chronic diabetic complications -...

Department of MedicineUniversity of Helsinki

Finland

CHRONIC DIABETIC COMPLICATIONS INCLINICALLY, IMMUNOLOGICALLY AND

GENETICALLY DEFINED SUBGROUPS

Bo Isomaa

ACADEMIC DISSERTATION

To be presented for public examination with the permission of the Medical Facultyof the University of Helsinki in the Auditorium 2 of the Meilahti Hospital on

September 28th, 2001, at 12 noon.

Helsinki 2001

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Supervisors Leif Groop, MDProfessorDepartment of EndocrinologyUniversity Hospital MASLund UniversityMalmö, Sweden

and

Marja-Riitta Taskinen, MDProfessorDepartment of MedicineDivision of CardiologyUniversity of HelsinkiHelsinki, Finland

Reviewers Markku Laakso, MDProfessorDepartment of MedicineUniversity of KuopioKuopio, Finland

and

Paula Summanen, MDDocentDepartment of OphthalmologyUniversity of HelsinkiHelsinki, Finland

Opponent Carl-David Agardh, MDProfessorDepartment of EndocrinologyUniversity Hospital MASLund UniversityMalmö, Sweden

Cover drawing (Malmska Hospital, Jakobstad) by Henrik Tikkanen.

ISBN 952-91-3737-0ISBN 952-10-0103-8 (PDF version http://ethesis.helsinki.fi)

YliopistopainoHelsinki 2001

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“Det finns vissa saker som är absoluta, till exempel havsströmmar och årstideroch att solen går upp om mornarna. Och att fyrarna brinner.”

Tove Jansson“Pappan och havet”

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Contents

List of original publications .................................................................................. 6

Abbreviations ......................................................................................................... 7

Introduction ........................................................................................................... 8

Review of the literature ......................................................................................... 9

1. Subclassification of diabetes ......................................................................................................... 91.1. Towards a classification ................................................................................................ 91.2. The new classification ................................................................................................ 101.3. Autoimmunity in diabetes .......................................................................................... 101.4. Type 2 diabetes and the metabolic syndrome ............................................................. 111.5. Maturity-onset diabetes in the young (MODY) ......................................................... 12

2. Chronic diabetic complications .................................................................................................. 132.1. Pathogenesis of diabetic complications ...................................................................... 132.2. Retinopathy ................................................................................................................. 152.3. Nephropathy ............................................................................................................... 172.4. Neuropathy.................................................................................................................. 202.5. Cardiovascular disease ............................................................................................... 22

Aims of the study ................................................................................................. 26

Study design and subjects ................................................................................... 27

1. Chronic diabetic complications in patients with MODY3 diabetes (I). .................................... 27 2. Chronic complications in patients with slowly progressing autoimmune type 1 diabetes (LADA) (II). ................................................................................................................ 27 3. Cardiovascular morbidity and mortality associated with the metabolic syndrome (III). .......... 27 4. Chronic diabetic complications in patients with and without the metabolic syndrome (IV) ............................................................................................................................. 28

Methods ................................................................................................................ 29

1. Assessment of diabetic complications ........................................................................................ 29 2. Assessment of mortality .............................................................................................................. 31 3. Assessment of glucose tolerance ................................................................................................. 31 4. Measurements ............................................................................................................................. 31

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5. Assays .......................................................................................................................................... 31 6. Statistical analysis ....................................................................................................................... 32

Results ................................................................................................................... 34

1. Complications in in patients with MODY3 diabetes (I). ............................................................ 342. Complications in patients with slowly progressing autoimmune type 1 diabetes (LADA) (II). ................................................................................................................................ 363. Cardiovascular morbidity and mortality associated with the metabolic syndrome (III). ............................................................................................................................ 364. Complications in patients with the metabolic syndrome (IV). ................................................... 38

Discussion ............................................................................................................. 40

1. Subjects and methods ................................................................................................................... 401.1. Subjects ....................................................................................................................... 401.2. Methods ...................................................................................................................... 40

2. Complications in diabetic subgroups ........................................................................................... 422.1. Retinopathy ................................................................................................................. 422.2. Micro- and macroalbuminuria ................................................................................... 422.3. Neuropathy.................................................................................................................. 432.4. Cardiovascular disease ............................................................................................... 44

3. Cardiovascular risk and the metabolic syndrome........................................................................ 45

Summary and conclusions .................................................................................. 48

Acknowledgements .............................................................................................. 49

References ............................................................................................................. 51

Original publications ........................................................................................... 67

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List of original publications

This thesis is based on the following original publications, which will be referred to in the text bytheir Roman numerals:

I. Isomaa B, Henricsson M, Lehto M, Forsblom C, Karanko S, Sarelin L, Häggblom M,Groop L: Chronic complications in patients with MODY3 diabetes. Diabetologia 41: 467-473, 1998

II. Isomaa B, Almgren P, Henricsson M, Taskinen M-R, Tuomi T, Groop L, Sarelin L:Chronic complications in patients with slowly progressing autoimmune type 1 diabetes(LADA). Diabetes Care 22:1347-1353, 1999

III. Isomaa B, Almgren P, Tuomi T, Forsén B, Lahti K, Nissén M, Taskinen M-R, Groop L:Cardiovascular morbidity and mortality associated with the metabolic syndrome. DiabetesCare 24:683-689, 2001

IV. Isomaa B, Henricsson M, Almgren P, Tuomi T, Taskinen M-R, Groop L: The metabolicsyndrome influences the risk of chronic complications in patients with type 2 diabetes.(Accepted for Diabetologia)

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Abbreviations

ABI Ankle-brachial indexACR Albumin-to-creatinine ratioAER Albumin excretion rateAGE Advanced glycation end productBMI Body mass indexCHD Coronary heart diseaseCI Confidence intervalsCV Coefficient of variationCVD Cardiovascular diseaseDCCT The Diabetes Control and Complications TrialDR Diabetic retinopathyECG ElectrocardiogramESRD End-stage renal diseaseGADA Antibody to glutamic acid decarboxylaseGDM Gestational diabetes mellitusHDL High-density lipoproteinHOMA Homeostasis model assessmentIDDM Insulin-dependent diabetes mellitusIFG Impaired fasting glucoseIGT Impaired glucose toleranceLADA Latent autoimmune diabetes in adultsLDL Low-density lipoproteinMODY Maturity-onset diabetes in the youngMSDR+ Patients with the metabolic syndromeMSDR- Patients without the metabolic syndromeNGT Normal glucose toleranceNIDDM Non-insulin-dependent diabetes mellitusNPDR Non-proliferative diabetic retinopathyOGTT Oral glucose tolerance testPAI-1 Plasminogen activator inhibitor-1PDR Proliferative diabetic retinopathyPKC Protein kinase CRR Relative riskUKPDS United Kingdom Prospective Diabetes StudyVLDL Very-low-density lipoproteinWHO World Health OrganizationWHR Waist-to-hip ratio

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Introduction

The prevalence of diabetes shows great vari-ations in different populations. An epidemic ofnon-insulin-dependent diabetes mellitus (type 2diabetes) is occurring across the world, particu-larly affecting developing countries and migrantsto westernised societies. The number of personswith type 2 diabetes is expected to rise to morethan 200 million world-wide in the next 10 years(WHO Study Group 1994).

