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1. Subclinical thyroid dysfunction and incident diabetes: a systematic review and an individual participant data analysis of prospective cohort studies

Author

Alwan, Heba, Villoz, Fanny, Feller, Martin, Dullaart, Robin PF, Bakker, Stephan JL, Peeters, Robin P, Kavousi, Maryam, Bauer, Douglas C, Cappola, Anne R, Yeap, Bu B, Walsh, John P, Brown, Suzanne J, Ceresini, Graziano, Ferrucci, Luigi, Gussekloo, Jacobijn, Trompet, Stella, Iacoviello, Massimo, Moon, Jae Hoon, Razvi, Salman, Bensenor, Isabela M, Azizi, Fereidoun, Amouzegar, Atieh, Valdés, Sergio, Colomo, Natalia, Wareham, Nick J, Jukema, J Wouter, Westendorp, Rudi GJ, Kim, Ki Woong, Rodondi, Nicolas, Del Giovane, Cinzia, and Collaboration, for the Thyroid Studies

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Prevention, Diabetes, Clinical Research, Detection, screening and diagnosis, 4.2 Evaluation of markers and technologies, Metabolic and endocrine, Adult, Cohort Studies, Data Analysis, Diabetes Mellitus, Female, Humans, Hyperthyroidism, Hypothyroidism, Male, Middle Aged, Prospective Studies, Thyroid Diseases, Thyrotropin, Paediatrics and Reproductive Medicine, Endocrinology & Metabolism, Clinical sciences, Reproductive medicine
Abstract

ObjectiveFew prospective studies have assessed whether individuals with subclinical thyroid dysfunction are more likely to develop diabetes, with conflicting results. In this study, we conducted a systematic review of the literature and an individual participant data analysis of multiple prospective cohorts to investigate the association between subclinical thyroid dysfunction and incident diabetes.MethodsWe performed a systematic review of the literature in Medline, Embase, and the Cochrane Library from inception to February 11, 2022. A two-stage individual participant data analysis was conducted to compare participants with subclinical hypothyroidism and subclinical hyperthyroidism vs euthyroidism at baseline and the adjusted risk of developing diabetes at follow-up.ResultsAmong 61 178 adults from 18 studies, 49% were females, mean age was 58 years, and mean follow-up time was 8.2 years. At the last available follow-up, there was no association between subclinical hypothyroidism and incidence of diabetes (odds ratio (OR) = 1.02, 95% CI: 0.88-1.17, I2 = 0%) or subclinical hyperthyroidism and incidence of diabetes (OR = 1.03, 95% CI: 0.82-1.30, I2 = 0%), in age- and sex-adjusted analyses. Time-to-event analysis showed similar results (hazard ratio for subclinical hypothyroidism: 0.98, 95% CI: 0.87-1.11; hazard ratio for subclinical hyperthyroidism: 1.07, 95% CI: 0.88-1.29). The results were robust in all sub-group and sensitivity analyses.ConclusionsThis is the largest systematic review and individual participant data analysis to date investigating the prospective association between subclinical thyroid dysfunction and diabetes. We did not find an association between subclinical thyroid dysfunction and incident diabetes. Our results do not support screening patients with subclinical thyroid dysfunction for diabetes.Significance statementEvidence is conflicting regarding whether an association exists between subclinical thyroid dysfunction and incident diabetes. We therefore aimed to investigate whether individuals with subclinical thyroid dysfunction are more prone to develop diabetes in the long run as compared to euthyroid individuals. We included data from 18 international cohort studies with 61 178 adults and a mean follow-up time of 8.2 years. We did not find an association between subclinical hypothyroidism or subclinical hyperthyroidism at baseline and incident diabetes at follow-up. Our results have clinical implications as they neither support screening patients with subclinical thyroid dysfunction for diabetes nor treating them in the hope of preventing diabetes in the future.

Published
2022

2. Incorporating Baseline Outcome Data in Individual Participant Data Meta-Analysis of Non-randomized Studies

Author

Syrogiannouli, Lamprini, Wildisen, Lea, Meuwese, Christiaan, Bauer, Douglas C, Cappola, Anne R, Gussekloo, Jacobijn, Elzen, Wendy PJ den, Trompet, Stella, Westendorp, Rudi GJ, Jukema, J Wouter, Ferrucci, Luigi, Ceresini, Graziano, Åsvold, Bjørn O, Chaker, Layal, Peeters, Robin P, Imaizumi, Misa, Ohishi, Waka, Vaes, Bert, Völzke, Henry, Sgarbi, Josè A, Walsh, John P, Dullaart, Robin PF, Bakker, Stephan JL, Iacoviello, Massimo, Rodondi, Nicolas, and Del Giovane, Cinzia

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Prevention, individual participant data, continuous outcome, non-randomized studies, cohorts, baseline imbalance, Public Health and Health Services, Psychology, Clinical sciences
Abstract

BackgroundIn non-randomized studies (NRSs) where a continuous outcome variable (e.g., depressive symptoms) is assessed at baseline and follow-up, it is common to observe imbalance of the baseline values between the treatment/exposure group and control group. This may bias the study and consequently a meta-analysis (MA) estimate. These estimates may differ across statistical methods used to deal with this issue. Analysis of individual participant data (IPD) allows standardization of methods across studies. We aimed to identify methods used in published IPD-MAs of NRSs for continuous outcomes, and to compare different methods to account for baseline values of outcome variables in IPD-MA of NRSs using two empirical examples from the Thyroid Studies Collaboration (TSC).MethodsFor the first aim we systematically searched in MEDLINE, EMBASE, and Cochrane from inception to February 2021 to identify published IPD-MAs of NRSs that adjusted for baseline outcome measures in the analysis of continuous outcomes. For the second aim, we applied analysis of covariance (ANCOVA), change score, propensity score and the naïve approach (ignores the baseline outcome data) in IPD-MA from NRSs on the association between subclinical hyperthyroidism and depressive symptoms and renal function. We estimated the study and meta-analytic mean difference (MD) and relative standard error (SE). We used both fixed- and random-effects MA.ResultsTen of 18 (56%) of the included studies used the change score method, seven (39%) studies used ANCOVA and one the propensity score (5%). The study estimates were similar across the methods in studies in which groups were balanced at baseline with regard to outcome variables but differed in studies with baseline imbalance. In our empirical examples, ANCOVA and change score showed study results on the same direction, not the propensity score. In our applications, ANCOVA provided more precise estimates, both at study and meta-analytical level, in comparison to other methods. Heterogeneity was higher when change score was used as outcome, moderate for ANCOVA and null with the propensity score.ConclusionANCOVA provided the most precise estimates at both study and meta-analytic level and thus seems preferable in the meta-analysis of IPD from non-randomized studies. For the studies that were well-balanced between groups, change score, and ANCOVA performed similarly.

