Proteomic analysis of cardiorespiratory fitness for prediction of mortality and multisystem disease risks.


Journal

Nature medicine
ISSN: 1546-170X
Titre abrégé: Nat Med
Pays: United States
ID NLM: 9502015

Informations de publication

Date de publication:
04 Jun 2024
Historique:
received: 18 10 2023
accepted: 30 04 2024
medline: 5 6 2024
pubmed: 5 6 2024
entrez: 4 6 2024
Statut: aheadofprint

Résumé

Despite the wide effects of cardiorespiratory fitness (CRF) on metabolic, cardiovascular, pulmonary and neurological health, challenges in the feasibility and reproducibility of CRF measurements have impeded its use for clinical decision-making. Here we link proteomic profiles to CRF in 14,145 individuals across four international cohorts with diverse CRF ascertainment methods to establish, validate and characterize a proteomic CRF score. In a cohort of around 22,000 individuals in the UK Biobank, a proteomic CRF score was associated with a reduced risk of all-cause mortality (unadjusted hazard ratio 0.50 (95% confidence interval 0.48-0.52) per 1 s.d. increase). The proteomic CRF score was also associated with multisystem disease risk and provided risk reclassification and discrimination beyond clinical risk factors, as well as modulating high polygenic risk of certain diseases. Finally, we observed dynamicity of the proteomic CRF score in individuals who undertook a 20-week exercise training program and an association of the score with the degree of the effect of training on CRF, suggesting potential use of the score for personalization of exercise recommendations. These results indicate that population-based proteomics provides biologically relevant molecular readouts of CRF that are additive to genetic risk, potentially modifiable and clinically translatable.

Identifiants

pubmed: 38834850
doi: 10.1038/s41591-024-03039-x
pii: 10.1038/s41591-024-03039-x
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024. The Author(s).

