Neuro-molecular mediators of yoga intervention in females with prediabetes: A randomized controlled trial

Summary

Type 2 diabetes (T2D) is primarily a lifestyle-related disorder, which can be controlled by early detection of high-risk individuals with diabetes. It will be beneficial to halt the onset of diabetes by adopting lifestyle modification tools such as Yoga. The present research work emphasizes upon detecting the high-risk individual for diabetes through the Indian Diabetes Risk Score (IDRS). This manuscript addresses an important gap in lifestyle intervention research by highlighting the role of non-glycemic pathways in prediabetes management. Beyond conventional glucose regulation, the findings underscore how yoga-based interventions may influence broader metabolic, psychological, and cognitive domains that are critical in delaying or preventing disease progression. The study carries meaningful implications for preventive healthcare policy and practice. The findings also lay a strong scientific foundation for future longitudinal and mechanistic investigations into the durability of yoga’s effects on metabolic regulation, stress resilience, and cognitive health, thereby advancing the evidence base for holistic approaches to chronic disease prevention.

Graphical abstract

Highlights

• •Three months practice of DYP brings improvements in psychological well-being
• •The DYP and control group did not significantly differ in glycemic indices
• •Improvement in the angiogenesis and neurogenesis markers was observed in DYP group
• •DYP practice may have potential as a primary preventive strategy against type 2 diabetes

Health sciences

Introduction

Diabetes has been a continuing global public health concern with estimated global affliction of ∼1.3 billion people by 2050.¹ More worrisome are the figures of the burden of the disease as it remains one of the ten principal reasons for mortality across the world accounting for ∼4 million deaths.² According to IDF, the prevalence of diabetes in India is 9.6% in 2021 which will be escalated up to 10.4% in 2030.³

Initially identified as a metabolic disorder with chronic hyperglycemia, caused by lack of insulin secretion or reduced insulin action, the evolved understanding of diabetes is of a multisystem disorder basically driven by the convoluted interactions between genetic predisposition and environmental variables. Over the years, there have been interesting facts added to the understanding of the pathophysiology of diabetes, and pre-diabetic conditions.

Prediabetes is a state of hyperglycemia, intermediate between normoglycaemia and the diagnostic cut-off for indices of glycemia, used to diagnose type 2 diabetes (T2D). Prediabetes has emerged to be associated with a significantly increased risk of macrovascular and microvascular complications essentially identical to those of diabetes and also with subclinical derangements of the function of microvasculature and neurons that likely amplify the risk of complications characterized by molecular pathways. This includes vascular endothelial growth factor (VEGF) and angiogenin for angiogenesis, and brain-derived neurotrophic factor (BDNF) for neurogenesis. These molecules are also of relevance from the perspective of metabolic control, inflammatory response, and involvement in reducing insulin resistance. These are also associated with leptin levels and glycemic regulation as direct points of the multifaceted pathogenesis of diabetes mellitus.⁴ Hence, regulation of these biomarkers could also play a significant role in halting the risk of vascular complications.

Normoglycemia, prediabetes, and T2D appear to be part of a continuum of increased risk of adverse outcomes. To this end, short-term preventive interventions at prediabetes stage have sought long-term reductions in the risk of complications.⁵ However, according to American Diabetes Association (ADA), an individual falls under the category of diabetes if one has fasting plasma glucose (FPG)- ≥126, 2 hour plasma glucose (2-h PG) ≥ 200 mg/dL mg/dL and glycated hemoglobin (HbA1c) ≥ 6.5%.⁶

As per the Diabetes Prevention Program Study from 2015, intensive lifestyle intervention along with metformin for 15 years, reduced the incidence of diabetes found in comparison to standard care or placebo.⁷ Similarly, another longitudinal study showed that lifestyle intervention improved health-related quality of life in comparison to metformin.^8,9 This highlights the importance of lifestyle interventions in the prevention of metabolic disorders like T2D.

Moreover, ameliorating effects of yoga intervention have also been seen in improving the overall cardiovascular well-being by reducing the risk of associated risk factors.¹⁰ Isath et al., 2023 conducted a meta-analysis to explore the impact of yoga on cardiovascular diseases, and the results of the study advocate the beneficial role of yoga in improving the lipid profile and further suggested that yoga can play the subsidiary role in the prevention of cardiovascular disorders.¹¹ We utilized a India specific non-pharmacological, economical, and efficient Indian Diabetes Risk Score (IDRS) as screening tool for prediabetes (sensitivity and specificity of 78.05 and 62.68, respectively).¹²

As prediabetes is a condition between normal glycemic index and diabetes, which is often argued as a state with increased propensity for reversal by lifestyle moderation it is characterized by insulin resistance and impaired β cell function which propels pre-diabetes toward full blown disease if unintervened by exercise and nutrition. Since pre-diabetes is believed to initiate years before the diabetes,¹³ it is an alarming condition which, with timely preventive measures, can delay conversion to diabetes. For aforementioned reasons, prediabetes is an important state to examine the impact of any lifestyle moderation, as the prospects of reversal are greater before the actual emergence of the disease. The risk factors for prediabetes are similar to diabetes, and include inactive lifestyle, obesity, heredity, and age.

Though glycemic control remains the most reasonable therapeutic strategy, we wanted to know what role does angiogenesis play in diabetes. Angiogenesis which is an essential process of formation of new blood vessels is of paramount importance to allow oxygen and nutrient supply to the cells throughout the system. This process is primarily mediated by intrinsic and extrinsic factors, VEGF and angiogenin are two such mediators. Diabetes often leads to incompetent angiogenesis which leads to tissue specific paradoxical changes, such as uncontrolled blood vessel formation leading to conditions like diabetic retinopathy. The other aspect is the incomplete formation of small blood vessels in peripheral tissues, such as skin, leading to impaired skin wound healing.^14,15,16

Neurogenesis is another important physiological mechanism by which new neurons are formed in the adult nervous system. This process is important for maintaining cognitive functions like memory, attention, and learning. Besides many regulators of the mechanisms, one of the primary mediator molecules of this pathway is BDNF. Metabolic condition like diabetes affects the process of neurogenesis, which may be a contributor to reduced cognitive abilities in diabetic individuals.¹⁷ Similarly, a stress hormone, cortisol, and hunger hormone leptin levels are also dysregulated under the diabetic metabolic state.^18,19,20

Diabetes and prediabetes are characterized by complex dysregulation of blood vessel formation, where both excessive and insufficient angiogenesis occurs in the same individual in different tissues, thereby overall leading to endothelial dysfunction.^21,22 The VEGF levels in the diabetes and prediabetes are also dysregulated. Similarly, BDNF also displays a complex relationship with diabetes, with lower BDNF levels associated with diabetes, further correlating with insulin resistance,²³ cognitive decline,²⁴ and inflammation.²⁵ Physical activity or yoga may aid in regulating angiogenesis^26,27 and neurogenesis mechanisms in diabetes pathophysiology,^26,28 besides providing other health benefits, as reported through studies.

