It is extremely important to recognize insulin resistance early as it can precede overt diabetes by several years. [i] Read part 3 of the ODX Insulin Series on the best ways to assesses insulin resistance
Insulin resistance itself may not by symptomatic though it is a common finding in metabolic syndrome which is characterized by: [iii]
Risk factors for insulin resistance include: [iv] [v]
Even in young subjects ages 8-19 years old, increased insulin resistance was significantly associated with central obesity, high blood pressure, elevated triglycerides, low HDL, and impairments in glucose tolerance and fasting glucose. [vi]
Insulin resistance is becoming more common though less obvious in seemingly healthy individuals. Both insulin resistance and metabolic syndrome pave the way to type 2 diabetes.
Air pollution is another risk factor for insulin resistance and inflammation, especially in those with prediabetes. For those with diabetes, increasing exposure to traffic on a major roadway was associated with elevations in blood glucose. [vii]
Insulin resistance is also associated with other disorders including: [viii]
Cerebral insulin resistance is suspected of being a factor in cognitive impairment and Alzheimer’s. Both human and animal research suggest that insulin plays an important role in brain metabolism, synaptic viability, neurotransmitter turnover, and possibly amyloid beta peptide clearance. [ix]
Considering how sensitive the brain is to insulin and glucose levels, it should be no surprise the depression is also associated with insulin resistance. A cross-sectional cohort study of 639 subjects revealed that women suffering from depressive symptoms had a greater waist circumference, higher HOMA-IR, and higher levels of leptin and tumor necrosis factor than those without symptoms. In men, depressive symptoms were associated with higher C-reactive protein levels but lower body fat compared to men without symptoms. [x]
Fasting glucose:
Fasting insulin:
Adiponectin:
Inflammatory markers
Markers for inflammation include interleukin-1 and glycoprotein acetylation (GlycA) in addition to hs-CRP and interleukin-6. [xiii]
Triglycerides
Hypertriglyceridemia may serve as a predictor of insulin resistance as it significantly correlated with fasting insulin, HOMA, and metabolic syndrome in subjects with an increased waist circumference (greater than 102 cm for males, greater than 85 cm for females). [xiv]
In a cohort study of Manitoba First Nation individuals, elevated fasting triglycerides were significantly associated with changes in insulin resistance and incident diabetes. Those with fasting triglycerides 187 mg/dL (2.11 mmol/L) or greater had a 4 times greater risk of diabetes than those with a fasting triglyceride level of less than 120 mg/dL (1.36 mmol/L). [xv]
Branched chain amino acids
Research suggests that insulin resistance promotes measurable increases in circulating levels of amino acids, especially branched-chain amino acids (BCAAs- leucine, isoleucine, valine) which are in turn associated with risk of T2DM. Underlying causes of this phenomenon may be genetic and not related to dietary intake of BCAAs. [xvi]
In fact, dietary BCAAs have been associated with positive effects including muscle protein synthesis, glucose homeostasis, and regulation of body weight and body composition. It appears that elevated fasting levels of BCAAs may reflect metabolic dysregulation in those with obesity and increased risk of T2DM. [xvii] [xviii]
Insulin has an inhibitory effect on the release of BCAAs from skeletal muscle. Blood levels of BCAAs increase sharply and significantly in the absence of insulin (or its effects) as occurs in diabetic ketoacidosis. [xix]
Researchers suggest that circulating BCAAs may serve as a biomarker for evaluating risk of T2DM. [xx]
C-peptide
C-peptide reflects insulin production and release as it is a byproduct of the conversion of pro-insulin to insulin. C-peptide correlates significantly with HOMA-IR and may serve as a surrogate marker. [xxi]
Alpha-hydroxybutyrate
Alpha-hydroxybutyrate, an organic acid formed from alpha-ketobutyrate, may be an early marker for insulin resistance and impaired glucose tolerance. Elevations in alpha-hydroxybutyrate appear to be related to oxidative stress, increased lipid oxidation, amino acid catabolism, and increased demand for hepatic glutathione. [xxii]
A cohort study of 82 individuals found that fasting levels of alpha-hydroxybutyrate correlated significantly with elevations in fasting glucose, fasting insulin, HOMA-IR, BMI, body fat, waist circumference, waist-to-hip ratio, triglycerides, total cholesterol, and LDL cholesterol. [xxiii]
Fortunately, evaluating individual biomarkers listed above along with a full assessment of individual risk factors will help to reveal where one may be on the road to insulin resistance and diabetes.
Biomarkers can also be looked at in their relationship to one another to gauge insulin resistance in an individual. Homeostasis Model Assessment (HOMA2) calculations incorporate fasting glucose, fasting insulin, and C-peptide levels, while the Quantitative Insulin Sensitivity Check Index (QUICKI) utilizes the log of fasting glucose and fasting insulin. We will cover these calculations in a separate blog.
