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JGH Open: An Open Access Journal of Gastroenterology and Hepatology logoLink to JGH Open: An Open Access Journal of Gastroenterology and Hepatology
. 2021 Jun 29;5(8):915–922. doi: 10.1002/jgh3.12606

Prevalence of clinically relevant liver fibrosis due to nonalcoholic fatty liver disease in Indian individuals with type 2 diabetes

Mohammad Shafi Kuchay 1,, Narendra Singh Choudhary 2, Sunil Kumar Mishra 1, Tarannum Bano 1, Sakshi Gagneja 1, Anu Mathew 1, Manish Kumar Singh 3, Parjeet Kaur 1, Harmandeep Kaur Gill 1, Jasjeet Singh Wasir 1, Randhir Sud 2, Ambrish Mithal 1
PMCID: PMC8341185  PMID: 34386600

Abstract

Background and Aim

Type 2 diabetes (T2D) in associated with higher prevalence and worse outcomes of nonalcoholic fatty liver disease (NAFLD). However, data regarding the prevalence of clinically relevant liver fibrosis (CRLF) in Indian individuals with T2D are scarce. We investigated the prevalence of, and factors associated with, CRLF in Indians with T2D.

Methods

We conducted a prospective study of 601 consecutive adults with T2D. Steatosis was diagnosed using ultrasonography. Liver stiffness measurement (LSM) by transient elastography of ≥8.0 kPa was taken as cutoff suggesting CRLF. Individuals with LSM > 13.0 kPa underwent dynamic magnetic resonance imaging (MRI) of liver for detecting changes consistent with cirrhosis.

Results

The prevalence of steatosis was 84.2%. Higher body mass index (BMI, P = 0.022), alanine aminotransferase (ALT; P = 0.001), and lower high‐density lipoprotein (HDL; P = 0.002) were independent factors associated with steatosis. The prevalence of CRLF was 28.2%. Higher BMI (P = 0.001), aspartate aminotransferase (AST; P < 0.0001), gamma‐glutamyl transpeptidase (GGT; P < 0.0001), and concomitant hypertension (P = 0.03) were independent factors associated with CRLF. Elevated ALT and AST (≥40 units/L) levels were present in 70.6 and 51.6% individuals with CRLF, respectively. Thirty‐one (7.2%) individuals had LSM > 13.0 kPa. Among them, 25 individuals underwent dynamic MRI of liver, which revealed features consistent with cirrhosis in 18 patients.

Conclusion

CRLF, an established risk factor for cirrhosis and overall mortality, affects at least one out of four (25%) Indians with T2D. These results support screening of all patients with T2D and NAFLD for liver fibrosis.

Keywords: cirrhosis, clinically relevant liver fibrosis, FibroScan, nonalcoholic fatty liver disease, steatosis


Type 2 diabetes (T2D) and nonalcoholic fatty liver disease (NAFLD) often coexist. T2D promotes the progression of NAFLD to more severe liver pathologies. We found high prevalence of clinically relevant liver fibrosis in individuals with T2D and NAFLD.

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Introduction

Type 2 diabetes (T2D) and nonalcoholic fatty liver disease (NAFLD) often exist together. This is a high‐risk population, as the presence of T2D promotes the progression of NAFLD to more severe histology forms. 1 Approximately 50 million individuals in India have coexisting T2D and NAFLD. Among them, an estimated 12.4 million people have NAFLD‐related advanced liver fibrosis. 2 Advanced liver fibrosis is an imminent risk factor for liver‐related and overall mortality. 3 Yet there is hardly any consensus regarding screening of T2D patients for clinically relevant liver fibrosis (CRLF) or compensated cirrhosis. This is partly because of lack of data regarding true burden of liver fibrosis and cirrhosis in Indian population with T2D.

NAFLD is also strongly associated with the components of metabolic syndrome (obesity, hypertension, hyperglycemia, and dyslipidemia). 4 The prevalence of metabolic syndrome is rapidly increasing in Indian population probably due to increasing urbanization and rapid transition from undernutrition to overnutrition. 5 , 6 , 7 There are a few NAFLD prevalence studies from India that have used ultrasonography (USG) as a diagnostic tool for evaluating NAFLD. 8 , 9 , 10 , 11 Unfortunately, USG does not give any information regarding liver fibrosis, which is the main determinant of liver‐related and overall mortality.

Transient elastography (TE) is an ultrasound‐based technique for fibrosis risk assessment. TE generates two parameters: controlled attenuation parameter (CAP), which gives estimation of liver steatosis, and liver stiffness measurement (LSM), which gives estimation of liver fibrosis. 12

There is scarcity of data regarding the prevalence of CRLF and compensated cirrhosis due to NAFLD in Indian people with T2D. Therefore, the aim of our study was to investigate the prevalence of, and factors associated with, CRLF and cirrhosis in a large cohort of Indian individuals with T2D.

Materials and methods

Study population

This cross‐sectional prospective study was conducted between 1 September 2019 and 31 August 2020 in the Department of Endocrinology and Diabetes, and in Wellness Clinic of Medanta, The Medicity Hospital, a tertiary care facility in New Delhi NCR, India. We enrolled 601 consecutive patients with T2D, aged 18 years and above, who underwent prespecified set of investigations including fasting plasma glucose, glycated hemoglobin (HbA1c), lipid profile, complete blood counts, liver function tests, kidney function tests, thyrotropin (TSH), abdominal USG and body composition by dual‐energy X‐ray absorptiometry (DEXA). In addition to these investigations, each individual underwent TE by FibroScan. Exclusion criteria were positive hepatitis B surface antigen or antibody against hepatitis C virus, elevation of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) more than five times the upper limit of normal values, excessive alcohol consumption (>30 g per day for men and >20 g per day for women), congestive heart failure with hepatomegaly, pregnancy, drugs causing fatty liver such as tamoxifen, and amiodarone, end‐stage renal disease, active malignancy, and unreliable or invalid TE measurements. The study was approved by the institutional ethics review board (MICR‐1184/2020, Gurugram, Haryana, India) and was approved by the ethics committee. Informed consent was obtained from all participants. The study protocol was conducted according to the Helsinki Declaration.