Published
2022

3. An individual participant data analysis of prospective cohort studies on the association between subclinical thyroid dysfunction and depressive symptoms.

Author

Wildisen, Lea, Del Giovane, Cinzia, Moutzouri, Elisavet, Beglinger, Shanthi, Syrogiannouli, Lamprini, Collet, Tinh-Hai, Cappola, Anne R, Åsvold, Bjørn O, Bakker, Stephan JL, Yeap, Bu B, Almeida, Osvaldo P, Ceresini, Graziano, Dullaart, Robin PF, Ferrucci, Luigi, Grabe, Hans, Jukema, J Wouter, Nauck, Matthias, Trompet, Stella, Völzke, Henry, Westendorp, Rudi, Gussekloo, Jacobijn, Klöppel, Stefan, Aujesky, Drahomir, Bauer, Douglas, Peeters, Robin, Feller, Martin, and Rodondi, Nicolas

Abstract

In subclinical hypothyroidism, the presence of depressive symptoms is often a reason for starting levothyroxine treatment. However, data are conflicting on the association between subclinical thyroid dysfunction and depressive symptoms. We aimed to examine the association between subclinical thyroid dysfunction and depressive symptoms in all prospective cohorts with relevant data available. We performed a systematic review of the literature from Medline, Embase, Cumulative Index to Nursing and Allied Health Literature, and the Cochrane Library from inception to 10th May 2019. We included prospective cohorts with data on thyroid status at baseline and depressive symptoms during follow-up. The primary outcome was depressive symptoms measured at first available follow-up, expressed on the Beck's Depression Inventory (BDI) scale (range 0-63, higher values indicate more depressive symptoms, minimal clinically important difference: 5 points). We performed a two-stage individual participant data (IPD) analysis comparing participants with subclinical hypo- or hyperthyroidism versus euthyroidism, adjusting for depressive symptoms at baseline, age, sex, education, and income (PROSPERO CRD42018091627). Six cohorts met the inclusion criteria, with IPD on 23,038 participants. Their mean age was 60 years, 65% were female, 21,025 were euthyroid, 1342 had subclinical hypothyroidism and 671 subclinical hyperthyroidism. At first available follow-up [mean 8.2 (± 4.3) years], BDI scores did not differ between participants with subclinical hypothyroidism (mean difference = 0.29, 95% confidence interval =  - 0.17 to 0.76, I2 = 15.6) or subclinical hyperthyroidism (- 0.10, 95% confidence interval =  - 0.67 to 0.48, I2 = 3.2) compared to euthyroidism. This systematic review and IPD analysis of six prospective cohort studies found no clinically relevant association between subclinical thyroid dysfunction at baseline and depressive symptoms during follow-up. The results were robust in all sensitivity and subgroup analyses. Our results are in contrast with the traditional notion that subclinical thyroid dysfunction, and subclinical hypothyroidism in particular, is associated with depressive symptoms. Consequently, our results do not support the practice of prescribing levothyroxine in patients with subclinical hypothyroidism to reduce the risk of developing depressive symptoms.

Published
2020

4. Low thyroid function is not associated with an accelerated deterioration in renal function

Author

Meuwese, Christiaan L, van Diepen, Merel, Cappola, Anne R, Sarnak, Mark J, Shlipak, Michael G, Bauer, Douglas C, Fried, Linda P, Iacoviello, Massimo, Vaes, Bert, Degryse, Jean, Khaw, Kay-Tee, Luben, Robert N, Åsvold, Bjørn O, Bjøro, Trine, Vatten, Lars J, de Craen, Anton JM, Trompet, Stella, Iervasi, Giorgio, Molinaro, Sabrina, Ceresini, Graziano, Ferrucci, Luigi, Dullaart, Robin PF, Bakker, Stephan JL, Jukema, J Wouter, Kearney, Patricia M, Stott, David J, Peeters, Robin P, Franco, Oscar H, Völzke, Henry, Walsh, John P, Bremner, Alexandra, Sgarbi, José A, Maciel, Rui MB, Imaizumi, Misa, Ohishi, Waka, Dekker, Friedo W, Rodondi, Nicolas, Gussekloo, Jacobijn, and Elzen, Wendy PJ den

Subjects
Clinical Research, Kidney Disease, Renal and urogenital, Metabolic and endocrine, Aged, Aged, 80 and over, Cross-Sectional Studies, Female, Glomerular Filtration Rate, Humans, Incidence, Longitudinal Studies, Male, Meta-Analysis as Topic, Middle Aged, Netherlands, Prognosis, Renal Insufficiency, Chronic, Thyroid Diseases, Thyroid Function Tests, Thyroid Hormones, chronic renal failure, CKD, creatinine clearance, epidemiology, thyroid function, Thyroid Studies Collaboration, Clinical Sciences, Urology & Nephrology
Abstract

