لایب سان

Department of Physiology, School of Medical Sci- ences, Universiti Sains Malaysia Health Campus, Kubang Kerian, Kelantan, Malaysia Andrzej S. Januszewski NHMRC Clinical Trials Centre, The University of Syd- ney, Camperdown, NSW, Australia Department of Medicine, University of Melbourne, Fitzroy, VIC, Australia Alicia J. Jenkins Department of Medicine, University of Melbourne, Fitzroy, VIC, Australia Zhuyi Jiang Department of Endocrinology, Shenzhen People’s Hospital, Shenzhen, Guangdong, China Hale Maral Kır Department of Medical Biochemistry, Faculty of Medicine, Kocaeli University, Kocaeli, Turkey Yulia Karakulova Department of Neurology and Medical Genetics, Academician Ye.A.Vagner Perm State Medical University, Perm, Russia Kazuomi Kario Division of Cardiovascular Medicine, Department of Medicine, Jichi Medical University School of Medicine, Tochigi, Japan Min Kim Department of Ophthalmology, Gangnam Severance Hospital, Institute of Vision Research, Yonsei University College of Medicine, Seoul, South Korea Adam Kretowski Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland Department of Endocrinology, Diabetology, and Internal Medicine, Medical Uni- versity of Bialystok, Bialystok, Poland Marlene Lages ciTechCare, Polytechnic of Leiria, Leiria, Portugal Ivan Pochou Lai Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan Ricardo Lamy Department of Ophthalmology, School of Medicine, University of California, San Francisco, San Francisco, CA, USA Ming-Jui Lee National Taiwan University Hospital, Taipei, Taiwan Idris Long School of Health Sciences, Universiti Sains Malaysia Health Campus, Kubang Kerian, Kelantan, Malaysia Contributors xix Carolina Madeira Department of Ophthalmology, Centro Hospitalar de Vila Nova de Gaia e Espinho, Porto, Portugal Faculty of Medicine, University of Porto, Porto, Portugal Per Lav Madsen Department of Cardiology, Herlev-Gentofte Hospital, Copenha- gen University Hospital, Herlev, Denmark João P. Magalhães Exercise and Health Laboratory, Faculty of Human Kinetics, University of Lisbon, Centre for the Study of Human Performance (CIPER), Estrada da Costa, Cruz Quebrada – Dafundo, Portugal Tandi E. Matsha SAMRC/CPUT Cardiometabolic Health Research Unit, Depart- ment of Biomedical Sciences, Faculty of Health and Wellness Sciences, Cape Peninsula University of Technology, Bellville, South Africa Don M. Matshazi SAMRC/CPUT Cardiometabolic Health Research Unit, Depart- ment of Biomedical Sciences, Faculty of Health and Wellness Sciences, Cape Peninsula University of Technology, Bellville, South Africa Marwa Ahmed Meheissen Medical Microbiology & Immunology Department, Faculty of Medicine, Alexandria University, Azarita, Alexandria, Egypt Rauf Melekoglu Department of Obstetrics and Gynecology, School of Medicine, Inonu University, Malatya, Turkey Maria Mirabelli Department of Health Sciences, University “Magna Græcia”, Catanzaro, Italy Raghavendra G. Mirmira Department of Medicine, University of Chicago, Chi- cago, IL, USA Kayvan Mirnia Department of Neonatology, School of Medicine, Tehran Univer- sity of Medical Sciences, Tehran, Iran Jee-Young Moon Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA Shinje Moon Division of Endocrinology and Metabolism, Department of Internal Medicine, Hallym University College of Medicine, Seoul, South Korea Rafael Noal Moresco Laboratory of Clinical Biochemistry, Department of Clinical and Toxicological Analysis, Center of Health Sciences, Federal University of Santa Maria, Santa Maria, RS, Brazil Jesús A. Mosquera-Sulbarán Instituto de Investigaciones Clínicas Dr. Américo Negrette, Facultad de Medicina, Universidad del Zulia, Maracaibo, Venezuela Dipuo D. Motshwari SAMRC/CPUT Cardiometabolic Health Research Unit, Department of Biomedical Sciences, Faculty of Health and Wellness Sciences, Cape Peninsula University of Technology, Bellville, South Africa xx Contributors Shinsuke Noso Department of Endocrinology, Metabolism and Diabetes, Faculty of Medicine, Kindai University, Osaka, Japan