Studies have shown improvement in glycemic profile of diabetics, improvement in neurocognitive function,^29,30 and improvement in Quality of Life (QoL) after yoga,³¹ besides affecting positive molecular changes.³² But its effect on the prediabetic population is limited. For instance, previous studies done on prediabetic subjects reported improvements in cardiometabolic parameters and reduction in the malondialdehyde (MDA) levels which further highlights the mechanistic effects of yoga intervention in delaying the conversion from prediabetes to diabetes via molecular mechanism.^33,34

Therefore, we aimed to study the impact of yoga-based intervention in prediabetic individuals on aforementioned molecular and biochemical mechanisms, and cognitive functions.

After three months of yoga intervention, the molecular assessments of molecular mediators of angiogenesis, i.e., VEGF and angiogenin, along with BDNF were evaluated. We also evaluated the changes in the cortisol and leptin level. This is among the very few studies which investigates the impact of yoga interventions on the molecular or cellular levels in the prediabetic population.^33,34 In general, there is scarcity of literature which has focused upon the neurogenesis, angiogenesis, or other non-glycemic mechanisms in prediabetics. The study was planned to bridge the critical gap and to understand the impact of non-pharmacological approaches in transforming prediabetic trajectory.

These findings provide valuable insights into the potential of yoga to modulate vascular and neural plasticity, contributing to comprehensive prediabetes management. It is a valuable addition to the growing body of evidence supporting yoga as a scientifically validated intervention for improving metabolic health performance and innovation in neural pathways making it highly relevant for preventive medicine. This topic is timely and relevant, addressing a critical gap in understanding how yoga influences molecular and psychosomatic health in individuals at risk for diabetes.

Results

Baseline characteristics

The high-risk women (for diabetes) were selected and segregated into control and diabetic yoga protocol (DYP) groups as shown in Figure 1. The assessments were done at baseline and after three months. The study population associated baseline characteristics have been reproduced below for both groups in Table 1.

Table 1.

Baseline characteristics of the participants in the DYP and control group

Characteristic	DYP group n = 81 mean (S.D)	Control group n = 81 mean (S.D)	p value
Age (years)	43.57 (9.50)	44.47 (9.22)	0.541
Primary endpoints: molecular biomarkers
Molecular Biomarkers
Angiogenin (ng/mL)	471.58 (431.27)	535.80 (350.32)	0.062
VEGF (pg/mL)	43.23 (28.77)	47.14 (24.87)	0.151
BDNF (pg/mL)	3717.49 (2772.23)	3572.73 (2639.67)	0.980
Cortisol (ng/mL)	167.84 (125.47)	97.92 (97.41)	0.002
Leptin (ng/mL)	2.88 (1.17)	3.40 (1.35)	<0.001
Secondary Endpoints: biochemical parameters, anthropometric parameters, neuropsychological parameters, and Quality of Life (QoL) and its associated domains.
Biochemical parameters
HbA1c (%)	5.62 (0.50)	5.85 (0.74)	0.020
FBS (mg/dL)	95.28 (15.96)	99.65 (20.41)	0.130
Anthropometric parameters
Weight (Kg)	68.64 (10.81)	70.76 (13.25)	0.266
BMI (Kg/m2)	28.68 (4.42)	28.77 (5.78)	0.905
WC (cm)	93.94 (9.04)	96.88 (16.29)	0.158
HC (cm)	104.43 (9.78)	104.43 (10.53)	1.000
WHR (ratio)	0.90 (0.06)	0.93 (0.12)	0.085
Neuropsychological parameters
Sustained Attention	24.85 (11.35)	27.67 (11.86)	0.125
General Health	13.27 (5.48)	10.75 (6.32)	0.007
State Anxiety	44.33 (11.64)	43.55 (11.80)	0.593
Perceived Stress	19.11 (6.34)	18.25 (6.63)	0.398
Quality of Life and its associated domains
Physical Domain of QoL	56.21(9.38)	57.27 (9.76)	0.482
Psycho Domain of QoL	56.21(8.66	58.80 (9.74)	0.075
Social Domain of QoL	64.84 (13.76)	65.32 (15.21)	0.833
Environmental Domain of QoL	72.80 (8.78)	72.33 (10.19)	0.754
QoL	249.44 (25.24)	253.20 (28.19)	0.373

HbA1c, glycated hemoglobin; FBS,fasting blood sugar; BMI, body mass index; WC, waist circumference; HC, hip circumference; WHR, waist-hip ratio; QoL, Quality of Life; VEGF, vascular endothelial growth factor; BDNF, brain derived neurotropic factor. The data presented in Table 2 postulate the mean and SD values for different primary and secondary endpoints selected for the present study in high risk North Indian Women for Diabetes.

Clinical characteristics of participants

Table 1 shows baseline clinical characteristics of the participants in both DYP and control group. Primary endpoints in the present study were 12-week changes in the molecular biomarkers. The secondary endpoints were the 12-week changes on biochemical parameters, anthropometric parameters, neuropsychological parameters and QoL and its associated domains. The data in the present study were collected after screening of high-risk individuals based on IDRS. The sociodemographic characteristics of the participants are presented in Table 2. The adjusted mean difference for primary (molecular markers) and secondary endpoints outcomes like biochemical parameters, anthropometric parameters, neuropsychological parameters, QoL, and its associated domains are shown in Table 3. Moreover, the sub group analysis for primary outcome measures after 3 months follow-up according to age (Age ≤43 years & Age >43 years) is shown in Table 4.

Table 2.

Sociodemographic variable distribution of the participants between the study groups

Variables	yoga (n = 81)	control (n = 81)	significance χ2/Mann-Whitney test
Age (years)	43.57 (9.50)	44.47 (9.22)	0.057
History of diabetes	no history: 47 one parent diabetic: 32 both parents: 02	no history: 74 one parent diabetic: 06 both parents: 01	<0.001
Education	no formal schooling- 9 primary- 10 middle- 8 high school- 22 senior secondary- 3 graduate- 17 PG or above- 12	no formal schooling- 8 primary- 13 middle- 16 high school- 15 senior secondary- 10 graduate- 16 PG or above- 3	0.034
Occupation	housewife- 53 working- 21 professional- 07	housewife- 58 working- 18 professional- 05	0.674
Socio-economic class	upper- 50 upper middle- 13 middle- 17 lower middle- 1	upper- 26 upper middle-23 middle-27 lower middle-5	0.002
Physical Activity	no physical activity- 38 mild - 43 moderate - 0	no physical activity- 40 mild - 36 moderate - 5	0.059

The data presented are presented as mean (SD) for continuous variables as number (%) for categorical variables. the comparative distribution for age was done using Mann-Whitney t test, and categorical variables were assessed through for sociodemographic characteristics for the present study in high risk North Indian Women for Diabetes.

Table 3.