Diabetes has traditionally been divided intoinsulin-dependent (type 1) and non-insulin-de-pendent (type 2) diabetes. Our knowledge aboutthe causes of diabetes, especially the role ofautoimmunity and genetics, has increased sig-nificantly since the classification of diabetes in1985 (WHO 1985). It has also become evidentthat the old classification is too simple and thatdiabetes is a much more heterogeneous disorderthan thought thus far. Therefore a WHO consul-tation group proposed a new classification of dia-betes in 1998 (Alberti and Zimmet 1998) andintroduced some new subgroups. About 10 % ofpersons with adult onset diabetes have a slowlyprogressing form of type 1 diabetes, also calledLADA (latent autoimmmune diabetes in adults)(Tuomi et al.1993). Specific genetic defects asdifferent forms of MODY (maturity-onset dia-betes in the young) and diabetes associated withmutations in mitochondrial DNA may accountfor about 5 % of all cases of diabetes (Hattersley1998). A majority of patients with type 2 diabe-tes has features of the metabolic syndrome, whichincreases the risk of cardiovascular disease andpremature death (Reaven 1988). There is alsosupport for an interaction between type 1 and

type 2 diabetes with impact on the phenotype ofdiabetes (Dahlqvist et al. 1989, Li et al. 1998).

Since the introduction of insulin in the 1920s,which made survival possible for patients withinsulin-dependent diabetes, the long-term com-plications of diabetes, i.e. retinopathy, nephropa-thy, neuropathy and cardiovascular disease, havebecome the major health problem for the patientswith type 1 diabetes. In patients with type 2 dia-betes cardiovascular complications are commonand determine prognosis. In the industrialisedworld diabetes is nowadays the most commoncause of severely impaired vision in people be-low 65 years of age (Trautner et al. 1997) andthe most important cause of renal failure (Markellet al.1992; Finnish Registry for Kidney Disease1998). Diabetic neuropathy and the diabetic footare examples of diabetes-related problems withgreat impact on health care costs and are oftenassociated with great disability and suffering forthe patient (Apelqvist et al. 1994).

Most studies on diabetic complications haveassumed that adult-onset diabetes is a more orless homogeneous disease. We know now thatthis is not the case. The question thus ariseswhether it is possible to identify specific risk fac-tors in subgroups of diabetes, which in additionto hyperglycaemia increase the risk for chronicdiabetic complications and are some diabetic sub-groups protected from the expected long-termcomplications? This study was initiated to an-swer these questions and to clinically character-ise diabetic subgroups.

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Review of the literature

1. Subclassification of diabetes

1.1. Towards a classification of diabe-tes

Diabetes mellitus has been known for over2000 years. Already from the earliest descrip-tions, it was evident that diabetes was not a sin-gle disorder. Indian descriptions from about 600BC distinguish two forms of diabetes; one af-fecting older, fatter people and the other affect-ing thin people, who did not survive long. How-

ever, most descriptions in the ancient literaturerelate to what is now recognised as insulin-de-pendent diabetes (MacFarlane et al. 1997).

The successful use of insulin in rescuingyoung patients supported the view that older pa-tients could develop diabetes, but did not requireinsulin for survival. In 1936, Himsworth pro-posed that there are at least two distinct clinicaltypes of diabetes: an insulin-sensitive and an in-sulin-insensitive type (Himsworth 1936). Thisobservation was confirmed after the developmentof a bioassay for insulin in blood (Bornstein etal. 1951). Thereafter diabetes was generally clas-sified as “juvenile-onset”, insulin-dependent or

Table 1: Aetiological classification of diabetes (WHO 1998) Classification I. Type I (Beta cell destruction, usually leading to absolute

insulin deficiency) A. Autoimmune

1. Slowly progressive (LADA) 2. Rapidly progressive

B. Idiopathic II. Type II (May range from predominantly insulin resistance

with relative insulin deficiency to a predominantly secretory defect with or without insulin resistance)

III. Other specific types A. Genetic defects of the beta cell function

(MODY, mitochondrial DNA) B. Genetic defects in insulin action

(type A insulin resistance etc) C. Diseases of the exocrine pancreas

(pancreatitis, hemocromatosis etc.) D. Endocrinopathies

(Cushings syndrome, acromegaly etc) E. Drug- or chemical induced F. Infections G. Uncommon forms of immune -mediated diabetes

(antibodies to insulin , anti-insulin receptor antibodies etc) H. Other genetic syndromes sometimes associated with diabetes IV. Gestational hyperglycemia

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“maturity-onset”, non-insulin-dependent diabe-tes.

The US National Diabetes Data Group(NDDG) presented a working classification in1979 in which insulin-dependent (IDDM) dia-betes was separated from obese and non-obeseforms of non-insulin-dependent (NIDDM) dia-betes. Different forms of secondary diabetesmellitus, impaired glucose tolerance (IGT) andgestational diabetes (GDM) were also defined(National Diabetes Data Group 1979). TheNDDG classification has been revised by WHOin 1980 (WHO 1980) and 1985 (WHO 1985).

1.2. The new classification of diabetes(WHO 1998)

Our knowledge about the causes of diabetes,especially regarding the role of autoimmunity andgenetics in the pathogenesis of diabetes, has in-creased markedly since 1985 (WHO 1985). Itbecame evident that the old classification is toosimple and that diabetes is a much more hetero-geneous disorder than thought thus far (Beck-Nielsen et al.1994; Zimmet 1995). In 1998 aWHO consultation group (Alberti et al.1998)proposed a new classification of diabetes (Table1). In addition to the etiological classification,the proposal introduces three clinical stages: non-insulin requiring, insulin requiring for controland insulin requiring for survival.

1.3. Autoimmunity in diabetes - Type1 diabetes and LADA

The demonstration of insulitis; i.e.lymphocythic infiltration of the islets of Langer-hans in pancreata from recent juvenile-onset dia-betic patients indicated that autoimmunity is in-volved in the pathogenesis of this type of diabe-tes (Gepts 1965). The subsequent detection ofantibodies directed against islet cells, islet cellantibodies (ICA), suggested an immune reactiondirected towards the islet cells themselves(Bottazzo et al. 1974). Later on antibodies toother structures of the islets have been detected;

islet cell surface antibodies (ICSA) (Lernmarket al. 1978), insulin autoantibodies (IAA) (Palmeret al. 1983) and antibodies against glutamic aciddecarboxylase (GADA) (Baekkeskov et al.1987). ICA and GADA are markers ofautoimmune β-cell destruction and detected inthe majority of type 1 diabetic patients at the onsetof the disease (Groop et al. 1986; Landin-Olssonet al. 1992; Tuomi et al. 1993).

A subgroup of patients with adult-onset dia-betes has ICA and more often GADA. Severalstudies have shown that positivity for ICA orGADA is associated with relative insulin defi-ciency (Irwine et al. 1977; Groop et al. 1986;Groop et al. 1988; Landin-Olsson et al. 1990;Tuomi et al. 1993; Zimmet et al. 1994). Within10 years 50 % of newly diagnosed GADA-posi-tive patients developed relative insulin deficiency,defined as glucagon-stimulated C-peptide con-centration <0.7 nmol/l, compared to 3 % ofGADA-negative patients (Niskanen et al. 1995).Therefore, a proportion of adults who presentwith type 2 diabetes seems to have a slowly pro-gressing autoimmune type of diabetes also calledLADA (latent autoimmune diabetes in adults).

