Purpose

To identify determinants of quadriceps weakness among persons with end-stage knee osteoarthritis (OA).

Methods

One-hundred twenty-three individuals (mean age 64.9 ± 8.5 yr) with Kellgren/Lawrence grade IV knee OA participated. Quadriceps strength (MVIC) and volitional muscle activation (CAR) were measured using a burst superimposition test. Muscle composition (lean muscle cross-sectional area (LMCSA) and fat CSA (FCSA)) were quantified using magnetic resonance imaging. Specific strength (MVIC/LMCSA) was computed. Interlimb differences were analyzed using paired-sample t-tests. Regression analysis was applied to identify determinants of MVIC. An alpha level of 0.05 was adopted.

Results

The OA limb was significantly weaker, had lower CAR, and had smaller LMCSA than the contralateral limb. CAR explained 17% of the variance in the contralateral limb's MVIC compared with 40% in the OA limb. LMCSA explained 41% of the variance in the contralateral limb's MVIC compared with 27% in the OA limb.

Conclusion

Both reduced CAR and LMCSA contribute to muscle weakness in persons with knee OA. Similar to healthy elders, the best predictor of strength in the contralateral, nondiseased limb was largely determined by LMCSA, whereas CAR was found to be the primary determinant of strength in the OA limb. Deficits in CAR may undermine the effectiveness of volitional strengthening programs in targeting quadriceps weakness in the OA population.

Muscle-actuated simulations of pathological gait have the capacity to identify muscle impairments and compensatory strategies, but the lack of subject-specific solutions prevents the prescription of personalized therapies. Conversely, electromyographic-driven models are limited to muscles for which data are available but can capture the true neural drive initiated by an individual subject. In order to improve subject-specificity and enforce physiological constraints on muscle activity, we propose a hybrid strategy for the optimization of subject-specific muscle patterns that involves forward dynamic simulation of whole body movement coupled with electromyographic-driven models of muscle subsets. In this paper we apply the hybrid approach to an example of post-stroke gait and demonstrate its unique ability to account for the unusual muscle activation patterns and muscle properties in patients with neuromuscular impairments.

The real-time estimation of muscle forces could be a very valuable tool for rehabilitation. By seeing how much muscle force is being produced during rehabilitation, therapists know whether they are working within safe limits in their therapies and patients know if they are producing enough force to expect improvement. This is especially true for rehabilitation of Achilles tendon ruptures where, out of fear of overloading and causing a re-rupture, minimal therapy is typically done for eight weeks post-surgery despite animal studies that show that low-level loading is beneficial. To address this need, we have developed a biomechanical model that allows for the real-time estimation of forces in the triceps surae muscle and Achilles tendon. Forces are estimated using a Hill-type muscle model. To account for differences in neuromuscular control of each subject, the model used EMGs as input. To make this clinically useful, joint angles were measured using electrogoniometers. A dynamometer was used to measure joint moments during the model calibration stage, but was not required during real-time studies. The model accounts for the force-length and force-velocity properties of muscles, and other parameters such as tendon slack length and optimal fiber length. Additional parameters, such as pennation angle and moment arm of each muscle in the model, vary as functions of joint angle. In this paper, the model is presented and it application is demonstrated in two subjects: one with a healthy Achilles tendon and a second six months post Achilles tendon rupture and repair.

To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 = × 10−50) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 × 10−15). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 × 10−7) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 × 10−57) and GCK (rs4607517, P = 1.0 × 10−25) loci.

Muscle atrophy is one of many factors contributing to post-stroke hemiparetic weakness. Since muscle force is a function of muscle size, the amount of muscle atrophy an individual muscle undergoes has implications for its overall force-generating capability post-stroke. In this study, post-stroke atrophy was determined bilaterally in fifteen leg muscles with volumes quantified using magnetic resonance imaging (MRI). All muscle volumes were adjusted to exclude non-contractile tissue content, and muscle atrophy was quantified by comparing the volumes between paretic and non-paretic sides. Non-contractile tissue or intramuscular fat was calculated by determining the amount of tissue excluded from the muscle volume measurement. With the exception of the gracilis, all individual paretic muscles examined had smaller volumes in the non-paretic side. The average decrease in volume for these paretic muscles was 23%. The gracilis volume, on the other hand, was approximately 11% larger on the paretic side. The amount of non-contractile tissue was higher in all paretic muscles except the gracilis, where no difference was observed between sides. To compensate for paretic plantar flexor weakness, one idea might be that use of the paretic gracilis actually causes the muscle to increase in size and not develop intramuscular fat. By eliminating non-contractile tissue from our volume calculations, we have presented volume data that more appropriately represents force-generating muscle tissue. Non-uniform muscle atrophy was observed across muscles and may provide important clues when assessing the effect of muscle atrophy on post-stroke gait.