Chang-Myung Oh Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, South Korea Ademola O. Olaniran Discipline of Microbiology, School of Life Sciences, Uni- versity of Kwazulu-Natal, Durban, South Africa Tosin A. Olasehinde Discipline of Microbiology, School of Life Sciences, Univer- sity of Kwazulu-Natal, Durban, South Africa Nutrition and Toxicology Division, Food Technology Department, Federal Institute of Industrial Research, Oshodi, Nigeria Sunday I. Oyeleye Department of Biomedical Technology, Federal University of Technology, Akure, Nigeria Berrin Öztaş Department of Medical Biochemistry, Faculty of Medicine, Kocaeli University, Kocaeli, Turkey Vinood B. Patel School of Life Sciences, University of Westminster, London, UK Wei Perng Lifecourse Epidemiology of Adiposity and Diabetes, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA Victor R. Preedy Department of Nutrition and Dietetics, School of Life Course and Population Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, UK Salvatore Andrea Pullano Department of Health Sciences, University “Magna Græcia”, Catanzaro, Italy Anggelia Puspasari Department of Medical Biology and Biochemistry, Faculty of Medicine and Health Sciences, Universitas Jambi, Jambi, Indonesia Qibin Qi Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA Mohamed Rafiullah Strategic Center for Diabetes Research, College of Medicine, King Saud University, Riyadh, Saudi Arabia Shanel Raghubeer SAMRC/CPUT Cardiometabolic Health Research Unit, Department of Biomedical Sciences, Faculty of Health and Wellness Sciences, Cape Peninsula University of Technology, Bellville, South Africa Rajkumar Rajendram College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia Department of Medicine, King Abdulaziz Medical City, King Abdullah International Medical Research Center, Riyadh, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia Contributors xxi Anusha S. J Department of Pharmacology, Dr. Chandramma Dayanand Sagar Institute of Medical Education and Research (CDSIMER), Devarakaggalahalli, Karnataka, India Joana F. Sacramento CEDOC, NOVA Medical School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Lisbon, Portugal Alessandro Salatino Department of Health Sciences, University “Magna Græcia”, Catanzaro, Italy Armin Salek Maghsoudi Toxicology and Diseases Group (TDG), Pharmaceutical Sciences Research Center (PSRC), The Institute of Pharmaceutical Sciences (TIPS), Tehran University of Medical Sciences, Tehran, Iran Deborah Conte Santos Diabetes Unit, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brasil Joost H. N. Schuitemaker Division of Medical Biology, Department of Pathology and Medical Biology, University Medical Center Groningen, Groningen, The Netherlands Vaithinathan Selvaraju Department of Nutrition, Dietetics, and Hospitality Man- agement, Auburn University, Auburn, AL, USA Sabyasachi Sen Department of Medicine, The George Washington University, School of Medicine and Health Sciences, Washington, DC, USA Department of Medicine, Veterans Affairs Medical Center, Washington, DC, USA Shilpa S. Shetty Central Research Laboratory, K.S. Hegde Medical Academy, Nitte (Deemed to be University), Deralakatte, Karnataka, India Padmaja Shetty K Department of Pharmacology, Dr. Chandramma Dayanand Sagar Institute of Medical Education and Research (CDSIMER), Devarakaggalahalli, Karnataka, India Khalid Siddiqui Strategic Center for Diabetes Research, College of Medicine, King Saud University, Riyadh, Saudi Arabia Matthew J. Singleton WellSpan Health, York, PA, USA Peter S. Spencer Department of Neurology, School of Medicine and Oregon Institute of Occupational Health Sciences, Oregon Health & Science University, Portland, OR, USA George S. Stergiou Hypertension Center STRIDE-7, National and Kapodistrian University of Athens, School of Medicine, Third Department of Medicine, Sotiria Hospital, Athens, Greece Jay M. Stewart Department of Ophthalmology, School of Medicine, University of California, San Francisco, San