Références

Shah, R. V. et al. Association of fitness in young adulthood with survival and cardiovascular risk: the Coronary Artery Risk Development in Young Adults (CARDIA) study. JAMA Intern. Med. 176, 87–95 (2016).
pubmed: 26618471 pmcid: 5292201 doi: 10.1001/jamainternmed.2015.6309
Kodama, S. et al. Cardiorespiratory fitness as a quantitative predictor of all-cause mortality and cardiovascular events in healthy men and women: a meta-analysis. JAMA 301, 2024–2035 (2009).
pubmed: 19454641 doi: 10.1001/jama.2009.681
Mancini, D. M. et al. Value of peak exercise oxygen consumption for optimal timing of cardiac transplantation in ambulatory patients with heart failure. Circulation 83, 778–786 (1991).
pubmed: 1999029 doi: 10.1161/01.CIR.83.3.778
Sandvik, L. et al. Physical fitness as a predictor of mortality among healthy, middle-aged Norwegian men. N. Engl. J. Med. 328, 533–537 (1993).
pubmed: 8426620 doi: 10.1056/NEJM199302253280803
Wei, M. et al. Relationship between low cardiorespiratory fitness and mortality in normal-weight, overweight, and obese men. JAMA 282, 1547–1553 (1999).
pubmed: 10546694 doi: 10.1001/jama.282.16.1547
Ross, R. et al. Importance of assessing cardiorespiratory fitness in clinical practice: a case for fitness as a clinical vital sign. A scientific statement from the American Heart Association. Circulation 134, e653–e699 (2016).
pubmed: 27881567 doi: 10.1161/CIR.0000000000000461
Balady, G. J. et al. Clinician’s guide to cardiopulmonary exercise testing in adults: a scientific statement from the American Heart Association. Circulation 122, 191–225 (2010).
pubmed: 20585013 doi: 10.1161/CIR.0b013e3181e52e69
Nayor, M. et al. Metabolic architecture of acute exercise response in middle-aged adults in the community. Circulation 142, 1905–1924 (2020).
pubmed: 32927962 pmcid: 8049528 doi: 10.1161/CIRCULATIONAHA.120.050281
Robbins, J. M. et al. Association of dimethylguanidino valeric acid with partial resistance to metabolic health benefits of regular exercise. JAMA Cardiol. 4, 636–643 (2019).
pubmed: 31166569 pmcid: 6551586 doi: 10.1001/jamacardio.2019.1573
Robbins, J. M. et al. Human plasma proteomic profiles indicative of cardiorespiratory fitness. Nat. Metab. 3, 786–797 (2021).
pubmed: 34045743 pmcid: 9216203 doi: 10.1038/s42255-021-00400-z
Contrepois, K. et al. Molecular choreography of acute exercise. Cell 181, 1112–1130.e1116 (2020).
pubmed: 32470399 pmcid: 7299174 doi: 10.1016/j.cell.2020.04.043
Nayor, M. et al. Integrative analysis of circulating metabolite levels that correlate with physical activity and cardiorespiratory fitness. Circ. Genom. Precis Med 15, e003592 (2022).
pubmed: 35536222 pmcid: 9233103 doi: 10.1161/CIRCGEN.121.003592
Shah, R. V. et al. Blood-based fingerprint of cardiorespiratory fitness and long-term health outcomes in young adulthood. J. Am. Heart Assoc. 11, e026670 (2022).
pubmed: 36073631 pmcid: 9683648 doi: 10.1161/JAHA.122.026670
Gonzales, T. I. et al. Descriptive epidemiology of cardiorespiratory fitness in UK adults: the Fenland Study. Med. Sci. Sports Exerc. 55, 507–516 (2023).
pubmed: 36730941 doi: 10.1249/MSS.0000000000003068
Shock, N. W. et al. Normal Human Aging: The Baltimore Longitudinal Study of Aging NIH publication 84-2450 (National Institutes of Health, 1984).
Williams, S. A. et al. Plasma protein patterns as comprehensive indicators of health. Nat. Med. 25, 1851–1857 (2019).
pubmed: 31792462 pmcid: 6922049 doi: 10.1038/s41591-019-0665-2
Klos, A. et al. The role of the anaphylatoxins in health and disease. Mol. Immunol. 46, 2753–2766 (2009).
pubmed: 19477527 pmcid: 2725201 doi: 10.1016/j.molimm.2009.04.027
Camus, G. et al. Anaphylatoxin C5a production during short-term submaximal dynamic exercise in man. Int. J. Sports Med. 15, 32–35 (1994).
pubmed: 8163323 doi: 10.1055/s-2007-1021016
Yang, F. et al. Proteomic insights into the associations between obesity, lifestyle factors, and coronary artery disease. BMC Med 21, 485 (2023).
