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LOW INTAKE OF CHOLINE IS ASSOCIATED WITH DIMINISHED STRENGTH AND LEAN MASS GAINS IN OLDER ADULTS

 

C.W. Lee1, E. Galvan2, T.V. Lee3, V.C.W. Chen4, S. Bui5, S.F. Crouse6,7, J.D. Fluckey6, S.B. Smith8, S.E. Riechman6,7

 

1. College of Education and Health Professions, University of Houston-Victoria, Victoria, TX, USA; 2. School of Osteopathic Medicine in Arizona, A.T. Still University, Mesa, AZ, USA; 3. Life Sciences Department, Pierce College, Woodland Hills, CA, USA; 4. Department of Integrative Health and Exercise Science, Georgian Court University, Lakewood, NJ, USA; 5. Department of Health and Human Performance, Utah Tech University, St. George, UT, USA; 6. Department of Health and Kinesiology, Texas A&M University, College Station, TX, USA; 7. Department of Nutrition, Texas A&M University, College Station, TX, USA; 8. Department of Animal Science, Texas A&M University, College Station, TX, USA

Corresponding Author: Chang Woock Lee, Ph.D., Assistant Professor, Kinesiology, College of Education and Health Professions, University of Houston-Victoria, Victoria, TX 77901, USA, leec3@uhv.edu

J Frailty Aging 2022;in press
Published online September 18, 2022, http://dx.doi.org/10.14283/jfa.2022.50

 


Abstract

Objectives: Choline is an essential micronutrient for many physiological processes related to exercise training including biosynthesis of acetylcholine. Though dietary choline intake has been studied in relation to endurance training and performance, none have studied it during resistance exercise training (RET) in older adults. The objective of the study was to examine the relationship between choline intake and muscle responses to RET in older adults.
Methods: Forty-six, 60-69-year-old individuals (M=19, F=27) underwent 12 weeks of RET (3x/week, 3 sets, 8-12 reps, 75% of maximum strength [1RM], 8 exercises). Body composition (DEXA) and 1RM tests were performed before and after training. After analyzing 1,656 diet logs (3x/week, 46 participants, 12 weeks), participants’ mean choline intakes were categorized into three groups: Low (2.9-5.5 mg/kg lean/d), Med-Low (5.6-8.0 mg/kg lean/d), or Adequate (8.1-10.6 mg/kg lean/d). These correspond to <50%, ~63%, and ~85% of Adequate Intake (AI) for choline, respectively.
Results: Gains in composite strength (leg press + chest press 1RM) were significantly lower in the Low group compared with the other groups (Low: 30.9 ± 15.1%, Med-Low: 70.3 ± 48.5%, Adequate: 81.9 ± 68.4%; p=0.004). ANCOVA with cholesterol, protein, or other nutrients did not alter this result. Reduced gains in lean mass were also observed in the Low group, compared with higher choline intake of 5.6-10.6 mg/kg lean/d (1.3 ± 0.6% vs. 3.2 ± 0.6%, p<0.05).
Conclusion: These data suggest that this population of older adults does not consume adequate choline and lower choline intake is negatively and independently associated with muscle responses to RET.

Key words: Sarcopenia, exercise, muscle, nutrition, resistance training.


 