Outcome measures (primary and secondary) after 3 months of follow-up

Variable	adjusted means (yoga) mean (SE)	adjusted means (control) mean (SE)	β (95% CI)	p value
Primary endpoints
Molecular biomarkers
VEGF (ng/mL)	48.59 (0.81)	43.55 (0.81)	0.10 (0.05, 0.14)	<0.001
Angiogenin (ng/mL)	782.72 (55.51)	615.10 (62.82)	0.13 (−0.11,0.26)	0.051
BDNF (pg/mL)	4108.34 (2739.76)	2684.33 (2043.37)	0.26 (0.18, 0.34)	<0.001
Cortisol (ng/mL)	129.45 (7.816)	158.42 (7.816)	−28.96 (−51.52, --6.40)	0.012
Leptin (ng/mL)	2.93 (0.12)	3.57 (0.12)	−0.23 (−0.37-, −0.11)	<0.001
Secondary endpoints
Biochemical parameters
HbA1c (%)	5.70 (0.48)	5.60 (0.48)	−0.10(-0.23, −0.04)	0.152
FBS (mg/dL)	101.68 (2.226)	97.63 (2.226)	4.04 (−2.21, 10.29)	0.203
Anthropometric parameters
Weight (kg)	69.04 (0.922)	70.23 (0.922)	−1.19(-3.78, 1.40)	0.364
BMI (Kg/m2)	28.41 (0.352)	29.14 (0.352)	−0.73 (−1.72,0.25)	0.143
WC (cm)	92.30 (0.988)	96.66 (0.988)	−4.37(-7.14, −1.59)	0.002
HC (cm)	102.37 (0.904)	105.77- (0.904)	−3.40 (−5.94, −0.87)	0.009
WHR (ratio)	0.89 (0.007)	0.91 (0.007)	−0.02 (−0.38, −0.001)	0.046
Neuropsychological parameters
Sustained attention	28.33 (1.374)	20.13 (1.374)	8.21 (4.34, 12.07)	<0.001
General health	7.68 (0.520)	10.09 (0.520)	−2.41 (−3.88, - −0.94)	0.002
State anxiety	33.45 (12.80)	38.14 (12.80)	−4.69 (−8.27,--1.11)	0.011
Perceived stress	12.65 (0.712)	19.23 (0.712)	−6.59 (−8.58-(-4.595)	0.00
Quality of Life and its associated domains
Physical domain of QoL	61.04 (1.081)	58.99 (1.081)	2.050 (−0.975-(-5.075)	0.183
Psycho domain of QoL	59.27 (1.955)	56.99 (1.955)	2.276 (−3.221–7.773)	0.415
Social domain of QoL	64.22 (1.640)	65.93 (1.640)	−1.709 (−6.402–2.984)	0.473
Environmental domain of QoL	82.23(1.577)	76.48 (1.577)	5.747 (1.336–10.159)	0.011
Total QoL	280.28(4.709)	258.79(4.709)	21.48 (8.299–34.679)	0.002

Generalized linear model was used for analysis. The adjusted means of all variables are presented along with standard errors (SE). Adjusted mean difference is calculated by Univariate model adjusted for baseline values, BMI and age. Overall effect is analyzed by Hotelling’s test of Multivariate model adjusting for baseline, BMI and age. HbA1c, glycated hemoglobin; FBS,fasting blood sugar; BMI, body mass index; WC, waist circumference; HC, hip circumference; WHR, waist-hip ratio; QoL, Quality of Life; VEGF, vascular endothelial growth factor; BDNF, brain-derived neurotropic factor; AMD, adjusted mean difference, differences in the adjusted means between the two groups (i.e., adjusted for the covariate). CI, confidence interval; DYP, diabetic yoga protocol. The bold enteries shows the statisitically significant differences in the p value column.

Table 4.

Sub-group analyses for primary measures after 3 months of follow-up

Variable	adjusted means (yoga) mean (SE)	adjusted means (control) mean (SE)	β (95% CI)	p value	P interaction
Primary endpoints
Molecular biomarkers
VEGF (pg/mL)
Age ≤43 years	47.38 (1.08)	40.93 (1.08)	0.13 (0.07, 0.19)	<0.001	0.135
Age >43 years	49.67 (1.32)	46.17 (1.23)	0.06 (−0.001, −0.12)	0.06
Angiogenin (ng/mL)
Age ≤43 years	653.52 (68.22)	552.84 (82.34)	0.09 (−0.11–0.21)	0.360	0.951
Age >43 years	804.99 (892.44)	815.07 (506.10)	0.16 (−0.02–0.34)	0.08
BDNF (pg/mL)
Age ≤43 years	3972.93 (204.67)	2657.49 (220.43)	0.25 (0.13–0.36)	<0.001	0.659
Age >43 years	3938.81 (2661.01)	2992.50 (2101.94)	0.26 (0.15–0.37)	<0.001
Cortisol (ng/mL)
Age ≤43 years	128.93 (18.51)	177.13 (20.00)	−0.17 [-0.36-(0.03)]	0.09	0.603
Age >43 years	106.23 (13.81)	171.31 (12.76)	−0.32 [(-0.51)-0.13]	0.001
Leptin (ng/mL)
Age ≤43 years	3.00 (0.14)	3.49 (0.15)	−0.17 [-0.32-(-0.03)]	0.02	0.500
Age >43 years	2.66 (0.27)	3.60 (0.25)	−0.25 [-0.48]	0.003

β refers to standard beta coefficient, P interaction indicates the significance of interaction between group and the covariates like age, number of yoga sessions. The bold enteries shows the statisitically significant differences in the p value column.

Primary endpoints

DYP practice modulates angiogenesis and neurogenesis markers

The biomarker analysis after the three-month DYP intervention depicted in Table 5 showed significant alteration of candidate angiogenesis and neurogenesis markers as well as hormonal markers. The angiogenesis markers e.g., angiogenin, VEGF, and neurogenesis markers i.e., BDNF exhibited a significant escalation whereas cortisol and leptin hormone showcased the significant reduction after DYP practice. The significant effects of DYP on angiogenesis, neurogenesis markers, cortisol, and leptin concentration show the modulatory role of DYP on the cell survival pathways. For instance, in the case of a control group the physical inactivity resulted in the decreased expression of angiogenesis and neurogenesis markers. Significant changes were seen in angiogenin (β value, 0.13, 95% confidence interval [CI] [−0.11–0.26], p = 0.051), VEGF (β value, 0.10, 95% CI [0.05–0.14], p < 0.001), BDNF (β value, 0.26, 95% CI [0.18–0.34], p < 0.001), cortisol (β value, −28.959, 95% CI [−51.517 to (−6.402)], p = 0.012), and leptin levels (β value, −0.23, 95% CI [−0.37 to (−0.11)], p < 0.001) in yoga group as compared to the control group, following adjusted for baseline score and age as shown in Table 3.

Table 5.