Up Next - Insulin Resistance part 4 - Take a U-Turn and Reverse Insulin Resistance
[i] Tripathy, Devjit et al. “Contribution of insulin-stimulated glucose uptake and basal hepatic insulin sensitivity to surrogate measures of insulin sensitivity.” Diabetes care vol. 27,9 (2004): 2204-10.
[ii] MD App insulin sensitivity QUICKI calculator. Retrieved September 27, 2020
[iii] Geloneze, Bruno et al. “HOMA1-IR and HOMA2-IR indexes in identifying insulin resistance and metabolic syndrome: Brazilian Metabolic Syndrome Study (BRAMS).” Arquivos brasileiros de endocrinologia e metabologia vol. 53,2 (2009): 281-7.
[iv] MD App insulin sensitivity QUICKI calculator. Retrieved September 27, 2020
[v] Gutch, Manish et al. “Assessment of insulin sensitivity/resistance.” Indian journal of endocrinology and metabolism vol. 19,1 (2015): 160-4.
[vi] Lee, SoJung et al. “Insulin resistance: link to the components of the metabolic syndrome and biomarkers of endothelial dysfunction in youth.” Diabetes care vol. 30,8 (2007): 2091-7.
[vii] Wolf, Kathrin et al. “Association Between Long-term Exposure to Air Pollution and Biomarkers Related to Insulin Resistance, Subclinical Inflammation, and Adipokines.” Diabetes vol. 65,11 (2016): 3314-3326.
[viii] Gutch, Manish et al. “Assessment of insulin sensitivity/resistance.” Indian journal of endocrinology and metabolism vol. 19,1 (2015): 160-4.
[ix] Kellar, Derek, and Suzanne Craft. “Brain insulin resistance in Alzheimer's disease and related disorders: mechanisms and therapeutic approaches.” The Lancet. Neurology vol. 19,9 (2020): 758-766.
[x] Webb, M'Balu et al. “The association between depressive symptoms and insulin resistance, inflammation and adiposity in men and women.” PloS one vol. 12,11 e0187448. 30 Nov. 2017.
[xi] Herder, Christian et al. “Biomarkers of subclinical inflammation and increases in glycaemia, insulin resistance and beta-cell function in non-diabetic individuals: the Whitehall II study.” European journal of endocrinology vol. 175,5 (2016): 367-77.
[xii] Herder, Christian et al. “Biomarkers of subclinical inflammation and increases in glycaemia, insulin resistance and beta-cell function in non-diabetic individuals: the Whitehall II study.” European journal of endocrinology vol. 175,5 (2016): 367-77.
[xiii] Wang, Qin et al. “Genetic Support for a Causal Role of Insulin Resistance on Circulating Branched-Chain Amino Acids and Inflammation.” Diabetes care vol. 40,12 (2017): 1779-1786.
[xiv] Li, Zhaoping et al. “Hypertriglyceridemia is a practical biomarker of metabolic syndrome in individuals with abdominal obesity.” Metabolic syndrome and related disorders vol. 11,2 (2013): 87-91.
[xv] Riediger, Natalie D et al. “Fasting triglycerides as a predictor of incident diabetes, insulin resistance and β-cell function in a Canadian First Nation.” International journal of circumpolar health vol. 76,1 (2017): 1310444.
[xvi] Wang, Qin et al. “Genetic Support for a Causal Role of Insulin Resistance on Circulating Branched-Chain Amino Acids and Inflammation.” Diabetes care vol. 40,12 (2017): 1779-1786.
[xvii] Lynch, Christopher J, and Sean H Adams. “Branched-chain amino acids in metabolic signalling and insulin resistance.” Nature reviews. Endocrinology vol. 10,12 (2014): 723-36.
[xviii] Yoon, Mee-Sup. “The Emerging Role of Branched-Chain Amino Acids in Insulin Resistance and Metabolism.” Nutrients vol. 8,7 405. 1 Jul. 2016.
[xix] Adeva, María M et al. “Insulin resistance and the metabolism of branched-chain amino acids in humans.” Amino acids vol. 43,1 (2012): 171-81.
[xx] Roberts, Lee D et al. “Towards metabolic biomarkers of insulin resistance and type 2 diabetes: progress from the metabolome.” The lancet. Diabetes & endocrinology vol. 2,1 (2014): 65-75.
[xxi] Khan, Haseeb A et al. “Biomarker potential of C-peptide for screening of insulin resistance in diabetic and non-diabetic individuals.” Saudi journal of biological sciences vol. 25,8 (2018): 1729-1732.
[xxii] Gall, Walter E et al. “alpha-hydroxybutyrate is an early biomarker of insulin resistance and glucose intolerance in a nondiabetic population.” PloS one vol. 5,5 e10883. 28 May. 2010.
[xxiii] Sarı, Hakan, et al. "Serum α-Hydroxybutyrate: A Candidate Marker of Insulin Resistance Is Associated with Deterioration in Anthropometric Measurements in Individuals with Low Diabetes Risk." The Journal of Applied Laboratory Medicine 1.5 (2017): 562-567.