Clinical assessment

Clinical assessment, anthropometric, and demographic data were collected at the day of TE examination. Information on medical history, and current drugs was collected. All investigations were performed on the same day in the fasting state from the center laboratory of the institute. Abdominal ultrasound was used to grade hepatic steatosis from grade 0 to grade 3. Body weight, body mass index (BMI), body fat percentage, and total fat mass (kg) were measured by DEXA using the Hologic Horizon DXA System (USA) with Discovery software, version 12.3 (Bellingham, WA, USA). Normal weight, overweight, and obesity were defined as BMI < 23 kg/m2, BMI between ≥23 and <25 kg/m2, and BMI > 25 kg/m2, respectively, in accordance with World Health Organization (WHO) Asia Pacific guidelines. 13 Patient was considered to have hypertension if the blood pressure was ≥140/90 mmHg, if the patient was taking antihypertensive drugs or if there was positive medical history. Dyslipidemia was defined as positive medical history, use of lipid‐lowering drugs, or if the serum low‐density lipoprotein (LDL) cholesterol level was >100 mg/dL. Hypothyroidism was defined as positive medical history, use of thyroxine, or if the serum TSH level was >10 mIU/L. Established CVD was defined as a positive history of angioplasty and/or coronary artery bypass graft surgery.

Transient elastography

TE was performed with a FibroScan device (EchoSens, Paris, France), in fasting conditions for more than 4 h, with the patient in a supine position, right arm in maximum abduction, by intercostal approach, in the right liver lobe. In each patient, we aimed for 10 valid LSM, with a success rate of measurements >60%. The examination was performed using the M probe (standard probe—transducer frequency 3.5 MHz) or the XL probe (transducer frequency 2.5 MHz). M and XL probes were used according to the European recommendation on M and XL probe selection. A median value of 10 valid LSM was calculated, and the results were expressed in kilopascals (kPa). Reliable measurements were defined as the median value of 10 valid LSM with an interquartile range interval/median ratio (IQR/M) < 30%. LSM ≥ 8.0 kPa was taken as cutoff suggesting CRLF. 14

Dynamic liver magnetic resonance imaging

A subset of individuals with LSM >13.0 kPa underwent dynamic magnetic resonance imaging (MRI) of liver for further verification of cirrhosis, portal hypertension, and to look for any space occupying lesions. MRI was performed at the same hospital.

Statistical analysis

Categorical variables are shown as number and percentages, and continuous variables as means with standard deviation (parametric data) or medians with interquartile range (25th and 75th percentiles, nonparametric data). The chi‐square test was used for comparing proportions expressed as percentages. Linear and logistic regression were used for univariate and multivariate analyses of factors that may influence LSM and CAP values. Furthermore, 95% confidence intervals (CIs) were calculated for each predictive test, and a two‐tailed P‐value < 0.05 was considered significant for all statistical tests. All the statistical analyses were performed using SPSS V.22.0 (SPSS Inc., Chicago, IL, USA).

Results

Patient characteristics

A total of 531 subjects with T2D were analyzed after inclusion and exclusion criteria were applied. Seventy subjects were excluded due to various reasons as shown in Figure 1. The mean age of our cohort was 53.1 (10.8) years and 68% were males. The median duration of T2D diagnosis was 7.0 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 years and mean HbA1c was 7.4 (1.8). The mean BMI of the cohort was 27.5 (4.1) kg/m2, and the median LSM was 6.0 (4.6–8.2) kPa. The demographics, biochemical results, and comorbidities of all study participants with T2D are summarized in Table 1.

Figure 1.

Figure 1

Derivation of the study cohort. LSM, liver stiffness measurement; NAFLD, nonalcoholic fatty liver disease; T2D, type 2 diabetes; USG, ultrasonography.

Table 1.

Baseline characteristics of all subjects

Characteristics All subjects (n = 531)
Age, years 53.1 (10.8)
Males, n (%) 361 (68.0)
Females, n (%) 170 (32.0)
Weight, kg 75.8 (13.5)
BMI (kg/m2) 27.5 (4.1)
Body fat percentage 34.7 (7.1)
Total fat mass, kg 26.4 (8.1)
Diabetes duration, years 7.0 (3–12)
Obesity (BMI ≥ 25 (kg/m2), n (%) 412 (75.9)
Hypertension (n, %) 288 (54.2)
Dyslipidemia (n, %) 347 (65.3)
Established CVD (n, %) 47 (8.9)
Hypothyroidism, (n, %) 67 (12.6)
Fasting plasma glucose, mg/dL 153 (67)
Hemoglobin A1c (%) 7.4 (1.8)
Urea, mg/dL 29.0 (13.0)
Creatinine, mg/dL 0.85 (0.44)
Uric acid, mg/dL 5.3 (1.4)
Na, mmol/L 139.7 (2.2)
K, mmol/L 4.6 (0.4)
Total bilirubin, mg/dL 0.6 (0.3)
Albumin, g/dL 4.4 (0.4)
Aspartate aminotransferase, IU/L 30 (23–40)
Alanine aminotransferase, IU/L 32 (22–50)
Gamma‐glutamyl transpeptidase, IU/L 30 (21–44)
Alkaline phosphatase, IU/L 89 (73–108)
Hemoglobin, g/dL 13.5 (12.4–14.7)
Total leucocyte count × 103/mm3 7.31 (6.11–8.68)
Platelets × 103/mm3 206 (154–265)
Total cholesterol, mg/dL 164 (138–197)
Triglycerides, mg/dL 139 (103–191)
HDL, mg/dL 38 (32–45)
LDL, mg/dL 105 (80–131)
Thyrotropin (TSH), mIU/mL 2.4 (1.5–3.5)
Steatosis by ultrasonography
Grade 0, n (%) 84 (15.8)
Grade 1, n (%) 266 (50.1)
Grade 2, n (%) 158 (29.8)
Grade 3, n (%) 23 (4.3)
Transient elastography
Liver stiffness measurement (LSM), kPa, 6.0 (4.6–8.2)
Clinically relevant fibrosis, LSM ≥ 8.0 kPa, n (%) 147 (27.7)
LSM‐based cirrhosis, LSM >13.0 kPa, n (%) 31 (7.2%)

