Non-alcoholic fatty liver disease (NAFLD) has emerged over the past two decades as one of the most prevalent chronic liver disorders worldwide, paralleling the global rise in obesity, insulin resistance, and type 2 diabetes mellitus (T2DM). Once considered a relatively benign accumulation of fat within hepatocytes, it is now recognized as a dynamic spectrum of disease ranging from simple steatosis to non-alcoholic steatohepatitis, progressive fibrosis, cirrhosis, and even hepatocellular carcinoma [1]. In individuals with T2DM, the burden of NAFLD is disproportionately high, reflecting shared metabolic pathways between the two conditions; diabetes not only increases the prevalence of fatty liver but also accelerates its progression and worsens hepatic and extrahepatic outcomes, making this association clinically significant rather than incidental [1,2].

T2DM is fundamentally characterized by insulin resistance and relative insulin deficiency, both of which play a central role in the pathogenesis of hepatic steatosis. In the insulin-resistant state, adipose tissue lipolysis is inadequately suppressed, leading to an increased flux of free fatty acids to the liver. At the same time, hyperinsulinemia promotes de novo lipogenesis within hepatocytes while impairing fatty acid oxidation and very-low-density lipoprotein export [2]. The net result is triglyceride accumulation within hepatocytes; over time, oxidative stress, mitochondrial dysfunction, endoplasmic reticulum stress, and inflammatory signaling may convert simple steatosis into steatohepatitis. In patients with T2DM these mechanisms are often amplified, explaining the higher prevalence of advanced fibrosis and cirrhosis observed in this group compared with non-diabetic individuals with fatty liver [2,3].

Beyond the liver, NAFLD is increasingly viewed as a multisystem disease with far-reaching consequences, being closely associated with cardiovascular disease, chronic kidney disease, and other microvascular and macrovascular complications of diabetes. Among these, the relationship between NAFLD and microalbuminuria has gained particular attention. Microalbuminuria, defined as a modest increase in urinary albumin excretion below the threshold of overt proteinuria, is a well-established early marker of diabetic nephropathy. It also reflects generalized endothelial dysfunction and increased vascular permeability, serving as a surrogate marker for systemic microvascular injury [3,4].

In subjects with T2DM, the coexistence of NAFLD and microalbuminuria appears to be more than a simple coincidence. Epidemiological studies have consistently shown a higher prevalence of microalbuminuria in diabetic patients with fatty liver compared with those without hepatic steatosis, even after adjusting for traditional risk factors such as glycemic control, blood pressure, and duration of diabetes, suggesting shared pathophysiological pathways linking hepatic fat accumulation to early renal damage [4].

Insulin resistance lies at the heart of this connection. In the kidney, insulin resistance contributes to glomerular hyperfiltration, increased intraglomerular pressure, and enhanced sodium reabsorption, all of which predispose to albumin leakage. Simultaneously, systemic insulin resistance drives hepatic steatosis and inflammation; the liver, acting as an active endocrine and immunological organ, releases hepatokines, inflammatory mediators, and pro-atherogenic factors that can adversely affect renal microcirculation. Elevated tumor necrosis factor-α, interleukin-6, and C-reactive protein commonly observed in NAFLD may promote glomerular endothelial dysfunction, facilitating the development of microalbuminuria [4,5].

Oxidative stress represents another important mechanistic link. In NAFLD, excessive fatty acid oxidation and mitochondrial dysfunction generate reactive oxygen species, leading to lipid peroxidation and cellular injury. These oxidative processes are not confined to the liver but exert systemic effects, contributing to vascular inflammation and endothelial damage; in the diabetic kidney, oxidative stress impairs the integrity of the glomerular basement membrane and podocyte function, increasing albumin permeability. Activation of the renin–angiotensin–aldosterone system, common in diabetes, further strengthens this association, promoting both hepatic stellate cell activation/fibrogenesis and increased glomerular pressure and albumin excretion [5,6]. Reduced adiponectin levels, frequently seen in obesity and T2DM, are similarly associated with increased hepatic fat accumulation and loss of the protective, endothelium-stabilizing effects of adiponectin on the kidney [7].

From a clinical perspective, the coexistence of NAFLD and microalbuminuria in T2DM carries important implications. Both conditions are independent markers of heightened cardiometabolic risk, and their concurrence may identify a subgroup of patients with more severe insulin resistance, greater inflammatory burden, and a higher likelihood of progression to advanced liver disease and overt diabetic nephropathy [7,8]. Early recognition offers an opportunity for timely intervention: lifestyle modification aimed at weight reduction and improved insulin sensitivity, together with pharmacological agents that improve hepatic fat content and reduce renal risk, underscore the interconnected nature of these organ systems [8,9].

Despite this well-described biological plausibility, prospective data quantifying the prevalence of NAFLD and its association with microalbuminuria within a single Indian T2DM cohort, evaluated concurrently with detailed glycemic, lipid, and hepatic biochemical profiling, remain limited. This study was therefore undertaken to determine the prevalence of NAFLD in patients with T2DM attending a tertiary care hospital and to evaluate its association with microalbuminuria, with the aim of informing integrated screening strategies for hepatic and renal complications in this population.

1.1 Aim and Objectives

The aim of this study was to evaluate NAFLD in patients with T2DM and its association with microalbuminuria, with the following specific objectives:

• To study the prevalence of non-alcoholic fatty liver disease in patients with type 2 diabetes mellitus.
• To study the association of non-alcoholic fatty liver disease with microalbuminuria in patients with type 2 diabetes mellitus.

