RBCC Red Blood Cell Collection

SLC2A4 (GLUT4) [Confidence: high (present in two of the MS resources)]
Solute carrier family 2, facilitated glucose transporter member 4 (Glucose transporter type 4, insulin-responsive; GLUT-4)

hRBCD IPI00027281
IPI00027281 Solute carrier family 2, facilitated glucose transporter, member 4 ERPLSLLQLLGSR unique Solute carrier family 2, facilitated glucose transporter, member 4 ERPLSLLQLLGSR unique membrane n/a n/a 1 n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a integral membrane protein ERPLSLLQLLGSR (identified at least 3 times) found at its expected molecular weight found at molecular weight

UniProt P14672
ID GTR4_HUMAN Reviewed; 509 AA.
AC P14672; Q14CX2;
DT 01-APR-1990, integrated into UniProtKB/Swiss-Prot.
read moreDT 01-APR-1990, sequence version 1.
DT 22-JAN-2014, entry version 165.
DE RecName: Full=Solute carrier family 2, facilitated glucose transporter member 4;
DE AltName: Full=Glucose transporter type 4, insulin-responsive;
DE Short=GLUT-4;
GN Name=SLC2A4; Synonyms=GLUT4;
OS Homo sapiens (Human).
OC Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi;
OC Mammalia; Eutheria; Euarchontoglires; Primates; Haplorrhini;
OC Catarrhini; Hominidae; Homo.
OX NCBI_TaxID=9606;
RN [1]
RP NUCLEOTIDE SEQUENCE [MRNA].
RX PubMed=2656669;
RA Fukumoto H., Kayano T., Buse J.B., Edwards Y., Pilch P.F., Bell G.I.,
RA Seino S.;
RT "Cloning and characterization of the major insulin-responsive glucose
RT transporter expressed in human skeletal muscle and other insulin-
RT responsive tissues.";
RL J. Biol. Chem. 264:7776-7779(1989).
RN [2]
RP NUCLEOTIDE SEQUENCE [GENOMIC DNA], AND VARIANT THR-385.
RX PubMed=1397719; DOI=10.2337/diab.41.11.1436;
RA Buse J.B., Yasuda K., Lay T.P., Seo T.S., Olson A.L., Pessin J.E.,
RA Karam J.H., Seino S., Bell G.I.;
RT "Human GLUT4/muscle-fat glucose-transporter gene. Characterization and
RT genetic variation.";
RL Diabetes 41:1436-1445(1992).
RN [3]
RP NUCLEOTIDE SEQUENCE [LARGE SCALE MRNA].
RC TISSUE=Colon;
RX PubMed=15489334; DOI=10.1101/gr.2596504;
RG The MGC Project Team;
RT "The status, quality, and expansion of the NIH full-length cDNA
RT project: the Mammalian Gene Collection (MGC).";
RL Genome Res. 14:2121-2127(2004).
RN [4]
RP NUCLEOTIDE SEQUENCE [GENOMIC DNA] OF 1-11.
RX PubMed=7916714; DOI=10.1016/0378-1119(93)90438-9;
RA Chiaramonte R., Martini R., Taramelli R., Comi P.;
RT "Identification of the 5' end of the gene encoding a human insulin-
RT responsive glucose transporter.";
RL Gene 130:307-308(1993).
RN [5]
RP SUBCELLULAR LOCATION, AND MUTAGENESIS OF 489-LEU-LEU-490.
RX PubMed=8300557;
RA Verhey K.J., Birnbaum M.J.;
RT "A Leu-Leu sequence is essential for COOH-terminal targeting signal of
RT GLUT4 glucose transporter in fibroblasts.";
RL J. Biol. Chem. 269:2353-2356(1994).
RN [6]
RP INTERACTION WITH DAXX, AND SUMOYLATION.
RX PubMed=11842083; DOI=10.1074/jbc.M110294200;
RA Lalioti V.S., Vergarajauregui S., Pulido D., Sandoval I.V.;
RT "The insulin-sensitive glucose transporter, GLUT4, interacts
RT physically with Daxx. Two proteins with capacity to bind Ubc9 and
RT conjugated to SUMO1.";
RL J. Biol. Chem. 277:19783-19791(2002).
RN [7]
RP INTERACTION WITH SRFBP1.
RX PubMed=16647043; DOI=10.1016/j.bbrc.2006.04.017;
RA Lisinski I., Matsumoto H., Yver D.R., Schuermann A., Cushman S.W.,
RA Al-Hasani H.;
RT "Identification and characterization of p49/STRAP as a novel GLUT4-
RT binding protein.";
RL Biochem. Biophys. Res. Commun. 344:1179-1185(2006).
RN [8]
RP PHOSPHORYLATION AT SER-274 BY SGK1.
RX PubMed=17382906; DOI=10.1016/j.bbrc.2007.03.029;
RA Jeyaraj S., Boehmer C., Lang F., Palmada M.;
RT "Role of SGK1 kinase in regulating glucose transport via glucose
RT transporter GLUT4.";
RL Biochem. Biophys. Res. Commun. 356:629-635(2007).
RN [9]
RP IDENTIFICATION BY MASS SPECTROMETRY [LARGE SCALE ANALYSIS].
RC TISSUE=Cervix carcinoma;
RX PubMed=18669648; DOI=10.1073/pnas.0805139105;
RA Dephoure N., Zhou C., Villen J., Beausoleil S.A., Bakalarski C.E.,
RA Elledge S.J., Gygi S.P.;
RT "A quantitative atlas of mitotic phosphorylation.";
RL Proc. Natl. Acad. Sci. U.S.A. 105:10762-10767(2008).
RN [10]
RP GLYCOSYLATION [LARGE SCALE ANALYSIS] AT ASN-57, AND MASS SPECTROMETRY.
RC TISSUE=Leukemic T-cell;
RX PubMed=19349973; DOI=10.1038/nbt.1532;
RA Wollscheid B., Bausch-Fluck D., Henderson C., O'Brien R., Bibel M.,
RA Schiess R., Aebersold R., Watts J.D.;
RT "Mass-spectrometric identification and relative quantification of N-
RT linked cell surface glycoproteins.";
RL Nat. Biotechnol. 27:378-386(2009).
RN [11]
RP VARIANT NIDDM ILE-383.
RX PubMed=1918382; DOI=10.1172/JCI115437;
RA Kusari J., Verma U.S., Buse J.B., Henry R.R., Olefsky J.M.;
RT "Analysis of the gene sequences of the insulin receptor and the
RT insulin-sensitive glucose transporter (GLUT-4) in patients with
RT common-type non-insulin-dependent diabetes mellitus.";
RL J. Clin. Invest. 88:1323-1330(1991).
RN [12]
RP VARIANT NIDDM ILE-383.
RX PubMed=1756912; DOI=10.2337/diab.40.12.1712;
RA Choi W.H., O'Rahilly S., Buse J.B., Rees A., Morgan R., Flier J.S.,
RA Moller D.E.;
RT "Molecular scanning of insulin-responsive glucose transporter (GLUT4)
RT gene in NIDDM subjects.";
RL Diabetes 40:1712-1718(1991).
RN [13]
RP VARIANT NIDDM ILE-383.
RX PubMed=1521731; DOI=10.1007/BF02342449;
RA O'Rahilly S., Krook A., Morgan R., Rees A., Flier J.S., Moller D.E.;
RT "Insulin receptor and insulin-responsive glucose transporter (GLUT 4)
RT mutations and polymorphisms in a Welsh type 2 (non-insulin-dependent)
RT diabetic population.";
RL Diabetologia 35:486-489(1992).
CC -!- FUNCTION: Insulin-regulated facilitative glucose transporter.
CC -!- SUBUNIT: Interacts with NDUFA9 (By similarity). Binds to DAXX.
CC Interacts via its N-terminus with SRFBP1.
CC -!- SUBCELLULAR LOCATION: Cell membrane; Multi-pass membrane protein
CC (By similarity). Endomembrane system; Multi-pass membrane protein.
CC Cytoplasm, perinuclear region. Note=Localizes primarily to the
CC perinuclear region, undergoing continued recycling to the plasma
CC membrane where it is rapidly reinternalized. The dileucine
CC internalization motif is critical for intracellular sequestration.
CC -!- TISSUE SPECIFICITY: Skeletal and cardiac muscles; brown and white
CC fat.
CC -!- PTM: Sumoylated.
CC -!- DISEASE: Diabetes mellitus, non-insulin-dependent (NIDDM)
CC [MIM:125853]: A multifactorial disorder of glucose homeostasis
CC caused by a lack of sensitivity to the body's own insulin.
CC Affected individuals usually have an obese body habitus and
CC manifestations of a metabolic syndrome characterized by diabetes,
CC insulin resistance, hypertension and hypertriglyceridemia. The
CC disease results in long-term complications that affect the eyes,
CC kidneys, nerves, and blood vessels. Note=The disease may be caused
CC by mutations affecting the gene represented in this entry.
CC -!- MISCELLANEOUS: Insulin-stimulated phosphorylation of TBC1D4 is
CC required for GLUT4 translocation (By similarity).
CC -!- SIMILARITY: Belongs to the major facilitator superfamily. Sugar
CC transporter (TC 2.A.1.1) family. Glucose transporter subfamily.
CC -!- WEB RESOURCE: Name=Wikipedia; Note=GLUT4 entry;
CC URL="http://en.wikipedia.org/wiki/Glut4";
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DR EMBL; M20747; AAA59189.1; -; mRNA.
DR EMBL; M91463; AAA52569.1; -; Genomic_DNA.
DR EMBL; BC069615; AAH69615.1; -; mRNA.
DR EMBL; BC069621; AAH69621.1; -; mRNA.
DR EMBL; BC113592; AAI13593.1; -; mRNA.
DR EMBL; BC126164; AAI26165.1; -; mRNA.
DR EMBL; X58489; CAA41399.1; -; Genomic_DNA.
DR PIR; A49158; A33801.
DR RefSeq; NP_001033.1; NM_001042.2.
DR UniGene; Hs.380691; -.
DR ProteinModelPortal; P14672; -.
DR SMR; P14672; 31-481.
DR IntAct; P14672; 1.
DR MINT; MINT-232088; -.
DR STRING; 9606.ENSP00000320935; -.
DR ChEMBL; CHEMBL5874; -.
DR GuidetoPHARMACOLOGY; 878; -.
DR TCDB; 2.A.1.1.80; the major facilitator superfamily (mfs).
DR PhosphoSite; P14672; -.
DR DMDM; 121761; -.
DR PaxDb; P14672; -.
DR PRIDE; P14672; -.
DR DNASU; 6517; -.
DR Ensembl; ENST00000317370; ENSP00000320935; ENSG00000181856.
DR GeneID; 6517; -.
DR KEGG; hsa:6517; -.
DR UCSC; uc002gfp.3; human.
DR CTD; 6517; -.
DR GeneCards; GC17P007186; -.
DR HGNC; HGNC:11009; SLC2A4.
DR HPA; CAB016544; -.
DR MIM; 125853; phenotype.
DR MIM; 138190; gene.
DR neXtProt; NX_P14672; -.
DR PharmGKB; PA35879; -.
DR eggNOG; COG0477; -.
DR HOGENOM; HOG000202871; -.
DR HOVERGEN; HBG014816; -.
DR InParanoid; P14672; -.
DR KO; K07191; -.
DR OMA; AMLVNNI; -.
DR PhylomeDB; P14672; -.
DR Reactome; REACT_111045; Developmental Biology.
DR Reactome; REACT_111217; Metabolism.
DR Reactome; REACT_11123; Membrane Trafficking.
DR Reactome; REACT_15518; Transmembrane transport of small molecules.
DR GeneWiki; GLUT4; -.
DR GenomeRNAi; 6517; -.
DR NextBio; 25341; -.
DR PRO; PR:P14672; -.
DR ArrayExpress; P14672; -.
DR Bgee; P14672; -.
DR CleanEx; HS_SLC2A4; -.
DR Genevestigator; P14672; -.
DR GO; GO:0030136; C:clathrin-coated vesicle; IDA:UniProtKB.
DR GO; GO:0005905; C:coated pit; IEA:Ensembl.
DR GO; GO:0030659; C:cytoplasmic vesicle membrane; IEA:Ensembl.
DR GO; GO:0012505; C:endomembrane system; ISS:UniProtKB.
DR GO; GO:0009897; C:external side of plasma membrane; IDA:MGI.
DR GO; GO:0070062; C:extracellular vesicular exosome; IEA:Ensembl.
DR GO; GO:0032593; C:insulin-responsive compartment; IDA:UniProtKB.
DR GO; GO:0005887; C:integral to plasma membrane; TAS:ProtInc.
DR GO; GO:0005771; C:multivesicular body; IEA:Ensembl.
DR GO; GO:0048471; C:perinuclear region of cytoplasm; IDA:UniProtKB.
DR GO; GO:0042383; C:sarcolemma; IEA:Ensembl.
DR GO; GO:0030140; C:trans-Golgi network transport vesicle; IEA:Ensembl.
DR GO; GO:0012506; C:vesicle membrane; IDA:MGI.
DR GO; GO:0055056; F:D-glucose transmembrane transporter activity; IEA:Ensembl.
DR GO; GO:0005355; F:glucose transmembrane transporter activity; TAS:ProtInc.
DR GO; GO:0010021; P:amylopectin biosynthetic process; IEA:Ensembl.
DR GO; GO:0050873; P:brown fat cell differentiation; IEA:Ensembl.
DR GO; GO:0005975; P:carbohydrate metabolic process; TAS:Reactome.
DR GO; GO:0032869; P:cellular response to insulin stimulus; IDA:UniProtKB.
DR GO; GO:0071470; P:cellular response to osmotic stress; IEA:Ensembl.
DR GO; GO:0042593; P:glucose homeostasis; IDA:BHF-UCL.
DR GO; GO:0046323; P:glucose import; NAS:BHF-UCL.
DR GO; GO:0045471; P:response to ethanol; IEA:Ensembl.
DR GO; GO:0044281; P:small molecule metabolic process; TAS:Reactome.
DR InterPro; IPR002441; Glc_transpt_4.
DR InterPro; IPR020846; MFS_dom.
DR InterPro; IPR016196; MFS_dom_general_subst_transpt.
DR InterPro; IPR005828; Sub_transporter.
DR InterPro; IPR003663; Sugar/inositol_transpt.
DR InterPro; IPR005829; Sugar_transporter_CS.
DR Pfam; PF00083; Sugar_tr; 1.
DR PRINTS; PR01193; GLUCTRSPORT4.
DR PRINTS; PR00171; SUGRTRNSPORT.
DR SUPFAM; SSF103473; SSF103473; 1.
DR TIGRFAMs; TIGR00879; SP; 1.
DR PROSITE; PS50850; MFS; 1.
DR PROSITE; PS00216; SUGAR_TRANSPORT_1; 1.
DR PROSITE; PS00217; SUGAR_TRANSPORT_2; 1.
PE 1: Evidence at protein level;
KW Cell membrane; Complete proteome; Cytoplasm; Diabetes mellitus;
KW Disease mutation; Glycoprotein; Membrane; Phosphoprotein;
KW Polymorphism; Reference proteome; Sugar transport; Transmembrane;
KW Transmembrane helix; Transport; Ubl conjugation.
FT CHAIN 1 509 Solute carrier family 2, facilitated
FT glucose transporter member 4.
FT /FTId=PRO_0000050363.
FT TOPO_DOM 1 24 Cytoplasmic (Potential).
FT TRANSMEM 25 45 Helical; Name=1; (Potential).
FT TOPO_DOM 46 81 Extracellular (Potential).
FT TRANSMEM 82 102 Helical; Name=2; (Potential).
FT TOPO_DOM 103 111 Cytoplasmic (Potential).
FT TRANSMEM 112 132 Helical; Name=3; (Potential).
FT TOPO_DOM 133 142 Extracellular (Potential).
FT TRANSMEM 143 163 Helical; Name=4; (Potential).
FT TOPO_DOM 164 171 Cytoplasmic (Potential).
FT TRANSMEM 172 192 Helical; Name=5; (Potential).
FT TOPO_DOM 193 201 Extracellular (Potential).
FT TRANSMEM 202 222 Helical; Name=6; (Potential).
FT TOPO_DOM 223 287 Cytoplasmic (Potential).
FT TRANSMEM 288 308 Helical; Name=7; (Potential).
FT TOPO_DOM 309 323 Extracellular (Potential).
FT TRANSMEM 324 344 Helical; Name=8; (Potential).
FT TOPO_DOM 345 353 Cytoplasmic (Potential).
FT TRANSMEM 354 374 Helical; Name=9; (Potential).
FT TOPO_DOM 375 384 Extracellular (Potential).
FT TRANSMEM 385 405 Helical; Name=10; (Potential).
FT TOPO_DOM 406 417 Cytoplasmic (Potential).
FT TRANSMEM 418 438 Helical; Name=11; (Potential).
FT TOPO_DOM 439 445 Extracellular (Potential).
FT TRANSMEM 446 466 Helical; Name=12; (Potential).
FT TOPO_DOM 467 509 Cytoplasmic (Potential).
FT REGION 7 13 SRFBP1-binding.
FT REGION 295 297 Defines substrate specificity (By
FT similarity).
FT MOTIF 489 490 Dileucine internalization motif.
FT MOD_RES 274 274 Phosphoserine; by SGK1.
FT CARBOHYD 57 57 N-linked (GlcNAc...).
FT VARIANT 55 55 S -> R (in dbSNP:rs35198331).
FT /FTId=VAR_052503.
FT VARIANT 78 78 T -> S (in dbSNP:rs5434).
FT /FTId=VAR_012060.
FT VARIANT 358 358 A -> V (in dbSNP:rs8192702).
FT /FTId=VAR_020336.
FT VARIANT 383 383 V -> I (in NIDDM; dbSNP:rs121434581).
FT /FTId=VAR_007170.
FT VARIANT 385 385 I -> T.
FT /FTId=VAR_007171.
FT MUTAGEN 489 490 LL->AA: Changes subcellular location
FT mainly to the plasma membrane.
FT CONFLICT 151 154 Missing (in Ref. 2; AAA52569).
SQ SEQUENCE 509 AA; 54787 MW; 8E20CD97562C1EBF CRC64;
MPSGFQQIGS EDGEPPQQRV TGTLVLAVFS AVLGSLQFGY NIGVINAPQK VIEQSYNETW
LGRQGPEGPS SIPPGTLTTL WALSVAIFSV GGMISSFLIG IISQWLGRKR AMLVNNVLAV
LGGSLMGLAN AAASYEMLIL GRFLIGAYSG LTSGLVPMYV GEIAPTHLRG ALGTLNQLAI
VIGILIAQVL GLESLLGTAS LWPLLLGLTV LPALLQLVLL PFCPESPRYL YIIQNLEGPA
RKSLKRLTGW ADVSGVLAEL KDEKRKLERE RPLSLLQLLG SRTHRQPLII AVVLQLSQQL
SGINAVFYYS TSIFETAGVG QPAYATIGAG VVNTVFTLVS VLLVERAGRR TLHLLGLAGM
CGCAILMTVA LLLLERVPAM SYVSIVAIFG FVAFFEIGPG PIPWFIVAEL FSQGPRPAAM
AVAGFSNWTS NFIIGMGFQY VAEAMGPYVF LLFAVLLLGF FIFTFLRVPE TRGRTFDQIS
AAFHRTPSLL EQEVKPSTEL EYLGPDEND
//

