The constellation of abnormalities caused by insulin deficiency is called Diabetes mellitus (DM). Greek and Roman physicians used the term to refer to conditions in which the cardinal finding was a large urine volume, and two types were distinguished. “Diabetes mellitus” in which the urine tasted sweet, and “Diabetes insipidus” in which the urine had little taste. Diabetes mellitus is characterized by polyuria, polydipsia, and weight loss in spite of polyphagia, hyperglycemia, glycosuria, ketosis, acidosis and coma.

Diabetes mellitus (DM) is a metabolic disorder characterized by chronic hyperglycemia with derangement of carbohydrate, fat, and protein metabolism due to absolute or relative deficiency of insulin secretion and action, or both. DM, especially type-2 DM, is a serious general medical issue which has arrived at scourge extents because of the quickly expanding paces of this ailment around the world. Target organ confusions, auxiliary to diabetes, are one of the most significant restorative worries of right now. According to a recent World Health Organization (WHO) report, India, with 32 million diabetic individuals, currently has the highest incidence of diabetes worldwide; this may be increased to 80 million by the year 2030 [1] Inflammation is a defensive mechanism of the body. Be that as it may, in interminable illnesses like, diabetes mellitus, hypertension, asthma and so forth., this defensive system turns into a significant component for movement of sickness. In Type 2 diabetes mellitus the diminishing β cell mass is likewise connected with glucose harmfulness interceded through IL-1β incited apoptosis. There are numerous examinations accentuating the nearness and significance of the fiery part in the pathogenesis of Diabetes mellitus. A very important role is played by adipose tissue, which releases various pro-inflammatory cytokines, such as, tumor necrosis factor alpha (TNF-α), interleukin-6 (IL-6), C Reactive Protein (hs CRP) [2,3,4]. Hyperglycemia produces reactive oxygen species (ROS), which in turn cause damage to the cells in many ways. Damage to the cells ultimately results in secondary complications in diabetes mellitus[5]. Increased oxidative stress is a widely accepted participant in the development and progression of diabetes and its complications [6]. A well-established correlation exists between the development of macro and micro vascular disease in diabetes mellitus [7]. In diabetics, the hyperglycemic status was the primary cause for including oxidative stress. Further increase in oxidative stress is due to autoxidation of glucose and advanced glycation end products. Advanced glycation end product is a varied compound expected to play a major role in diabetes and its consequences [8]. Reports suggest oxidative stress is predominantly involved

in the pathophysiology of diabetes [9,10], and in the increase of effects of DM. Also, the beta cell dysfunction and IR that occur much earlier before the onset of diabetes are related to oxidative stress [11]

Aim: To examine the association of visceral fat with cardiopulmonary fitness, oxidative stress and inflammatory markers in asymptomatic individuals with and without family history of type 2 diabetes mellitus.

Objectives:

• To estimate the visceral fat, cardiopulmonary fitness, in asymptomatic individuals with and without family history of type 2 diabetes mellitus.
• To estimate the oxidative stress and inflammation markers in asymptomatic individuals with and without family history of type 2 diabetes mellitus.

After getting clearance from institutional ethics committee, all the subjects gave written and informed consent.

Type of study: Cross sectional study Sampling technique: Random sampling Sample size formula:

Group 1: FDRDM – 50,

Group 2: Controls: 50.

Sample size: Sample size was computed basing on expecting an association of levels of visceral fat composition with oxidative stress, inflammation may be 0.56.For testing that it could be significantly varies from 0 at alpha-error of 0.05 and power 90%, with two sided test, we needed to conduct a study thirty seven subjects in each of the group. After interim analysis, sample size was adjusted to 50 in each group.

No of groups: 2 Sample size: 100

Subjects: Apparently healthy cases in the age group of 18 - 30 y who accompanies with DM patients in F.H. Medical college and Hospital, Agra, India and students were considered for study as cases (n = 50). Individuals who are using any medicines for any health condition to restrict in performing sub- maximal exercise and individuals who are practicing regular physical activity, yoga, and/other bio-feedback were excluded from this study were not included in thi study. Candidate who showed willingness to enroll in the study were included.

