Oppenheimer GM, Benrubi ID. McGovern’s Senate Select Committee on Nutrition and Human Needs versus the meat industry on the diet-heart question (1976-1977). Am J Public Health. 2014;104(1):59–69.
Article
PubMed
PubMed Central
Google Scholar
Abbasi J. TMAO and heart disease: the new red meat risk? JAMA. 2019;321(22):2149–51.
Article
PubMed
Google Scholar
Wang ZY, Liu YY, Liu GH, Lu HB, Mao CY. L-carnitine and heart disease. Life Sci. 2018;194:88–97.
Article
CAS
PubMed
Google Scholar
Kim J, Park J, Lim K. Nutrition supplements to stimulate lipolysis: a review in relation to endurance exercise capacity. J Nutr Sci Vitaminol. 2016;62(3):141–61.
Article
CAS
PubMed
Google Scholar
Koeth RA, Wang Z, Levison BS, Buffa JA, Org E, Sheehy BT, et al. Intestinal microbiota metabolism of L-carnitine, a nutrient in red meat, promotes atherosclerosis. Nat Med. 2013;19(5):576–85.
Article
CAS
PubMed
PubMed Central
Google Scholar
Schooling CM, Huang JV, Zhao JV, Kwok MK, Au Yeung SL, Lin SL. Disconnect between genes associated with ischemic heart disease and targets of ischemic heart disease treatments. EBioMedicine. 2018;28:311–5.
Article
CAS
PubMed
PubMed Central
Google Scholar
Odle J, Adams SH, Vockley J. Carnitine. Adv Nutr. 2014;5(3):289–90.
Article
PubMed
PubMed Central
Google Scholar
Ahmed MM, Ibrahim ZS, Alkafafy M, El-Shazly SA. L-carnitine protects against testicular dysfunction caused by gamma irradiation in mice. Acta Histochem. 2014;116(6):1046–55.
Article
CAS
PubMed
Google Scholar
Zhu B, Zheng YF, Zhang YY, Cao YS, Zhang L, Li XG, et al. Protective effect of L-carnitine in cyclophosphamide-induced germ cell apoptosis. J Zhejiang Univ Sci B. 2015;16(9):780–7.
Article
CAS
PubMed
PubMed Central
Google Scholar
Schooling CM, Zhao JV, Au Yeung SL, Leung GM. Investigating pleiotropic effects of statins on ischemic heart disease in the UK Biobank using Mendelian randomisation. Elife. 2020;9:e58567.
Article
CAS
PubMed
PubMed Central
Google Scholar
Luo S, Au Yeung SL, Zhao JV, Burgess S, Schooling CM. Association of genetically predicted testosterone with thromboembolism, heart failure, and myocardial infarction: mendelian randomisation study in UK Biobank. BMJ. 2019;364:l476.
Article
PubMed
PubMed Central
Google Scholar
Zhao JV, Schooling CM. Endogenous androgen exposures and ischemic heart disease, a separate sample Mendelian randomization study. Int J Cardiol. 2016;222:940–5.
Article
PubMed
Google Scholar
Schooling CM. Practical applications of evolutionary biology in public health. Lancet. 2017;390(10109):2246.
Article
PubMed
Google Scholar
DiNicolantonio JJ, Lavie CJ, Fares H, Menezes AR, O'Keefe JH. L-carnitine in the secondary prevention of cardiovascular disease: systematic review and meta-analysis. Mayo Clin Proc. 2013;88(6):544–51.
Article
CAS
PubMed
Google Scholar
Song X, Qu H, Yang Z, Rong J, Cai W, Zhou H. Efficacy and safety of L-carnitine treatment for chronic heart failure: a meta-analysis of randomized controlled trials. Biomed Res Int. 2017;2017:6274854.
PubMed
PubMed Central
Google Scholar
Johri AM, Heyland DK, Hetu MF, Crawford B, Spence JD. Carnitine therapy for the treatment of metabolic syndrome and cardiovascular disease: evidence and controversies. Nutr Metab Cardiovasc Dis. 2014;24(8):808–14.
Article
CAS
PubMed
Google Scholar
Lawlor DA, Harbord RM, Sterne JA, Timpson N, Davey Smith G. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med. 2008;27(8):1133–63.
Article
PubMed
Google Scholar
Bennett DA, Holmes MV. Mendelian randomisation in cardiovascular research: an introduction for clinicians. Heart. 2017;103(18):1400–7.
Article
CAS
PubMed
Google Scholar
Schooling CM, Freeman G, Cowling BJ. Mendelian randomization and estimation of treatment efficacy for chronic diseases. Am J Epidemiol. 2013;177(10):1128–33.