Detailed of diabetic yoga protocol

Diabetic yoga protocol (DYP)
	Sanskrit	English	time duration
Starting prayer: the yoga session begin with the starting prayer.	Asatoma Sat Gamaya	from ignorance lead me to truth	2 min
Loosening exercises: these are light exercises used to warm up the body and loosening of the muscles. These exercises prepare the body to smoothly perform the upcoming asanas.	1.Urdhva-hasta Shvasana 2.Kati-Shakti Vikasaka (3 rounds) 3. Sarvangapushti (3 rounds clockwise, 3 rounds anticlockwise)	(hand stretching synergized breathing 3 rounds at 90°, 135° and 180° each) a) forward and backward bending b)twisting rotatory circular movements.	6 min
Surya Namaskara: it is a combination of 7 asanas done in an sequential way. It helps in buliding the wholesome (mind and body) well being of the individual.	Surya Namaskara(SN) 10 steps of fast Surya Namaskara 6 rounds 12 step slow Surya Namaskara 1 round	sun salutation fast sun salutation slow sun salutation	9 min
Asanas(1 min perAsana)	Physical Postures	–	15 min
1.Standing position (1 min perAsana)	Trikonasana: both legs are wide opened and the same hand touches the same feet and other hand in an erect position toward sky, with eyes focused on the same Parvritta Trikonasana: both the legs are wide opened and the opposite hand rests asides the corresponding feet while another hand in an erect position toward sky, with eyes focused on the same Prasarita Padhastasana: both legs are wide opened and the head touches the ground between the legs and hands are on the sides of the head and arms bends from elbow.	triangle pose reverse triangle pose wide-legged forward bend pose	–
2.Supine position	Jatara Parivartanasana: both hands are wide opened at shoulder level. Both legs are folded from the knees and take them near abdomen and head is in opposite direction. Pawanmuktasana: fold both the legs bring them near the chest and then try to touch the head with the knees. Whereas, hands will join each other around both the knees in a folded position. Viparitakarani: lift both legs gradually in an upward position and then taken support of both the hands at the back.	abdominal twist pose wind relieving pose inverted leg pose	–
3 Prone position	Bhujangasana: keep both the feet together and then gradually lift the body in an upward direction by pressing the feet against the floor keeping the elbows near the body with hands on ground at the shoulder level. Dharuasana: fold both knees toward the hips while hands hold the ankles and uplift the body while keeping thigh, chest and head high.	cobra pose bow pose	–
4. Sitting position	Mandukasana/Vakrasana: in Vajrasana position make clench fist of both the hands and keep them together near the naval region and press the abdomen inwards and bend the body forward. Ardhamatsayendrasana: keep one leg straight and then fold the other leg and place it near the knee of the opposite leg. Then keep the one hand behind the back and with the other hand hold the ankle of folded knee and then gradually twist your spine backwards looing on the opposite side Paschimatanasana: keep both legs straight and then join both feet together after that while bending toward forward direction touch the feet with both hands. Ardha Ushtrasana: sit in Vajrasana and then stand on knees, keep both feet together and then keep both the hands behind the back and gradually bend backwards. Vishranti: at the end, relax with abdominal breathing in supine position (vishranti), 10–15 rounds (2 min)	frog pose half spinal twist pose forward bend pose half camel pose	–
Kriya	a.Agnisara b.Kapalabhati	abdomen churning forceful exhalation	1 min 1 min
Pranayam	Nadishuddhi Bhramari	alternate nostril breathing bee breath	6 min 3 min
	Dhayana	meditation (for stress, for deep relaxation and silencing of mind)	15 min
Closing prayer: yoga session closes with the closing prayer	Sarvebhavantu Sukhina… … … …	let all be happy and free from diseases	1 min
	total duration	–	60 min

Bold enteries are the headings of the specific practices.

Moreover, in Table 4 sub-group analyses for primary measures after 3 months of follow-up age wise analysis (Age ≤43 years and age >43 years) shows non-significant results. When stratified by sub-groups based on age cut-off 43 years, there were no significant differential effects of age on influence of DYP for any of the studied variables. Further, the female population of age ≤43 years was considered perimenopausal, and age >43 years was among the menopausal population. Table 6 profiles the impact of the number of yoga sessions (number of yoga sessions ≤45 days and number of yoga sessions >45 days) attended by the participants. The BDNF shows significant improvements (p = 0.042) in the participants who attended more than >45 days of yoga sessions. Although the non-significant changes were seen among other biomarkers between the ≤45 and >45 days yoga groups. As expected, higher yoga attendance yielded higher BDNF levels among yoga participants. However, a similar pattern could not be observed for other variables, indicating the limitations associated with small sample size of the study group. The results are also in line with the other study, wherein a significant increase was seen in BDNF levels, but non-significant improvements seen in the VEGF levels after aerobic exercise in rats.³⁵ Moreover, another study reported the negative findings on neurogenesis and angiogenesis markers after 3 months of aerobic exercise in older adults.³⁶

Table 6.

Sub-group analyses based on number of yoga sessions for primary measures after 3 months of follow-up

Variable	adjusted means (number of sessions ≤45 days) mean (SE)	adjusted means (number of sessions >45 days) mean (SE)	partial Eta squared	p value
Primary endpoints
Molecular biomarkers
VEGF (ng/mL)	47.52 (1.26)	45.90 (1.47)	0.009	0.429
Angiogenin (ng/mL)	788.44 (80.94)	530.54 (94.53)	0.053	0.053
BDNF (pg/mL)	3746.76 (203.64)	4428.13 (237.80)	0.058	0.042
Cortisol (ng/mL)	137.92 (13.88)	140.13 (16.22)	0.000	0.922
Leptin (ng/mL)	2.68 (0.16)	2.93 (0.18)	0.014	0.317

Generalized linear model is used for analysis. The adjusted means of all variables are presented along with standard errors (SE). Adjusted mean difference is calculated by multivariate model adjusted for baseline values, BMI and age. Overall effect is analyzed by Hotelling’s test of Multivariate model adjusting for baseline, BMI and age. The bold enteries shows the statisitically significant differences in the p value column.

Secondary endpoints

No difference in glycemic control between DYP and control group

The DYP as well as control group showed no significant changes in the HbA1c and FBS levels (Table 3). No changes were seen on the biochemical parameters i.e., HbA1c (β value, −0.098, 95% CI [−0.233–0.036], p = 0.152) and FBS (β value, 4.039, 95% CI [−2.205–10.284], p = 0.203).

Amelioration in anthropometric parameters after DYP intervention

The 3-month DYP practice exerted significant impact on anthropometric parameters, waist circumference (WC) (β value, −4.365, 95% CI [−7.140–(−1.591)], p = 0.002), hip circumference (β value, −3.396, 95% CI [−5.935–(−0.867)], p = 0.009), and waist-hip ratio (WHR) (β value, −0.019, 95% CI [−0.38–0.00], p = 0.046) but no statistically significant change was noted in weight (β value, −1.194, 95% CI [−3.783–1.396], p = 0.364) and body mass index (BMI) (β value, −0.734, 95% CI [−1.717–0.250], p = 0.364) as compared to controls. (Table 3).

Improvements in neuropsychological parameters after DYP intervention

The 3 months of DYP intervention modulated the neuropsychological parameters, including sustained attention (β value, 8.208, 95% CI [4.344–12.072], p = 0.000), general health (β value, −2.407, 95% CI [−3.879–(−0.935)], p = 0.002), anxiety (β value, −4.691, 95% CI [−8.273–(−1.110], p = 0.011), and perceived stress (β value, −6.590, 95% CI [−8.584–(−4.595)], p = 0.00) in comparison with the controls (Table 3).