2.1 Study Design and Setting A prospective, cross-sectional, observational study was conducted to examine the relationship between NAFLD and microalbuminuria in patients with T2DM. No interventions or modifications to existing treatment were made; the study observed and recorded clinical, demographic, and investigational parameters at a single time-point. The study was carried out in the Department of General Medicine, Mysore Medical College and Research Institute (MMCRI), Mysuru, with patient recruitment from both the outpatient and inpatient departments of K.R. Hospital, MMCRI, a tertiary care referral centre. The study duration was 18 months (April 2024 – September 2025), including ethical clearance, recruitment, data collection, laboratory and radiological investigation, and statistical analysis. 2.2 Participants Patients aged above 18 years with a diagnosis of T2DM (newly diagnosed or long-standing), who provided written informed consent, were eligible for inclusion. Patients were excluded if they had a history of significant alcohol intake (>1 drink/day in women, >2 drinks/day in men), known viral hepatitis, intake of hepatotoxic medications (e.g., methotrexate, amiodarone, synthetic estrogens, antiretroviral therapy, anti-tubercular therapy, corticosteroids, NSAIDs, or valproate) for more than one month, pre-existing renal dysfunction antedating diabetes, inborn errors of lipid metabolism, inflammatory bowel disease, total parenteral nutrition, prior bariatric surgery, or known thyroid disorders. Participants were selected from the eligible pool by simple random sampling to minimize selection bias. The sample size was calculated using the formula S = Z²PQ/D² (Z = 1.96 at 95% confidence; P = estimated NAFLD prevalence in T2DM of 5%; Q = 1 − P; D = margin of error of 5%), yielding a minimum requirement that was rounded up to 73 participants to account for potential dropouts. This was a single-cohort observational study; subgroups were formed post hoc according to the presence or absence of NAFLD (by ultrasonography) and of microalbuminuria (by UPCR). 2.3 Clinical and Laboratory Assessment Demographic and clinical data collected included age, sex, duration of diabetes, treatment history, personal and family history, and findings of general physical and systemic examination. Laboratory investigations comprised fasting blood sugar (FBS), post-prandial blood sugar (PPBS), and glycated hemoglobin (HbA1c) for glycemic assessment; liver function tests (serum bilirubin, ALT, AST, ALP, and proteins); renal function tests (blood urea, serum creatinine), urine routine examination, and UPCR for detection of microalbuminuria; and a fasting lipid profile. Ultrasonography of the abdomen and pelvis was the primary tool for diagnosing and grading NAFLD, based on echogenicity features such as hepatorenal echo contrast, liver brightness, and vascular blurring, and was graded as Grade 0 (normal), Grade 1 (mild), Grade 2 (moderate), or Grade 3 (severe) steatosis. After institutional ethics committee approval and written informed consent, eligible participants underwent a structured clinical assessment followed by the prescribed panel of investigations. All data were recorded in a pre-tested, structured proforma (case record form) comprising demographic/clinical history, examination findings, and investigation results, to ensure uniformity and completeness of data collection. 2.4 Statistical Analysis Data were entered in Microsoft Excel and analyzed using SPSS software, version 28. Categorical variables were expressed as frequency and percentage, and continuous variables as mean ± standard deviation (SD). The chi-square test was used to assess association between categorical variables (e.g., presence of NAFLD and presence of microalbuminuria), and the independent-samples t-test was used to compare means of continuous variables between groups. Pearson's correlation coefficient was used to assess linear relationships between continuous variables; where data were non-normally distributed, equivalent non-parametric tests (Mann–Whitney U test, Spearman's correlation) were applied. A two-tailed p-value < 0.05 was considered statistically significant. 2.5 Ethical Considerations The study protocol, informed consent form, and subject information sheet were reviewed and approved by the Institutional Ethics Committee of MMCRI prior to commencement, and the study was conducted in accordance with the ethical principles of the Declaration of Helsinki and Good Clinical Practice guidelines. Voluntary, written, informed consent was obtained from all participants, who were informed of their right to withdraw at any time without affecting their standard care. All participant data were anonymized using identification numbers, and confidentiality was maintained throughout. The study was observational and involved only routine blood draws and ultrasonography, carrying minimal risk.

A total of 73 patients with T2DM were enrolled. The mean age was 48.71 ± 14.77 years (range 26–74 years), and males constituted a slight majority (56.16%). The mean duration of diabetes was 5.07 ± 3.57 years. Oral hypoglycemic agents (OHA) alone were the most common treatment modality (43.84%), followed by insulin alone (28.77%), combined OHA and insulin (23.29%), and diet control alone (4.11%). A family history of diabetes was present in 53.42% of participants. Hypertension (68.49%) and dyslipidemia (61.64%) were common comorbidities. Baseline demographic, anthropometric, and clinical characteristics are summarized in Table 1.

Table 1. Baseline Demographic, Anthropometric, and Clinical Characteristics of the Study Population (n = 73)

SD, standard deviation; OHA, oral hypoglycemic agent.

Biochemical parameters showed suboptimal glycemic control overall, with a mean FBS of 162.36 ± 53.66 mg/dL, PPBS of 253.36 ± 86.16 mg/dL, and HbA1c of 8.07 ± 1.46%. Lipid parameters showed moderately elevated total cholesterol and triglycerides, with borderline-high LDL and VLDL and preserved HDL. Renal parameters were relatively preserved, with a mean eGFR of 89.92 ± 11.85 mL/min/1.73 m² and serum creatinine of 0.94 ± 0.20 mg/dL, while mean UPCR was 165.81 ± 94.21 mg/g (range 10.1–584.7 mg/g), reflecting considerable heterogeneity in urinary protein excretion. Liver function tests showed mild elevation of transaminases (mean SGOT 44.29 ± 20.14 U/L; SGPT 67.53 ± 27.73 U/L). Detailed biochemical, hepatic, and renal parameters are presented in Table 2.

Table 2. Glycemic, Lipid, Hepatic, and Renal Biochemical Parameters of the Study Population (n = 73)

FBS, fasting blood sugar; PPBS, post-prandial blood sugar; HbA1c, glycated hemoglobin; SGOT/SGPT, serum glutamic-oxaloacetic/pyruvic transaminase; eGFR, estimated glomerular filtration rate.

