Metabolic Diseases Predictor Analysis Based on Single Nucleotide Polymorphisms and Lifestyle Factors: Preliminary Study in Indonesia

Dionysius Subali; James Setiawan; Patricia Kimberly; Rendy Dijaya; Felicia Kartawidjajaputra; Lina Antono; Revelo Eved Christos; Lenny Mulianie Wibisana; Yang-Chia Shih

doi:10.56303/jhnresearch.v4i3.527

Authors

Dionysius Subali Department of Biotechnology, Faculty of Bioscience, Technology, and Innovation, Atma Jaya Catholic University of Indonesia, Indonesia
James Setiawan Department of Food Technology, Faculty of Bioscience, Technology, and Innovation, Atma Jaya Catholic University of Indonesia, Indonesia
Patricia Kimberly Department of Food Technology, Faculty of Bioscience, Technology, and Innovation, Atma Jaya Catholic University of Indonesia, Indonesia
Rendy Dijaya Nutrifood Research Center, PT. Nutrifood Indonesia, Jakarta, Indonesia
Felicia Kartawidjajaputra Nutrifood Research Center, PT. Nutrifood Indonesia, Jakarta, Indonesia
Lina Antono Nutrifood Research Center, PT. Nutrifood Indonesia, Jakarta, Indonesia
Revelo Eved Christos Department of Medical Laboratory Science and Biotechnology, Asia University, Taiwan
Lenny Mulianie Wibisana Nutrifood Research Center, PT. Nutrifood Indonesia, Jakarta, Indonesia
Yang-Chia Shih Department of Medical Laboratory Science and Biotechnology, Asia University, Taiwan

Keywords:

Blood Glucose Profile, Lipid Profile, Single Nucleotide Polymorphism, Diabetes Mellitus, Cardiovascular Disease

Abstract

Type 2 Diabetes Mellitus (T2DM) and cardiovascular disease (CVD) emerged as a cause of high mortality rates in low-middle-income countries, including Indonesia. Understanding predictor variables to the commonly used biomarkers, including lipid profiles and blood glucose levels, can thus be beneficial in disease prevention strategies. To support that, this study aims to analyze the genetic, lifestyle, and disease history variables as predictors towards lipid and blood glucose profiles. The respondent’s data were collected from clinical data, food recall, health history, and genetic profiling. From the results, APOA5 rs662799 is positively correlated with triglyceride (TG) levels. Sugar, fat, fiber, and calorie intake also significantly affect lipid and blood glucose profiles. Exercise conditions such as aerobic and flexibility exercise duration significantly correlated with low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) profiles. Disease history in individuals and families emerged as additional variables associated with the response variables. These findings can serve as a preliminary study for understanding health predictors that can be used to predict incident of metabolic diseases in the Indonesian population.

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References

Galicia-Garcia U, Benito-Vicente A, Jebari S, Larrea-Sebal A, Siddiqi H, Uribe KB, et al. Pathophysiology of Type 2 diabetes mellitus. Int J Mol Sci. 2020;21(17).

O'Hearn M, Lara-Castor L, Cudhea F, Miller V, Reedy J, Shi P, et al. Incident type 2 diabetes attributable to suboptimal diet in 184 countries. Nat Med. 2023;29(4):982-95.

De Rosa S, Arcidiacono B, Chiefari E, Brunetti A, Indolfi C, Foti DP. Type 2 diabetes mellitus and cardiovascular disease: genetic and epigenetic links. Front Endocrinol (Lausanne). 2018;9:2.

Mc Namara K, Alzubaidi H, Jackson JK. Cardiovascular disease as a leading cause of death: how are pharmacists getting involved? Integr Pharm Res Pract. 2019;8:1-11.

Ma CX, Ma XN, Guan CH, Li YD, Mauricio D, Fu SB. Cardiovascular disease in type 2 diabetes mellitus: progress toward personalized management. Cardiovasc Diabetol. 2022;21(1):74.

Jin J. Testing for “silent” coronary heart disease. JAMA. 2014;312(8):858.

Peer N, Balakrishna Y, Durao S. Screening for type 2 diabetes mellitus. Cochrane Database Syst Rev. 2020;5(5):CD005266.

Chen R, Ovbiagele B, Feng W. Diabetes and stroke: epidemiology, pathophysiology, pharmaceuticals and outcomes. Am J Med Sci. 2016;351(4):380-6.

Ghodeshwar GK, Dube A, Khobragade D. Impact of lifestyle modifications on cardiovascular health: a narrative review. Cureus. 2023;15(7):e42616.