BackgroundChronic kidney disease (CKD) is frequently accompanied by thyroid hormone dysfunction. It is currently unclear whether these alterations are the cause or consequence of CKD. This study aimed at studying the effect of thyroid hormone alterations on renal function in cross-sectional and longitudinal analyses in individuals from all adult age groups.MethodsIndividual participant data (IPD) from 16 independent cohorts having measured thyroid stimulating hormone, free thyroxine levels and creatinine levels were included. Thyroid hormone status was defined using clinical cut-off values. Estimated glomerular filtration rates (eGFR) were calculated by means of the four-variable Modification of Diet in Renal Disease (MDRD) formula. For this IPD meta-analysis, eGFR at baseline and eGFR change during follow-up were computed by fitting linear regression models and linear mixed models in each cohort separately. Effect estimates were pooled using random effects models.ResultsA total of 72 856 individuals from 16 different cohorts were included. At baseline, individuals with overt hypothyroidism (n = 704) and subclinical hypothyroidism (n = 3356) had a average (95% confidence interval) -4.07 (-6.37 to -1.78) and -2.40 (-3.78 to -1.02) mL/min/1.73 m2 lower eGFR as compared with euthyroid subjects (n = 66 542). In (subclinical) hyperthyroid subjects (n = 2254), average eGFR was 3.01 (1.50-4.52) mL/min/1.73 m2 higher. During 329 713 patient years of follow-up, eGFR did not decline more rapidly in individuals with low thyroid function compared with individuals with normal thyroid function.ConclusionsLow thyroid function is not associated with a deterioration of renal function. The cross-sectional association may be explained by renal dysfunction causing thyroid hormone alterations.

Published
2019

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Author

Interne Geneeskunde Vasculaire, Circulatory Health, Heidemann, Britt E., Wolters, Frank J., Kavousi, Maryam, Gruppen, Eke G., Dullaart, Robin PF, Marais, A. David, Visseren, Frank LJ, Koopal, Charlotte, Interne Geneeskunde Vasculaire, Circulatory Health, Heidemann, Britt E., Wolters, Frank J., Kavousi, Maryam, Gruppen, Eke G., Dullaart, Robin PF, Marais, A. David, Visseren, Frank LJ, and Koopal, Charlotte

Published
2021

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Author

Heidemann, Britt E., Wolters, Frank J., Kavousi, Maryam, Gruppen, Eke G., Dullaart, Robin PF, Marais, A. David, Visseren, Frank LJ, Koopal, Charlotte, Heidemann, Britt E., Wolters, Frank J., Kavousi, Maryam, Gruppen, Eke G., Dullaart, Robin PF, Marais, A. David, Visseren, Frank LJ, and Koopal, Charlotte

Published
2021

12. Cognitive Performance and the Hippocampus in Patients with Postoperative Pituitary Radiotherapy: A Detailed Dosimetric Study

Author

Brummelman, Pauline, primary, Sattler, Margriet GA, additional, van den Bergh, Alfons CM, additional, Meiners, Linda C, additional, Dullaart, Robin PF, additional, van den Berg, Gerrit, additional, Izaks, Gerbrand J, additional, Koerts, Janneke, additional, Tucha, Oliver, additional, Wolffenbuttel, Bruce HR, additional, and van Beek, Andre P, additional

Published
2011
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17. The first Dutch SDHB founder deletion in paraganglioma – pheochromocytoma patients

Author

Devilee Peter, Dullaart Robin PF, Jansen Jeroen C, Lenders Jacques W, Kunst Henricus P, van der Wielen Michiel, van Bunderen Patrick A, Grimbergen Anneliese EM, Bayley Jean-Pierre, Corssmit Eleonora P, Vriends Annette H, Losekoot Monique, and Weiss Marjan M

Subjects
Internal medicine, RC31-1245, Genetics, QH426-470
Abstract

Abstract Background Germline mutations of the tumor suppressor genes SDHB, SDHC and SDHD play a major role in hereditary paraganglioma and pheochromocytoma. These three genes encode subunits of succinate dehydrogenase (SDH), the mitochondrial tricarboxylic acid cycle enzyme and complex II component of the electron transport chain. The majority of variants of the SDH genes are missense and nonsense mutations. To date few large deletions of the SDH genes have been described. Methods We carried out gene deletion scanning using MLPA in 126 patients negative for point mutations in the SDH genes. We then proceeded to the molecular characterization of deletions, mapping breakpoints in each patient and used haplotype analysis to determine whether the deletions are due to a mutation hotspot or if a common haplotype indicated a single founder mutation. Results A novel deletion of exon 3 of the SDHB gene was identified in nine apparently unrelated Dutch patients. An identical 7905 bp deletion, c.201-4429_287-933del, was found in all patients, resulting in a frameshift and a predicted truncated protein, p.Cys68HisfsX21. Haplotype analysis demonstrated a common haplotype at the SDHB locus. Index patients presented with pheochromocytoma, extra-adrenal PGL and HN-PGL. A lack of family history was seen in seven of the nine cases. Conclusion The identical exon 3 deletions and common haplotype in nine patients indicates that this mutation is the first Dutch SDHB founder mutation. The predominantly non-familial presentation of these patients strongly suggests reduced penetrance. In this small series HN-PGL occurs as frequently as pheochromocytoma and extra-adrenal PGL.

Published
2009
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18. Hair cortisol in twins:heritability and genetic overlap with psychological variables and stress-system genes