On ultrasonographic evaluation, NAFLD was present in 49 of 73 participants (67.12%). Among these, mild (Grade 1) steatosis was most common (27.40% of the total cohort), followed by moderate (Grade 2, 24.66%) and severe (Grade 3, 15.07%) steatosis, while 32.88% had a normal liver echotexture (Grade 0). Microalbuminuria, based on UPCR, was present in 50 of 73 participants (68.49%). The coexistence of NAFLD and microalbuminuria was observed in 38 participants (52.05% of the total cohort), representing a high-risk metabolic phenotype with combined hepatic and renal involvement (Table 3).

Table 3. Prevalence and Severity of NAFLD, Prevalence of Microalbuminuria, and Their Coexistence (n = 73)

USG, ultrasonography.

3.1 Comparison of Clinical and Biochemical Parameters by NAFLD Status

Demographic and anthropometric characteristics (age, duration of diabetes, height, weight, BMI) and clinical parameters (pulse rate, systolic and diastolic blood pressure) did not differ significantly between participants with and without NAFLD (all p > 0.05). In contrast, several biochemical parameters differed significantly by NAFLD status. Patients with NAFLD had significantly higher FBS (173.37 ± 56.57 vs. 139.88 ± 39.37 mg/dL; p = 0.0112), PPBS (271.51 ± 91.21 vs. 216.29 ± 61.15 mg/dL; p = 0.0091), LDL (125.32 ± 33.44 vs. 120.71 ± 30.34 mg/dL; p = 0.0026), triglycerides (180.32 ± 77.78 vs. 177.50 ± 79.37 mg/dL; p = 0.0381), and UPCR (176.23 ± 98.32 vs. 168.19 ± 97.21 mg/g; p = 0.0167) than those without NAFLD. HDL, VLDL, serum creatinine, and HbA1c did not differ significantly between groups (all p > 0.05); notably, HbA1c was numerically lower in the NAFLD group (7.91 ± 1.26% vs. 8.40 ± 1.78%; p = 0.318), indicating that short-term glycemic excursions were more strongly associated with NAFLD than long-term glycemic control in this cohort (Table 4).

Table 4. Comparison of Biochemical Parameters Between Participants Without and With NAFLD

*Statistically significant, p < 0.05. FBS, fasting blood sugar; PPBS, post-prandial blood sugar; HbA1c, glycated hemoglobin; UPCR, urine protein–creatinine ratio.

3.2 Association Between NAFLD and Microalbuminuria

Among participants with microalbuminuria, NAFLD was present in 38 of 50 (76.00%), compared with 11 of 23 (47.83%) among those without microalbuminuria — a statistically significant association (χ² test, p = 0.0173), corresponding to an approximately 1.59-fold higher likelihood of NAFLD in patients with microalbuminuria (Table 5).

Table 5. Cross-Tabulation of NAFLD Status by Microalbuminuria Status (n = 73)

*Statistically significant association by chi-square test, p < 0.05.

This prospective observational study of 73 patients with T2DM demonstrates a high prevalence of both NAFLD (67.12%) and microalbuminuria (68.49%), with a statistically significant association between the two conditions (p = 0.0173). NAFLD was present in 76.00% of patients with microalbuminuria compared with 47.83% of those without, corresponding to an approximately 1.59-fold increased likelihood of hepatic steatosis in the presence of early renal involvement. These findings support the concept that NAFLD represents a multisystem metabolic disorder with important renal implications in the diabetic population. The demographic profile of the cohort — a mean age of 48.71 ± 14.77 years with a slight male predominance (56.16%) — is broadly consistent with earlier reports in which mean age ranged from 45 to 60 years and male predominance from 55% to 65% [16,69,70]. The relatively younger mean age observed here, compared with the 52.1 ± 9.9 years reported by Kanakamani et al. [69], may reflect an earlier onset of metabolic disease in the current population, a trend increasingly described in developing countries and attributed to urbanization, calorie-dense diets, reduced physical activity, and rising obesity [20]. Glycemic control in the cohort was suboptimal, with mean FBS, PPBS, and HbA1c values 62%, 69%, and 24% above conventional reference thresholds, respectively — consistent with earlier studies reporting mean HbA1c of 7–9% in diabetic patients with NAFLD and supporting the role of sustained hyperglycemia in the pathogenesis of hepatic steatosis and microvascular complications [31]. The observed NAFLD prevalence of 67.12% falls within, albeit toward the higher end of, the 60–75% range previously reported in T2DM populations [45], while the microalbuminuria prevalence of 68.49% exceeds the 30–50% typically reported in diabetic cohorts [69]. The higher figures observed here may be explained by the hospital-based nature of the study population, which tends to capture patients with more advanced metabolic derangement, together with the relatively poor glycemic control noted in this cohort. Comparison of biochemical parameters by NAFLD status revealed that patients with NAFLD had significantly higher FBS and PPBS, higher LDL and triglycerides, and higher UPCR than those without NAFLD, while HDL, VLDL, serum creatinine, and HbA1c did not differ significantly. The lack of association with HbA1c, despite significant associations with FBS and PPBS, suggests that acute glycemic excursions may be more closely linked to hepatic fat accumulation than cumulative long-term glycemic control in this population — a distinction that merits further prospective evaluation. The modest absolute differences in LDL, triglycerides, and UPCR, despite reaching statistical significance, indicate that while these associations are real, their independent clinical discriminatory value may be limited; they are more useful as part of an overall risk profile than as isolated markers. Mechanistically, the association between NAFLD and microalbuminuria observed in this study is consistent with shared pathophysiological pathways described in the literature. Insulin resistance promotes both hepatic triglyceride accumulation and glomerular hyperfiltration with increased intraglomerular pressure, while systemic release of pro-inflammatory cytokines from the fatty liver — including tumor necrosis factor-α, interleukin-6, and C-reactive protein — may contribute to glomerular endothelial injury and increased albumin permeability [58,59]. Oxidative stress and lipotoxicity further compound both hepatic and renal damage, supporting the concept of NAFLD and microalbuminuria as parallel manifestations of a common underlying metabolic derangement rather than independent, coincidental findings [60]. These results are concordant with previous studies demonstrating a 1.5- to 2-fold higher prevalence of albuminuria among patients with NAFLD and an increased risk of diabetic nephropathy in this group [75,76,79]. The coexistence of NAFLD and microalbuminuria in 52.05% of the present cohort identifies a substantial subgroup of patients with combined hepatic and renal involvement — a high-risk metabolic phenotype in which NAFLD may serve as an accessible, non-invasive early marker prompting more vigilant renal screening, and vice versa. Given the high background prevalence of both conditions in this population, integrating routine abdominal ultrasonography and UPCR testing into standard diabetic care may allow earlier identification of patients at increased risk of progression to chronic kidney disease and cardiovascular complications, complementing existing screening for retinopathy and neuropathy. Clinically, these findings reinforce that lifestyle interventions — weight reduction, dietary modification, and increased physical activity — which improve insulin sensitivity and reduce hepatic fat, together with pharmacological management of glycemia and dyslipidemia, are likely to have combined benefit for both hepatic and renal outcomes in patients with T2DM [32]. Integrating hepatic and renal evaluation into routine diabetic follow-up, rather than treating these as separate surveillance pathways, may therefore improve early diagnosis and long-term outcomes. 4.1 Limitations This study has several limitations. The relatively small sample size (n = 73) from a single tertiary care center may limit generalizability and may bias the cohort toward more severe metabolic derangement. The cross-sectional design precludes causal inference despite the statistically significant association observed. NAFLD was diagnosed by ultrasonography, which may underestimate mild hepatic steatosis compared with more sensitive quantitative modalities (e.g., MR-based fat fraction) or liver biopsy. Microalbuminuria was assessed using a single UPCR measurement without confirmatory repeat testing, which may overestimate prevalence due to transient physiological variation. Potential confounders such as diet, physical activity, and genetic predisposition were not quantitatively assessed, and the absence of longitudinal follow-up precluded evaluation of progression to advanced liver disease or overt diabetic nephropathy.

