The Association between Circulating Branched Chain Amino Acids and the Temporal Risk of Developing Type 2 Diabetes Mellitus: A Systematic Review & Meta-Analysis
Abstract
:1. Introduction
2. Materials and Methods
2.1. Protocol and Registration
2.2. Eligibility Criteria
2.3. Information Sources and Searches
2.4. Study Selection
2.5. Data Collection Process
2.6. Intra-Study Risk of Bias Assessment
Summary Measures
2.7. Synthesis of Results
2.8. Risk of Bias across Studies
2.9. Additional Analyses
3. Results
3.1. Study Selection
3.2. Study Characteristics
3.3. Risk of Bias within Studies
3.4. Results of Individual Studies
3.5. Valine
3.6. Leucine
3.7. Isoleucine
3.8. Synthesis of Results
Risk of Bias across Studies
3.9. Sensitivity
4. Discussion
4.1. Summary of Evidence
4.2. Limitations
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
BCAA | Branch Chain Amino Acid |
BCKA | Branched-chain α-ketoacids |
mTORc1 | Mammalian Target Rapamycin Complex 1 |
NICE | National Institute for Clinical Excellence |
PRISMA | Preferred Reporting Items for Systematic Reviews and Meta-Analyses |
PICOS | Population, Intervention, Comparison and Studies |
PROSPERO | International Prospective Register of Systematic Reviews |
T2DM | Type 2 Diabetes Mellitus |
BMI | Body Mass Index |
WHO | World Health Organisation |
ID | Identification |
IR | Insulin Resistance |
SD | Standard Deviation |
C2 | Aceylcarnitine |
CI | Confidence Interval |
TSA | Trial Sequential Analysis |
FBC | Fasting Blood Glucose |
BP | Blood Pressure |
IV | Inverse Variance |
ORs | Odds Ratios |
RoB | Risk of Bias |
SMD | Standardised Mean Difference |
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Lead Author | Publication Date | Study Design | Cases (n) | Control (n) | Patient Demographics (Intervention(s)) | Follow-Up Period (Y) | Covariates | Cases Group Status | Control Group Status | Individual BCAAs | BCAA Metabolites |
---|---|---|---|---|---|---|---|---|---|---|---|
F Ottosson [31] | 2018 | Case-control | 204 | 496 | Mean of 69.5 years, predominantly male (69%), Swedish nationality | 6.3 | Age and Sex. | T2DM | Non-diabetic | Leucine, Isoleucine, Valine | C5, C4 and C3 |
Y Lu [30] | 2016 | Case-control | 197 | 197 | 55.15 ± 2.8 years, predominantly female (59.4%), Chinese nationality | 6 | BMI, smoking, history of hypertension | T2DM | Non-diabetic, | Leucine, Isoleucine, Valine | C10 |
L Shi [41] | 2018 | Case-control | 503 | 503 | 50.1 ± 8 years, predominantly female (55.5%), Swedish nationality | 10 | BMI, FBC, PA, education, smoking, consumption of alcohol, dietary fibre, red and processed meat, and coffee, plasma total cholesterol, triglycerols, and systolic and diastolic BP. | T2DM (no medication | Non-diabetic, | Leucine, Isoleucine, Valine | C3 and KMV |
T Wang (Framingham) [42] | 2011 | Case-control | 189 | 189 | 56.5 ± 8.5 years, predominantly male (58%), USA nationality | 12 | Age, sex, BMI, fasting glucose, and parental history. | T2DM | Non-diabetic | Leucine, Isoleucine, Valine | - |
