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Copy number variation: markers and predictors for type 2 diabetes

How to cite this article: Ramírez-Valverde AG, Antúnez-Ortiz DL, Méndez-Beleche A, Flores-Alfaro E, Ascencio-Montiel IJ, Cruz M. Copy number variation: markers and predictors for type 2 diabetes. Rev Med Inst Mex Seguro Soc. 2015 May-Jun;53(3):348-55.



Received: June 30th 2014

Accepted: July 15th 2014

Copy number variation: markers and predictors for type 2 diabetes

Alan Gilberto Ramírez-Valverde,a Diana Lizzete Antúnez-Ortiz,a Alberto Méndez-Beleche,a Eugenia Flores-Alfaro,b Iván de Jesús Ascencio-Montiel,c Miguel Cruza

aUnidad de Investigación Médica en Bioquímica, Hospital de Especialidades “Bernardo Sepúlveda”, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Distrito Federal

bUnidad Académica de Ciencias Químico Biológicas, Universidad Autónoma de Guerrero, Chilpancingo, Guerrero

cCoordinación de Vigilancia Epidemiológica, Unidad de Atención Primaria a la Salud, Dirección de Prestaciones Médicas, Instituto Mexicano del Seguro Social, Distrito Federal


Communication with: Miguel Cruz

Telephone: (55) 5761 2358


Type 2 diabetes (T2D) is a disease characterized by a deficiency in production or action of insulin. It is the result mainly of the interaction of the environment, lifestyle, as well as genetic factors. It is considered as one of the major health issues in the world because it affects severely the psychological well-being and overall life quality. Recently it has been shown that DNA copy number variations (CNVs) are associated with several diseases, including obesity and T2D. The CNVs are present from 9 to 18 % of the genome and can modify the expression levels of mRNA and proteins encoded by genes located near their localization. Less is known about their contribution to the pathogenesis of metabolic diseases, which is necessary to characterize so that these variations can be potentially used as biomarkers of genetic risk CNVs of T2D.

Keywords: Type 2 diabetes; DNA copy number variation; Single nucleotide polymorphism

Type 2 diabetes (T2D) is a metabolic disorder characterized by chronic hyperglycemia with disturbances in the metabolism of carbohydrates, lipids, and proteins. It is caused by a defect in the secretion and/or action of insulin.1 This epidemic is recognized by the World Health Organization (WHO) as a global threat. It is estimated that there are over 346 million people with T2D in the world and that 3.4 million deaths occur from complications. It is expected to more than double by the year 2030,2 a situation that also represents a public health problem in Mexico.3 The prevalence of the disease was estimated at 14.42% according to ENSANUT 2006, which represents 7.3 million Mexicans over 20 years of age.4 ENSANUT 2012 on the prevalence of T2D showed 9.2% by previous medical diagnosis, higher than that reported in the previous survey.5

T2D is a multifactorial disease with a high influence of genetics of the individual. Factors associated in the Mexican population are age, low education, co-existing renal disease or hypercholesterolemia, and abdominal obesity.6,7 In terms of genetic variation it has been observed that the presence of single nucleotide polymorphisms (SNP) is associated with obesity and T2D.8 To date 70 loci associated with T2D have been identified; thus, research has shown an increased risk for developing diabetes in patients with SNP in the FTO and MC4R genes with an inadequate diet,9 and decreased risk of T2D in patients with SNP in TCF7L2 subject to lifestyle interventions.10 Despite having over 70 genes involved, the cases attributable to these SNPs do not exceed 10% of the total cases of T2D, so new possibilities have been explored, such as copy number variations (CNV).