Francisco, CA, USA xxii Contributors N. Suchetha Kumari Department of Biochemistry/Central Research Laboratory, K.S. Hegde Medical Academy, Nitte (Deemed to be University), Deralakatte, Karnataka, India Daisuke Suzuki Division of Cardiovascular Medicine, Department of Medicine, Jichi Medical University School of Medicine, Tochigi, Japan Department of Medicine, Division of Endocrinology and Metabolism, Jichi Medical University Saitama Medical Center, Saitama, Japan Sarah A. Tersey Department of Medicine, University of Chicago, Chicago, IL, USA Meng-Ju Tsai Department of Ophthalmology, Taoyuan General Hospital, Ministry of Health and Welfare, Taoyuan, Taiwan Seyfettin Üstünsoy Department of Central Clinical Biochemistry Laboratory, Pri- vate Anadolu Hospital, Silivri/İstanbul, Turkey Remya Varadarajan Central Research Laboratory, K.S. Hegde Medical Academy, Nitte (Deemed to be University), Deralakatte, Karnataka, India Andriani Vazeou Diabetes Centre, A’ Department of Pediatrics, P&A Kyriakou Children’s Hospital, Athens, Greece David H. Wagner Department of Medicine, The University of Colorado Anschutz Medical Campus, Aurora, CO, USA Cecil J. Weale SAMRC/CPUT Cardiometabolic Health Research Unit, Depart- ment of Biomedical Sciences, Faculty of Health and Wellness Sciences, Cape Peninsula University of Technology, Bellville, South Africa Betul Yakistiran Perinatology Department, University of Health Sciences, Ankara Bilkent City Hospital, Ankara, Turkey Marcos Yukio Yoshinaga Department of Biochemistry, Institute of Chemistry, University of São Paulo, São Paulo, SP, Brazil Aykan Yucel Perinatology Department, University of Health Sciences, Ankara Bilkent City Hospital, Ankara, Turkey Em Yunir Division of Endocrinology, Metabolism, and Diabetes, Department of Internal Medicine, Dr. Cipto Mangunkusumo National General Hospital, Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia Chang Zeng Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA Wei Zhang Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA Contributors xxiii Part I General Aspects Linking Variants of Hemoglobin A1C and Glycemic Status 1 Jee-Young Moon and Qibin Qi Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Overview of Genome-Wide Association Studies of HbA1c . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Functional Characterization of HbA1c-Associated Genetic Variants . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Glycemic-Related Genetic Variants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Erythrocyte-Related Genetic Variants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Unclassified Genetic Variants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Erythrocyte-Related HbA1c Variants and Glycemic Status Screening . . . . . . . . . . . . . . . . . . . . . . . . . . 12 G6PD: rs1050828 and rs76723693 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 HBB-rs334 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 G6PD-rs1050828 and HBB-rs334 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Cumulative Effect of Erythrocyte-Related Genetic Variants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Applications to Other Diseases or Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Mini-Dictionary of Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Key Facts of HbA1c . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Summary Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Reference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Abstract Hemoglobin A1C (HbA1c) has been used as a convenient screening test for the diagnosis of diabetes and prediabetes, requiring no fasting, as well as a reliable measure for monitoring the glycemic control in people with diabetes. As HbA1c is the measure of the fraction of glycated hemoglobin out of total hemoglobin in red blood cells, both blood glucose levels and blood cell conditions affect levels of HbA1c. Consistently, genome-wide association studies on HbA1c have iden- tified multiple genetic loci, largely grouped into two separate pathways – via the J.