Data are presented as mean (SD), median (25th–75th percentile), or percentage.

BMI, body mass index; HDL, high‐density lipoprotein; LDL, low‐density lipoprotein.

Overall, 447 (84.2%) participants had hepatic steatosis. Among them, 50.1, 29.8, and 4.3% individuals had ultrasound‐based grade 1, grade 2, and grade 3 steatosis, respectively (Table 1). One hundred twenty‐six participants (28.2%) had LSM ≥8.0 kPa, suggesting CRLF. Grading of CAP‐based steatosis and LSM‐based fibrosis is given in Table S1.

Prevalence of NAFLD and associated risk factors

The prevalence of NAFLD was 84.2%. Relative to T2D subjects without NAFLD (non‐NAFLD), BMI (28.0 vs 25.1 kg/m2, P < 0.0001), body fat (27.1 vs 22.1 kg, P < 0.0001), AST (34.8 vs 29.2 U/L, P = 0.003), ALT (41.3 vs 32.0 U/L, P = 0.002), GGT (44.9 vs 30.0 U/L, P = 0.004), and triglycerides (168 vs 145 mg/dL, P = 0.048) were significantly higher in NAFLD subjects (Table 2). No significant difference in age, duration of diabetes, and platelet levels were observed. Higher proportion of subjects with NAFLD were obese (BMI ≥ 25 kg/m2) (80.5 vs 52.4%, P < 0.0001).

Table 2.

Characteristics of T2D individuals with and without NAFLD

Characteristics Non‐NAFLD (n = 84) NAFLD (n = 447) P value
Age, years 53.0 (12.3) 53.2 (10.5) 0.908
Males, n (%) 55 (65.5) 306 (68.5) 0.591
Females, n (%) 29 (34.5) 141 (31.5)
Weight, kg 67.8 (11.9) 77.3 (13.3) <0.0001*
BMI (kg/m2) 25.1 (3.9) 28.0 (3.9) <0.0001*
Body fat percentage 32.5 (7.4) 35.1 (6.9) 0.002*
Total fat mass, kg 22.1 (7.0) 27.1 (8.1) <0.0001*
Diabetes duration, years 8.6 (6.8) 8.4 (6.5) 0.778
Obesity (BMI  25 (kg/m2), n (%) 44 (52.4) 355 (80.5) <0.0001*
Hypertension (n, %) 47 (56) 241 (54) 0.731
Dyslipidemia (n, %) 54 (64.3) 293 (65.5) 0.823
Established CVD (n, %) 7 (8.3) 40 (8.9) 0.855
Hypothyroidism (n, %) 9 (10.7) 58 (13.0) 0.567
Fasting plasma glucose, mg/dL 158 (80) 151 (64) 0.377
Hemoglobin A1c (%) 7.2 (1.8) 7.4 (1.8) 0.367
Total bilirubin, mg/dL 0.58 (0.36) 0.59 (0.3) 0.788
Albumin, g/dL 4.36 (0.4) 4.35 (0.4) 0.564
Aspartate aminotransferase, IU/L 29.2 (11.9) 34.8 (16.2) 0.003*
Alanine aminotransferase, IU/L 32.0 (20.4) 41.3 (25.9) 0.002*
Gamma‐glutamyl transpeptidase, IU/L 30.0 (27.4) 44.9 (45.5) 0.004*
Alkaline phosphatase, IU/L 94.4 (31.0) 93.5 (28.9) 0.684
Hemoglobin, g/dL 13.9 (1.7) 13.7 (1.8) 0.215
Total leucocyte count × 103/mm3 7.424 (1.99) 7.597 (2.03) 0.474
Platelets × 103/mm3 225 (77) 218 (79) 0.434
Total cholesterol, mg/dL 173 (46) 168 (46) 0.325
Triglycerides, mg/dL 145 (76) 168 (102) 0.048*
HDL, mg/dL 46 (19) 39 (11) <0.0001*
LDL, mg/dL 110 (41) 106 (39) 0.613
Thyrotropin (TSH), mIU/mL 3.2 (3.5) 2.9 (2.7) 0.300
LSM, kPa 6.9 (5.4) 7.2 (4.2) 0.600

*Statistically significant.

Data are presented as mean (SD) or percentage as indicated.

BMI, body mass index; HDL, high‐density lipoprotein; LDL, low‐density lipoprotein, LSM, liver stiffness measurement.

