Insulin Sensitivity and Skeletal Muscle Mitochondrial Respiration in Black and White Women With Obesity

Justine M Mucinski; Giovanna Distefano; John Dubé; Frederico G S Toledo; Paul M Coen; Bret H Goodpaster; James P DeLany

doi:10.1210/clinem/dgae600

. 2024 Aug 29;110(6):e2026–e2036. doi: 10.1210/clinem/dgae600

Insulin Sensitivity and Skeletal Muscle Mitochondrial Respiration in Black and White Women With Obesity

Justine M Mucinski ¹, Giovanna Distefano ², John Dubé ³, Frederico G S Toledo ⁴, Paul M Coen ⁵, Bret H Goodpaster ⁶, James P DeLany ^7,^✉

PMCID: PMC12086411 PMID: 39207205

Abstract

Objectives

Non-Hispanic Black women (BW) have a greater risk of type 2 diabetes (T2D) and insulin resistance (IR) compared to non-Hispanic White women (WW). The mechanisms leading to these differences are not understood, and it is unclear whether synergistic effects of race and obesity impact disease risk. To understand the interaction of race and weight, hepatic and peripheral IR were compared in WW and BW with and without obesity.

Methods

Hepatic and peripheral IR were measured by a labeled, hyperinsulinemic-euglycemic clamp in BW (n = 32) and WW (n = 32) with and without obesity. Measurements of body composition, cardiorespiratory fitness, and skeletal muscle (SM) respiration were completed. Data were analyzed by mixed model ANOVA.

Results

Subjects with obesity had greater hepatic and peripheral IR and lower SM respiration (P < .001). Despite 14% greater insulin (P = .066), BW tended to have lower peripheral glucose disposal (Rd; P = .062), which was driven by women without obesity (P = .002). BW had significantly lower glucose production (P = .005), hepatic IR (P = .024), and maximal coupled and uncoupled respiration (P < .001) than WW. Maximal coupled and uncoupled SM mitochondrial respiration was strongly correlated with peripheral and hepatic IR (P < .01).

Conclusion

While BW without obesity had lower Rd than WW, race and obesity did not synergistically impact peripheral IR. Paradoxically, WW with obesity had greater hepatic IR compared to BW. Relationships between SM respiration and IR persisted across a range of body weights. These data provide support for therapies in BW, like exercise, that improve SM mitochondrial respiration to reduce IR and T2D risk.

Keywords: insulin sensitivity, skeletal muscle, mitochondrial respiration, racial differences

Type 2 diabetes (T2D) affects over 460 million people worldwide (1), and non-Hispanic Black women (BW) have a disproportionately higher risk of developing T2D and insulin resistance compared to non-Hispanic White women (WW) (2-5). The etiology of racial differences in T2D and insulin resistance remains poorly defined and, in BW, may progress through nontraditional risk factors. Indeed, visceral and hepatic adiposity, which are related to insulin resistance (6), are paradoxically lower in BW when compared to WW (7, 8). Within skeletal muscle, characteristics like fiber type (9), substrate use/metabolic flexibility (10), and mitochondrial function (3-5, 11, 12) have been hypothesized to contribute to risk differences. Our group has previously demonstrated that BW had lower skeletal muscle mitochondrial respiration and reduced peripheral insulin sensitivity when compared to WW (3), although this earlier study only included women without obesity. These physiological factors that contribute to increased disease risk in BW may be impacted by inherited differences (13). For example, mitochondrial DNA (mtDNA) haplogroup is maternally inherited and is associated with mitochondrial function (14-16), cardiorespiratory fitness (17, 18), and T2D (19). Characterizing the key impact of inherited genetic variations will aid in our understanding of risk disparities across BW and WW.

In addition to race differences between BW and WW, overweight and obesity increase the risk for T2D and multiorgan insulin resistance (20), potentially due to poor mitochondrial function (21, 22). Insulin resistance, often a result of disrupted glucose homeostasis in obesity, affects many tissues including the liver and the periphery, predominantly skeletal muscle and adipose tissue. Early disruptions in insulin signaling can exacerbate glucose intolerance thereby contributing to worsening of insulin resistance and potentially leading to prediabetes, T2D, and other metabolic conditions (23-25). The mechanisms driving these processes in BW and WW with and without obesity have not been differentiated. As outlined earlier, regional and total adiposity differ between BW and WW (7, 8) and it is unclear whether increased body weight in BW would synergistically increase disease risk and metabolic dysfunction more than WW of similar body weights. Finally, underlying mechanisms contributing to T2D and insulin resistance, specifically skeletal muscle mitochondrial health, have not been investigated in a setting of obesity in BW.

This study expanded our previous analysis in BW and WW without obesity (3) by including women with obesity to understand the effects of weight and race on hepatic and peripheral insulin sensitivity. Furthermore, we sought to understand if any observed differences may be explained by selected physiological outcomes, including skeletal muscle mitochondrial respiration. Based on our earlier work (3), we hypothesized that the groups would have similar hepatic insulin sensitivity while BW would have lower peripheral insulin sensitivity, which would be related to lower skeletal muscle mitochondrial respiration. Finally, an exploratory analysis of mtDNA haplogroups in the women with obesity highlighted the need for more detailed investigations on the impact of mtDNA on racial differences in insulin sensitivity and skeletal muscle mitochondrial respiration.

Materials and Methods

Participants

BW (n = 32) and WW (n = 32) with [n = 20; body mass index (BMI): 30.0-39.9 kg/m²] and without obesity (n = 44; BMI: 18.0-29.9 kg/m²) were recruited using print advertisements in the Pittsburgh area. Within a weight group, subjects were matched for body weight, BMI, and age. Characteristics of the women without obesity were described previously (3). Inclusion criteria were weight stability over the previous 3 months, fasting blood glucose ≤101 mg/dL, hemoglobin A1c ≤ 5.6%, and sedentary lifestyle (<20 minutes of structured activity, 3x/week) by self-report. Exclusion criteria included significant disease or unstable medical condition, diabetes mellitus, tobacco use, pregnancy or currently lactating, elevated lipid levels (cholesterol >300 mg/dL, triglycerides >350 mg/dL), and use of medications that alter glucose or lipid metabolism. Subject medication use is shown in Supplementary Table S1 (26). The protocol was approved by the University of Pittsburgh Institutional Review Board, and all participants provided written informed consent.