pubmed: 38049831 pmcid: 10696760 doi: 10.1186/s12916-023-03197-8
Huttunen, H. J. & Saarma, M. CDNF protein therapy in Parkinson’s disease. Cell Transplant. 28, 349–366 (2019).
pubmed: 30947516 pmcid: 6628563 doi: 10.1177/0963689719840290
Pimenta, A. F. et al. The limbic system-associated membrane protein is an Ig superfamily member that mediates selective neuronal growth and axon targeting. Neuron 15, 287–297 (1995).
pubmed: 7646886 doi: 10.1016/0896-6273(95)90034-9
Knupp, J., Arvan, P. & Chang, A. Increased mitochondrial respiration promotes survival from endoplasmic reticulum stress. Cell Death Differ. 26, 487–501 (2019).
pubmed: 29795335 doi: 10.1038/s41418-018-0133-4
Gonzalez-Garcia, I. et al. Olfactomedin 2 deficiency protects against diet-induced obesity. Metabolism 129, 155122 (2022).
pubmed: 35026233 pmcid: 9449885 doi: 10.1016/j.metabol.2021.155122
Numao, S., Uchida, R., Kurosaki, T. & Nakagaichi, M. Differences in circulating fatty acid-binding protein 4 concentration in the venous and capillary blood immediately after acute exercise. J. Physiol. Anthropol. 40, 5 (2021).
pubmed: 33568227 pmcid: 7876805 doi: 10.1186/s40101-021-00255-z
Li, B., Syed, M. H., Khan, H., Singh, K. K. & Qadura, M. The role of fatty acid binding protein 3 in cardiovascular diseases. Biomedicines 10, 2283 (2022).
pubmed: 36140383 pmcid: 9496114 doi: 10.3390/biomedicines10092283
Huck, I., Morris, E. M., Thyfault, J. & Apte, U. Hepatocyte-specific hepatocyte nuclear factor 4 alpha (HNF4) deletion decreases resting energy expenditure by disrupting lipid and carbohydrate homeostasis. Gene Expr. 20, 157–168 (2021).
pubmed: 33691903 pmcid: 8201658 doi: 10.3727/105221621X16153933463538
Carayol, J. et al. Protein quantitative trait locus study in obesity during weight-loss identifies a leptin regulator. Nat. Commun. 8, 2084 (2017).
pubmed: 29234017 pmcid: 5727191 doi: 10.1038/s41467-017-02182-z
Roxin, L. E., Hedin, G. & Venge, P. Muscle cell leakage of myoglobin after long-term exercise and relation to the individual performances. Int. J. Sports Med. 7, 259–263 (1986).
pubmed: 3793334 doi: 10.1055/s-2008-1025771
Wu, J. et al. The unfolded protein response mediates adaptation to exercise in skeletal muscle through a PGC-1alpha/ATF6alpha complex. Cell Metab. 13, 160–169 (2011).
pubmed: 21284983 pmcid: 3057411 doi: 10.1016/j.cmet.2011.01.003
Zhao, Y. et al. GLIPR2 is a negative regulator of autophagy and the BECN1-ATG14-containing phosphatidylinositol 3-kinase complex. Autophagy 17, 2891–2904 (2021).
pubmed: 33222586 doi: 10.1080/15548627.2020.1847798
Khera, A. V. et al. Genetic risk, adherence to a healthy lifestyle, and coronary disease. N. Engl. J. Med. 375, 2349–2358 (2016).
pubmed: 27959714 pmcid: 5338864 doi: 10.1056/NEJMoa1605086
Rutten-Jacobs, L. C. et al. Genetic risk, incident stroke, and the benefits of adhering to a healthy lifestyle: cohort study of 306 473 UK Biobank participants. Br. Med. J. 363, k4168 (2018).
doi: 10.1136/bmj.k4168
Al Ajmi, K., Lophatananon, A., Mekli, K., Ollier, W. & Muir, K. R. Association of nongenetic factors with breast cancer risk in genetically predisposed groups of women in the UK Biobank cohort. JAMA Netw. Open 3, e203760 (2020).
pubmed: 32329772 pmcid: 7182796 doi: 10.1001/jamanetworkopen.2020.3760
Lourida, I. et al. Association of lifestyle and genetic risk with incidence of dementia. JAMA 322, 430–437 (2019).
pubmed: 31302669 pmcid: 6628594 doi: 10.1001/jama.2019.9879
Robbins, J. M. & Gerszten, R. E. Exercise, exerkines, and cardiometabolic health: from individual players to a team sport. J. Clin. Invest. 133, e168121 (2023).
pubmed: 37259917 pmcid: 10231996 doi: 10.1172/JCI168121
Robbins, J. M. et al. Plasma proteomic changes in response to exercise training are associated with cardiorespiratory fitness adaptations. JCI Insight 8, e165867 (2023).
pubmed: 37036009 pmcid: 10132160 doi: 10.1172/jci.insight.165867
Maciel, L. et al. New cardiomyokine reduces myocardial ischemia/reperfusion injury by PI3K-AKT pathway via a putative KDEL-receptor binding. J. Am. Heart Assoc. 10, e019685 (2021).