MIM 125853
*RECORD*
*FIELD* NO
125853
*FIELD* TI
#125853 DIABETES MELLITUS, NONINSULIN-DEPENDENT; NIDDM
;;DIABETES MELLITUS, TYPE II; T2D;;
read moreNONINSULIN-DEPENDENT DIABETES MELLITUS;;
MATURITY-ONSET DIABETES
INSULIN RESISTANCE, SUSCEPTIBILITY TO, INCLUDED
*FIELD* TX
A number sign (#) is used with this entry because of evidence that more
than one gene is involved in the causation of noninsulin-dependent
diabetes mellitus (NIDDM).

See 601283 for description of a form of NIDDM linked to 2q, which may be
caused by mutation in the gene encoding calpain-10 (CAPN10; 605286). See
601407 for description of a chromosome 12q locus, NIDDM2, found in a
Finnish population. See 603694 for description of a locus on chromosome
20, NIDDM3.

A mutation has been observed in hepatocyte nuclear factor-4-alpha
(HNF4A; 600281.0004) in a French family with NIDDM of late onset.
Mutations in the NEUROD1 gene (601724) on chromosome 2q32 were found to
cause type II diabetes mellitus in 2 families. Mutation in the GLUT4
glucose transporter was associated with NIDDM in 1 patient (138190.0001)
and in the GLUT2 glucose transporter in another (138160.0001). Mutation
in the MAPK8IP1 gene, which encodes the islet-brain-1 protein, was found
in a family with type II diabetes in individuals in 4 successive
generations (604641.0001). Polymorphism in the KCNJ11 gene (600937.0014)
confers susceptibility. In French white families, Vionnet et al. (2000)
found evidence for a susceptibility locus for type II diabetes on
3q27-qter. They confirmed the diabetes susceptibility locus on 1q21-q24
reported by Elbein et al. (1999) in whites and by Hanson et al. (1998)
in Pima Indians. A mutation in the GPD2 gene (138430.0001) on chromosome
2q24.1, encoding mitochondrial glycerophosphate dehydrogenase, was found
in a patient with type II diabetes mellitus and in his
glucose-intolerant half sister. Mutations in the PAX4 gene (167413) have
been identified in patients with type II diabetes. Triggs-Raine et al.
(2002) stated that in the Oji-Cree, a gly319-to-ser change in HNF1-alpha
(142410.0008) behaves as a susceptibility allele for type II diabetes.
Mutation in the HNF1B gene (189907.0007) was found in 2 Japanese
patients with typical late-onset type II diabetes. Mutations in the IRS1
gene (147545) have been found in patients with type II diabetes.
Reynisdottir et al. (2003) mapped a susceptibility locus for type II
diabetes to chromosome 5q34-q35.2 (NIDDM4; 608036). A missense mutation
in the AKT2 gene (164731.0001) caused autosomal dominant type II
diabetes in 1 family. A (single-nucleotide polymorphism) SNP in the
3-prime untranslated region of the resistin gene (605565.0001) was
associated with susceptibility to diabetes and to insulin
resistance-related hypertension in Chinese subjects. Susceptibility to
insulin resistance has been associated with polymorphism in the TCF1
(142410.0011), PPP1R3A (600917.0001), PTPN1 (176885.0001), ENPP1
(173335.0006), IRS1 (147545.0002), and EPHX2 (132811.0001) genes. The
K121Q polymorphism of ENPP1 (173335.0006) is associated with
susceptibility to type II diabetes; a haplotype defined by 3 SNPs of
this gene, including K121Q, is associated with obesity, glucose
intolerance, and type II diabetes. A SNP in the promoter region of the
hepatic lipase gene (151670.0004) predicts conversion from impaired
glucose tolerance to type II diabetes. Variants of transcription factor
7-like-2 (TCF7L2; 602228.0001), located on 10q, have also been found to
confer risk of type II diabetes. A common sequence variant, dbSNP
rs10811661, on chromosome 9p21 near the CDKN2A (600160) and CDKN2B
(600431) genes has been associated with risk of type II diabetes.
Variation in the PPARG gene (601487) has been associated with risk of
type 2 diabetes. A promoter polymorphism in the IL6 gene (147620) is
associated with susceptibility to NIDDM. Variation in the KCNJ15 gene
(602106) has been associated with T2DM in lean Asians. Variation in the
HMGA1 gene (600701.0001) is associated with an increased risk of type II
diabetes. Mutation in the MTNR1B gene (600804) is associated with
susceptibility to type 2 diabetes.

Noninsulin-dependent diabetes mellitus is distinct from MODY (606391) in
that it is polygenic, characterized by gene-gene and gene-environment
interactions with onset in adulthood, usually at age 40 to 60 but
occasionally in adolescence if a person is obese. The pedigrees are
rarely multigenerational. The penetrance is variable, possibly 10 to 40%
(Fajans et al., 2001). Persons with type II diabetes usually have an
obese body habitus and manifestations of the so-called metabolic
syndrome (see 605552), which is characterized by diabetes, insulin
resistance, hypertension, and hypertriglyceridemia.

INHERITANCE

In 3 families with MODY and 7 with 'common' type II diabetes mellitus,
O'Rahilly et al. (1992) excluded linkage to the INS locus (176730).
Exclusive of the mendelian forms of NIDDM represented by MODY, the high
incidence of diabetes in certain populations and among first-degree
relatives of type II diabetic patients, as well as the high concordance
in identical twins, provides strong evidence that genetic factors
underlie susceptibility to the common form of NIDDM which affects up to
6% of the United States population. Although defects in both insulin
secretion and insulin action may be necessary for disease expression in
groups with a high incidence of NIDDM, such as offspring of type II
diabetic parents and Pima Indians, insulin resistance and decreased
glucose disposal can be shown to precede and predict the onset of
diabetes (Martin et al., 1992; Bogardus et al., 1989). In both of these
groups, relatives and Pima Indians, there is evidence of familial
clustering of insulin sensitivity. Thus, insulin resistance appears to
be a central feature of NIDDM and may be an early and inherited marker
of the disorder.

Martinez-Marignac et al. (2007) analyzed and discussed the use of
admixture mapping of type 2 diabetes genetic risk factors in Mexico
City. Type 2 diabetes is at least twice as prevalent in Native American
populations as in populations of European ancestry. The authors
characterized the admixture proportions in a sample of 286 unrelated
type 2 diabetes patients and 275 controls from Mexico City. Admixture
proportions were estimated using 69 autosomal ancestry-informative
markers (AIMs). The average proportions of Native American, European,
and West African admixture were estimated as 65%, 30%, and 5%,
respectively. The contributions of Native American ancestors to maternal
and paternal lineages were estimated as 90% and 40%, respectively. In a
logistic model with higher educational status as dependent variable, the
odds ratio for higher educational status associated with an increase
from 0 to 1 in European admixture proportions was 9.4. This association
of socioeconomic status with individual admixture proportion showed that
genetic stratification in this population is paralleled, and possibly
maintained, by socioeconomic stratification. The effective number of
generations back to unadmixed ancestors was 6.7, from which
Martinez-Marignac et al. (2007) could estimate the number of evenly
distributed AIMs required to localize genes underlying disease risk
between populations of European and Native American ancestry, i.e.,
about 1,400. Sample sizes of about 2,000 cases would be required to
detect any locus that contributed an ancestry risk ratio of at least
1.5.

Kong et al. (2009) found 3 SNPs at 11p15 that had association with type
2 diabetes and parental origin specific effects; These were dbSNP
rs2237892, dbSNP rs231362, and dbSNP rs2334499. For dbSNP rs2334499 the
allele that confers risk when paternally inherited (T) is protective
when maternally inherited.

BIOCHEMICAL FEATURES

A subgroup of patients diagnosed with type II diabetes have circulating
antibodies to islet cell cytoplasmic antigens, most frequently to
glutamic acid decarboxylase (see GAD2; 138275). Among 1,122 type II
diabetic patients, Tuomi et al. (1999) found GAD antibody in 9.3%, a
significantly higher prevalence than that found in patients with
impaired glucose tolerance or in controls. The GADab+ patients had lower
fasting C-peptide concentration, lower insulin response to oral glucose,
and higher frequency of the high-risk HLA-DQB1*0201/0302 (see 604305)
genotype (though significantly lower than in patients with type I
diabetes) when compared with GADab- patients. Tuomi et al. (1999)
suggested the designation latent autoimmune diabetes in adults (LADA) to
define the subgroup of type II diabetes patients with GADab positivity
(greater than 5 relative units) and age at onset greater than 35 years.