This study demonstrates a high prevalence of NAFLD (67.12%) and microalbuminuria (68.49%) among patients with T2DM, with a statistically significant association between the two conditions (p = 0.0173); NAFLD was 28.17% more prevalent among patients with microalbuminuria and was associated with an approximately 1.59-fold higher likelihood of renal involvement. Patients with NAFLD had significantly higher fasting and post-prandial glucose, LDL, triglycerides, and UPCR, although HbA1c did not differ significantly, suggesting that short-term glycemic parameters were more strongly associated with NAFLD than long-term glycemic control in this cohort. These findings support NAFLD as a marker of systemic metabolic dysfunction with clinically relevant renal implications. Early ultrasonographic screening for NAFLD and routine assessment of microalbuminuria, integrated with comprehensive management of glycemic control, blood pressure, weight, and dyslipidemia, may help identify high-risk patients earlier and reduce progression to chronic kidney disease and cardiovascular complications in patients with T2DM.

Declarations

Ethics approval and consent to participate: The study was approved by the Institutional Ethics Committee of Mysore Medical College and Research Institute, Mysuru, and conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants.

Conflict of interest: The authors declare no conflict of interest.

Funding: No specific funding was received for this study.

Acknowledgements: The authors thank the Department of General Medicine and the Institutional Ethics Committee, Mysore Medical College and Research Institute, Mysuru, and all patients who participated in this study.

Author contributions: Both authors contributed to study conception and design, data collection and analysis, manuscript preparation, and approved the final manuscript.

Browning JD, Szczepaniak LS, Dobbins R, Nuremberg P, Horton JD, Cohen JC, Grundy SM, Hobbs HH. Prevalence of hepatic steatosis in an urban population in the United States: impact of ethnicity. Hepatology. 2004 Dec;40(6):1387-95. doi: 10.1002/hep.20466. PMID: 15565570.