pubmed: 33372525 doi: 10.1161/JAHA.120.019685
Chow, L. S. et al. Exerkines in health, resilience and disease. Nat. Rev. Endocrinol. 18, 273–289 (2022).
pubmed: 35304603 pmcid: 9554896 doi: 10.1038/s41574-022-00641-2
Lewis, G. D. et al. Metabolic signatures of exercise in human plasma. Sci. Transl. Med. 2, 33ra37 (2010).
pubmed: 20505214 pmcid: 3010398 doi: 10.1126/scitranslmed.3001006
Stanford, K. I. et al. 12,13-diHOME: an exercise-induced lipokine that increases skeletal muscle fatty acid uptake. Cell Metab. 27, 1111–1120.e1113 (2018).
pubmed: 29719226 pmcid: 5935136 doi: 10.1016/j.cmet.2018.03.020
Shah, R. et al. Small RNA-seq during acute maximal exercise reveal RNAs involved in vascular inflammation and cardiometabolic health. Am. J. Physiol. Heart Circ. Physiol. 13, H1162–H1167 (2017).
doi: 10.1152/ajpheart.00500.2017
Clausen, J. S. R., Marott, J. L., Holtermann, A., Gyntelberg, F. & Jensen, M. T. Midlife cardiorespiratory fitness and the long-term risk of mortality: 46 years of follow-up. J. Am. Coll. Cardiol. 72, 987–995 (2018).
pubmed: 30139444 doi: 10.1016/j.jacc.2018.06.045
Hansen, G. M. et al. Midlife cardiorespiratory fitness and the long-term risk of chronic obstructive pulmonary disease. Thorax 74, 843–848 (2019).
pubmed: 31209150 doi: 10.1136/thoraxjnl-2018-212821
Ekblom-Bak, E. et al. Association between cardiorespiratory fitness and cancer incidence and cancer-specific mortality of colon, lung, and prostate cancer among Swedish men. JAMA Netw. Open 6, e2321102 (2023).
pubmed: 37382952 pmcid: 10311389 doi: 10.1001/jamanetworkopen.2023.21102
Wu, C. H. et al. Cardiorespiratory fitness is associated with sustained neurocognitive function during a prolonged inhibitory control task in young adults: an ERP study. Psychophysiology 59, e14086 (2022).
pubmed: 35506488 doi: 10.1111/psyp.14086
Nayor, M. et al. Physical activity and fitness in the community: the Framingham Heart Study. Eur. Heart J. 42, 4565–4575 (2021).
pubmed: 34436560 pmcid: 8633734 doi: 10.1093/eurheartj/ehab580
Lewis, G. D. et al. Developments in exercise capacity assessment in heart failure clinical trials and the rationale for the design of METEORIC-HF. Circ. Heart Fail. 15, e008970 (2022).
pubmed: 35236099 doi: 10.1161/CIRCHEARTFAILURE.121.008970
Swank, A. M. et al. Modest increase in peak VO
pubmed: 22773109 pmcid: 3732187 doi: 10.1161/CIRCHEARTFAILURE.111.965186
Kitzman, D. W. et al. Effect of caloric restriction or aerobic exercise training on peak oxygen consumption and quality of life in obese older patients with heart failure with preserved ejection fraction: a randomized clinical trial. JAMA 315, 36–46 (2016).
pubmed: 26746456 pmcid: 4787295 doi: 10.1001/jama.2015.17346
Sanford, J. A. et al. Molecular transducers of physical activity consortium (MoTrPAC): mapping the dynamic responses to exercise. Cell 181, 1464–1474 (2020).
pubmed: 32589957 pmcid: 8800485 doi: 10.1016/j.cell.2020.06.004
Jackson, A. S. et al. Prediction of functional aerobic capacity without exercise testing. Med. Sci. Sports Exerc. 22, 863–870 (1990).
pubmed: 2287267 doi: 10.1249/00005768-199012000-00021
Heil, D. P., Freedson, P. S., Ahlquist, L. E., Price, J. & Rippe, J. M. Nonexercise regression models to estimate peak oxygen consumption. Med. Sci. Sports Exerc. 27, 599–606 (1995).
pubmed: 7791593 doi: 10.1249/00005768-199504000-00020
Whaley, M. H., Kaminsky, L. A., Dwyer, G. B. & Getchell, L. H. Failure of predicted VO2peak to discriminate physical fitness in epidemiological studies. Med. Sci. Sports Exerc. 27, 85–91 (1995).
pubmed: 7898344 doi: 10.1249/00005768-199501000-00016
George, J. D., Stone, W. J. & Burkett, L. N. Non-exercise VO2max estimation for physically active college students. Med. Sci. Sports Exerc. 29, 415–423 (1997).
pubmed: 9139183 doi: 10.1097/00005768-199703000-00019
Matthews, C. E., Heil, D. P., Freedson, P. S. & Pastides, H. Classification of cardiorespiratory fitness without exercise testing. Med. Sci. Sports Exerc. 31, 486–493 (1999).