Risk factors associated with NAFLD included higher BMI, body fat percentage, AST, ALT, GGT, TG, and lower high‐density lipoprotein (HDL) levels. Obesity was also associated with NAFLD from univariate logistic regression. Multivariate analyses revealed that only higher BMI (odds ratio [OR], 1.168, confidence interval [CI], 1.02–1.33, P = 0.022), ALT (OR, 1.031, 1.01–1.04, P = 0.001), and lower HDL (OR, 0.969, 0.95–1.00, P = 0.002) were independent factors associated with steatosis (Table 3).

Table 3.

Factors associated with hepatic steatosis in univariate and multivariate analyses

Univariate analysis Multivariate analysis
Variables OR 95% CI P value OR 95% CI P value
Age 1.001 0.98–1.02 0.908
Gender 1.144 0.7–1.87 0.591
BMI 1.268 1.17–1.37 <0.0001 1.168 1.02–1.33 0.022*
Body fat percentage 1.061 1.02–1.1 0.002
Obesity (BMI ≥ 25 (kg/m2) 3.75 2.30–6.12 <0.0001
Diabetes duration, years 0.963 0.93–1.08 0.628
Hypertension 0.921 0.58–1.47 0.731
Dyslipidemia 1.057 0.65–1.72 0.823
Established CVD 1.081 0.47–2.5 0.856
Hypothyroidism 1.243 0.59–2.62 0.568
Hemoglobin A1c 1.064 0.93–1.22 0.361
Albumin 1.88 0.98–3.02 0.392
AST 1.034 1.01–1.06 0.002
ALT 1.031 1.01–1.04 <0.0001 1.031 1.01–1.04 0.001*
GGT 1.019 1.01–1.03 0.004
Platelets 0.999 0.99–1.00 0.433
Triglycerides 1.003 1–1.01 0.048
HDL 0.969 0.95–0.98 <0.0001 0.969 0.95–1.00 0.002*
LDL 0.998 0.99–1 0.612
Thyrotropin (TSH) 0.964 0.9–1.03 0.308

*Statistically significant.

ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; CVD, cardiovascular disease; GGT, gamma‐glutamyl transpeptidase; HDL, high‐density lipoprotein; LDL, low‐density lipoprotein.

Prevalence of CRLF and associated risk factors

CRLF was detected in 126 (28.2%) participants. Relative to T2D subject without CRLF (LSM < 8.0 kPa), higher BMI (29.4 vs 27.4 kg/m2, P = <0.0001), AST (44 vs 31 U/L, P = <0.0001), ALT (53 vs 37 U/L, P = <0.0001), GGT (71 vs 35 U/L, P = <0.0001), and ALP (99 vs 91 U/L, P = 0.018) were significantly higher in subjects with CRLF (LSM ≥ 8.0 kPa). No significant difference in age, duration of diabetes, triglycerides, and platelet levels were observed (Table 4). Hypertension was also associated with CRLF from univariate logistic regression. Multivariate analysis revealed that only higher BMI (OR, 1.084, CI, 1.03–1.14, P = 0.002), AST (OR, 1.031, 1.01–1.06, P = 0.016), and GGT (OR, 1.02, 1.01–1.02, P = <0.0001) and hypertension (OR, 1.729, 1.10–2.72, P = 0.018) were independent factors associated with CRLF (Table 5).

Table 4.

Characteristics of T2DM subjects with NAFLD, with or without clinically relevant liver stiffness (LSM ≥ 8.0 kPa)

Characteristics LSM <8.0 kPa n = 321 LSM ≥8.0 kPa n = 126 P value
Age, years 53.0 (10.7) 53.7 (10.1) 0.526
Males, n (%) 206 (69.4) 90 (67.7) 0.726
Females 91 (30.6) 43 (32.3)
Weight, kg 76.1 (13.1) 80.1 (13.4) 0.004*
BMI (kg/m2) 27.4 (3.6) 29.4 (4.4) <0.0001*
Body fat percentage 34.9 (7.2) 35.6 (6.4) 0.343
Total fat mass, kg 26.6 (8.4) 28.5 (6.9) 0.033*
Diabetes duration, years 8.1 (6.7) 8.3 (6.0) 0.793
Obesity (BMI  25 (kg/m2) 229 (77.9) 111 (84.1) 0.140
Hypertension (n, %) 153 (51.5) 84 (63.2) 0.025*
Dyslipidemia (n, %) 191 (64.3) 95 (71.4) 0.148
Established CVD (n, %) 24 (8.1) 14 (10.5) 0.409
Hypothyroidism (n, %) 37 (12.5) 23 (17.3) 0.181
Fasting plasma glucose, mg/dL 148 (66) 160 (57) 0.093
Hemoglobin A1c (%) 7.3 (1.9) 7.7 (1.6) 0.041*
Total bilirubin, mg/dL 0.6 (0.3) 0.6 (0.3) 0.374
Albumin, g/dL 4.4 (0.3) 4.4 (0.4) 0.850
Aspartate aminotransferase, IU/L 31 (14) 44 (19) <0.0001*
Alanine aminotransferase, IU/L 37 (23) 53 (30) <0.0001*
Gamma‐glutamyl transpeptidase, IU/L 35 (26) 71 (69) <0.0001*
Alkaline phosphatase, IU/L 91 (28) 99 (30) 0.018*
Hemoglobin, g/dL 13.8 (1.8) 13.3 (2.0) 0.016*
Total leucocyte count × 103/mm3 7.537 (2.08) 7.750 (1.93) 0.320
Platelets × 103/mm3 220 (80) 211 (78) 0.278
Total cholesterol, mg/dL 172 (46) 158 (42) 0.003*
Triglycerides, mg/dL 167 (107) 171 (89) 0.760
HDL, mg/dL 40 (11) 38 (11) 0.107
LDL, mg/dL 109 (39) 103 (39) 0.092
Thyrotropin (TSH), mIU/mL 3.0 (2.8) 2.6 (2.7) 0.187

*Statistically significant.