Epidemiological data demonstrate thatLADA accounts for about 10% of all cases withdiabetes thereby making it almost as common asrapidly progressing type 1 diabetes (Turner etal. 1997; Tuomi et al. 1999). The clinical char-acteristics of patients with slowly progressingtype 1 diabetes (LADA) are seen in Table 2.

Table 2: Clinical features of slowly progressing autoimmune type 1 diabetes (LADA).

Age at onset usually > 35 years

Clinical presentation as non-obese type 2 diabetes

Initial control with diet or oral agents

Progressive deterioration of insulin secretion

Positive markers of autoimmunity to the beta-cell

Subclassification of diabetes

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1.4. Type 2 diabetes and the meta-bolic syndrome

Type 2 diabetes is the most common form ofdiabetes and also responsible for the explosiveincrease in diabetes prevalence in many parts ofthe world (King et al. 1993). The prevalence oftype 2 diabetes shows great variations in differ-ent populations. In a Finnish study from theBotnia region 85% of the diabetic patients werediagnosed with type 2 diabetes, with a prevalenceof diabetes in subjects over 30 years of 3.9%(Eriksson et al. 1992). In some ethnic groups suchas Pima Indians and Nauruans the prevalence ofdiabetes in the adult population is much higher,about 50 % (King et al. 1993).

Type 2 diabetes is a heterogeneous diseasewhere both impaired β-cell function and insulinresistance contribute to the manifestation of thedisease (Beck-Nielsen et al. 1994). Epidemiologi-cal studies provide evidence that the development

of type 2 diabetes is influenced both by adverseenvironmental (lifestyle) factors and genetic sus-ceptibility. Familial clustering of insulin resist-ance and insulin deficiency suggests that thesedefects are most likely genetically determined(Groop et al. 1996a, Vauhkonen et al. 1998).

A majority of patients with type 2 diabeteshave features of the so-called metabolic syn-drome, which has also been called “SyndromeX”, the insulin resistance syndrome and thedeadly quartet (Reaven 1988; DeFronzo et al.1991; Kaplan 1989). “Syndrome X” was re-in-troduced in 1988 by Gerald Reaven, who sug-gested that insulin resistance and compensatoryhyperinsulinaemia underlie the clustering of car-diovascular risk factors like glucose intolerance,hypertension and dyslipidaemia (Reaven 1988).The syndrome is, however, much older, alreadyin 1923 Kylin described the clustering of hyper-tension, hyperglycaemia and gout (Kylin 1923).Several other components have subsequently beenassociated with the syndrome, including obesity


Table 3: The definition of the metabolic syndrome (WHO 1998)

Definition of the components

A. In subjects with diabetes or IFG/IGT at least 2 of the following components:

1. Obesity high BMI (≥30 kg/m2) and/or high WHR (>0.9 in males; >0.85 in females)

2. Hypertension antihypertensive treatment and/or elevated blood pressure (>160 mmHg systolic or > 90 mmHg diastolic)

3. Dyslipidemia high triglycerides (≥1.7 mmol/l) and/or low HDL cholesterol (<0.9 mmol/l in males; <1.0 mmol/l in females)

4. Microalbuminuria AER ≥20 µg/min.

B. In subjects with NGT also a criteria of insulin resistance

glucose uptake below lowest quartile for background population under investigation

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and especially abdominal obesity (Björntorp1994), microalbuminuria (Groop et al. 1993;Mykkänen et al. 1998), abnormalities in fibri-nolysis and coagulation (Yudkin 1999) andhyperuricemia (Modan et al. 1987; Vuorinen-Markkola et al. 1992). The name insulin resist-ance syndrome has been widely used and refersto insulin resistance as a common denominatorof the syndrome (Modan et al. 1985; DeFronzoet al. 1991; Haffner et al. 1992).

The prevalence of the metabolic syndrome hasvaried markedly between different studies, mostlikely because of the lack of accepted criteria forthe definition of the syndrome (Bonora et al.1998; Rantala et al. 1999). In 1998 WHO pro-posed a unifying definition for the syndrome andchose to call it the metabolic syndrome, ratherthan the insulin resistance syndrome (Alberti etal.1998). The reason was mainly that it was notconsidered established that insulin resistance isthe cause of all the components of the syndrome.The WHO proposal for definition of the meta-bolic syndrome is shown in Table 3.

1.5. Maturity-onset diabetes of theyoung

A mild form of diabetes in young people wasreported already in the pre-insulin era (Joslin1916; Graham 1921). After the introduction ofsulfonylureas in the 1950s it was observed thattolbutamide could improve or normalize glucosetolerance in some young non-obese patients withmild diabetes (Fajans et al. 1962; Fajans 1973).In 1974, Tattersall reported an atypical form ofearly-onset diabetes inherited in an autosomaldominant pattern in three families (Tattersall1974). The patients did not develop ketoacido-sis, and diabetic complications were absent ormild despite of a long duration of diabetes. Thepatients were considered to belong to a subgroupof diabetes called maturity-onset diabetes of theyoung (MODY) (Tattersall et al. 1975). A diag-nosis of MODY was considered if diabetes hadbeen diagnosed before the age of 25 (also in 1-2members of the family), fasting hyperglycaemiahad been normalised without insulin treatmentover 2 years and the patients had a strong family


Table 4: Comparison of the most common subtypes of MODY. MODY1 MODY2 MODY3 Chromosomal location 20q 7p 12q Gene HNF4-α glucokinase HNF1-α Proportion of MODY* ~ 10 % ~ 15 % ~ 60 % Onset of hypergycemia adolescence,

early childhood

early childhood

adolescence early childhood

Severity of diabetes progressive, may be severe

mild, minor deterioration

progressive, may be severe

Pathophysiology beta-cell dysfunction

beta-cell dysfunction, impaired glucose-sensing

beta-cell dysfunction

Microvascular complications

frequent rare frequent

Modified from Hattersley AT: Diabet. Med. 15:15 -24,1998; * data from Scandinavia (Lehto et al. 1999)

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history of diabetes (often in 3 generations).In 1991, Bell et al. demonstrated linkage to

the long arm of chromosome 20 (MODY1) in alarge MODY-family, the so-called RW familyfrom Ann Arbor (Bell et al. 1991). It was lateron shown that this linkage was due to mutationsin a liver-specific transcription factor gene, thehepatocyte nuclear factor (HNF-4α) (Yamagataet al. 1996b). Soon after the demonstration oflinkage to chromosome 20, a positive linkage tothe short arm of chromosome 7 (MODY2) wasreported in some families with early-onset dia-betes (Froguel et al. 1992). This region harboursthe glucokinase gene, and mutations in this geneare responsible for MODY2 (Vionnet et al. 1992).In 1995, Vaxillaire et al. performed a genomewide scan in 12 MODY families that were notlinked to chromosome 20 or 7. In several of thesefamilies linkage to the long arm of chromosome12 (MODY3) could be observed (Vaxillaire etal. 1995). Mutations in another transcription fac-tor gene, HNF-1α, are the cause of MODY3(Yamagata et al.1996a). Mutations in the genefor insulin promoter factor 1 (IPF1), located tochromosome 13 explain MODY4 (Stoffers et al.1997a). Interestingly, pancreatic agenesis hasbeen reported in a homozygous IPF1 mutationcarrier (Stoffers et al. 1997b). Finally, mutationsin the HNF-1β gene (heterodimer with HNF-1α)are considered responsible for MODY5(Horikawa et al. 1997). Of note, this form ofMODY is also associated with severe cystic kid-ney disease or urogenital abnormalities (Iwasakiet al. 1998). Obviously, there are MODY genesnot yet detected, as there are MODY familieswithout linkage to any of the known MODYgenes (Hattersley 1998; Lehto M et al 1999b).

