Michael Mambiya†
Mengke Shang†Yue WangQian LiShan LiuLuping YangQian ZhangKaili ZhangMengwei LiuFangfang NieFanxin Zeng
Wanyang Liu*- Department of Nutrition and Food Hygiene, School of Public Health, China Medical University, Shenyang, China
Diabetes has been a disease of public health concern for a number of decades. It was in the 1930s when scientists made an interesting discovery that the disease is actually divided into two types as some patients were insensitive to insulin treatment then. Type 2 Diabetes which happens to be the non-insulin dependent one is the most common form of the disease and is caused by the interaction between genetic and non-genetic factors. Despite conflicting results, numerous studies have identified genetic and non-genetic factors associated with this common type of diabetes. This review has summarized literature on some genes and non-genetic factors which have been identified to be associated with Type 2 diabetes. It has sourced literature from PubMed, Web of Science and Medline without any limitation to regions, publication types, or languages. The paper has started with the introduction, the play of non-genetic factors, the impact of genes in general, and ended with the interaction between some genes and environmental factors.
Introduction
Diabetes has been a disease of public health concern for a number of decades. It was in the 1930s when scientists made an interesting discovery that the disease is actually divided into two types, as some patients were insensitive to insulin treatment then (1). Since then, the study of the disease took a new twist with researchers looking at it in different perspectives. Although all the types of diabetes result in high blood sugar levels over a prolonged period, Type 1 diabetes is said to be an autoimmune disorder which results in the destruction of insulin-producing pancreatic β-cells making it insulin dependent while Type 2 diabetes is non-insulin dependent (2). Another form reported in some papers was gestational diabetes happening in pregnant women due to the hormones produced during pregnancy (3). Type 2 diabetes, the most common type of this complex disorder, is said to account for 85% of cases (some studies put the figure closer to 90%) and generally happens at an older age of life (4).
WHO puts Diabetes as the seventh death causing disease, affecting most communities in the world. They projected that the number of people with diabetes may increase up to 522 million by 2030. This is in line with the dramatic increase in the disease prevalence from 108 million people affected in 1980 to about 422 million adults in 2014. The global prevalence (age-standardized) of the disease nearly doubled in the same period, increasing from 4.7 to 8.5% in the adult population (5). The primary cause of death in individuals with diabetes is not the disease itself but its complications. If compared to the general non-diabetic population, patients with Type 2 diabetes have about 7 years shorter life expectancy and this can be attributed directly to the effects brought by the major diabetic complications (6). The motility rate of people with Type 2 diabetes tend to increase with age with some studies suggesting that diabetic men exhibit a higher mortality risk than diabetic women (7, 8).
The study for the pathogenesis of Type 2 diabetes has taken so many interesting turns with time but as many chronic disorders, it is understood that the disease is as a result of some genetic predisposition and environmental factors. There are so many non-genetic factors that have been found and identified to be associated with Type 2 diabetes by different researchers in different studies. These factors range from lifestyle, food and its components to some toxins and pollutants (1, 9, 10). Although environmental factors may play a role in the development of Type 2 diabetes (11), even with the same environmental exposure, some individuals may be highly affected and become more susceptible to this complex disorder than others, confirming that heredity has its own impact on the disease. It was until the 1980s when genetic research generally advanced and made it possible to investigate and identify some loci which could explain the hereditary components.
This review therefore aims at bringing literature from different researchers on genetic and non-genetic factors that are associated with Type 2 Diabetes. This information may be used to help in sharpening up the knowledge of future researchers and also improve the understanding of different individuals on the prevention, progression as well as treatment of the disease.
The Role of Non-Genetic Factors on Type 2 Diabetes
There are a number of non-genetic factors mentioned in different studies that are associated with Type 2 diabetes. The factors range from life style, food and its components, persistent organic pollutants as well as the gut ecosystem. Some of these factors also lead directly or indirectly to obesity and oxidative stress which are also known to be directly linked to Type 2 diabetes (12).
Life Style Factors
One's way of living has an impact on their health and well-being. Dating back to two decades ago, a number of behaviors have been associated with many chronic disorders including diabetes (13). Despite having a few conflicting results, behaviors such as alcohol intake, smoking, exercises and sedentariness have been known to be associated with Type 2 diabetes for decades (14), however some more factors such as stress, insomnia (15) and the use of certain clinical drugs such as antibiotics (16) have emerged and found to be associated with the diseases in recent years. Stress has an effect on glucose metabolism through the activities of hypothalamic-pituitary-adrenal (HPA) axis as its chronic activation and joint mechanisms affect insulin activities and may cause insulin resistance and β-cell dysfunction (17). Although other papers suggest that the association between insomnia and Type 2 diabetes is mainly confounded by other factors such as alcohol intake, smoking, sex and stress (18), insomnia stimulates appetite regulating hormones causing unnecessary gaining of weight which causally result in obesity and is also associated with increased blood pressure and sympathetic nervous system activities which are all linked to insulin resistance and Type 2 diabetes (19). Not excluding other types of antibiotics, the exposure to Fluoroquinolone antibiotics which are used to treat variety of illnesses such as respiratory, urinary tract and other infections are said to be associated with insulin resistance as they cause oxidative stress (20) and have the capacity to penetrate cell membranes and induce an intracellular magnesium deficiency which are all linked to Type 2 diabetes (21).
Food and Its Components
For decades nutrition and diets have been considered to play an important role in the development of many chronic disorders and the consumption of diets rich in certain food components such as saturated fats and high consumption of fast foods have all been linked to Type 2 diabetes (22). In recent years researchers have gone deeper to find out some more food components whose highly intake or deficiency can lead to Type 2 diabetes. It is necessary to investigate majority of micro nutrients as many prospective observational studies and clinical trials have shown that eating foods rich in or adequate intake or supplementation of some micronutrients or minerals such as Vitamin K (23), Vitamin D (24), Magnesium (25), and antioxidants such as β-carotene and α-tocopherol (26) has a reduced risk factor on Type 2 diabetes. Although other studies suggest otherwise, Vitamin K2 supplementation have shown that it could increase insulin sensitivity whereas Vitamin D plays a major role in insulin synthesis, release and sensitivity (23, 24, 27). Other vitamins such as Vitamin A or Retinol, Vitamins B, Vitamin C, or Ascorbic Acid and Vitamin E as well as their supplements have also been investigated to be associated with the disease but there results are conflicting (28). And what interests us is that there is a new evidence from a meta-regression analysis of some prospective cohort studies recently show that dietary magnesium intake is related to a reduced risk of Type 2 diabetes. A 100 mg/day increment in dietary magnesium intake was associated with an 8–13% reduction in risk of Type 2 diabetes (29).