pubmed: 10188755 doi: 10.1097/00005768-199903000-00019
Malek, M. H., Housh, T. J., Berger, D. E., Coburn, J. W. & Beck, T. W. A new nonexercise-based VO
pubmed: 15595304 doi: 10.1249/01.MSS.0000142299.42797.83
Malek, M. H., Housh, T. J., Berger, D. E., Coburn, J. W. & Beck, T. W. A new non-exercise-based Vo2max prediction equation for aerobically trained men. J. Strength Cond. Res. 19, 559–565 (2005).
pubmed: 16095416
Jurca, R. et al. Assessing cardiorespiratory fitness without performing exercise testing. Am. J. Prev. Med. 29, 185–193 (2005).
pubmed: 16168867 doi: 10.1016/j.amepre.2005.06.004
Bradshaw, D. I. et al. An accurate VO2max nonexercise regression model for 18-65-year-old adults. Res. Q. Exerc. Sport 76, 426–432 (2005).
pubmed: 16739680 doi: 10.1080/02701367.2005.10599315
Nes, B. M. et al. Estimating V·O 2peak from a nonexercise prediction model: the HUNT Study, Norway. Med. Sci. Sports Exerc. 43, 2024–2030 (2011).
pubmed: 21502897 doi: 10.1249/MSS.0b013e31821d3f6f
Cao, Z. B. et al. Prediction of VO2max with daily step counts for Japanese adult women. Eur. J. Appl. Physiol. 105, 289–296 (2009).
pubmed: 18985375 doi: 10.1007/s00421-008-0902-8
Cao, Z. B. et al. Predicting VO2max with an objectively measured physical activity in Japanese women. Med. Sci. Sports Exerc. 42, 179–186 (2010).
pubmed: 20010115 doi: 10.1249/MSS.0b013e3181af238d
Cao, Z. B., Miyatake, N., Higuchi, M., Miyachi, M. & Tabata, I. Predicting VO
pubmed: 20145947 doi: 10.1007/s00421-010-1376-z
Cai, L. et al. Causal associations between cardiorespiratory fitness and type 2 diabetes. Nat. Commun. 14, 3904 (2023).
pubmed: 37400433 pmcid: 10318084 doi: 10.1038/s41467-023-38234-w
Spathis, D. et al. Longitudinal cardio-respiratory fitness prediction through wearables in free-living environments. NPJ Digit. Med. 5, 176 (2022).
pubmed: 36460766 pmcid: 9718831 doi: 10.1038/s41746-022-00719-1
Katz, D. H. et al. Proteomic profiling platforms head to head: leveraging genetics and clinical traits to compare aptamer- and antibody-based methods. Sci. Adv. 8, eabm5164 (2022).
pubmed: 35984888 pmcid: 9390994 doi: 10.1126/sciadv.abm5164
da Silva, W. A. B. et al. Physical exercise increases the production of tyrosine hydroxylase and CDNF in the spinal cord of a Parkinson’s disease mouse model. Neurosci. Lett. 760, 136089 (2021).
pubmed: 34182056 doi: 10.1016/j.neulet.2021.136089
Graham, J. R. et al. Serine protease HTRA1 antagonizes transforming growth factor-beta signaling by cleaving its receptors and loss of HTRA1 in vivo enhances bone formation. PLoS ONE 8, e74094 (2013).
pubmed: 24040176 pmcid: 3770692 doi: 10.1371/journal.pone.0074094
Lee, J. et al. EWSR1, a multifunctional protein, regulates cellular function and aging via genetic and epigenetic pathways. Biochim. Biophys. Acta, Mol. Basis Dis. 1865, 1938–1945 (2019).
pubmed: 30481590 doi: 10.1016/j.bbadis.2018.10.042
Jung, I. H. et al. SVEP1 is a human coronary artery disease locus that promotes atherosclerosis. Sci. Transl. Med. 13, eabe0357 (2021).
pubmed: 33762433 pmcid: 8109261 doi: 10.1126/scitranslmed.abe0357
Nakamura, R. et al. Serum fatty acid-binding protein 4 (FABP4) concentration is associated with insulin resistance in peripheral tissues, a clinical study. PLoS ONE 12, e0179737 (2017).
pubmed: 28654680 pmcid: 5487042 doi: 10.1371/journal.pone.0179737
Wagenknecht, L. E. et al. Cigarette smoking behavior is strongly related to educational status: the CARDIA study. Prev. Med. 19, 158–169 (1990).
pubmed: 2193307 doi: 10.1016/0091-7435(90)90017-E
Dyer, A. R. et al. Alcohol intake and blood pressure in young adults: the CARDIA Study. J. Clin. Epidemiol. 43, 1–13 (1990).
pubmed: 1969463 doi: 10.1016/0895-4356(90)90050-Y
Bild, D. E. et al. Physical activity in young black and white women. The CARDIA Study. Ann. Epidemiol. 3, 636–644 (1993).
pubmed: 7921312 doi: 10.1016/1047-2797(93)90087-K