Obesity is a growing problem in the United States and throughout the world. It is a risk factor for many chronic diseases. The BMI has been used to assess body fat for almost 200 years. BMI is known to be of limited accuracy, and is different for males and females with similar %body adiposity. Here, we define an alternative parameter, the body adiposity index (BAI = ((hip circumference)/((height)1.5) − 18)). The BAI can be used to reflect %body fat for adult men and women of differing ethnicities without numerical correction. We used a population study, the “BetaGene” study, to develop the new index of body adiposity. %Body fat, as measured by the dual-energy X-ray absorptiometry (DXA), was used as a “gold standard” for validation. Hip circumference (R = 0.602) and height (R = −0.524) are strongly correlated with %body fat and therefore chosen as principal anthropometric measures on which we base BAI. The BAI measure was validated in the “Triglyceride and Cardiovascular Risk in African-Americans (TARA)” study of African Americans. Correlation between DXA-derived %adiposity and the BAI was R = 0.85 for TARA with a concordance of C_b = 0.95. BAI can be measured without weighing, which may render it useful in settings where measuring accurate body weight is problematic. In summary, we have defined a new parameter, the BAI, which can be calculated from hip circumference and height only. It can be used in the clinical setting even in remote locations with very limited access to reliable scales. The BAI estimates %adiposity directly.

Identifying the genetic variants that increase the risk of type 2 diabetes (T2D) in humans has been a formidable challenge. Adopting a genome-wide association strategy, we genotyped 1161 Finnish T2D cases and 1174 Finnish normal glucose-tolerant (NGT) controls with >315,000 single-nucleotide polymorphisms (SNPs) and imputed genotypes for an additional >2 million autosomal SNPs. We carried out association analysis with these SNPs to identify genetic variants that predispose to T2D, compared our T2D association results with the results of two similar studies, and genotyped 80 SNPs in an additional 1215 Finnish T2D cases and 1258 Finnish NGT controls. We identify T2D-associated variants in an intergenic region of chromosome 11p12, contribute to the identification of T2D-associated variants near the genes IGF2BP2 and CDKAL1 and the region of CDKN2A and CDKN2B, and confirm that variants near TCF7L2, SLC30A8, HHEX, FTO, PPARG, and KCNJ11 are associated with T2D risk. This brings the number of T2D loci now confidently identified to at least 10.

OBJECTIVE

To identify physiological and clinical variables associated with development of type 2 diabetes up to 12 years after pregnancies complicated by gestational diabetes.

RESEARCH DESIGN AND METHODS

Seventy-two islet cell antibody–negative nondiabetic Hispanic women had oral (oGTT) and intravenous (ivGTT) glucose tolerance tests, glucose clamps, and body composition assessed between 15 and 30 months after pregnancies complicated by gestational diabetes mellitus (GDM). They returned for oGTTs at 15-month intervals until they dropped out, developed diabetes, or reached 12 years postpartum. Cox regression analysis was used to identify baseline predictors and changes during follow-up that were associated with development of type 2 diabetes.

RESULTS

At baseline, relatively low insulin sensitivity, insulin response, and β-cell compensation for insulin resistance were independently associated with development of diabetes. During follow-up, weight and fat gain and rates of decline in β-cell compensation were significantly associated with diabetes, while additional pregnancy and use of progestin-only contraception were marginally associated with diabetes risk.

CONCLUSIONS

In Hispanic women, GDM represents detection of a chronic disease process characterized by falling β-cell compensation for chronic insulin resistance. Women who are farthest along at diagnosis and/or deteriorating most rapidly are most likely to develop type 2 diabetes within 12 years after the index pregnancy. Weight gain, additional pregnancy, and progestin-only contraception are potential modifiable factors that increase diabetes risk.