Introduction

Skeletal muscle constitutes ~50% of body mass and is responsible for more than half of the whole body metabolism (1). It is also the largest reservoir of amino acids and disposal site for glucose, and its dysfunction is closely related to several clinical conditions including cardiovascular diseases, diabetes, obesity, and osteoporosis. In addition, after the age of 40, skeletal muscle mass is lost by 5% per decade, which can result in sarcopenia, or age-related muscle loss and strength (2, 3). Considering the effects on overall health and well-being, it is important to optimize skeletal muscle mass and function, especially for older adults.
It is well known that resistance exercise (RE) has a significant impact on increasing/maintaining muscle mass, strength, and function. It is also well established that the effects of RE can be moderated by nutritional intake. However, besides total energy intake, carbohydrate, and protein, the effects of other macro/micronutrients on the muscle responses to RE are still not clear (4).
The micronutrient choline plays important roles in human physiology including cell membrane integrity/signaling, lipid transport, and methylation. Choline is also a precursor to acetylcholine (ACh), the neurotransmitter released at the neuromuscular junction to initiate skeletal muscle contraction. Because choline deficiency (<10% Adequate Intake [AI]) is associated with clinical manifestations of muscle damage, liver dysfunction, and neurological disorders, choline was acknowledged as an essential micronutrient by the Institute of Medicine (IOM) in 1998 (5, 6), but few data on choline content of foods were available until 2004 (7).
There have been a few studies in which the relationship between choline and exercise was examined. Marathon runs or long-duration high-speed bicycle rides decreased blood choline concentrations, but the effect of lowered blood choline levels on exercise performance was equivocal (8-11). In other studies, treadmill exercises, cycling, and cross country racing had no effect on blood choline, and choline supplementation to maintain or increase blood choline concentrations did not affect exercise performance (9, 12-16).
However, these studies were mostly conducted in the context of acute bouts of endurance or anaerobic exercises, and there has been no study that examined the effect of habitual choline intake on skeletal muscle responses (mass and strength) to resistance exercise training (RET). Considering that synthesis and release of ACh is proportional to neural activation rate, and endurance exercise has a relatively low frequency activation rate (17, 18), it is not surprising that choline effects are equivocal with endurance exercises. Moreover, many of the previous studies lacked nutritional control, which may have further obscured potential effects of choline on muscle responses to exercise.
The purpose of this study was to examine the relationship between variability of choline intake in the context of a healthy diet, as recommended by the Dietary Guidelines for Americans (19), and muscle responses to RET in older adults. We hypothesized that choline intake would be linearly associated with strength and lean mass gains following 12 weeks of RET.

 

Methods

Participants

Forty-six, 60-69-year-old individuals (males: 64.3 ± 3.3 yrs.; females: 63.7 ± 2.9 yrs., postmenopausal for more than two years), recruited through advertisements, completed a 12-week RET program. All the participants were non-smokers, apparently healthy, and untrained: Individuals with uncontrolled hypertension (>160/100 mmHg), diabetes, cardiac arrhythmias, cancer, hernia, aortic aneurysm, kidney disease, or lung disease were excluded, and those who engaged in more than one hour of RET per week in the previous year (physical activity questionnaire) (20) were not eligible. This study was approved by the Kent State University (03-472) and Texas A&M University (2015-0182M) Institutional Review Boards, and all the participants provided written informed consent. Other details on this cohort are provided elsewhere (21, 22).

Pre-study Orientation

Before starting the 12-week RET, participants attended six orientation sessions over two weeks. Each orientation session comprised one hour of exercise familiarization, wherein the participants learned correct exercise techniques by exercising at low intensity (40% of their estimated maximum strength based on the Omnibus-RE Scale [OMNI-RES] ratings of perceived exertion [RPE]) (23) to reduce the possibility of injury and standardize early gains in strength due to motor learning. Additionally, they received 30 minutes of nutrition education by a registered dietitian on proper nutrient intake and accurate diet log documentation. Participants were instructed to maintain isocaloric food intake (50% carbohydrate, 30% fat, 20% protein, and <10% saturated fat) and consume >1.0 g/kg/d of protein, 25-30 g/d of fiber, and <300 mg/d of cholesterol throughout the study.

Testing

Upon completion of the orientation, body composition was measured by dual energy X-ray absorptiometry (DEXA) using Hologic 4500 QDR (Bedford, MA). Then, maximum strengths (1RM) for all the exercises of the RET program were determined (23). After a three-minute warm-up on cycle ergometers (Schwinn Fitness, Inc., Denver, CO) and stretching, participants performed four warm-up repetitions with a resistance set at 55% of estimated 1RM based on OMNI-RES RPE. The resistance was then adjusted to 75% of re-estimated 1RM, and participants performed one repetition. The resistance was increased again to 90% of re-estimated 1RM for participants to perform one repetition. The attempts for the best estimated 1RM were made by gradually increasing resistance in a manner that the total number of 1RM attempts were minimized. The exercise order for 1RM measurement was the same for all participants, and the rest interval between each attempt was 60 seconds. The same testing was repeated at the completion of the 12-week program.