-Y. Moon (*) · Q. Qi Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA e-mail: jee-young.moon@einsteinmed.edu; qibin.qi@einsteinmed.edu © Springer Nature Switzerland AG 2023 V. B. Patel, V. R. Preedy (eds.), Biomarkers in Diabetes, Biomarkers in Disease: Methods, Discoveries and Applications, https://doi.org/10.1007/978-3-031-08014-2_2 3 glycemic pathway and via the erythrocyte pathway. Two genetic variants, G6PD- rs1050828 and HBB-rs334, specifically found in individuals with African ances- try, were noted for their relatively large effects on HbA1c via the erythrocytic pathway, compared to other genetic variants. The glycemic status of individuals carrying the HbA1c-lowering alleles might be underestimated by HbA1c levels, as lower HbA1c level is observed compared to their actual glycemic status due to their genetic influences on blood cell biology. In addition, several erythrocyte- related genetic variants of small effects may also have a combined impact on HbA1c in this regard. Thus, the influences of these non-glycemic-related variants need to be considered when the HbA1c test is performed to measure glycemic status. Keywords HbA1c · Type 2 diabetes · Diabetes diagnosis · Genetic variant · SNP · GWAS · Erythrocyte · Blood traits · RBC · Glucose · G6PD deficiency · Hemoglobin · Sickle cell trait · HbA1c recalibration Abbreviations 2 hr. OGTT 2-hour oral glucose tolerance test ADA American Diabetes Association G6PD Glucose-6-phosphate dehydrogenase GRS Genetic risk score GWAS Genome-wide association study HbA1c Hemoglobin A1C MAF Minor allele frequency MAGIC The Meta-Analysis of Glucose and Insulin-related Traits Consortium MCV Mean corpuscular volume RBC Red blood cell SCT Sickle cell trait SNP Single nucleotide polymorphism T2D Type 2 diabetes WGS Whole genome sequencing Introduction Hemoglobin A1C or glycated hemoglobin (HbA1c) has been used for diabetes diagnosis as well as for monitoring glycemic control over the past 3 months for people with diabetes (American Diabetes Association 2010). This glycated hemo- globin is formed by blood glucose attached to the hemoglobin, specifically, N-terminal of beta-chains, in red blood cells (RBC, erythrocyte) by the non-enzymatic and irreversible reaction. Hence, the fraction of glycated hemoglo- bin out of total hemoglobin reflects the blood glucose levels over the lifespan of 4 J.-Y. Moon and Q. Qi erythrocytes, typically 120 days. While HbA1c indirectly measures blood glucose levels, HbA1c is a robust indicator of chronic hyperglycemia (high blood sugar) over the past 3–4 months, compared to a glucose-level measurement at one time point from a fasting blood glucose test or an oral glucose tolerance test, which can vary depending on the activity levels, stress, and hormone levels (Bonora and Tuomilehto 2011). Another strength of HbA1c test is that it can be performed any time without requiring 8 h of fasting or waiting for 2 h for the oral glucose test. Furthermore, HbA1c is a prognostic marker of diabetic complication risk such as diabetic retinopathy, nephropathy, and neuropathy (Skyler 1996). On the other hand, HbA1c levels can be influenced by hematologic conditions such as hemoglobinopathy, anemia, iron deficiency or overload, and recent blood loss or transfusion (Cohen et al. 2008; Sacks 2012; American Diabetes Association 2021). Given this clinical importance of HbA1c, recent genome-wide association studies (GWASs) have been conducted to understand the genetics of HbA1c. These genetic studies suggest two major pathways on how genetic variants influence HbA1c levels. One is glycemic-related pathway and the other is erythrocytic-related path- way. We will look in detail on the identified genetic associations with HbA1c and describe the clinical implications of these findings. Overview of Genome-Wide Association Studies of HbA1c Since the first GWAS of HbA1c in 2007 (Meigs et al. 2007) until now in 2021, over 15 GWASs have been conducted on HbA1c by