In this article, we outline a method for computing Achilles tendon moment arm. The moment arm is computed from data collected using two reliable measurement instruments: ultrasound and video-based motion capture. Ultrasound is used to measure the perpendicular distance from the surface of the skin to the midline of the tendon. Motion capture is used to determine the perpendicular distance from the bottom of the probe to the ankle joint center. The difference between these two measures is the Achilles tendon moment arm. Unlike other methods, which require an angular change in joint position to approximate the moment arm, the hybrid method can be used to compute the moment arm directly at a specific joint angle. As a result, the hybrid method involves fewer error-prone measurements and the moment arm can be computed at the limits of the joint range of motion. The method is easy to implement and uses modalities that are less costly and more accessible than MRI. Preliminary testing using a lamb shank as a surrogate for a human ankle revealed good accuracy (3.3% error). We believe the hybrid method outlined here can be used to measure subject-specific moment arms in vivo and thus will potentially benefit research projects investigating ankle mechanics.

OBJECTIVE

Recent genome-wide association studies have revealed loci associated with glucose and insulin-related traits. We aimed to characterize 19 such loci using detailed measures of insulin processing, secretion, and sensitivity to help elucidate their role in regulation of glucose control, insulin secretion and/or action.

RESEARCH DESIGN AND METHODS

We investigated associations of loci identified by the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) with circulating proinsulin, measures of insulin secretion and sensitivity from oral glucose tolerance tests (OGTTs), euglycemic clamps, insulin suppression tests, or frequently sampled intravenous glucose tolerance tests in nondiabetic humans (n = 29,084).

RESULTS

The glucose-raising allele in MADD was associated with abnormal insulin processing (a dramatic effect on higher proinsulin levels, but no association with insulinogenic index) at extremely persuasive levels of statistical significance (P = 2.1 × 10−71). Defects in insulin processing and insulin secretion were seen in glucose-raising allele carriers at TCF7L2, SCL30A8, GIPR, and C2CD4B. Abnormalities in early insulin secretion were suggested in glucose-raising allele carriers at MTNR1B, GCK, FADS1, DGKB, and PROX1 (lower insulinogenic index; no association with proinsulin or insulin sensitivity). Two loci previously associated with fasting insulin (GCKR and IGF1) were associated with OGTT-derived insulin sensitivity indices in a consistent direction.

CONCLUSIONS

Genetic loci identified through their effect on hyperglycemia and/or hyperinsulinemia demonstrate considerable heterogeneity in associations with measures of insulin processing, secretion, and sensitivity. Our findings emphasize the importance of detailed physiological characterization of such loci for improved understanding of pathways associated with alterations in glucose homeostasis and eventually type 2 diabetes.

OBJECTIVE

To identify factors associated with declining β-cell compensation for insulin resistance.

RESEARCH DESIGN AND METHODS

In a cohort of Hispanic women with recent gestational diabetes mellitus, oral glucose tolerance tests (OGTTs), intravenous glucose tolerance tests (IVGTTs), and bioelectrical impedance measurements were performed at 15-month intervals for up to 5 years, or until fasting plasma glucose exceeded 140 mg/dl (7.8 mmol/l). Data were analyzed to identify predictors of declining β-cell compensation for insulin resistance (the disposition index [DI]) and to examine the mechanism of weight gain and changes in circulating levels of selected adipokines and inflammatory markers on β-cell compensation decline.

RESULTS

A total of 60 nondiabetic women had a median of four sets of OGTT + IVGTT during a median follow-up of 52 months. Fourteen of the women developed diabetes. None of the baseline characteristics were significantly predictive of a decline in DI. There were significant univariate associations between declining DI and weight gain (specifically fat gain), declining adiponectin and rising C-reactive protein. Multivariate analysis showed that the weight gain was the most significant factor associated with declining DI. The amount of association between weight gain and declining DI was explained 31% by changes in adiponectin and C-reactive protein and 40% by changes in insulin resistance.

