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Original Investigation|Articles in Press

Sex-Specific Computed Tomography Abdominal Fat and Skeletal Muscle Characteristics in Type 2 Diabetic Retinopathy Patients With/Without Comorbid Diabetic Kidney Disease

Published:February 22, 2023DOI:https://doi.org/10.1016/j.acra.2023.01.033

      Rationale and Objectives

      To investigate differences in sex-specific computed tomography abdominal fat and skeletal muscle (SM) characteristics between type 2 diabetic retinopathy (DR) patients with and without diabetic kidney disease (DKD).

      Materials and Methods

      This retrospective study included type 2 diabetes mellitus DR patients with/without DKD between January 2019 and July 2021. Visceral adipose tissue (VAT), subcutaneous adipose tissue, perirenal adipose tissue (PAT), intramuscular adipose tissue, and SM areas were measured. Univariate and multivariate logistic regression analyses were used to analyze risk factors for DKD. Correlation and multiple linear regression analyses were used to clarify the association between computed tomography abdominal fat, SM characteristics, and cystatin C.

      Results

      Two hundred and forty-one patients were enrolled and divided into DR with DKD group (n = 142) and DR without DKD group (n = 99). In men, hypertension (OR: 5.21; 95%CI: 1.93–14.05; p = 0.001), diastolic pressure (OR: 1.07; 95%CI: 1.01–1.12; p = 0.011), hemoglobin (OR: 0.94; 95%CI: 0.92–0.97; p < 0.001) and PAT attenuation value (OR: 1.09; 95%CI: 1.01–1.17; p = 0.026) were independent risk factors for DKD progression in DR patients, while the VAT index (VATI) (OR: 1.03; 95%CI: 1.01–1.05; p = 0.014) was an independent risk factor for female patients. Multiple linear regression analysis revealed significant correlations between hypertension (β = 0.22, p = 0.002) and hemoglobin (β = -0.53, p < 0.001) with cystatin C in men, and a significant correlation between VATI and cystatin C (β = 0.35, p = 0.037) in women after adjustment for confounders.

      Conclusion

      Female DR patients with elevated VAT level may suffer from a higher risk of DKD than that in male patients.

      KEY WORDS

      Abbreviations:

      T2DM (type 2 diabetes mellitus), DR (diabetic retinopathy), DKD (diabetic kidney disease), eGFR (estimated glomerular filtration rate), GHBA1c (glycosylated hemoglobin), CT (computed tomography), VAT (visceral adipose tissue), VATI (visceral adipose tissue index), SAT (subcutaneous adipose tissue), SATI (subcutaneous adipose tissue index), PAT (perirenal adipose tissue), PATI (perirenal adipose tissue index), IMAT (intramuscular adipose tissue), IMATI (intramuscular adipose tissue index), SM (skeletal muscle), SMI (skeletal muscle index), UACR (urine albumin-to-creatinine ratio), Scr (serum creatinine), ICCs (intra-class correlation coefficients), CIs (confidence intervals), OR (odds ratios), TAT (thrombin-antithrombin III complex), COVID-19 (Coronavirus disease 2019)
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      REFERENCES