Both defective insulin secretion and insulin resistance have been
reported in relatives of NIDDM subjects. Elbein et al. (1999) tested 120
members of 26 families containing an NIDDM sib pair with a
tolbutamide-modified, frequently sampled intravenous glucose tolerance
test to determine the insulin sensitivity index (SI) and acute insulin
response to glucose (AIRglucose). Both SI x AIRglucose and SI showed
strong negative genetic correlations with diabetes (-85 +/- 3% and -87
+/- 2%, respectively, for all family members), whereas AIRglucose did
not correlate with diabetes. The authors concluded that insulin
secretion, as measured by SI x AIRglucose, is decreased in nondiabetic
members of familial NIDDM kindreds; that SI x AIRglucose in these
high-risk families is highly heritable; and that the same polygenes may
determine diabetes status and a low SI x AIRglucose. They also suggested
that insulin secretion, when expressed as an index normalized for
insulin sensitivity, is more familial than either insulin sensitivity or
first-phase insulin secretion alone, and may be a very useful trait for
identifying genetic predisposition to NIDDM.

GENOTYPE/PHENOTYPE CORRELATIONS

Li et al. (2001) assessed the prevalence of families with both type I
and type II diabetes in Finland and studied, in patients with type II
diabetes, the association between a family history of type 1 diabetes,
GAD antibodies (GADab), and type I diabetes-associated HLA-DQB1
genotypes. Further, in mixed type I/type II diabetes families, they
investigated whether sharing an HLA haplotype with a family member with
type I diabetes influenced the manifestation of type II diabetes. Among
695 families with more than 1 patient with type II diabetes, 100 (14%)
also had members with type I diabetes. Type II diabetic patients from
the mixed families more often had GADab (18% vs 8%) and DQB1*0302/X
genotype (25% vs 12%) than patients from families with only type II
diabetes; however, they had a lower frequency of DQB1*02/0302 genotype
compared with adult-onset type I patients (4% vs 27%). In the mixed
families, the insulin response to oral glucose load was impaired in
patients who had HLA class II risk haplotypes, either
DR3(17)-DQA1*0501-DQB1*02 or DR4*0401/4-DQA1*0301-DQB1*0302, compared
with patients without such haplotypes. This finding was independent of
the presence of GADab. The authors concluded that type I and type II
diabetes cluster in the same families. A shared genetic background with
a patient with type I diabetes predisposes type II diabetic patients
both to autoantibody positivity and, irrespective of antibody
positivity, to impaired insulin secretion. Their findings also supported
a possible genetic interaction between type I and type II diabetes
mediated by the HLA locus.

CLINICAL MANAGEMENT

Fonseca et al. (1998) studied the effects of troglitazone monotherapy on
glycemic control in patients with NIDDM in 24 hospital and outpatient
clinics in the U.S. and Canada. Troglitazone 100, 200, 400, or 600 mg,
or placebo, was administered once daily with breakfast to 402 patients
with NIDDM and fasting serum glucose (FSG) greater than 140 mg/dL,
glycosylated hemoglobin (HbA1c) greater than 6.5%, and fasting C-peptide
greater than 1.5 ng/mL. Patients treated with 400 and 600 mg
troglitazone had significant decreases from baseline in mean FSG (-51
and -60 mg/dL, respectively) and HbA1c (-0.7% and -1.1%, respectively)
at month 6 compared to placebo-treated patients. In the diet-only
subset, 600 mg troglitazone therapy resulted in a significant (P less
than 0.05) reduction in HbA1c (-1.35%) and a significant reduction in
FSG (-42 mg/dL) compared with placebo. Patients previously treated with
sulfonylurea therapy had significant (P less than 0.05) decreases in
mean FSG with 200 to 600 mg troglitazone therapy compared with placebo
(-48, -61, and -66 mg/dL, respectively). The authors concluded that
troglitazone monotherapy significantly improves HbA1c and fasting serum
glucose, while lowering insulin and C-peptide in patients with NIDDM.

Chung et al. (2000) studied the effect of HMG-CoA reductase inhibitors
on bone mineral density (BMD) of type II diabetes mellitus by a
retrospective review of medical records. In the control group, BMD of
the spine significantly decreased after 14 months. In the treatment
group, BMD of the femoral neck significantly increased after 15 months.
In male subjects treated with HMG-CoA reductase inhibitors, there was a
significant increase in BMD of the femoral neck and femoral trochanter,
but in female subjects, only BMD of the femoral neck increased. The
authors concluded that HMG-CoA reductase inhibitors may increase BMD of
the femur in male patients with type II diabetes mellitus.

Aljada et al. (2001) investigated the effect of troglitazone on the
proinflammatory transcription factor NF-kappa-B (see 164011) and its
inhibitory protein I-kappa-B (see 164008) in mononuclear cells (MNC) in
obese patients with type II diabetes. Seven obese patients with type II
diabetes were treated with troglitazone (400 mg/day) for 4 weeks, and
blood samples were obtained at weekly intervals. NF-kappa-B binding
activity in MNC nuclear extracts was significantly inhibited after
troglitazone treatment at week 1 and continued to be inhibited up to
week 4. On the other hand, I-kappa-B protein levels increased
significantly after troglitazone treatment at week 1, and this increase
persisted throughout the study. The authors concluded that troglitazone
has profound antiinflammatory effects in addition to antioxidant effects
in obese type II diabetics, and that these effects may be relevant to
the beneficial antiatherosclerotic effects of troglitazone at the
vascular level.

In a multicenter, double-blind trial, Garber et al. (2003) enrolled
patients with type II diabetes who had inadequate glycemic control
(glycosylated hemoglobin A1C greater than 7% and less than 12%) with
diet and exercise alone to compare the benefits of initial therapy with
glyburide/metformin tablets versus metformin or glyburide monotherapy.
They randomized 486 patients to receive glyburide/metformin tablets,
metformin, or glyburide. Changes in A1C, fasting plasma glucose,
fructosamine, serum lipids, body weight, and 2-hour postprandial glucose
after a standardized meal were assessed after 16 weeks of treatment.
Glyburide/metformin tablets caused a superior mean reduction in A1C from
baseline versus metformin and glyburide monotherapy. Glyburide/metformin
also significantly reduced fasting plasma glucose and 2-hour
postprandial glucose values compared with either monotherapy. The final
mean doses of glyburide/metformin were lower than those of metformin and
glyburide. The authors concluded that first-line treatment with
glyburide/metformin tablets provided superior glycemic control over
component monotherapy, allowing more patients to achieve American
Diabetes Association treatment goals with lower component doses in
drug-naive patients with type II diabetes.

The GoDARTs and UKPDS Diabetes Pharmacogenetics Study Group and Wellcome
Trust Case Control Consortium 2 (2011) performed a genomewide
association study for glycemic response to metformin in 1,024 Scottish
individuals with type 2 diabetes with replication in 2 cohorts including
1,783 Scottish individuals and 1,113 individuals in the UK Prospective
Diabetes Study. In a combined metaanalysis, the consortia identified a
SNP, dbSNP rs11212617, associated with treatment success (n = 3,920, P =
2.9 x 10(-9), OR = 1.35, 95% CI 1.22-1.49) at a locus containing the ATM
gene (607585). In a rat hepatoma cell line, inhibition of ATM with
KU-55933, a selective ATM inhibitor, attenuated the phosphorylation and
activation of AMP-activated protein kinase (see 602739) in response to
metformin. The consortia concluded that ATM, a gene known to be involved
in DNA repair and cell cycle control, plays a role in the effect of
metformin upstream of AMP-activated protein kinase, and variation in
this gene alters glycemic response to metformin.

Yee et al. (2012) commented on the GoDARTS and UKPDS paper and examined
the inhibitory effect of KU-55933 on metformin in H4IIE cells and in
HEK293 cells stably expressing OCT1. They demonstrated in both cases
that KU-55933 inhibits metformin uptake via inhibition of OCT1 and that
the attenuation of metformin-induced AMPK phosphorylation is a result of
its inhibition of metformin uptake into the cells. This effect is
independent of ATM. Yee et al. (2012) demonstrated that ATM does not
have a detectable effect on OCT1 activity. Woods et al. (2012) also
found that in hepatocytes lacking AMPK activity (see Woods et al.,
2011), metformin still has the ability to reduce hepatic glucose output.
Woods et al. (2012) argued that the SNP dbSNP rs11212617 maps to a locus
on chromosome 11q22 that encodes a number of genes and that no direct
evidence had been found that ATM acts upstream of AMPK; Woods et al.
(2012) concluded that other genes within this locus should be considered
as candidates responsible for the reduced therapeutic effect of
metformin action. Zhou et al. (2012) concurred with the comments of Yee
et al. (2012) and Woods et al. (2012) that all genes surrounding dbSNP
rs11212617 should be examined.

PATHOGENESIS

Piatti et al. (2000) compared resistance to insulin-mediated glucose
disposal and plasma concentrations of nitric oxide (NO) and cGMP in 35
healthy volunteers with, or 27 without, at least 1 sib and 1 parent with
type II diabetes. The mean insulin sensitivity index (ISI) was
significantly greater in those without a family history as compared with
nondiabetic volunteers with a family history of type II diabetes,
whether they had normal glucose tolerance or impaired glucose tolerance.
In addition, basal NO levels, evaluated by the measurement of its stable
end products (i.e., nitrite and nitrate levels, NO2-/NO3-) were
significantly higher, and levels of cGMP, its effector messenger, were
significantly lower in those with a family history, irrespective of
their degree of glucose tolerance, when compared with healthy volunteers
without a family history of type II diabetes. Furthermore, when the 62
volunteers were analyzed as 1 group, there was a negative correlation
between ISI and NO2-/NO3- levels and a positive correlation between ISI
and cGMP levels. The authors concluded that alterations of the NO/cGMP
pathway seem to be an early event in nondiabetic individuals with a
family history of type II diabetes, and that these changes are
correlated with the degree of insulin resistance. To investigate how
insulin resistance arises, Petersen et al. (2003) studied 16 healthy,
lean elderly aged 61 to 84 and 13 young participants aged 18 to 39
matched for lean body mass (BMI less than 25) and fat mass assessed by
DEXA (dual energy X-ray absorptiometry) scanning, and activity level.
Elderly study participants were markedly insulin-resistant as compared
with young controls, and this resistance was attributable to reduced
insulin-stimulated muscle glucose metabolism. These changes were
associated with increased fat accumulation in muscle and liver tissue,
assessed by NMR spectroscopy, and with an approximately 40% reduction in
mitochondrial oxidative and phosphorylation activity, as assessed by in
vivo NMR spectroscopy. Petersen et al. (2003) concluded that their data
support the hypothesis that an age-associated decline in mitochondrial
function contributes to insulin resistance in the elderly.

Petersen et al. (2004) performed glucose clamp studies in healthy,
young, lean, insulin-resistant offspring of patients with type II
diabetes and insulin-sensitive subjects matched for age, height, weight,
and physical activity. The insulin-stimulated rate of glucose uptake by
muscle was approximately 60% lower in insulin-resistant subjects than in
controls (p less than 0.001) and was associated with an increase of
approximately 80% in intramyocellular lipid content (p less than 0.005).
The authors attributed the latter increase to mitochondrial dysfunction,
noting a reduction of approximately 30% in mitochondrial phosphorylation
(p = 0.01 compared to controls). Petersen et al. (2004) concluded that
insulin resistance in the skeletal muscle of insulin-resistant offspring
of patients with type II diabetes is associated with dysregulation of
intramyocellular fatty acid metabolism, possibly because of an inherited
defect in mitochondrial oxidative phosphorylation.

Do et al. (2005) assessed the correlation between persistent diabetic
macular edema and hemoglobin A1c (HbA1C). Patients with type II diabetes
and persistent clinically significant macular edema had higher HbA1C at
the time of their disease than patients with resolved macular edema.
Patients with bilateral disease had more elevated HbA1C than those with
unilateral disease.

Foti et al. (2005) reported 4 patients with insulin resistance and type
II diabetes in whom cell-surface insulin receptors were decreased and
INSR (147670) gene transcription was impaired, although the INSR genes
were normal. In these individuals, expression of HMGA1 (600701) was
markedly reduced; restoration of HMGA1 protein expression in their cells
enhanced INSR gene transcription and restored cell-surface insulin
receptor protein expression and insulin-binding capacity. Foti et al.
(2005) concluded that defects in HMGA1 may cause decreased insulin
receptor expression and induce insulin resistance.

Increases in the concentration of circulating glucose activate the
hexosamine biosynthetic pathway and promote the O-glycosylation of
proteins by O-glycosyl transferase (OGT; 300255). Dentin et al. (2008)
showed that OGT triggered hepatic gluconeogenesis through the
O-glycosylation of the transducer of regulated cAMP response
element-binding protein (CREB) 2 (TORC2 or CRTC2; 608972). CRTC2 was
O-glycosylated at sites that normally sequester CRTC2 in the cytoplasm
through a phosphorylation-dependent mechanism. Decreasing amounts of
O-glycosylated CRTC2 by expression of the deglycosylating enzyme
O-GlcNAcase (604039) blocked effects of glucose on gluconeogenesis,
demonstrating the importance of the hexosamine biosynthetic pathway in
the development of glucose intolerance.

MAPPING

In an autosomal genome screen in 363 nondiabetic Pima Indians at 516
polymorphic microsatellite markers, Pratley et al. (1998) found a
suggestion of linkage at several chromosomal regions with particular
characteristics known to be predictive of NIDDM: 3q21-q24, linked to
fasting plasma insulin concentration and in vivo insulin action;
4p15-q12, linked to fasting plasma insulin concentration; 9q21, linked
to 2-hour insulin concentration during oral glucose tolerance testing;
and 22q12-q13, linked to fasting plasma glucose concentration. None of
the linkages exceeded a lod score of 3.6 (a 5% probability of occurring
in a genomewide screen).