DYP intervention improves QoL and its associated domains

In DYP group, environmental domain of QoL (β value, 5.747, 95% CI [1.336–10.159], p = 0.011) and total QoL (β value, 21.48, 95% CI [8.299–34.679], p = 0.002) significantly improved comparatively. However, no significant differences were found between intervention group and controls on physical domain (β value, 2.050, 95% CI [−0.975–(−5.075)], p = 0.183), psychological domain (β value, 2.276, 95% CI [−3.221–7.773], p = 0.415), and sociological domain (β value, −1.709, 95% CI [−6.402–2.984], p = 0.473) (Table 3).

Discussion

Lifestyle interventions and glucose homeostasis

In the present scenario, several therapeutic efforts have been made to normalize the hyperglycemic condition, which is considered as a causative agent for the diabetes pathogenesis.^37,38,39 The existing therapies manage blood glucose levels without halting the disease progression.⁴⁰ Clinical trials of sugar normalizing treatments have yielded inconsistent outcomes with limited success.⁴¹ On the other hand, exercise and fitness interventions are often proposed as holding greater promise than anti-hyperglycemic treatment.^42,43,44 Moreover, a systematic and meta-analysis review published by Galaviz et al., (2022) compares pharmacological and non-pharmacological approaches in prediabetes reversal and has reported lifestyle modification approaches to be more effective in improving prediabetic conditions.⁴⁵ Besides, Sharma et al., argues the fact that Ayurveda intervention with addition to lifestyle modification and Yoga is beneficial in managing glycemic indices in diabetic and prediabetic conditions.⁴⁶ Specifically, yoga-based studies in the management of prediabetes studies have shown promising results in controlling blood glucose levels.^47,48 Subsequently, in comparison to the walking, yoga has been shown to be more effective in better glycemic control.^49,50 DYP which was specifically designed for improving glycemic parameters in prediabetic population^51,52,53 supports its relative effectiveness in comparison with other interventions. A consensus statement of the American Diabetic Association states “Large cohort studies have found that higher levels of habitual aerobic fitness and/or physical activity are associated with significantly lower subsequent cardiovascular and overall mortality, to a much greater extent than could be explained by glucose lowering alone”.⁵⁴ However, there is little clarity about the pathways by which exercises (or yoga) reduce diabetic complications independent of glucose. Our study takes precedence in showing that DYP may improve angiogenesis by altering key regulatory molecules independent of glucose.

Yoga protocols on cardiometabolic and body parameters

Emerging studies have also examined the effect of various different yoga protocols for diabetes management,^55,56 but none have examined the effect of widely practised national consensus DYP^57,58 nor have these studies clarified whether or not such effects are mediated independent of glucose. Therefore, we not only investigated the effects of 3-month DYP on anthropometric, neuropsychological, QoL, and biochemical parameters but also the putative molecular markers among high-risk women for diabetes. For identification of high-risk individuals, we used IDRS, which captures the four risk factors i.e., age, level of physical activity, parental history, and waist circumference.

Various studies conducted in the past have revealed the ameliorating impact of yoga on diabetes. For instance, a meta-analysis done by Cui et al., 2017 demonstrated that after yoga practices among the diabetes patients have reported improvements in the lipid profile and blood glucose levels.⁵⁷ Moreover, the significant beneficial result of yoga and breathing exercises has been shown to impact fasting blood glucose (FBG), post prandial blood glucose (PPBG), HbA1c, oxidative stress, and memory.

As a multisystem approach, yoga exerts benefits in achieving preventive health.⁵⁹ For instance, various previous studies have supported the fact that yoga played a crucial and therapeutic role in preventing and managing various diseases and disorders, such as cardiovascular diseases,¹¹ endocrine disorders,⁵⁹ obesity,⁶⁰ polycystic ovarian disorders,⁶¹ arthritis,⁶² stress management,⁶³ and cancer.⁶⁴

The DYP study revealed change in the anthropometric parameters presumably because it increases the consumption of energy and additional calories.⁶⁵ Therefore, we next assessed the anthropometric parameters in our participants that showed significant decline in WC, HC, and WHR. However, no significant change was observed on weight and BMI (Table 3), whereas the improvements were noticed in these variables.

Synergistic impact of diet and yoga on holistic health

The role of diet in the BMI reduction is also crucial which is well cited in the previous literature. For instance, the intermittent energy restriction diet was helpful in weight reduction and amelioration of metabolic parameters in obese populations.⁶⁶ Similarly low carbohydrate diet and Mediterranean diet have shown positive results on weight loss, better glycemic control, and also benefits in managing various cardiovascular risk factors in obese T2D patients.⁶⁷ Moreover, the studies with combined approaches (yoga and diet) on different epidemiological populations can be useful for further advancing our knowledge with common yoga protocol (CYP) investigation. A study undertaken by Rao et al., 2023 showed the reduction in systolic blood pressure (SBP), FBG, HbA1c, total cholesterol, and triglycerides levels after combined approaches of yoga and diet for 6 months.⁶⁸ Another study involving obese individuals showed decreases in anthropometric measures and serum leptin levels after 6 days of combined yoga and diet; however, a reduction in HDL cholesterol was also observed.⁶⁹ Particularly, Saboo and Kacker investigated the impact of twenty 4 week yoga intervention with diet and dietary intervention alone on prediabetic subjects demonstrates the amelioration in various lipid and glycemic indices after post-intervention specifically in the yoga intervention with diet group.⁷⁰

The modulatory role of yoga on psychosomatic health

The relationship between diabetes and cognitive impairment⁷¹ as well as stress⁷² has been well documented in the previous studies. DYP includes breathing practices like pranayama, which regulates stress and anxiety levels and improves psychosomatic health.⁷³ Our findings further indicate a significant improvement of neuropsychological factors like sustained attention, general health, state anxiety, and perceived stress in the DYP intervention group. Moreover, there is substantial increase in total QoL and its associated domains in the DYP group (Table 3), consistent with other studies.^31,74

Despite yoga’s established benefits, the absence of significant improvement in physical and psychological QoL domains in this study can be attributed to factors such as insufficient intervention duration or intensity, variability in participant adherence, and the multifactorial nature of QoL influenced by external psychosocial and lifestyle factors beyond yoga’s scope. Additionally, measurement tools may lack sensitivity to detect subtle changes within the study time frame.

Additionally, measurement tools may lack sensitivity to detect subtle changes within the study time frame. These limitations suggest that longer, more intensive interventions or complementary strategies may be required to observe measurable QoL improvements.

The yogic practices regulate the central nervous system (CNS) thereby improving psychological well-being.⁶³ Hence, DYP is useful for bringing positive neuropsychological changes in the prediabetic participants. We speculate that this may prevent the further conversion of prediabetes state to diabetic condition.