single ancestral group analysis in Europeans (Meigs et al. 2007; Pare et al. 2008; Franklin et al. 2010; Soranzo et al. 2010; An et al. 2014; Prins et al. 2017), Hispanics/Latinos (Moon et al. 2019; Wojcik et al. 2019), and East Asians or South Asians (Ryu and Lee 2012; Chen et al. 2013; Chen et al. 2014; Hachiya et al. 2017; Kanai et al. 2018; Spracklen et al. 2018; Chai et al. 2020) as well as by trans-ancestral analysis (Wheeler et al. 2017; Chen et al. 2021; Sarnowski et al. 2019) (Table 1). Very recently, the Meta- Analysis of Glucose and Insulin-related Traits Consortium (MAGIC) published the most diverse and 1 of the largest GWASs on HbA1c of 215,977 individuals free of diabetes from 76 cohorts (including majority of prior GWAS cohorts), comprised of 70% Europeans, 13% East Asians, 7% Hispanics/Latinos, 6% African Ameri- cans, 3% South Asians, and 2% sub-Saharan Africans (Chen et al. 2021). The study identified 127 HbA1c-associated loci (218 variants), explaining about 4.5–6% of HbA1c variation (Chen et al. 2021). In addition, a whole genome sequencing (WGS)-based association study identified several low-frequency or rare variants associated with HbA1c (i.e., rs1039215 in HBG2 and HBE1, rs76723693 in coding region of G6PD with p.Leu353Pro) in 10,338 individuals (6158 Europeans, 3123 Africa Americans, 650 Hispanics, and 407 East Asians) in the Trans-Omics for Precision Medicine (TOPMed) Program (Sarnowski et al. 2019). The analysis with WGS is expected to grow and provide enhanced under- standing of genetics of HbA1c. 1 Linking Variants of Hemoglobin A1C and Glycemic Status 5

Contents Part I General Aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1 Linking Variants of Hemoglobin A1C and Glycemic Status . . . . . 3 Jee-Young Moon and Qibin Qi 2 Treatment Regimes in Diabetes and Their Impact on Biomarkers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 João P. Magalhães, Megan Hetherington-Rauth, and Luís Bettencourt Sardinha Part II Circulating and Body Fluid Biomarkers: Impact of Diabetes on Pathology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 3 Resistin as a Biomarker and Applications to Prediabetes . . . . . . . 67 Seyfettin Üstünsoy 4 Altered Metabolome of Amino Acids Species: A Source of Signature Early Biomarkers of T2DM . . . . . . . . . . . . . . . . . . . . . . 83 Anna Czajkowska, Ahsan Hameed, Mauro Galli Muhammad Umair Ijaz, Adam Kretowski, and Michal Ciborowski 5 Components of the Purine Metabolism Pathways as Biomarkers for the Early Diagnosis of Diabetes . . . . . . . . . . . . . . . . . . . . . . . . 127 Ahsan Hameed, Mauro Galli, Anna Czajkowska, Adam Kretowski, and Michal Ciborowski 6 Serpin A12 (Vaspin) as a Serine Protease Inhibitor . . . . . . . . . . . . 153 Armin Salek Maghsoudi, Shokoufeh Hassani, Kayvan Mirnia, and Mohammad Abdollahi 7 Advanced Glycation End Products in Diabetes . . . . . . . . . . . . . . . 171 Jesús A. Mosquera-Sulbarán and Juan Pablo Hernández-Fonseca 8 Markers of Liver Function and Insulin Resistance . . . . . . . . . . . . 195 Vicente Aleixandre Benites-Zapata, Sofía Lorena Bohórquez-Medina, and Andrea Lisbet Bohórquez-Medina vii 9 Biological Markers of Insulin Sensitivity Links with Dietary Antioxidant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217 Andrea Lisbet Bohórquez-Medina, Sofía Lorena Bohórquez-Medina, and Vicente Aleixandre Benites-Zapata 10 Serum Uric Acid and Metabolic Markers in Diabetes . . . . . . . . . . 239 Mohamed Rafiullah and Khalid Siddiqui 11 Urinary Interleukins and Kidney Damage in Diabetes . . . . . . . . . . 261 Rafael Noal Moresco, Guilherme Vargas Bochi, Manuela Borges Sangoi Cardoso, and José Antonio Mainardi de Carvalho 12 Serum Homocysteine as a Biomarker in Diabetes . . . . . . . . . . . . . 279 Em Yunir and Yully Astika Nugrahayning Aziza 13 3-Hydroxyisobutyrate (3-HIB): Features and Links as a Biological Marker in Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299 Simon Nitter Dankel 14 Proteomic Biomarkers: What They Are and How Type 2 Diabetes Mellitus Has Similarities with Other Diseases . . . . . . . . . 