Otherwise, studies in past two decades have also repeatedly mentioned that oxidative stress and inflammation are associated with Type 2 diabetes and this is mainly because of insufficient antioxidant defense. Evidence has it that low dietary intake of antioxidants such as β-carotene, α-tocopherol, and vitamin E play independent roles in the pathogenesis of Type 2 diabetes by increasing insulin resistance or impairing insulin action. Intake of diets with sufficient antioxidants, commonly fruits and vegetables, ensure a balanced defense mechanism on harmful effects of reactive oxygen species as they could prevent the gradual impairing of pancreatic β-cell, therefore reducing the risk of Type 2 diabetes (30, 31).
Dietary Structures
Dietary patterns, including traditional, healthy, Mediterranean, and Western dietary patterns, have recently gotten great attention in the evaluation of the relationship between diet and health (32). And dietary patterns may influence health more than certain nutrients or nutritional groups and the identification of one desirable dietary structure has gotten a lot of attention in public health in recent years to prevent Type 2 diabetes (33).
The types and quality of diet compounds might be related with the risk of Type 2 diabetes, disease progress, and its secondary disease. Some researches carried out in the Western societies shown that Western dietary structure including higher intake of red meat, processed meat, and refined grains was significantly associated with increased risk of Type 2 diabetes (34). Meanwhile, Erber et al. also found that an increased risk of diabetes was observed for participants adhering to a Western diet (35). One research from Greenland showed that the traditional food (mostly consisting of marine mammals and fish) was positively associated with Type 2 diabetes, impaired fasting glucose (IFG), and fasting plasma glucose (36). And a latest systematic review from de Carvalho et al. presented that Vegetarian, vegan, Mediterranean, and Dietary Approaches to Stop Hypertension dietary patterns reduced 0.8% on average of percentage of glycated hemoglobin, meanwhile, the reduction in fasting glycemia and improvement in Homeostasis Model Assessment of insulin sensitivity was also observed, considering all included studies (37). In addition, another umbrella review of meta-analyses of prospective observational studies found that dietary factors have an critical role in the primary prevention of Type 2 diabetes, and the study also pointed out that the high quality of evidence was only targeted at associations for incidence of Type 2 diabetes with moderate alcohol consumption, cereal fiber, whole grains, red meat, processed meat, bacon, and sugar sweetened beverages (38).
Role of Socioeconomic Status on Type 2 Diabetes
The public health of population groups links with socioeconomic status (SES) inextricably in different ways. SES is composed of many dimensions and is often measured by several index, such as income, education and occupation. SES has been recognized as an important determinate factor of population's health in both industrialized and developing countries (39). And the association between SES and Type 2 diabetes, which depends on the stage of economic and social development, differs worldwide (40, 41). The relationship between SES and Type 2 diabetes was positive several decades ago but is now negative in developed countries while in developing societies the relationship remains positive (41–43). What's more, a systematic review from Wu et al. found that low education is probably associated with an increased prevalence of Type 2 diabetes in China (40). And education in men and the measure of income in both genders is positively related to self-reported and total diabetes prevalence and awareness of diabetes in a Chinese population aged 45 years or older (44). Also, a latest finding from Tang et al. found economic development, income and gender differences also played a critical role in Type 2 diabetes (45).
Regional Imbalance on Type 2 Diabetes
Practically, diversity in natural environments, ethnic differences and social environment differences such as economic status, dietary structure, lifestyle, physical activity et al. in different regions, all of them might have impacts on Type 2 diabetes partly, and thus the integrated effects might result in regional imbalance on Type 2 diabetes. For example, different studies have observed different effects of fish intake on the risk of Type 2 diabetes (46). In reality, these differences can be put down to the geographical diversity of the studied regions. Fish intake in Europe and North America was within recommended intake, while in Asian countries, it was correlated with the decreased risk of Type 2 diabetes (46). Although the reason has not been recognized yet, it might be due to the differences in kinds of the consumed fish, type of cooking as well as the differences in the types and level of exposure to some levels of some contaminants (46). For the same ethnic population in societies at different levels of development may be observed for Chinese communities in Hong Kong, where there is a negative association between socioeconomic status and Type 2 diabetes, and Mainland China, where there is a positive association (47). Those research results might remind us that different and diverse factors existing in different regions might affect the incidence and prevalence of Type 2 diabetes which in return result in regional imbalance of Type 2 diabetes.
Persistent Organic Pollutants (POPs)
POPs which are mainly classified into five main types (polychloro-dibenzopara dioxins (PCDD), polychloro-dibenzo furans (PCBF), poly-chlorinated biphenyls (PCBs), organo-chlorine (OC) pesticides, and poly-brominated flame retardants) are said to be organic compounds that are/were produced as industrial chemicals or byproducts and have a resistant characteristic to any form of degradation process and find their way into the food web, resulting in potential effects on human health by accumulating in lipid containing tissues such as adipose tissue and circulating in the body while bound to lipids (48). polychloro-dibenzopara dioxins (PCDD), polychloro-dibenzo furans (PCBF), poly-chlorinated biphenyls (PCBs), organo-chlorine (OC) pesticides are Organo-chlorine compounds whose production and use were banned in the 1970s because of their toxicity characteristics but their residues are still found in water and soil and humans' exposure to Organo-chlorine compounds and POPs in general is mainly through the intake of animal fats by the consumption of meat, fish and daily products (49). Activities of a number of active low materials found in POPs such as γ-aminobutyric acid disturb the ion channel systems that are beneficial for regular pancreatic function thereby causing glucose homeostasis (50).