Age and gender matched apparently healthy individuals with no family history of diabetes were recruited for control group (n = 50). Participants were requested to have adequate sleep one day before recording and to refrain from caffeinated beverages, exercise, alcohol and nicotine 24 h prior to recording. Individuals were asked to report to the Department of Physiology in the morning after overnight fasting (149). The fasting venous blood sample (5 mL) was drawn in sodium fluoride tubes from median cubital vein for biochemical analysis of lipid profile, inflammatory markers and oxidative stress markers, as soon as they reported to lab. They were then oriented to research lab and explained about the procedures that will be done on subsequent day.

Table 1: Demographic profile of without family history of type 2 diabetes mellitus (controls) and with family history of type 2 diabetes mellitus subjects (cases)

Table 2. Cardiovascular parameters of individuals based on age distribution among the study population

Table 3: Body fat distribution, cardio respiratory fitness and blood glucose levels based on age distribution among the study population

Table 4: Oxidative stress markers levels based on age distribution among the study population

Table 5: Inflammatory markers levels based on age distribution among the study population

Table 6: Lipid profile based on age distribution among the study population

In the present study, statistically not significant difference in mean and standard deviation of heart rate in 18-21 years in control group (80.34 + 3.34 bpm) and case group (88.45 + 3.92 bpm) (p=0.57), besides change in HR in 22-25 years in

18-21 years in control group (77.83 + 2.86 bpm) then case group (86.81 + 2.94 bpm) (p=0.62) (Table 2). The interesting finding of another study was significantly increased heart rate with family history of type 2 diabetes in Koizumi K et.al. [12] Alike a study also conducted by Nielsen et al there is a change in heart rate between case and control group. [16] Conflicting, a study also reported by Eckberg DL et al there is no change in heart rate between case and control group.

[13] Contrary, a study also reported by Hedman AE et al there is no change is heart rate between case and control group. Increase in heart rate due to attributed to dominant of sympathetic activity over parasympathetic activity in case group. [14] In our study presume that the subjects with family history of type 2 diabetes has more HR compare with control group.

Our findings about increase in heart rate in case group is also supported by Hainsworth R et.al. They proposed that, an exaggerated cardiovascular reactivity to stressors is known to be a risk factor for cardiovascular diseases whereas reduced reactivity is an indicator of fitness. Therefore, a reduction in exercise- induced stress on cardio-vascular system by walking exercise has physiological significance as well as clinical applications. [15]

In our present study, in 18-21 years in case group after walking test of SBP (124.07 + 4.36 mmHg) and DBP (84.21 + 3.56 mmHg) are significantly increased in case group than control group of SBP (114.26 + 4.58 mmHg) and DBP (75.74 + 3.19 mmHg), additionally in 22-25 years in case group of SBP (124.38 + 3.98 mmHg) and DBP (84.76 + 3.71 mmHg) are significantly increased in case group than control group of SBP (111.00 + 2.63 mmHg) and DBP (73.50 + 3.63 mmHg) (Table 2). In our finding is suggestive of efficacy of walking exercise in modulating the cardiovascular response to exercise. Our results showing that increase in SBP and DBP in case group are similar to the results of Bhatt DL, et.al. [16] Identical study also reported by Azizi M et al there is change of SBP and DBP between case and control group. [17] Contrary, a study also reported by Bisognano JD et al there is no change is SBP and DBP between case and control group. [18] Opposing, a study also reported by Booth et al there is no change of SBP and DBP between case and control group. [19] This positive response might be indicating that more stress is produced on heart muscle during exercise in case group.

Moreover, pulse pressure (PP) in 18-21 years in case group (39.86 + 6.23 mmHg) and control group (38.53 +3.50 mmHg) was statistically not significant difference (p=0.11), similarly PP in 22-25 years in case group (39.62 + 5.24 mmHg) and control group (37.50 +4.91 mmHg) was statistically not significant difference (p=0.79). The mean arterial pressure (MAP) was statistically significant difference in 18-21 years in case (97.49 + 2.48 mmHg) and control group (88.58 + 3.33 mmHg) (p=0.016), alike in 22-25 years of MAP was statistically significant difference in 18-21 years in case (97.97 + 2.89 mmHg) and control group (85.99 + 2.39 mmHg) (p=0.207). On the other hand, Rate Pressure Product (RPP) also statistically significant difference between both the case (10980.0 + 724.15) and control group (9175.80 + 447.12) (p=0.021). A study by Heusser K et.al reported significant change in MAP and RPP in case group compared to control group. [20] Contrary, a study also reported by Robertson D et al there is no change is MAP and RPP between case and control group. [21] Opposing, a study also reported by Norel X et al there is no change of MAP and RPP between case and control group. [22]