In 719 Finnish sib pairs with type II diabetes, Ghosh et al. (2000)
performed a genome scan at an average resolution of 8 cM. The strongest
results were for chromosome 20, where they observed a weighted maximum
lod score of 2.15 at map position 69.5 cM from pter, and secondary
weighted lod score peaks of 2.04 at 56.5 cM and 1.99 at 17.5 cM. The
next largest maximum lod score was for chromosome 11 (maximum lod score
= 1.75 at 84.0 cM), followed by chromosomes 2, 10, and 6. When they
conditioned on chromosome 2 at 8.5 cM, the maximum lod score for
chromosome 20 increased to 5.50 at 69.0 cM.

Watanabe et al. (2000) reported results from an autosomal genome scan
for type II diabetes-related quantitative traits in 580 Finnish families
ascertained for an affected sib pair and analyzed by the variance
components-based quantitative-trait locus linkage approach. In diabetic
individuals, the strongest results were observed on chromosomes 3 and
13. Integrating genome scan results of Ghosh et al. (2000), they
identified several regions that may harbor susceptibility genes for type
II diabetes in the Finnish population.

In a genomewide scan of 359 Japanese individuals with type II diabetes
from 159 families, including 224 affected sib pairs, Mori et al. (2002)
found suggestive linkage at chromosome 11p13-p12, with a maximum lod
score of 3.08. Analysis of sib pairs who had a BMI of less than 30
revealed suggestive linkage at chromosomes 7p22-p21 and 11p13-p12 (lod
scores of 3.51 and 3.00, respectively). Analysis of sib pairs who were
diagnosed before the age of 45 revealed suggestive linkage at chromosome
15q13-q21, with a maximum lod score of 3.91.

Demenais et al. (2003) applied the genome search metaanalysis (GSMA)
method to genomewide scans conducted with 4 European type II diabetes
mellitus cohorts comprising a total of 3,947 individuals, 2,843 of whom
were affected. The analysis provided evidence for linkage of type II
diabetes to 6 regions, with the strongest evidence on chromosome
17p11.2-q22 (p = 0.0016), followed by 2p22.1-p13.2 (p = 0.027),
1p13.1-q22 (p = 0.028), 12q21.1-q24.12 (p = 0.029), 6q21-q24.1 (p =
0.033), and 16p12.3-q11.2 (p = 0.033). Linkage analysis of the pooled
raw genotype data generated maximum lod scores in the same regions as
identified by GSMA; the maximum lod score for the 17p11.2-q22 region was
1.54.

Using nonparametric linkage analyses, Van Tilburg et al. (2003)
performed a genomewide scan to find susceptibility loci for type II
diabetes mellitus in the Dutch population. They studied 178 families
from the Netherlands, who constituted 312 affected sib pairs. Because
obesity and type II diabetes mellitus are interrelated, the dataset was
stratified for the subphenotype BMI, corrected for age and gender. This
resulted in a suggestive maximum multipoint lod score of 2.3
(single-point P value, 9.7 x 10(-4); genomewide P value, 0.028) for the
most obese 20% pedigrees of the dataset, between marker loci D18S471 and
D18S843. In the lowest 80% obese pedigrees, 2 interesting loci on
chromosome 2 and 19 were found, with lod scores of 1.5 and 1.3.

Shtir et al. (2007) performed ordered subset analysis on affected
individuals from 2 sets of families ascertained on affected sib pairs
with type 2 diabetes mellitus and found that 33 families with the lowest
average fasting insulin (606035) showed evidence for linkage to a locus
on chromosome 6q (maximum lod score of 3.45 at 128 cM near D6S1569,
uncorrected p = 0.017) that was coincident with QTL linkage results for
fasting and 2-hour insulin levels in family members without type 2
diabetes mellitus.

The Wellcome Trust Case Control Consortium (2007) described a joint
genomewide association study using the Affymetrix GeneChip 500K Mapping
Array Set, undertaken in the British population, which examined
approximately 2,000 individuals and a shared set of approximately 3,000
controls for each of 7 major diseases. Case-control comparisons
identified 3 significant independent association signals for type 2
diabetes, at dbSNP rs9465871 on chromosome 6p22, dbSNP rs4506565 on
chromosome 10q25, and dbSNP rs9939609 on chromosome 16q12.

In a genomewide association study of 1,363 French type 2 diabetes cases
and controls, Sladek et al. (2007) confirmed the known association with
dbSNP rs7903146 of the TCF7L2 gene (602228.0001) on chromosome 10q25.2
(p = 3.2 x 10(-17)). They also found significant association between T2D
and 2 SNPs on chromosome 10q23.33 (dbSNP rs1111875 and dbSNP rs7923837),
located near the telomeric end of a 270-kb linkage disequilibrium block
containing the IDE (146680), HHEX (604420), KIF11 (148760) genes. Sladek
et al. (2007) stated that fine mapping of the HHEX locus and biologic
studies would be required to identify the causative variant.

The Diabetes Genetics Initiative of Broad Institute of Harvard and MIT,
Lund University, and Novartis Institutes for BioMedical Research (2007)
analyzed 386,731 common SNPs in 1,464 patients with type 2 diabetes and
1,467 matched controls, each characterized for measures of glucose
metabolism, lipids, obesity, and blood pressure. With collaborators
Finland-United States Investigation of NIDDM Genetics (FUSION) and
Wellcome Trust Case Control Consortium/United Kingdom Type 2 Diabetes
Genetics Consortium (WTCCC/UKT2D), this group identified and confirmed 3
loci associated with type 2 diabetes--in a noncoding region near CDKN2A
(600160) and CDKN2B (600431), in an intron of IGF2BP2 (608289), and in
an intron of CDKAL1 (611259)--and replicated associations near HHEX and
SLC30A8 (611145) by recent whole-genome association study. The Diabetes
Genetics Initiative of Broad Institute of Harvard and MIT, Lund
University, and Novartis Institutes for BioMedical Research (2007)
identified and confirmed association of a SNP in an intron of
glucokinase regulatory protein (GCKR; 600842) with serum triglycerides
(see 613463). The authors concluded that the discovery of associated
variants in unsuspected genes and outside coding regions illustrates the
ability of genomewide association studies to provide potentially
important clues to the pathogenesis of common diseases.

Onuma et al. (2010) analyzed the GCKR SNP dbSNP rs780094 in 488 Japanese
patients with type 2 diabetes and 398 controls and found association
between a reduced risk of T2DM and the A allele (odds ratio, 0.711; p =
4.2 x 10(-4)). A metaanalysis with 2 previous association studies
(Sparso et al., 2008 and Horikawa et al., 2008) confirmed the
association of dbSNP rs780094 with T2D susceptibility. In the general
Japanese population, individuals with the A/A genotype had lower levels
of fasting plasma glucose (see 613463), fasting plasma insulin, and
HOMA-IR than those with the G/G genotype (p = 0.008, 0.008, and 0.002,
respectively); conversely, those with the A/A genotype had higher
triglyceride levels than those with the G/G genotype (p = 0.028).

Adopting a genomewide association strategy, Scott et al. (2007)
genotyped 1,161 Finnish type 2 diabetes cases and 1,174 Finnish normal
glucose tolerant controls with greater than 315,000 SNPs and imputed
genotypes for an additional greater than 2 million autosomal SNPs. Scott
et al. (2007) carried out association analysis with these SNPs to
identify genetic variants that predispose to type 2 diabetes, compared
to their type 2 diabetes association results with the results of 2
similar studies, and genotyped 80 SNPs in an additional 1,215 Finnish
type 2 diabetes cases and 1,258 Finnish normal glucose tolerant
controls. Scott et al. (2007) identified type 2 diabetes-associated
variants in an intergenic region of chromosome 11p12, contributed to the
identification of type 2 diabetes-associated variants near the genes
IGF2BP2 and CDKAL1 and the region of CDKN2A and CDKN2B, and confirmed
that variants near TCF7L2, SLC30A8, HHEX, FTO (610966), PPARG (601487),
and KCNJ11 (600937) are associated with type 2 diabetes risk. Scott et
al. (2007) concluded that this brings the number of type 2 diabetes loci
now confidently identified to at least 10.

Starting from genomewide genotype data for 1,924 diabetic cases and
2,938 population controls generated by the Wellcome Trust Case Control
Consortium, Zeggini et al. (2007) set out to detect replicated diabetes
association signals through analysis of 3,757 additional cases and 5,346
controls and by integration of their findings with equivalent data from
other international consortia. Zeggini et al. (2007) detected diabetes
susceptibility loci in and around the genes CDKAL1, CDKN2A/CDKN2B, and
IGF2BP2 and confirmed associations at HHEX/IDE and at SLC30A8. Zeggini
et al. (2007) concluded that their findings provided insight into the
genetic architecture of type 2 diabetes, emphasizing the contribution of
multiple variants of modest effect. The regions identified underscore
the importance of pathways influencing pancreatic beta cell development
and function in the etiology of type 2 diabetes.

Van Vliet-Ostaptchouk et al. (2008) genotyped 501 unrelated Dutch
patients with type 2 diabetes and 920 healthy controls for 2 SNPs in
strong linkage disequilibrium near the HHEX gene, dbSNP rs7923837 and
dbSNP rs1111875, and found that for both SNPs, the risk for T2D was
significantly increased in carriers of the major alleles (OR of 1.57 and
p = 0.017; OR of 1.68 and p = 0.003, respectively). Assuming a dominant
genetic model, the population-attributable risks for diabetes due to the
at-risk alleles of dbSNP rs7923837 and dbSNP rs1111875 were estimated to
be 33% and 36%, respectively.

Gudmundsson et al. (2007) found that the A allele of dbSNP rs4430796 in
the HNF1B gene (189907) was associated with a protective effect against
type 2 diabetes in a study of 1,380 Icelandic patients and 9,940
controls, and in 7 additional type 2 diabetes case-control groups of
European, African, and Asian ancestry (p = 2.7 x 10(-7) and odds ratio
of 0.91, for the combined results). This SNP is also associated with
prostate cancer risk (see HPC11, 611955).

Prokopenko et al. (2008) reviewed advances in identifying common genetic
variants that contribute to complex multifactorial phenotypes such as
type 2 diabetes (T2D), particularly the ability to perform genomewide
association studies in large samples. They noted that the 2 most robust
T2D candidate-gene associations previously reported, for common
polymorphisms in PPARG and KCNJ11, have only modest effect sizes, with
each copy of the susceptibility allele increasing the risk of disease by
15 to 20%. In contrast, microsatellite mapping detected an association
with variation in the TCF7L2 gene that has a substantially stronger
effect, with the 10% of Europeans who are homozygous for the risk allele
having approximately twice the odds of developing T2D compared to those
carrying no copies of the risk allele. Prokopenko et al. (2008) stated
that about 20 common variants had been robustly implicated in T2D
susceptibility to date, but noted that for most of the loci, causal
variants had yet to be identified with any certainty.

The Wellcome Trust Case Control Consortium (2010) undertook a large
direct genomewide study of association between copy number variants
(CNVs) and 8 common human diseases involving approximately 19,000
individuals. Association testing and follow-up replication analyses
confirmed association of CNV at the TSPAN8 (600769) locus with type 2
diabetes.

- Association with Variation in KCNQ1

Yasuda et al. (2008) carried out a multistage genomewide association
study of type 2 diabetes mellitus in Japanese individuals, with a total
of 1,612 cases and 1,424 controls and 100,000 SNPs. The most significant
association was obtained with SNPs in KCNQ1 (607542), and dense mapping
within the gene revealed that dbSNP rs2237892 in intron 15 showed the
lowest P value (6.7 x 10(-13), odds ratio = 1.49). The association of
KCNQ1 with type 2 diabetes was replicated in populations of Korean,
Chinese, and European ancestry as well as in 2 independent Japanese
populations, and metaanalysis with a total of 19,930 individuals (9,569
cases and 10,361 controls) yielded a P value of 1.7 x 10(-42) (odds
ratio = 1.40; 95% confidence interval = 1.34-1.47) for dbSNP rs2237892.
Among control subjects, the risk allele of this polymorphism was
associated with impairment of insulin secretion according to the
homeostasis model assessment of beta-cell function or the corrected
insulin response.

Unoki et al. (2008) conducted a genomewide association study using
207,097 SNP markers in Japanese individuals with type 2 diabetes and
unrelated controls, and identified KCNQ1 to be a strong candidate for
conferring susceptibility to type 2 diabetes. Unoki et al. (2008)
detected consistent association of a SNP in KCNQ1 (dbSNP rs2283228) with
the disease in several independent case-control studies (additive model
P = 3.1 x 10(-12); odds ratio = 1.26, 95% confidence interval =
1.18-1.34). Several other SNPs in the same linkage disequilibrium block
were strongly associated with type 2 diabetes. The association of these
SNPs with type 2 diabetes was replicated in samples from Singaporean and
Danish populations.

- Association with Variation in SHBG

Ding et al. (2009) analyzed levels of sex hormone-binding globulin (see
SHBG; 182205) in 359 women newly diagnosed with type 2 diabetes and 359
female controls and found that higher plasma levels of SHBG were
prospectively associated with a lower risk of type 2 diabetes, with
multivariable odds ratios ranging from 1.00 for the lowest quartile of
plasma levels to 0.09 for the highest quartile; the results were
replicated in an independent cohort of men (p less than 0.001 for
results in both women and men). Ding et al. (2009) identified an SHBG
SNP, dbSNP rs6259, that was associated with a 10% higher plasma level of
SHBG, and another SNP, dbSNP rs6257, that was associated with a 10%
lower plasma level of SHBG; variants of both SNPs were also associated
with a risk of type 2 diabetes in directions corresponding to their
associated SHBG levels. In mendelian randomization analyses, the
predicted odds ratio of type 2 diabetes per standard deviation increase
in plasma level of SHBG was 0.28 among women and 0.29 among men. Ding et
al. (2009) suggested that variation in the SHBG gene on chromosome
17p13-p12 may have a causal role in the risk of type 2 diabetes.

Kong et al. (2009) identified a differentially methylated CTCF binding
site at 11p15 and demonstrated correlation of dbSNP rs2334499 with
decreased methylation of that site. The CTCF-binding site is OREG0020670
and its 2-kb region located 17 kb centromeric to the type 2 diabetes
marker dbSNP rs2334499.