CONCLUSIONS

These results identify weight gain as the strongest factor associated with declining β-cell compensation for insulin resistance in Hispanic women at high risk for type 2 diabetes. Such effect may be mediated through at least two effects: alterations in adipokine levels and increasing insulin resistance.

OBJECTIVE

Glucokinase (GCK) and glucose-6-phosphatase catalytic subunit 2 (G6PC2) regulate the glucose-cycling step in pancreatic β-cells and may regulate insulin secretion. GCK rs1799884 and G6PC2 rs560887 have been independently associated with fasting glucose, but their interaction on glucose-insulin relationships is not well characterized.

RESEARCH DESIGN AND METHODS

We tested whether these variants are associated with diabetes-related quantitative traits in Mexican Americans from the BetaGene Study and attempted to replicate our findings in Finnish men from the METabolic Syndrome in Men (METSIM) Study.

RESULTS

rs1799884 was not associated with any quantitative trait (corrected P > 0.1), whereas rs560887 was significantly associated with the oral glucose tolerance test 30-min incremental insulin response (30′ Δinsulin, corrected P = 0.021). We found no association between quantitative traits and the multiplicative interaction between rs1799884 and rs560887 (P > 0.26). However, the additive effect of these single nucleotide polymorphisms was associated with fasting glucose (corrected P = 0.03) and 30′ Δinsulin (corrected P = 0.027). This additive association was replicated in METSIM (fasting glucose, P = 3.5 × 10−10 30′ Δinsulin, P = 0.028). When we examined the relationship between fasting glucose and 30′ Δinsulin stratified by GCK and G6PC2, we noted divergent changes in these quantitative traits for GCK but parallel changes for G6PC2. We observed a similar pattern in METSIM.

CONCLUSIONS

Our data suggest that variation in GCK and G6PC2 have additive effects on both fasting glucose and insulin secretion.

Individuals following stroke exhibit altered muscle activation and movement patterns. Improving the efficiency of gait can be facilitated by knowing which muscles are affected and how they contribute to the pathological pattern. In this paper we present an electromyographically (EMG) driven musculoskeletal model to estimate muscle forces and joint moments. Subject specific EMG for the primary ankle plantar and dorsiflexor muscles, and joint kinematics during walking for four subjects following stroke were used as inputs to the model to predict ankle joint moments during stance. The model’s ability to predict the joint moment was evaluated by comparing the model output with the moment computed using inverse dynamics. The model did predict the ankle moment with acceptable accuracy, exhibiting an average R2 value ranging between 0.87 and 0.92, with RMS errors between 9.7% and 14.7%. The values are in line with previous results for healthy subjects, suggesting that EMG-driven modeling in this population of patients is feasible. It is our hope that such models can provide clinical insight into developing more effective rehabilitation therapies and to assess the effects of an intervention.

Ghrelin and peptide YY (PYY) stimulate hunger and satiety, respectively. The physiology of these hormones during normal meal intake remains unclear. The present study was designed to compare the responses of these two hormones to meal intake between lean and obese Hispanic adolescents. Ten obese and seven lean Hispanic youth, aged 11–14 yr, consumed two mixed meals, one small and one large, during which plasma measurements of active and total ghrelin and total PYY were obtained. Obese subjects tended to consume more calories during the small meal than lean subjects, although this did not reach statistical significance. Intake of the small meal significantly suppressed active ghrelin and stimulated PYY levels in the lean subjects, and these changes were further accentuated by the large meals. In obese subjects, the suppression of active ghrelin and stimulation of PYY by caloric intake were blunted. Interestingly, a paradoxical stimulation of active ghrelin levels was noted during the small meals in both lean and obese subjects. This stimulation was not seen during the larger meals in lean subjects, but remained present in the obese subjects. Thus, meal-related changes in active ghrelin and PYY are blunted in obese as compared to lean Hispanic subjects. This blunting could contribute to the development or worsening of obesity.

OBJECTIVE

We have tested whether the Pro12Ala variant of the peroxisome proliferator-activated receptor (PPAR)-γ nuclear receptor involved in thiazolidinedione (TZD) action accounted for the failure of troglitazone to increase insulin sensitivity in nondiabetic Hispanic women with previous gestational diabetes treated in the Troglitazone in Prevention of Diabetes (TRIPOD) study.