Data are presented as mean (SD) or percentage as indicated.

BMI, body mass index; CVD, cardiovascular disease; HDL, high‐density lipoprotein; LDL, low‐density lipoprotein; NAFLD, nonalcoholic fatty liver disease; T2DM, type 2 diabetes mellitus.

Table 5.

Factors associated with clinically relevant liver stiffness (LSM ≥8.0 kPa) in univariate and multivariate analyses in patients with NAFLD

Univariate analysis Multivariate analysis
Variables OR 95% CI P value OR 95% CI P value
Age, years 1.001 0.99–1.03 0.525
Gender 0.892 0.57–1.38 0.610
BMI (kg/m2) 1.135 1.07–1.2 <0.0001 1.084 1.03–1.140 0.002*
Body fat percentage 1.014 0.98–1.04 0.343
Diabetes duration, years 1.004 0.97–1.04 0.793
Obesity (BMI ≥ 25 (kg/m2) 1.775 1.0–3.16 0.051
Hypertension 1.650 1.08–2.52 0.020 1.729 1.10–2.72 0.018*
Dyslipidemia 1.184 0.76–1.84 0.451
Established CVD 1.418 0.71–2.81 0.318
Hypothyroidism 1.405 0.78–2.52 0.255
Fasting plasma glucose 1.00 1.00–1.01 0.194
Hemoglobin A1c 1.121 1.00–1.25 0.043
Total bilirubin 1.374 0.68–2.77 0.373
Albumin 0.946 0.54–1.67 0.850
AST 1.052 1.04–1.07 <0.0001 1.031 1.01–1.06 0.016*
ALT 1.024 1.02–1.03 <0.0001
GGT 1.023 1.01–1.03 <0.0001 1.02 1.01–1.02 <0.0001*
Platelets 0.999 1.00–1.00 0.282
Triglycerides 1.00 1.00–1.00 0.760
HDL 0.984 0.96–1.00 0.108
LDL 0.94 0.99–1.00 0.063
Thyrotropin (TSH) 0.957 0.87–1.05 0.337

*Statistically significant.

ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; CVD, cardiovascular disease; GGT, gamma‐glutamyl transpeptidase; HDL, high‐density lipoprotein; LDL, low‐density lipoprotein; NAFLD, nonalcoholic fatty liver disease.

Prevalence of transaminitis in individuals with T2D and CRLF

Eighty‐nine (70.6%) individuals with steatosis and CRLF had elevated ALT (≥40 U/L). Sixty‐five (51.6%) individuals with steatosis and CRLF had elevated AST (≥40 U/L). Thirty‐seven (29.4%) and 61 (48.4%) individuals with steatosis and CRLF had normal ALT and AST, respectively (Table S2).

Prevalence of cirrhosis and associated risk factors

Thirty‐one (7.2%) patients with NAFLD were found to have LSM > 13.0 kPa. Of these, 22 (71%) were males, and mean age of 56.9 (8.7) years. The baseline characteristics of all NAFLD patients with LSM >13.0 kPa are given in Table S3. Multivariate analysis revealed that higher AST (OR, 1.04, 1.02–1.06, P < 0.0001) and GGT (OR, 1.01, 1.01–1.02, P < 0.0001) were independent factors associated with cirrhosis (Table S4). Out of 31 patients with LSM > 13.0 kPa, 25 patients underwent dynamic MRI of liver and 18 patients were diagnosed as having features consistent with cirrhosis. Among them, ultrasound showed changes of cirrhosis in only two patients.

Discussion

Our study demonstrated a remarkably high prevalence of NAFLD among type 2 diabetes mellitus (T2DM) patients, which was 84.2% using USG. The prevalence of CRLF (LSM ≥ 8.0 kPa) was 28.2%. Furthermore, among 31 subjects with LSM ≥ 13.0 kPa, 25 underwent dynamic MRI of liver, and 18 were found to have definitive cirrhosis.

There are five large TE‐based studies among individuals with coexisting T2D and NAFLD, one each from Hong Kong (2015), Malaysia (2019), Singapore (2020), Croatia (2020), and the United States (2021). 15 , 16 , 17 , 18 , 19 These studies revealed high prevalence of NAFLD among individuals with T2D, ranging from 70% in the United States, 72.4% in Malaysia, 72.8% in Hong Kong, 78.7% in Singapore, and 83.6% in Croatia. Our study is the first from India and revealed a high prevalence of USG‐based NAFLD (84.2%). Some differences in prevalence of NAFLD among these nations are because of using different CAP cutoffs and may be because of different populations.

We found that higher BMI, ALT, and lower HDL were independent risk factors associated with liver steatosis. Kwok et al. demonstrated that female gender, higher BMI, fasting plasma glucose, ALT, and triglycerides were independently associated with increased CAP. 15 We did not find female gender as a risk factor. We acknowledge that our study population had fewer female representation (32%), probably fewer females getting access to tertiary medical facility in our region. Other risk factors for NAFLD were similar to the study by Kwok et al. In the study by Lai et al., 16 NAFLD was found to be independently associated with central obesity, triglycerides, and ALT levels. Chen et al. 17 showed that higher ALT, obesity, and metabolic syndrome were independently associated with increased CAP. Mikolasevic et al. 18 found that higher BMI, longer duration of T2D, and higher triglycerides were independently associated with NAFLD in the multivariate analysis.