RET

For 12 weeks, participants performed whole body RET three times per week (on non-consecutive days) using Cybex RET machines (Cybex International Inc., Medway, MA). The exercises comprised leg press, knee extension, seated leg curl, chest press, lat pull down, triceps extension, biceps curl, and calf raises. On each exercise day, the participants performed a 10-minute warm-up on cycle ergometers, five-minute stretching, and three sets of 8-12 repetitions of the exercises. Resistance was set at 75% of each participant’s 1RM, and the participants performed as many repetitions as possible until they reached 12 repetitions or failure. When a participant achieved 12 repetitions on all three sets of an exercise, the exercise weight was increased so that the participant would only be able to achieve eight repetitions per set in the next session. This is to ensure that relative exercise intensity (75% of 1RM) was maintained throughout the study as participants gained strength. All the exercise sessions were monitored by research assistants, and the rest time was 60 seconds between sets and two minutes between exercises. The participants were instructed to maintain their non-RET physical activities at current levels and not to perform additional RET outside of the study.

Nutrition

The participants were required to submit diet logs three times per week on non-consecutive days to investigators for the entire duration of the study, from the first week through the last week. The investigators reviewed each diet log thoroughly, and feedback on the diet logs was provided weekly to ensure accuracy of documentation and compliance to the diet recommendations. To ensure enough protein consumption for muscle gain and to minimize potential effects of variable protein intake, participants consumed post-workout supplements (Boost High Protein; Nestle S.A., Vevey, Switzerland) immediately after each exercise session. The amount of the supplement was adjusted to each participant’s lean mass so that 0.4 g of protein/kg lean mass was consumed with each supplement.
The average intakes of all macro/micro nutrients during the 12-week intervention were calculated using NutriBase software (version 5; Cybersoft Inc., Phoenix, AZ) and the USDA database for choline (24). Then participants’ mean choline intakes for 12 weeks were categorized into three groups (Low: <5.6 mg/kg lean/d, Med-Low: 5.6-8.0 mg/kg lean/d, and Adequate: >8.0 mg/kg lean/d) based on the clusters in their distribution.

Statistical Analysis

All statistical analyses were conducted using IBM SPSS Statistics software (version 27; IBM Corporation, Armonk, NY). The assumption of normal distribution was checked using Shapiro-Wilk test, and non-normal variables were log or square root transformed before tested with parametric statistical procedures. Non-parametric tests were also conducted with non-transformed data to confirm consistency of the test results.
Student’s independent t-tests were performed to examine differences between two groups (e.g., males and females), and paired t-tests were used to compare pre- and post-training values. Pearson’s correlations were used to examine associations between nutrient intakes and RET responses, and linear regression analyses were performed to examine the independent association of choline consumption with changes in composite strength and lean mass. Composite strength was defined as chest press 1RM + leg press 1RM, and percent change was calculated as 100 x (post-training measurement minus pre-training measurement) / pre-training measurement.
The differences in RET responses between choline intake groups were examined using one-way ANOVA. A two-way ANOVA was performed to determine if there were differences in RET responses between choline groups or sex, and analysis of covariance (ANCOVA) tests were used to account for effects of potential confounders (other nutrients, age, etc.). The assumption of equal variance was tested using Levene’s test, and the Bonferroni method was used to perform multiple comparisons. P values of <0.05 were considered statistically significant, and data are presented as mean ± SD unless stated otherwise.

 

Results

Participants

The baseline characteristics of 46 participants who completed the study are presented in Table 1. There were no significant differences among choline groups in age, body weight, body fat, or BMI. But there were more male participants in the Low group, of which participants had greater baseline lean mass compared with the other groups.