Perry et al. (2010) genotyped 27,657 type 2 diabetes patients and 58,481
controls from 15 studies at the SHBG promoter SNP dbSNP rs1799941 that
is strongly associated with serum levels of SHBG. The authors used data
from additional studies to estimate the difference in SHBG levels
between type 2 diabetes patients and controls. The dbSNP rs1799941
variant was associated with type 2 diabetes (OR, 0.94; 95% CI,
0.91-0.97; p = 2 x 10(-5)), with the SHBG-raising A allele associated
with reduced risk of type 2 diabetes, the results were very similar in
men and women. There was no evidence that dbSNP rs1799941 was associated
with diabetes-related intermediate traits, including several measures of
insulin secretion and resistance.

- Association with Variation in RBP4

Serum levels of RBP4 (180250), a protein secreted by adipocytes, are
increased in insulin-resistant states. Experiments in mice suggested
that elevated RBP4 levels cause insulin resistance (Yang et al., 2005).
Graham et al. (2006) found that serum RBP4 levels correlated with the
magnitude of insulin resistance in human subjects with obesity (601665),
impaired glucose tolerance, or type 2 diabetes and in nonobese,
nondiabetic subjects with a strong family history of type 2 diabetes.
Elevated serum RBP4 was associated with components of the metabolic
syndrome, including increased body mass index (BMI), waist-to-hip ratio,
serum triglyceride levels, and systolic blood pressure and decreased
high-density lipoprotein cholesterol levels. Exercise training was
associated with a reduction in serum RBP4 levels only in subjects in
whom insulin resistance improved. Adipocyte GLUT4 protein (138190) and
serum RBP4 levels were inversely correlated. Graham et al. (2006)
concluded that RBP4 is elevated in serum before the development of frank
diabetes and appears to identify insulin resistance and associated
cardiovascular risk factors in subjects with varied clinical
presentations. They suggested that these findings provide a rationale
for antidiabetic therapies aimed at lowering serum RBP4 levels.

Aeberli et al. (2007) studied serum RBP4, serum retinol (SR), the
RBP4-to-SR molar ratio, and dietary vitamin A intakes in seventy-nine 6-
to 14-year-old normal-weight and overweight children and investigated
the relationship of these variables to insulin resistance, subclinical
inflammation, and the metabolic syndrome. Only 3% of children had low
vitamin A status. Independent of age, vitamin A intakes, and C-reactive
protein (see 123260), BMI, body fat percentage, and waist-to-hip ratio
were significant predictors of RBP4, serum retinol, and RBP4/SR. Aeberli
et al. (2007) concluded that independent of subclinical inflammation and
vitamin A intakes, serum RBP4 and the RBP4-to-SR ratio are correlated
with obesity, central obesity, and components of the metabolic syndrome
in prepubertal and early pubertal children.

MOLECULAR GENETICS

- Mutation in PPAR-Gamma

Altshuler et al. (2000) confirmed an association of the common
pro12-to-ala polymorphism in PPAR-gamma (601487.0002) with type II
diabetes. They found a modest but significant increase in diabetes risk
associated with the more common proline allele (approximately 85%
frequency). Because the risk allele occurs at such high frequency, its
modest effect translates into a large population-attributable
risk--influencing as much as 25% of type II diabetes in the general
population.

Savage et al. (2002) described a family, which they referred to as a
'Europid pedigree,' in which several members had severe insulin
resistance. The grandparents had typical late-onset type II diabetes
with no clinical features of severe insulin resistance. Three of their 6
children and 2 of their grandchildren had acanthosis nigricans, elevated
fasting plasma insulin levels. Hypertension was also a feature. By
mutation screening, Savage et al. (2002) identified a heterozygous
frameshift resulting in a premature stop mutation of the PPARG
(601487.0011) gene which was present in the grandfather, all 5 relatives
with severe insulin resistance, and 1 other relative with normal insulin
levels. Further candidate gene studies revealed a heterozygous
frameshift/premature stop mutation in PPP1R3A (600917.0003) which was
present in the grandmother, in all 5 individuals with severe insulin
resistance, and in 1 other relative. Thus, all 5 family members with
severe insulin resistance, and no other family members, were double
heterozygotes with respect to frameshift mutations. (Although the
article by Savage et al. (2002) originally stated that the affected
individuals were compound heterozygotes, they were actually double
heterozygotes. Compound heterozygosity is heterozygosity at the same
locus for each of 2 different mutant alleles; double heterozygosity is
heterozygosity at each of 2 separate loci. The use of an incorrect term
in the original publication was the result of a 'copy-editing error that
was implemented after the authors returned corrected proofs' (Savage et
al., 2002).)

- Association with Insulin Receptor Substrate-2

Mammarella et al. (2000) genotyped 193 Italian patients with type II
diabetes and 206 control subjects for the insulin receptor substrate-2
G1057D polymorphism (600797.0001). They found evidence for a strong
association between type II diabetes and the polymorphism, which appears
to be protective against type II diabetes in a codominant fashion.

- Association with Adiponectin

For a discussion of an association between variation in the ADIPOQ gene
(605441) on chromosome 3q27 and type 2 diabetes, see ADIPQTL1 (612556).

- Association with Mitochondrial DNA Variation

A common mtDNA variant (T16189C) in a noncoding region of mtDNA was
positively correlated with blood fasting insulin by Poulton et al.
(1998). Poulton et al. (2002) demonstrated a significant association
between the 16189 variant and type II diabetes in a population-based
case-control study in Cambridgeshire, UK (n = 932, odds ratio = 1.61;
1.0-2.7, P = 0.048), which was greatly magnified in individuals with a
family history of diabetes from the father's side (odds ratio =
infinity; P less than 0.001). Poulton et al. (2002) demonstrated that
the 16189 variant had arisen independently many times and on multiple
mitochondrial haplotypes. They speculated that the 16189 variant may
alter mtDNA bending and hence could influence interactions with
regulatory proteins which control replication or transcription.

Mohlke et al. (2005) presented data supporting previous evidence for
association of 16189T-C with reduced ponderal index at birth and also
showed evidence for association with reduced birth weight but not with
diabetes status. This study suggested that mitochondrial genome variants
may play at most a modest role in glucose metabolism in the Finnish
population studied. Furthermore, the data did not support a reported
maternal inheritance pattern of type II diabetes mellitus but instead
showed a strong effect of recall bias.

Because mitochondria play pivotal roles in both insulin secretion from
the pancreatic beta cells and insulin resistance of skeletal muscles,
Fuku et al. (2007) performed a large-scale association study to identify
mitochondrial haplogroups that may confer resistance against or
susceptibility to type II diabetes mellitus. The study population
comprised 2,906 unrelated Japanese individuals, including 1,289 patients
with type II diabetes mellitus and 1,617 controls, and 1,365 unrelated
Korean individuals, including 732 patients with type II diabetes and 633
controls. The genotypes for 25 polymorphisms in the coding region of the
mitochondrial genome were determined, and the haplotypes were classified
into 10 major haplogroups. Multivariate logistic regression analysis
with adjustment for age and sex revealed that the mitochondrial group
N9a was significantly associated with resistance against type II
diabetes mellitus (P = 0.0002) with an odds ratio of 0.55 (95%
confidence interval 0.40-0.75). Even in the modern environment, which is
often characterized by satiety and physical inactivity, this haplotype
might confer resistance against type II diabetes mellitus. The N9a
haplogroup found to be associated with reduced susceptibility to type II
diabetes mellitus by Fuku et al. (2007) consisted of a synonymous SNP in
ND2 (516001), 5231G-A; a missense change in ND5 (516005), thr8 to ala;
and a synonymous change also in ND5, 12372G-A.

- Mutation in PAX4

Shimajiri et al. (2001) scanned the PAX4 gene (167413) in 200 unrelated
Japanese probands with type 2 diabetes and identified an arg121-to-tyr
mutation (R121W; 167413.0001) in 6 heterozygous patients and 1
homozygous patient (mutant allele frequency 2.0%). The mutation was not
found in 161 nondiabetic subjects (p = 0.01). Six of 7 patients had a
family history of diabetes or impaired glucose tolerance, and 4 of 7 had
transient insulin therapy at the onset. One of them, a homozygous
carrier, had relatively early-onset diabetes and slowly fell into an
insulin-dependent state without an autoimmune-mediated process.

- Association with TFAP2B

Maeda et al. (2005) performed a genomewide, case-control association
study using gene-based SNPs in Japanese patients with type II diabetes
and controls and identified several variations within the TFAP2B gene
(601601) that were significantly associated with type II diabetes: an
intron 1 VNTR (p = 0.0009), intron 1 +774G-T (p = 0.0006), and intron 1
+2093A-C (p = 0.0004). The association of TFAP2B with type II diabetes
was also observed in a U.K. population. Maeda et al. (2005) suggested
that the TFAP2B gene may confer susceptibility to type II diabetes.

- Mutation in ABCC8

Babenko et al. (2006) screened the ABCC8 gene (600509) in 34 patients
with permanent neonatal diabetes (606176) or transient neonatal diabetes
(see 601410) and identified heterozygosity for 7 missense mutations in 9
patients (see, e.g., 600509.0017-600509.0020). The mutation-positive
fathers of 5 of the probands with transient neonatal diabetes developed
type II diabetes mellitus in adulthood; Babenko et al. (2006) proposed
that mutations of the ABCC8 gene may give rise to a monogenic form of
type II diabetes with variable expression and age at onset.

- Association with WFS1

Sandhu et al. (2007) conducted a gene-centric association study for type
2 diabetes in multiple large cohorts and identified 2 SNPs located in
the WFS1 gene, dbSNP rs10010131 (606201.0021) and dbSNP rs6446482
(602201.0022), that were strongly associated with diabetes risk (P = 1.4
x 10(-7) and P = 3.4 x 10(-7), respectively, in the pooled study set).
The risk allele was the major allele for both SNPs, with a frequency of
60% for both. The authors noted that both are intronic, with no obvious
evidence for biologic function.

- Association with IL6

Mohlig et al. (2004) investigated the IL6 -174C-G SNP (147620.0001) and
development of NIDDM. They found that this SNP modified the correlation
between BMI and IL6 by showing a much stronger increase of IL6 at
increased BMI for CC genotypes compared with GG genotypes. The -174C-G
polymorphism was found to be an effect modifier for the impact of BMI
regarding NIDDM. The authors concluded that obese individuals with BMI
greater than or equal to 28 kg/m2 carrying the CC genotype showed a more
than 5-fold increased risk of developing NIDDM compared with the
remaining genotypes and, hence, might profit most from weight reduction.

Illig et al. (2004) investigated the association of the IL6 SNPs -174C-G
and -598A-G on parameters of type 2 diabetes and the metabolic syndrome
in 704 elderly participants of the Kooperative Gesundheitsforschung im
Raum Augsburg/Cooperative Research in the Region of Augsburg (KORA)
Survey 2000. They found no significant associations, although both SNPs
exhibited a positive trend towards association with type 2 diabetes.
Illig et al. (2004) also found that circulating IL6 levels were not
associated with the IL6 polymorphisms; however, significantly elevated
levels of the chemokine monocyte chemoattractant protein-1 (MCP1;
158105)/CC chemokine ligand-2 (CKR2; 601267) in carriers of the
protective genotypes suggested an indirect effect of these SNPs on the
innate immune system.

- Association with KCNJ15

Okamoto et al. (2010) identified a synonymous SNP (dbSNP rs3746876,
C566T) in exon 4 of the KCNJ15 (602106) that showed significant
association with type 2 diabetes mellitus affecting lean individuals in
3 independent Japanese sample sets (p = 2.5 x 10(-7); odds ratio, 2.54)
and with unstratified T2DM (p = 6.7 x 10(-6); OR, 1.76). The diabetes
risk allele frequency was, however, very low among Europeans and no
association between the variant and T2DM could be shown in a Danish
case-control study. Functional analysis in HEK293 cells demonstrated
that the risk T allele increased KCNJ15 expression via increased mRNA
stability, which resulted in higher expression of protein compared to
the C allele.

- Mutation in MTNR1B

Bonnefond et al. (2012) performed large-scale exon resequencing of the
MTNR1B gene (600804) in 7,632 Europeans, including 2,186 individuals
with type 2 diabetes mellitus, and identified 36 very rare variants
associated with T2D. Among the very rare variants, partial or total
loss-of-function variants but not neutral ones contributed to T2D (odds
ratio, 5.67; p = 4.09 x 10(-4)). Genotyping 4 variants with complete
loss of melatonin-binding and signaling capabilities (A42P, 600804.0001;
L60R, 600804.0002; P95L, 600804.0003; and Y308S, 600804.0004) as a pool
in 11,854 additional French individuals, including 5,967 with T2D,
demonstrated their association with T2D (odds ratio, 3.88; p = 5.37 x
10(-3)). Bonnefond et al. (2012) concluded that their study established
a firm functional link between MTNR1B and T2D risk.

OTHER FEATURES

Diabetes mellitus is a recognized consequence of hereditary
hemochromatosis (HFE; 235200). To test whether common mutations in the
HFE gene (613609) that associate with this condition and predispose to
increases in serum iron indices are overrepresented in diabetic
populations, Halsall et al. (2003) determined the allele frequencies of
the C282Y (613609.0001) and H63D (613609.0002) HFE mutations among a
cohort of 552 patients with typical type II diabetes mellitus. There was
no evidence for overrepresentation of iron-loading HFE alleles in type
II diabetes mellitus, suggesting that screening for HFE mutations in
this population is of no value.