The clinical burden from NAFLD‐related complications is expected to be considerable because T2D is known to be an accelerating factor for NAFLD progression and associated with increased mortality. NAFLD is largely an asymptomatic condition and only manifests at late stage of liver disease. We, therefore, demonstrated the prevalence of complication of NAFLD as CRLF. In our study, the prevalence of CRLF was 28.2% among people with coexisting T2D and NAFLD, which is much higher than that of the general population 14 , 15 , 20 as well as of T2D population. The prevalence of increased LSM in subjects with T2D were 17.7% (Hong Kong), 15 21.0% (Malaysia), 16 13.08% (Singapore) 17 ; moderate (26.9%) and advanced (12.6%) liver fibrosis (Croatia) 18 ; and 21% (LSM ≥7.0 kPa) (United States). 19 In our study, we found much higher prevalence of CRLF. Mikolasevic et al. used LSM cutoff of ≥7.0 kPa for defining moderate liver fibrosis, still the prevalence of increased LSM was lower than that of ours (26.9% vs 28.2% at cutoff of ≥8.0 kPa). This is not surprising as our population has several risk factors predisposing them to NAFLD‐related complications. It has been demonstrated that healthy, normal‐weight Asian Indians are profoundly insulin resistant and hyperinsulinemic compared with age‐ and BMI‐matched Caucasians. Moreover, Asian Indians have greater amounts of total, visceral, and subcutaneous fat compared with Caucasians matched for BMI. 20 Asian Indians also have lower HDL and higher LDL and triglycerides compared with Caucasians. These data demonstrate that altered body composition is associated with insulin resistance, hyperinsulinemia, and dyslipidemia in Asian Indians, and this may explain their heightened risk for diabetes and associated conditions. 21 In non‐obese Asian Indians with T2D, subcutaneous fat and intra‐abdominal obesity, including fatty liver, were higher than BMI‐matched nondiabetic subjects. 22 These observations indicate that our population are particularly at risk for developing metabolic complications including NAFLD‐related conditions.

The substantial number of subjects with increased CRLF is concerning, especially since there are usually no associated symptoms. Our study demonstrated higher BMI, AST, GGT, and concomitant hypertension as independent factors associated with increased LSM. In the Hong Kong study, longer duration of diabetes, higher BMI, increased ALT, and lower HDL cholesterol were associated with increased LSM. 15 In the Malaysia study, higher ALT, and GGT; and lower HDL cholesterol and platelet levels were associated with increased LSM. 16 In the Singapore study, higher AST and CAP** values; and lower platelet count and concomitant hypertension were independent factors associated with increased liver stiffness. 17 In the Croatia study, independent factors associated with advanced fibrosis were female gender, higher BMI, ALT and GGT levels. 18 Overall, the risk factors associated with increased LSM are similar in all the studies. Some differences might be because of different populations and number of subjects included for the analysis. We did not find any association of duration of diabetes with CRLF. Out of the four aforementioned studies, only Hong Kong study had shown association of duration of diabetes with liver fibrosis. 15

Older age had been reported in several studies as an association factor with the development of liver fibrosis, 23 , 24 however this was not demonstrated in our study and in other aforementioned similar four studies. One possible explanation could be that the presence of T2D accelerated the progression of NAFLD which lead to a higher prevalence of liver fibrosis independent of age. Indeed this was demonstrated by a study reporting similarly the higher probability of liver fibrosis in T2D patients independent of age. 14

Our study also demonstrated that 31 (7.2%) subjects had LSM >13.0 kPa, which is a high risk for cirrhosis. Among them, 25 patients underwent dynamic MRI of liver and 18 patients were diagnosed with definitive cirrhosis. All these patients were asymptomatic and had compensated cirrhosis. Diagnosis of all these patients would have been missed if there was no screening by TE. Among them, USG could detect changes of cirrhosis in only two patients. Higher AST and GGT values were independently associated with cirrhosis in the multivariate analysis.

Nonalcoholic steatofibrosis (NASF) may be an important marker for clinical usage in patients with NAFLD. Using biopsy data, it has been demonstrated that NASH and NASF are similarly and significantly associated with liver‐related mortality, but only NASF is associated with overall mortality in patients with NAFLD. 25 Although liver biopsy is the gold standard to assess fibrosis and changes of NASH, it is often not performed except in clinical trials, due to risk of complications. What is interesting is that steatosis and fibrosis can be assessed using noninvasive methods, such as USG, CAP, and MRI proton density fat fraction for steatosis; and serological fibrosis scores, TE, and magnetic resonance elastography for fibrosis. Indeed, it has been demonstrated that NASF (steatosis by ultrasound and fibrosis by NAFLD fibrosis score) predicted overall mortality in a large cohort of patients with NAFLD. 26 In our study, we have assessed steatosis using USG and fibrosis using TE. Thus, we have assessed steatofibrosis (NASF) in our cohort, which may better predict liver‐related and overall mortality in this cohort. However, it needs further validation whether NASF has an edge over NASH or not.

Our study had several limitations, including its cross‐sectional nature and absence of biopsy in patients with advanced fibrosis. However, we used TE, which is a noninvasive technique to evaluate hepatic fibrosis. TE has been endorsed as an alternative to liver biopsy by international guidelines in guiding clinical management of NAFLD. 27 , 28 Therefore, TE is a validated modality in assessing NAFLD fibrosis in a real‐world setting where liver biopsy is not practical for all subjects. Another limitation of our study is that we assessed individuals with T2D who prefer to get treatment from a tertiary care center. These individuals usually had multiple metabolic comorbidities. Therefore, our study population is a high‐risk group, and the results may not apply to community people with T2D. The strength of our study is a large sample size of consecutive Indian patients with T2D. Another strength is that we assessed steatofibrosis with USG and TE, which is a practical way of screening all people with T2D in a clinical setting.