Yoga and its cross-talk with angiogenesis and neurogenesis

To deepen our understanding of the effects of mind-body techniques, we further wanted to analyze the changes brought about by DYP on prediabetic individuals at the molecular level. The various studies emphasize the role of physical exercise that promotes brain functioning and exerts vascular benefits through angiogenesis, neurogenesis, and synaptogenesis.^75,76 Angiogenesis associated with VEGF cited in several studies indicates that this factor can also be regarded as “angioneurotic” that is related to vascular benefits.^77,78 Exercise-induced angiogenesis is a well-established physiological adaptation to compensate for the increased demand of the blood and oxygen to the working muscles.⁷⁹

Consistent with exercised-based physiological effects on angiogenesis, increased circulating levels of VEGF resulting from yoga intervention promotes cardiovascular and metabolic health due to increased muscle glucose uptake diabetes risk reduction.⁷⁹

Studies have shown that blood VEGF levels trigger neurogenesis.⁸⁰ Our findings reveal that BDNF levels increase⁸¹ contributing toward better cognitive functions^82,83 and reduced depressive symptoms.^84,85 Mechanistically, the elevation in BDNF concentrations could be attributed to enhanced vagal tone^84,85 through meditative component of yoga.

BDNF plays a key role in the complex regulation of inflammation, mood regulation, immunity, stress response, and metabolism.⁸⁶ Importantly, BDNF plays a crucial role in regulating energy homeostasis by modulating food intake, glucose metabolism, and insulin sensitivity.⁸⁷ Experimental studies in prediabetic and diabetic rodent models show that BDNF treatment prevents diabetes onset, reduces blood glucose and insulin resistance, and protects pancreatic islet function.⁸⁷ Notably, systemic and central administration of BDNF lowers hyperglycemia independent of food intake changes, acting via central metabolic pathways and peripheral modulation of glucagon secretion through TrkB receptors on pancreatic alpha cells.⁸⁸ The evidence of these findings originates from the pre-clinical observations in prediabetic db/db mice, wherein treatment with BDNF was been documented to prevent the development of diabetes.⁸⁹ Further, BDNF injection attenuated serum insulin and glucose levels in obese diabetic mice.⁸⁹ Protective effect of brain-derived neurotrophic factor on pancreatic islets in obese diabetic mice has also been reported.⁹⁰ Besides, improvement of serum BDNF levels might decrease the risk of T2D and its complications, in particular cognitive dysfunction and depression wherein role of BDNF has been well documented.^81,91 Moreover, a previous study even demonstrated that VEGF found to be positively correlated with the angiogenin. Interestingly, a negative correlation has been reported between the BDNF and VEGF with stress and anxiety.⁹² Yoga practices may be found to be effective in various disease conditions related to the altered angio-neuro mechanism.³² Yoga intervention studies have shown that it impacts the hypothalamic pituitary axis (HPA), axis mediated by BDNF, eventually triggering the cortisol awakening response (CAR) activity.⁸¹ We report opposing effects of yoga on BDNF and cortisol levels consistent with previously reported association between plasma levels of BDNF and increases in the magnitude of the CAR.⁸¹ Given the previous considerations, and the interlinks between BDNF, CAR, and stress, yoga might non-redundantly prevent stress-induced exacerbation of HPA in diabetes progression and the micro- and macrovascular complications.

Physical activity, exercise, walking, and Tai chi have similarly shown improvements in VEGF and BDNF levels along with improvements in the glycemic and metabolic indices in diabetes.^{28,93,94,95,96,97} Furthermore, animals studies with treadmill exercise training and exercise programs have demonstrated improvements in VEGF and BDNF concentrations in rats alongwith significant reduction seen on the brain cell’s mortality rates and its moderating effects on the hippocampal regions.^35,98 Notably, contradictory results were also observed in some studies which reported negative findings on VEGF and BDNF levels in older adults and Parkinson’s disease patients after aerobic exercise training and task oriented training.³⁶ Mechanistically, the exercise-induced muscle contractions release myokines that stimulate the production of neurotrophic factors like BDNF, which promotes neurogenesis and synaptic plasticity. Additionally, exercise triggers release of anti-inflammatory factors that help maintain the brain’s redox balance, countering various pathological processes.⁹⁹ Research shows that exercise mitigates age-related hippocampal volume loss, contributing to preserved memory, and neuroplasticity.¹⁰⁰

Lactate, released during anaerobic exercise, crosses the blood-brain barrier and induces expression of brain plasticity through BDNF, Arc, and c-fos, enhancing neurogenesis. Lactate also activates hydroxycarboxylic acid receptor 1 (HCAR1), leading to elevated VEGF levels, which stimulates angiogenesis and supports cognitive function.¹⁰⁰ This coordinated response underscores the critical role of exercise-induced metabolites and signaling pathways in promoting brain health and function.

Overall, yoga-induced increases in circulating BDNF correlate positively with angiogenic factors such as VEGF and angiogenin, which themselves inversely associate with stress and anxiety markers-a relationship indicative of yoga’s modulatory effects on the angio-neuroendocrine axis. This suggests therapeutic benefits of yoga in diseases characterized by impaired neurovascular function and metabolic disturbances. We can draw conclusion from the literature search that further studies are required to explore the implications of various non-pharmacological methods on various prognostic markers. The analysis of related molecular biomarkers viz.VEGF, BDNF, GDNF, IGF, CRP, and IL-6 etc. in future studies can aid in uncovering the potential role of lifestyle modification tools or non-pharmacological methods in understanding the mechanism of action aforementioned biomarkers in metabolic diseases pathology.

Our report of significantly decreased expression of cortisol and leptin levels in the DYP group simultaneously contrasts and also remains consistent with the previously published studies which have shown a decrease,^69,101 increase,^18,102 and absent changes¹⁰³ in cortisol and leptin levels after yoga intervention, calling for multi centric studies.

Sex-specific recruitments and challenges

Moreover, the recruitment of female participants enabled us to focus on sex-specific metabolic, hormonal, and psychosocial factors relevant to conditions like prediabetes. This approach minimizes biological variability and confounding from sex differences, allowing a clearer assessment of the intervention’s effects in women. It also addresses the persistent underrepresentation of women in clinical research, helping to fill vital knowledge gaps related to female health outcomes.

Unfortunately, some participants attended the entire Yoga camp but refused to give blood samples after 3 months. We often confront these challenges in such studies. Particularly, in the control group the participants may have dropped out as they were not able to derive any significant benefit at follow-up after 3 months. Further, possible reason for big dropout in control group could be the reduced participation in the study protocol, disappointment for not recruited in the intervention group,¹⁰⁴ lack of interest, in providing follow-up data. We speculate that the major reason for the dropouts in the intervention group can include laziness, family responsibilities, sedentary or inactive lifestyle, occupation, physical discomforts, and oversleeping besides lack of interest also highlighted in the previous study.¹⁰⁵