2. Younossi ZM, Golabi P, Paik JM, Henry A, Van Dongen C, Henry L. The global epidemiology of nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH): a systematic review. Hepatology. 2023 Apr 1;77(4):1335- 1347. doi: 10.1097/HEP.0000000000000004. Epub 2023 Jan 3. PMID: 36626630; PMCID: PMC10026948.
3. Williams CD, Stengel J, Asike MI, Torres DM, Shaw J, Contreras M, Landt CL, Harrison SA. 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 Jan;140(1):124-31. doi: 10.1053/j.gastro.2010.09.038. Epub 2010 Sep 19. PMID: 20858492.
4. Younossi Z, Anstee QM, Marietti M, Hardy T, Henry L, Eslam M, George J, Bugianesi E. Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat Rev Gastroenterol Hepatol. 2018 Jan;15(1):11-20. doi: 10.1038/nrgastro.2017.109. Epub 2017 Sep 20. PMID: 28930295.
5. Hazlehurst JM, Woods C, Marjot T, Cobbold JF, Tomlinson JW. Non-alcoholic fatty liver disease and diabetes. Metabolism. 2016 Aug;65(8):1096-108. doi: 10.1016/j.metabol.2016.01.001. Epub 2016 Jan 11. PMID: 26856933; PMCID: PMC4943559.
6. Loomba R, Sanyal AJ. The global NAFLD epidemic. Nat Rev Gastroenterol Hepatol. 2013 Nov;10(11):686-90. doi: 10.1038/nrgastro.2013.171. Epub 2013 Sep 17. PMID: 24042449.
7. Targher G, Bertolini L, Rodella S, Zoppini G, Lippi G, Day C, Muggeo M. Non- alcoholic fatty liver disease is independently associated with an increased prevalence of chronic kidney disease and proliferative/laser-treated retinopathy in type 2 diabetic patients. Diabetologia. 2008 Mar;51(3):444-50. doi: 10.1007/s00125-007-0897-4. Epub 2007 Dec 6. PMID: 18058083.
8. Targher G, Chonchol M, Zoppini G, Abaterusso C, Bonora E. Risk of chronic kidney disease in patients with non-alcoholic fatty liver disease: is there a link? J Hepatol. 2011 May;54(5):1020-9. doi: 10.1016/j.jhep.2010.11.007. Epub 2010 Nov 17. PMID: 21145850.
9. Goyal R, Singhal M, Jialal I. Type 2 Diabetes. [Updated 2023 Jun 23]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK513253/
10. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2009 Jan;32 Suppl 1(Suppl 1):S62-7. doi: 10.2337/dc09-S062. PMID: 19118289; PMCID: PMC2613584.
11. Solis-Herrera C, Triplitt C, Reasner C, et al. Classification of Diabetes Mellitus. [Updated 2018 Feb 24]. In: Feingold KR, Adler RA, Ahmed SF, et al., editors. Endotext [Internet]. South Dartmouth (MA): MDText.com, Inc.; 2000-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK279119/
12. Popoviciu MS, Kaka N, Sethi Y, Patel N, Chopra H, Cavalu S. Type 1 Diabetes Mellitus and Autoimmune Diseases: A Critical Review of the Association and the Application of Personalized Medicine. J Pers Med. 2023 Feb 26;13(3):422. doi: 10.3390/jpm13030422. PMID: 36983604; PMCID: PMC10056161.
13. Banday MZ, Sameer AS, Nissar S. Pathophysiology of diabetes: An overview. Avicenna J Med. 2020 Oct 13;10(4):174-188. doi: 10.4103/ajm.ajm_53_20. PMID: 33437689; PMCID: PMC7791288.
14. Gieroba B, Kryska A, Sroka-Bartnicka A. Type 2 diabetes mellitus - conventional therapies and future perspectives in innovative treatment. Biochem Biophys Rep. 2025 May 2;42:102037. doi: 10.1016/j.bbrep.2025.102037. PMID: 40395625; PMCID: PMC12090304.
15. Merz KE, Thurmond DC. Role of Skeletal Muscle in Insulin Resistance and Glucose Uptake. Compr Physiol. 2020 Jul 8;10(3):785-809. doi: 10.1002/cphy.c190029. PMID: 32940941; PMCID: PMC8074531.
16. Sosale A, Prasanna Kumar KM, Sadikot SM, Nigam A, Bajaj S, Zargar AH, Singh SK. Chronic complications in newly diagnosed patients with Type 2 diabetes mellitus in India. Indian J Endocrinol Metab. 2014 May;18(3):355-60. doi: 10.4103/2230- 8210.131184. PMID: 24944931; PMCID: PMC4056135.
17. Kunarathnam V, Vadakekut ES, Mahdy H. Gestational Diabetes. [Updated 2025 Sep 15]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 Jan- . Available from: https://www.ncbi.nlm.nih.gov/books/NBK545196/
18. Plows JF, Stanley JL, Baker PN, Reynolds CM, Vickers MH. The Pathophysiology of Gestational Diabetes Mellitus. Int J Mol Sci. 2018 Oct 26;19(11):3342. doi: 10.3390/ijms19113342. PMID: 30373146; PMCID: PMC6274679.
19. Wang D, Jiao Y. Pancreatogenic diabetes: Pathophysiology, diagnosis, and management challenges. World J Gastrointest Surg. 2025 Nov 27;17(11):112204. doi: 10.4240/wjgs.v17.i11.112204. PMID: 41357647; PMCID: PMC12678996.
20. Chauhan S, Khatib MN, Ballal S, Bansal P, Bhopte K, Gaidhane AM, Tomar BS, Ashraf A, Kumar MR, Chauhan AS, Shabil M, Jena D, Bushi G, Satapathy P, Jain L, Jaiswal V, Pant M. The rising burden of diabetes and state-wise variations in India: insights from the Global Burden of Disease Study 1990-2021 and projections to 2031. Front Endocrinol (Lausanne). 2025 May 12;16:1505143. doi: 10.3389/fendo.2025.1505143. PMID: 40421244; PMCID: PMC12104079.