Genetic diversity in the Mexican population

The Mexican population is characterized by a high degree of genetic diversity. The population consists of a mix of native Amerindian genes ranging between 49 and 65%, of European genes between 30 and 45.8%, and East African genes between 1.8 and 6%, depending on geographic region of the country studied.11-14 At present genetic variants associated with European population and Amerindians have been shown, among others. Measuring ancestry in genetic studies in ethnically mixed populations is necessary, given that stratification is a confounding factor for genetic associations.15 Ethnic differences among the Mexican population and the populations of European origin, in whom most of the genome-wide association studies (GWAS) have been done, have shown differences in the genetic signals associated with T2D.16-18 The first GWAS for T2D done with Mexicans showed replication of only four gene regions of all the 46 regions reported in the literature in 2011 (HNF1A, KCNQ1, CDKN2A, CDKN2B).19 To date, 18 gene loci have been described associated with T2D in the Mexican population, which have mostly been obtained from comparative and case-control studies (Table I).20-36 Recently, a meta-analysis of 26,488 cases of T2D and 83,964 controls of European, East Asian, South Asian, Mexican and Mexican-American origin showed seven loci associated with diabetes, regardless of ancestry (TMEM154, SSR1-RREB1, FAF1, POU5F1-TCF19, LPP, ARL15, MPHOSPH9).16  

Table I Loci associated with type 2 diabetes (DT2) in Mexican population
Author, year Gene/Locus Gene name Location Association
Ortega-Pierres, 200720 ACE Angiotensin I converting enzyme 17q23.3 Diabetic nephropathy
Santos, 200221 APOE Apolipoprotein E 19q13.2 Macular edema
Del Bosque-Plata, 200422 CAPN10 Calpain 10 2q37.3 Type 2 diabetes
Gamboa-Melendez, 201223 CDKN2AIPNL N-terminal CDKN2A interaction protein 5q31.1 Type 2 diabetes
CDKN2A Kinase 2A-dependent cyclin Inhibitor 9 p 21 Type 2 diabetes
Quiroz-Mercado, 200224 HLADR7 HLA-DR7 6p21.3 Diabetic retinopathy
Pérez-Luque, 200325 HLADB1 HLADB1 6p21.3 Diabetes type 2 and terminal renal disease
Weissglas-Volkov, 200626 HNF1A HNF1 homebox A 12q24.2 Diabetes type 2 and lipid levels
Martínez-Gómez, 201127 IRS1 Substrate 1 in insulin receptor 2q36 Type 2 diabetes
Long, 201228 IGF2BP2 mRNA binding protein of insulin-like growth factor 3q27.2 Type 2 diabetes
Valladares-Salgado, 201029 LTBP1 Beta 1 latent transforming growth factor binding protein 2p22-p21 Diabetic nephropathy
Gutierrez-Vidal, 201130 LOC387761 LOC387761 11 p 12 Type 2 diabetes
Cameron, 200731 MGEA5 meningioma expression antigen 5 10q24.1-q24.3 Type 2 diabetes
Campbell, 201232 KCNQ1 Member 1 of KQT subfamily of voltage-dependent K channels 11p15.5 Type 2 diabetes
Williams, 201433 SLC16A11 Member 11 of solute carrier family 16 17p13.1 Type 2 diabetes
Huertas-Vazquez, 200834 TCF7L2 Transcription factor 7 similar to 2 10q25.3 Type 2 diabetes and triglyceride levels
Pérez-Luque, 201235 TNF Tumor necrosis factor 6p21.3 Type 2 diabetes
Duggirala, 199936 10q --- 10q Type 2 diabetes

Copy number variants in the genome

The human genome varies as a result of changes in sequence and structure. Variations in the sequence include the SNP and small insertions and eliminations (deletions) of a few nucleotides. Structural variation includes the CNV and chromosomal aneuploidy.37 Through complete genome analysis and using arrays based on comparative genomic hybridization and other types of genome-scanning technologies, CNV have been identified and classified according to their size. Typically DNA fragments are larger than 1 kb, and their difference in copy number is evident when compared with two or more genomes,38  including genomic insertions, deletions, translocations and inversions.39 It is believed that at least 12% the human genome contains CNV.40 These are common among healthy individuals; in fact, two people will differ in copy number by around 0.78% of their genomes.41 Initially, the CNV were identified during locus-specific studies42 or during the analysis of families of genes.43 Identifying CNV throughout the genome can be done by sequencing or by microarray. The use of microarrays has been the most widely used instrument that has advanced knowledge of CNV.44 It has now been determined that CNV can affect human phenotypic variation and contribute to the propensity to diseases such as autism,45 psoriasis,46 schizophrenia,47 obesity,48 and Crohn’s disease.49