RESEARCH DESIGN AND METHODS

Ninety-three women assigned to troglita-zone had intravenous glucose tolerance tests at randomization and after 3 months of treatment with troglitazone, 400 mg/day, and were genotyped for the Pro12Ala variant of the PPAR-γ gene. Subjects were divided into tertiles based on their change in minimal model insulin sensitivity (Si) during the first 3 months of troglitazone treatment.

RESULTS

The mean changes in Si in the bottom, middle, and top tertiles of Si response were −0.21 ± 0.57, 0.91 ± 0.26, and 2.58 ± 1.32 min−1 per μU/ml · 10−4, respectively. Frequencies of the Ala/− genotype were 30, 22, and 26% in the same three tertiles (P = 0.77). Analysis of phenotypes by genotype revealed only small differences between the Pro/Pro and Ala/− groups, respectively, in baseline Si (2.76 ± 0.19 vs. 2.33 ± 0.33 × 10−4 min−1 per μU/ml; P = 0.27), the change in Si after 3 months of troglitazone treatment (1.19 ± 0.17 vs. 0.93 ± 0.30; P = 0.46), and the cumulative incidence of diabetes during a median follow-up of 30 months (13 vs. 17%; P = 0.66).

CONCLUSIONS

Among young Hispanic women at high risk for type 2 diabetes, the Pro12Ala variant of the PPAR-γ receptor gene did not explain the failure of ~1/3 of subjects to increase their insulin sensitivity when placed on troglitazone at a dose of 400 mg/day.

OBJECTIVE

Variation in transcription factor 7-like 2 (TCF7L2) gene has been shown to be associated with type 2 diabetes and diabetes-related quantitative traits. We examined variation in a 0.1-Mb region surrounding marker DG10S478 for association with diabetes-related quantitative traits in 132 Mexican-American families of a proband with previous gestational diabetes mellitus (GDM).

RESEARCH DESIGN AND METHODS

Study participants were phenotyped by an oral glucose tolerance test (OGTT) and an intravenous glucose tolerance test and by a dual-energy X-ray absorptiometry scan for percentage of body fat. Of the 42 tag single nucleotide polymorphisms (SNPs) genotyped, 15 were identified.

RESULTS

On univariate analysis, none of the SNPs showed association with diabetes-related quantitative traits. However, rs12255372 showed association with 30′ Δinsulin (OGTT 30′ min fasting insulin) in an interaction with percentage of body fat (Bonferroni-corrected P = 0.027). The effect of adiposity to increase 30′ Δinsulin was greater in subjects with the T allele. This interaction was not associated with acute insulin response to intravenous glucose. rs12255372 also showed an association with β-cell compensation for insulin resistance based on 30′ Δinsulin in an interaction with percentage of body fat (Bonferroni-corrected P = 0.014). rs12255372 was also associated with GDM (odds ratio [OR] 2.49 [95% CI 1.17–5.31]; P = 0.018) in our case-control sample.

CONCLUSIONS

We conclude that variation in TCF7L2 is associated with GDM and interacts with adiposity to alter insulin secretion in Mexican Americans. Our observations partly explain the increased ORs observed in previous associated studies when analyses were restricted to lean subjects and the variability in quantitative trait association results.

Objectives

The purpose of this study was to examine carefully heterogeneity underlying evidence for linkage to type 2 diabetes (T2DM) on chromosome 6q from two sets of FUSION families.

Methods

Ordered subsets analysis (OSA) was performed on two sets of FUSION families. For OSA results showing significant improvement in evidence for linkage, T2DM-related phenotypes were compared between individuals with T2DM within the subset versus the complement.

Results

OSA analysis revealed 105 families with the highest average HDL to total cholesterol ratio (HDL ratio) that had strongly increased evidence for linkage (MLS = 7.91 at 78.0 cM; uncorrected p = 0.00002). Subjects with T2DM within this subset were significantly leaner, had lower fasting glucose, insulin, and C-peptide, and more favorable cardiovascular risk profile compared to the complement set of subjects with T2DM. OSA also revealed 33 families with the lowest average fasting insulin that had increased evidence for linkage at a second locus (MLS = 3.45 at 128 cM; uncorrected p = 0.017) coincident with quantitative trait locus linkage analysis results for fasting and 2-hour insulin in subjects without T2DM.