Meigs et al. (2008) genotyped SNPs at 18 loci associated with diabetes
in 2,377 participants of the Framingham Offspring Study. They created a
genotype score from the number of risk alleles and used logistic
regression to generate C statistics indicating the extent to which the
genotype score can discriminate the risk of diabetes when used alone and
in addition to clinical risk factors. There were 255 new cases of
diabetes during 28 years of follow-up. The mean (+/- standard deviation)
genotype score was 17.7 +/- 2.7 among subjects in whom diabetes
developed and 17.1 +/- 2.6 among those in whom diabetes did not develop
(P = less than 0.001). The sex-associated odds ratio for diabetes was
1.12 per risk allele (95% confidence interval, 1.07 to 1.17). The C
statistic was 0.534 without the genotype score and 0.581 with the score
(P = 0.01). In a model adjusted for age, sex, family history, body mass
index, fasting glucose level, systolic blood pressure, high-density
lipoprotein cholesterol level, and triglyceride level, the C statistic
was 0.900 without the genotype score and 0.901 with the score, not
significantly different. The genotype score resulted in the appropriate
risk reclassification of, at most, 4% of the subjects. Meigs et al.
(2008) concluded that a genotype score based on 18 risk alleles
predicted new cases of diabetes in the community but provided only a
slightly better prediction of risk than knowledge of common risk factors
alone.

Lyssenko et al. (2008) genotyped 16 SNPs and examined clinical factors
in 16,061 Swedish and 2,770 Finnish subjects. Type 2 diabetes developed
in 2,201 (11.7%) of these subjects during a median follow-up period of
23.5 years. Strong predictors of diabetes were a family history of the
disease, increased body mass index, elevated liver enzyme levels,
current smoking status, and reduced measures of insulin secretion
action. Variants in 11 genes were significantly associated with the risk
of type 2 diabetes independently of clinical risk factors; variants in 8
of these genes were associated with impaired beta cell function. The
addition of specific genetic information to clinical factors slightly
improved the prediction of future diabetes, with a slight increase in
the area under the receiver-operating-characteristic (also known as C
statistics) curve from 0.74 to 0.75; however, the magnitude of the
increase was significant (P = 1.0 x 10(-4)). Lyssenko et al. (2008)
concluded that as compared with clinical risk factors alone, common
genetic variants associated with the risk of diabetes had a small effect
on the ability to predict the future development of type 2 diabetes. The
value of genetic factors increased with an increasing duration of
follow-up.

ANIMAL MODEL

The most widely used animal model of nonobese NIDDM is the Goto-Kakizaki
(GK) rat. Galli et al. (1996) mapped 3 independent loci involved in the
disease. Thus, NIDDM in the rat is polygenic. The 3 NIDDM loci were
found to have distinct physiologic effects. One affected postprandial
but not fasting hyperglycemia, whereas the other 2 affected both.
Gauguier et al. (1996) mapped up to 6 independently segregating loci
predisposing to hyperglycemia, glucose intolerance, or altered insulin
secretion in the GK rat. Both Galli et al. (1996) and Gauguier et al.
(1996) identified a locus implicated in body weight. The close
similarity between diabetes-related phenotypes in the GK rat and human
NIDDM suggested to the authors that similar patterns of genetic
heterogeneity may underlie the disease in humans and that the results in
rats may be useful in understanding the human disease.

Fakhrai-Rad et al. (2000) mapped the NIDDM1B locus in the GK rat to a
1-cM region by genetic and pathophysiologic characterization of new
congenic substrains for the locus. The gene encoding insulin-degrading
enzyme (IDE; 146680) was also mapped to this 1-cM region, and 2 amino
acid substitutions (H18R and A890V) were identified in the GK allele
which reduced insulin-degrading activity by 31% in transfected cells.
However, when the H18R and A890V variants were studied separately, no
effects were observed, suggesting a synergistic effect of the 2 variants
on insulin degradation. No effect on insulin degradation was observed in
cell lysates, suggesting that the effect may be coupled to
receptor-mediated internalization of insulin. Congenic rats with the IDE
GK allele displayed postprandial hyperglycemia, reduced lipogenesis in
fat cells, blunted insulin-stimulated glucose transmembrane uptake, and
reduced insulin degradation in isolated muscle. Analysis of additional
rat strains demonstrated that the dysfunctional IDE allele was unique to
GK rats. The authors concluded that IDE plays an important role in the
diabetic phenotype in GK rats.

Bruning et al. (1997) created a polygenic (or at least digenic) model of
NIDDM in mice. The model reproduced the characteristics of the human
disease, namely insulin resistance in muscle, fat, and liver, followed
by failure of pancreatic beta-cells to compensate adequately for this
resistance despite increased insulin secretion. Mice doubly heterozygous
for null alleles in the insulin receptor (147670) and insulin receptor
substrate-1 (IRS1; 147545) genes exhibited the expected reduction by
approximately 50% in expression of these 2 proteins, but a synergism at
the level of insulin resistance with 5- to 50-fold elevated plasma
insulin levels and comparable levels of beta-cell hyperplasia. At 4 to 6
months of age, 40% of these doubly heterozygote mice became overtly
diabetic. Thus, diabetes arose in an age-dependent manner from an
interaction between 2 genetically determined, subclinical defects in the
insulin signaling cascade, demonstrating the role of epistatic
interactions in the pathogenesis of common diseases with nonmendelian
genetics.

Terauchi et al. (1997) likewise created a polygenic model of NIDDM by
heterozygous knockout of the IRS1 gene with heterozygous knockout of the
beta-cell GCK gene. They found that the genetic abnormalities, each of
which was nondiabetogenic by itself, caused overt diabetes if they
coexisted.

The Zucker diabetic fatty (ZDF) rat is another animal model of human
adipogenic NIDDM. Shimabukuro et al. (1998) demonstrated in islets of
obese ZDF rats a pathway of lipotoxicity leading to diabetes. Elevated
levels of circulating free fatty acids (Lee et al., 1994) and
lipoproteins transport to islets of obese ZDF rats far more free fatty
acids than can be oxidized. Because fa/fa islets exhibit a markedly
increased lipogenic capacity and a decreased oxidative capacity, unused
free fatty acids in islets are esterified and over time an excessive
quantity is deposited (Lee et al., 1997). This is associated with an
increase in ceramide, inducible NOS expression, and NO production, which
causes apoptosis. That troglitazone, an agent that reduces islet fat in
ZDF rats (Shimabukuro et al., 1997) and prevents their diabetes (Sreenan
et al., 1996), is equally efficacious in human NIDDM suggests a
comparable pathway of lipotoxicity to diabetes in humans.

Hart et al. (2000) showed that FGF receptors 1 and 2 (136350, 176943),
together with ligands FGF1 (131220), FGF2 (134920), FGF4 (164980), FGF5
(165190), FGF7 (148180), and FGF10 (602115), are expressed in adult
mouse beta cells, indicating that FGF signaling may have a role in
differentiated beta cells. When Hart et al. (2000) perturbed signaling
by expressing dominant-negative forms of the receptors, FGFR1C and
FGFR2B, in the pancreas, they found that mice with attenuated FGFR1C
signaling, but not those with reduced FGFR2B signaling, developed
diabetes with age and exhibited a decreased number of beta cells,
impaired expression of glucose transporter 2 (138160), and increased
proinsulin content in beta cells owing to impaired expression of
prohormone convertases 1/3 and 2. These defects are all characteristic
of patients with type II diabetes. Mutations in the homeobox gene
IPF1/PDX1 (600733) are linked to diabetes in both mouse and human. Hart
et al. (2000) showed that IPF1/PDX1 is required for the expression of
FGFR1 signaling components in beta cells, indicating that IPF1/PDX1 acts
upstream of FGFR1 signaling in beta cells to maintain proper glucose
sensing, insulin processing, and glucose homeostasis.

Yuan et al. (2001) demonstrated that high doses of salicylates reverse
hyperglycemia, hyperinsulinemia, and dyslipidemia in obese rodents by
sensitizing insulin signaling. Activation or overexpression of IKBKB
(603258) attenuated insulin signaling in cultured cells, whereas IKKB
inhibition reversed insulin resistance. Thus, Yuan et al. (2001)
concluded that IKKB, rather than the cyclooxygenases (see 600262),
appears to be the relevant molecular target. Heterozygous deletion (IKKB
+/-) protected against the development of insulin resistance during high
fat feeding and in obese Lep (ob/ob) (see 164160) mice. Yuan et al.
(2001) concluded that their findings implicate an inflammatory process
in the pathogenesis of insulin resistance in obesity and type II
diabetes mellitus and identified the IKKB pathway as a target for
insulin sensitization.

Scheuner et al. (2005) studied glucose homeostasis in mice with a
ser51-to-ala substitution at the phosphorylation site of the translation
initiation factor eIF2-alpha (see 603907) and observed that heterozygous
mutant mice became obese and diabetic on a high-fat diet. Profound
glucose intolerance resulted from reduced insulin secretion accompanied
by abnormal distention of the ER lumen, defective trafficking of
proinsulin, and a reduced number of insulin granules in beta cells.
Scheuner et al. (2005) proposed that translational control couples
insulin synthesis with folding capacity to maintain ER integrity and
that this signal is essential to prevent diet-induced type II diabetes.

In Hmga1 (600701)-deficient mice, Foti et al. (2005) observed decreased
insulin receptor expression in muscle, fat, and liver, largely impaired
insulin signaling, and severely reduced insulin secretion, causing a
phenotype characteristic of human type II diabetes.

Matsuzaka et al. (2007) reported that Elovl6 (611546) -/- mice developed
obesity and hepatosteatosis when fed a high-fat diet or when mated to
leptin-deficient (ob/ob) mice, but showed marked protection from
hyperinsulinemia, hyperglycemia, and hyperleptinemia. Amelioration of
insulin resistance was associated with restoration of hepatic insulin
receptor substrate-2 (IRS2; 600797) and suppression of hepatic protein
kinase C-epsilon (PRKCE; 176975), resulting in restoration of Akt (see
164730) phosphorylation. Matsuzaka et al. (2007) noted that the Elovl6
-/- mice were unique in that their insulin resistance was reduced
without the amelioration of obesity or hepatosteatosis, and concluded
that hepatic fatty acid composition is a new determinant for insulin
sensitivity that acts independently of cellular energy balance and
stress.

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*FIELD* CS

Endo:
Noninsulin-dependent diabetes mellitus

Misc:
Late onset

Lab:
Insulin resistance;
Decreased glucose disposal

Inheritance:
Autosomal dominant

*FIELD* CN
Ada Hamosh - updated: 7/24/2012
Marla J. F. O'Neill - updated: 7/6/2012
Marla J. F. O'Neill - updated: 3/16/2012
Marla J. F. O'Neill - updated: 10/19/2011
Ada Hamosh - updated: 5/23/2011
Ada Hamosh - updated: 5/3/2011
Marla J. F. O'Neill - updated: 4/15/2011
George E. Tiller - updated: 1/5/2011
Ada Hamosh - updated: 4/28/2010
Marla J. F. O'Neill - updated: 2/26/2010
Ada Hamosh - updated: 1/6/2010
Marla J. F. O'Neill - updated: 10/5/2009
Marla J. F. O'Neill - updated: 9/16/2009
Marla J. F. O'Neill - updated: 2/12/2009
Marla J. F. O'Neill - updated: 1/29/2009
Ada Hamosh - updated: 11/21/2008
Ada Hamosh - updated: 10/22/2008
Marla J. F. O'Neill - updated: 8/4/2008
Ada Hamosh - updated: 4/16/2008
Victor A. McKusick - updated: 4/4/2008
Ada Hamosh - updated: 4/4/2008
Marla J. F. O'Neill - updated: 12/5/2007
Marla J. F. O'Neill - updated: 8/16/2007
George E. Tiller - updated: 5/21/2007
Victor A. McKusick - updated: 2/19/2007
Marla J. F. O'Neill - updated: 12/12/2006
Marla J. F. O'Neill - updated: 9/8/2006
Marla J. F. O'Neill - updated: 8/30/2006
Marla J. F. O'Neill - updated: 8/11/2006
Victor A. McKusick - updated: 6/6/2006
Marla J. F. O'Neill - updated: 4/4/2006
Victor A. McKusick - updated: 2/14/2006
Marla J. F. O'Neill - updated: 11/17/2005
Marla J. F. O'Neill - updated: 7/27/2005
Jane Kelly - updated: 7/19/2005
George E. Tiller - updated: 5/4/2005
George E. Tiller - updated: 3/21/2005
Marla J. F. O'Neill - updated: 3/1/2005
John A. Phillips, III - updated: 10/15/2004
Ada Hamosh - updated: 6/8/2004
George E. Tiller - updated: 2/4/2004
John A. Phillips, III - updated: 8/20/2003
Victor A. McKusick - updated: 8/11/2003
George E. Tiller - updated: 7/14/2003
Ada Hamosh - updated: 6/10/2003
John A. Phillips, III - updated: 2/26/2002
Ada Hamosh - updated: 10/18/2001
Ada Hamosh - updated: 9/12/2001
John A. Phillips, III - updated: 7/27/2001
John A. Phillips, III - updated: 3/5/2001
John A. Phillips, III - updated: 2/12/2001
George E. Tiller - updated: 2/5/2001
Ada Hamosh - updated: 12/21/2000
Victor A. McKusick - updated: 12/13/2000
Victor A. McKusick - updated: 11/21/2000
George E. Tiller - updated: 11/17/2000
Victor A. McKusick - updated: 9/22/2000
Victor A. McKusick - updated: 8/29/2000
John A. Phillips, III - updated: 10/7/1999
Wilson H. Y. Lo - updated: 8/24/1999
Wilson H. Y. Lo - updated: 7/26/1999
Victor A. McKusick - updated: 4/5/1999
John A. Phillips, III - updated: 3/2/1999
Victor A. McKusick - updated: 5/18/1998
Victor A. McKusick - updated: 3/25/1998
Victor A. McKusick - updated: 5/9/1997
Victor A. McKusick - updated: 4/7/1997
Mark H. Paalman - updated: 9/10/1996