Functional impact of CNV

CNV present in genes can influence expression levels of both mRNA and protein. It is estimated that between 9 and 18% of heritable variation may be associated with copy number.50 In addition CNV may directly or indirectly affect expression of neighboring genes, as the removal of regulatory regions (such as enhancers) decreases expression of the target gene and the amount of protein produced. Moreover, the loss of exon regions produces protein isoforms that are often not functional.51 Another alternative explanation for the observed change in relative expression levels of genes mapped near CNV about changes in copy number is based on recent evidence in the transcript of the entire genome.52 Recent studies show that multiple transcriptionally active regions associate to form a large variety of transcripts in a given locus with more than half, which are alternative non-coding transcriptions of protein-encoding genes. Similarly, genes use the promoter of neighboring genes in cells and specific stages of development.53

The onset of transcription-induced chimeras has been described, whereby exons are transcribed in tandem into a single mRNA molecule, which appears to be widespread, affecting more than half of the loci studied (Figure 1).54

Figure 1 Influence of CNV in the genome. The presence of CNV affects gene expression at mRNA and protein level: a) The presence of insertions or deletions at the level of transcription regulatory regions (enhancer and repressor) impedes their interaction with the gene promoter, leading to decreased expression. b) Duplication of exons and inversion of codifying regions leads to the production of chimeric proteins (modified from Hurles et al., 2008 56).

These genes may have several alternative regulatory regions, independent of promoters, and often their boundaries overlap with other genes, plus it is possible that the relative expression level of this unit of transcription may change.55,56

Scientific background: CNV and T2D

There are few studies evaluating the association between CNV and T2D (Table II).57-67

Table II Scientific precedents from studies of CNV and type 2 diabetes
Author, year N (case/control) Population Microarray Findings
Shtir, 200957 407 (194|213) Caucasian Affymetrix 500K No association
Wang, 200958 256 (128|128) African/caucasian-american PCR No association with region 1q
Jeon, 201059 395 (137|258) Korean Affymetrix 50K LEPR gene deletion
Kudo, 201160 200 (100|100) Japanese deCODE-Illumina CNV 370K Bead Chip Region 4p16.3
BAE, 201161 771 (275|496) Korean Illumina HumanHap BeadChip 300 Regions 15q21.1, 22q11.22 and 22q11.22
Craddock, 201062 5000 (2000|3000) Caucasian Aglient CGH, CGH NimbleGen, Illumina iSelect Region 12q14.1, CNVR5583.1(rs 1798090) gene TSPAN8
Chen, 201063 5000 (2000|3000) Caucasian Affymetrix 500K 1p34.3 (gene INPP5B), 1q41, gene MOSC2 and 19q13.2
Grassi, 201164 2137 (281|1856) Caucasian Affymetrix 5.0 Diabetic retinopathy and CNVR6685, 1 gene CCDC 101
Irvin, 201165 1040 African-American
(without diabetes)
Affymetrix 6.0 Association TCRVB gene and insulin resistance
Plengvidhya, 201266 555 (305|250) Thai Multiple PCR No association CNVs-DT2 in CAPN10 gene
Blackburn, 201367 1677 Mexican-American Illumina Infinium
765 CNVs previously not reported
CNV = copy number variation  