        • Liu J.
        • Ren Z.H.
        • Qiang H.
        • et al.
        Trends in the incidence of diabetes mellitus: results from the Global Burden of Disease Study 2017 and implications for diabetes mellitus prevention.
        BMC Public Health. 2020; 20: 1415
        • Doshi S.M.
        • Friedman A.N.
        diagnosis and management of type 2 diabetic kidney disease.
        Clin J Am Soc Nephrol. 2017; 12: 1366-1373
        • He F.
        • Xia X.
        • Wu X.F.
        • et al.
        Diabetic retinopathy in predicting diabetic nephropathy in patients with type 2 diabetes and renal disease: a meta-analysis.
        Diabetologia. 2013; 56: 457-466
        • Kramer C.K.
        • Rodrigues T.C.
        • Canani L.H.
        • et al.
        Diabetic retinopathy predicts all-cause mortality and cardiovascular events in both type 1 and 2 diabetes: meta-analysis of observational studies.
        Diabetes Care. 2011; 34: 1238-1244
        • Takao T.
        • Suka M.
        • Yanagisawa H.
        • et al.
        Combined effect of diabetic retinopathy and diabetic kidney disease on all-cause, cancer, vascular and non-cancer non-vascular mortality in patients with type 2 diabetes: a real-world longitudinal study.
        J Diabetes Investig. 2020; 11: 1170-1180
        • Tong P.C.
        • Kong A.P.
        • So W.Y.
        • et al.
        Interactive effect of retinopathy and macroalbuminuria on all-cause mortality, cardiovascular and renal end points in Chinese patients with Type 2 diabetes mellitus.
        Diabet Med. 2007; 24: 741-746
        • Penno G.
        • Solini A.
        • Zoppini G.
        • et al.
        Rate and determinants of association between advanced retinopathy and chronic kidney disease in patients with type 2 diabetes: the renal insufficiency and cardiovascular events (RIACE) Italian multicenter study.
        Diabetes Care. 2012; 35: 2317-2323
        • Yun K.J.
        • Kim H.J.
        • Kim M.K.
        • et al.
        Risk factors for the development and progression of diabetic kidney disease in patients with type 2 diabetes mellitus and advanced diabetic retinopathy.
        Diabetes Metab J. 2016; 40: 473-481
        • Magri C.J.
        • Calleja N.
        • Buhagiar G.
        • et al.
        Factors associated with diabetic nephropathy in subjects with proliferative retinopathy.
        Int Urol Nephrol. 2012; 44: 197-206
        • Cho A.
        • Park H.C.
        • Lee Y.K.
        • et al.
        Progression of diabetic retinopathy and declining renal function in patients with type 2 diabetes.
        J Diabetes Res. 2020; 20208784139
        • Torres S.
        • Fabersani E.
        • Marquez A.
        • et al.
        Adipose tissue inflammation and metabolic syndrome. The proactive role of probiotics.
        Eur J Nutr. 2019; 58: 27-43
        • Hall J.E.
        • Mouton A.J.
        • da Silva A.A.
        • et al.
        Obesity, kidney dysfunction, and inflammation: interactions in hypertension.
        Cardiovasc Res. 2021; 117: 1859-1876
        • Mourtzakis M.
        • Prado C.M.
        • Lieffers J.R.
        • et al.
        A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care.
        Appl Physiol Nutr Metab. 2008; 33: 997-1006
        • Palmer B.F.
        • Clegg D.J.
        The sexual dimorphism of obesity.
        Mol Cell Endocrinol. 2015; 402: 113-119
        • Volpato S.
        • Bianchi L.
        • Lauretani F.
        • et al.
        Role of muscle mass and muscle quality in the association between diabetes and gait speed.
        Diabetes Care. 2012; 35: 1672-1679
        • Wilkinson C.P.
        • Ferris 3rd, F.L.
        • Klein R.E.
        • et al.
        Proposed international clinical diabetic retinopathy and diabetic macular edema disease severity scales.
        Ophthalmology. 2003; 110: 1677-1682
        • McGrath K.
        • Edi R.
        Diabetic kidney disease: diagnosis, treatment, and prevention.
        Am Fam Physician. 2019; 99: 751-759