Article
CAS
PubMed
Google Scholar
Lotta LA, Pietzner M, Stewart ID, Wittemans LBL, Li C, Bonelli R, et al. A cross-platform approach identifies genetic regulators of human metabolism and health. Nat Genet. 2021;53(1):54–64.
Article
CAS
PubMed
PubMed Central
Google Scholar
Bowden J, Del Greco MF, Minelli C, Davey Smith G, Sheehan NA, Thompson JR. Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic. Int J Epidemiol. 2016;45(6):1961–74.
PubMed
PubMed Central
Google Scholar
Staiger D, Stock JH. Instrumental variables regression with weak instruments. Econometrica. 1997;65(3):557–86.
Article
Google Scholar
Richard MA, Lupo PJ, Zachariah JP. Causal inference of carnitine on blood pressure and potential mediation by uric acid: a Mendelian randomization analysis. Int J Cardiol Cardiovasc Risk Prev. 2021;11:200120.
Article
PubMed
PubMed Central
Google Scholar
Nikpay M, Goel A, Won HH, Hall LM, Willenborg C, Kanoni S, et al. A comprehensive 1,000 Genomes-based genome-wide association meta-analysis of coronary artery disease. Nat Genet. 2015;47(10):1121–30.
Article
CAS
PubMed
PubMed Central
Google Scholar
Malik R, Chauhan G, Traylor M, Sargurupremraj M, Okada Y, Mishra A, et al. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nat Genet. 2018;50(4):524–37.
Article
CAS
PubMed
PubMed Central
Google Scholar
FINNGEN. https://www.finngen.fi/fi. Accessed 7 June 2022.
Shah S, Henry A, Roselli C, Lin H, Sveinbjornsson G, Fatemifar G, et al. Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure. Nat Commun. 2020;11(1):163.
Article
CAS
PubMed
PubMed Central
Google Scholar
Nielsen JB, Thorolfsdottir RB, Fritsche LG, Zhou W, Skov MW, Graham SE, et al. Biobank-driven genomic discovery yields new insight into atrial fibrillation biology. Nat Genet. 2018;50(9):1234–9.
Article
CAS
PubMed
PubMed Central
Google Scholar
Sudlow C, Gallacher J, Allen N, Beral V, Burton P, Danesh J, et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015;12(3):e1001779.
Article
PubMed
PubMed Central
Google Scholar
Zuber V, Gill D, Ala-Korpela M, Langenberg C, Butterworth A, Bottolo L, et al. High-throughput multivariable Mendelian randomization analysis prioritizes apolipoprotein B as key lipid risk factor for coronary artery disease. Int J Epidemiol. 2021;50(3):893–901.
Article
PubMed
Google Scholar
Richardson TG, Wang Q, Sanderson E, Mahajan A, McCarthy MI, Frayling TM, et al. Effects of apolipoprotein B on lifespan and risks of major diseases including type 2 diabetes: a Mendelian randomisation analysis using outcomes in first-degree relatives. Lancet Healthy Longev. 2021;2(6):e317–26.
Article
PubMed
PubMed Central
Google Scholar
Xue A, Wu Y, Zhu Z, Zhang F, Kemper KE, Zheng Z, et al. Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes. Nat Commun. 2018;9(1):2941.
Article
PubMed
PubMed Central
CAS
Google Scholar
Lagou V, Magi R, Hottenga JJ, Grallert H, Perry JRB, Bouatia-Naji N, et al. Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability. Nat Commun. 2021;12(1):24.
Article
CAS
PubMed
PubMed Central
Google Scholar
Chen J, Spracklen CN, Marenne G, Varshney A, Corbin LJ, Luan J, et al. The trans-ancestral genomic architecture of glycemic traits. Nat Genet. 2021;53(6):840–60.
Article
CAS
PubMed
PubMed Central
Google Scholar
Global Lipids Genetics C, Willer CJ, Schmidt EM, Sengupta S, Peloso GM, Gustafsson S, et al. Discovery and refinement of loci associated with lipid levels. Nat Genet. 2013;45(11):1274–83.
Article
CAS
Google Scholar
Yengo L, Sidorenko J, Kemper KE, Zheng Z, Wood AR, Weedon MN, et al. Meta-analysis of genome-wide association studies for height and body mass index in approximately 700000 individuals of European ancestry. Hum Mol Genet. 2018;27(20):3641–9.
Article
CAS
PubMed
PubMed Central
Google Scholar
Burgess S, Scott RA, Timpson NJ, Davey Smith G, Thompson SG, Consortium E-I. Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors. Eur J Epidemiol. 2015;30(7):543–52.