A number of individual POPs have been investigated through epidemiological and laboratory based studies for over two decades now. Epidemiological studies and animal studies which started a decade ago indicated that exposure to some organochlorine pesticides (OC) is associated with obesity, dyslipidemia, and insulin resistance (51–53). A recent study done in Taiwan found that exposure to high dioxin level (PCDD/Fs ≥20 pg WHO98-TEQDF/g lipid), a byproduct of herbicide production and paper bleaching increase the risk to Type 2 diabetes (54). These findings were in line with another study done in Germany where the risk of Type 2 diabetes increased in workers exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in a phenoxy herbicides factory whereas that differed from one study done in the USA where the re-analysis of a study on military workers during the Vietnam war showed that there was no risk after exposure to Orange and its contaminant TCDD (55). Exposure to another compound Bisphenol A (BPA) which is the starting material for the production of plastics has an effect on insulin synthesis, secretion in pancreatic beta cells and modifies insulin signal in the liver, skeletal muscle and adipose tissue, all of which lead to insulin resistance, obesity and Type 2 diabetes (56). A recent study concluded that elevated POP exposure has diabetogenic potential after investigating 3 organochlorine pesticides [hexachlorobenzene (HCB, β-hexachlorocyclohexane (β-HCH) and p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE)] and measuring 20 polychlorinated biphenyls (PCBs) in blanked plasma (57). This corroborated most recent review on POPs that exposure to Dichlorodiphenyl dichloroethylene (DDE), a major metabolite of dichlorodiphenyltrichloroethane (DDT) and trans-nonachlor, were confirmed to be associated with the disease (58).
Role of the Gut Ecosystem on Type 2 Diabetes
The collection of all microorganism resident in the gastrointestinal tract is referred to as gut microbiota. The human gastrointestinal tract is residence to an estimated 100 trillion bacteria, almost 10 times the total number of cells in the human body (59). Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria are the four major phyla in the gut ecosystem. On top of playing a vital role in the digestion process, the gut microbiota is vital in the maintenance of one's individual health, but is also reported to be associated with the pathogenesis of various metabolic diseases including Obesity and Type 2 Diabetes (60, 61). Results in a number of recent studies have suggest that gut microbiota in individuals with Type 2 diabetes differs from that of non-diabetic individuals (62), such that there is a co relationship that exists between Type 2 diabetes and increased abundance of Lactobacillus, lowered abundance of butyrate-producing microbes and fewer Clostridia (and more Firmicutes), suggesting that that Proteobacteria and Gram-negative Bacteroidetes activities do induce the pathogenesis of Type 2 diabetes (62, 63). Scientists have gone on to say that these microbiome can exist as new biomarker for Type 2 diabetes prediction (64). The is also a relation present between diet and gut microbiota, that alters the autoimmunity and energy balance, causing inflammation and metabolic dysfunction including Type 2 diabetes (65).
The Role of Genetics on Type 2 Diabetes
Although the non-genetic factors play a major role in the development of Type 2 diabetes, even with the same exposure, the susceptibility to the disease will vary between individuals which make it possible for researchers to conclude that the disease is as a result of heredity as well. Heredity has all along been mentioned to play an important role in the development of diabetes but it was until 3 decades ago (in the 1980s) that genetic variants started to be identified to back up these heredity claims after the advancement of human genetic studies and the coming in of modern genetic technologies (10, 66). Candidate gene studies were the ancient studies used in identifying genes that are associated with Type 2 diabetes before the coming of genome wide linkage and genome wide association studies but only a few genes and variants were identified (67).
Candidate Gene Studies on Type 2 Diabetes
Candidate gene study approach, focusing on genes that are in some way related to the disease or with prior knowledge to the gene function, were the ancient research studies used in identifying genes associated with chronic diseases including Type 2 diabetes. By the year 2000 Candidate gene studies had identified a number of genes to be associated with Type 2 diabetes although the approach was being criticized for lacking roughness and sensitivity as some genes which were already known to have an impact on insulin activities were not confirmed in population studies as they showed association and having only investigated a limited number of variants and genes in limited, small or unmatched populations that made it difficult to replicate weak associations that were detected (68, 69). This prompted researchers to come up with large scale candidate genes association studies. One research group in the United Kingdom investigated 152 single polymorphisms in 71 candidate genes in 2003 and found ABCC8 (sulphonylurea receptor), KCNJ11 (KIR6.2), SLC2A2 (GLUT2), HNF4A (HNF4α), and INS genes having an effect on pancreatic β-cell function there by inducing insulin resistance and another three genes, INSR, PIK3R1, and SOS1 to be associated with insulin action. Replication studies confirmed these results (70). A similar large scale study was also performed in Japan (71) and was followed by another one in Germany 5 years later where some more genes (SLC27A5, FABP6, Thr79Met, DBI, PTGES2, and CLPS) were identified (72). Genes such as RAPGEF1, HNF1 homeobox A (HNF1A) and HNF1 homeoboxB (HNF1B) were also identified with the same approach.
Genetic Linkage Studies on Type 2 Diabetes
Linkage is a genetic tendency where genetic markers are inherited together as a result of being near to one another on the same chromosome. Genetic linkage analysis, one of the old study approaches, focuses on genomic regions with large genetic effect that can influence the development of a disease (73, 74). Genome-wide linkage scans have proved that some genes are associated with Type 2 diabetes on specific chromosomes such as 4q, 12q, and 22q in AA, 6p in EA, 2p in AI and 13q in African American (75), 3p at marker D3S2406 in Mexicans Americans (76) and 2p and 13p of Chinese (77) increase the risk of developing the disease. Linkage studies have been used to identify genes associated with different chronic disorders with unknown pathogenesis such as Type 2 diabetes, but they are considered to be unsuccessful by many researchers because they have only identified a few genes (75). Many studies, including one review (published in 2013) reported that these studies were only successful in reviewing two genes [calpain-10CAPN10 and transcription factor 7-like 2 (T-cell specific, HMG-box) (TCF7L2)] (10) associated with Type 2 diabetes although this differs from what was reported earlier where three more genes HNF4A, ENPP1, ADIPOQ were included (78).