The exact prevalence of MODY remains un-known, but MODY is thought to account for lessthan 5 % of diabetes (Velho et al. 1998). In Scan-dinavia MODY3 seems to be the most commonform of MODY (Lehto M et al. 1999b). Patientswith MODY1 and MODY3 diabetes are usuallydiagnosed in adoloscence or early adulthood.They are characterised by a defect in insulin se-cretion, and many patients are treated with insu-lin (Lehto M et al. 1997; Hattersley 1998; Velhoet al.1998). Gestational diabetes seems to be com-

mon in MODY3 families (Lehto et al. 1997).Most patients with MODY2 are diagnosed withmild fasting hyperglycaemia in childhood or earlyadulthood and can often be managed by diet only(Velho et al. 1997). The hyperglycaemia inMODY2 patients is thought to reflect a defect inglucokinase-mediated sensing of glucose in thepancreatic β-cell (Byrne et al. 1994). Features ofthe metabolic syndrome are not characteristic forpatients with MODY (Velho and Froguel 1998).Interestingly, triglyceride concentrations weresurprisingly low in a Swedish MODY1 family(Lehto M et al. 1999a). A comparison of the mostcommon MODY subtypes can be seen in theTable 4.

Mitochondial DNA mutations: Human cellscontain hundreds to thousands of mitochondria,each containing its own DNA as a small double-stranded molecule. As the tail of the sperm, whichcontains the paternal mitochondia, is left out-side the oocyte during fertilisation, the humanmitochondrial DNA is exclusively transmittedfrom the mother. The mitochondrial DNA ishighly vulnerable to mutations. More than 100mutations are known and are associated withvarious clinical syndromes, including maternallyinherited diabetes and deafness (MIDD)(Reardon et al. 1992; Van den Ouweland etal.1992).

2. Chronic diabetic complica-tions

2.1. Pathogenesis of complications

The natural history of both type 1 and type 2diabetes is darkened by the appearance of chroniccomplications. These include such diabetes-spe-cific complications as retinopathy, nephropathyand neuropathy. These have been named micro-vascular complications, even though the causeof neuropathy seems to be more complex thanstrictly a disorder of small blood vessels.Macrovascular complications are not specific todiabetes, but the atherosclerotic process seems

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to be more pronounced in diabetic patients(Stamler et al. 1993; Koivisto et al. 1996).

Hyperglycaemia, the common feature of alltypes of diabetes, appears to cause tissue dam-age by both acute reversible changes in cellularmetabolism and cumulative, irreversible changesin macromolecules. The possible biochemicalmechanisms include activation of the polyol path-way, activation of protein kinase C (PKC), for-mation of glycation endproducts and increasedoxygen stress (Giardino et al.1997).

The polyol pathway: Through the polyolpathway, glucose is converted to sorbitol by al-dose reductase, which is the rate-limiting enzyme(Greene et al. 1987). Aldose reductase is foundin the nervous system, retina, glomerulus andthe blood vessels, i.e. in tissues, which do notrequire insulin for glucose uptake. Sorbitols andother polyols accumulate intracellularily, lead-ing to osmotic damage and swelling. Aldose re-ductase inhibitors have improved neuropathy tosome extent in diabetic patients, including im-provement in nerve fiber density and nerve con-duction velocity (Greene et al. 1999). On theother hand, no convincing results have been seenregarding nephropathy (Passariello et al. 1993;Rangathan et al. 1993) or retinopathy (SorbinilRetinopathy Trial Reasearch Group 1990).

Protein kinase C (PKC): Hyperglycaemia in-duces synthesis of diacylglycerol, which can ac-tivate PKC (Lee at al. 1989). An activation ofPKC has been implicated in many processes rel-evant to diabetic complications, including regu-lation of vascular permeability and flow, in-creased production of cytokines and increasedsynthesis of basement membranes (Giardino etal. 1997).

Advanced glycation endproducts (AGE):Hyperglycaemia leads to the formation ofglycation products through a non-enzymaticprocess in which glucose is attached to aminogroups of proteins. The early glycation productscan by rearrangement form more stable products.Those formed on collagen, DNA and other long-lived macromolecules slowly undergo furtherchemical rearrangements to form AGEs(Brownlee et al. 1984). The formation of AGEscan contribute to tissue damage in several ways,including release of growth factors, stimulationof synthesis of extracellular matrix and cellularhypertrophy and hyperplasia. In animals withexperimental diabetes administration ofaminoguanidine, an inhibitor of AGE formation,prevents development of retinopathy (Brownlee1992) and the expected rise in albuminuria(Edelstein et al. 1992) and shows improvement

Chronic diabetic complications

Figure 1. A model for pathogenesis of microvascular diabetic complications.

Repeated changes in cellular metabolism

Diabetic tissue damage

Accumulated long-term changes in macromolecules

Hyperglycaemia

Genetic susceptibility

Accelerating factors

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in nerve condition velocity (Yagihashi et al.1992). Yet we have no results from clinical tri-als.

Increased oxidative stress: Hyperglycaemiaalso leads to increased oxidative stress leadingto peroxidation of lipid membranes, proteins andDNA (Van Dam et al. 1995).

Genetic susceptibility

Despite the important impact of hyperglycae-mia on diabetic complications, other factors un-doubtedly contribute. There are patients withlongstanding hyperglycaemia without complica-tions and patients with short duration of diseasewho seem to be very prone to complications.Genetic factors have been suspected as one ex-planation for the differences in susceptibility tocomplications. Diabetic nephropathy has beenfound to aggregate in families (Borch-Johnsenet al. 1992, Fioretto et al. 1999). Ethnic differ-ences seem to exist in the occurrence of diabeticnephropathy (Nelson et al. 1988; Ballard et al.1988; Kunzelman et al. 1989; Humphrey etal.1989) and retinopathy (Haffner et al. 1988;Nelson et al. 1989). The finding of elevated urinealbumin excretion rate (AER) in non-diabeticrelatives of type 2 diabetic patients also suggestsan important role of hereditary factors for thedevelopment of albuminuria (Forsblom et al.1999). In addition to hyperglycaemia and geneticsusceptibility, many other factors have been as-sociated with the evolution of diabetic complica-tions. These risk factors will be evaluated in thesections for the different complications. A hypo-thetical model for the development of chronicmicrovascular diabetic complications is depictedin Figure 1.

2.2. Retinopathy

Diabetes results in characteristic lesions inthe retinal blood vessels. This can result in for-mation of microaneurysms, haemorrhages andincreased leakage, causing retinal edema and li-pid exudates. These changes are defined as back-ground retinopathy (NPDR). They do notthreaten visual acuity unless they are located in

the macular region, where they can cause macu-lar edema. Capillary closure can lead to areas ofimpaired perfusion and ischaemia, which canresult in retinal infarcts and formation of newvessels, defined as proliferative retinopathy(PDR)(Fig.2). New vessels can cause intraocularbleeding and impair vision. The formation of fi-brous tissue may eventually cause retinal detach-ment and severe visual impairment (Forrester etal. 1997).