Conclusions

NAFLD and CRLF is highly prevalent in Indian people with T2D. Patients with T2D and higher BMI, AST, and GGT values or comorbidity of hypertension have higher risk for increased liver fibrosis. Our study supports the role of screening for NAFLD‐related liver fibrosis in T2D population.

Supporting information

Table S1. CAP and LSM‐based grading of steatosis and fibrosis of all patients with T2D (n = 531).

Table S2. Transaminitis in people with T2D and NAFLD, with and without clinically relevant liver fibrosis.

Table S3. Baseline characteristics of T2D patients with NAFLD and cirrhosis (LSM > 13.0 kPa).

Table S4. Factors associated with cirrhosis (LSM > 13.0 kPa) in univariate and multivariate analyses.

Acknowledgments

The authors thank Surender Rao (research coordinator, Division of Endocrinology and Diabetes, Medanta‐The Medicity Hospital, Gurugram, Haryana, India) and Bajarang Bahadur (statistician) for help in conduct of the study. The authors also thank the Endocrine and Diabetes Foundation, India, for providing the grant for this study. The current study was supported by an investigator‐initiated study grant to MSK from Medanta‐The Medicity's departmental research fund and a grant from the Endocrine and Diabetes Foundation (EDF), India. The funding agency did not have any role in the design and conduct of the study; collection, management, analysis, or interpretation of the data; or preparation, review, or approval of the manuscript.

Declaration of conflict of interest: M.S.K. has received speaker honoraria from Sanofi, Wockhardt Limited, Novo Nordisk, Novartis, and AstraZeneca. S.K.M. has received speaker honoraria from Novo Nordisk, Boehringer Ingelheim, Novartis, Sanofi, Lupin Limited and Abbott India Limited. J.S.W. has received speaker honoraria from Abbott India Limited, Novartis, AstraZeneca, and Sanofi. P.K. has received speaker honoraria from Novo Nordisk, Boehringer Ingelheim, and Sanofi. A.M. has received speaker and consultant fees from Boehringer Ingelheim. No other conflicts of interest relevant to this article were reported.

Author contribution: Mohammad Shafi Kuchay was responsible for the study concept and design, data collection, interpretation of data, drafting of the manuscript, and approved of the final submission. Sunil Kumar Mishra, Tarannum Bano, Sakshi Gagneja, Anu Mathew, and Jasjeet Singh Wasir contributed to the patient referrals, data collection, critical revision of the manuscript, and approval of the final submission. Manish Kumar Singh contributed to the statistical analysis, data collection, critical revision of the manuscript, and approval of the final submission. PK and Harmandeep Kaur Gill contributed to the patient referrals, analysis of data, critical revision of the manuscript, and approval of the final submission. Narendra Singh Choudhary and Randhir Sud contributed to the data collection (transient elastography and dynamic MRI of liver), critical revision of the manuscript, and approval of the final submission. Ambrish Mithal contributed to the patient referrals and study supervision, obtained funding, and contributed to the critical revision of the manuscript and approval of the final submission. Mohammad Shafi Kuchay is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