21. Galicia-Garcia U, Benito-Vicente A, Jebari S, Larrea-Sebal A, Siddiqi H, Uribe KB, Ostolaza H, Martín C. Pathophysiology of Type 2 Diabetes Mellitus. Int J Mol Sci. 2020 Aug 30;21(17):6275. doi: 10.3390/ijms21176275. PMID: 32872570; PMCID: PMC7503727.
22. Vithian K, Hurel S. Microvascular complications: pathophysiology and management. Clin Med (Lond). 2010 Oct;10(5):505-9. doi: 10.7861/clinmedicine.10-5-505. PMID: 21117389; PMCID: PMC4952418.
23. Rout P, Jialal I. Diabetic Nephropathy. [Updated 2025 Jan 9]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK534200/
24. Shukla UV, Tripathy K. Diabetic Retinopathy. [Updated 2023 Aug 25]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK560805/
25. Bodman MA, Dreyer MA, Varacallo MA. Diabetic Peripheral Neuropathy. [Updated 2024 Feb 25]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK442009/
26. Feldman EL, Callaghan BC, Pop-Busui R, Zochodne DW, Wright DE, Bennett DL, Bril V, Russell JW, Viswanathan V. Diabetic neuropathy. Nat Rev Dis Primers. 2019 Jun 13;5(1):42. doi: 10.1038/s41572-019-0097-9. PMID: 31197183; PMCID: PMC7096070.
27. Huang D, Refaat M, Mohammedi K, Jayyousi A, Al Suwaidi J, Abi Khalil C. Macrovascular Complications in Patients with Diabetes and Prediabetes. Biomed Res Int. 2017;2017:7839101. doi: 10.1155/2017/7839101. Epub 2017 Nov 7. PMID: 29238721; PMCID: PMC5697393.
28. Ye J, Li L, Wang M, Ma Q, Tian Y, Zhang Q, Liu J, Li B, Zhang B, Liu H, Sun G. Diabetes Mellitus Promotes the Development of Atherosclerosis: The Role of NLRP3. Front Immunol. 2022 Jun 29;13:900254. doi: 10.3389/fimmu.2022.900254. PMID: 35844498; PMCID: PMC9277049.
29. Soyoye DO, Abiodun OO, Ikem RT, Kolawole BA, Akintomide AO. Diabetes and peripheral artery disease: A review. World J Diabetes. 2021 Jun 15;12(6):827-838. doi: 10.4239/wjd.v12.i6.827. PMID: 34168731; PMCID: PMC8192257.
30. Singh VP, Bali A, Singh N, Jaggi AS. Advanced glycation end products and diabetic complications. Korean J Physiol Pharmacol. 2014 Feb;18(1):1-14. doi: 10.4196/kjpp.2014.18.1.1. Epub 2014 Feb 13. PMID: 24634591; PMCID: PMC3951818.
31. Hussain A. Chronic hyperglycemia and cardiovascular dysfunction: an in-depth exploration of metabolic and cellular pathways in type 2 diabetes mellitus. Cardiovasc Diabetol Endocrinol Rep. 2025 Dec 12;11(1):39. doi: 10.1186/s40842-025-00247-3. PMID: 41382274; PMCID: PMC12699840.
32. Galaviz KI, Narayan KMV, Lobelo F, Weber MB. Lifestyle and the Prevention of Type 2 Diabetes: A Status Report. Am J Lifestyle Med. 2015 Nov 24;12(1):4-20. doi: 10.1177/1559827615619159. PMID: 30202378; PMCID: PMC6125024.
33. Giannakogeorgou, Anna et al. "Diabetes mellitus as a multisystem disease: understanding subtypes, complications, and the link with steatotic liver diseases in humans." *Hormones (Athens, Greece)*, 10.1007/s42000-025-00701-y. 1 Aug. 2025, doi:10.1007/s42000-025-00701-y
34. Hameed I, Masoodi SR, Mir SA, Nabi M, Ghazanfar K, Ganai BA. Type 2 diabetes mellitus: From a metabolic disorder to an inflammatory condition. World J Diabetes. 2015 May 15;6(4):598-612. doi: 10.4239/wjd.v6.i4.598. PMID: 25987957; PMCID: PMC4434080.
35. Vancells Lujan P, Viñas Esmel E, Sacanella Meseguer E. Overview of Non-Alcoholic Fatty Liver Disease (NAFLD) and the Role of Sugary Food Consumption and Other Dietary Components in Its Development. Nutrients. 2021 Apr 24;13(5):1442. doi: 10.3390/nu13051442. PMID: 33923255; PMCID: PMC8145877.
36. Pouwels S, Sakran N, Graham Y, Leal A, Pintar T, Yang W, Kassir R, Singhal R, Mahawar K, Ramnarain D. Non-alcoholic fatty liver disease (NAFLD): a review of pathophysiology, clinical management and effects of weight loss. BMC Endocr Disord. 2022 Mar 14;22(1):63. doi: 10.1186/s12902-022-00980-1. PMID: 35287643; PMCID: PMC8919523.
37. Zhong H, Dong J, Zhu L, Mao J, Dong J, Zhao Y, Zou Y, Guo M, Ding G. Non-alcoholic fatty liver disease: pathogenesis and models. Am J Transl Res. 2024 Feb 15;16(2):387- 399. doi: 10.62347/KMSA5983. PMID: 38463579; PMCID: PMC10918142.
38. Somnay K, Wadgaonkar P, Sridhar N, Roshni P, Rao N, Wadgaonkar R. Liver Fibrosis Leading to Cirrhosis: Basic Mechanisms and Clinical Perspectives. Biomedicines. 2024 Sep 30;12(10):2229. doi: 10.3390/biomedicines12102229. PMID: 39457542; PMCID: PMC11505165.
39. Yu J, Marsh S, Hu J, Feng W, Wu C. The Pathogenesis of Nonalcoholic Fatty Liver Disease: Interplay between Diet, Gut Microbiota, and Genetic Background. Gastroenterol Res Pract. 2016;2016:2862173. doi: 10.1155/2016/2862173. Epub 2016 May 9. PMID: 27247565; PMCID: PMC4876215.
40. Pal SC, Méndez-Sánchez N. Insulin resistance and adipose tissue interactions as the cornerstone of metabolic (dysfunction)-associated fatty liver disease pathogenesis. World J Gastroenterol. 2023 Jul 7;29(25):3999-4008. doi: 10.3748/wjg.v29.i25.3999. PMID: 37476582; PMCID: PMC10354585.