Epidemiology

Population-based studies of patients with dia-betes show great variation in the reported preva-lence of retinopathy. Differences in age at diag-nosis, duration of diabetes, treatment and gly-caemic control could all influence the prevalence(Klein et al. 1984a, Agardh et al. 1989;Henricsson et al. 1996). The method used to de-tect retinopathy seems to be crucial. Photogra-phy has been demonstrated to be superior toophthalmoscopy for detection of early diabeticchanges (Moss et al. 1985; Kinyoun et al. 1992).Valuable information has been obtained fromprospective follow-up studies with standardisedgrading of retinal photographs. The WisconsinEpidemiological Study of Diabetic Retinopathy(WESDR) (Klein et al. 1984a; Klein et al. 1984b)followed both younger-onset (diagnosed before30 years of age, n=996) and older-onset diabeticpatients (diagnosed after 30 years of age) with(n=673) or without (n=692) insulin treatment.In the younger-onset group there was almost noretinopathy during the first 5 years of disease,but thereafter the rise was rapid and by 15 yearsmore than 90 % of the patients had some degreeof retinopathy. In contrast, over 20% of the older-onset patients had some signs of retinopathy dur-ing the first 5 years and after a long durationstill 20 % of the patients did not have signs ofretinopathy. The prevalence of PDR rose to about50% in the younger-onset patients and to about10-30 % in the older-onset patients after 25 yearsof diabetes. In the insulin-treated older-onsetpatients those treated with insulin had higherprevalence of retinopathy than the non-insulintreated. In a cross-sectional study from Sweden,using the same classification of retinopathy, the


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prevalence of retinopathy in younger-onset pa-tients was 64%, and in the older-onset patients57% in insulin-treated and 26% in non-insulintreated patients, respectively (Henricsson et al.1996). In the United Kingdom Prospective Dia-betes Study (UKPDS) diabetic retinopathy wasdetected in about one third of newly diagnosedtype 2 diabetic patients (Kohner et al. 1998).

The prevalence of retinopathy varies amongdifferent racial or ethnic groups. The Pima Indi-ans in Arizona and Mexican Americans in SanAntonio, Texas, with type 2 diabetes have a sig-nificantly higher prevalence of retinopathy thannon-Hispanic white patients from the WESDRpopulation (Haffner et al. 1988; Nelson et al.1989).

There are limited data on retinopathy in dia-betic subgroups, i.e. patients with MODY orLADA. In a study of 24 patients with MODY3diabetes proliferative retinopathy based onophthalmoscopy was seen in 5 patients (21%)(Velho et al. 1996). In patients with MODY1diabetes retinopathy is frequently described(Hattersley 1998, Iwasaki et al. 1998) whereasin MODY2 retinopathy seems to be rare (Pageet al. 1995; Velho et al. 1996; Velho et al. 1997).

Risk factors for diabetic retinopathy

Hyperglycaemia: A relationship between hy-perglycaemia and a higher prevalence and inci-dence and progression of retinopathy has beenseen in both type 1 and type 2 diabetes (Pirart1978; Klein et al. 1984a; Agardh et al. 1994;Henricsson et al. 1996; Stratton et al. 2001). TheDiabetes Control and Complications Trial(DCCT 1995a) reported a reduction in the de-velopment of retinopathy by 76 %, and in pro-gression to severe non-proliferative or prolifera-tive retinopathy by 47 % in patients intensivelytreated compared to conventionally treated pa-tients during a follow-up of 6.5 years. In theStockholm Study the need for photocoagulationwas reduced in intensively treated compared toconventionally treated patients (Reichard et al.1993). In the Kumamoto Study intensive insulintreatment of type 2 diabetic patients was associ-ated with less worsening of retinopathy comparedto the group with conventional insulin treatment(Shichiri et al. 2000). Although improvement inglycaemic control retards the development andprogression of retinopathy, there have been re-


Figure 2. Role of hyperglycaemia and hypertension in the evolution of diabetic retinopathy. Modified from E. Kohner 1993.

Hyperglycaemia

capillary damage

abnormal autoregulation

hyperperfusion

vasoactive factors

Hypertension

growth factors new vessels

pericyte loss endothelial damage

capillary non-perfusion

retinal ischaemia

leakage

17

ports on worsening of retinopathy after rapidlyimproved glycaemic control both in type 1 andtype 2 diabetes (Lauritzen et al. 1983; DCCT1998; Henricsson et al. 1999). The greatest riskof progression was related to the magnitude ofthe lowering of HbA1c (Henricsson et al 1999).The mechanisms by which the rapid improve-ment in glycaemia can impair retinopathy is notentirely clear but it has been suggested to involvealtered rheological conditions (Grunwald et al.1995).

Duration of diabetes: The association be-tween duration of diabetes and retinopathy hasbeen seen in many studies especially in type 1diabetes (Pirart 1978; Klein et al. 1984a). In type2 diabetes retinopathy is seen in many patientsalready at diagnosis (Kohner et al. 1998). Thisprobably reflects the difficulties in determiningthe exact duration of diabetes.

Hypertension: A relationship between el-evated blood pressure and retinopathy has alsobeen seen in several studies both in type 1 (Kleinet al. 1984a; Agardh et al. 1994) and type 2 dia-betic patients (Klein et al. 1984b; Teuscher et al.1988; Hamman et al. 1989). In a cohort study, a10 mmHg increase in systolic blood pressure wassignificantly associated with increased incidenceof retinopathy in subjects with younger-onsetdiabetes (age at diagnosis below 30 years), butnot in subjects with older-onset diabetes (Kleinet al. 1995a). In the UKPDS, tight blood pres-sure control decreased significantly the progres-sion of retinopathy (UKPDS 1998).

Both hypertension and hyperglycaemia in-crease the retinal blood flow, which is involvedin the evolution of diabetic retinopathy (Fig. 2).In contrast, conditions that reduce retinal bloodflow seem to protect from advanced retinopathy;these include moderate carotid stenosis and raisedintraocular pressure (Parving 1983; Grunwaldet al. 1990).

Nephropathy: There is a relationship be-tween the development of nephropathy and retin-opathy. When overt diabetic nephropathy ispresent, almost all patients already have a con-comitant proliferative retinopathy (Krolewski etal. 1986). However, about 30 % of patients withproliferative retinopathy do not show signs of ne-

phropathy (Agardh et al. 1987; Kostraba et al.1991), indicating that the development of thesetwo complications may follow different timecourses or that partly different mechanisms maybe involved (Mosier et al. 1997).

Smoking: The effect of smoking on the riskof retinopathy is controversial. Only a few stud-ies have found a harmful effect (Sjølie 1985;Chaturvedi et al. 1995). In contrast, in the cross-sectional and the prospective Wisconsin study noassociation between smoking and retinopathy wasseen (Moss et al. 1996).

Other factors: An association between retin-opathy and some other factors such as pregnancy(Klein et al. 1990; Lövestam-Adrian et al. 1997)and age at diagnosis (Krolewski et al. 1986;Agardh et al. 1989; Kostraba et al. 1989) hasbeen suggested, but results from studies are con-flicting. Studies regarding the impact of lipidsand lipoproteins on retinopathy have been incon-sistent (Klein et al. 1997).