Study Design

Subjects were enrolled, medically screened, and completed a series of tests at the Endocrinology and Metabolism Research Center at the University of Pittsburgh. Body composition was measured by dual-energy x-ray absorptiometry (Lunar iDXA, GE Healthcare, Madison, WI) and maximal aerobic capacity (VO₂ max) by graded exercise test using an incremental modified Astrand protocol and an electronically braked cycle ergometer (Lode, Groningen, Netherlands). Daily physical activity was assessed for 7.2 ± 1.7 days using multisensor activity monitors (Sensewear MF Armband, BodyMedia, Pittsburgh, PA) and did not include the VO₂ max test (27). Following completion of these tests, an overnight, inpatient visit was scheduled with at least 3 days between visits. The study design is presented in Fig. 1.

Figure 1. — Study design. Subjects were admitted to the Clinical Translational Research Center for an overnight visit with a biopsy and hyperinsulinemic-euglycemic clamp procedure the following morning. Standardized dinner: 10 kcal/kg (50% E from carbohydrates, 15% E protein, 35% E fat). *Hyperinsulinemic euglycemic clamp: prime: 210 mg/m²; continuous: 2.0 mg/m²/min.

Abbreviation: E, energy.

Insulin Sensitivity and Metabolic Flexibility

Following the screening visit (25 ± 15 days), participants were admitted to the Clinical Translational Research Center at 1700 hours for an overnight stay. They were instructed to refrain from exercise and strenuous physical activity for 2 days prior to the visit. Subjects received a standardized dinner (10 kcal/kg; 50% energy from carbohydrates, 15% protein, 35% fat) and then fasted until completion of the studies. The following morning, a fasting blood sample was collected, and a primed (210 mg/m²), continuous (2.0 mg/m²/min) infusion of [6,6-²H₂] glucose was initiated for measurement of basal endogenous glucose production (EGP). After 2 hours, a 2-step hyperinsulinemic-euglycemic clamp was initiated with a 2-hour infusion of insulin (Humulin-R) at 15 mU/m²/min followed by 2 hours at 40 mU/m²/min (28). Euglycemia was maintained (89 ± 4 mg/dL) with a variable infusion of 20% dextrose enriched with [6,6-²H₂] glucose (Cambridge Isotope Laboratory). Plasma [6,6-²H₂] glucose enrichments were quantified by gas chromatography/mass spectrometry and used to calculate glucose production and disposal with equations adapted from Steele (29). Plasma insulin concentrations were quantified by ELISA (Millipore Human Insulin Elisa Kit EZHI-14 K; RRID: AB_2800327). Plasma-free fatty acid (FFA) concentrations were quantified by gas chromatography-flame ionization detection as described in the Supplemental Materials and previously (26, 30).

Indirect calorimetry (Parvo Medics’ TrueOne 2400; Metabolic Measurement Systems) was completed 3 times throughout the study morning to determine basal and insulin-stimulated carbohydrate and fat oxidation. Substrate oxidation and metabolic flexibility [MetFlex; clamped steady-state respiratory quotient (RQ) (fasting RQ)] were measured before the insulin infusion and during the last 30 minutes of each clamp step. Nonoxidative glucose disposal represents the difference between glucose oxidation (indirect calorimetry) and total glucose disposal (clamp).

Skeletal Muscle Biopsy and Tissue Analysis

After beginning the glucose tracer but before the insulin infusion began, subjects underwent a percutaneous skeletal muscle biopsy, performed under local anesthesia (lidocaine) using the Bergstrom method (31). The specimen was cleared of blood and visible adipose tissue and then partitioned for high-resolution respirometry as previously described (3).

Mitochondrial Content and High-resolution Respirometry

Mitochondrial content was measured by electron microscopy to determine mitochondrial volume density as described previously (3). For each subject, 18 random micrographs from 3 random longitudinal tissue sections were imaged at X30 000 magnification. An analytical software (Metamorph version 6.3; Molecular Devices Corp) was used to analyze the micrographs using point counting in a blinded fashion. Mitochondrial respiration was completed in permeabilized myofibers as described previously (3). In brief, myofiber bundles (1.7 ± 1.5 mg wet weight) were teased apart using forceps. The bundles were permeabilized with saponin, contraction was inhibited with blebbistatin (25 µM) treatment, and then they were placed into the Oxygraph system (Oroboros, Oxygraphy-2k; Oroboros Instruments). Assays were run at 37 °C in MiR05 buffer supplemented with blebbistatin (25 μM). Glutamate (5 mM), malate (2 mM), succinate (10 mM), and palmitoylcarnitine (25 µM) were added to determine basal (state 4) respiration (32). Maximal coupled (state 3) and uncoupled (state U) respiration were assessed following an adenosine diphosphate (ADP) titration (37.5 µM to 4000 µM) and the addition of p-trifluoromethoxy carbonyl cyanide phenyl hydrazone (2 µM). Skeletal muscle mitochondrial membrane integrity was tested using cytochrome C (10 µM). No effect of cytochrome C was observed on respiration across all subjects (15 ± 2%; data not shown). Steady-state O₂ flux data were analyzed and normalized to fiber bundle dry weight using DatLab software.