Genome Wide Association Studies on Type 2 Diabetes
Until the early 2000s, so many candidate genes and linkage studies have been done but only succeeded in identifying very few susceptibility loci and the coming of genome wide association studies which focuses on searching single nucleotide polymorphisms (SNPs) that happen more frequent in people having a certain disease brought an interesting twist and is thought to be a breakthrough concerning the genetic research on Type 2 diabetes (10, 66, 79). Genes such KLF14, ENPP1, ADAMTS9, ADIPOQ, IRS, GCKR, SREBF1, FTO HNF4A, NOTCH2, IGF2BP2, CDKAL1, JAZF1, SCL30A8, HHEX, TCF7L2, EXT2, FTO and many others have been identified by this approach. By 2009 GWAS had identified 19 more SNPs associated with the Type 2 diabetes (80) and this number increased to more than 60 SNPs by 2016 in Asian and European ancestry alone with researchers not only identified the variants and the genes involved but also validated the effects conferred by these reported common variants in different populations (81) as conferred impacts may differ or might be the same but with substantial differences in allele frequencies as it is the evident with Chinese and European populations on variants in IGF2BP2, CDKAL1, JAZF1, SCL30A8, HHEX, TCF7L2, EXT2, and FTO (82) and Europeans and North African Arabs in variants in TCF7L2 and other genes (83) which made it possible to conclude that biological actions and activities of common variants may be similar in different ethnic groups.
The advancement in genetic tools and the coming of genome-wide association studies have also made it possible for researchers to do some comprehensive pharmacogenomics studies on variability in drug response and improve their understanding on why some patients develop drug resistance to Type 2 diabetes pharmacological treatment as the first recommended approach after failure in lifestyle changes. Researchers have identified more SNPs and genes involved in drug metabolism such as CYP2C9 and those involved in insulin signaling such as KCNJ11 and PPARG (84). GWAS have reviewed how certain variants and genes also have an impact on individual Type 2 diabetic drugs such as variants in ABCC8 and KCNJ11 on oldest oral agent Sulfonylureas as well as SLC12A1 and AQP2 on Thiazolidinediones (TZDs),which all help clinicians in making direct individual decisions on efficient dosages for prevention, treatment and management of Type 2 diabetes (85).
Gene-environmental Interaction and the Risk of Type 2 Diabetes
The interaction of genes and environment factors result in genotype plasticity and has become one of the interesting areas of study in finding the pathogenesis of different chronic diseases (86). The advancement in research tools on both genetic and environmental research has made it possible to identify variants and environmental factors that interact and increase the risk on Type 2 diabetes. In Chinese population, the interaction between an organochloride which is one of the isomers of hexachlorocyclohexane (HCH) called (β-hexachlorocyclohexane (β-HCH) and variants of ADIPOQ gene is said to be associated with Type 2 diabetes risk (52) where as SLC30A8 rs13266634 which on its own is associated with higher odds of the Type 2 diabetes has a modification effect on plasma zinc concentration association with the disease, where its lower odds association with Type 2 diabetes is nullified (87). Recent studies in the USA have reported negative association between two paired genes and environmental factors interactions. One was between variant rs1092393 found in NOTCH2 gene and heptachlor epoxide (a byproduct of insecticide Heptachlor) and another between the same variant and cis-b-carotene. Both the gene and its variants and the environmental factors mentioned here have been identified to be associated with Type 2 diabetes in isolation in different genetic and environmental studies recently (9). Dietary carbohydrates and fiber were also found to be modifiers of some genetic variants which were associated with Type 2 diabetes specifically for ADAMT59 rs4607103, DKN2A/2B rs1801282, FTO rs8050136 in non-Hispanic whites, ADAMT59 rs4607103, THADA rs7578597 in non-Hispanic blacks and NOTCH2 rs1092398 and TSPAN8-LGRS rs7961581 in Mexican Americans (88).
Epigenetics and Type 2 Diabetes
Despite advancement of genetic research tools, they have only been able to explain and identify genetic variants that increase the risk of Type 2 diabetes by 10.0–30.0% (89). Epigenetics is a field which can help in coming up of more understanding and clearance in the pathogenesis as it can provide a molecular link between genetics, environmental factors and Type 2 diabetes (90). Epigenetics which include DNA methylations, histone modifications, and microRNAs is the heritability alteration or change in gene functions, that do not involve changes in nucleotide sequence and is said to explain a portion of the pathogenesis of chronic diseases as it suggests that these modifications can be passed from one cell generation to the next and between generations of species as first evident in plant studies although there is minimal information of such in animal studies (91). In recent researches, a variety of epigenetic mechanisms and factors have been reported to increase the risk of developing Type 2 diabetes as they play vital roles in a number of cellular process. For example, maternal nutrition and environmental conditions such as famine result in the irreversible change in the methylation in infants and a research on mice showed that infants born from Gestational diabetes mellitus (GDM) mothers show hypermethylation and epigenetic down regulation of IGF2 and H19 genes which has an impact on insulin sensitivity (92). Epigenetic mechanisms also have an impact gene networks that are involved in insulin resistance and insufficiency as it controls genes like GLP1 receptor and Paired box 4 (PAX4) which are among the major genes that are associated with β-cell formation and functions (93). It is of much importance to conduct more human studies to explore more on the role of epigenetics on Type 2 diabetes and other chronic diseases as heritability that is observed and concluded may not be necessary as a result of inherited variations in DNA sequence, but a number of Epigenetic mechanisms and factors such as the intrauterine life observed in animal studies.
Conclusion
Type 2 Diabetes Mellitus development is as a result of both environmental and genetic factors. This paper has outlined how both environmental and genetic factors contribute to the development of T2DM. Hope to provide some useful clues for in-depth studies regarding to study on the Type 2 diabetes in the future.
Author Contributions
MM designed the paper and was responsible for the summarization of the review. MS contributed to the sourcing of data, selection of papers, data interpretation, manuscript development and revisions, approved the final version of the submitted manuscript, and was responsible for the summarization of the review. YW, QL, SL, LY, QZ, KZ, ML, FN, FZ, and WL contributed to data interpretation, manuscript development and revisions, and approved the final version of the submitted manuscript. WL was responsible for the supervision of the current work.
