FormalPara Key Summary Points

Why carry out this study?

Prevalence of neuropathy in people living with obesity even with normoglycaemia is well recognized. This study aimed to evaluate the differences in neuropathy phenotype between primarily hyperglycaemia-driven versus obesity-driven cardiometabolic factors in the development of axonal peripheral neuropathy.

What was learned from the study?

The prevalence and phenotype of peripheral neuropathy are comparable between normoglycaemic people with obesity and long-duration type 1 diabetes, suggesting that obesity-related risk factors and hyperglycaemia may contribute equally to the development of neuropathy.

Higher centripetal adiposity, BMI, total body fat and triglycerides in people with obesity are independent risk factors for elevated vibration perception threshold and peripheral neuropathy.

Metabolic markers of impaired fat oxidation are not associated with peripheral neuropathy in obesity.

Introduction

The global prevalence of obesity has more than doubled since the 1980s, affecting an estimated 604 million adults and 108 million children [1]. Within the UK, 27% of adults are obese (body mass index (BMI) ≥ 30 kg/m2) [2], and 3–4% are severely obese (BMI ≥ 40 kg/m2) [3]. Furthermore, the prevalence of obesity is projected to rise substantially by 2030 in the USA, such that 48.9% of adults will be obese and 24.2% will be severely obese [4].

Obesity is associated with systemic inflammation and endothelial dysfunction which can lead to peripheral neuropathy in both type 2 diabetes (T2D) [5], and type 1 diabetes (T1D) [6]. The EURODIAB study demonstrated that BMI, hypertension and dyslipidaemia had comparable risk to HbA1c for incident neuropathy in people with T1D [7]. The Anglo-Danish-Dutch study of Intensive Treatment of Diabetes in Primary Care (ADDITION) confirmed that abdominal obesity independently predicted peripheral neuropathy in newly diagnosed patients with T2D [8]. Furthermore, obesity has been associated with peripheral neuropathy independent of hyperglycaemia and hypertriglyceridemia [9]. The Rotterdam study reported that abdominal obesity, metabolic syndrome and dyslipidaemia were strongly associated with peripheral neuropathy in the absence of diabetes [10]. In addition, symptomatic peripheral neuropathy is more common in metabolic syndrome, independent of glycaemic status [1. The mean duration of T1D was 23.4 ± 13.5 years. As expected, participants with obesity (OB) had a greater BMI (P < 0.001), body fat percentage (P < 0.001), WC (P < 0.001), total cholesterol (P < 0.001), LDL-cholesterol (P < 0.001) and triglycerides (P < 0.001) compared to participants with T1D. According to the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATPIII) definition of metabolic syndrome, 58% of participants fulfilled the criteria for metabolic syndrome in the OB group.

Table 1 Demographics, clinical and metabolic characteristics in HVs and participants with T1D and OB
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Neuropathy Assessment

Peripheral neuropathy measures are summarised in Table 2. Peripheral neuropathy was present in 43.1% of participants with T1D and 33.3% of participants living with OB according to the Toronto consensus criteria for peripheral neuropathy. Impaired VPT (15–24 V) and advanced VPT deemed at high risk of neuropathic ulcer (≥ 25 V) were present in 19.6% and 31.4% in T1D and 23.5% and 19.6% of participants living with OB. There were no differences in VAS for pain, NSP, NDS, VPT, SNCV and SNAP between T1D and OB groups. However, both T1D and OB groups demonstrated greater VAS for pain, NDS, NSP, VPT, SNCV and SNAP compared to HV (P < 0.001). There was an association between VPT and VAS pain (R2 = 0.330) (Fig. S1 in the supplementary material).

Table 2 Peripheral neuropathy measurements in HVs and participants with T1D and OB
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We evaluated correlation between VPT as the primary dependent variable with anthropometric, metabolic and body composition measurements in the whole cohort (OB, HV, and T1D) using Pearson’s correlation analysis (Table 3). VPT correlated with NSP (ρ = 0.841, P < 0.001), VAS (ρ = 0.761, P < 0.001) and WC (ρ = 0.420, P < 0.001). VPT also correlated with age (ρ = 0.269, P = 0.002), BMI (ρ = 0.348, P < 0.001), body fat percentage (FM%) (ρ = 0.280, P = 0.001), HbA1c (ρ = 0.400, P < 0.001), total cholesterol (ρ = 0.227, P = 0.010), triglycerides (ρ = 0.299, P = 0.001), systolic BP (ρ = 0.379, P < 0.001), and diastolic BP (ρ = 0.350, P < 0.001) (Table 3). Subgroup analysis was performed in the OB group to evaluate the association between VPT and that of metabolic biomarkers obtained from indirect calorimetry (REE and RQ). REE and RQ data were obtained and performed in the OB group only (Table 3).