2.3. Nephropathy

The hallmark of renal damage in diabetes isincreased excretion of proteins, mainly albumin,in the urine. The natural history of diabetic ne-phropathy has been viewed as a descending pathfrom normoalbuminuria to microalbuminuria andovert proteinuria and eventually to end-stage re-nal disease (ESRD) (Fig. 3). In 1986 a consen-sus was reached about the term microalbumiuria,which was defined as urine AER 20-200 µg/minin a timed overnight or 30-300mg/24h in a 24-hurine collection (Mogensen et al.1986). UrineAER exceeding these values is calledmacroalbuminuria and considered a sign of mani-fest diabetic nephropathy.

Epidemiology

Approxmately 35-45% of patients with type1 diabetes will develop diabetic nephropathyduring a follow-up of about 40 years of diabetes(Andersen et al. 1983; Krolewski et al. 1985).The incidence of diabetic nephropathy increasesrapidly after duration of 10 years and begins todecrease after about 20 years of diabetes


18

(Andersen et al. 1983). The prevalence ofmicroalbuminuria rises from below 10% duringthe first years of diabetes to about 50% of pa-tients after duration of 20 years. The prevalenceof ESRD starts to rise after duration of 15 years,reaching a peak of about 20 % after duration of35 years (Krolewski et al. 1985). Compared totype 1 diabetic patients, in whommicroalbuminuria is rare during the first years,microalbuminuria is a common feature in type 2diabetic patients already at the diagnosis of dia-betes. In Caucasian newly diagnosed type 2 dia-betic patients, the prevalence ofmicroalbuminuria is about 20-30% (Uusitupa etal. 1987; UKPDS 1993). The high prevalence ofmicroalbuminuria in type 2 diabetes may be dueto difficulties in defining the exact duration intype 2 diabetes, the high prevalence of non-dia-betic renal disease (Parving et al. 1992) and thepresence of the metabolic syndrome, in whichmicroalbuminuria has been related to more gen-eralised vascular damage (Nannipieri et al. 1997).

There are few studies on the presence of dia-betic nephropathy in patients with MODY,LADA or other diabetic subgroups. In a study of26 patients with MODY3 diabetes 5 patients(19%) had dipstick positive proteinuria (lowerlimit of detection 2.5-3.0 mg/dl) (Velho etal.1996). In patients with MODY2 diabetes ne-phropathy has been virtually non-existing (Page

et al. 1995; Velho et al. 1996; Velho et al. 1997).Type 2 diabetic patients with ICA (LADA)showed a significantly lower prevalence of albu-minuria (micro- or macroalbuminuria) and lowerAER compared to type 2 diabetic patients with-out ICA 5 years after the diagnosis of diabetes(Gottsäter et al. 1996).

Risk factors

Hyperglycaemia: Poor glycaemic control hasbeen associated with the development ofmicroalbuminuria both in type 1(Microalbuminuria Collaborative Study Group1993; Mathiesen et al. 1995; Agardh et al. 1997)and in type 2 diabetic patients (Niskanen et al.1996; Gall et al. 1997; Forsblom et al. 1998a).In the DCCT study intensive therapy reduced theoccurrence of microalbuminuria by 39% and thatof albuminuria by 54% (Diabetes Control andComplication Trial 1993). In Type 2 diabeticpatients intensified therapy has been associatedwith a reduction in the progression ofmicroalbuminuria (Ohkubo et al. 1995).

Duration of diabetes: The duration of dia-betes has been associated with the developmentof nephropathy in both type 1 (Andersen et al.1983) and type 2 (Ballard et al. 1988) diabeticpatients. Progression from microalbuminuria toovert nephropathy has also been reported to oc-cur in a majority of type 1 diabetic patients in

Figure 3. The progression of albumin excretion (AER), risk factors and prognosis.

normal AER <20µg/min

microalbuminuria 20-200 µg/min

albuminuria >200 µg/min

end-stage renal disease

increased cardiovascular mortality

♦ hyperglycaemia ♦ hemodynamic factors ♦ genetic susceptibility ♦ the metabolic syndrome


19

follow-up studies (Parving et al. 1982; Mogensenet al. 1984). However, all patients withmicroalbuminuria and long duration of diabetesdo not progress. Signs and symptoms of insulinresistance seem to be more common in patientswho progress to nephropathy (Forsblom et al.1992).

Genetic factors: The prevalence of neph-ropathy in type 2 diabetes seems to be influencedby ethnic factors; in Pima Indians the cumula-tive incidence of diabetic nephropathy and ESRDafter 20 years duration was 50 and 15%, respec-tively, compared to about 25 and 6 %, respec-tively, in Caucasians (Nelson et al. 1988; Ballardet al. 1988; Kunzelman et al. 1989; Humphreyet al. 1989). Familial aggregation of nephropa-thy has been demonstrated in both type 1(Seaquist et al 1989; Borch-Johnsen et al. 1992,Fagerudd et al. 1998) and type 2 diabetes (Pettittet al 1990; Faronato et al 1997).

Hypertension: The importance of hyperten-sion in the development of nephropathy is diffi-cult to assess, as elevation of blood pressure gen-erally follows the development of nephropathyin type 1 diabetic patients (Poulsen et al. 1994).In type 2 diabetic patients microalbuminuria andhypertension often coincide as components of the

metabolic syndrome (Groop et al. 1993; Albertiet al. 1998).

Gender: Male sex has been associated withan increased risk of diabetic nephropathy in bothtype 1 (Jacobsen et al. 1999) and type 2 (Gall etal. 1997; Forsblom et al. 1998a) diabetic patients.

Smoking: Smoking seems to increase the riskof nephropathy in type 1 diabetes (Chase et al.1991; Microalbuminuria Collaborative StudyGroup 1993). In type 2 diabetic patients the re-sults have been conflicting (Gall et al. 1997;Forsblom et al. 1998a).

Dietary protein intake: Reduction of dietaryprotein intake seems to have a beneficial effecton the rate of loss of kidney function in diabeticrenal disease (Walker et al. 1989; Zeller et al.1991; Pedrini et al. 1996). The conducted stud-ies have been small and further studies are neededto define the role of protein restriction in dia-betic nephropathy. The effect is thought to bemediated by a reduction in glomerularhyperfiltration.

Lipids and lipoproteins: In type 1 diabeticpatients multiple lipid abnormalities are seen inpatients with nephropathy, but little is knownabout the role of lipid abnormalities in the de-velopment of diabetic nephropathy (Groop et al.


Table 5: Clinical classification of neuropathy. Classification Symptoms Signs Prognosis 1.Distal symmetrical asymptomatic,

altered sensation, pain

normal, sensory loss, muscle atrophy

progressive, neuropathic ulcer, Charcot arthropathy

2. Autonomic asymptomatic, gustatory sweating, hypotension, gastroparesis, diarrea, impotence etc

abnormal autonomic functions

progressive, disabling, increased mortality

3.Mononeuropathies mucle weakness, pain

femoral amyotrophy, ocular palsies, truncal radiculopathy

slow recovery

4.Acute painful distal

pain, sensory loss, weight loss

sensory loss slow recovery

20

1996b). In type 2 diabetic patients dyslipidaemiaoften clusters with microalbuminuria as part ofthe metabolic syndrome (Kuusisto et al. 1995).