Table 1. Participants’ Baseline Characteristics

Data are presented as mean ± SD. Low (n=20): choline intakes of 2.9-5.5 mg/kg lean/d. Med-Low (n=19): choline intakes of 5.6-8.0 mg/kg lean/d. Adequate (n=7): choline intakes of 8.1-10.6 mg/kg lean/d. § denotes a significant difference from Low group (p<0.01). * denotes a significant difference from Low group (p<0.05).

 

Nutritional Intakes

Based on 1,656 diet logs collected throughout the study (36 diet logs for each of the 46 participants), all the participants met dietary recommendations for total energy, protein, cholesterol, and macronutrient proportions. There were no differences among groups except for protein/kg (higher in Adequate group) and percent of kcal from carbohydrate (lower in Med-Low group) (Table 2). No significant differences were observed in intakes of micronutrients related to choline metabolism such as vitamins B5, B6, B12, folate, and betaine.

Table 2. Nutritional Intakes

Data are presented as mean ± SD. Low (n=20): choline intakes of 2.9-5.5 mg/kg lean/d. Med-Low (n=19): choline intakes of 5.6-8.0 mg/kg lean/d. Adequate (n=7): choline intakes of 8.1-10.6 mg/kg lean/d. § denotes a significant difference from the other groups (p<0.05). * denotes a significant difference from Low group (p<0.05).

 

The average choline consumption during the study was 304.2 ± 70 mg/day (6.1 ± 1.6 mg/kg lean/d or 3.9 ± 0.9 mg/kg/d). Dietary choline (mg/kg lean/d) was significantly correlated with total energy (kcal/kg lean/d, r=0.516, p<0.001), protein (g/kg lean/d, r=0.733, p<0.001), carbohydrate (g/kg lean/d, r=0.295, p=0.047), fat (g/kg lean/d, r=0.442, p=0.002), and cholesterol (mg/kg lean/d, r=0.519, p<0.001) intakes, but none of these nutrients were significantly correlated with muscle responses to RET except for cholesterol, which was significantly correlated with percent changes in composite strength (r=0.386, p=0.009) and lean mass (r=0.364, p=0.013).

Effects of Choline on RET Responses

Choline intake (mg/kg lean/d) was significantly correlated with percent change in composite strength (r=0.36, p=0.015) while a trend was observed between choline consumption and percent change in lean mass (r=0.265, p=0.075). A linear regression analysis shows that choline intake explains (β=0.655, t=2.534, R2=0.13) the variability of percent change in composite strength.
There was a significant difference in composite strength gains among choline groups (Figure 1). While RET resulted in significant increases in lean mass and strength in all three groups (Table 3 and 4), the Low group gained significantly less composite strength compared with the other groups (Low: 30.9 ± 15.1%, Med-Low: 70.3 ± 48.5%, Adequate: 81.9 ± 68.4%; p=0.004). The Low group also showed significantly reduced improvements in 1RM for leg press and chest press compared with the higher choline intake groups (Table 4), and similar trends were observed for calf raises (p=0.08) and triceps extension (p=0.07).

Table 3. The Effect of Choline Intakes on Body Composition

Data are presented as mean ± SD. Low (n=20): choline intakes of 2.9-5.5 mg/kg lean/d. Med-Low (n=19): choline intakes of 5.6-8.0 mg/kg lean/d. Adequate (n=7): choline intakes of 8.1-10.6 mg/kg lean/d. All changes from baseline are statistically significant except for change in body fat (kg) in Adequate group. No differences were observed between choline intake groups (p>0.1).

 

Table 4. The Effect of Choline Intakes on Changes (%) in 1RM

Data are presented as mean ± SD. Low (n=20): choline intakes of 2.9-5.5 mg/kg lean/d. Med-Low (n=19): choline intakes of 5.6-8.0 mg/kg lean/d. Adequate (n=7): choline intakes of 8.1-10.6 mg/kg lean/d. All changes from baseline are statistically significant. * denotes a significant difference from Low group (p<0.05).