Author

Rietschel, Liz, Streit, Fabian, McGrath, John, Davies, Gareth, Davies, Gail, de Geus, Eco J C, De Jager, Philip, Deary, Ian J, Degenhardt, Franziska, Dunn, Erin C, Ehli, Erik A, Eley, Thalia C, Escott-Price, Valentina, Hickie, Ian B, Esko, Tõnu, Finucane, Hilary K, Gill, Michael, Gordon, Scott D, Grove, Jakob, Hall, Lynsey S, Hansen, Thomas F, Søholm Hansen, Christine, Heath, Andrew C, Hansell, Narelle K, Henders, Anjali K, Herms, Stefan, Hoffmann, Per, Homuth, Georg, Horn, Carsten, Hottenga, Jouke- Jan, Hougaard, David, Huang, Hailiang, Ising, Marcus, Jansen, Rick, Wright, Margaret J, Jorgenson, Eric, Kloiber, Stefan, Knowles, James A, Kretzschmar, Warren W, Krogh, Jesper, Kutalik, Zoltán, Lang, Maren, Lewis, Glyn, Li, Yihan, MacIntyre, Donald J, Gillespie, Nathan A, Madden, Pamela Af, Marchine, Jonathan, Mbarek, Hamdi, McGuffin, Peter, Mehta, Divya, Metspalu, Andres, Middeldorp, Christel M, Mihailov, Evelin, Milani, Lili, Montgomery, Grant W, Forstner, Andreas J, Mostafavi, Sara, Mullins, Niamh, Nauck, Matthias, Ng, Bernard, Nordentoft, Merete, Nyholt, Dale R, O'Donovan, Michael C, O'Reilly, Paul F, Oskarsson, Hogni, Owen, Michael J, Schulze, Thomas G, Paciga, Sara A, Pedersen, Carsten Bøcker, Pedersen, Marianne Giørtz, Pedersen, Nancy L, Pergadia, Michele L, Peterson, Roseann E, Pettersson, Erik, Peyrot, Wouter J, Porteous, David J, Posthuma, Danielle, Wüst, Stefan, Potash, James B, Quiroz, Jorge A, Rice, John P, Riley, Brien P, Rivera, Margarita, Ruderfer, Douglas M, Saeed Mirza, Saira, Schoevers, Robert, Shen, Ling, Shi, Jianxin, Nöthen, Markus M, Sigurdsson, Engilbert, Sinnamon, Grant Cb, Smit, Johannes H, Smith, Daniel J, Smoller, Jordan W, Stephansson, Hreinn, Steinberg, Stacy, Strohmaier, Jana, Tansey, Katherine E, Teumer, Alexander, Baumgartner, Markus R, Thompson, Wesley, Thomson, Pippa A, Thorgeirsson, Thorgeir E, Treutlein, Jens, Trzaskowski, Maciej, Umbricht, Daniel, van der Auwera, Sandra, van Grootheest, Gerard, van Hemert, Albert M, Viktorin, Alexander, Zhu, Gu, Walker, Brian R, Völzke, Henry, Wang, Yunpeng, Webb, Bradley T, Weissman, Myrna M, Wellmann, Jürgen, Willemsen, Gonneke, Xi, Hualin S, Baune, Bernhard T, Blackwood, Douglas H R, Boomsma, Dorret I, Crawford, Andrew A, Børglum, Anders D, Buttenschøn, Henriette N, Cichon, Sven, Domenici, Enrico, Flint, Jonathan, Grabe, Hans J, Hamilton, Steven P, Kendler, Kenneth S, Li, Qingqin S, Lucae, Susanne, Colodro-Conde, Lucía, Magnusson, Patrik K, McIntosh, Andrew M, Mors, Ole, Bo Mortensen, Preben, Müller-Myhsok, Bertram, Penninx, Brenda Wjh, Perlis, Roy H, Preisig, Martin, Schaefer, Catherine, Medland, Sarah E, Stephansson, Kari, Tiemeier, Henning, Uher, Rudolf, Werge, Thomas, Winslow, Ashley R, Breen, Gerome, Levinson, Douglas F, Lewis, Cathryn M, Wray, Naomi R, Sullivan, Patrick F, Martin, Nicholas G, Rietschel, Marcella, Bolton, Jennifer L, Hayward, Caroline, Direk, Nese, Anderson, Anna, McAloney, Kerrie, Huffman, Jennifer, Wilson, James F, Campbell, Harry, Rudan, Igor, Wright, Alan, Hastie, Nicholas, Wild, Sarah H, Velders, Fleur P, Hofman, Albert, Uitterlinden, Andre G, Frank, Josef, Lahti, Jari, Räikkönen, Katri, Kajantie, Eero, Widen, Elisabeth, Palotie, Aarno, Eriksson, Johan G, Kaakinen, Marika, Järvelin, Marjo-Riitta, Timpson, Nicholas J, Davey Smith, George, Couvy-Duchesne, Baptiste, Ring, Susan M, Evans, David M, St Pourcain, Beate, Tanaka, Toshiko, Milaneschi, Yuri, Bandinelli, Stefania, Ferrucci, Luigi, van der Harst, Pim, Rosmalen, Judith Gm, Bakker, Stephen Jl, Witt, Stephanie H, Verweij, Niek, Dullaart, Robin Pf, Mahajan, Anubha, Lindgren, Cecilia M, Morris, Andrew, Lind, Lars, Ingelsson, Erik, Anderson, Laura N, Pennell, Craig E, Lye, Stephen J, Binz, Tina M, Matthews, Stephen G, Eriksson, Joel, Mellstrom, Dan, Ohlsson, Claes, Price, Jackie F, Strachan, Mark Wj, Reynolds, Rebecca M, Ripke, Stephan, Mattheisen, Manuel, CORtisolNETwork, Abdellaoui, Abdel, Adams, Mark J, Agerbo, Esben, Air, Tracy M, Andlauer, Till Fm, Bacanu, Silviu-Alin, Bækvad-Hansen, Marie, Beekman, Aartjan Tf, Bennett, David A, Berger, Klaus, Consortium, Major Depressive Disorder Working Group of the Psychiatric Genomics, Bigdeli, Tim B, Bybjerg-Grauholm, Jonas, Byrne, Enda M, Cai, Na, Castelao, Enrique, Clarke, Toni-Kim, Coleman, Jonathan Ri, Consortium, Converge, Craddock, Nick, Dannlowski, Udo, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, APH - Mental Health, Internal medicine, Amsterdam Reproduction & Development (AR&D), Human genetics, APH - Methodology, APH - Digital Health, Centre of Excellence in Complex Disease Genetics, Research Programme of Molecular Medicine, Research Programs Unit, Aarno Palotie / Principal Investigator, Institute for Molecular Medicine Finland, Genomics of Neurological and Neuropsychiatric Disorders, University of Zurich, Rietschel, Liz, Biological Psychology, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Health Behaviors & Chronic Diseases, and APH - Personalized Medicine