Mitochondrial Genetics

In a subset of the women with obesity, DNA was isolated from skeletal muscle tissue as previously described (33). Mitochondrial DNA was amplified using 2 long-range PCR reactions (34). Library preparation was performed using the Ion Xpress^TM Plus Fragment Library kit (ThermoFisher) according to manufacturer instructions. The fragmented DNA was run on the Agilent Tape Station 4200 using the High Sensitivity D1000 assay to verify that the median fragment size was 350 to 450 bp. Sequencing adapters and Ion Xpress barcodes were ligated to fragmented DNA, nick repair was performed, and double SPRI size selection was carried out using Ampure beads. Following template generation and bead enrichment, the sample was loaded on an Ion Torrent PGM 318 V2 chip (ThermoFisher), and a sequencing reaction was run for 850 flows. Reads aligned well with the human mitochondrial reference (88%). The average number of quantity values > 20 bases per sample was 22 181 005 for average depth of coverage of >1000X. Following mitochondrial sequencing, haplogroups were assigned using mtDNA-Server (35). Nuclear genetic ancestry was also measured by a panel of 64 ancestry information genetic markers enriched for European-African differences (36). The University of Pittsburgh Genomics Research Core extracted the DNA and conducted the analysis. A 2-population ancestry model using allele frequencies from Hapmap CEU and YRI was utilized (37).

Calculations

Systemic net carbohydrate and fat oxidation rates were calculated from indirect calorimetry using standard equations (38). Basal EGP was calculated as tracer infusion rate divided by plasma glucose enrichment. The hepatic insulin resistance index (HIRI) was calculated as the product of EGP and plasma insulin concentrations (39). Peripheral insulin sensitivity, driven predominantly by skeletal muscle, is represented by the average glucose disposal (Rd) during steady state [Rd or M per kg of fat-free mass (FFM): mg/FFM/min] divided by plasma insulin (I) concentrations to account for variations in steady-state insulinemia (40).

Statistical Analyses

Unless otherwise indicated, data are presented as mean ± SEM. Differences in subject characteristics were determined using a 2-way ANOVA (race × weight status; R version 4.2.1; R Studio version 2022.07.0). Outcomes derived during the hyperinsulinemic-euglycemic clamp were analyzed by mixed model ANOVA (lmer in lme4 package) with race, weight status (with and without obesity), and clamp step as fixed effects and subjects as random effects. Similarly, respiration was analyzed by mixed model ANOVA with race, weight status (with and without obesity), and respiratory state (4, 3, and U) as fixed effects and subjects as random effects. Age was significantly different between the subjects with and without obesity and, therefore, was controlled for in each statistical model. Least square mean differences (lmertest in lme4 package) were used for post hoc testing where appropriate. Pearson correlation coefficients were used to examine associations between metabolic parameters and insulin sensitivity. Alpha values were set at P ≤ .05.

Results

Subject Characteristics

As shown in Table 1, the subjects with obesity were, on average, 10 years older than the subjects without obesity. Thus, age was included in subsequent models to control for this difference. Per the experimental design, subjects with obesity had greater BMI, body weight, FFM, fat mass (absolute and relative), trunk FFM, and trunk fat mass. BW had greater FFM and lower percent fat mass than WW, regardless of obesity. With regard to free-living physical activity, women with obesity had 66 ± 33 fewer minutes of moderate activity throughout the 7.2 ± 1.7 days of assessment and 33% fewer steps than subjects without obesity. Cardiorespiratory fitness (absolute VO₂ max, with FFM as a covariate) was significantly lower in BW, with no differences between subjects with and without obesity. Fasting glucose and insulin were greater in subjects with obesity.

Table 1.

Subject characteristics

	With obesity		Without obesity		P-value^a
	BW (n = 10)	WW (n = 10)	BW (n = 22)	WW (n = 22)
Age (years)	34 ± 3	34 ± 3	23 ± 1	24 ± 1	.678*
Body composition
BMI (kg/m²)	35.1 ± 1.0	33.3 ± 0.7	23.2 ± 0.6	23.3 ± 0.7	.263*
Body weight (kg)	95.9 ± 4.2	91.4 ± 1.6	62.0 ± 2.0	63.0 ± 1.9	.270*
FFM (kg)	52.9 ± 2.0	48.7 ± 1.9	44.8 ± 1.2	42.4 ± 1.1	.484*^,╪
Fat mass (kg)	42.7 ± 2.4	42.4 ± 1.5	17.2 ± 1.2	20.5 ± 1.4	.305*
Fat mass (%)	44 ± 1	46 ± 2	27 ± 1	32 ± 1	.463*^,╪
Trunk FFM (kg)	23.2 ± 0.9	22.2 ± 0.8	19.8 ± 1.2	19.7 ± 1.1	.516*
Trunk fat mass (kg)	20.2 ± 1.5	21.2 ± 1.0	6.9 ± 0.6	9.1 ± 0.7	.579*^,╪
Physical activity and fitness
Moderate activity (min/day)^b	34 ± 9	27 ± 9	100 ± 10	87 ± 12	.832*
Vigorous activity (min/day)^b	1 ± 1	12 ± 6	26 ± 10	27 ± 9	.632
Steps/day^b	6475 ± 726	6057 ± 534	9926 ± 962	8721 ± 736	.687*
VO₂ max (L/min)	1.94 ± 0.12	2.21 ± 0.20	2.02 ± 0.09	2.32 ± 0.10	.849^╪
VO₂ max (mL/FFM/min)	37.1 ± 2.6	44.9 ± 2.8	45.1 ± 1.5	54.4 ± 1.7	.639*^,╪
Fasting plasma biochemistries
Glucose (mg/dL)	88 ± 2	92 ± 1	86 ± 2	84 ± 1	.116*
Insulin (µU/mL)^b	12.7 ± 2.4	12.9 ± 2.1	3.9 ± 0.6	3.6 ± 0.4	.911*

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Data are presented as mean ± SEM.

Abbreviations: BMI, body mass index; BW, Black women; FFM, fat-free mass; VO₂ max, maximal aerobic capacity; WW, White women.