DYP exerts neuroprotective effects independent of plasma glucose

An enormous amount of research work has been carried out in the past on diabetes and its pathophysiology. Apparently, the majority of studies continue to focus on the glucocentric approach of diabetes, which predominantly includes FBG, PPBG, HbA1c, fasting insulin, c-peptide measurements, and its correlation to the related comorbidities. This is a typical approach used for the detection of various diseases. For example, the lipid profile test is used to understand the status of cardiovascular diseases and, HbA1c test for estimating the glycemic level of an individual. Although these are the important aspects of Diabetes, yet the crosstalk between these parameters with underlying molecular mechanisms need further investigation as part of knowledge advancement in new markers. In this context, it is pertinent to note that there is a lack of studies describing the neuronal and cell survival processes related to diabetes as we depend only on glucose and insulin levels, not the underlying or preceding molecular changes that impact cell survival pathways operative in diabetes. Even the anti-diabetic drug development strategies are based on a particular test result, ignoring the underlying mechanisms that drive pancreatic or neuronal cell survival pathways. Hence, most pharmacological efforts to normalize sugar levels have gone in vain and a permanent treatment of diabetes eludes us. Our results have led to a new realization which might not only depend on glycemic index but also the key molecules involved in angiogenesis and neurogenesis pathways which seem more central to cell survival. If these reference tests are examined in tandem with such molecular markers, it may significantly impact insights as to why some diabetics survive without severe comorbidities and others don’t^42,106,107 with contradictory response to interventions.⁴² Therefore, any new interventions including the effective lifestyle modification, especially yoga, might be useful in the field saturated with HbA1c and FBG data. As discussed, it is widely believed that glucose levels and obesity are the chief predictors for diabetes. Yet, in our study with DYP intervention, we observed a significant alteration of the aforementioned molecular markers as compared to the control group. We speculate that some of the key growth factors in angiogenesis and neuronal health can independently impact the outcome of diabetes regardless of the glycemic levels. Hence, this study is an effort to open new vistas that glucose parameters alone are not central to diabetes and therefore emerging treatments should also focus on improving growth factor expression and vascular-neuronal health. In this context, yoga might promote cellular growth and neuronal survival, among diabetics, aiding their recovery and prolonged survival without severe comorbidities.

Therefore, DYP, a consensus yoga protocol, can not only be used to test whether the conversion of prediabetes into diabetes is halted or not but also to develop novel therapeutics that similarly target these pathways. This protocol is proposed as a preventive strategy for inclusion in the 150,000-wellness centers being established in India where DYP’s pivotal role in angiogenesis-neurogenesis cross-talk can be explored through long-term studies.

Adverse events

During the 3-month intervention period, no major adverse events were reported by any of the participants. However, mild muscular fatigue or soreness and moderate cramps were experienced by some (n = 20) during the first 7–15 days of the yoga practice. Additionally, a few participants reported muscle tension and stretching sensations during specific asanas, including Padottanasana, Surya Namaskar, Trikonasana, Bhujangasana, Dhanurasana, Ardha Matsyendrasana, Paschimottanasana, and Mandukasana. These symptoms gradually decreased over time. Yoga instructors provided clear instructions before each session and prior to every loosening, posture formation, and breathing exercise, highlighting indications and contraindications. Moreover, instructors exercised due care to ensure participant safety and prevent major injuries throughout the intervention.

Limitations of the study

The present study does not include longitudinal follow up after six months. Moreover, no dietary assessments were taken before, during, and after the interventions from the participants. Due to missing dietary data and physical activity data (particularly in control group), we are not able to provide an in-depth justification to the results of the present study. However, future work with dietary consideration and physical activity data may help in better interpretation of the results. There are some limitations to our study for e.g., control group was only contacted telephonically; we didn’t employ any personal check-ins or activity trackers to ensure that they were not engaged in similar activities. Subsequently, the present study did not include the other relevant biomarkers, such as inflammatory markers like CRP, IL-6, and lipid profiles.

A key limitation of this study is the absence of detailed dietary and physical activity data from participants. This omission restricts our ability to control for lifestyle factors that could confound the observed effects of the intervention. Without this information, we cannot fully assess participants’ baseline behaviors or monitor changes that may have influenced outcomes, thus limiting insights into potential mechanisms.

Additionally, the lack of adherence data related to diet and activity compromises evaluation of intervention fidelity. Future studies should incorporate comprehensive, objective assessments of dietary intake and physical activity to better elucidate their role in mediating intervention effects and to enhance the robustness of findings.

A major limitation of this study was the high attrition rate, particularly 58% in the control group. Although the sample size was inflated for an anticipated 30% attrition, final analyzed groups were 71 and 36 participants. With these sample sizes and a moderate effect size (Cohen’s d = 0.5), statistical power was approximately 54%, much lower than the planned 80%, increasing the risk of type II error. Multiple imputation was used to address missing data, improving efficiency and reducing bias compared to complete-case analysis. Although this approach cannot fully restore lost power, it helps minimize information loss and enhance the reliability of findings. Such differential dropout introduces attrition bias, which threatens the internal validity by potentially skewing group comparability and treatment effect estimates. This imbalance may have biased the study results and limits the confidence in interpreting the control group outcomes.

Resource availability

Lead contact

Requests for further information and resources should be directed to and will be fulfilled by the lead contact, Akshay Anand (akshay1anand@rediffmail.com).

Materials availability

This study did not generate new unique reagents.

Data and code availability

• •The datasets generated and analyzed during this study are available from lead contact upon request.
• •This study did not generate original code.
• •Any additional information required to re-analyze data reported in this study is available upon request from lead contact.

Acknowledgments

The authors would like to thanks Dr Manjari Rain, Dr Saras Jyoti, Dr Davinder Dhawan, Mr. Surinder, Ms. Sarika Dhiman, Mr. Sumit Rana, and Bhai Ghaniya ji Institute of Health, Panjab University, Chandigarh for helping and providing valuable inputs in the study. The authors also thanks Panjab University , Chandigarh for provide funding for this research. The authors acknowledge all the study participants for their involvement in the trial.

Author contributions

Writing, review, and data collection, N.K; writing and quality assurance, P.B; study supervision and editing, N.M.; lab experimentation, K.S.; analysis of data, R.N. and V.M.; editing, R.M and G.S.; conceptualization, study design, and editing, A.A.

Declaration of interests

The author declares no conflict of interest.

STAR★Methods

Experimental model and study participant details

Estimation of sample size

Given the near absence previous studies on influence of yoga on the markers chosen like VEGF, in pre-diabetes, we assumed a moderate effect size, cohen’s d=0.5. Using G power the sample size for two groups for 80% power and alpha =0.05, was derived as 64 per group. Further, based on an assumed attrition of 30% over 3 months, the sample size was fixed at 166, with 84 individuals per group. A moderate effect size (Cohen’s d = 0.5) was assumed due to the lack of prior studies on yoga’s impact on markers like VEGF in prediabetes. Using G∗Power software, the required sample size for two groups to achieve 80% power at α = 0.05 was calculated as 64.

participants per group, based on the formula:

n=2(Z1−α/2+Z1−β)2d2n=d22(Z1−α/2+Z1−β)2

where Z1−α/2Z1−α/2 and Z1−βZ1−β correspond to the standard normal critical values for significance level and power, and dd is the effect size. To account for a 30% attrition rate over three months, the sample size was further adjusted to a total sample size to 166 participants, with 83 per group.¹⁰⁸

Recruitments

The Indian Diabetes Risk Score (IDRS) modelled by Mohan et al. 2005,¹⁰⁹ was used to identify the high-risk population (≥60) for Diabetes among the rural and urban population of Chandigarh. The validation for IDRS is well established by previously published literature and they found IDRS a suitable tool for screening of diabetes risk assessment.^{110,111,112,113}

The high-risk individuals were screened in a door-to-door survey. Written informed consent was taken from the recruited participants. The ethics committee of Panjab University Institutional Ethics Committee (PUIEC) vide letter no. PUIEC/2017/80/A-1/08/08 and PGIMER, Chandigarh (No: INT/IEC/2018/000184, Dated: 16.02.18) approved the present study. All methods were performed as per relevant guidelines and regulations.