*FIELD* CD
Victor A. McKusick: 5/14/1993

*FIELD* ED
tpirozzi: 07/12/2013
terry: 4/4/2013
carol: 4/4/2013
carol: 3/29/2013
terry: 11/13/2012
alopez: 7/31/2012
terry: 7/27/2012
terry: 7/24/2012
carol: 7/6/2012
carol: 3/16/2012
terry: 3/16/2012
carol: 10/19/2011
terry: 5/27/2011
alopez: 5/25/2011
terry: 5/23/2011
alopez: 5/9/2011
terry: 5/3/2011
wwang: 4/19/2011
terry: 4/15/2011
wwang: 1/19/2011
terry: 1/5/2011
alopez: 11/10/2010
carol: 10/21/2010
alopez: 7/21/2010
terry: 7/7/2010
alopez: 5/25/2010
alopez: 4/29/2010
terry: 4/28/2010
wwang: 4/1/2010
terry: 3/30/2010
carol: 3/9/2010
carol: 2/26/2010
wwang: 2/25/2010
alopez: 1/15/2010
terry: 1/6/2010
terry: 12/16/2009
wwang: 10/22/2009
terry: 10/5/2009
carol: 9/16/2009
wwang: 3/6/2009
carol: 2/12/2009
wwang: 2/5/2009
wwang: 2/2/2009
terry: 1/29/2009
alopez: 1/21/2009
wwang: 12/30/2008
terry: 12/19/2008
alopez: 12/16/2008
terry: 11/21/2008
alopez: 10/31/2008
terry: 10/22/2008
alopez: 8/28/2008
carol: 8/6/2008
terry: 8/4/2008
mgross: 7/25/2008
alopez: 6/27/2008
alopez: 5/13/2008
terry: 4/16/2008
alopez: 4/4/2008
alopez: 3/13/2008
alopez: 12/7/2007
wwang: 12/5/2007
wwang: 8/16/2007
terry: 5/21/2007
carol: 4/13/2007
alopez: 2/27/2007
terry: 2/19/2007
wwang: 12/14/2006
terry: 12/12/2006
alopez: 11/21/2006
wwang: 9/22/2006
wwang: 9/12/2006
terry: 9/8/2006
wwang: 9/6/2006
carol: 9/5/2006
terry: 8/30/2006
wwang: 8/16/2006
terry: 8/11/2006
alopez: 6/12/2006
terry: 6/6/2006
wwang: 5/17/2006
carol: 4/4/2006
terry: 2/14/2006
wwang: 1/13/2006
wwang: 11/21/2005
terry: 11/17/2005
terry: 10/4/2005
alopez: 8/22/2005
wwang: 8/3/2005
terry: 7/27/2005
alopez: 7/27/2005
alopez: 7/19/2005
tkritzer: 5/4/2005
alopez: 4/1/2005
alopez: 3/30/2005
alopez: 3/21/2005
wwang: 3/1/2005
alopez: 10/15/2004
alopez: 8/19/2004
alopez: 6/9/2004
terry: 6/8/2004
terry: 6/2/2004
carol: 5/4/2004
ckniffin: 4/27/2004
terry: 3/18/2004
cwells: 2/4/2004
alopez: 9/30/2003
alopez: 8/21/2003
alopez: 8/20/2003
carol: 8/13/2003
mgross: 8/13/2003
terry: 8/11/2003
cwells: 7/14/2003
alopez: 6/11/2003
terry: 6/10/2003
alopez: 1/21/2003
alopez: 9/25/2002
carol: 3/1/2002
alopez: 2/26/2002
carol: 10/18/2001
carol: 10/17/2001
alopez: 9/17/2001
terry: 9/12/2001
mgross: 7/27/2001
alopez: 6/4/2001
alopez: 3/6/2001
alopez: 3/5/2001
terry: 2/12/2001
carol: 2/5/2001
carol: 12/23/2000
terry: 12/21/2000
terry: 12/13/2000
mcapotos: 12/11/2000
mcapotos: 11/30/2000
mcapotos: 11/27/2000
terry: 11/21/2000
mcapotos: 11/21/2000
terry: 11/17/2000
alopez: 9/25/2000
terry: 9/22/2000
alopez: 8/29/2000
alopez: 3/1/2000
alopez: 2/17/2000
alopez: 2/4/2000
alopez: 12/6/1999
alopez: 11/5/1999
alopez: 11/4/1999
mgross: 10/7/1999
carol: 8/24/1999
carol: 7/26/1999
mgross: 4/5/1999
mgross: 3/11/1999
mgross: 3/2/1999
carol: 6/9/1998
terry: 5/18/1998
alopez: 3/25/1998
terry: 3/20/1998
alopez: 5/9/1997
alopez: 5/7/1997
mark: 4/7/1997
terry: 4/2/1997
mark: 9/10/1996
terry: 9/5/1996
mark: 5/30/1996
terry: 5/28/1996
mark: 1/4/1996
terry: 12/29/1995
jason: 7/14/1994
mimadm: 6/25/1994
carol: 5/10/1994
carol: 12/22/1993
carol: 7/13/1993
carol: 5/14/1993

MIM 138190
*RECORD*
*FIELD* NO
138190
*FIELD* TI
*138190 SOLUTE CARRIER FAMILY 2 (FACILITATED GLUCOSE TRANSPORTER), MEMBER
4; SLC2A4
read more;;GLUCOSE TRANSPORTER 4; GLUT4;;
GLUCOSE TRANSPORTER, INSULIN-RESPONSIVE
*FIELD* TX

CLONING

Facilitated glucose transport by mammalian cells is not a property of a
single protein but an activity associated with a family of structurally
related proteins. From rat skeletal muscle, Birnbaum (1989) cloned a
gene encoding an insulin-responsive glucose transporter protein. Bell et
al. (1990) isolated and completely characterized the human GLUT4 gene.

GENE FUNCTION

Garvey et al. (1998) concluded that insulin (176730) alters the
subcellular localization of GLUT4 vesicles in human muscle, and that
this effect is impaired equally in insulin-resistant subjects with and
without diabetes (see 125853). The translocation defect was associated
with abnormal accumulation of GLUT4 in a dense membrane compartment
demonstrable in basal muscle. They had previously observed a similar
pattern of defects causing insulin resistance in human adipocytes. They
proposed that human insulin resistance involves a defect in GLUT4
traffic and targeting leading to accumulation in a dense membrane
compartment from which insulin is unable to recruit GLUT4 to the cell
surface.

The stimulation of glucose uptake by insulin in muscle and adipose
tissue requires translocation of the GLUT4 glucose transporter from
intracellular storage sites to the cell surface. Activation of
phosphatidylinositol-3-OH kinase (PI3K; see 601232) is required for this
trafficking event, but it is not sufficient to produce GLUT4
translocation. Ribon et al. (1998) and Baumann et al. (2000) described a
pathway involving the insulin-stimulated tyrosine phosphorylation of CBL
(165360), which is recruited to the insulin receptor (147670) by the
adaptor protein CAP (605264). On phosphorylation, CBL is translocated to
lipid rafts. Blocking this step completely inhibits the stimulation of
GLUT4 translocation by insulin. Chiang et al. (2001) showed that
phosphorylated CBL recruits the CRK2-C3G (164762, 600303) complex to
lipid rafts, where C3G specifically activates the small GTP-binding
protein TC10 (605857). This process is independent of PI3K, but requires
the translocation of CBL, CRK, and C3G to the lipid raft. The activation
of TC10 is essential for insulin-stimulated glucose uptake and GLUT4
translocation. The TC10 pathway functions in parallel with PI3K to
stimulate fully GLUT4 translocation in response to insulin.

Insulin stimulates glucose uptake in muscle and adipocytes by signaling
the translocation of GLUT4 glucose transporters from intracellular
membranes to the cell surface. The translocation of GLUT4 may involve
signaling pathways that are both independent of and dependent on PI3K.
This translocation also requires the actin cytoskeleton, and the rapid
movement of GLUT4 along linear tracks may be mediated by molecular
motors. Bose et al. (2002) reported that the unconventional myosin MYO1C
(606538) is present in GLUT4-containing vesicles purified from 3T3-L1
adipocytes. MYO1C, which contains a motor domain, 3 IQ motifs, and a
carboxy-terminal cargo domain, is highly expressed in primary and
cultured adipocytes. Insulin enhances the localization of MYO1C with
GLUT4 in cortical tubulovesicular structures associated with actin
filaments, and this colocalization is insensitive to wortmannin.
Insulin-stimulated translocation of GLUT4 to the adipocyte plasma
membrane is augmented by the expression of wildtype MYO1C and inhibited
by a dominant-negative cargo domain of MYO1C. A decrease in the
expression of endogenous MYO1C mediated by small interfering RNAs
inhibited insulin-stimulated uptake of 2-deoxyglucose. Thus, Bose et al.
(2002) concluded that MYO1C functions in a PI3K-independent insulin
signaling pathway that controls the movement of intracellular
GLUT4-containing vesicles to the plasma membrane.

Inoue et al. (2003) showed that TC10 (605857) interacts with EXO70, a
component of the exocyst complex. They found that EXO70 translocates to
the plasma membrane in response to insulin through the activation of
TC10, where it assembles as a multiprotein complex that includes SEC8
(608185) and SEC6 (608186). Overexpression of an EXO70 mutant blocked
insulin-stimulated glucose uptake, but not the trafficking of GLUT4 to
the plasma membrane. This mutant did, however, block the extracellular
exposure of the GLUT4 protein. Inoue et al. (2003) concluded that the
exocyst might have a crucial role in targeting the GLUT4 vesicle to the
plasma membrane, perhaps directing the vesicle to the precise site of
fusion.

In the absence of insulin (176730), GLUT4 is sequestered intracellularly
and is redistributed to the plasma membrane within minutes of insulin
stimulation. Bogan et al. (2003) described a functional screen to
identify proteins that modulate GLUT4 distribution, and identified TUG
(606236) as a putative tether, containing a UBX domain, for GLUT4. In
truncated form, TUG acts in a dominant-negative manner to inhibit
insulin-stimulated GLUT4 redistribution in Chinese hamster ovary cells
and 3T3-L1 adipocytes. Full-length TUG forms a complex specifically with
GLUT4; in 3T3-L1 adipocytes, this complex is present in unstimulated
cells and is largely disassembled by insulin. Endogenous TUG is
localized with the insulin-mobilizable pool of GLUT4 in unstimulated
3T3-L1 adipocytes, and is not mobilized to the plasma membrane by
insulin. Distinct regions of TUG are required to bind GLUT4 and to
retain GLUT4 intracellularly in transfected, nonadipose cells. Bogan et
al. (2003) concluded that TUG traps endocytosed GLUT4 and tethers it
intracellularly, and that insulin mobilizes this pool of retained GLUT4
by releasing this tether.

Oshel et al. (2000) identified a region in the 5-prime UTR of GLUT4,
designated domain I, that was required for full GLUT4 promoter function.
By yeast 1-hybrid analysis, DNase footprint analysis, and
electrophoretic mobility shift assays, they demonstrated that GEF
(SLC2A4RG; 609493) specifically bound domain I of the GLUT4 promoter.
GEF cooperated with MEF2 (see MEF2A; 600660), which has its own binding
site, to regulate GLUT4 expression in transgenic animals.

By assaying reporter gene activity in transfected COS-7 cells, Knight et
al. (2003) found that GEF, MEF2A, and MEF2D (600663) had weak activity
individually in transactivating the GLUT4 promoter, but cotransfection
of GEF and MEF2A showed significantly greater activity. Cotransfection
of GEF and MEF2D or MEF2C (600662) did not increase GLUT4 promoter
function. Coimmunoprecipitation assays indicated that GEF bound both
MEF2A and MEF2D in vitro, and MEF2D interfered with the transcriptional
activation promoted by the cooperative interaction of MEF2A and GEF.

Intracellular trafficking of the glucose transporter GLUT4 from storage
compartments to the plasma membrane is triggered in muscle and fat
during the body's response to insulin. Clathrin is involved in
intracellular trafficking, and in humans, the clathrin heavy-chain
isoform CHC22 (601273) is highly expressed in skeletal muscle.
Vassilopoulos et al. (2009) found a role for CHC22 in the formation of
insulin-responsive GLUT4 compartments in human muscle and adipocytes.
CHC22 also associated with expanded GLUT4 compartments in muscle from
type 2 diabetic patients. Tissue-specific introduction of CHC22 in mice,
which have only a pseudogene for this protein, caused aberrant
localization of GLUT4 transport pathway components in their muscle, as
well as features of diabetes. Thus, Vassilopoulos et al. (2009)
concluded that CHC22-dependent membrane trafficking constitutes a
species-restricted pathway in human muscle and fat with potential
implications for type 2 diabetes.

Herman et al. (2012) reported that adipose tissue GLUT4 regulates the
expression of carbohydrate-responsive element-binding protein (CHREBP,
also known as MLXIPL; 605678), a transcriptional regulator of lipogenic
and glycolytic genes. Furthermore, adipose CHREBP is a major determinant
of adipose tissue fatty acid synthesis and systemic insulin sensitivity.
Herman et al. (2012) found a new mechanism for glucose regulation of
CHREBP: glucose-mediated activation of the canonical CHREBP isoform
(CHREBP-alpha) induces expression of a novel, potent isoform
(CHREBP-beta) that is transcribed from an alternative promoter.
CHREBP-beta expression in human adipose tissue predicts insulin
sensitivity.

GENE STRUCTURE

Bell et al. (1990) determined that the GLUT4 gene spans a region of
8,000 bp and is contains 11 exons.

MAPPING

By hybridization of cDNA probes to a panel of somatic cell hybrids and
by in situ hybridization, Fan et al. (1989) showed that the
insulin-responsive glucose transporter gene maps to 17p13.

MOLECULAR GENETICS

The description of cDNA clones encoding GLUT4 and a KpnI RFLP associated
with this locus were reported by Bell et al. (1989). Muraoka et al.
(1991) found a RFLP in Japanese. Unlike GLUT1 (138140), GLUT4
polymorphic markers showed no association with noninsulin-dependent
diabetes mellitus (Baroni et al., 1992).

In a patient with noninsulin-dependent diabetes mellitus (125853),
Kusari et al. (1991) identified a val383-to-ile mutation (138190.0001)
caused by a GTC-to-ATC substitution in the GLUT4 gene.