^a P-value represents the interaction between race and obesity (2-way ANOVA) with age as a covariate (excluding the test for differences in age) and FFM as a covariate for VO₂max only. Significant effects (P < .05) of weight are represented with an asterisk (*) while main effect of race is represented with a hatched bar (^╪).

^bSample sizes are as noted except for n = 9 in BW with obesity for moderate activity, vigorous activity, steps/day, and insulin concentrations.

Insulin Sensitivity

Peripheral insulin sensitivity (relative to insulin: Fig. 2A) was significantly lower in subjects with obesity (average 67% lower across both steady states; P < .001) and tended to be lower in BW (average 21%; P = .062). BW tended to have 14% greater clamped insulin concentrations (Table 2), suggesting that even with a trend toward greater levels of circulating insulin (P = .066), BW were unable to achieve similar levels of glucose disposal. The effects of race were abrogated when Rd was analyzed without corrections for insulin concentrations (Table 2).

Figure 2. — Tissue-specific insulin sensitivity. Data are presented as mean ± SEM; BW are presented with filled bars and WW with unfilled bars. Women with obesity (+; n = 10, unless otherwise noted) are shown with a circle [OB(+); ◯] and women without obesity (−; n = 22) with a triangle [OB(−); ▵]. Mixed models were fitted to the data using the R package LMER with age as a covariate. Race, weight, and time were fixed effects, and the participants were included as random effects. Interaction P-values refer to the race × weight effects. (A) Peripheral insulin sensitivity relative to plasma insulin concentrations (µU/mL); n = 9 BW with obesity. (B) Relative EPG to FFM; n = 7 BW with obesity, step 2 and n = 21 WW without obesity, step 2. (C) Hepatic insulin resistance index (relative EGP multiplied by plasma insulin concentrations, µU/mL); n = 7 BW with obesity, step 2 and n = 21 WW without obesity, step 2. (D) Percentage suppression of EGP from basal; n = 7 BW with obesity, step 2 and n = 21 WW without obesity, step 2.

Abbreviations: BW, Black women; EPG, endogenous glucose production; FFM, fat-free mass; WW, White women.

Table 2.

Hyperinsulinemic-euglycemic clamp and substrate oxidation

	Steady state 1				Steady state 2
	With obesity		Without obesity		With obesity		Without obesity		P-value^a
	BW (n = 10)	WW (n = 10)	BW (n = 22)	WW (n = 22)	BW (n = 10)	WW (n = 10)	BW (n = 22)	WW (n = 22)	Race	Obesity	State
Glucose metabolism
Glucose (mg/dL)	94 ± 2	92 ± 1	90 ± 1	88 ± 2	83 ± 3	91 ± 1	86 ± 1	88 ± 1	.087	.023	<.001
Insulin (µU/mL)^b	43.7 ± 6.2	41.9 ± 4.0	16.4 ± 0.8	14.4 ± 0.8	103.7 ± 8.8	91.2 ± 10.4	44.2 ± 4.2	34.4 ± 2.5	.066	<.001	<.001
Rd (M)^b	4.0 ± 0.3	4.4 ± 0.4	4.1 ± 0.2	5.0 ± 0.2	7.5 ± 0.7	7.7 ± 1.2	9.5 ± 0.5	10.0 ± 0.8	.470	.008	<.001
GluInf (mL/min)	44 ± 6	38 ± 5	45 ± 3	53 ± 4	145 ± 19	112 ± 15	143 ± 9	148 ± 10	.087	.023	<.001
Substrate oxidation
MetFlex (ΔRQ)^b	0.03 ± 0.01	0.03 ± 0.01	0.07 ± 0.01	0.07 ± 0.01	0.06 ± 0.02	0.06 ± 0.02	0.13 ± 0.01	0.12 ± 0.01	.954	.150	<.001
GluOx (mg/min)^b	116 ± 7	112 ± 12	102 ± 8	109 ± 7	142 ± 14	142 ± 15	148 ± 13	145 ± 8	.990	.824	<.001
NOGD (mg/min)^b	92 ± 14	95 ± 11	83 ± 10	102 ± 13	262 ± 37	223 ± 39	275 ± 23	282 ± 35	.830	.245	<.001
FatOx (mg/min)^b	48 ± 6	57 ± 8	44 ± 4	49 ± 4	41 ± 7	42 ± 8	33 ± 6	36 ± 5	.402	.303	<.001

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Data are presented as mean ± SEM.

Abbreviations: BW, Black women; FatOx, fat oxidation; GluInf, glucose infusion rate; GluOx, glucose oxidation; M, glucose disposal (mg/fat-free mass/min); MetFlex, metabolic flexibility (difference between basal RQ and step 1 or 2); NOGD, nonoxidative glucose disposal; Rd, glucose disposal; RQ, respiratory quotient; WW, White women.

^a P-value represents main effects of race, obesity, or clamp state (steady state 1: 15mU/m²/min; steady state 2: 40mU/m²/min) from a mixed model with age as a covariate.

^bn = 9 BW with obesity for insulin concentrations (all timepoints), Rd (steady state 2); n = 21 BW and WW without obesity for GluOx, NOGD, and FatOx (steady state 1); n = 20 BW without obesity for FatOx (steady state 2); n = 21 WW without obesity for FatOx (steady state 2); n = 19 for BW and WW without obesity for MetFlex (steady state 1); n = 20 BW without obesity for MetFlex (steady state 2); n = 19 WW without obesity for MetFlex (steady state 2).