Sidney, S. et al. Comparison of two methods of assessing physical activity in the Coronary Artery Risk Development in Young Adults (CARDIA) Study. Am. J. Epidemiol. 133, 1231–1245 (1991).
pubmed: 2063831 doi: 10.1093/oxfordjournals.aje.a115835
Sidney, S. et al. Symptom-limited graded treadmill exercise testing in young adults in the CARDIA study. Med. Sci. Sports Exerc. 24, 177–183 (1992).
pubmed: 1549006 doi: 10.1249/00005768-199202000-00004
Pettee Gabriel, K. et al. Factors associated with age-related declines in cardiorespiratory fitness from early adulthood through midlife: CARDIA. Med. Sci. Sports Exerc. 54, 1147–1154 (2022).
pubmed: 35704440 doi: 10.1249/MSS.0000000000002893
Lindsay, T. et al. Descriptive epidemiology of physical activity energy expenditure in UK adults (the Fenland study). Int J. Behav. Nutr. Phys. Act. 16, 126 (2019).
pubmed: 31818302 pmcid: 6902569 doi: 10.1186/s12966-019-0882-6
Ferrucci, L. The Baltimore Longitudinal Study of Aging (BLSA): a 50-year-long journey and plans for the future. J. Gerontol. A Biol. Sci. Med. Sci. 63, 1416–1419 (2008).
pubmed: 19126858 doi: 10.1093/gerona/63.12.1416
Simonsick, E. M., Fan, E. & Fleg, J. L. Estimating cardiorespiratory fitness in well-functioning older adults: treadmill validation of the long distance corridor walk. J. Am. Geriatr. Soc. 54, 127–132 (2006).
pubmed: 16420209 doi: 10.1111/j.1532-5415.2005.00530.x
Bouchard, C. et al. The HERITAGE family study. Aims, design, and measurement protocol. Med. Sci. Sports Exerc. 27, 721–729 (1995).
pubmed: 7674877 doi: 10.1249/00005768-199505000-00015
Protocol for a Large-Scale Prospective Epidemiological Resource (UK Biobank, 2006); www.ukbiobank.ac.uk/media/gnkeyh2q/study-rationale.pdf
Carnethon, M. R. et al. Association of 20-year changes in cardiorespiratory fitness with incident type 2 diabetes: the coronary artery risk development in young adults (CARDIA) fitness study. Diabetes Care 32, 1284–1288 (2009).
pubmed: 19324945 pmcid: 2699748 doi: 10.2337/dc08-1971
Balke, B. & Ware, R. W. An experimental study of physical fitness of Air Force personnel. US Armed Forces Med. J. 10, 675–688 (1959).
Brage, S., Brage, N., Franks, P. W., Ekelund, U. & Wareham, N. J. Reliability and validity of the combined heart rate and movement sensor Actiheart. Eur. J. Clin. Nutr. 59, 561–570 (2005).
pubmed: 15714212 doi: 10.1038/sj.ejcn.1602118
Tanaka, H., Monahan, K. D. & Seals, D. R. Age-predicted maximal heart rate revisited. J. Am. Coll. Cardiol. 37, 153–156 (2001).
pubmed: 11153730 doi: 10.1016/S0735-1097(00)01054-8
Brage, S. et al. Hierarchy of individual calibration levels for heart rate and accelerometry to measure physical activity. J. Appl. Physiol. (1985) 103, 682–692 (2007).
pubmed: 17463305 doi: 10.1152/japplphysiol.00092.2006
Pietzner, M. et al. Synergistic insights into human health from aptamer- and antibody-based proteomic profiling. Nat. Commun. 12, 6822 (2021).
pubmed: 34819519 pmcid: 8613205 doi: 10.1038/s41467-021-27164-0
Candia, J., Daya, G. N., Tanaka, T., Ferrucci, L. & Walker, K. A. Assessment of variability in the plasma 7k SomaScan proteomics assay. Sci. Rep. 12, 17147 (2022).
pubmed: 36229504 pmcid: 9561184 doi: 10.1038/s41598-022-22116-0
Sun, B. B. et al. Plasma proteomic associations with genetics and health in the UK Biobank. Nature 622, 329–338 (2023).
pubmed: 37794186 pmcid: 10567551 doi: 10.1038/s41586-023-06592-6
Gonzales, T. I. et al. Cardiorespiratory fitness assessment using risk-stratified exercise testing and dose-response relationships with disease outcomes. Sci. Rep. 11, 15315 (2021).
pubmed: 34321526 pmcid: 8319417 doi: 10.1038/s41598-021-94768-3
Wu, P. et al. Mapping ICD-10 and ICD-10-CM codes to phecodes: workflow development and initial evaluation. JMIR Med. Inf. 7, e14325 (2019).
doi: 10.2196/14325
Thompson, D. J. et al. UK Biobank release and systematic evaluation of optimised polygenic risk scores for 53 diseases and quantitative traits. Preprint at medRxiv https://doi.org/10.1101/2022.06.16.22276246 (2022).