Funding
This work was supported by the National Natural Science Foundation of China (Grant No. 81573240). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
References
1. Das AK, Shah S. History of diabetes: from ants to analogs. J Assoc Physicians India. (2011) 59(Suppl.):6–7.
2. Zaccardi F, Webb DR, Yates T, Davies MJ. Pathophysiology of type 1 and type 2 diabetes mellitus: a 90-year perspective. Postgrad Med J. (2016) 92:63–9. doi: 10.1136/postgradmedj-2015-133281
3. Kharroubi AT, Darwish HM. Diabetes mellitus: the epidemic of the century. World J Diabetes. (2015) 6:850–67. doi: 10.4239/wjd.v6.i6.850
4. Cho NH, Shaw JE, Karuranga S, Huang Y, da Rocha Fernandes JD, Ohlrogge AW, et al. IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045. Diabet Res Clin Pract. (2018) 138:271–81. doi: 10.1016/j.diabres.2018.02.023
6. Deshpande AD, Harris-Hayes M, Schootman M. Epidemiology of diabetes and diabetes-related complications. Phys Therapy. (2008) 88:1254–64. doi: 10.2522/ptj.20080020
7. Zhu M, Li J, Li Z, Luo W, Dai D, Weaver SR, et al. Mortality rates and the causes of death related to diabetes mellitus in Shanghai Songjiang District: an 11-year retrospective analysis of death certificates. BMC Endocr Disord. (2015) 15:45. doi: 10.1186/s12902-015-0042-1
8. Kang YM, Kim YJ, Park JY, Lee WJ, Jung CH. Mortality and causes of death in a national sample of type 2 diabetic patients in Korea from 2002 to 2013. Cardiovasc Diabetol. (2016) 15:131. doi: 10.1186/s12933-016-0451-0
9. Patel CJ, Chen R, Kodama K, Ioannidis JP, Butte AJ. Systematic identification of interaction effects between validated genome- and environment-wide associations on Type 2 Diabetes Mellitus. AMIA Jt Summits Transl Sci Proc. (2013) 2013:135. doi: 10.1007/s00439-012-1258-z
10. Ali O. Genetics of type 2 diabetes. World J Diabetes. (2013) 4:114–23. doi: 10.4239/wjd.v4.i4.114
11. Dong G, Qu L, Gong X, Pang B, Yan W, Wei J. Effect of social factors and the natural environment on the etiology and pathogenesis of diabetes mellitus. Int J Endocrinol. (2019) 2019:8749291. doi: 10.1155/2019/8749291
12. Marseglia L, Manti S, D'Angelo G, Nicotera A, Parisi E, Di Rosa G, et al. Oxidative stress in obesity: a critical component in human diseases. Int J Mol Sci. (2014) 16:378–400. doi: 10.3390/ijms16010378
13. Steyn K, Damasceno A. Lifestyle and related risk factors for chronic diseases. In: Jamison DT, Feachem RG, Makgoba MW, Bos ER, Baingana FK, Hofman KJ, et al., editors. Disease and Mortality in Sub-Saharan Africa. 2nd ed. Washington, DC: Disease and Mortality in Sub-Saharan Africa (2006). p. 247–66.
14. Agborsangaya CB, Gee ME, Johnson ST, Dunbar P, Langlois MF, Leiter LA, et al. Determinants of lifestyle behavior in type 2 diabetes: results of the 2011 cross-sectional survey on living with chronic diseases in Canada. BMC Public Health. (2013) 13:451. doi: 10.1186/1471-2458-13-451
15. Spruijt-Metz D, O'Reilly GA, Cook L, Page KA, Quinn C. Behavioral contributions to the pathogenesis of type 2 diabetes. Curr Diab Rep. (2014) 14:475. doi: 10.1007/s11892-014-0475-3
16. Mikkelsen KH, Knop FK, Vilsboll T, Frost M, Hallas J, Pottegard A. Use of antibiotics in childhood and risk of Type 1 diabetes: a population-based case-control study. Diabet Med. (2017) 34:272. doi: 10.1111/dme.13262
17. Harris ML, Oldmeadow C, Hure A, Luu J, Loxton D, Attia J. Stress increases the risk of type 2 diabetes onset in women: A 12-year longitudinal study using causal modelling. PLoS ONE. (2017) 12:e0172126. doi: 10.1371/journal.pone.0172126
18. Green MJ, Espie CA, Popham F, Robertson T, Benzeval M. Insomnia symptoms as a cause of type 2 diabetes Incidence: a 20 year cohort study. BMC Psychiatry. (2017) 17:94. doi: 10.1186/s12888-017-1268-4
19. Li Y, Gao X, Winkelman JW, Cespedes EM, Jackson CL, Walters AS, et al. Association between sleeping difficulty and type 2 diabetes in women. Diabetologia. (2016) 59:719–27. doi: 10.1007/s00125-015-3860-9
20. Kalghatgi S, Spina CS, Costello JC, Liesa M, Morones-Ramirez JR, Slomovic S, et al. Bactericidal antibiotics induce mitochondrial dysfunction and oxidative damage in mammalian cells. Sci Trans Med. (2013) 5:192ra85. doi: 10.1126/scitranslmed.3006055
21. Telfer SJ. Fluoroquinolone antibiotics and type 2 diabetes mellitus. Med Hypotheses. (2014) 83:263–9. doi: 10.1016/j.mehy.2014.05.013
22. Hu FB, van Dam RM, Liu S. Diet and risk of Type II diabetes: the role of types of fat and carbohydrate. Diabetologia. (2001) 44:805–17. doi: 10.1007/s001250100547
23. Li Y, Chen JP, Duan L, Li S. Effect of vitamin K2 on type 2 diabetes mellitus: a review. Diabetes Res Clin Pract. (2018) 136:39–51. doi: 10.1016/j.diabres.2017.11.020
24. Lu L, Bennett DA, Millwood IY, Parish S, McCarthy MI, Mahajan A, et al. Association of vitamin D with risk of type 2 diabetes: a mendelian randomisation study in European and Chinese adults. PLoS Med. (2018) 15:e1002566. doi: 10.1371/journal.pmed.1002566
25. Barbagallo M, Dominguez LJ. Magnesium and type 2 diabetes. World J Diabet. (2015) 6:1152–7. doi: 10.4239/wjd.v6.i10.1152
26. Arnlov J, Zethelius B, Riserus U, Basu S, Berne C, Vessby B, et al. Serum and dietary beta-carotene and alpha-tocopherol and incidence of type 2 diabetes mellitus in a community-based study of Swedish men: report from the Uppsala Longitudinal Study of Adult Men (ULSAM) study. Diabetologia. (2009) 52:97–105.