T Wang (Malmo) [42] | 2011 | Case-control | 163 | 163 | Mean of 58 years, predominantly female (55%), Swedish nationality | 12.6 | Age, sex, BMI, and fasting glucose. | T2DM | Non-diabetic | Leucine, Isoleucine, Valine | - |
A Floegel [43] | 2013 | Case-control | 800 | 2282 | 52.1 ± 8.1 years, predominantly women (52.1%), German nationality | 7 | age, sex, alcohol intake, smoking, physical activity, education, coffee intake, red meat intake, prevalent hypertension, BMI, and waist circumference (cm) | T2DM | Non-diabetic | Isoleucine, Valine | - |
R Wang-Sattler [44] | 2012 | Case-control | 91 | 866 | 64.7 ± 5.45 years, predominantly male (53%), German nationality | 7 | Age, sex, BMI, physical activity, alcohol intake, smoking, systolic BP, HDL cholesterol, HbA1c, fasting glucose and fasting insulin | T2DM(no medication) | Non-diabetic | Leucine, Isoleucine, Valine | C2 |
A Stancáková [45] | 2012 | Case-control | 646 | 3026 | 57 ± 7 years, all male, Finnish nationality | 4.7 | Age and BMI | T2DM(no medication) | Non-diabetic | Leucine, Isoleucine, Valine | - |
T Tillin (European) [46] | 2015 | Case-control | 643 | 1007 | 50.6 ± 7.0 years, all male, South Asian origin | 19 | Age, WHR, truncal skinfold thickness, Matsuda-IR, HDL cholesterol level, current smoking, and alcohol consumption. | T2DM(no medication) | Non-diabetic | Leucine, Isoleucine, Valine | - |
T Tillin (South Asian) [46] | 2015 | Case-control | 801 | 1279 | 52.75 ± 7.25 years, all male, European origin | 19 | Age, WHR, truncal skinfold thickness, Matsuda-IR, HDL cholesterol level, current smoking, and alcohol consumption. | T2DM(no medication) | Non-diabetic | Leucine, Isoleucine, Valine | - |
ND Palmer [29] | 2015 | Case-control | 76 | 70 | 56 ± 8 years, predominantly female (63%), European-American, Hispanic, and African American ethnicity | 5 | Age, sex, and BMI | T2DM(no medication) | Non-diabetic | Leucine or isoleucine, valine | C2, C5 and C10 |
Lead Author | Publication Date | Valine Outcome Measure | Leucine Outcome Measure | Isoleucine Outcome Measure | ||||||
---|---|---|---|---|---|---|---|---|---|---|
Log(OR) | SE | p-Value | Log(OR) | SE | p-Value | Log(OR) | SE | p-Value | ||
F Ottosson [31] | 2018 | 0.73 | 0.01 | 0.94 | 0.74 | 0.02 | 0.197 | 0.75 | 0.03 | 0.064 |
Y Lu [30] | 2016 | 0.94 | 0.84 | 0.0003 * | 0.92 | 0.83 | 0.0023 | 0.92 | 0.83 | 0.4 * |
L Shi [41] | 2018 | 0.84 | 0.27 | <0.001 * | 0.81 | 0.22 | 0.002 | 0.81 | 0.22 | 0.002 * |
T Wang [42] | 2011 | 0.75 | 0.14 | 0.34 | 0.79 | 0.18 | 0.034 | 0.80 | 0.17 | 0.01 * |
T Wang [42] | 2011 | 0.24 | 0.05 | 5.89 × 10−5 * | - | - | - | 0.26 | 0.05 | 3.04 × 10−5 * |
A Floegel [43] | 2013 | 0.81 | 0.28 | 0.03 * | 0.81 | 0.28 | 0.06 | 0.85 | 0.37 | 0.008 * |
R Wang-Sattler [44] | 2012 | 0.79 | 0.15 | 0.016 * | 0.84 | 0.22 | 0.006 | 0.85 | 0.23 | 0.001 * |
A Stancáková [45] | 2012 | 0.82 | 0.29 | 0.02 * | 0.84 | 0.32 | 0.006 | 0.85 | 0.32 | 0.004 * |
T Tillin [46] | 2015 | 0.88 | 0.57 | 0.01 * | 0.83 | 0.29 | 0.009 | 0.80 | 0.26 | 0.09 |
T Tillin [46] | 2015 | 0.78 | 0.14 | 0.044 * | 0.77 | 0.14 | 0.074 | 0.77 | 0.14 | 0.13 |
ND Palmer [29] | 2015 | 0.73 | 0.12 | 0.9 | 0.75 | 0.12 | 0.4 | 0.75 | 0.13 | 0.4 |