Campbell IW. Type 2 diabetes mellitus: ‘the silent killer’. Practical Diabetes International. 2001;18(6):187-91.

Conradie A, Atherton J, Chowdhury E, Duong M, Schwarz N, Worthley S, et al. Health-related quality of life (HRQoL) and the effect on outcome in patients presenting with coronary artery disease and treated with percutaneous coronary intervention (PCI): differences noted by sex and age. J Clin Med. 2022;11(17).

Gupta J, Kapoor D, Sood V. Quality of life and its determinants in patients with diabetes mellitus from two health institutions of Sub-Himalayan region of India. Indian J Endocrinol Metab. 2021;25(3):211-9.

Tonnies T, Hoyer A, Brinks R. Productivity-adjusted life years lost due to type 2 diabetes in Germany in 2020 and 2040. Diabetologia. 2021;64(6):1288-97.

WHO. Global status report on noncommunicable diseases 2010. Italy: WHO Library; 2011.

Wang L, Yan N, Zhang M, Pan R, Dang Y, Niu Y. The association between blood glucose levels and lipids or lipid ratios in type 2 diabetes patients: A cross-sectional study. Front Endocrinol (Lausanne). 2022;13:969080.

ElSayed NA, Aleppo G, Aroda VR, Bannuru RR, Brown FM, Bruemmer D, et al. Classification and Diagnosis of Diabetes: Standards of Care in Diabetes-2023. Diabetes Care. 2023;46(Suppl 1):S19-S40.

Higgins T. HbA1c for screening and diagnosis of diabetes mellitus. Endocrine. 2013;43(2):266-73.

Hajian-Tilaki K, Heidari B, Bakhtiari A. Triglyceride to high-density lipoprotein cholesterol and low-density lipoprotein cholestrol to high-density lipoprotein cholesterol ratios are predictors of cardiovascular risk in Iranian adults: Evidence from a population-based cross-sectional study. Caspian J Intern Med. 2020;11(1):53-61.

Lee WJ, Peng LN, Loh CH, Chen LK. Sex-different associations between serum homocysteine, high-sensitivity C-reactive protein and sarcopenia: Results from I-Lan Longitudinal Aging Study. Exp Gerontol. 2020;132:110832.

Collins GS, Mallett S, Omar O, Yu L. Developing risk prediction models for type 2 diabetes: a systematic review of methodology and reporting. BMC Medicine. 2011;9(103):1-14.

Markovic R, Grubelnik V, Vosner HB, Kokol P, Zavrsnik M, Jansa K, et al. Age-related changes in lipid and glucose levels associated with drug use and mortality: an observational study. J Pers Med. 2022;12(2).

Nicchio IG, Cirelli T, Nepomuceno R, Hidalgo MAR, Rossa C, Jr., Cirelli JA, et al. Polymorphisms in genes of lipid metabolism are associated with type 2 diabetes mellitus and periodontitis, as comorbidities, and with the subjects' periodontal, glycemic, and lipid profiles. J Diabetes Res. 2021;2021:1049307.

de Hoogh IM, Oosterman JE, Otten W, Krijger AM, Berbee-Zadelaar S, Pasman WJ, et al. The effect of a lifestyle intervention on type 2 diabetes pathophysiology and remission: the stevenshof pilot study. Nutrients. 2021;13(7).

Vassy JL, Meigs JB. Is genetic testing useful to predict type 2 diabetes? Best Pract Res Clin Endocrinol Metab. 2012;26(2):189-201.

Sitinjak BDP, Murdaya N, Rachman TA, Zakiyah N, Barliana MI. The Potential of Single Nucleotide Polymorphisms (SNPs) as biomarkers and their association with the increased risk of coronary heart disease: a systematic review. Vasc Health Risk Manag. 2023;19:289-301.

Lyssenko V, Jonsson A, Almgren P, Pulizzi P, Isomaa B, Tuomi T, et al. Clinical risk factors, DNA variants, and the development of type 2 diabetes. The New England Journal of Medicine. 2008;359(21):2220-32.

Xu L, Chen S, Zhan L. Association of uncoupling protein-2 -866G/A and Ala55Val polymorphisms with susceptibility to type 2 diabetes mellitus: A meta-analysis of case-control studies. Medicine (Baltimore). 2021;100(6):e24464.

Dieter C, Assmann TS, Lemos NE, Massignam ET, Souza BM, Bauer AC, et al. -866G/A and Ins/Del polymorphisms in the UCP2 gene and diabetic kidney disease: case-control study and meta-analysis. Genet Mol Biol. 2020;43(2):e20180374.

