV, Hu YH, Jiménez B, Sargurupremraj M, Sudre C, Wang R, Wittfeld K, Yang Q, Wardlaw JM, Völzke H, Vernooij MW, Schott JM, Richards M, Proitsi P, Nauck M, Lewis MR, Launer L, Hosten N, Grabe HJ, Ghanbari M, Deary IJ, Cox SR, Chaturvedi N, Barnes J, Rotter JI, Debette S, Ikram MA, Fornage M, Paus T, Seshadri S, Pausova Z. Circulating Metabolome and White Matter Hyperintensities in Women and Men. Circulation 2022; 145:1040-1052. [PMID: 35050683 PMCID: PMC9645366 DOI: 10.1161/circulationaha.121.056892] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 12/02/2021] [Indexed: 11/16/2022]
Abstract
BACKGROUND White matter hyperintensities (WMH), identified on T2-weighted magnetic resonance images of the human brain as areas of enhanced brightness, are a major risk factor of stroke, dementia, and death. There are no large-scale studies testing associations between WMH and circulating metabolites. METHODS We studied up to 9290 individuals (50.7% female, average age 61 years) from 15 populations of 8 community-based cohorts. WMH volume was quantified from T2-weighted or fluid-attenuated inversion recovery images or as hypointensities on T1-weighted images. Circulating metabolomic measures were assessed with mass spectrometry and nuclear magnetic resonance spectroscopy. Associations between WMH and metabolomic measures were tested by fitting linear regression models in the pooled sample and in sex-stratified and statin treatment-stratified subsamples. Our basic models were adjusted for age, sex, age×sex, and technical covariates, and our fully adjusted models were also adjusted for statin treatment, hypertension, type 2 diabetes, smoking, body mass index, and estimated glomerular filtration rate. Population-specific results were meta-analyzed using the fixed-effect inverse variance-weighted method. Associations with false discovery rate (FDR)-adjusted P values (PFDR)<0.05 were considered significant. RESULTS In the meta-analysis of results from the basic models, we identified 30 metabolomic measures associated with WMH (PFDR<0.05), 7 of which remained significant in the fully adjusted models. The most significant association was with higher level of hydroxyphenylpyruvate in men (PFDR.full.adj=1.40×10-7) and in both the pooled sample (PFDR.full.adj=1.66×10-4) and statin-untreated (PFDR.full.adj=1.65×10-6) subsample. In men, hydroxyphenylpyruvate explained 3% to 14% of variance in WMH. In men and the pooled sample, WMH were also associated with lower levels of lysophosphatidylcholines and hydroxysphingomyelins and a larger diameter of low-density lipoprotein particles, likely arising from higher triglyceride to total lipids and lower cholesteryl ester to total lipids ratios within these particles. In women, the only significant association was with higher level of glucuronate (PFDR=0.047). CONCLUSIONS Circulating metabolomic measures, including multiple lipid measures (eg, lysophosphatidylcholines, hydroxysphingomyelins, low-density lipoprotein size and composition) and nonlipid metabolites (eg, hydroxyphenylpyruvate, glucuronate), associate with WMH in a general population of middle-aged and older adults. Some metabolomic measures show marked sex specificities and explain a sizable proportion of WMH variance.
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Affiliation(s)
- Eeva Sliz
- The Hospital for Sick Children, and Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Jean Shin
- The Hospital for Sick Children, and Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Shahzad Ahmad
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Dylan M. Williams
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Stefan Frenzel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Friederike Gauß
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Sarah E. Harris
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Ann-Kristin Henning
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Maria Valdes Hernandez
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
| | - Yi-Han Hu
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Baltimore, MD, USA
| | - Beatriz Jiménez
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Muralidharan Sargurupremraj
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000 Bordeaux, France
| | - Carole Sudre
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
- Centre for Medical Image Computing, Department of Computer Science, University College London
- School of Biomedical Engineering & Imaging Sciences, King’s College London
| | - Ruiqi Wang
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- Germany Center for Neurodegenerative Diseases (DZNE), partner site Rostock/Greifswald, Greifswald, Germany
| | - Qiong Yang
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Joanna M. Wardlaw
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Meike W. Vernooij
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, and Department of Neurology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Petroula Proitsi
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Matthew R. Lewis
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Lenore Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Baltimore, MD, USA
| | - Norbert Hosten
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- Germany Center for Neurodegenerative Diseases (DZNE), partner site Rostock/Greifswald, Greifswald, Germany
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Ian J. Deary
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Simon R. Cox
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Nishi Chaturvedi
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA USA
| | - Stephanie Debette
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000 Bordeaux, France
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Myriam Fornage
- University of Texas Health Science Center at Houston McGovern Medical School, Houston, TX, USA
| | - Tomas Paus
- Departments of Psychiatry and Neuroscience and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, QC, Canada
- ECOGENE-21, Chicoutimi, QC, Canada
- Departments of Psychology and Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Sudha Seshadri
- The Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Zdenka Pausova
- The Hospital for Sick Children, and Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada
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