 

Since there was a difference between choline groups in sex distribution, and females had higher intakes of protein (g/kg lean/d), cholesterol (mg/kg lean/d), and choline (mg/kg lean/d), a two-way ANOVA test was conducted to determine if there was a difference in composite strength gains (%) between choline groups or sex. There was no interaction between sex and choline group, and the effect of sex was not significant while the main effect for choline intake was significant (p<0.05). Multiple comparisons showed the Low group gained significantly less composite strength compared with the other groups (p<0.05).
Choline consumption was correlated with total energy, protein, carbohydrate, fat, and cholesterol intakes in the present study. Since many choline rich foods (e.g., eggs, fish, and meat) are also rich in fat, protein, and cholesterol (24), and choline metabolism is intertwined with betaine, folate, and vitamins B5, B6, and B12 metabolism (5, 25), ANCOVA tests were conducted to separate the effects of these dietary factors as well as other covariates such as age and baseline lean mass from the effects of choline. Significant (p<0.05) differences in composite strength gains (%) among choline groups were observed after adjusting for these covariates, either separately or in various combinations, indicating independent effects of choline intake on strength gains.
Multiple linear regression analyses were also conducted to further separate the effects of choline from those of other variables such as age, sex, and other nutrients, especially cholesterol, because cholesterol was previously reported to be associated with strength and lean mass gains in older adults (22) and was correlated with RET responses in the present study. All of the aforementioned variables were initially entered into the equation, and after a series of backward elimination procedures, only low choline intake (β=-1.833, p=0.036), age (β=-0.002, p=0.089), and cholesterol intake (β=0.341, p=0.156) remained in the final model, which showed that choline intake independently explains percent change in composite strength.
Because RET responses, nutritional intakes, and demographic characteristics were similar between Med-Low and Adequate groups (Tables 1-3, Figure 1), the two groups were pooled (“higher” choline intake group) for further analyses. ANCOVA showed that the Low group gained significantly less lean mass compared with the higher choline intake (5.6-10.6 mg/kg lean/d) group (1.3 ± 0.6% vs. 3.2 ± 0.6%, estimated marginal mean ± SE, folate/kg lean/d as a covariate, p<0.05). Two-way ANOVA showed a trend (p=0.076) indicating the effect of choline intake on percent change in lean mass while sex and the interaction between choline intake and sex were not significant (p>0.5).

Figure 1. The Effect of Choline Intake on Changes in Composite Strength (%)

Data are presented as mean ± SE. Composite strength is defined as chest press 1RM + leg press 1RM. * denotes a significant difference from Low group (p<0.01).

 