Although no significant interaction between race and weight was observed (M/I: P = .132), BW without obesity had 37% lower peripheral insulin sensitivity compared to WW (P = .002 with Tukey correction). In subjects with obesity, no differences in peripheral insulin sensitivity were detected between BW and WW (P = .828 with Tukey correction), suggesting obesity and Black race did not synergistically reduce peripheral insulin sensitivity. Put simply, women with obesity, regardless of race, had similar defects in peripheral insulin sensitivity, and women without obesity appeared to drive the observed race differences in peripheral insulin sensitivity in this study. Across all subjects, nonoxidative glucose disposal increased 207% from basal to step 2 (step 1 to step 2: +187%, P < 0001) but was not different by obesity or race (Table 2).

No differences in basal EGP were observed between BW and WW (data not shown). As shown in Fig. 2B, subjects with obesity had significantly greater clamped EGP (P < .0001), and BW had lower EGP (Fig. 2B, P = .005; step 1: 14% and step 2: 78%). This racial difference persisted when EGP was adjusted for plasma insulin levels (Fig. 2C, P = .024; step 1: 11% and step 2: 35%) and the significant effect of obesity was maintained; subjects without obesity had 75% lower HIRI (12.6 ± 1.3 mg/FFM/min • µU/mL) compared to those with obesity (50.7 ± 6.6 mg/FFM/min • µU/mL; P < .001; Fig. 2C). Despite a lack of interaction between race, obesity, and clamp step, upon consideration of early clamped timepoints (30 and 60 minutes, not shown), WW with obesity did not reduce insulin-adjusted EGP to the same degree as the remaining groups: △30 to 240 minutes: 70% BW with obesity, 36% WW with obesity, 73% BW without obesity, and 78% WW without obesity. EGP suppression at steps 1 and 2 tended to be greater in BW (P = .092) and was 8% to 12% lower in subjects with obesity vs those without obesity (Fig. 2D). Across time, EGP suppression increased in all subjects (△basal to 240 minutes: 91 ± 12%, not shown) and total FFA concentrations dropped significantly [P < .001, Supplementary Fig. S1A (26)] which was mirrored by significant suppression of FFA, with no effects of obesity or race [Supplementary Fig. S1B (26)].

Substrate Oxidation and Metabolic Flexibility

Fasting RQ was 5% higher in subjects with obesity (P = .001, data not shown) but did not differ at step 1, step 2, or between BW and WW at any timepoint. RQ did significantly increase throughout the clamp (7%; P < .001), with all groups responding similarly. MetFlex, which reflects the ability to shift substrate preference for oxidation (ie, an increase in glucose oxidation and a decrease in fat oxidation), tended to be blunted in subjects with obesity, although this difference was not significant (P = .150, Table 2).

Skeletal Muscle Mitochondrial Content and Respiration

Mitochondrial content is shown in Fig. 3A. No interaction of race and weight was observed on content, yet the main effect of race was significant (P = .013) demonstrating BW had lower mitochondrial content than WW. This observation may have been driven primarily by women without obesity (BW: 3.7 ± 0.3% vs WW: 4.8 ± 0.4%; within weight group t-test: P = .013) as BW and WW with obesity had similar mitochondrial content (BW: 4.5 ± 0.3% vs WW: 4.6 ± 0.3%; P = .766). High-resolution respirometry of permeabilized myofibers demonstrated significant effects of race and obesity on oxygen flux (Fig. 3B). Mixed model analysis revealed a significant interaction between obesity and respiratory state (P < .001); subjects with obesity had 71% lower respiration during maximal coupled respiration (state 3; P < .001) and 38% lower maximal uncoupled respiration (state U; P < .001) when compared to subjects without obesity. No differences were detected in basal (state 4; P = .612) respiration. Similarly, a significant interaction was observed between race and respiratory state (P < .001), with BW having lower respiration than WW in state 3 (24%, P < .001) and state U (22%; P < .001) but not in state 4. Titration of ADP (37.5-4000 µM, data not shown) revealed a significant main effect of obesity (P < .001; with obesity: 54 ± 70 µm; without obesity: 266 ± 79 µM) and race (P = .029; BW: 182 ± 128 µM vs WW: 216 ± 128 µM) on the ADP concentration required to meet half maximal oxygen flux. When added to each model as a covariate, mitochondrial content did not impact any of the respiration results discussed earlier. Basal, maximal coupled, and maximal uncoupled respiration were significant predictors of VO₂ max when controlling for race, obesity, and age (data not shown, all P < .05).

Figure 3. — Skeletal muscle mitochondrial content and respiration. Data are presented as mean ± SEM; BW are presented with filled bars and WW with unfilled bars. Women with obesity (+) are shown with a circle [OB(+); ◯] and women with normal weight (−) with a triangle [OB(−); ▵]. With age as a covariate, (A) mitochondrial content was analyzed by two-way ANOVA and (B) respiration was analyzed by mixed models (R package LMER) with race, weight, and state as fixed effects and the participants as random effects. P-values above the bars represent post hoc test (Tukey correction) for comparisons between subjects with obesity and normal weight within a respiratory state. Due to sample quality or technical errors, sample sizes are as follows: mitochondrial content: n = 8 BW and WW with obesity; n = 21 BW without obesity; n = 20 WW without obesity; state 4 and 3: n = 10 BW with obesity; n = 6 WW with obesity; n = 21 BW without obesity, n = 20 WW without obesity; state U: n = 8 BW with obesity; n = 5 WW with obesity; n = 21 BW without obesity, n = 17 WW without obesity.

Abbreviations: BW, Black women; OB, obesity; WW, White women.