Conclusions

These results suggest two diabetes susceptibility loci on chromosome 6q that may affect subsets of individuals with a milder form of T2DM.

Thiazolidinediones (TZDs) are peroxisome proliferator–activated receptor-γ (PPARG) agonists used to treat type 2 diabetes. TZDs can also be used to reduce rates of type 2 diabetes in at-risk individuals. However, a large fraction of TZD-treated patients (30–40%) do not respond to TZD treatment with an improvement in insulin sensitivity (Si). We hypothesized that variation within the gene encoding PPARG may underlie this differential response to TZD therapy. We screened ~40 kb of PPARG in 93 nondiabetic Hispanic women (63 responders and 30 nonresponders) with previous gestational diabetes who had participated in the Troglitazone In the Prevention Of Diabetes study. TZD nonresponse was defined as the lower tertile in change in Si after 3 months of treatment. Baseline demographic and clinical measures were not different between responders and nonresponders. We identified and genotyped 131 variants including 126 single nucleotide polymorphisms and 5 insertion-deletion polymorphisms. Linkage disequilibrium analysis identified five haplotype blocks. Eight variants were associated with TZD response (P < 0.05). Three variants were also associated with changes in Si as a continuous variable. Our results suggest that PPARG variation may underlie response to TZD therapy in women at risk for type 2 diabetes.

The purpose of this study was to develop a biomechanical model to estimate anterior tibial translation (ATT), anterior shear forces, and ligament loading in the healthy and anterior cruciate ligament (ACL)-deficient knee joint during gait. This model used electromyography (EMG), joint position, and force plate data as inputs to calculate ligament loading during stance phase. First, an EMG-driven model was used to calculate forces for the major muscles crossing the knee joint. The calculated muscle forces were used as inputs to a knee model that incorporated a knee–ligament model in order to solve for ATT and ligament forces. The model took advantage of using EMGs as inputs, and could account for the abnormal muscle activation patterns of ACL-deficient gait. We validated our model by comparing the calculated results with previous in vitro, in vivo, and numerical studies of healthy and ACL-deficient knees, and this gave us confidence on the accuracy of our model calculations. Our model predicted that ATT increased throughout stance phase for the ACL-deficient knee compared with the healthy knee. The medial collateral ligament functioned as the main passive restraint to anterior shear force in the ACL-deficient knee. Although strong co-contraction of knee flexors was found to help restrain ATT in the ACL-deficient knee, it did not counteract the effect of ACL rupture. Posterior inclination angle of the tibial plateau was found to be a crucial parameter in determining knee mechanics, and increasing the tibial slope inclination in our model would increase the resulting ATT and ligament forces in both healthy and ACL-deficient knees.

Objective

Diabetes and atherosclerosis may share common genetic determinants. A prior study in Hispanics found association of haplotypes in the diabetes gene calpain-10 (CAPN10) with carotid artery intima-media thickness (CIMT). This study sought to replicate this association in an independent cohort.

Methods

Four CAPN10 SNPs were genotyped and haplotypes determined in 487 Hispanic Americans from 143 families ascertained via an index case with hypertension. CIMT was measured from B-mode ultrasound, and glycemic traits quantified from euglycemic clamps. Association of SNPs and haplotypes with CIMT was determined.

Results

The minor alleles of SNP-56 and SNP-63 were associated with increased CIMT in dominant and additive models. The association of haplotype 1112 with increased CIMT was replicated. No associations with fasting insulin, insulin secretion, or insulin sensitivity were observed.

Conclusions

CAPN10 association with CIMT was replicated, further supporting its role as a common genetic determinant of diabetes and atherosclerosis in Hispanics.

To identify novel genetic loci associated with fasting glucose concentrations, we examined the leading association signals in 10 genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding the melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G-allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95%CI 0.06–0.08) mmol/L in fasting glucose levels (P=3.2×10−50) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P=1.1×10−15). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05–1.12), per G allele P=3.3×10−7) in a meta-analysis of thirteen case-control studies totalling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P=1.1×10−57) and GCK (rs4607517, P=1.0×10−25) loci.