Subjects
Male, Oncology, Netherlands Twin Register (NTR), Multifactorial Inheritance, Hydrocortisone, lcsh:Medicine, 340 Law, Genome-wide association study, 3124 Neurology and psychiatry, 0302 clinical medicine, Twins, Dizygotic, SOCIOECONOMIC-STATUS, Young adult, lcsh:Science, Child, 610 Medicine & health, Genetics, Multidisciplinary, Depression, PSYCHIATRIC-DISORDERS, 10218 Institute of Legal Medicine, Neuroticism, DEPRESSIVE SYMPTOMS, MORNING CORTISOL, Female, FUTURE-DIRECTIONS, Adult, medicine.medical_specialty, Cortisol awakening response, Adolescent, PERCEIVED STRESS, Biology, Genetic correlation, Article, LONG-TERM CORTISOL, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Internal medicine, medicine, Journal Article, Humans, neoplasms, Behavioural genetics, 1000 Multidisciplinary, Models, Genetic, lcsh:R, Twins, Monozygotic, ADRENAL AXIS ACTIVITY, MAJOR DEPRESSION, Heritability, Twin study, R1, digestive system diseases, 030227 psychiatry, ddc:000, INTRAINDIVIDUAL STABILITY, lcsh:Q, Stress, Psychological, 030217 neurology & neurosurgery, Hair
Abstract