ANIMAL MODEL

Ikemoto et al. (1995) found that transgenic mice harboring the entire
GLUT4 gene, as well as 7 kb of 5-flanking and 1 kb of 3-flanking
sequence, expressed 2 or more times the normal level of GLUT4 mRNA and
protein in skeletal muscle and adipose tissue. This modest
tissue-specific increase in GLUT4 expression led to an unexpectedly
rapid blood glucose clearance rate following oral glucose
administration. In nontransgenic animals, exercise caused a 1.5-fold
increase in expression of GLUT4 mRNA and protein, as well as a
significant improvement of glycemic control. In transgenic animals
harboring the minigene, exercise increased expression of GLUT4 mRNA and
protein derived from the transgene and endogenous gene and led to a
further improvement of glycemic control. The findings were interpreted
as indicating that GLUT4 plays a pivotal role in glucose homeostasis in
vivo.

Katz et al. (1995) disrupted the Glut4 gene in 'knockout' mice and found
that, surprisingly, the Glut4-null mice had nearly normal glycemia but
that Glut4 was absolutely essential for sustained growth, normal
cellular glucose and fat metabolism, and expected longevity. They
observed increased expression of other glucose transporters in the liver
(Glut2) and heart (Glut1) but not in skeletal muscle. Insulin tolerance
tests indicated that these mice were less sensitive to insulin action.

Glucose enters the heart via GLUT1 and GLUT4 glucose transporters.
GLUT4-deficient mice develop striking cardiac hypertrophy and die
prematurely, but it was unclear whether their cardiac changes were
caused primarily by GLUT4 deficiency in cardiomyocytes or by metabolic
changes resulting from the absence of GLUT4 in skeletal muscle and
adipose tissue. To determine the role of GLUT4 in the heart, Abel et al.
(1999) used Cre-loxP recombination to generate mice in which GLUT4
expression was abolished in the heart but present in skeletal muscle and
adipose tissue. Life span and serum concentrations of insulin, glucose,
free fatty acids, lactate, and beta-hydroxybutyrate were normal. Basal
cardiac glucose transport and GLUT1 expression were both increased
approximately 3-fold in homozygous deficient mice, but
insulin-stimulated glucose uptake was abolished. Homozygous deficient
mice developed modest cardiac hypertrophy associated with increased
myocyte size and induction of atrial natriuretic and brain natriuretic
peptide gene expression in the ventricles. Myocardial fibrosis did not
occur. Basal and isoproterenol-stimulated isovolumic contractile
performance was preserved. Thus, selective ablation of GLUT4 in the
heart initiated a series of events that resulted in compensated cardiac
hypertrophy.

To determine the role of adipose GLUT4 in glucose homeostasis, Abel et
al. (2001) used Cre/loxP DNA recombination to generate mice with
adipose-selective reduction of GLUT4 (G4A -/-). G4A -/- mice had normal
growth and adipose mass despite markedly impaired insulin-stimulated
glucose uptake in adipocytes. Although GLUT4 expression is preserved in
muscle, these mice developed insulin resistance in muscle and liver,
manifested by decreased biologic responses and impaired activation of
phosphatidylinositol-3-OH kinase (PI3K; see 601232). G4A -/- mice
developed glucose intolerance and hyperinsulinemia. Thus, downregulation
of GLUT4 and glucose transport selectively in adipose tissue can cause
insulin resistance and thereby increase the risk of developing diabetes.
In G4A -/- mice, mean plasma leptin levels were normal and plasma leptin
concentrations showed the same linear relationship with body weight in
G4A -/- mice as in control littermates. Thus, normal glucose uptake in
adipocytes is not necessary to maintain normal plasma leptin levels.
Elevated TNF-alpha (191160) was noted in G4A -/- mice.

Zisman et al. (2000) generated mice with selective disruption of GLUT4
in muscle. A profound reduction in basal glucose transport and
near-absence of stimulation by insulin or contraction resulted. The mice
showed severe insulin resistance and glucose intolerance from an early
age. Thus, GLUT4-mediated glucose transport in muscle is essential to
the maintenance of normal glucose homeostasis.

Kim et al. (2001) found that Glut4 knockout mice had a 92% decrease in
insulin-stimulated glucose uptake in skeletal muscle as well as a
decrease in insulin-induced glucose uptake in adipose tissue compared to
controls. Hepatic glucose production was also decreased in the mutant
mice. Whole body glucose uptake was decreased by 55%, indicating severe
insulin resistance. The authors concluded that a primary defect in
muscle glucose transport can lead to secondary defects in insulin action
in adipose tissue and liver due to glucose toxicity; the secondary
defects likely contribute to insulin resistance and the development of
diabetes.

To clarify the physiologic function of STXBP3 (608339) in
insulin-stimulated GLUT4 exocytosis, Kanda et al. (2005) generated mouse
embryos deficient in the syntaxin-4 (see 186591)-binding protein Stxbp3
and developed Stxbp3 -/- adipocytes from their mesenchymal fibroblasts.
The insulin-induced appearance of Glut4 at the cell surface was enhanced
in Stxbp3 -/- adipocytes compared to +/+ cells. Wortmannin, an inhibitor
of PI3K, inhibited insulin-stimulated Glut4 externalization in +/+ but
not -/- adipocytes. Kanda et al. (2005) suggested that disruption of the
interaction between syntaxin-4 and STXBP3 in adipocytes might result in
enhancement of insulin-stimulated GLUT4 externalization.

*FIELD* AV
.0001
DIABETES MELLITUS, NONINSULIN-DEPENDENT
SLC2A4, VAL383ILE

Kusari et al. (1991) sequenced the entire coding region of the GLUT4
gene in 6 NIDDM (125853) patients. One patient was heterozygous for a
mutation in which isoleucine (ATC) was substituted for valine (GTC) at
position 383. Subsequently, the GLUT4 sequence at position 383 was
determined in 24 additional NIDDM patients and 30 nondiabetic controls
and all showed only the normal sequence. Although they concluded that
the great majority of patients with NIDDM do not have genetic variation
in the coding sequence of GLUT4, a subpopulation of patients may have
variation in the gene which is responsible for insulin resistance.

*FIELD* RF
1. Abel, E. D.; Kaulbach, H. C.; Tian, R.; Hopkins, J. C. A.; Duffy,
J.; Doetschman, T.; Minnemann, T.; Boers, M.-E.; Hadro, E.; Oberste-Berghaus,
C.; Quist, W.; Lowell, B. B.; Ingwall, J. S.; Kahn, B. B.: Cardiac
hypertrophy with preserved contractile function after selective deletion
of GLUT4 from the heart. J. Clin. Invest. 104: 1703-1714, 1999.

2. Abel, E. D.; Peroni, O.; Kim, J. K.; Kim, Y.-B.; Boss, O.; Hadro,
E.; Minnemann, T.; Shulman, G. I.; Kahn, B. B.: Adipose-selective
targeting of the GLUT4 gene impairs insulin action in muscle and liver. Nature 409:
729-733, 2001.

3. Baroni, M. G.; Oelbaum, R. S.; Pozzilli, P.; Stocks, J.; Li, S.-R.;
Fiore, V.; Galton, D. J.: Polymorphisms at the GLUT1 (HepG2) and
GLUT4 (muscle/adipocyte) glucose transporter genes and non-insulin-dependent
diabetes mellitus (NIDDM). Hum. Genet. 88: 557-561, 1992.

4. Baumann, C. A.; Ribon, V.; Kanzaki, M.; Thurmond, D. C.; Mora,
S.; Shigematsu, S.; Bickel, P. E.; Pessin, J. E.; Saltiel, A. R.:
CAP defines a second signalling pathway required for insulin-stimulated
glucose transport. Nature 407: 202-207, 2000.

5. Bell, G. I.; Kayano, T.; Buse, J. B.; Burant, C. F.; Takeda, J.;
Lin, D.; Fukumoto, H.; Seino, S.: Molecular biology of mammalian
glucose transporters. Diabetes Care 13: 198-208, 1990.

6. Bell, G. I.; Murray, J. C.; Nakamura, Y.; Kayano, T.; Eddy, R.
L.; Fan, Y.-S.; Byers, M. G.; Shows, T. B.: Polymorphic human insulin-responsive
glucose-transporter gene on chromosome 17p13. Diabetes 38: 1072-1075,
1989.

7. Birnbaum, M. J.: Identification of a novel gene encoding an insulin-responsive
glucose transporter protein. Cell 57: 305-315, 1989.

8. Bogan, J. S.; Hendon, N.; McKee, A. E.; Tsao, T.-S.; Lodish, H.
F.: Functional cloning of TUG as a regulator of GLUT4 glucose transporter
trafficking. Nature 425: 727-733, 2003.

9. Bose, A.; Guilherme, A.; Robida, S. I.; Nicoloro, S. M. C.; Zhou,
Q. L.; Jiang, Z. Y.; Pomerleau, D. P.; Czech, M. P.: Glucose transporter
recycling in response to insulin is facilitated by myosin Myo1c. Nature 420:
821-824, 2002.

10. Chiang, S.-H.; Baumann, C. A.; Kanzaki, M.; Thurmond, D. C.; Watson,
R. T.; Neudauer, C. L.; Macara, I. G.; Pessin, J. E.; Saltiel, A.
R.: Insulin-stimulated GLUT4 translocation requires the CAP-dependent
activation of TC10. Nature 410: 944-948, 2001.

11. Fan, Y.-S.; Eddy, R. L.; Byers, M. G.; Haley, L. L.; Henry, W.
M.; Kayano, T.; Shows, T. B.; Bell, G. I.: Assignment of genes encoding
three human glucose transporter/transporter-like proteins (GLUT4,
GLUT5 and GLUT6) to chromosomes 17, 1 and 5, respectively. (Abstract) Cytogenet.
Cell Genet. 51: 997 only, 1989.

12. Garvey, W. T.; Maianu, L.; Zhu, J.-H.; Brechtel-Hook, G.; Wallace,
P.; Baron, A. D.: Evidence for defects in the trafficking and translocation
of GLUT4 glucose transporters in skeletal muscle as a cause of human
insulin resistance. J. Clin. Invest. 101: 2377-2386, 1998.

13. Herman, M. A.; Peroni, O. D.; Villoria, J.; Schon, M. R.; Abumrad,
N. A.; Bluher, M.; Klein, S.; Kahn, B. B.: A novel ChREBP isoform
in adipose tissue regulates systemic glucose metabolism. Nature 484:
333-338, 2012.

14. Ikemoto, S.; Thompson, K. S.; Itakura, H.; Lane, M. D.; Ezaki,
O.: Expression of an insulin-responsive glucose transporter (GLUT4)
minigene in transgenic mice: effect of exercise and role in glucose
homeostasis. Proc. Nat. Acad. Sci. 92: 865-869, 1995.

15. Inoue, M.; Chang, L.; Hwang, J.; Chiang, S.-H.; Saltiel, A. R.
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16. Kanda, H.; Tamori, Y.; Shinoda, H.; Yoshikawa, M.; Sakaue, M.;
Udagawa, J.; Otani, H.; Tashiro, F.; Miyazaki, J.; Kasuga, M.: Adipocytes
from Munc18c-null mice show increased sensitivity to insulin-stimulated
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17. Katz, E. B.; Stenbit, A. E.; Hatton, K.; DePinho, R.; Charron,
M. J.: Cardiac and adipose tissue abnormalities but not diabetes
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18. Kim, J. K.; Zisman, A.; Fillmore, J. J.; Peroni, O. D.; Kotani,
K.; Perret, P.; Zong, H.; Dong, J.; Kahn, C. R.; Kahn, B. B.; Shulman,
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2001.

19. Knight, J. B.; Eyster, C. A.; Griesel, B. A.; Olson, A. L.: Regulation
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20. Kusari, J.; Verma, U. S.; Buse, J. B.; Henry, R. R.; Olefsky,
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21. Muraoka, A.; Sakura, H.; Kim, K.; Kishimoto, M.; Akanuma, Y.;
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22. Oshel, K. M.; Knight, J. B.; Cao, K. T.; Thai, M. V.; Olson, A.
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25. Zisman, A.; Peroni, O. D.; Abel, E. D.; Michael, M. D.; Mauvais-Jarvis,
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*FIELD* CN
Ada Hamosh - updated: 5/8/2012
Ada Hamosh - updated: 6/16/2009
Patricia A. Hartz - updated: 7/25/2005
Marla J. F. O'Neill - updated: 4/12/2005
Cassandra L. Kniffin - updated: 11/11/2004
Ada Hamosh - updated: 10/29/2003
Ada Hamosh - updated: 8/12/2003
Ada Hamosh - updated: 2/5/2003
Ada Hamosh - updated: 4/16/2001
Victor A. McKusick - updated: 2/26/2001
Ada Hamosh - updated: 2/5/2001
Victor A. McKusick - updated: 1/21/2000
Victor A. McKusick - updated: 6/26/1998

*FIELD* CD
Victor A. McKusick: 6/1/1989

*FIELD* ED
alopez: 05/08/2012
terry: 5/8/2012
alopez: 6/22/2009
terry: 6/16/2009
carol: 10/11/2006
mgross: 7/25/2005
tkritzer: 4/12/2005
ckniffin: 11/11/2004
carol: 2/18/2004
alopez: 10/29/2003
terry: 10/29/2003
mgross: 10/28/2003
mgross: 8/13/2003
terry: 8/12/2003
alopez: 2/6/2003
terry: 2/5/2003
carol: 3/8/2002
terry: 3/8/2002
alopez: 4/18/2001
terry: 4/16/2001
mcapotos: 3/5/2001
terry: 2/26/2001
alopez: 2/7/2001
terry: 2/5/2001
carol: 2/3/2000
carol: 2/2/2000
mcapotos: 2/2/2000
mcapotos: 2/1/2000
terry: 1/21/2000
carol: 6/30/1998
terry: 6/26/1998
alopez: 6/4/1997
mark: 2/23/1997
terry: 10/30/1995
mark: 9/13/1995
carol: 2/15/1995
davew: 6/28/1994
warfield: 4/20/1994
carol: 6/3/1992