Discussion

To our knowledge, the present study is the first to examine the effect of dietary choline intake on muscle responses to RET in older adults. The major finding of the present study is that choline intake (in the 49th-85th percentile of AI) is strongly associated with the magnitude of strength gains following 12 weeks of RET in older adults. Our data also showed a moderate effect of choline intake on lean mass gains.
The mechanism through which choline may affect strength and lean mass gains with RET is unknown. However, since ACh production/release can be mediated by availability of choline (26, 27), dietary choline may affect ACh at the neuromuscular junctions (NMJ), influencing skeletal muscle responses. While previous studies utilizing endurance exercise models failed to observe meaningful effects of choline, RE may have different results. Neuromuscular transmission failure is suggested as a major factor in fatigue of skeletal muscles composed of predominantly fast-twitch fibers (28), which are highly recruited with RE (29). The low frequency motor output and lower number of active motor units associated with endurance exercise might allow sufficient re-synthesis of ACh in motor neurons while high frequency motor output and greater number of motor units recruited with RE might reduce ACh availability at the NMJ (18, 30).
Choline is also a precursor to phosphatidylcholine (PC), the most abundant phospholipid in all membranes. Choline deficiency has been shown to compromise cell membranes and cause muscle damage (31), thus may negatively influence the muscle’s ability to handle mechanical load of RE. In addition, PC is a precursor to phosphatidic acid (PA), which is required to activate mammalian target of rapamycin (mTOR), a central element in the regulation of protein synthesis (32). Therefore, insufficient choline consumption might limit skeletal muscle hypertrophy and strength gains associated with RET.
We also observed the majority of the participants in the present study consumed less than the recommended amount of choline (90th percentile of choline intake was 393 mg/d), which is similar to previously published data. In the Framingham Offspring Study, only 20% of the subjects (mean age:54y) consumed >401 mg/d choline while 80% of 1,477 females (mean age: 52y) consumed less than 361 mg of choline per day in Chiuve et al.’s study (33, 34). The present study provides additional evidence that inadequate choline consumption is prevalent in older populations. The current AI of choline for adults is ~7 mg/kg body weight/day (550 mg/d for males and 425 mg/d for females) (6). In the present study, Low, Med-Low, and Adequate groups consumed ~49%, ~63%, and ~85% AI of choline, respectively. We observed that Low group (<50% of AI) gained significantly less strength and lean mass following 12 weeks of RET compared with higher choline intake groups. Reduced strength gains with inadequate choline intake adds to the established list of consequences identified with low choline consumption including muscle/liver damage, cardiovascular disease, neurological disorder, and even cancer. Our results emphasize that even typical/average intakes, which are below AI but do not present overt clinical signs, still have consequences that may negatively affect health and well-being of older adults.
It should be noted that there are several limitations to our study. The results of the present study provide evidence only in the low to near-adequate levels of choline consumption. Therefore, the effects of higher choline intake on lean mass and strength gains still remain unknown even though previous studies did not observe any effect of choline supplementation (higher than AI) on acute exercise performances (12-16).
In addition, we were not able to determine blood choline concentrations. Therefore, the associations of blood choline with muscle responses to RET were not examined. However, we believe this does not change the overall conclusions of our observation because blood choline levels do not effectively reflect moderate changes in choline intake (35). Data also suggest that blood choline is regulated at relatively constant levels with moderately low choline consumption in resting individuals, and blood concentration of choline does not represent intracellular levels of choline (35-37). Also, the well-known limitations of diet logs, such as potentially inaccurate measurement and/or documentation of food intake, may have affected the accuracy of our analyses. However, the impact of potentially inaccurate diet logs was minimized by combined effects of pre-study nutrition education, collection of 1,656 total diet logs for 12 weeks (>36 diet logs per participant, including baseline reports), and provision of regular feedback to ensure compliance to the diet guidelines and accurate documentation of food intake.

 

Conclusion

Our data suggest that dietary choline has a linear relation (in the 49th-85th percentile of AI) with skeletal muscle responses to 12-week RET in generally healthy 60–69-year-old men and women. Lower intake of choline was associated with reduced gains in strength and lean mass in this population. Considering the effects of skeletal muscle on overall health and well-being, especially in older population whose choline intake is persistently low, it is important to optimize nutritional factors to maximize the benefits of RET. Future studies are warranted to confirm the results of the present study and elucidate the mechanism through which choline affects skeletal muscle responses to RET.

 

Acknowledgements: This work was partially supported by Mead Johnson and Novartis who provided the protein supplement.

Conflict of Interest: Authors have no conflict of interest to disclose, and the study results are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation.

Ethical Standards: All the experiments in the present study comply with the current laws of the United States of America.

 