Hair cortisol concentration (HCC) is a promising measure of long-term hypothalamus-pituitary-adrenal (HPA) axis activity. Previous research has suggested an association between HCC and psychological variables, and initial studies of inter-individual variance in HCC have implicated genetic factors. However, whether HCC and psychological variables share genetic risk factors remains unclear. The aims of the present twin study were to: (i) assess the heritability of HCC; (ii) estimate the phenotypic and genetic correlation between HPA axis activity and the psychological variables perceived stress, depressive symptoms, and neuroticism; using formal genetic twin models and molecular genetic methods, i.e. polygenic risk scores (PRS). HCC was measured in 671 adolescents and young adults. These included 115 monozygotic and 183 dizygotic twin-pairs. For 432 subjects PRS scores for plasma cortisol, major depression, and neuroticism were calculated using data from large genome wide association studies. The twin model revealed a heritability for HCC of 72%. No significant phenotypic or genetic correlation was found between HCC and the three psychological variables of interest. PRS did not explain variance in HCC. The present data suggest that HCC is highly heritable. However, the data do not support a strong biological link between HCC and any of the investigated psychological variables. Consortia CORtisolNETwork (CORNET) Consortium Jennifer L. Bolton21 Caroline Hayward23 Nese Direk24,25 Anna Anderson21 Jennifer Huffman23 James F. Wilson26 Harry Campbell26 Igor Rudan26 Alan Wright23 Nicholas Hastie23 Sarah H. Wild26 Fleur P. Velders24 Albert Hofman24 Andre G. Uitterlinden24,27 Jari Lahti28 Katri Räikkönen28 Eero Kajantie29 Elisabeth Widen30 Aarno Palotie30,31 Johan G. Eriksson29,32,33,34,35 Marika Kaakinen36 Marjo-Riitta Järvelin36,37,38,39 Nicholas J. Timpson40 George Davey Smith40 Susan M. Ring41 David M. Evans40 Beate St Pourcain41 Toshiko Tanaka42 Yuri Milaneschi42,43 Stefania Bandinelli44 Luigi Ferrucci42 Pim van der Harst45,46,47 Judith GM Rosmalen48 Stephen JL Bakker49 Niek Verweij45 Robin PF Dullaart49 Anubha Mahajan50 Cecilia M. Lindgren50 Andrew Morris50 Lars Lind51 Erik Ingelsson51 Laura N. Anderson52 Craig E. Pennell53 Stephen J. Lye52 Stephen G. Matthews54 Joel Eriksson55 Dan Mellstrom55 Claes Ohlsson55 Jackie F. Price26 Mark WJ Strachan21 Rebecca M. Reynolds21 Henning Tiemeier24,56,57 Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium (PGC) Stephan Ripke58,59,60 Manuel Mattheisen61,62,63 Abdel Abdellaoui64 Mark J. Adams65 Esben Agerbo66,8,67 Tracy M. Air68 Till FM Andlauer69,70 Silviu-Alin Bacanu71 Marie Bækvad-Hansen67,72 Aartjan TF Beekman43 David A. Bennett73 Klaus Berger74 Tim B. Bigdeli71,11 Jonas Bybjerg-Grauholm67,72 Enda M. Byrne5 Na Cai75 Enrique Castelao76 Toni-Kim Clarke65 Jonathan RI Coleman77 Converge Consortium78 Nick Craddock79 Udo Dannlowski80,81 Gareth Davies82 Gail Davies83 Eco. J. C. de Geus64,84 Philip De Jager85 Ian J. Deary83 Franziska Degenhardt12,13 Erin C. Dunn86,87,88 Erik A. Ehli82 Thalia C. Eley77 Valentina Escott-Price89 Tõnu Esko58,90,91,92 Hilary K. Finucane93,94 Michael Gill95 Scott D. Gordon96 Jakob Grove61,62,67,97 Lynsey S. Hall65,98 Thomas F. Hansen99,100 Christine Søholm Hansen67,72 Thomas F. Hansen101 Andrew C. Heath102 Anjali K. Henders5 Stefan Herms12,13,15 Per Hoffmann12,13,15 Georg Homuth103 Carsten Horn104 Jouke- Jan Hottenga64 David Hougaard67,72 Hailiang Huang59,86,105 Marcus Ising106 Rick Jansen43 Eric Jorgenson107 Stefan Kloiber108,109 James A Knowles110 Warren W. Kretzschmar50 Jesper Krogh111 Zoltán Kutalik112,113 Maren Lang3 Glyn Lewis114 Yihan Li50 Donald J. MacIntyre115,116 Pamela AF Madden102 Jonathan Marchine117 Hamdi Mbarek118,64 Peter McGuffin77 Divya Mehta119 Andres Metspalu92,120 Christel M. Middeldorp64 Evelin Mihailov92,121 Lili Milani92 Grant W. Montgomery122 Sara Mostafavi123,124 Niamh Mullins77 Matthias Nauck125,126 Bernard Ng124 Merete Nordentoft67,127 Dale R. Nyholt128 Michael C. O’Donovan129 Paul F. O’Reilly77 Hogni Oskarsson130 Michael J. Owen129 Sara A. Paciga131 Carsten Bøcker Pedersen66,67,8 Marianne Giørtz Pedersen66,67,8 Nancy L. Pedersen132 Michele L. Pergadia133 Roseann E. Peterson11,71 Erik Pettersson134 Wouter J. Peyrot43 David J. Porteous135 Danielle Posthuma136,137 James B. Potash138 Jorge A. Quiroz139 John P. Rice102 Brien P. Riley71 Margarita Rivera77,140 Douglas M. Ruderfer141 Saira Saeed Mirza24 Robert Schoevers142 Ling Shen107 Jianxin Shi143 Engilbert Sigurdsson144 Grant CB Sinnamon145 Johannes H. Smit43 Daniel J. Smith146 Jordan W. Smoller86 Hreinn Stephansson147 Stacy Steinberg147 Jana Strohmaier3 Katherine E. Tansey148 Alexander Teumer149 Wesley Thompson100,135,150,151,152 Pippa A. Thomson135 Thorgeir E. Thorgeirsson147 Jens Treutlein3 Maciej Trzaskowski153 Daniel Umbricht154 Sandra van der Auwera155 Gerard van Grootheest43 Albert M. van Hemert156 Alexander Viktorin132 Henry Völzke149 Yunpeng Wang67,100,151 Bradley T. Webb157 Myrna M. Weissman158,159 Jürgen Wellmann74 Gonneke Willemsen64 Hualin S. Xi160 Bernhard T. Baune68 Douglas H. R. Blackwood65 Dorret I. Boomsma64 Anders D. Børglum61,62,67 Henriette N. Buttenschøn62,67,161 Sven Cichon12,162,163,164 Enrico Domenici165 Jonathan Flint50,166 Hans J. Grabe155 Steven P. Hamilton167 Kenneth S. Kendler71 Qingqin S. Li168 Susanne Lucae106 Patrik K. Magnusson132 Andrew M. McIntosh65,83 Ole Mors67,169 Preben Bo Mortensen62,8,67 Bertram Müller-Myhsok69,70,170 Brenda WJH Penninx43 Roy H. Perlis87,171 Martin Preisig76 Catherine Schaefer107 Jordan W. Smoller87,88 Kari Stephansson147 Henning Tiemeier24,56,57 Rudolf Uher172 Thomas Werge100,150,173 Ashley R. Winslow174,175 Gerome Breen77,176 Douglas F. Levinson177 Cathryn M. Lewis77,178 Naomi R. Wray5,153 Patrick F. Sullivan134,179,180 23MRC Human Genetics Unit, Institute for Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK. 24Department of Epidemiology, Erasmus Medical Centre, Rotterdam, Netherlands. 25Psychiatry, Dokuz Eylul University School Of Medicine, Izmir, TR, Turkey. 26Centre for Population Health Sciences, Institute for Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH8 9AG, UK. 27Internal Medicine, Erasmus MC, Rotterdam, NL, Netherlands. 28Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland. 29National Institute for Health and Welfare, Helsinki, Finland. 30Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland. 31Department of Medical Genetics, University of Helsinki and University Central Hospital, Helsinki, Finland. 32Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland. 33Helsinki University Central Hospital, Unit of General Practice, Helsinki, Finland. 34Folkhalsan Research Centre, Helsinki, Finland. 35Vasa Central Hospital, Vasa, Finland. 36Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland. 37Department of Children and Yond People and Families, National Institute for Health and elfare, Oulu, Finland. 38Department of Epidemiology and Biostatistics, MRC-HPA Centre for Environment and Health, Imperial College London, London, UK. 39Unit of Primary Care, Oulu University Hospital, Oulu, Finland. 40MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol, UK. 41School of Social and Community Medicine, University of Bristol, Bristol, UK. 42Longitudinal Studies Section, Clinical Research Branch, National Institute on Aging, Baltimore, MD, USA. 43Department of Psychiatry, VU University Medical Center/GGZ inGeest, Amsterdam, Netherlands. 44Geriatric Unit, ASF, Florence, Italy. 45University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen, Netherlands. 46University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, Netherlands. 47Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, Netherlands. 48University of Groningen, University Medical Center Groningen, Interdisciplinary Center for Psychiatric Epidemiology, Groningen, Netherlands. 49University of Groningen, University Medical Center Groningen, Department of Internal Medicine, Groningen, Netherlands. 50Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK. 51Department of Medical Sciences, Uppsala University, Uppsala, Sweden. 52Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada. 53School of Women’s and Infant’s Health, The University of Western Australia, Crawley, Australia. 54Department of Physiology, University of Toronto, Toronto, Ontario, Canada. 55Center for Bone and Arthritis Research, Institute of Medicin, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. 56Child and Adolescent Psychiatry, Erasmus MC, Rotterdam, Netherlands. 57Psychiatry, Erasmus MC, Rotterdam, Netherlands. 58Medical and Population Genetics, Broad Institute, Cambridge, USA. 59Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, USA. 60Department of Psychiatry and Psychotherapy, Universitätsmedizin Berlin Campus Charité Mitte, Berlin, Germany. 