References

  • 1. Williams CD, Stengel J, Asike MI et al. Prevalence of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis among a largely middle‐aged population utilizing ultrasound and liver biopsy: a prospective study. Gastroenterology. 2011; 140: 124–31. [DOI] [PubMed] [Google Scholar]
  • 2. Kuchay MS, Choudhary NS, Mishra SK, Misra A. Nonalcoholic fatty liver disease should be considered for treatment allocation in standard management algorithms for type2 diabetes. Diabetes Metab. Syndr. Clin. Res. Rev. 2020; 14: 2233–9. [DOI] [PubMed] [Google Scholar]
  • 3. Angulo P, Kleiner DE, Dam‐Larsen S et al. Liver fibrosis, but no other histologic features, is associated with long‐term outcomes of patients with nonalcoholic fatty liver disease. Gastroenterology. 2015; 149: 389–97.e10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Yang KC, Hung HF, Lu CW, Chang HH, Lee LT, Huang KC. Association of non‐alcoholic fatty liver disease with metabolic syndrome independently of central obesity and insulin resistance. Sci. Rep. 2016; 6: 27034. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Gupta R, Deedwania PC, Gupta A, Rastogi S, Panwar RB, Kothari K. Prevalence of metabolic syndrome in an Indian urban population. Int. J. Cardiol. 2004; 97: 257–61. [DOI] [PubMed] [Google Scholar]
  • 6. Misra A, Athiko D, Sharma R, Pandey RM, Khanna N. Non‐obese hyperlipidemic Asian northern Indian males have adverse anthropometric profile. Nutr. Metab. Cardiovasc. Dis. 2002; 12: 178–83. [PubMed] [Google Scholar]
  • 7. Misra A, Vikram NK. Insulin resistance syndrome (metabolic syndrome) and obesity in Asian Indians: evidence and implications. Nutrition. 2004; 20: 482–91. [DOI] [PubMed] [Google Scholar]
  • 8. Singh SP, Nayak S, Swain M et al. Prevalence of nonalcoholic fatty liver disease in coastal eastern India: a preliminary ultrasonographic survey. Trop. Gastroenterol. 2004; 25: 76–9. [PubMed] [Google Scholar]
  • 9. Amarapurkar D, Kamani P, Patel N et al. Prevalence of non‐alcoholic fatty liver disease: population based study. Ann. Hepatol. 2007; 6: 161–3. [PubMed] [Google Scholar]
  • 10. Mohan V, Farooq S, Deepa M, Ravikumar R, Pitchumoni CS. Prevalence of non‐alcoholic fatty liver disease in urban south Indians in relation to different grades of glucose intolerance and metabolic syndrome. Diabetes Res. Clin. Pract. 2009; 84: 84–91. [DOI] [PubMed] [Google Scholar]
  • 11. Das K, Das K, Mukherjee PS et al. Nonobese population in a developing country has a high prevalence of nonalcoholic fatty liver and significant liver disease. Hepatology. 2010; 51: 1593–602. [DOI] [PubMed] [Google Scholar]
  • 12. Siddiqui MS, Vuppalanchi R, Van Natta ML et al. Vibration‐controlled transient elastography to assess fibrosis and steatosis in patients with nonalcoholic fatty liver disease. Clin. Gastroenterol. Hepatol. 2019; 17: 156–163.e2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13. Regional Office for the Western Pacific (WPRO), World Health Organization. International Association for the Study of Obesity and the International Obesity Task Force . The Asia Pacific Perspective: Redefining Obesity and Its Treatment. St Leonards, Australia: Health Communications Australia Pty Limited, 2000; 22–9. [Google Scholar]
  • 14. Koehler EM, Plompen EP, Schouten JN et al. Presence of diabetes mellitus and steatosis is associated with liver stiffness in a general population: The Rotterdam study. Hepatology. 2016; 63: 138–47. [DOI] [PubMed] [Google Scholar]
  • 15. Kwok R, Choi KC, Wong GL et al. Screening diabetic patients for non‐alcoholic fatty liver disease with controlled attenuation parameter and liver stiffness measurements: a prospective cohort study. Gut. 2016; 65: 1359–68. [DOI] [PubMed] [Google Scholar]
  • 16. Lai LL, Wan Yusoff WNI, Vethakkan SR, Nik Mustapha NR, Mahadeva S, Chan WK. Screening for non‐alcoholic fatty liver disease in patients with type 2 diabetes mellitus using transient elastography. J. Gastroenterol. Hepatol. 2019; 34: 1396–403. [DOI] [PubMed] [Google Scholar]
  • 17. Chen K, Sng WK, Quah JH et al. Clinical spectrum of non‐alcoholic fatty liver disease in patients with diabetes mellitus. PLoS One. 2020; 15: e0236977. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Mikolasevic I, Domislovic V, Turk Wensveen T et al. Screening for nonalcoholic fatty liver disease in patients with type 2 diabetes mellitus using transient elastography ‐ a prospective, cross sectional study. Eur. J. Intern. Med. 2020; 82: 68–75. [DOI] [PubMed] [Google Scholar]
  • 19. Lomonaco R, Godinez Leiva E, Bril F et al. Advanced liver fibrosis is common in patients with type 2 diabetes followed in the outpatient setting: the need for systematic screening. Diabetes Care. 2021; 44: 399–406. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20. Younossi ZM, Golabi P, de Avila L et al. The global epidemiology of NAFLD and NASH in patients with type 2 diabetes: a systematic review and meta‐analysis. J. Hepatol. 2019; 71: 793–801. [DOI] [PubMed] [Google Scholar]
  • 21. Raji A, Seely EW, Arky RA, Simonson DC. Body fat distribution and insulin resistance in healthy Asian Indians and Caucasians. J. Clin. Endocrinol. Metab. 2001; 86: 5366–71. [DOI] [PubMed] [Google Scholar]
  • 22. Misra A, Anoop S, Gulati S, Mani K, Bhatt SP, Pandey RM. Body fat patterning, hepatic fat and pancreatic volume of non‐obese Asian Indians with type 2 diabetes in North India: A case‐control study. PLoS One. 2015; 10: e0140447. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Goh GB, Pagadala MR, Dasarathy J et al. Clinical spectrum of non‐alcoholic fatty liver disease in diabetic and non‐diabetic patients. BBA Clin. 2014; 3: 141–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Roulot D, Costes JL, Buyck JF et al. Transient elastography as a screening tool for liver fibrosis and cirrhosis in a community‐based population aged over 45 years. Gut. 2011; 60: 977–84. [DOI] [PubMed] [Google Scholar]
  • 25. Younossi ZM, Stepanova M, Rafiq N et al. Nonalcoholic steatofibrosis independently predicts mortality in nonalcoholic fatty liver disease. Hepatol. Commun. 2017; 1: 421–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Golabi P, Stepanova M, Pham HT et al. Non‐alcoholic steatofibrosis (NASF) can independently predict mortality in patients with non‐alcoholic fatty liver disease (NAFLD). BMJ Open Gastroenterol. 2018; 5: e000198. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Chalasani N, Younossi Z, Lavine JE et al. The diagnosis and management of nonalcoholic fatty liver disease: practice guidance from the American Association for the Study of Liver Diseases. Hepatology. 2018; 67: 328–57. [DOI] [PubMed] [Google Scholar]
  • 28. European Association for the Study of the Liver (EASL); European Association for the Study of Diabetes (EASD); European Association for the Study of Obesity (EASO) . EASL‐EASD‐EASO Clinical Practice Guidelines for the management of non‐alcoholic fatty liver disease. J. Hepatol. 2016; 64: 1388–402. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table S1. CAP and LSM‐based grading of steatosis and fibrosis of all patients with T2D (n = 531).

Table S2. Transaminitis in people with T2D and NAFLD, with and without clinically relevant liver fibrosis.

Table S3. Baseline characteristics of T2D patients with NAFLD and cirrhosis (LSM > 13.0 kPa).

Table S4. Factors associated with cirrhosis (LSM > 13.0 kPa) in univariate and multivariate analyses.


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