2.4. Neuropathy

Diabetic neuropathy includes a spectrum ofclinical manifestations, which can vary fromasymptomatic findings to disabling disease(Vinik et al. 2000). The clinical classification andcharacteristics of diabetic neuropathy are shownin Table 5. The most common form is distal, sym-metric polyneuropathy. The complex nature ofneuropathy and the lack of a unifying definitioncomplicate the comparison of study results ondiabetic neuropathy. Although efforts have beenmade to define diabetic neuropathy (Report andrecommendations of the San Antonio conferenceon diabetic neuropathy 1988), the definitionsused in different studies show great variations.Commonly used tests for the examination of dia-betic neuropathy are shown in Table 6. As theuse of electrophysiological tests are difficult in aclinical setting most studies have used a combi-nation of a scored questionnaire, a standardisedclinical examination and some method of quan-titative sensory testing. Some of these combina-tions of tests have reached wider use, as theMichigan Neuropathy Screening Instrument(MNSI) and the Michigan Diabetic NeuropathyScore (MDNS) (Feldman et al. 1994) and the

Neuropathy Disability Score (NDS) and Neuropa-thy Symptom Score (NSS) used in the UK hos-pital clinic study (Young et al. 1993). Monofila-ment testing (cutaneous pressure perception) ina standardised setting has also been widely usedin order to identify diabetic patients at high riskfor foot ulceration (Kumar et al. 1991; Pham etal. 2000).

Epidemiology

In unselected populations the prevalence of

diabetic neuropathy ranges between 10 and 90% depending upon definitions and the methodsused to detect neuropathy (Feldman et al.1994).In a study by Pirart 8% of the patients had evi-dence of neuropathy at diagnosis while the preva-lence was 50 % after a follow-up of 25 years(Pirart 1978). In studies where distal neuropa-thy was defined as the presence of significantsymptoms and/or abnormalities in the physicalexamination the prevalence has been 20-35%both in type 1 and type 2 diabetic patients (Ziegleret al. 1993; Young et al. 1993; Tesfaye et al. 1996;Fedele et al. 1997). The prevalence of autonomicneuropathy has also shown great variations prob-ably depending on different methods used andvarying populations studied. In type 2 diabeticpatients Töyry et al. found parasympathetic neu-ropathy in 5 % of patients at diagnosis and 65%after a follow-up of 10 years (Töyry et al. 1996).Although pathological testresults are seen inmany patients, symptomatic autonomic neuropa-

Table 6: Commonly used tests for diabetic neuropathy.

Symptoms history or scored questionnaire Clinical examination tendon reflexes, sensory testing for

vibration, pain, temperature, light touch Quantitive sensory testing threshold for vibration, thermal sensation,

light touch Electrophysiologic tests motor and sensory conduction, needle

electromyography Autonomic tests cardiovascular, sudomotor, vasomotor tests


21

thy is relatively rare.Neither have the studies on neuropathy taken

into account heterogeneity of diabetes. In theFrench study of MODY3 patients only one outof 27 patients showed clinical signs of periph-eral neuropathy (Velho et al. 1996). In MODY2neuropathy seems to be very rare (Page et al.1995; Velho et al. 1996; Velho et al. 1997).

Antibodies to glutamic acid decarboxylase(GADA) have been associated with presence ofperipheral neuropathy in type 1 diabetic patients(Kaufman et al. 1992). This finding is interest-ing, as immunological mechanisms have beensuggested to play a role in the pathogenesis ofneuropathy, and glutamic acid decarboxylase(GAD) is widely distributed throughout the pe-ripheral and autonomic nervous system. Furtherstudies have not confirmed an association be-tween GADA and diabetic neuropathy (Zanoneet al. 1994, Roll et al. 1995).

Risk factors for neuropathyHyperglycaemia: Poor glycaemic control has

been associated with increased risk of neuropa-thy in many studies of both type 1 (Tesfaye et al.1996; Dyck et al.1999) and type 2 diabetes(Partanen et al. 1995; Adler et al.1997). In theDCCT study intensive therapy, with HbA

1c about

7%, in type 1 diabetic patients reduced the ap-

pearance of neuropathy by 69 % (DCCT 1993).In the Kumamoto study, comparing intensive andconventional insulin therapy in type 2 diabeticpatients, the patients with intensive therapyshowed significant improvement in nerve con-dition velocity and vibration threshold comparedto the conventional group (Shichiri et al. 2000).A model for the pathogenesis of neuropathy andthe importance of hyperglycaemia is shown inFigure 4.

Duration: The prevalence of neuropathyseems to increase with longer duration of dis-ease (Pirart 1978; Young et al. 1993; Partanen etal.1995).

Age: Increased age of the patients has beenassociated with neuropathy in some studies(Ziegler et al. 1993; Adler et al.1997).

Smoking: Smoking is thought to have a toxiceffect on peripheral nerves. However, the resultsregarding smoking as a risk factor for neuropa-thy are conflicting both in type 1 and type 2 dia-betic patients (Mitchell et al. 1990; Sands et al.1997). In the large EURODIAB study cigarettesmoking was associated with neuropathy (Tesfayeet al. 1996).

Height: In some studies increased height hasbeen associated with neuropathy (Tesfaye et al.1996; Adler et al. 1997). Height has been inter-preted as a marker of neuronal length and could


Figure 4. A model for the pathogenesis of diabetic neuropathy. Modified from Sima et al. 1999. NCV: nerve condition velocity.

hyperglycaemia

polyol pathway ↑

AGEs ↑

oxidative stress ↑

nerve growth factors ↓

C-peptide/ insulin deficiency

blood flow ↓

NCV ↓

axonal atrophy ↑

regeneration ↓

cell death ↑

essential fatty acids ↓

demyelination ↑

22

imply an increased vulnerability for diabetic dam-age to the nerve. Height is also associated withgreater pressure in lower extremities, which coulddecrease capillary blood flow (Richardson 1988).

C-peptide: Both insulin and C-peptide seemto have neuroprotective effects (Ido et al. 1997).This theory is supported by the results from aFinnish 10-year follow-up study, where the pa-tients who developed neuropathy in addition topoor metabolic control also had lower baselineinsulin values (Partanen et al. 1995).

2.5. Cardiovascular disease

The clinical manifestations of CVD includecoronary heart disease (CHD), cerebrovasculardisease and peripheral vascular disease(PVD).The underlying disease mechanism isaccelerated atherothrombosis. The atheroscleroticprocess starts from fatty streaks, consisting ofintimal deposits of lipids and macrophages withlipid droplets (foam cells), gradually developinginto more advanced plaques. The process endsup in a complicated atherosclerotic lesion, whichthrough a plaque rupture and thrombosis cancause an acute myocardial infarction (Stary etal. 1994; Stary et al. 1995).

Atherosclerotic lesions in diabetic patients arehistologically similar to those in non-diabeticsubjects, but appear to be more extensive and se-vere than in non-diabetic subjects. This is illus-trated by a Finnish 7-year follow-up study inwhich patients with type 2 diabetes without priormyocardial infarction had a risk of infarctionsimilar to that among non-diabetic men with a

previous infarction (Haffner et al. 1998).The prevalence of CVD is highly dependent

upon which methods are used to detect the dis-ease (Table 7). CHD, the most important mani-festation of CVD, represents a wide spectrumfrom angina pectoris, myocardial infarction andsudden death to silent myocardial ischaemia(Naka et al. 1992). Silent myocardial ischaemiahas a reported prevalence of 10-20 % in diabeticpopulations compared with 1-4 % in non-dia-betic populations (Janand-Delenne et al. 1999).