Correlates of Insulin Sensitivity

Our previous work in women without obesity demonstrated that skeletal muscle respiration was the only correlate of peripheral insulin sensitivity (3). In a group of women with a wide range of body weight, we found that hepatic insulin resistance was significantly positively related to BMI and fat mass, while greater peripheral insulin sensitivity was related to lower BMI and percentage fat mass (Table 3). Moderate exercise levels, but not vigorous, were significantly associated with HIRI (negative) and peripheral insulin sensitivity (positive). Total daily steps were inversely related to HIRI, but cardiorespiratory fitness was not related to insulin sensitivity. Interestingly, MetFlex at steps 1 and 2 strongly correlated with both HIRI and peripheral insulin sensitivity. In line with our previous findings, state 4 and U skeletal muscle respiration remained strong correlates of peripheral insulin sensitivity, and when including women with obesity, an inverse relationship was also observed with HIRI. These relationships remained significant when mitochondrial content was controlled for (P < .01). Finally, given that self-reported race in the US population corresponds significantly to mtDNA haplogroup (41), we conducted an exploratory analysis of the respiratory differences in BW and WW based upon haplogroup. The analysis revealed lower skeletal muscle mitochondrial respiration in individuals with African L haplogroup, and 1 Black woman (only 8% European admixture, compared to an average 33%) with a haplogroup of A2, which originates outside of Africa, had respiration values similar to WW and 73 ± 29% (average across respiratory states) greater respiration than the remaining BW. Exclusion of this participant did not alter the insulin sensitivity results (not shown).

Table 3.

Relationships between metabolic characteristics and insulin sensitivity

	Hepatic insulin resistance (mg/FFM/min × I)		Peripheral insulin sensitivity (mg/FFM/min/I)
	r	P	r	P
BMI (kg/m²)	0.715	<0.001	−0.496	<.001
Fat mass (%)	0.611	<0.001	−0.351	.006
Moderate activity (min/day)	−0.422	<0.001	0.267	.041
Vigorous activity (min/day)	−0.182	0.158	0.053	.691
Steps/day	−0.297	0.019	0.175	.186
VO₂ max (L/min)	−0.023	0.858	0.100	.448
Step 1 MetFlex (ΔRQ)	−0.443	<0.001	0.573	<.001
Step 2 MetFlex (ΔRQ)	−0.565	<0.001	0.519	<.001
State 4 Respiration	0.144	0.289	0.131	.349
State 3 Respiration	−0.568	<0.001	0.581	<.001
State U Respiration	−0.394	0.006	0.469	<.001

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Pearson correlations between metabolic outcomes and hepatic insulin resistance (mg/FFM/min•µU/mL; step 1) and peripheral insulin sensitivity (mg/FFM/min/µU/mL; step 2). MetFlex: calculated as the difference in clamped (Step 1 or Step 2) steady state RQ and fasting RQ. State 4: glutamate (5 mM), malate (2 mM), succinate (10 mM), and palmitoylcarnitine (25 µM). State 3: adenosine diphosphate titration (37.5 µM to 4000 µM). State U: p-trifluoromethoxy carbonyl cyanide phenyl hydrazone (2 µM).

Abbreviations: BMI, body mass index; FFM, fat-free mass; RQ, respiratory quotient; VO_2, maximal aerobic capacity.

Discussion

Compared to WW, BW are at greater risk of developing T2D and insulin resistance (7, 42). While the mechanisms of these differences are not fully known, multiple factors have been investigated, including differences in socioeconomic status (43), genetics/epigenetics (21, 44-46) [potentially including mitochondrial genetics (19)], beta cell response to a glucose load (45, 47, 48), hepatic insulin extraction (45, 46), adipose tissue dynamics (49), and skeletal muscle mitochondrial function (3, 4, 11). Despite these important investigations, a paucity of evidence is available to explain the mechanisms that contribute to the increased risk of insulin resistance and T2D in BW or whether disease risk is disproportionately increased in BW with obesity. Our group (3, 11) has demonstrated that lower skeletal muscle mitochondrial respiration was associated with insulin resistance in BW without obesity. Few studies have investigated whether these observations are extended into a setting of obesity, which is often characterized by existing skeletal muscle and hepatic insulin resistance as well as decreased mitochondrial capacity (22). Thus, the goal of this study was to expand our previous findings in WW and BW without obesity (3) into a setting of obesity to determine if disproportionately greater peripheral insulin resistance in BW may be explained by defects in metabolic factors. Consistent with our previous findings, a strong relationship was observed between peripheral insulin sensitivity and skeletal muscle mitochondrial respiration in women with a wide range of body weights. Additionally, we show a strong inverse association between HIRI and skeletal muscle mitochondrial respiration.

Peripheral Insulin Sensitivity Tended to be Lower in BW Compared to WW

Previous work from our group (3) and others (47, 48, 50) in healthy adult and adolescent males and females have shown peripheral insulin sensitivity, measured using a hyperinsulinemic-euglycemic clamp, was lower in healthy Black individuals compared to non-Hispanic White individuals. One goal of the study was to extend these findings into a setting of obesity to understand the interaction between race and weight on glucose disposal. Some studies have reported no differences in insulin-stimulated glucose disposal during a hyperinsulinemic-euglycemic clamp between Black and non-Hispanic White individuals with overweight or obesity (47, 50-54), while others, using similar methods, have found lower peripheral insulin sensitivity in BW compared to WW (55, 56). A study that included male and female participants across a range of BMI (17-43 kg/m²) reported that the Black participants had lower peripheral insulin sensitivity than the White participants as measured by a hyperinsulinemic-euglycemic clamp (4), which may be due to differences in lean mass and body fat distribution (57). However, it was unclear whether differences existed across BMI setpoints for normal weight, overweight, or obesity. In our study, the effects of race on peripheral insulin sensitivity were blunted in subjects with obesity, independent of insulin concentrations, cardiorespiratory fitness, and age.