41. Geng Y, Faber KN, de Meijer VE, Blokzijl H, Moshage H. How does hepatic lipid accumulation lead to lipotoxicity in non-alcoholic fatty liver disease? Hepatol Int. 2021 Feb;15(1):21-35. doi: 10.1007/s12072-020-10121-2. Epub 2021 Feb 6. PMID: 33548031; PMCID: PMC7886759.
42. Allameh A, Niayesh-Mehr R, Aliarab A, Sebastiani G, Pantopoulos K. Oxidative Stress in Liver Pathophysiology and Disease. Antioxidants (Basel). 2023 Aug 22;12(9):1653. doi: 10.3390/antiox12091653. PMID: 37759956; PMCID: PMC10525124.
43. Stojsavljević S, Gomerčić Palčić M, Virović Jukić L, Smirčić Duvnjak L, Duvnjak M. Adipokines and proinflammatory cytokines, the key mediators in the pathogenesis of nonalcoholic fatty liver disease. World J Gastroenterol. 2014 Dec 28;20(48):18070-91. doi: 10.3748/wjg.v20.i48.18070. PMID: 25561778; PMCID: PMC4277948.
44. Jonas W, Schürmann A. Genetic and epigenetic factors determining NAFLD risk. Mol Metab. 2021 Aug;50:101111. doi: 10.1016/j.molmet.2020.101111. Epub 2020 Nov 5. PMID: 33160101; PMCID: PMC8324682.
45. Dharmalingam M, Yamasandhi PG. Nonalcoholic Fatty Liver Disease and Type 2 Diabetes Mellitus. Indian J Endocrinol Metab. 2018 May-Jun;22(3):421-428. doi: 10.4103/ijem.IJEM_585_17. PMID: 30090738; PMCID: PMC6063173.
46. Sharma P, Arora A. Clinical presentation of alcoholic liver disease and non-alcoholic fatty liver disease: spectrum and diagnosis. Transl Gastroenterol Hepatol. 2020 Apr 5;5:19. doi: 10.21037/tgh.2019.10.02. PMID: 32258523; PMCID: PMC7063523.
47. Kasper P, Martin A, Lang S, Kütting F, Goeser T, Demir M, Steffen HM. NAFLD and cardiovascular diseases: a clinical review. Clin Res Cardiol. 2021 Jul;110(7):921-937. doi: 10.1007/s00392-020-01709-7. Epub 2020 Jul 21. PMID: 32696080; PMCID: PMC8238775.
48. Metrakos P, Nilsson T. Non-alcoholic fatty liver disease--a chronic disease of the 21^st^ century. J Biomed Res. 2018 Sep 29;32(5):327-335. doi: 10.7555/JBR.31.20160153. PMID: 28550272; PMCID: PMC6163117.
49. Weir MR. Microalbuminuria in type 2 diabetics: an important, overlooked cardiovascular risk factor. J Clin Hypertens (Greenwich). 2004 Mar;6(3):134-41; quiz 142-3. doi: 10.1111/j.1524-6175.2004.02524.x. PMID: 15010646; PMCID: PMC8109345.
50. Ritz E, Schmieder RE, Pollock CA. Renal protection in diabetes: lessons from ONTARGET. Cardiovasc Diabetol. 2010 Oct 1;9:60. doi: 10.1186/1475-2840-9-60. PMID: 20920303; PMCID: PMC2959007.
51. Toto RD. Microalbuminuria: definition, detection, and clinical significance. J Clin Hypertens (Greenwich). 2004 Nov;6(11 Suppl 3):2-7. doi: 10.1111/j.1524- 6175.2004.4064.x. PMID: 15538104; PMCID: PMC8109505.
52. Satchell SC, Tooke JE. What is the mechanism of microalbuminuria in diabetes: a role for the glomerular endothelium? Diabetologia. 2008 May;51(5):714-25. doi: 10.1007/s00125-008-0961-8. Epub 2008 Mar 18. PMID: 18347777; PMCID: PMC2292427.
53. Al-Maskari F, El-Sadig M, Obineche E. Prevalence and determinants of microalbuminuria among diabetic patients in the United Arab Emirates. BMC Nephrol. 2008 Jan 29;9:1. doi: 10.1186/1471-2369-9-1. PMID: 18230135; PMCID: PMC2270810.
54. Feldt-Rasmussen, B. "Microalbuminuria, endothelial dysfunction and cardiovascular risk." *Diabetes & metabolism* vol. 26 Suppl 4 (2000): 64-6.
55. Knudsen, Søren Tang et al. "Screening for microalbuminuria in patients with type 2 diabetes is incomplete in general practice." *Danish medical journal* vol. 59,9 (2012): A4502.
56. Mikolasevic I, Milic S, Turk Wensveen T, Grgic I, Jakopcic I, Stimac D, Wensveen F, Orlic L. Nonalcoholic fatty liver disease - A multisystem disease? World J Gastroenterol. 2016 Nov 21;22(43):9488-9505. doi: 10.3748/wjg.v22.i43.9488. PMID: 27920470; PMCID: PMC5116593.
57. Kasapoglu, Benan et al. "Increased microalbuminuria prevalence among patients with nonalcoholic fatty liver disease." *Renal failure* vol. 38,1 (2016): 15-9. doi:10.3109/0886022X.2015.1106845
58. Rinaldi L, Pafundi PC, Galiero R, Caturano A, Morone MV, Silvestri C, Giordano M, Salvatore T, Sasso FC. Mechanisms of Non-Alcoholic Fatty Liver Disease in the Metabolic Syndrome. A Narrative Review. Antioxidants (Basel). 2021 Feb 10;10(2):270. doi: 10.3390/antiox10020270. PMID: 33578702; PMCID: PMC7916383.
59. Umbro I, Baratta F, Angelico F, Del Ben M. Nonalcoholic Fatty Liver Disease and the Kidney: A Review. Biomedicines. 2021 Oct 1;9(10):1370. doi: 10.3390/biomedicines9101370. PMID: 34680486; PMCID: PMC8533178.
60. Glassock RJ. Is the presence of microalbuminuria a relevant marker of kidney disease? Curr Hypertens Rep. 2010 Oct;12(5):364-8. doi: 10.1007/s11906-010-0133-3. PMID: 20686930; PMCID: PMC2941636.