Article
PubMed
PubMed Central
Google Scholar
Burgess S. Sample size and power calculations in Mendelian randomization with a single instrumental variable and a binary outcome. Int J Epidemiol. 2014;43(3):922–9.
Article
PubMed
PubMed Central
Google Scholar
Freeman G, Cowling BJ, Schooling CM. Power and sample size calculations for Mendelian randomization studies using one genetic instrument. Int J Epidemiol. 2013;42(4):1157–63.
Article
PubMed
Google Scholar
Paternoster R, Brame R, Mazerolle P, Piquero A. Using the correct statistical test for the equality of regression coefficients. Criminology. 1998;36(4):859–66.
Article
Google Scholar
Ong JS, MacGregor S. Implementing MR-PRESSO and GCTA-GSMR for pleiotropy assessment in Mendelian randomization studies from a practitioner’s perspective. Genet Epidemiol. 2019;43(6):609–16.
PubMed
PubMed Central
Google Scholar
Verbanck M, Chen CY, Neale B, Do R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet. 2018;50(5):693–8.
Article
CAS
PubMed
PubMed Central
Google Scholar
Burgess S, Bowden J, Fall T, Ingelsson E, Thompson SG. Sensitivity analyses for robust causal inference from mendelian randomization analyses with multiple genetic variants. Epidemiology. 2017;28(1):30–42.
Article
PubMed
Google Scholar
Hartwig FP, Smith GD, Bowden J. Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption. Int J Epidemiol. 2017;46(6):1985–98.
Article
PubMed
PubMed Central
Google Scholar
Tan YD, Xiao P, Guda C. In-depth Mendelian randomization analysis of causal factors for coronary artery disease. Sci Rep. 2020;10(1):9208.
Article
CAS
PubMed
PubMed Central
Google Scholar
Bjornsson E, Thorleifsson G, Helgadottir A, Guethnason T, Guethbjartsson T, Andersen K, et al. Association of genetically predicted lipid levels with the extent of coronary atherosclerosis in Icelandic adults. JAMA Cardiol. 2020;5(1):13–20.
Article
PubMed
Google Scholar
Samulak JJ, Sawicka AK, Hartmane D, Grinberga S, Pugovics O, Lysiak-Szydlowska W, et al. L-carnitine supplementation increases trimethylamine-N-oxide but not markers of atherosclerosis in healthy aged women. Ann Nutr Metab. 2019;74(1):11–7.
Article
CAS
PubMed
Google Scholar
Takiyama N, Matsumoto K. Age-and sex-related differences of serum carnitine in a Japanese population. J Am Coll Nutr. 1998;17(1):71–4.
Article
CAS
PubMed
Google Scholar
Fukami K, Yamagishi S, Sakai K, Kaida Y, Minami A, Nakayama Y, et al. Carnitine deficiency is associated with late-onset hypogonadism and depression in uremic men with hemodialysis. Aging Male. 2014;17(4):238–42.
Article
PubMed
Google Scholar
Kraemer WJ, Spiering BA, Volek JS, Ratamess NA, Sharman MJ, Rubin MR, et al. Androgenic responses to resistance exercise: effects of feeding and L-carnitine. Med Sci Sports Exerc. 2006;38(7):1288–96.
Article
CAS
PubMed
Google Scholar
Rothman KJ, Gallacher JE, Hatch EE. Why representativeness should be avoided. Int J Epidemiol. 2013;42(4):1012–4.
Article
PubMed
PubMed Central
Google Scholar
Flynn E, Tanigawa Y, Rodriguez F, Altman RB, Sinnott-Armstrong N, Rivas MA. Sex-specific genetic effects across biomarkers. Eur J Hum Genet. 2021;29(1):154–63.
Article
CAS
PubMed
Google Scholar
Schooling CM, Lopez P, Yang Z, Zhao JV, Au Yeung SL, Huang JV. Use of multivariable Mendelian randomization to address biases due to competing risk before recruitment. Front Genet. 2020. https://doi.org/10.3389/fgene.2020.610852.
Rose G. Sick individuals and sick populations. Int J Epidemiol. 2001;30(3):427–32 discussion 433-424.
Article
CAS
PubMed
Google Scholar
Spracklen CN, Horikoshi M, Kim YJ, Lin K, Bragg F, Moon S, et al. Identification of type 2 diabetes loci in 433,540 East Asian individuals. Nature. 2020;582(7811):240–5.
Article
CAS
PubMed
PubMed Central
Google Scholar