In 2010, Jeon et al. found an association between T2D and the number of copies < 2 in the LEPR gene (odds ratio [OR] 1.92) in 137 cases and 258 controls of Korean origin.59 In studies conducted in Asian populations and published in 2011, Kudo et al. reported the association between removal of region 4p16.3 and early onset T2D in 100 cases and 100 controls of Japanese origin;60 whereas Bae et al, in a study of 275 cases and 496 controls of Korean origin, reported three regions associated (15q21.1, 22q11.22 and 22q11.22) with T2D.61 In a study published in Nature in 2010, an association was found between the variable number region CNVR5583.1 (rs1798090), located in the gene tetraspanin 8 (TSPAN8) 12q14.1 and T2D, demonstrated in 2000 cases and 3000 controls.62 Similarly, using patient samples genotyped with Affymetrix Mapping 500K microarray, Chen et al. identified three regions associated with T2D (1p34.3, rs16824514, 1q41, rs337147, and 19q13.2, rs2016070) using a new strategy for CNV analysis associations in GWAS.63 In a study published in 2011 by Grassi et al. association was found between severe diabetic retinopathy and the CNVR6685.1 region of 28.5 Mb, located in the intron of the gene CCDC101 (p = 3.4x10-6) on chromosome 16p11.2. The study included 281 patients with diabetic retinopathy and 1856 controls.64 In 2011 Irvin et al. published a study done with 1040 African Americans without diabetes to find the association between insulin levels and insulin resistance (as measured by HOMA-IR) with CNV. For insulin levels two regions were associated (rs10277702 and rs361367 of gene TCRVB; rs12552047 on chromosome 9) while for insulin resistance another four (rs10277702 and rs361367 of gene TCRVB; rs13003829 of gene ARHGEF4; and rs12509348 of gene DCK). Thus, the most significant associations were given in gene TCRVB.65 In 2012, Plengvidhya et al. conducted a case-control study in 305 patients with T2D and 250 controls at Siriraj Hospital, Bangkok, Thailand, to search for CNV in the region of gene CAPN10. No differences were found in the presence of duplications or deletions between cases and controls (3.9 vs. 2.9, 1.3 vs. 0.3, p = 0.692); however, the insertion/deletion (in/del) 19 was found associated with T2D in the recessive model (OR: 0.66; 95% CI: 0.47-0.94, p = 0.022).66 In a recent study in 1677 Mexican-American subjects in San Antonio, Texas, the heritability of 2937 CNV detected by the algorithms PennCNV and QuantiSNP was studied; regions with low frequencies (0.2%) were found, as well as 765 previously unreported.67

Conclusions and perspectives

Diabetes is a multifactorial metabolic disease with varying degrees of hereditary predisposition and mainly caused by exposure to environmental factors. The disease is characterized by persistent hyperglycemia due to deficiency in the production or action of insulin, which affects the metabolism of carbohydrates, proteins and fats. Epidemiological data indicate that the risk of developing this disease is higher in populations of Amerindian origin than in populations of European origin. In addition, there is evidence that there are genetic risk factors involved in these differences in prevalence. Mexico is among the countries with the highest occurrence of T2D globally and this is related to the genetic differences of the Mexican population, combined with environmental exposure. Several studies have focused on finding the genomic variations that contribute to the propensity to disease. Thus SNP and CNV have been characterized as contributing to genetic diversity among individuals. CNVs are variants in the genome of size greater than 1 kb; they are found in approximately 9 to 18% of the genome and affect nearby genes and alter their expression at the mRNA and protein level. This variability is the basis for different phenotypic characteristics associated with CNV. Despite its importance, CNV have been little studied, so it is important to continue analyzing them to determine their size and location and thus to know their contribution to the pathophysiology of the disease. The CNV affect important regions of the genome, which are involved in various signaling pathways and are metabolic, so understanding their mechanism of action is a prerequisite for consideration of possible prognostic, preventive, and treatment strategies for T2D, but not without reiterating the role of lifestyle modifications as the main effort to control this disease

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Conflict of interest statement: The authors have completed and submitted the form translated into Spanish for the declaration of potential conflicts of interest of the International Committee of Medical Journal Editors, and none were reported in relation to this article.

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