Body fat in 18-21 years in Case Group showed an increase in Mean percentage 26.91 + 2.25 then control group 24.10 + 1.66 (p=0.21), comparable Body fat in 22-25 years in Case Group showed an increase in Mean percentage 24.49 + 2.62 then control group 24.32 + 1.66. It shows that body fat increased in case group was 1.39 %. Ainsworth BE et al., have also observed similar results among a study population. [23] Most obese individuals, despite being insulin resistant, do not develop hyperglycaemia. Alike, a study also reported by Alahmadi MA et al there is change in body fat between case and control group. [24] Differing, a study also reported by Andersen RE et al there is no change in body fat between case and control group. [25] Contrary, a study also reported by Bahr R et al there is no change in body fat between case and control group. [26] Pancreatic β-cells of the islet of Langerhans release adequate amounts of insulin that are sufficient to overcome insulin level reductions under normal circumstances, thus maintaining normal glucose tolerance.

The FBS in between 18-21 years in Case Group showed an increase in Mean levels 88.03 + 4.95 mg/dl then control group 84.29 + 4.37 mg /dl (p=0.53), likewise FBS in between 22-25 years in Case Group showed an increase in Mean levels 87.29 + 4.37 mg/dl then control group 83.91 + 4.74 mg /dl (p=74). It reflects that 18-21 years of Mean increase of blood glucose was 3.74 mg/dl in case group then Control Group in our study. According to King P et al stated that increase in blood glucose level in case control study. [27] Similarly, a study also reported by Koyama Y et al there is change in FBG between case and control group. [28] Differing, a study also reported by Arciero PJ et al there is no change of FBG between case and control group. [29] Contrary, a study also reported by Boden G et al there is no change is Fasting blood glucose between case and control group. [30]

Data strongly support a genetic predisposition to β-cell failure. A genetic subtype of the disease characterized by diagnosis at <25 years of age, β-cell dysfunction, an autosomal dominant mode of inheritance, and heterozygous mutations in β- cell transcription factors has been identified as a common cause of early-onset type 2 diabetes. However, in most patients in clinical practice, it is impossible to identify a genetic abnormality clinically and environmental factors predominate. [31]

TAOS while comparing between control group (without family history of type 2 diabetes) and case group (with family history of type 2 diabetes), in our study found that in mean and standard deviation of TAOS in 18- 21 years in control group (1.45 + 0 .34 mM) and case group (0.71 + 0.46 mM) was statistically not significant difference between both groups (p=0.061), meanwhile TAOS in 22- 25 years in control group (1.37 + 0 .47 mM) and case group (0.45 + 0.14 mM) was statistically significant difference between both groups (p=0.003). MDA in 18-21 years in Case Group showed an increase in Mean 11.05 + 9.26 mM then control group 6.14 + 0.89m M (p<0.0001), MDA in 22-25 years in Case Group showed an increase in Mean 13.05 + 9.34 mM then control group 5.74 + 1.19m M. Similar results were obtained by Kashyap MK et al in-case group then control group. [32]

Alike, a study also reported by Banarjee S et al there is change TAOS and MDA between case and control group. [33] Conflicting, a study also reported by Kunwar A et al there is no change in TAOS and MDA between case and control group. [32] Contrary, a study also reported by Yoshikawa T et al there is no change in TAOS and MDA between case and control group. [34]

From the present study results it can be concluded that in our present study, case group (with family history of type 2 diabetes) and control group (without family history of type 2 diabetes) as per study protocol. The parameters of Cardiovascular system (HR, SBP, DBP, PP, MAP, RPP), FBS, visceral fat, Inflammatory markers (TNF alpha, IL6, hsCRP) and Lipid Profile (TC, HDL, TGL, LDL, VLDL).