311 Karina Braga Gomes 15 Salivary C-Reactive Protein as a Biomarker and Implications for Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 Vaithinathan Selvaraju, Jeganathan Ramesh Babu, and Thangiah Geetha 16 Assessing Insulin Sensitivity in People with Type 1 Diabetes Without Euglycemic-Hyperinsulinemic Clamps . . . . . . . . . . . . . . . 349 Andrzej S. Januszewski and Alicia J. Jenkins 17 Serum Betatrophin: What It Shows and How It Alters in Gestational Diabetes Mellitus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375 Rauf Melekoglu and Ebru Celik 18 Biomarkers in Disease: Diabetes Methods, Discoveries, and Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395 Luiz Sérgio F. de Carvalho, Aline Ioshie Akamine Asari, Bruna Stefany Bento de Sousa Teles, Adriano de Britto Chaves Filho, and Marcos Yukio Yoshinaga 19 Correlations Between Renal Biomarkers and the Treatment Outcomes in Diabetes: Ophthalmic Aspects . . . . . . . . . . . . . . . . . . 411 Meng-Ju Tsai, Ivan Pochou Lai, Ming-Jui Lee, and Yi-Ting Hsieh 20 Serum Paraoxonase 1 as a Biomarker: Features and Applications in Type 2 Diabetes Mellitus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 435 Berrin Öztaş, Fatma Ceyla Eraldemir, and Hale Maral Kır viii Contents 21 The Ratio of Omega-6/Omega-3 Fatty Acid: Implications and Application as a Marker to Diabetes . . . . . . . . . . . . . . . . . . . . . . . 449 Shilpa S. Shetty, N. Suchetha Kumari, and Remya Varadarajan 22 Engulfment and Cell Motility Protein (ELMO)-1 as a Biomarker in Type II Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 469 Elfiani Elfiani, Anggelia Puspasari, and Zulkhair Ali 23 Brain-Derived Neurotrophic Factor and Vascular Endothelial Growth Factor A: Biomarkers Potential in Diabetes . . . . . . . . . . . 485 Yulia Karakulova and Tamara Filimonova 24 The Role of Glycated Albumin as a Biomarker of Glycemic Control in Diabetes and Chronic Kidney Disease . . . . . . . . . . . . . 513 Shanel Raghubeer, Don M. Matshazi, Dipuo D. Motshwari, Cecil J. Weale, Rajiv T. Erasmus, and Tandi E. Matsha Part III Genetic, Molecular, and Cellular Variables . . . . . . . . . . . . . 539 25 Epigenetics and 5-Hydroxymethylcytosines as a Biomarker in Type 2 Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 541 Chang Zeng and Wei Zhang 26 Adult Stem Cells as a Biomarker in Diabetes . . . . . . . . . . . . . . . . . 559 Scott Cohen and Sabyasachi Sen 27 The Search for Immunological Biomarkers in Type 1 Diabetes Mellitus (T1DM) and Multiple Sclerosis (MS): Th40 Cells Provide a Common Autoimmune Link . . . . . . . . . . . . . . . . . . . . . . 575 David H. Wagner 28 Epigenetically Modified DNA Fragments . . . . . . . . . . . . . . . . . . . . 597 Sarah A. Tersey and Raghavendra G. Mirmira 29 Urinary Glucose Excretion as a Biomarker for Precision Medicine in Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 615 Shinsuke Noso and Hiroshi Ikegami 30 Secreted Frizzled-Related Proteins 4 and 5: What They Are and Can They Be Used as a Biomarker in Gestational Diabetes Mellitus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 629 Rik H. J. Beernink and Joost H. N. Schuitemaker 31 Insights into the World of MicroRNAs . . . . . . . . . . . . . . . . . . . . . . 649 Marta Greco, Eusebio Chiefari, Maria Mirabelli, Alessandro Salatino, Salvatore Andrea Pullano, Antonio Aversa, Daniela Patrizia Foti, and Antonio Brunetti Contents ix 32 Genomic Ancestry as Biomarkers . . . . . . . . . . . . . . . . . . . . . . . . . . 