Shou W, Wang Y, Xie F, Wang B, Yang L, Wu H, et al. A functional polymorphism affecting the APOA5 gene expression is causally associated with plasma triglyceride levels conferring coronary atherosclerosis risk in Han Chinese Population. Biochim Biophys Acta. 2014;1842(11):2147-54.

Jacob J, Boczkowska S, Zaluska W, Buraczynska M. Apolipoprotein A5 gene polymorphism (rs662799) and cardiovascular disease in end-stage kidney disease patients. BMC Nephrol. 2022;23(1):307.

Jasim OH, Mahmood MM, Ad'hiah AH. Significance of lipid profile parameters in predicting pre-diabetes. Arch Razi Inst. 2022;77(1):277-84.

Dietrich S, Jacobs S, Zheng JS, Meidtner K, Schwingshackl L, Schulze MB. Gene-lifestyle interaction on risk of type 2 diabetes: A systematic review. Obes Rev. 2019;20(11):1557-71.

Asshiddiqi MIN, Yodchai K, Taniwattananon P. Predictors of diabetes distress among older persons with type 2 diabetes mellitus in Indonesia. J Res Nurs. 2021;26(4):307-17.

Sulistiowati E, Pradono J. Development of a validated diabetes risk chart as a simple tool to predict the onset of diabetes in Bogor, Indonesia. J ASEAN Fed Endocr Soc. 2022;37(1):46-52.

Jiang CQ, Liu B, Cheung BM, Lam TH, Lin JM, Li Jin Y, et al. A single nucleotide polymorphism in APOA5 determines triglyceride levels in Hong Kong and Guangzhou Chinese. Eur J Hum Genet. 2010;18(11):1255-60.

Demirdogen BC, Sahin E, Turkanoglu Ozcelik A, Bek S, Demirkaya S, Adali O. Apolipoprotein A5 polymorphisms in Turkish population: association with serum lipid profile and risk of ischemic stroke. Mol Biol Rep. 2012;39(12):10459-68.

Perera SD, Hegele RA. Genetic variation in apolipoprotein A-V in hypertriglyceridemia. Curr Opin Lipidol. 2024;35(2):66-77.

Deng L, Vrieling F, Stienstra R, Hooiveld GJ, Feitsma AL, Kersten S. Macrophages take up VLDL-sized emulsion particles through caveolae-mediated endocytosis and excrete part of the internalized triglycerides as fatty acids. PLoS Biol. 2022;20(8):e3001516.

Garelnabi M, Lor K, Jin J, Chai F, Santanam N. The paradox of ApoA5 modulation of triglycerides: evidence from clinical and basic research. Clin Biochem. 2013;46(1-2):12-9.

Heeren J, Scheja L. Metabolic-associated fatty liver disease and lipoprotein metabolism. Mol Metab. 2021;50:101238.

Bell JA, Richardson TG, Wang Q, Sanderson E, Palmer T, Walker V, et al. Effects of general and central adiposity on circulating lipoprotein, lipid, and metabolite levels in UK Biobank: A multivariable Mendelian randomization study. Lancet Reg Health Eur. 2022;21:100457.

Hjellvik V, Sakshaug S, Strom H. Body mass index, triglycerides, glucose, and blood pressure as predictors of type 2 diabetes in a middle-aged Norwegian cohort of men and women. Clin Epidemiol. 2012;4:213-24.

Wu Y, Li D, Vermund SH. Advantages and limitations of the Body Mass Index (BMI) to assess adult obesity. Int J Environ Res Public Health. 2024;21(6).

Khanna D, Peltzer C, Kahar P, Parmar MS. Body Mass Index (BMI): a screening tool analysis. Cureus. 2022;14(2):e22119.

Darbandi M, Pasdar Y, Moradi S, Mohamed HJJ, Hamzeh B, Salimi Y. Discriminatory capacity of anthropometric indices for cardiovascular disease in adults: a systematic review and meta-analysis. Prev Chronic Dis. 2020;17:E131.

Dalton M, Cameron AJ, Zimmet PZ, Shaw JE, Jolley D, Dunstan DW, et al. Waist circumference, waist-hip ratio and body mass index and their correlation with cardiovascular disease risk factors in Australian adults. J Intern Med. 2003;254(6):555-63.

Marlowe F, Apicella C, Reed D. Men's preferences for women's profile waist-to-hip ratio in two societies. Evolution and Human Behavior. 2005;26(6):458-68.