        • Levey A.S.
        • Stevens L.A.
        • Schmid C.H.
        • et al.
        A new equation to estimate glomerular filtration rate.
        Ann Intern Med. 2009; 150: 604-612
        • Schweitzer L.
        • Geisler C.
        • Pourhassan M.
        • et al.
        What is the best reference site for a single MRI slice to assess whole-body skeletal muscle and adipose tissue volumes in healthy adults?.
        Am J Clin Nutr. 2015; 102: 58-65
        • Steele S.
        • Lin F.
        • Le T.L.
        • et al.
        Segmentation and linear measurement for body composition analysis using Slice-O-Matic and Horos.
        J Vis Exp. 2021; 21 (PMID: 33818558)https://doi.org/10.3791/61674
        • Fujiwara N.
        • Nakagawa H.
        • Kudo Y.
        • et al.
        Sarcopenia, intramuscular fat deposition, and visceral adiposity independently predict the outcomes of hepatocellular carcinoma.
        J Hepatol. 2015; 63: 131-140
        • Pacquelet B.
        • Morello R.
        • Pelage J.P.
        • et al.
        Abdominal adipose tissue quantification and distribution with CT: prognostic value for surgical and oncological outcome in patients with rectal cancer.
        Eur Radiol. 2022; 32: 6258-6269
        • Du Y.
        • Yang W.
        • Liu H.
        • et al.
        Perirenal fat as a new independent prognostic factor in patients with surgically treated clear cell renal cell carcinoma.
        Clin Genitourin Cancer. 2022; 20: e75-e80
        • Shrout P.E.
        • Fleiss J.L.
        Intraclass correlations: uses in assessing rater reliability.
        Psychol Bull. 1979; 86: 420-428
        • Devereaux P.J.
        • Lamy A.
        • Chan M.T.V.
        • et al.
        High-sensitivity troponin i after cardiac surgery and 30-day mortality.
        N Engl J Med. 2022; 386: 827-836
        • Norman G.
        • Monteiro S.
        • Salama S.
        Sample size calculations: should the emperor's clothes be off the peg or made to measure?.
        BMJ. 2012; 345: e5278
        • Hopkins W.G.
        • Marshall S.W.
        • Batterham A.M.
        • Hanin J.
        Progressive statistics for studies in sports medicine and exercise science.
        Med Sci Sports Exerc. 2009; 41: 3-13
        • Hanai K.
        • Babazono T.
        • Nyumura I.
        • et al.
        Involvement of visceral fat in the pathogenesis of albuminuria in patients with type 2 diabetes with early stage of nephropathy.
        Clin Exp Nephrol. 2010; 14: 132-136
        • Delaney K.Z.
        • Santosa S.
        Sex differences in regional adipose tissue depots pose different threats for the development of Type 2 diabetes in males and females.
        Obes Rev. 2022; 23: e13393
        • Zhu J.
        • Zhou W.
        • Xie Z.
        • et al.
        Impact of sex and menopausal status on the association between epicardial adipose tissue and diastolic function in patients with type 2 diabetes mellitus.
        Acad Radiol. 2022; https://doi.org/10.1016/j.acra.2022.08.017
        • De Cosmo S.
        • Menzaghi C.
        • Prudente S.
        • et al.
        Role of insulin resistance in kidney dysfunction: insights into the mechanism and epidemiological evidence.
        Nephrol Dial Transplant. 2013; 28: 29-36
        • Asakawa H.
        • Tokunaga K.
        • Kawakami F.
        Elevation of fibrinogen and thrombin-antithrombin III complex levels of type 2 diabetes mellitus patients with retinopathy and nephropathy.
        J Diabetes Complications. 2000; 14: 121-126
        • Wang K.
        • Xu W.
        • Zha B.
        • et al.
        Fibrinogen to albumin ratio as an independent risk factor for type 2 diabetic kidney disease.
        Diabetes Metab Syndr Obes. 2021; 14: 4557-4567
        • Rigalleau V.
        • Beauvieux M.C.
        • Moigne F.Le
        • et al.
        Cystatin C improves the diagnosis and stratification of chronic kidney disease, and the estimation of glomerular filtration rate in diabetes.