61Department of Biomedicine, Aarhus University, Aarhus, Denmark. 62iSEQ, Centre for Integrative Sequencing, Aarhus University, Aarhus, Denmark. 63iSPYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark. 64Dept of Biological Psychology, VU University Amsterdam, Amsterdam, Netherlands. 65Division of Psychiatry, University of Edinburgh, Edinburgh, UK. 66Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark. 67iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark. 68Discipline of Psychiatry, University of Adelaide, Adelaide, Australia. 69Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany. 70Munich Cluster for Systems Neurology (SyNergy), Munich, Germany. 71Department of Psychiatry, Virginia Commonwealth University, Richmond, USA. 72Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark. 73Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, USA. 74Institute of Epidemiology and Social Medicine, University of Muenster, Muenster, UK. 75Human Genetics, Wellcome Trust Sanger Institute, Cambridge, UK. 76Department of Psychiatry, University Hospital of Lausanne, Prilly, Switzerland. 77MRC Social Genetic and Developmental Psychiatry Centre, King’s College London, London, UK. 78University of Oxford, Oxford, UK. 79Psychological Medicine, Cardiff University, Cardiff, UK. 80Department of Psychiatry, University of Marburg, Marburg, Germany. 81Department of Psychiatry, University of Münster, Münster, Germany. 82Avera Institute for Human Genetics, Sioux Falls, USA. 83Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK. 84EMGO+ Institute, VU University Medical Center, Amsterdam, Netherlands. 85Neurology, Brigham and Women’s Hospital, Boston, USA. 86Stanley Center for Psychiatric Research, Broad Institute, Cambridge, USA. 87Department of Psychiatry, Massachusetts General Hospital, Boston, USA. 88Psychiatric and Neurodevelopmental Genetics Unit (PNGU), Massachusetts General Hospital, Boston, USA. 89Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, UK. 90Division of Endocrinology, Children’s Hospital Boston, Boston, USA. 91Department of Genetics, Harvard Medical School, Boston, USA. 92Estonian Genome Center, University of Tartu, Tartu, Estonia. 93Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, USA. 94Department of Mathematics, Massachusetts Institute of Technology, Cambridge, USA. 95Department of Psychiatry, Trinity College Dublin, Dublin, Ireland. 96Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Australia. 97Bioinformatics Research Centre (BiRC), Aarhus University, Aarhus, Denmark. 98Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK. 99Danish Headache Centre, Department of Neurology, Rigshospitalet Glostrup, Glostrup, Denmark. 100Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Capital Region of Denmark, Roskilde, Denmark. 101iPSYCH, The Lundbeck Foundation Initiative for Psychiatric Research, Copenhagen, Denmark. 102Department of Psychiatry, Washington University in Saint Louis School of Medicine, Saint Louis, USA. 103Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine and Ernst Moritz Arndt University Greifswald, Greifswald, Germany. 104Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland. 105Department of Medicine, Harvard Medical School, Boston, USA. 106Max Planck Institute of Psychiatry, Munich, Germany. 107Division of Research, Kaiser Permanente Northern California, Oakland, USA. 108Centre for Addiction and Mental Health, Toronto, Canada. 109Department of Psychiatry, University of Toronto, Toronto, Canada. 110Psychiatry & The Behavioral Sciences, University of Southern California, Los Angeles, USA. 111Department of Endocrinology at Herlev University Hospital, University of Copenhagen, Copenhagen, Denmark. 112Swiss Institute of Bioinformatics, Lausanne, Switzerland. 113Institute of Social and Preventive Medicine (IUMSP), Lausanne University Hospital, Lausanne, Switzerland. 114Division of Psychiatry, University College London, London, UK. 115Mental Health NHS 24, Glasgow, UK. 116Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK. 117Statistics, University of Oxford, Oxford, UK. 118EMGO+ Institute for Health and Care Research, Amsterdam, Netherlands. 119School of Psychology and Counseling, Queensland University of Technology, Brisbane, Australia. 120Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia. 121Estonian Biocentre, Tartu, Estonia. 122Institute for Molecular Biology, University of Queensland, Brisbane, Australia. 123Medical Genetics, University of British Columbia, Vancouver, Canada. 124Statistics, University of British Columbia, Vancouver, Canada. 125DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Matthias Nauck, Greifswald, Germany. 126Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany. 127Mental Health Centre Copenhagen, Copenhagen Universtity Hospital, Copenhagen, Denmark. 128Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia. 129MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK. 130Humus, Reykjavik, Iceland. 131Human Genetics and Computational Biomedicine, Pfizer Global Research and Development, Groton, USA. 132Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. 133Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, USA. 134Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. 135Medical Genetics Section, CGEM, IGMM, University of Edinburgh, Edinburgh, UK. 136Complex Trait Genetics, VU University Amsterdam, Amsterdam, Netherlands. 137Clinical Genetics, VU University Medical Center, Amsterdam, Netherlands. 138Psychiatry, University of Iowa, Iowa City, USA. 139Solid GT, Boston, USA. 140Department of Biochemistry and Molecular Biology II, Institute of Neurosciences, Center for Biomedical Research, University of Granada, Granada, Spain. 141Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA. 142Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, Netherlands. 143Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, USA. 144Faculty of Medicine, Department of Psychiatry, School of Health Sciences, University of Iceland, Reykjavik, Iceland. 145School of Medicine and Dentistry, James Cook University, Townsville, Australia. 146Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK. 147deCODE Genetics/Amgen, Reykjavik, Iceland. 148College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK. 149Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany. 150iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark. 151KG Jebsen Centre for Psychosis Research, Norway Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway. 152Department of Psychiatry, University of California, San Diego, San Diego, USA. 153Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia. 154Roche Pharmaceutical Research and Early Development, Neuroscience, Ophthalmology and Rare Diseases Discovery & Translational Medicine Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland. 155Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany. 156Department of Psychiatry, Leiden University Medical Center, Leiden, Netherlands. 157Virginia Institute of Psychiatric & Behavioral Genetics, Virginia Commonwealth University, Richmond, USA. 158Psychiatry, Columbia University College of Physicians and Surgeons, New York, USA. 159Division of Epidemiology, New York State Psychiatric Institute, New York, USA. 160Computational Sciences Center of Emphasis, Pfizer Global Research and Development, Cambridge, USA. 161Department of Clinical Medicine, Translational Neuropsychiatry Unit, Aarhus University, Aarhus, Denmark. 162Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, Juelich, Germany. 163Department of Biomedicine, University of Basel, Basel, CH, Switzerland. 164Division of Medical Genetics, University of Basel, Basel, CH, Switzerland. 165Centre for Integrative Biology, Università degli Studi di Trento, Trento, Italy. 166Psychiatry, University of California Los Angeles, Los Angeles, USA. 167Psychiatry, Kaiser Permanente Northern California, San Francisco, USA. 168Neuroscience Therapeutic Area, Janssen Research and Development, LLC, Titusville, USA. 169Psychosis Research Unit, Aarhus University Hospital, Risskov, Aarhus, Denmark. 170Institute of Translational Medicine, University of Liverpool, Liverpool, UK. 171Psychiatry, Harvard Medical School, Boston, USA. 172Psychiatry, Dalhousie University, Halifax, Canada. 173Institute of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark. 174Human Genetics and Computational Biomedicine, Pfizer Global Research and Development, Cambridge, USA. 175Orphan Disease Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA. 176NIHR BRC for Mental Health, King’s College London, London, UK. 177Psychiatry & Behavioral Sciences, Stanford University, Stanford, USA. 178Department of Medical & Molecular Genetics, King’s College London, London, UK. 179Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, USA. 180Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, USA.