References

1. Riechman SE, Lee CW, Chikani G, Chen VCW, Lee TV. Cholesterol and skeletal muscle health. World Rev Nutr Diet 2009;100:71-79. doi:10.1159/000235713
2. Melton LJ 3rd, Khosla S, Crowson CS, O’Connor MK, O’Fallon WM, Riggs BL. Epidemiology of sarcopenia. J Am Geriatr Soc 2000;48(6):625-630. doi:10.1111/j.1532-5415.2000.tb04719.x
3. Evans WJ. What is sarcopenia? J Gerontol A Biol Sci Med Sci 1995;50 Spec No:5-8. doi:10.1093/gerona/50a.special_issue.5
4. Mithal A, Bonjour JP, Boonen S, et al. Impact of nutrition on muscle mass, strength, and performance in older adults. Osteoporos Int 2013;24:1555-1566. doi:10.1007/s00198-012-2236-y
5. Zeisel SH, da Costa KA. Choline: an essential nutrient for public health. Nutr Rev 2009;67(11):615-623. doi:10.1111/j.1753-4887.2009.00246.x
6. Institute of Medicine. Dietary reference intakes for thiamin, riboflavin, niacin, vitamin B6, folate, vitamin B12, pantothenic acid, biotin, and choline. 1998. National Academies Press, Washington, DC. doi:10.17226/6015
7. Howe JC, Williams JR, Holden JM, Nutrient Data Laboratory (U.S.). USDA database for the choline content of common foods. 2004. USDA Agricultural Research Service, Beltsville, MD. https://handle.nal.usda.gov/10113/47335
8. Conlay LA, Sabounjian LA, Wurtman RJ. Exercise and neuromodulators: choline and acetylcholine in marathon runners. Int J Sports Med 1992;13:S141-142. doi:10.1055/s-2007-1024619
9. von Allworden HN, Horn S, Kahl J, Feldheim W. The influence of lecithin on plasma choline concentrations in triathletes and adolescent runners during exercise. Eur J Appl Physiol 1993;67:87-91. doi:10.1007/bf00377711
10. Buchman AL, Jenden D, Roch M. Plasma free, phospholipid-bound and urinary free choline all decrease during a marathon run and may be associated with impaired performance. J Am Coll Nutr 1999;18(6):598-601. doi:10.1080/07315724.1999.10718894
11. Høeg, TB, Chmiel K, Warrick AE, Taylor SL, Weiss RH. Ultramarathon plasma metabolomics: phosphatidylcholine levels associated with running performance. Sports 2020;8(4):44. doi:10.3390/sports8040044
12. Spector SA, Jackman MR, Sabounjian LA, Sakkas C, Landers DM, Willis WT. Effect of choline supplementation on fatigue in trained cyclists. Med Sci Sports Exerc 1995;27(5):668-673. doi:10.1249/00005768-199505000-00008
13. Warber JP, Patton JF, Tharion WJ, et al. The effects of choline supplementation on physical performance. Int J Sport Nutr Exerc Metab 2000;10(2):170-181. doi:10.1123/ijsnem.10.2.170
14. Buchman AL, Awal M, Jenden D, Roch M, Kang SH. (2000) The effect of lecithin supplementation on plasma choline concentrations during a marathon. J Am Coll Nutr 2000;19(6): 768-770. doi:10.1080/07315724.2000.10718076
15. Deuster P, Singh A, Coll R, Hyde D, Becker W. Choline ingestion does not modify physical or cognitive performance. Mil Med 2002;167(12):1020-1025. doi:10.1093/milmed/167.12.1020
16. Bunn JA, Crossley A, Timiney MD. Acute ingestion of neuromuscular enhancement supplements do not improve power output, work capacity, and cognition. J Sports Med Phys Fitness 2018;58(7-8):974-979. doi:10.23736/s0022-4707.17.07022-0
17. Taylor P, Brown JH. Synthesis, storage, and release of acetylcholine. In: Siegel GJ, Agranoff BW, Albers RW, et al. (ed) Basic neurochemistry: molecular, cellular, and medical aspects, 6th edn. 1999. Lippincott-Raven, Philadelphia. https://www.ncbi.nlm.nih.gov/books/NBK28051/
18. Enoka RM, Duchateau J. Rate coding and the control of muscle force. Cold Spring Harb Perspect Med 2017;7(10):a029702. doi:10.1101/cshperspect.a029702
19. U.S. Department of Health and Human Services, U.S. Department of Agriculture. Dietary Guidelines for Americans, 6th edn. 2005. U.S. Government Printing Office, Washington, DC. https://health.gov/sites/default/files/2020-01/DGA2005.pdf