61. Singh A, Satchell SC. Microalbuminuria: causes and implications. Pediatr Nephrol. 2011 Nov;26(11):1957-65. doi: 10.1007/s00467-011-1777-1. Epub 2011 Feb 8. PMID: 21301888; PMCID: PMC3178015.
62. Koroshi A. Microalbuminuria, is it so important? Hippokratia. 2007 Jul;11(3):105-7. PMID: 19582202; PMCID: PMC2658722.
63. Kang SH, Cho KH, Do JY. Non-alcoholic fatty liver disease is associated with low- grade albuminuria in men without diabetes mellitus. Int J Med Sci. 2019 Jan 1;16(2):285-291. doi: 10.7150/ijms.28264. PMID: 30745809; PMCID: PMC6367539.
64. Viberti, G C et al. "Microalbuminuria as a predictor of clinical nephropathy in insulin- dependent diabetes mellitus." *Lancet (London, England)* vol. 1,8287 (1982): 1430-2. doi:10.1016/s0140-6736(82)92450-3
65. Lane, James T. "Microalbuminuria as a marker of cardiovascular and renal risk in type 2 diabetes mellitus: a temporal perspective." *American journal of physiology. Renal physiology* vol. 286,3 (2004): F442-50. doi:10.1152/ajprenal.00247.2003
66. Bennett, P H et al. "Screening and management of microalbuminuria in patients with diabetes mellitus: recommendations to the Scientific Advisory Board of the National Kidney Foundation from an ad hoc committee of the Council on Diabetes Mellitus of the National Kidney Foundation." *American journal of kidney diseases : the official journal of the National Kidney Foundation* vol. 25,1 (1995): 107-12. doi:10.1016/0272- 6386(95)90636-3
67. Tobe SW, McFarlane PA, Naimark DM. Microalbuminuria in diabetes mellitus. CMAJ. 2002 Sep 3;167(5):499-503. PMID: 12240818; PMCID: PMC121969.
68. Prasad RM, Bali A, Tikaria R. Microalbuminuria. [Updated 2023 May 30]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK563255/
69. Varghese A, Deepa R, Rema M, Mohan V. Prevalence of microalbuminuria in type 2 diabetes mellitus at a diabetes centre in southern India. Postgrad Med J. 2001 Jun;77(908):399-402. doi: 10.1136/pmj.77.908.399. PMID: 11375456; PMCID: PMC1742050.
70. Kalra, Sanjay et al. "Study of prevalence of nonalcoholic fatty liver disease (NAFLD) in type 2 diabetes patients in India (SPRINT)." *The Journal of the Association of Physicians of India* vol. 61,7 (2013): 448-53.
71. Heidari Z, Gharebaghi A. Prevalence of Non Alcoholic Fatty Liver Disease and its Association with Diabetic Nephropathy in Patients with Type 2 Diabetes Mellitus. J Clin Diagn Res. 2017 May;11(5):OC04-OC07. doi: 10.7860/JCDR/2017/25931.9823. Epub 2017 May 1. PMID: 28658824; PMCID: PMC5483726.
72. Alsabaani AA, Mahfouz AA, Awadalla NJ, Musa MJ, Al Humayed SM. Non-Alcoholic Fatty Liver Disease among Type-2 Diabetes Mellitus Patients in Abha City, South Western Saudi Arabia. Int J Environ Res Public Health. 2018 Nov 11;15(11):2521. doi: 10.3390/ijerph15112521. PMID: 30423871; PMCID: PMC6266142.
73. Amin, Reham F et al. "Serum Ferritin level, microalbuminuria and non-alcoholic fatty liver disease in type 2 diabetic patients." *Diabetes & metabolic syndrome* vol. 13,3 (2019): 2226-2229. doi:10.1016/j.dsx.2019.05.030
74. Athyros VG, Polyzos SA, Kountouras J, Katsiki N, Anagnostis P, Doumas M, Mantzoros CS. Non-Alcoholic Fatty Liver Disease Treatment in Patients with Type 2 Diabetes Mellitus; New Kids on the Block. Curr Vasc Pharmacol. 2020;18(2):172-181. doi: 10.2174/1570161117666190405164313. PMID: 30961499.
75. Bansal A, Sikri T, Nayyar SB. Evaluation of renal microvascular damage by measuring microalbuminuria in nonalcoholic fatty liver disease -- a study from Punjab, India. J Evid Based Med Healthc 2021;8(28):2497-2502. DOI: 10.18410/jebmh/2021/462
76. Han E, Kim MK, Jang BK, Kim HS. Albuminuria Is Associated with Steatosis Burden in Patients with Type 2 Diabetes Mellitus and Nonalcoholic Fatty Liver Disease. Diabetes Metab J. 2021 Sep;45(5):698-707. doi: 10.4093/dmj.2020.0118. Epub 2021 Feb 2. PMID: 33517613; PMCID: PMC8497925.
77. Asghar S, Asghar S, Mahmood T, Bukhari SMH, Mumtaz MH, Rasheed A. Microalbuminuria as the Tip of Iceberg in Type 2 Diabetes Mellitus: Prevalence, Risk Factors, and Associated Diabetic Complications. Cureus. 2023 Aug 9;15(8):e43190. doi: 10.7759/cureus.43190. PMID: 37692611; PMCID: PMC10485877.
78. Wahiduzzaman M, Ferdous NE, Haque KMM, Kabir AKMS, Siddiki MA, Hossain MT, Rahman QA, Rahman AIU, Kibria AHMG. Assessment of Non-alcoholic Fatty Liver Disease and Level of Risk of Fibrosis in Diabetic and Non-diabetic Individuals. Cureus. 2024 Dec 21;16(12):e76162. doi: 10.7759/cureus.76162. PMID: 39840152; PMCID: PMC11747980.
79. Shao J, Zhou M, Xie X, Lan S. Association between fatty liver disease and risk of microvascular complications in Type-2 diabetes mellitus: A systematic review and meta-analysis. Pak J Med Sci. 2025 Mar;41(3):902-909. doi: 10.12669/pjms.41.3.11362. PMID: 40103889; PMCID: PMC11911733.