27. Gulseth HL, Wium C, Angel K, Eriksen EF, Birkeland KI. Effects of Vitamin D Supplementation on insulin sensitivity and insulin secretion in subjects with type 2 diabetes and Vitamin D deficiency: a randomized controlled trial. Diabetes Care. (2017) 40:872–8. doi: 10.2337/dc16-2302
28. Valdés-Ramos R, Ana Laura GL, Elina MCB, Donají BAA. Vitamins and Type 2 Diabetes Mellitus. Endocrine Metabolic Immune Disorders Drug Targets. (2015) 15:54–63. doi: 10.2174/1871530314666141111103217
29. Fang X, Han H, Li M, Liang C, Fan Z, Aaseth J, et al. Dose-response relationship between dietary magnesium intake and risk of type 2 diabetes mellitus: a systematic review and meta-regression analysis of prospective cohort studies. Nutrients. (2016) 8:E739. doi: 10.3390/nu8110739
30. Quansah DY, Ha K, Jun S, Kim SA, Shin S, Wie GA, et al. Associations of dietary antioxidants and risk of type 2 diabetes: data from the 2007-2012 korea national health and nutrition examination survey. Molecules. (2017) 22:E1664. doi: 10.3390/molecules22101664
31. Arnlov J, Zethelius B, Riserus U, Basu S, Berne C, Vessby B, et al. Serum and dietary beta-carotene and alpha-tocopherol and incidence of type 2 diabetes mellitus in a community-based study of Swedish men: report from the Uppsala Longitudinal Study of Adult Men (ULSAM) study. Diabetologia. (2009) 52:97–105. doi: 10.1007/s00125-008-1189-3
32. Mandalazi E, Drake I, Wirfalt E, Orho-Melander M, Sonestedt E. A high diet quality based on dietary recommendations is not associated with lower incidence of type 2 diabetes in the malmo diet and cancer cohort. Int J Mol Sci. (2016) 17:901. doi: 10.3390/ijms17060901
33. Baxter AJ, Coyne T, McClintock C. Dietary patterns and metabolic syndrome–a review of epidemiologic evidence. Asia Pacific J Clin Nutrit. (2006) 15:134–42.
34. van Dam RM, Rimm EB, Willett WC, Stampfer MJ, Hu FB. Dietary patterns and risk for type 2 diabetes mellitus in U.S. men. Ann Int Med. (2002) 136:201–9. doi: 10.7326/0003-4819-136-3-200202050-00008
35. Erber E, Hopping BN, Grandinetti A, Park SY, Kolonel LN, Maskarinec G. Dietary patterns and risk for diabetes: the multiethnic cohort. Diabetes Care. (2010) 33:532–8. doi: 10.2337/dc09-1621
36. Jeppesen C, Bjerregaard P, Jorgensen ME. Dietary patterns in Greenland and their relationship with type 2 diabetes mellitus and glucose intolerance. Public Health Nutrit. (2014) 17:462–70. doi: 10.1017/S136898001300013X
37. de Carvalho GB, Dias-Vasconcelos NL, Santos RKF, Brandao-Lima PN, da Silva DG, Pires LV. Effect of different dietary patterns on glycemic control in individuals with type 2 diabetes mellitus: a systematic review. Crit Rev Food Sci Nutrit. (2019) 16:1–12. doi: 10.1080/10408398.2019.1624498
38. Neuenschwander M, Ballon A, Weber KS, Norat T, Aune D, Schwingshackl L, et al. Role of diet in type 2 diabetes incidence: umbrella review of meta-analyses of prospective observational studies. BMJ. (2019) 366:l2368. doi: 10.1136/bmj.l2368
39. Cutler D, Lleras-Muney A, Vogl T. Socioeconomic Status and Health: Dimensions and Mechanisms. Oxford: The Oxford Handbook of Health Economics (2008). doi: 10.3386/w14333
40. Wu H, Meng X, Wild SH, Gasevic D, Jackson CA. Socioeconomic status and prevalence of type 2 diabetes in mainland China, Hong Kong and Taiwan: a systematic review. J Global Health. (2017) 7:011103. doi: 10.7189/jogh.07.011103
41. Bird Y, Lemstra M, Rogers M, Moraros J. The relationship between socioeconomic status/income and prevalence of diabetes and associated conditions: a cross-sectional population-based study in Saskatchewan, Canada. Int J Equity Health. (2015) 14:93. doi: 10.1186/s12939-015-0237-0
42. Imkampe AK, Gulliford MC. Increasing socio-economic inequality in type 2 diabetes prevalence–repeated cross-sectional surveys in England 1994-2006. Eur J Public Health. (2011) 21:484–90. doi: 10.1093/eurpub/ckq106
43. Illangasekera U, Rambodagalla S, Tennakoon S. Temporal trends in the prevalence of diabetes mellitus in a rural community in Sri Lanka. J Roy Soc Promot Health. (2004) 124:92–4. doi: 10.1177/146642400412400214
44. Wu H, Jackson CA, Wild SH, Jian W, Dong J, Gasevic D. Socioeconomic status and self-reported, screen-detected and total diabetes prevalence in Chinese men and women in 2011-2012: a nationwide cross-sectional study. J Global Health. (2018) 8:020501. doi: 10.7189/jogh.08.020501
45. Tang K, Wang H, Liu Y, Tan SH. Interplay of regional economic development, income, gender and type 2 diabetes: evidence from half a million Chinese. J Epidemiol Commun Health. (2019) 73:867–73. doi: 10.1136/jech-2018-211091
46. Wu JH, Micha R, Imamura F, Pan A, Biggs ML, Ajaz O, et al. Omega-3 fatty acids and incident type 2 diabetes: a systematic review and meta-analysis. Br J Nutrit. (2012) 107(Suppl. 2):S214–27. doi: 10.1017/S0007114512001602
47. Ko GT, Chan JC, Yeung VT, Chow CC, Tsang LW, Cockram CS. A low socio-economic status is an additional risk factor for glucose intolerance in high risk Hong Kong Chinese. Eur J Epidemiol. (2001) 17:289–95. doi: 10.1023/A:1017935707807
48. La Merrill M, Emond C, Kim MJ, Antignac JP, Le Bizec B, Clement K, et al. Toxicological function of adipose tissue: focus on persistent organic pollutants. Environ Health Perspect. (2013) 121:162–9. doi: 10.1289/ehp.1205485