We have created a model to estimate the corrective changes in muscle activation patterns needed for a person who has had a stroke to walk with an improved gait—nearing that of an unimpaired person. Using this model, we examined how different functional electrical stimulation (FES) protocols would alter gait patterns. The approach is based on an electromyographically (EMG) driven model to estimate joint moments. Different stimulation protocols were examined which generated different corrective muscle activation patterns. These approaches grouped the muscles together into flexor and extensor groups (to simulate FES using surface electrodes) or left each muscle to vary independently (to simulate FES using intramuscular electrodes). In addition, we limited the maximal change in muscle activation (to reduce fatigue). We observed that with the two protocols (grouped and ungrouped muscles), the calculated corrective changes in muscle activation yielded improved joint moments nearly matching those of unimpaired subjects. The protocols yielded different muscle activation patterns, which could be selected based on practical condition. These calculated corrective muscle activation changes can be used in studying FES protocols, to determine the feasibility of gait retraining with FES for a given subject and to determine which protocols are most reasonable.

Ultrasonography was used to measure pennation angle and electromyography (EMG) to record muscle activity of the human tibialis anterior (TA), lateral gastrocnemius (LG), medial gastrocnemius (MG), and soleus (SOL) muscles during graded isometric ankle plantar and dorsiflexion contractions done on a Biodex dynamometer. Data from eight male and eight female subjects were collected in increments of approximately 25% of maximum voluntary contraction (MVC) ranging from rest to MVC. A significant positive linear relationship (p < 0.05) between normalized EMG and pennation angle for all muscles was observed when subject specific pennation angles at rest and MVC were included in the analysis. These were included to account for gender differences and inter-subject variability in pennation angle. The coefficient of determination, R2, ranged between 0.76 for the TA to 0.87 for the SOL. The EMG-pennation angle relationships have ramifications for use in EMG-driven models of muscle force. The regression equations can be used to characterize fiber pennation angle more accurately and to determine how it changes with contraction intensity, thus providing improved estimates of muscle force when using musculoskeletal models.

Background

Impaired glucose tolerance (IGT) is a prediabetic state. If IGT can be prevented from progressing to overt diabetes, hyperglycemia-related complications can be avoided. The purpose of the present study was to examine whether pioglitazone (ACTOS®) can prevent progression of IGT to type 2 diabetes mellitus (T2DM) in a prospective randomized, double blind, placebo controlled trial.

Methods/Design

602 IGT subjects were identified with OGTT (2-hour plasma glucose = 140–199 mg/dl). In addition, IGT subjects were required to have FPG = 95–125 mg/dl and at least one other high risk characteristic. Prior to randomization all subjects had measurement of ankle-arm blood pressure, systolic/diastolic blood pressure, HbA1C, lipid profile and a subset had frequently sampled intravenous glucose tolerance test (FSIVGTT), DEXA, and ultrasound determination of carotid intima-media thickness (IMT). Following this, subjects were randomized to receive pioglitazone (45 mg/day) or placebo, and returned every 2–3 months for FPG determination and annually for OGTT. Repeat carotid IMT measurement was performed at 18 months and study end. Recruitment took place over 24 months, and subjects were followed for an additional 24 months. At study end (48 months) or at time of diagnosis of diabetes the OGTT, FSIVGTT, DEXA, carotid IMT, and all other measurements were repeated.

Primary endpoint is conversion of IGT to T2DM based upon FPG ≥ 126 or 2-hour PG ≥ 200 mg/dl. Secondary endpoints include whether pioglitazone can: (i) improve glycemic control (ii) enhance insulin sensitivity, (iii) augment beta cell function, (iv) improve risk factors for cardiovascular disease, (v) cause regression/slow progression of carotid IMT, (vi) revert newly diagnosed diabetes to normal glucose tolerance.

Conclusion

ACT NOW is designed to determine if pioglitazone can prevent/delay progression to diabetes in high risk IGT subjects, and to define the mechanisms (improved insulin sensitivity and/or enhanced beta cell function) via which pioglitazone exerts its beneficial effect on glucose metabolism to prevent/delay onset of T2DM.

Trial Registration

clinical trials.gov identifier: NCT00220961