Lee JJ, Pedley A, Hoffmann U, Massaro JM, Fox CS. Association of changes in abdominal fat quantity and quality with incident cardiovascular disease risk factors. J Am Coll Cardiol. 2016;68(14):1509-21.

Frank AP, de Souza Santos R, Palmer BF, Clegg DJ. Determinants of body fat distribution in humans may provide insight about obesity-related health risks. J Lipid Res. 2019;60(10):1710-9.

Goh LG, Dhaliwal SS, Welborn TA, Lee AH, Della PR. Ethnicity and the association between anthropometric indices of obesity and cardiovascular risk in women: a cross-sectional study. BMJ Open. 2014;4(5):e004702.

Cui J, Sun J, Wang W, Xin H, Qiao Q, Baloch Z, et al. The association of triglycerides and total cholesterol concentrations with newly diagnosed diabetes in adults in China. Oncotarget. 2017;8(61):103477-85.

Karr S. Epidemiology and management of hyperlipidemia. The American Journal of Managed Care. 2017;23(1):S139-S48.

Gao S, Pei Z. Effect and improvement of lifestyle intervention on hyperlipidemia. In: Hamasaki H, editor. New Horizons of Excercise Medicine. United Kingdom: IntechOpen; 2024.

Zampelas A, Magriplis E. New Insights into cholesterol functions: a friend or an enemy? Nutrients. 2019;11(7).

Vance JE. Cellular itinerary of LDL cholesterol. Proc Natl Acad Sci U S A. 2022;119(6).

Lu J, Han G, Liu X, Chen B, Peng K, Shi Y, et al. Association of high-density lipoprotein cholesterol with all-cause and cause-specific mortality in a Chinese population of 3.3 million adults: a prospective cohort study. The Lancet Regional Health - Western Pacific. 2024;42:100874.

Goldberg IJ. Fat in the blood, fat in the artery, fat in the heart: triglyceride in physiology and disease. Arterioscler Thromb Vasc Biol. 2018;38(4):700-6.

Luna-Castillo KP, Olivares-Ochoa XC, Hernandez-Ruiz RG, Llamas-Covarrubias IM, Rodriguez-Reyes SC, Betancourt-Nunez A, et al. The effect of dietary interventions on hypertriglyceridemia: from public health to molecular nutrition evidence. Nutrients. 2022;14(5).

Perrone MA, Feola A, Pieri M, Donatucci B, Salimei C, Lombardo M, et al. The effects of reduced physical activity on the lipid profile in patients with high cardiovascular risk during COVID-19 lockdown. Int J Environ Res Public Health. 2021;18(16).

Chen Z, Zhang X, Duan Y, Mo T, Liu W, Ma Y, et al. The Relationship Between Sleep Duration and Blood Lipids Among Chinese Middle-Aged and Older Adults: Cross-Lagged Path Analysis From CHARLS. Front Public Health. 2022;10:868059.

Chou CW, Fang WH, Chen YY, Wang CC, Kao TW, Wu CJ, et al. Association between serum calcium and risk of cardiometabolic disease among community-dwelling adults in Taiwan. Sci Rep. 2020;10(1):3192.

Brett T, Arnold-Reed D. Familial hypercholesterolaemia. The Australian Journal of General Practice. 2019;48(9):650-2.

Khil J, Kim SM, Chang J, Choi S, Lee G, Son JS, et al. Changes in total cholesterol level and cardiovascular disease risk among type 2 diabetes patients. Sci Rep. 2023;13(1):8342.

Tanoey J, Becher H. Diabetes prevalence and risk factors of early-onset adult diabetes: results from the Indonesian family life survey. Glob Health Action. 2021;14(1):2001144.

Lattimer JM, Haub MD. Effects of dietary fiber and its components on metabolic health. Nutrients. 2010;2(12):1266-89.

den Besten G, van Eunen K, Groen AK, Venema K, Reijngoud DJ, Bakker BM. The role of short-chain fatty acids in the interplay between diet, gut microbiota, and host energy metabolism. J Lipid Res. 2013;54(9):2325-40.

Mann S, Beedie C, Jimenez A. Differential effects of aerobic exercise, resistance training and combined exercise modalities on cholesterol and the lipid profile: review, synthesis and recommendations. Sports Med. 2014;44(2):211-21.

Artha I, Bhargah A, Dharmawan NK, Pande UW, Triyana KA, Mahariski PA, et al. High level of individual lipid profile and lipid ratio as a predictive marker of poor glycemic control in type-2 diabetes mellitus. Vasc Health Risk Manag. 2019;15:149-57.