49. Carpenter DO. Environmental contaminants as risk factors for developing diabetes. Rev Environment Health. (2008) 23:59–74. doi: 10.1515/REVEH.2008.23.1.59
50. Buijsse B, Simmons RK, Griffin SJ, Schulze MB. Risk assessment tools for identifying individuals at risk of developing type 2 diabetes. Epidemiol Rev. (2011) 33:46–62. doi: 10.1093/epirev/mxq019
51. Howell GE III, Mulligan C, Meek E, Chambers JE. Effect of chronic p,p'-dichlorodiphenyldichloroethylene (DDE) exposure on high fat diet-induced alterations in glucose and lipid metabolism in male C57BL/6H mice. Toxicology. (2015) 328:112–22. doi: 10.1016/j.tox.2014.12.017
52. Lee DH, Steffes MW, Sjodin A, Jones RS, Needham LL, Jacobs DR Jr. Low dose organochlorine pesticides and polychlorinated biphenyls predict obesity, dyslipidemia, and insulin resistance among people free of diabetes. PLoS ONE. (2011) 6:e15977. doi: 10.1371/journal.pone.0015977
53. Kelly BC, Ikonomou MG, Blair JD, Morin AE, Gobas FA. Food web-specific biomagnification of persistent organic pollutants. Science. (2007) 317:236–9. doi: 10.1126/science.1138275
54. Huang CY, Wu CL, Yang YC, Chang JW, Kuo YC, Cheng YY, et al. Association between dioxin and diabetes mellitus in an endemic area of exposure in taiwan: a population-based study. Medicine. (2015) 94:e1730. doi: 10.1097/MD.0000000000001730
55. Kerger BD, Scott PK, Pavuk M, Gough M, Paustenbach DJ. Re-analysis of Ranch Hand study supports reverse causation hypothesis between dioxin and diabetes. Crit Rev Toxicol. (2012) 42:669–87. doi: 10.3109/10408444.2012.694095
56. Chevalier N, Fenichel P. [Endocrine disruptors: a missing link in the pandemy of type 2 diabetes and obesity?]. Presse Med. (2016) 45:88–97. doi: 10.1016/j.lpm.2015.08.008
57. Zong G, Valvi D, Coull B, Goen T, Hu FB, Nielsen F, et al. Persistent organic pollutants and risk of type 2 diabetes: a prospective investigation among middle-aged women in Nurses' Health Study II. Environ Int. (2018) 114:334–42. doi: 10.1016/j.envint.2017.12.010
58. Taylor KW, Novak RF, Anderson HA, Birnbaum LS, Blystone C, DeVito M, et al. Evaluation of the association between Persistent Organic Pollutants (POPs) and diabetes in epidemiological studies: a national toxicology program workshop review. Environ Health Perspect. (2013) 121:774–83. doi: 10.1289/ehp.1205502
59. Berg RD. The indigenous gastrointestinal microflora. Trends Microbiol. (1996) 4:430–5. doi: 10.1016/0966-842X(96)10057-3
60. Han JL, Lin HL. Intestinal microbiota and type 2 diabetes: from mechanism insights to therapeutic perspective. World J Gastroenterol. (2014) 20:17737–45. doi: 10.3748/wjg.v20.i47.17737
61. Ley RE, Backhed F, Turnbaugh P, Lozupone CA, Knight RD, Gordon JI. Obesity alters gut microbial ecology. Proc Natl Acad Sci USA. (2005) 102:11070–5. doi: 10.1073/pnas.0504978102
62. Larsen N, Vogensen FK, van den Berg FWJ, Nielsen DS, Andreasen AS, Pedersen BK, et al. Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults. PLoS ONE. (2010) 5:e9085. doi: 10.1371/journal.pone.0009085
63. Qin J, Li Y, Cai Z, Li S, Zhu J, Zhang F, et al. A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature. (2012) 490:55–60. doi: 10.1038/nature11450
64. Wang Y, Luo X, Mao X, Tao Y, Ran X, Zhao H, et al. Gut microbiome analysis of type 2 diabetic patients from the Chinese minority ethnic groups the Uygurs and Kazaks. PLoS ONE. (2017) 12:e0172774. doi: 10.1371/journal.pone.0172774
65. Ganesan K, Chung SK, Vanamala J, Xu B. Causal relationship between diet-induced gut microbiota changes and diabetes: a novel strategy to transplant faecalibacterium prausnitzii in preventing diabetes. Int J Mol Sci. (2018) 19:3720. doi: 10.3390/ijms19123720
66. McCarthy MI, Zeggini E. Genome-wide association studies in type 2 diabetes. Curr Diab Rep. (2009) 9:164–71. doi: 10.1007/s11892-009-0027-4
67. Song Y, Niu T, Manson JE, Kwiatkowski DJ, Liu S. Are variants in the CAPN10 gene related to risk of type 2 diabetes? A quantitative assessment of population and family-based association studies. Ame J Hum Genet. (2004) 74:208–22. doi: 10.1086/381400
68. Altshuler D, Hirschhorn JN, Klannemark M, Lindgren CM, Vohl MC, Nemesh J, et al. The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat Genet. (2000) 26:76–80. doi: 10.1038/79216
69. Prasad RB, Groop L. Genetics of type 2 diabetes—pitfalls and possibilities. Genes. (2015) 6:87–123. doi: 10.3390/genes6010087
70. Barroso I, Luan J, Middelberg RP, Harding AH, Franks PW, Jakes RW, et al. Candidate gene association study in type 2 diabetes indicates a role for genes involved in beta-cell function as well as insulin action. PLoS Biol. (2003) 1:E20. doi: 10.1371/journal.pbio.0000020
71. Daimon M, Ji G, Saitoh T, Oizumi T, Tominaga M, Nakamura T, et al. Large-scale search of SNPs for type 2 DM susceptibility genes in a Japanese population. Biochem Biophys Rescommunicat. (2003) 302:751–8. doi: 10.1016/S0006-291X(03)00248-1
72. Fisher E, Nitz I, Lindner I, Rubin D, Boeing H, Mohlig M, et al. Candidate gene association study of type 2 diabetes in a nested case-control study of the EPIC-Potsdam cohort - role of fat assimilation. Mol Nutrit Food Res. (2007) 51:185–91. doi: 10.1002/mnfr.200600162