        Diabetes Metab. 2008; 34: 482-489
        • Foster M.C.
        • Hwang S.J.
        • Porter S.A.
        • et al.
        Fatty kidney, hypertension, and chronic kidney disease: the Framingham Heart Study.
        Hypertension. 2011; 58: 784-790
        • Spit K.A.
        • Muskiet M.H.A.
        • Tonneijck L.
        • et al.
        Renal sinus fat and renal hemodynamics: a cross-sectional analysis.
        Magma. 2020; 33: 73-80
        • Han N.Y.
        • Sung D.J.
        • Kim M.J.
        • et al.
        Perirenal fat stranding on CT: is there an association with bladder outlet obstruction?.
        Br J Radiol. 2016; 8920160195
        • Fang Y.
        • Xu Y.
        • Yang Y.
        • et al.
        The relationship between perirenal fat thickness and reduced glomerular filtration rate in patients with type 2 diabetes.
        J Diabetes Res. 2020; 20206076145
        • Geraci G.
        • Zammuto M.M.
        • Mattina A.
        • et al.
        Para-perirenal distribution of body fat is associated with reduced glomerular filtration rate regardless of other indices of adiposity in hypertensive patients.
        J Clin Hypertens (Greenwich). 2018; 20: 1438-1446
        • Miljkovic I.
        • Kuipers A.L.
        • Cvejkus R.
        • et al.
        Myosteatosis increases with aging and is associated with incident diabetes in African ancestry men.
        Obesity (Silver Spring). 2016; 24: 476-482
        • Kitagawa F.
        • Ogawa M.
        • Yoshiko A.
        • et al.
        Factors related to trunk intramuscular adipose tissue content: a comparison of younger and older men.
        Exp Gerontol. 2022; 168111922
        • Song J.J.
        • Ma Z.
        • Wang J.
        • et al.
        Gender Differences in Hypertension.
        J Cardiovasc Transl Res. 2020; 13: 47-54
        • Zhang Z.Z.
        • Wang W.
        • Jin H.Y.
        • et al.
        Apelin Is a Negative Regulator of Angiotensin II-Mediated Adverse Myocardial Remodeling and Dysfunction.
        Hypertension. 2017; 70: 1165-1175
        • Zhong J.
        • Basu R.
        • Guo D.
        • et al.
        Angiotensin-converting enzyme 2 suppresses pathological hypertrophy, myocardial fibrosis, and cardiac dysfunction.
        Circulation. 2010; 122 (18 p following 728): 717-728
        • Adetunji O.R.
        • Mani H.
        • Olujohungbe A.
        • et al.
        Microalbuminuric anaemia'–the relationship between haemoglobin levels and albuminuria in diabetes'.
        Diabetes Res Clin Pract. 2009; 85: 179-182
        • Nath K.A.
        Tubulointerstitial changes as a major determinant in the progression of renal damage.
        Am J Kidney Dis. 1992; 20: 1-17
        • Sahai A.
        • Mei C.
        • Schrier R.W.
        • et al.
        Mechanisms of chronic hypoxia-induced renal cell growth.
        Kidney Int. 1999; 56: 1277-1281
        • Yamanouchi M.
        • Furuichi K.
        • Shimizu M.
        • et al.
        Serum hemoglobin concentration and risk of renal function decline in early stages of diabetic kidney disease: a nationwide, biopsy-based cohort study.
        Nephrol Dial Transplant. 2022; 37: 489-497
        • Weiner D.E.
        • Tighiouart H.
        • Vlagopoulos P.T.
        • et al.
        Effects of anemia and left ventricular hypertrophy on cardiovascular disease in patients with chronic kidney disease.
        J Am Soc Nephrol. 2005; 16: 1803-1810
        • Astor B.C.
        • Muntner P.
        • Levin A.
        • et al.
        Association of kidney function with anemia: the Third National Health and Nutrition Examination Survey (1988-1994).
        Arch Intern Med. 2002; 162: 1401-1408
        • Burns J.E.
        • Yao J.
        • Chalhoub D.
        • et al.
        A machine learning algorithm to estimate sarcopenia on abdominal CT.
        Acad Radiol. 2020; 27: 311-320
        • Kim S.G.
        Quantitative imaging of body fat distribution in the era of deep learning.
        Acad Radiol. 2021; 28: 1488-1490