Table 3 Pearson’s correlation of variables against vibration perception threshold
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Stepwise multivariate linear regression modelling was performed with VPT as the dependent variable from the entire cohort (HV, T1D and OB) (Table 4). In model 1, BMI (β = 0.333; P < 0.001) and age (β = 0.249; P = 0.002) correlated with VPT as the primary dependent variable. In model 2, VPT correlated with age (β = 0.257; P < 0.001) and WC (β = 0.433; P < 0.001), but not BMI (P = 0.214) and FM% (P = 0.119). In model 3, VPT correlated with age (β = 0.149; P = 0.037), WC (β = 0.382; P = 0.018), FM% (β = 0.783; P < 0.001) and HbA1c (β = 1.051; P < 0.001) but there was no significant correlation with BMI, total cholesterol, triglycerides, systolic and diastolic blood pressure.

Table 4 Multivariate linear regression model using VPT as the dependent variable
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Obese With and Without Peripheral Neuropathy

Of the 51 participants with OB, 33.3% (n = 17) fulfilled the criteria for peripheral neuropathy according to the Toronto consensus criteria on peripheral neuropathy [15]. Within the OB group, the prevalence of impaired VPT (15–24 V) was 23.5% (n = 12) and prevalence of advanced VPT deemed at high risk of neuropathic ulcer (VPT ≥ 25 V) was 19.6% (n = 10). The peripheral neuropathy subgroup within OB had a greater NSP (P < 0.001), VAS for pain (P < 0.001) and VPT (P < 0.001) with lower SNCV (P < 0.001) and SNAP (P = 0.003). WC (P = 0.028) and FM% (P < 0.001) were significantly higher in obese participants with peripheral neuropathy compared to those without peripheral neuropathy.

In the OB group, measured substrate oxidation, represented by the RQ (mean RQ = 1.016; 95% CI 0.9888–1.044) during the rested and overnight fasted metabolic state, was not associated with VPT (P = 0.934), sural nerve conduction velocity (SNCV) (P = 0.743) or sural nerve amplitude (SNAP) (P = 0.677).

Discussion

This cross-sectional study demonstrated a comparable prevalence of peripheral neuropathy in normoglycaemic people with obesity compared to people with long-duration T1D. This advocates that peripheral neuropathy is a result of a culmination of complex interaction of several aetiologically linked pathophysiological processes. Furthermore, our report demonstrates that there is a positive association between obesity and greater centripetal adiposity, approximated by increased waist circumference and increased body fat percentage, with increased and/or impaired VPT. The link between obesity and peripheral neuropathy have been attributed to metabolically driven cardiovascular risk factors such as hypertension, hyperlipidaemia and inflammation [7, 17] leading to degenerative processes within the small nerve fibres. However, these mechanisms are not fully elucidated. Obesity and hypertriglyceridemia predict the development of diabetic neuropathy in T2D, independent of glycaemic control [18]. In a recent cross-sectional study of 47 participants with severe obesity and 30 age-matched controls, participants with severe obesity had a higher NSP, abnormal thermal thresholds and lower sural and peroneal nerve amplitudes compared to controls, and those with obesity and small nerve fibre damage had higher triglycerides and prevalence of metabolic syndrome (58% vs 23%; P = 0.02) [19]. Interestingly, we did not demonstrate an association between neuropathy and triglycerides, likely because of the good control of lipids in the OB cohort as they were under the care of a tertiary weight management clinic. Experimental studies have demonstrated that neurones send vasoactive signals to increase vascular permeability and attract adaptive immunogenic cells in high fat diet-fed rodents with obesity, dyslipidaemia and neuropathy [20, 21]. Although initially a protective mechanism, persistent dysfunction secondary to obesity-mediated inflammation results in structural neuronal damage. Further, inflammatory mediators (tumour necrosis alpha and interleukin-1B) and macrophages promote a long-term microvascular inflammatory response and impairment of insulin signalling in the peripheral nervous system [22]. Peripheral neuropathy has been associated with increased abdominal and visceral obesity [23]. In addition, obstructive sleep apnoea (OSA) which is prevalent in severe obesity and even in T1D is an independent risk factor for axonal dysfunction of peripheral sensory nerves [24]. Unfortunately, OSA data was not available within this cohort and this risk factor could not be further investigated in the current study.