Auteurs

Andrew S Perry (AS)

Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA.

Eric Farber-Eger (E)

Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA.

Tomas Gonzales (T)

MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.

Toshiko Tanaka (T)

Longtidudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, MD, USA.

Jeremy M Robbins (JM)

Cardiovascular Institute, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.

Venkatesh L Murthy (VL)

Department of Medicine, University of Michigan, Ann Arbor, MI, USA.

Lindsey K Stolze (LK)

Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA.

Shilin Zhao (S)

Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA.

Shi Huang (S)

Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA.

Laura A Colangelo (LA)

Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.

Shuliang Deng (S)

Cardiovascular Institute, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.

Lifang Hou (L)

Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.

Donald M Lloyd-Jones (DM)

Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.

Keenan A Walker (KA)

Multimodal Imaging of Neurodegenerative Disease (MIND) Unit, National Institute on Aging, NIH, Baltimore, MD, USA.

Luigi Ferrucci (L)

Longtidudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, MD, USA.

Eleanor L Watts (EL)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.

Jacob L Barber (JL)

Cardiovascular Institute, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.

Prashant Rao (P)

Cardiovascular Institute, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.

Michael Y Mi (MY)

Cardiovascular Institute, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.

Kelley Pettee Gabriel (KP)

Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.

Bjoern Hornikel (B)

Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.

Stephen Sidney (S)

Kaiser Permanente, Oakland, CA, USA.

Nicholas Houstis (N)

Cardiology Division, Massachusetts General Hospital, Boston, MA, USA.

Gregory D Lewis (GD)

Cardiology Division, Massachusetts General Hospital, Boston, MA, USA.

Gabrielle Y Liu (GY)

Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, University of California Davis, Sacramento, CA, USA.

Bharat Thyagarajan (B)

Department of Laboratory Medicine and Pathology, University of Minnesota, Minnesota, MN, USA.

Sadiya S Khan (SS)

Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.

Bina Choi (B)

Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.

George Washko (G)

Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.

Ravi Kalhan (R)

Division of Pulmonary and Critical Care Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.

Nick Wareham (N)

MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.

Claude Bouchard (C)

Human Genomic Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA.

Mark A Sarzynski (MA)

Department of Exercise Science, University of South Carolina Columbia, Columbia, SC, USA.

Robert E Gerszten (RE)

Cardiovascular Institute, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.

Soren Brage (S)

MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.

Quinn S Wells (QS)

Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA.

Matthew Nayor (M)

Sections of Cardiovascular Medicine and Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA.

Ravi V Shah (RV)

Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA. ravi.shah@vumc.org.

Classifications MeSH