The molecular genetic definition of T2DM pathophysiology will certainly satisfy our intellectual curiosity about this common disease, but will it impact health care. Our knowledge to predict T2DM is currently limited. Pharmacological intervention rather than prevention remains the primary approach to this disease. These investigations achieved a notable four–fold increased risk in with family history of type 2 diabetes This study is a landmark in combining individually weak genetic risk factors with traditional risk factors to improve the prediction of future T2DM. Although the combination of genetic risk factors in this model has been challenged, the methods of Lyssenko and colleagues model was in which multiple small genetic risk factors can be combined to predict risk. The utility of genetic approaches will depend on a holistic understanding of the interactions of among genetic variants, and between genetic variants and the environmental, lifestyle factors and treatments.

1. Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care. 2004 May;27(5):1047–53.
2. Navarro JF, Mora C. Role of inflammation in diabetic complications. Nephrol Dial Transplant. 2005 Dec;20(12):2601–4.
3. Doi Y, Kiyohara Y, Kubo M, Ninomiya T, Wakugawa Y, Yonemoto K, et al. Elevated C-reactive protein is a predictor of the development of diabetes in a general Japanese population: the Hisayama Study. Diabetes Care. 2005 Oct;28(10):2497–500.
4. Barzilay JI, Abraham L, Heckbert SR, Cushman M, Kuller LH, Resnick HE, et al. The relation of markers of inflammation to the development of glucose disorders in the elderly: the Cardiovascular Health Study. Diabetes. 2001 Oct;50(10):2384–9.
5. Leung GM, Lam KS. Diabetic complications and their implications on health care in Asia. Hong Kong Med J. 2000 Mar;6(1):61–8.
6. Ramakrishna V, Jailkhani R. Evaluation of oxidative stress in Insulin Dependent Diabetes Mellitus (IDDM) patients. Diagn Pathol. 2007;2:22.
7. Heistad   Oxidative  stress  and  vascular  disease:  2005  Duff  lecture. ArteriosclerThrombVasc Biol. 2006 Apr;26(4):689–95.
8. Vlassara H, Uribarri J. Advanced Glycation End Products (AGE) and Diabetes: Cause, Effect, or Both? Curr Diab Rep. 2014 Jan;14(1):453.
9. Giacco F, Brownlee M. Oxidative stress and diabetic complications. Circ Res. 2010 Oct 29;107(9):1058–70.
10. Henriksen EJ, Diamond-Stanic MK, Marchionne EM. Oxidative stress and the etiology of insulin resistance and type 2 diabetes. Free Radic Biol Med. 2011 Sep 1;51(5):993–9.
11. Leahy JL. Pathogenesis of type 2 diabetes mellitus. Arch Med Res. 2005 Jun;36(3):197–209.
12. Elliott MJ, Maini RN, Feldmann M, Kalden JR, Antoni C, Smolen JS, et al. Randomised double-blind comparison of chimeric monoclonal antibody to tumour necrosis factor alpha (cA2) versus placebo in rheumatoid arthritis. Lancet. 1994 Oct 22;344(8930):1105–10.
13. Kraaijeveld AO, de Jager SCA, van Berkel TJC, Biessen E a. L, Jukema JW. Chemokines and atherosclerotic plaque progression: towards therapeutic targeting? Curr Pharm Des. 2007;13(10):1039–52.
14. Targan SR, Hanauer SB, van Deventer SJ, Mayer L, Present DH, Braakman T, et al. A short-term study of chimeric monoclonal antibody cA2 to tumor necrosis factor alpha for Crohn’s disease. Crohn’s Disease cA2 Study Group. N Engl J Med. 1997 Oct 9;337(15):1029–35.
15. Koster A, Stenholm S, Alley DE, Kim LJ, Simonsick EM, Kanaya AM, et al. Body fat distribution and inflammation among obese older adults with and without metabolic syndrome. Obesity (Silver Spring). 2010 Dec;18(12):2354– 61.
16. Meshkani R, Adeli K. Hepatic insulin resistance, metabolic syndrome and cardiovascular disease. Clin Biochem. 2009 Sep;42(13–14):1331–46.
17. Hotamisligil GS, Shargill NS, Spiegelman BM. Adipose expression of tumor necrosis factor-alpha: direct role in obesity-linked insulin resistance. Science. 1993 Jan 1;259(5091):87–91.