669 Deborah Conte Santos 33 Hp1-1 as a Genetic Marker in Diabetes: Measures, Applications, and Correlations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 681 Agnieszka Filipek Part IV Functional Variables, Physiological Variables, and Platforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 703 34 Day-by-Day Home Blood Pressure Monitoring as a Biomarker in Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 705 Daisuke Suzuki, Satoshi Hoshide, and Kazuomi Kario 35 Methods for Measuring Blood Pressure and Applications to Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 729 Andriani Vazeou and George S. Stergiou 36 Carotid Bodies: Use of Chemosensitivity as a Biomarker in Prediabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 751 Silvia V. Conde, Marlene Lages, Maria P. Guarino, and Joana F. Sacramento 37 Optical Coherence Tomography Angiography for Biomarker Indices in Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 777 Eun Young Choi and Min Kim 38 Urinary Profiling with Liquid Chromatography-Mass Spectrometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 791 Lay-Harn Gam 39 Physiologic Measures in Diabetes: QTc Prolongation . . . . . . . . . . 809 Lauren Ehrhardt-Humbert and Matthew J. Singleton 40 Biomarkers of Myocardial Fibrosis in Diabetes, Echocardiography, and Magnetic Resonance Imaging . . . . . . . . . 821 Per Lav Madsen 41 Measures of Endothelial Function in Type 2 Diabetes: A Focus on Non-circulatory Methods of Measurement . . . . . . . . . . . . . . . . 849 Caroline Wei Shan Hoong 42 Measures of Endothelial Function in Type 2 Diabetes: A Focus on Circulatory Biomarkers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 867 Caroline Wei Shan Hoong x Contents Part V Biomarkers in Specific Conditions or Scenarios of Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 889 43 Biomarkers of Diabetes-Induced Nephropathy . . . . . . . . . . . . . . . 891 Bamidele Stephen Ajilore and Bosede Olaitan Ajilore 44 Serum Vitamin D As a Biomarker in Diabetic: Applications and Associations with Retinopathy . . . . . . . . . . . . . . . . . . . . . . . . . 909 Carolina Madeira and Manuel Falcão 45 Markers of Bacterial Translocation in Type 2 Diabetes Mellitus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 923 Marwa Ahmed Meheissen 46 Serum Leptin as a Biomarker in Diabetes . . . . . . . . . . . . . . . . . . . 947 Hind Shakir Ahmed 47 Vitreous Biomarkers: What They Are and How They May Be Used to Advance the Management of Diabetic Retinopathy . . . . . 963 Ricardo Lamy and Jay M. Stewart 48 Protein Pyrrole Adducts in Diabetes Mellitus . . . . . . . . . . . . . . . . . 991 Xiao Chen, Zhuyi Jiang, and Peter S. Spencer 49 Biomarkers in Gestational Diabetes . . . . . . . . . . . . . . . . . . . . . . . . 1021 Aykan Yucel and Betul Yakistiran 50 Metabolomic Biomarkers, Metabolite Patterns, and Gestational Diabetes Mellitus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1033 Ellen C. Francis and Wei Perng 51 Neuroinflammatory Biomarkers in Diabetic Encephalopathy: Linking Cholinergic and Cognitive Dysfunction . . . . . . . . . . . . . . 1053 Tosin A. Olasehinde, Sunday I. Oyeleye, Ademola O. Olaniran, and Md. Shahidul Islam Part VI Diet and Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1073 52 Selenium and Risk of Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1075 Shinje Moon and Chang-Myung Oh Part VII Models and Modeling in Diabetes . . . . . . . . . . . . . . . . . . . 1087 53 Models of Diabetes in Rats: A Focus on Diabetic Neuropathy and Biomarkers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1089 Che Aishah Nazariah Ismail and Idris Long Contents xi 54 Biomarkers in Experimental Diabetes: Studies with Syzygium Cumini (L.) and Links with the Sulfonylurea 1 Receptor . . . . . . . . 1111 Pratibha D. Nadig, Padmaja Shetty K, Anusha S. J, Meharban Asanaliyar, and Nagakumar Bharatam Part VIII Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1139 55 Recommended Resources for Biomarkers in Diabetes: Methods, Discoveries, and Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1141 Rajkumar Rajendram, Daniel Gyamfi, Vinood B. Patel, and Victor R. Preedy Correction to: Assessing Insulin Sensitivity in People with Type 1 Diabetes Without Euglycemic-Hyperinsulinemic Clamps . . . . . . . . . . . C1 Andrzej S. Januszewski and Alicia J. Jenkins Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1155

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