Autonomic dysfunction may be involved in the development of obesity and visceral/central obesity with increased peripheral insulin resistance [25, 26]. Xu et al. showed that BMI was an independent risk factor for abnormal plantar pressures and increased VPT [27]. In patients with T2D, Gao et al. [35].

Emerging research suggests that the development and progression of neuropathy is associated with an impaired metabolic switch from glucose to fatty acid or lipid oxidation [36] with an association between cholesterol oxidation and glycated LDL and the pathogenesis of neuropathy [37]. Reduced peripheral insulin sensitivity also leads to increased fatty acid flux into Schwann cells and subsequent peripheral neuropathy [38, 39]. Obesity is associated with the loss of peripheral sensory neurons and pathology to intra-epidermal nerve fibres [40, 41]. Local fat metabolism in the peripheral nerve is of importance in maintaining an intact and functional peripheral nerve. Previous data has demonstrated that several genes are only maximally expressed in the mature nerve, after the completion of myelination, and are also linked to the metabolism of storage lipids [42]. Within obesity and T2D, there is intracellular accumulation of metabolites with enhanced fatty acid uptake and blunted fatty acid oxidation and lack of insulin-mediated inhibition of lipolysis [43]. This leads to excess circulatory ‘spill’ with uptake by non-adipose tissue like the liver, muscle, heart and pancreas leading to ectopic fat deposition and dyslipidemia. Consequent to the dyslipidemia state, free fatty acid-induced lipotoxicity alters lipid-induced intracellular signaling and drives neurological dysfunction and neurodegeneration [44]. Whilst this study has shown impaired fat oxidation and ‘overreliance’ on glucose oxidation in obesity, fat oxidation per se was not associated with peripheral neuropathy measures. However, cross-sectional measures of fat oxidation which are fluid may not correlate with more ‘fixed’ quantitative measures of peripheral neuropathy.

In a large retrospective cohort study of 88,981 patients with T2D, bariatric surgery was associated with significantly lower rates of microvascular and macrovascular complications, compared to a non-surgically treated group over 9 years [45], and this has been corroborated by other studies [46]. Bariatric surgery in people with obesity with and without T2D is associated with improved biomarkers of neuropathy, specifically evidence of small nerve fibre regeneration over 12 months [40, 41] evaluated with corneal confocal microscopy. The prevalence of peripheral neuropathy measured with the Michigan Neuropathy Screening Instrument (MNSI) was found to be reduced (pre-bariatric surgery 20.4% to post-bariatric surgery 10.5%) approximately 10 years after Roux-en-Y gastric bypass and sleeve gastrectomy [47]. Several randomized controlled studies (DiRECT, DROPLET and PREVIEW) have demonstrated the efficacy of low-calorie diets (LCDs; 800–850 kcal/day) in severe obesity [48,49,50]; and recently, a dietary weight loss study of 800 kcal/day (for 12 weeks) followed by 1200–1500 kcal/day resulted in an improvement in metabolic parameters, whilst intra-epidermal nerve fibre density (IENFD) remained stable after 2 years [51].

We acknowledge that causality between obesity and neuropathy cannot be inferred from a cross-sectional study. We have also not undertaken small fibre phenoty** which may be more relevant to obesity-related neuropathy. A larger sample size may also have allowed adjustment of confounding factors for neuropathy in relation to RQ or index of fat oxidation, and RQ subanalysis may be limited because of the severe obesity present in the participant population.

Conclusion

The prevalence and characteristics of peripheral neuropathy were comparable between normoglycaemic people with obesity and long-duration T1D, suggesting that metabolic factors linked to obesity play a significant role in development of peripheral neuropathy. Further studies are needed to investigate the role of visceral adiposity in peripheral neuropathy.