The heterogeneity of results in the literature may be explained by multiple factors. First, it is possible that high rates of insulin infusion during the hyperinsulinemic-euglycemic clamp may overcome racial differences. In studies that failed to find race differences, insulin infusion rates went up to 200 mU/m²/min (47, 50-54), while the 2 studies that have reported differences used ∼35 (55) and 80 mU/m²/min (56). The current study employed modest insulin doses (15 and 40 mU/m²/min). Furthermore, the insulin concentrations observed during step 2 (high insulin) of the clamp in the current study were similar to insulin levels reported following a mixed meal tolerance test in WW and BW with obesity (58). Thus, factors beyond methodological differences in the clamp procedure may explain the variability in the literature. For example, using intravenous glucose tolerance tests (IVGTT), reports in BW and WW with obesity have shown significant racial differences in insulin sensitivity (7, 12, 59, 60). However, the use of IVGTTs for quantifying insulin sensitivity has recently been challenged (50, 51, 61) due to the reliance on concentrations rather than the kinetics of plasma glucose and insulin. Black individuals have higher baseline plasma insulin concentrations compared to White people matched for age, weight, and even skeletal muscle insulin sensitivity (21, 52). This race difference ultimately leads to an underestimation of insulin sensitivity in Black people when IVGTTs are used (50, 51, 62). More studies are needed to fully elucidate the mechanisms of racial differences in glucose disposal in settings of obesity.

Hepatic Insulin Sensitivity was Greater in BW Compared to WW

While limited studies have applied hyperinsulinemic-euglycemic clamps to assess racial differences (3, 4, 47, 51, 52, 57), even fewer have included measures of hepatic insulin sensitivity using stable isotope tracers (3, 47, 51, 52). To our knowledge, this is the first study to measure hepatic insulin sensitivity using the gold-standard insulin clamp method in BW and WW with and without obesity. In line with previous studies (51, 52), BW had greater hepatic insulin sensitivity than WW, despite higher circulating insulin. In a similar cohort of men and women with obesity, hepatic insulin sensitivity was approximately 50% greater in Black subjects than the non-Hispanic White subjects (50 mU/m²/min) (51). In contrast to the current results, our previous findings in women without obesity (3) demonstrated no differences in hepatic insulin sensitivity between BW and WW. Together, these observations suggest that BW may be partially protected from hepatic insulin resistance that is observed in WW, particularly in settings of obesity. One explanation may be the ethnic differences in ectopic lipid deposition (52, 57); BW tend to accumulate less hepatic and visceral fat than WW (8), which may predispose WW to liver lipid accumulation and impaired hepatic insulin sensitivity (20). Alternatively, Black individuals with and without obesity have consistently been characterized as having lower hepatic insulin clearance (21, 45, 51, 58), which supports increased clamped insulin concentrations and differences in hepatic insulin sensitivity between the ethnic groups.

We observed a strong relationship between HIRI and skeletal muscle respiration across all subjects, where greater maximal coupled and uncoupled respiration was associated with greater hepatic insulin sensitivity. The relationship between skeletal muscle function and hepatic insulin sensitivity is not well defined in the existing literature. In subjects with low liver fat, poor muscle function and dysregulated hepatic substrate handling often occur in tandem (63), and this observation is exacerbated in subjects with obesity and high liver fat (22, 64-66). It is possible that subjects with greater skeletal muscle function, as evidenced by greater mitochondrial respiration, also exhibit enhanced systemic substrate handling, thereby reducing the burden on the liver and enhancing hepatic insulin response. Indeed, we observed strong negative relationships between metabolic flexibility, a marker systemic substrate switching, and HIRI, which supports the theory that greater muscle function and fuel switching are associated with greater hepatic insulin response. However, the mechanisms driving altered skeletal muscle respiration and insulin sensitivity are debated (67, 68), and our analysis was not designed to determine the directionality of these relationships. Our understanding of the progression of skeletal muscle dysfunction as it relates to mitochondrial respiration and insulin resistance and the interaction with liver function are not well defined. Finally, it remains to be tested how interorgan communication between skeletal muscle and the liver may become disrupted in settings of obesity and chronic disease.

Correlates of Insulin Sensitivity: Skeletal Muscle Mitochondrial Function is Lower in BW

Excess lipid accumulation, particularly ectopic lipid, is associated with insulin resistance, which was confirmed in the current study. Percent fat mass and BMI were positively related to HIRI and negatively related to peripheral insulin sensitivity. Paradoxically, BW tend to have lower abdominal fat mass despite higher peripheral insulin resistance (7), and in line with this, we observed lower percentage fat mass and trunk fat in BW when compared to WW. Lower trunk fat correlates with lower liver fat (69), which may grant some protection against hepatic insulin resistance in BW. With regard to peripheral insulin sensitivity, racial differences in adiposity do not explain the tendency for BW to have lower glucose disposal. These differences may be better explained by factors more closely related to skeletal muscle. For example, BW had lower cardiorespiratory fitness levels than WW, despite similar levels of free-living physical activity as measured through moderate and vigorous physical activity and steps per day. Differences in absolute VO₂ max in Black participants have been reported before (70) and when controlled for in the current study did not explain a significant portion of the variability in insulin sensitivity. In line with our previous report, these results suggest that maximal fitness levels are not the main contributing factor to differences in insulin sensitivity. Similarly, while we found a significant effect of race on mitochondrial content, it did not account for differences in insulin sensitivity. Our group (3, 11) and others (4) have reported significant relationships between insulin sensitivity and skeletal muscle mitochondrial respiration, and the current results agree with these reports. Race and obesity significantly impacted skeletal muscle respiration; WW and subjects without obesity had higher respiration. The observed effect of race is in line with our previous findings in women without obesity (3). However, others have failed to report similar race differences (4). Fisher et al (4) examined sex and race differences and found no race effects on state 3 or 4 respiration. Differences between Fisher et al and the current study may have contributed to opposing observations. The current investigation only included women and examined those with and without obesity separately, whereas the earlier study (4) combined males and females across a range of body weight (BMI 17-43 kg/m²). Our results support a role for lower skeletal muscle mitochondrial function in contributing to race differences in both hepatic and peripheral insulin sensitivity. However, the mechanisms contributing to mitochondrial dysfunction in BW and WW are poorly understood.