73. Dawn Teare M, Barrett JH. Genetic linkage studies. Lancet. (2005) 366:1036–44. doi: 10.1016/S0140-6736(05)67382-5
74. Cui Y, Li G, Li S, Wu R. Designs for linkage analysis and association studies of complex diseases. Methods Mol Biol. (2010) 620:219–42. doi: 10.1007/978-1-60761-580-4_6
75. Malhotra A, Igo RP Jr, Thameem F, Kao WH, Abboud HE, Adler SG, et al. Genome-wide linkage scans for type 2 diabetes mellitus in four ethnically diverse populations-significant evidence for linkage on chromosome 4q in African Americans: the Family Investigation of Nephropathy and Diabetes Research Group. Diabetes Metabol Res Rev. (2009) 25:740–7. doi: 10.1002/dmrr.1031
76. Hunt KJ, Lehman DM, Arya R, Fowler S, Leach RJ, Goring HH, et al. Genome-wide linkage analyses of type 2 diabetes in Mexican Americans: the San Antonio Family Diabetes/Gallbladder Study. Diabetes. (2005) 54:2655–62. doi: 10.2337/diabetes.54.9.2655
77. Das SK, Elbein SC. The genetic basis of type 2 diabetes. Cellscience. (2006) 2:100–131. doi: 10.1901/jaba.2006.2-100
78. Murea M, Ma L, Freedman BI. Genetic and environmental factors associated with type 2 diabetes and diabetic vascular complications. Rev Diabet Stud. (2012) 9:6–22. doi: 10.1900/RDS.2012.9.6
79. Wang X, Strizich G, Hu Y, Wang T, Kaplan RC, Qi Q Genetic markers of type 2 diabetes: Progress in genome-wide association studies and clinical application for risk prediction. J Diabetes. (2016) 8:24–35. doi: 10.1111/1753-0407.12323
80. Lyssenko V, Groop L. Genome-wide association study for type 2 diabetes: clinical applications. Curr Opin Lipidol. (2009) 20:87–91. doi: 10.1097/MOL.0b013e32832923af
81. Rao P, Zhou Y, Ge SQ, Wang AX, Yu XW, Alzain MA, et al. Validation of type 2 diabetes risk variants identified by genome-wide association studies in Northern Han Chinese. Int J Environ Res Public Health. (2016) 13:863. doi: 10.3390/ijerph13090863
82. Chang YC, Liu PH, Yu YH, Kuo SS, Chang TJ, Jiang YD, et al. Validation of type 2 diabetes risk variants identified by genome-wide association studies in han chinese population: a replication study and meta-analysis. PLoS ONE. (2014) 9:e95045. doi: 10.1371/journal.pone.0095045
83. Cauchi S, Ezzidi I, El Achhab Y, Mtiraoui N, Chaieb L, Salah D, et al. European genetic variants associated with type 2 diabetes in North African Arabs. Diabet Metabol. (2012) 38:316–23. doi: 10.1016/j.diabet.2012.02.003
84. Pollastro C, Ziviello C, Costa V, Ciccodicola A. Pharmacogenomics of drug response in type 2 diabetes: toward the definition of tailored therapies? PPAR Res. (2015) 2015:415149. doi: 10.1155/2015/415149
85. Liao WL, Tsai FJ. Personalized medicine in type 2 diabetes. BioMedicine. (2014) 4:8. doi: 10.7603/s40681-014-0008-z
86. Singh RS. Darwin's legacy II: why biology is not physics, or why it has taken a century to see the dependence of genes on the environment. Genome. (2015) 58:55–62. doi: 10.1139/gen-2015-0012
87. Shan Z, Bao W, Zhang Y, Rong Y, Wang X, Jin Y, et al. Interactions between zinc transporter-8 gene (SLC30A8) and plasma zinc concentrations for impaired glucose regulation and type 2 diabetes. Diabetes. (2014) 63:1796–803. doi: 10.2337/db13-0606
88. Villegas R, Goodloe RJ, McClellan BE Jr, Boston J, Crawford DC. Gene-carbohydrate and gene-fiber interactions and type 2 diabetes in diverse populations from the National Health and Nutrition Examination Surveys (NHANES) as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study. BMC Genet. (2014) 15:69. doi: 10.1186/1471-2156-15-69
89. Brunetti A, Chiefari E, Foti D. Recent advances in the molecular genetics of type 2 diabetes mellitus. World J Diabetes. (2014) 5:128–40. doi: 10.4239/wjd.v5.i2.128
90. Karachanak-Yankova S, Dimova R, Nikolova D, Nesheva D, Koprinarova M, Maslyankov S, et al. Epigenetic alterations in patients with type 2 diabetes mellitus. Balkan J Med Genet. (2015) 18:15–24. doi: 10.1515/bjmg-2015-0081
91. Ling C, Groop L. Epigenetics: a molecular link between environmental factors and type 2 diabetes. Diabetes. (2009) 58:2718–25. doi: 10.2337/db09-1003
92. Ding GL, Wang FF, Shu J, Tian S, Jiang Y, Zhang D, et al. Transgenerational glucose intolerance with Igf2/H19 epigenetic alterations in mouse islet induced by intrauterine Hyperglycemia. Diabetes. (2012) 61:1133–42. doi: 10.2337/db11-1314
Keywords: non-genetic factors, gene, environmental factors, type 2 diabetes, variants
Citation: Mambiya M, Shang M, Wang Y, Li Q, Liu S, Yang L, Zhang Q, Zhang K, Liu M, Nie F, Zeng F and Liu W (2019) The Play of Genes and Non-genetic Factors on Type 2 Diabetes. Front. Public Health 7:349. doi: 10.3389/fpubh.2019.00349
Received: 11 January 2019; Accepted: 04 November 2019;
Published: 19 November 2019.
Edited by:
Ike Solomon Okosun, Georgia State University, United StatesReviewed by:
Zhong Jian, University of California, Davis, United StatesEugenia M. Bastos, Independent Researcher, Somerville, MA, United States
Copyright © 2019 Mambiya, Shang, Wang, Li, Liu, Yang, Zhang, Zhang, Liu, Nie, Zeng and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Wanyang Liu, d3lsaXUmI3gwMDA0MDtjbXUuZWR1LmNu
†These authors have contributed equally to this work