Yanai H, Katsuyama H, Hamasaki H, Abe S, Tada N, Sako A. Effects of dietary fat intake on HDL metabolism. J Clin Med Res. 2015;7(3):145-9.

Gillum RF. Distribution of waist-to-hip ratio, other indices of body fat distribution and obesity and associations with HDL cholesterol in children and young adults aged 4 ± 19 years: the third national health and nutrition examination survey. International J of Obesity. 1999;23:556-63.

Al-Mhanna SB, Leao C, Ghazali WSW, Mohamed M, Batrakoulis A, Afolabi HA, et al. Impact of exercise on high-density lipoprotein cholesterol in adults with overweight and obesity: a narrative review. Ann Appl Sport Sci. 2024;12(2):1-17.

Franczyk B, Gluba-Brzozka A, Cialkowska-Rysz A, Lawinski J, Rysz J. The Impact of Aerobic Exercise on HDL Quantity and Quality: A Narrative Review. Int J Mol Sci. 2023;24(5).

Naqvi S, Naveed S, Ali Z, Ahmad SM, Khan RA, Raj H, et al. Correlation between glycated hemoglobin and triglyceride level in type 2 diabetes mellitus. Cureus. 2017;9(6):e1347.

Tao X, Jiang M, Liu Y, Hu Q, Zhu B, Hu J, et al. Predicting three-month fasting blood glucose and glycated hemoglobin changes in patients with type 2 diabetes mellitus based on multiple machine learning algorithms. Sci Rep. 2023;13(1):16437.

Bala M, Meenakshi M, Aggarwal S. Correlation of body mass index and waist/hip ratio with glycated hemoglobin in prediabetes. The Journal of The International Federation of Clinical Chemistry and Laboratory Medicine. 2019;30(3):317-24.

Tan X, Benedict C. Sleep characteristics and HbA1c in patients with type 2 diabetes on glucose-lowering medication. BMJ Open Diabetes Res Care. 2020;8(1).

Chou YH, Cheng YY, Nfor ON, Chen PH, Chen CH, Chen HL, et al. Effects of aerobic and resistance exercise on glycosylated hemoglobin (HbA1c) concentrations in non-diabetic Taiwanese individuals based on the waist-hip ratio. PLoS One. 2022;17(5):e0267387.

Kang HM, Kim DJ. Total energy intake may be more associated with glycemic control compared to each proportion of macronutrients in the korean diabetic population. Diabetes Metab J. 2012;36(4):300-6.

Lin W. The Association between Body Mass Index and Glycohemoglobin (HbA1c) in the US Population's diabetes status. Int J Environ Res Public Health. 2024;21(5).

Barrera EL, Shively G. Excess calorie availability and adult BMI: A cohort analysis of patterns and trends for 156 countries from 1890 to 2015. Food Policy. 2022;109.

Fruh SM. Obesity: risk factors, complications, and strategies for sustainable long-term weight management. J Am Assoc Nurse Pract. 2017;29(S1):S3-S14.

Barazzoni R, Zanetti M, Stulle M, Mucci MP, Pirulli A, Dore F, et al. Higher total ghrelin levels are associated with higher insulin-mediated glucose disposal in non-diabetic maintenance hemodialysis patients. Clin Nutr. 2008;27(1):142-9.

Wandeler G, Paccaud F, Vollenweider P, Waeber G, Mooser V, Bochud M. Strength of family history in predicting levels of blood pressure, plasma glucose and cholesterol. Public Health Genomics. 2010;13(3):143-54.

Tatsumi Y, Morimoto A, Asayama K, Sonoda N, Miyamatsu N, Ohno Y, et al. Fasting blood glucose predicts incidence of hypertension independent of HbA1c levels and insulin resistance in middle-aged Japanese: the Saku study. Am J Hypertens. 2019;32(12):1178-85.

Pravednikova AE, Shevchenko SY, Kerchev VV, Skhirtladze MR, Larina SN, Kachaev ZM, et al. Association of uncoupling protein (Ucp) gene polymorphisms with cardiometabolic diseases. Mol Med. 2020;26(1):51.

Kumari P, Khan S, Wani IA, Gupta R, Verma S, Alam P, et al. Unravelling the role of epigenetic modifications in development and reproduction of angiosperms: a critical appraisal. Front Genet. 2022;13:819941.

Widayanti AW, Green JA, Heydon S, Norris P. Health-seeking behavior of people in Indonesia: a narrative review. J Epidemiol Glob Health. 2020;10(1):6-15.