Mitochondrial Genetics may Explain Racial Differences in Respiration and Insulin Sensitivity

A comprehensive understanding of the mechanisms driving racial differences in mitochondrial function and insulin sensitivity is lacking. One proposed mechanism contributing to these metabolic differences is mtDNA haplogroup. An analysis of mitochondrial haplogroups from the women with obesity in the current study revealed that 1 Black woman without an African haplogroup had respiratory rates similar to WW and 73 ± 29% greater than the remaining BW who had L-type haplogroups. Considering the nuclear genetic ancestry and mtDNA haplogroup, these data suggest that discordance between nuclear and mtDNA genetic ancestry may impact skeletal muscle respiration. Our data are in line with previous studies that demonstrated specific haplogroups, particularly those of African origin (L-type), were associated with lower mitochondrial respiration compared to European haplogroups (eg, H-type) (14-16). While these data are observational, they support future investigations into the underlying genetic makeup that may predispose BW to poor skeletal muscle mitochondrial function and lead to peripheral and, potentially, hepatic insulin resistance.

Limitations

The current study included only women who, until recently (71), were often excluded from study populations. Furthermore, the risk of diabetes is greater in BW than in Black men (12.2% vs 4.5%) (42), which supports investigations of mechanisms contributing to diabetes risk in BW. However, the study population does limit the generalizability of our results, especially considering the sex-specific differences that have been previously reported (4). Second, our correlation analysis does not imply causality, and intricate studies are needed to determine if skeletal muscle mitochondrial dysfunction directly impacts insulin sensitivity. Third, our groups differed by ∼10 years of age. To control for these effects, we included age within our statistical analysis but cannot rule out the potential effects of this difference. The sample size was limited, particularly women with obesity, and may have contributed to small effect sizes. Additionally, measurements of visceral and liver fat were not completed. These outcomes may have provided mechanistic insight into racial differences in HIRI. Finally, our mtDNA analysis was exploratory in nature and only included the women with obesity. Therefore, we cannot determine if any of the BW without obesity had haplogroups originating outside of Africa, which may have impacted our results.

Conclusions

As an extension of our previous study (3), this is the first analysis comparing BW and WW with and without obesity. Consistent with that study, BW had lower peripheral insulin sensitivity, although the effect was more pronounced in women without obesity. Paradoxically, hepatic insulin sensitivity was significantly greater in BW compared to WW, as evidenced by lower clamped EGP and HIRI and higher EGP suppression, particularly in BW with obesity. These results highlight racial differences across a range of body weights whereby BW have poor peripheral insulin sensitivity but greater hepatic insulin sensitivity compared to WW. Despite these differences, both peripheral insulin sensitivity and hepatic insulin resistance were related to skeletal muscle mitochondrial respiration, independent of mitochondrial content, across all subjects. Finally, mitochondrial genetics may be an important avenue to explore the underlying mechanisms driving these differences, especially in settings of exercise interventions.

Acknowledgments

The authors acknowledge the University of Pittsburgh Endocrinology and Metabolism Research Center staff for their support of sample collection and assistance in clinical research management. They are indebted to the study volunteers for their participation, time, and energy.

Contributor Information

Justine M Mucinski, AdventHealth Orlando, Translational Research Institute, Orlando, FL 32804, USA.

Giovanna Distefano, AdventHealth Orlando, Translational Research Institute, Orlando, FL 32804, USA.

John Dubé, School of Arts, Science, and Business, Chatham University, Pittsburgh, PA 15232, USA.

Frederico G S Toledo, Division of Endocrinology and Metabolism, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.

Paul M Coen, AdventHealth Orlando, Translational Research Institute, Orlando, FL 32804, USA.

Bret H Goodpaster, AdventHealth Orlando, Translational Research Institute, Orlando, FL 32804, USA.

James P DeLany, AdventHealth Orlando, Translational Research Institute, Orlando, FL 32804, USA.

Funding

This study was supported by National Institutes of Health grants R56DK091462-04A1 and R01 DK091462 (to J.P.D.).

Disclosures

The authors have nothing to disclose.

Data Availability

Data are available from the corresponding author upon reasonable request.

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Data Citations

Mucinski JM, Distefano G, Dubé J, et al. Supplemental files “Insulin Sensitivity and Skeletal Muscle Mitochondrial Respiration in Black and White Women With Obesity”. Figshare. 2024. 10.6084/m9.figshare.26947636.v1 [DOI] [PMC free article] [PubMed]

Data Availability Statement

Data are available from the corresponding author upon reasonable request.

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PERMALINK

Insulin Sensitivity and Skeletal Muscle Mitochondrial Respiration in Black and White Women With Obesity

Justine M Mucinski

Giovanna Distefano

John Dubé

Frederico G S Toledo

Paul M Coen

Bret H Goodpaster

James P DeLany

Abstract

Objectives

Methods

Results

Conclusion

Materials and Methods

Participants

Study Design

Figure 1.

Insulin Sensitivity and Metabolic Flexibility

Skeletal Muscle Biopsy and Tissue Analysis

Mitochondrial Content and High-resolution Respirometry

Mitochondrial Genetics

Calculations

Statistical Analyses

Results

Subject Characteristics

Table 1.

Insulin Sensitivity

Figure 2.

Table 2.

Substrate Oxidation and Metabolic Flexibility

Skeletal Muscle Mitochondrial Content and Respiration

Figure 3.

Correlates of Insulin Sensitivity

Table 3.

Discussion

Peripheral Insulin Sensitivity Tended to be Lower in BW Compared to WW

Hepatic Insulin Sensitivity was Greater in BW Compared to WW

Correlates of Insulin Sensitivity: Skeletal Muscle Mitochondrial Function is Lower in BW

Mitochondrial Genetics may Explain Racial Differences in Respiration and Insulin Sensitivity

Limitations

Conclusions

Acknowledgments

Contributor Information

Funding

Disclosures

Data Availability

References

Associated Data

Data Citations

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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