The subjects were recruited from different locations of Chandigarh. The residential areas were randomly selected and categorized into intervention and control group. After selection of the locations, the participants were screened door to door for recruitment of the high-risk individual for Diabetes.

The recruitment team followed a systematic approach by randomly selecting willing households within predefined geographic clusters to maximize representativeness and reduce selection bias.

The staff on ground provided detailed information about the study’s purpose, eligibility criteria, risks, and benefits, answering questions in person to ensure informed understanding. Various visits to each household were made at different times to increase contact rates and accommodate participant availability. Participants who met high-risk criteria for the study were invited to be enrolled, and informed consent was obtained on-site. This personalized, face-to-face recruitment method, helped foster trust, improve engagement and ensure accurate identification of eligible individuals in the community.

Those participants who met the approved inclusion criteria were included in the study. Further, Indian Diabetes Risk Score (IDRS) was used for the screening of high-risk individuals (IDRS≥60). The individuals whose IDRS score was found to be 60 and above and who gave consent for the study were recruited. A total of 162 pre-diabetic subjects met the eligibility criteria for recruitment into the study. The participants were segregated into the Control group (N=81) and the Diabetic Yoga protocol (DYP) (N=81) group. The randomized controlled trial (RCT) was carried out for the participants. The DYP group performed yoga for twelve weeks whereas the control group continued with the daily routine activities, verified by random calls and consequent documentation. Everyday attendance of the participants was noted in the attendance register to verify the adherence of the participants in the intervention group with an average attendance of the participants being 68%. The regular attendance register was maintained for monitoring of such compliance. Further, to ensure that participants performed DYP, regular instructions were provided by the instructor to the participants for adherence to the same and avoidance of any other kind of physical activity during the 12 weeks training program. The participants were also oriented before the beginning of the DYP intervention that they need to perform the DYP for next three months and any other physical activity must be avoided or if carried out, must be notified. Only those participants who assured to perform the DYP for next three months were recruited in the study. Adherence was monitored through regular check-ins and interviews to ensure compliance. The schematic presentation of the study participants is depicted in Figure 1.

Figure 1.

Flow chart of study design

PCA, principal-component analysis; MIP, multiple imputations with PCA.

Method details

Measures

The assessments for selected primary endpoints (molecular biomarkers) and secondary endpoints (biochemical parameters, neuropsychological, anthropometric parameters & quality of life) were taken at baseline and after 3 months. Allocation was concealed in an envelope during the baseline assessments. The assessments for glycemic parameters i.e., HbA1c and FBS were estimated by NABL compliant diagnostic laboratory. HbA1c was measured in the selected participants by Bio-Rad-10, and FBS was measured in the morning after 8-10 hours of overnight fasting (Rxl-Max 500). We collected the overnight fasting blood samples (8-10 hours) early in the morning. The intra- and inter coefficients of variation were within 2.5 % indicating controlled biological variability. The protein levels of selected molecular markers such as angiogenin, VEGF, BDNF, cortisol, and leptin were estimated using ELISA (enzyme-linked immunosorbent assay) as per manufacturer’s instructions. The measurements for anthropometric parameters like BMI and WHR were computed by using the formulae: BMI = weight (in Kilograms)/height (in meters)² and (W/H) respectively. Further, the neuropsychological parameters included Sustained attention, Perceived stress, State anxiety and General health using Six Letter Cancellation Test (SLCT),¹¹⁴ State and trait anxiety inventory (STAI),¹¹⁵ Perceived Stress Scale (PSS),¹¹⁶ and General Health Questionnaire –12 (GHQ-12)¹¹⁷ respectively. The total Quality of life and its associated domains (QoL) were estimated by BREF-WHOQOL scale¹¹⁸ The sociodemographic details of the participants were obtained by using the B.G. Prasad scale.¹¹⁹

Interventions

The Yoga training was imparted at the different locations eg community halls nearby the residence of participants. The Diabetic Yoga Protocol (DYP)⁵¹ was specifically meant for the people with pre-diabetes and was administered by the qualified instructor(s) meant for the DYP Group for 60 minutes were also provided with detail in Table 5. A 60 minutes of Yoga protocol which is designed by an expert team, Diabetes researchers and Indian Yoga Association (IYA) using the Delphi method specifically for diabetic and prediabetic conditions, was administered on the pre-diabetic study participants. The approved yoga protocol for type 2 diabetes mellitus and prediabetes was developed according to the delphi protocol which includes 16 experts. The experts designed the Diabetic yoga protocol via very rigorous process which includes brainstorming sessions, detailed discussions. The final protocol was approved after two Delphi rounds and two rounds of focus group discussion. The details of the Delphi method have been provided in the supplemental document (Appendix S2) and also mentioned in the previously published paper.¹²⁰

Endpoints

The chief endpoints in the present study included several molecular markers analyzed at 12-week. The secondary endpoints were analyzed at 12-week on biochemical, anthropometric, and neuropsychological parameters and Quality of Life (QoL) and its associated domains. The primary endpoints include biomarkers related with angiogenesis i.e VEGF and angiogenin and neurogenesis i.e BDNF. The secondary endpoints include biochemical parameters viz. FBS and HbA1c, anthropometric (Weight, BMI, WC, HC and WHR), neuropsychological (sustained attention, perceived stress, state anxiety and general health) parameters and measurement of QoL and its associated domains like physical, psychological, social and environmental domain.

Quantification and statistical analysis

The data of the present study was analyzed by using SPSS (version 21.0) 0 and R package were used. The Kolmogorov-Smirnov test was used to check the normalcy of data. To verify the changes from baseline and after 3 months, in both control and DYP groups, a paired t-test was employed. The statistical significance was set at with p-value ≤0.05 was considered statistically significant. Further, the intention to treat principle was implemented for which multiple imputations were used for the missing data for the loss of follow up. To estimate the effectiveness of DYP vs. control, primary and secondary outcome variables were analyzed using general linear models controlling for age, BMI, and baseline values of respective variables. The effect sizes of the intervention have been presented as standardized beta coefficients (β), 95% confidence intervals and adjusted mean differences. Analyses by age group were defined post hoc by age groups <45/≥45 years. Missing data was applied multiple imputations to the data using missMDA R package (v1.13) based on the principal component analysis method from the package, using 5 components to reconstruct the data and over 1000 imputed datasets. Missing data in the dataset were addressed using a Principal Component Analysis (PCA)-based multiple imputation approach to preserve the underlying data structure and correlations among variables. This method involves decomposing the observed data matrix into principal components that capture the major variance patterns and using these components to estimate the missing values. Subgroup analyses were performed for age, wherein a age cut off of ≤ 43 years was considered perimenopausal, and Age > 43 years was among the menopausal population. Moreover, all of the statistical details of experiments were found in the results tables.

Additional resources

The study was registered with India's clinical trials registry; registration number: (CTRI/2019/04/018647).

Published: July 8, 2026