Published
2017
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25. The first Dutch SDHB founder deletion in paraganglioma – pheochromocytoma patients

Author

Bayley, Jean-Pierre, primary, Grimbergen, Anneliese EM, additional, van Bunderen, Patrick A, additional, van der Wielen, Michiel, additional, Kunst, Henricus P, additional, Lenders, Jacques W, additional, Jansen, Jeroen C, additional, Dullaart, Robin PF, additional, Devilee, Peter, additional, Corssmit, Eleonora P, additional, Vriends, Annette H, additional, Losekoot, Monique, additional, and Weiss, Marjan M, additional

Published
2009
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30. Beneficial effects of reconstituted HDL on ex vivoand in vitroplatelet reactivity

Author

Dullaart, Robin Pf and Dallinga-Thie, Geesje M

Abstract

AbstractEvaluation of: Calkin AC, Drew BG, Ono A et al.: Reconstituted high-density lipoprotein attenuates platelet function in individuals with Type 2 diabetes mellitus by promoting cholesterol efflux. Circulation120(2), 2095-2104 (2009).The pathogenesis of the cardiovascular burden associated with Type 2 diabetes mellitus may in part be ascribed to prothrombotic mechanisms, including enhanced platelet reactivity. In this placebo-controlled study, the effect of a 4-h infusion of reconstituted HDL (r-HDL; CSL-111, 20 mg/kg/h) on ex vivoplatelet function in a small group of 13 men with Type 2 diabetes was determined. r-HDL infusion reversibly attenuated the platelet aggregation response to adenosine diphosphate (ADP) and collagen; this effect was accompanied by blunted platelet fibrinogen binding. Additional in vitrostudies demonstrated widespread inhibition of platelet function upon incubation with r-HDL. r-HDL-induced inhibition of platelet aggregation by ADP was independent from ApoA-I and from the HDL receptors, SR-BI and ABCAI. Interestingly, equivalent experiments with only the phospholipid component of r-HDL, soybean phosphatidylcholine, revealed identical results, suggesting that the phospholipid moiety of r-HDL is responsible for the observed effects. Efflux of radiolabeled cholesterol from platelets to r-HDL was also receptor independent. The authors suggest that stimulation of cholesterol efflux by r-HDL may alter platelet membrane cholesterol content. They propose that this results in reduced assembly of cholesterol-rich signaling microdomains, known as lipid rafts. This study clearly demonstrates attenuation of platelet function in response to short-term r-HDL infusion in Type 2 diabetes. The extent to which these effects could eventually translate into clinical benefit remains uncertain.

Published
2010
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31. Cell-free, high-density lipoprotein-specific phospholipid efflux assay predicts incident cardiovascular disease.

Author

Sato M, Neufeld EB, Playford MP, Lei Y, Sorokin AV, Aponte AM, Freeman LA, Gordon SM, Dey AK, Jeiran K, Hamasaki M, Sampson ML, Shamburek RD, Tang J, Chen MY, Kotani K, Anderson JL, Dullaart RP, Mehta NN, Tietge UJ, and Remaley AT

Subjects
Humans, Lipoproteins, HDL, Apolipoprotein A-I, Cholesterol, HDL, Phospholipids, Cardiovascular Diseases diagnosis, Cardiovascular Diseases epidemiology, Diabetes Mellitus, Type 2, Coronary Artery Disease
Abstract

BACKGROUNDCellular cholesterol efflux capacity (CEC) is a better predictor of cardiovascular disease (CVD) events than HDL-cholesterol (HDL-C) but is not suitable as a routine clinical assay.METHODSWe developed an HDL-specific phospholipid efflux (HDL-SPE) assay to assess HDL functionality based on whole plasma HDL apolipoprotein-mediated solubilization of fluorescent phosphatidylethanolamine from artificial lipid donor particles. We first assessed the association of HDL-SPE with prevalent coronary artery disease (CAD): study I included NIH severe-CAD (n = 50) and non-CAD (n = 50) participants, who were frequency matched for sex, BMI, type 2 diabetes mellitus, and smoking; study II included Japanese CAD (n = 70) and non-CAD (n = 154) participants. We also examined the association of HDL-SPE with incident CVD events in the Prevention of Renal and Vascular End-stage Disease (PREVEND) study comparing 340 patients with 340 controls individually matched for age, sex, smoking, and HDL-C levels.RESULTSReceiver operating characteristic curves revealed stronger associations of HDL-SPE with prevalent CAD. The AUCs in study I were as follows: HDL-SPE, 0.68; apolipoprotein A-I (apoA-I), 0.62; HDL-C, 0.63; and CEC, 0.52. The AUCs in study II were as follows: HDL-SPE, 0.83; apoA-I, 0.64; and HDL-C, 0.53. Also longitudinally, HDL-SPE was significantly associated with incident CVD events independent of traditional risk factors with ORs below 0.2 per SD increment in the PREVEND study (P < 0.001).CONCLUSIONHDL-SPE could serve as a routine clinical assay for improving CVD risk assessment and drug discovery.TRIAL REGISTRATIONClinicalTrials.gov NCT01621594.FUNDINGNHLBI Intramural Research Program, NIH (HL006095-06).

Published
2023
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