20. Sylvia LG, Bernstein EE, Hubbard JL, Keating L, Anderson EJ. Practical guide to measuring physical activity. J Acad Nutr Diet 2014;114(2):199-208. doi:10.1016/j.jand.2013.09.018
21. Andrews RD, MacLean DA, Riechman SE. Protein intake for skeletal muscle hypertrophy with resistance training in seniors. Int J Sport Nutr Exerc Metab 2006;16(4):362-372. doi:10.1123/ijsnem.16.4.362
22. Riechman SE, Andrews RD, Maclean DA, Sheather S. Statins and dietary and serum cholesterol are associated with increased lean mass following resistance training. J Gerontol A Biol Sci Med Sci 2007;62(10):1164-1171. doi:10.1093/gerona/62.10.1164
23. Gearhart RF Jr, Lagally KM, Riechman SE, Andrews RD, Robertson RJ. RPE at relative intensities after 12 weeks of resistance-exercise training by older adults. Percept Mot Skills 2008;106(3):893-903. doi:10.2466/pms.106.3.893-903
24. Patterson KY, Bhagwat SA, Williams JR, Howe JC, Holden JM, Nutrient Data Laboratory (U.S.). USDA database for the choline content of common foods release two. 2008. USDA Agricultural Research Service, Beltsville, MD. https://www.ars.usda.gov/ARSUserFiles/80400525/data/choline/choln02.pdf
25. Zeisel SH. Choline: an essential nutrient for humans. Nutrition 2000;16(7-8):669-671. doi:10.1016/s0899-9007(00)00349-x
26. Bierkamper GG, Goldberg AM. Release of acetylcholine from the vascular perfused rat phrenic nervehemidiaphragm. Brain Res 1980;202(1):234-237. doi:10.1016/s0006-8993(80)80052-7
27. Wurtman RJ, Hefti F, Melamed E. Precursor control of neurotransmitter synthesis. Pharmacol Rev 1980;32(4):315-335. https://pharmrev.aspetjournals.org/content/32/4/315.long
28. Pagala MKD, Namba T, Grob D. Failure of neuromuscular transmission and contractility during muscle fatigue. Muscle Nerve 1984;7(6):454-464. doi:10.1002/mus.880070607
29. Grgic J, Schoenfeld BJ. Are the hypertrophic adaptations to high and low-load resistance training muscle fiber type specific? Front Physiol 2018;9:402. doi:10.3389/fphys.2018.00402
30. Del Vecchio A, Casolo A, Negro F, et al. The increase in muscle force after 4 weeks of strength training is mediated by adaptations in motor unit recruitment and rate coding. J Physiol 2019;597(7):1873-1887. doi:10.1113/jp277250
31. da Costa KA, Badea M, Fischer LM, Zeisel SH. Elevated serum creatine phosphokinase in choline-deficient humans: mechanistic studies in C2C12 mouse myoblasts. Am J Clin Nutr 2004;80(1):163-170. doi:10.1093/ajcn/80.1.163
32. Fang Y, Vilella-Bach M, Bachmann R, Flanigan A, Chen J. Phosphatidic acid-mediated mitogenic activation of mTOR signaling. Science 2001;294(5548):1942-1945. doi:10.1126/science.1066015
33. Chiuve SE, Giovannucci EL, Hankinson SE, et al. The association between betaine and choline intakes and the plasma concentrations of homocysteine in women. Am J Clin Nutr 2007;86(4):1073-1081. doi:10.1093/ajcn/86.4.1073
34. Cho E, Zeisel SH, Jacques P, et al. Dietary choline and betaine assessed by food-frequency questionnaire in relation to plasma total homocysteine concentration in the Framingham Offspring Study. Am J Clin Nutr 2006;83(4):905-911. doi:10.1093/ajcn/83.4.905
35. Abratte CM, Wang W, Li R, Axume J, Moriarty DJ, Caudill MA. Choline status is not a reliable indicator of moderate changes in dietary choline consumption in premenopausal women. J Nutr Biochem 2009;20(1):62-69. doi:10.1016/j.jnutbio.2007.12.002
36. Fischer LM, da Costa KA, Kwock L, et al. Sex and menopausal status influence human dietary requirements for the nutrient choline. Am J Clin Nutr 2007;85(5):1275-1285. doi:10.1093/ajcn/85.5.1275
37. Mills JL, Fan R, Brody LC, et al. Maternal choline concentrations during pregnancy and choline-related genetic variants as risk factors for neural tube defects. Am J Clin Nutr 2014;100(4):1069-1074. doi:10.3945/ajcn.113.079319