18. Peraldi P, Spiegelman BM. Studies of the mechanism of inhibition of insulin signaling by tumor necrosis factor-alpha. J Endocrinol. 1997 Nov;155(2):219– 20.
19. Indulekha K, Surendar J, Mohan V. High sensitivity C-reactive protein, tumor necrosis factor-α, interleukin-6, and vascular cell adhesion molecule-1 levels in Asian Indians with metabolic syndrome and insulin resistance (CURES- 105). J Diabetes Sci Technol. 2011 Jul 1;5(4):982–8.
20. Potential role of TNF-alpha in the pathogenesis of insulin resistance and type 2 diabetes. - PubMed - NCBI [Internet]. [cited 2017 Sep 21].
21. Fletcher B, Gulanick M, Lamendola C. Risk factors for type 2 diabetes mellitus. J Cardiovasc Nurs. 2002 Jan;16(2):17–23
22. Erasmus RT, Blanco EB, Okesina AB, Arana JM, Gqweta Z, Matsha T. Importance of family history in type 2 black South African diabetic patients. Postgraduate Medical Journal [Internet]. 2001 May 1 [cited 2019 Oct 3];77(907):323–5. Available from: https://pmj.bmj.com/content/77/907/323
23. Plagemann A, Harder T, Franke K, Kohlhoff R. Long-term impact of neonatal breast-feeding on body weight and glucose tolerance in children of diabetic mothers. Diabetes Care. 2002 Jan;25(1):16–22.
24. Crook M. Type 2 diabetes mellitus: a disease of the innate immune system? An update. Diabetic Medicine [Internet]. 2004 [cited 2019 Oct 2];21(3):203–7.
25. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1046/j.1464- 5491.2003.01030.x
26. Bjørnholt JV, Erikssen G, Liestøl K, Jervell J, Erikssen J, Thaulow E. Prediction of Type 2 diabetes in healthy middle-aged men with special emphasis on glucose homeostasis. Results from 22.5 years’ follow-up. Diabet Med. 2001 Apr;18(4):261–7.
27. Tuomi T, Carlsson A, Li H, Isomaa B, Miettinen A, Nilsson A, et al. Clinical and genetic characteristics of type 2 diabetes with and without GAD antibodies. Diabetes. 1999 Jan;48(1):150–7.
28. Hamaguchi K, Kimura A, Kusuda Y, Yamashita T, Yasunami M, Takahasi M, et al. Clinical and genetic characteristics of GAD-antibody positive patients initially diagnosed as having type 2 diabetes. Diabetes Res Clin Pract. 2004 Nov;66(2):163–71.
29. Boyko EJ, Fujimoto WY, Leonetti DL, Newell-Morris L. Visceral adiposity and risk of type 2 diabetes: a prospective study among Japanese Americans. Diabetes Care. 2000 Apr;23(4):465–71.
30. Carstens MT, Goedecke JH, Dugas L, Evans J, Kroff J, Levitt NS, et al. Fasting substrate oxidation in relation to habitual dietary fat intake and insulin resistance in non-diabetic women: a case for metabolic flexibility? NutrMetab (Lond). 2013 Jan 14;10(1):8.
31. Groop L, Forsblom C, Lehtovirta M, Tuomi T, Karanko S, Nissén M, et al. Metabolic consequences of a family history of NIDDM (the Botnia study): evidence for sex-specific parental effects. Diabetes. 1996 Nov;45(11):1585–93.
32. Florez H, Ryder E, Campos G, Fernandez V, Morales LM, Valbuena H, et al. Women relatives of Hispanic patients with type 2 diabetes are more prone to exhibit metabolic disturbances. Invest Clin. 1999 Jun;40(2):127–42.
33. Gravante G, Pomara F, Angelomè C, Russo G, Truglio G. The basal energy expenditure of female athletes vs. sedentary women as related to their family history of type 2 diabetes. Acta Diabetol. 2001;38(2):63–70.
34. Tequeanes ALL, Fabián MG, Plata M del RF, Sancho MCG. Estudiometabólico de los familiares de pacientes con diabetes tipo 2. Med Int Mex [Internet]. 2011        [cited     2019      Oct         3];27(1):5–10.     Available             from: https://www.medigraphic.com/cgi- bin/new/resumenI.cgi?IDARTICULO=28462
35. Olive JL, Ballard KD, Miller JJ, Milliner BA. Metabolic rate and vascular function are reduced in women with a family history of typ