Temporal Subgroup (Years Follow-Up) | Data Sources (Lead Author; Year of Publication; BCAAs) | Covariates (Lead Author; Variables) | OR | 95% CI (Lower–Upper) | p-Value |
---|---|---|---|---|---|
0 to 6 | Palmer, 2015 [29] (iso, leu, val) Lu, 2016 [30] (iso, leu, val) | Palmer; Age, sex, BMI, and AIR Lu; BMI, smoking, history of hypertension | 2.28 | 1.77–2.94 | p < 0.00001 |
>6 to <12 | Ottosson, 2018 [31] (iso, leu, val) | Ottosson; age and sex | 2.17 | 1.81–2.60 | p < 0.00001 |
≥12 | Wang (Malmo dataset), 2011 [42] (iso, leu, val) | Wang [Malmo dataset]; age, sex, BMI, and fasting glucose | 2.27 | 1.59–3.25 | p < 0.00001 |
Lead Author | Valine | Leucine | Isoleucine | |||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
BMI | HOMA-IR | HbA1c | BMI | HOMA-IR | HbA1c | BMI | HOMA-IR | HbA1c | ||||||||||
Outcome | p-Value | Outcome | p-Value | Outcome | p-Value | Outcome | p-Value | Outcome | p-Value | Outcome | p-Value | Outcome | p-Value | Outcome | p-Value | Outcome | p-Value | |
F Ottosson [31] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
Y Lu [30] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
L Shi (S) [41] | 0.24 | - | 0.2 | 0.01 | - | - | 0.26 | - | 0.25 | <0.001 | - | - | 0.26 | - | 0.29 | <0.001 | - | - |
T Wang (P) (Framingham) [42] | - | - | 0.24 | 0.0008 | - | - | - | - | 0.24 | 0.0009 | - | - | - | - | 0.24 | 0.0007 | - | - |
T Wang (Malmo) [42] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
A Floegel [43] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
R Wang-Sattler (P) [44] | 0.27 | - | - | - | 0.08 | - | 0.19 | - | - | - | 0.09 | - | 0.19 | - | - | - | 0.09 | - |
A Stancáková [45] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
T Tillin (S) (European) [46] | 0.22 | <0.05 | 0.27 | <0.05 | - | - | 0.18 | <0.05 | 0.26 | <0.05 | - | - | 0.23 | <0.05 | 0.34 | <0.05 | - | - |
T Tillin (S) (South.Asian) [46] | 0.29 | <0.05 | 0.33 | <0.05 | - | - | 0.27 | <0.05 | 0.31 | <0.05 | - | - | 0.31 | <0.05 | 0.35 | <0.05 | - | - |
ND Palmer [29] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
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Ramzan, I.; Ardavani, A.; Vanweert, F.; Mellett, A.; Atherton, P.J.; Idris, I. The Association between Circulating Branched Chain Amino Acids and the Temporal Risk of Developing Type 2 Diabetes Mellitus: A Systematic Review & Meta-Analysis. Nutrients 2022, 14, 4411. https://doi.org/10.3390/nu14204411
Ramzan I, Ardavani A, Vanweert F, Mellett A, Atherton PJ, Idris I. The Association between Circulating Branched Chain Amino Acids and the Temporal Risk of Developing Type 2 Diabetes Mellitus: A Systematic Review & Meta-Analysis. Nutrients. 2022; 14(20):4411. https://doi.org/10.3390/nu14204411
Chicago/Turabian StyleRamzan, Imran, Arash Ardavani, Froukje Vanweert, Aisling Mellett, Philip J. Atherton, and Iskandar Idris. 2022. "The Association between Circulating Branched Chain Amino Acids and the Temporal Risk of Developing Type 2 Diabetes Mellitus: A Systematic Review & Meta-Analysis" Nutrients 14, no. 20: 4411. https://doi.org/10.3390/nu14204411