The atherosclerotic process can be studiednon-invasively by the use of imaging techniquessuch as measuring the intima-media thicknessby ultrasound (Wendelhag et al. 1991), and mag-netic resonance imaging (Fayad et al. 2000).Measurement of ankle-brachial index (ABI) hasalso been used to detect asymptomatic athero-sclerosis (Leng et al. 1996).

Epidemiology

Type 1 diabetes: The prevalence of CVD hasvaried markedly depending on the criteria ofCVD, duration of diabetes and the impact of dia-betic nephropathy. In the EURODIAB study theoverall prevalence of CVD in type 1 diabeticpatients was 10%, increasing with age and dura-tion and with a sixfold variation between differ-ent European centres (Koivisto et al. 1996). Thecumulative CHD mortality by age 55 years was35 % in type 1 diabetic men and women com-pared to 8 and 4 %, respectively, in nondiabeticmen and women (Krolewski et al. 1987). Dia-betic nephropathy markedly increases the risk ofCVD: in a follow-up study the risk ratio of CHDdeath was 37 in patients with proteinuria com-


Table 7: Methods to study prevalence of coronary heart disease, silent myocardial ischaemia and atherosclerosis. Clinical CHD Silent myocardial

ischaemia Atherosclerosis

medical history, typical symptoms, resting ECG, causes of death

exercise ECG, thallium scintigraphy, continuos 24-h ECG monitoring (Holter), coronary angiography

ankle-brachial index, intima-media thickness, magnetic resonance imaging

23

pared to 4.2 in patients without proteinuria(Borch-Johnsen et al. 1987). Dyslipidaemia hasbeen suggested as a possible mechanism behindthe increased CVD risk in patients with neph-ropathy. In connection with diabetic nephropa-thy total and LDL cholesterol, triglycerides andApoB concentrations are increased while HDLcholesterol is reduced (Groop et al. 1996b). Inpatients without diabetic nephropathy poor meta-bolic control predicted CHD events independ-ently of other cardiovascular risk factors (LehtoS et al. 1999).

Type 2 diabetes: In patients with type 2 dia-betes the age-adjusted, cause-specific mortalityfor CHD is two to four times higher than in non-diabetic control groups (Kannel et al. 1979;Stamler et al. 1993; Nathan et al. 1997). Therelative risk has been even greater for women inmany studies. The risk for stroke and peripheralvascular disease is also increased in diabetic pa-tients (Kannel et al. 1979; Brand et al. 1989,Siitonen et al. 1993). The prevalence of CVD isalso influenced by the prevalence of CVD inthe background population (WHO multinationalStudy of Vascular Disease in Diabetics 1985;Zimmet et al. 1997).

Again, few studies have considered hetero-geneity of diabetes when studying the presenceof CVD. The prevalence of CHD in patients withMODY diabetes has been difficult to assess asthe study populations have been small and thepatients have been relatively young. Patients withLADA have shown a more favourable cardio-vascular risk profile compared to other type 2diabetic patients (Gottsäter et al. 1996; Tuomi etal. 1999).

Risk factors for cardiovascular disease intype 2 diabetic patients

The classic risk factors: Data from popula-tion studies indicate that the major cardiovascu-lar risk factors in non-diabetic populations,namely smoking, hypertension andhypercholesterolemia, also operate in diabeticsubjects (Stamler et al. 1993). Genetic factors areobviously also important as the prevalence is in-fluenced by the background population (WHOMultinational Study of Vascular Disease in

Diabetics 1985). In the MRFIT (Stamler et al.1993) where 5000 diabetic and 350000 non-dia-betic subjects were followed up for 12 years, thecardiovascular death rate increased highly sig-nificantly with the number of risk factors (systolicblood pressure, smoking and total cholesterol)in both diabetic and non-diabetic men. However,the incidence of CVD death was increased 2-3fold in the diabetic men for each combination ofrisk factors (Fig. 5). The traditional risk factorsdo not explain all the excess risk of CVD diseasein patients with diabetes. Therefore, also otherrisk factors must be operative in diabetic patients.

Hyperglycaemia: Several prospective stud-ies mainly in type 2 diabetic patients have shownthat glycaemic control influences the risk of CVD(Klein 1995b; Wei et al. 1998; Laakso 1999). Inthe UKPDS the most important risk factor forCHD was high LDL cholesterol, followed by lowHDL cholesterol and hyperglycaemia (Turner etal. 1998). In a Finnish prospective study, poorglycaemic control in addition to hypertension anddyslipidaemia predicted fatal and non-fatal stroke(Lehto S et al. 1996). The results from prospec-tive studies indicate that hyperglycaemia is re-lated to macrovascular disease, but the risk ofmacrovascular disease seems to be smaller thanthe risk associated with microvascular compli-cations (Klein 1995b; Laakso 1999).

Hyperinsulinaemia / insulin resistance:Hyperinsulinaemia could influence atherogenesisboth by direct action on arterial wall and indi-rectly through other components of the metabolicsyndrome. In animal studies high insulin con-centrations stimulated cholesterol synthesis andbinding of LDL cholesterol to smooth musclecells and macrophages in the arterial wall (Stout1990). Hyperinsulinaemia has predicted CHDevents in non-diabetic men (Welborn et al. 1979;Ducimetière et al. 1980; Pyörälä et al. 1998).There are also data supporting an associationbetween hyperinsulinaemia and CHD risk in type2 diabetes (Rönnemaa et al. 1991, Hanefeld etal. 1997). Hyperinsulinaemia has generally beenconsidered as a marker of insulin resistance; adecrease in the effect of insulin to stimulate glu-cose uptake at a given insulin concentration. Thegolden standard for the measurement of insulin


24

sensitivity / resistance is the euglycaemichyperinsulinaemic clamp technique (Ferrannini1998). As this technique is time-consuming andexpensive the use has been limited to clinicalresearch centres. Other methods to assess insu-lin resistance have been the homeostasis modelassessment (HOMA), using fasting insulin andfasting plasma glucose concentrations ( Matthewset al. 1985), the frequently-sampled intravenousglucose tolerance test (FSIGT) (Haffner et al.1997) and fasting insulin concentration (Laakso1993).

Reaven introduced the term Syndrome X in1988 and suggested that insulin resistance andcompensatory hyperinsulinaemia underlie theclustering of cardiovascular risk factors such asglucose intolerance, hypertension anddyslipidaemia (Reaven 1988). This clustering ofcardiovascular risk factors has been suggestedas possible mechanism for the increased risk ofCVD in type 2 diabetes. In a recent Finnish studyclustering of a high BMI, high triglycerides, lowHDL cholesterol and endogenoushyperinsulinaemia predicted cardiovascular mor-tality in patients with type 2 diabetes (Lehto S etal. 2000).

Dyslipidaemia: In type 2 diabetes lipid ab-normalities are almost the rule. Typical findingsare elevation of total and VLDL triglyceride con-

centrations, exaggerated postprandial lipaemia,lowering of HDL cholesterol and a predominanceof small, dense LDL particles (Taskinen et al.1996). Insulin resistance is often involved inthis process (Syvänne et al. 1997).Hypertriglyceridaemia has been associated withincreased risk of CHD both in non-diabetic(Hokanson et al. 1996) and type 2 diabetic sub-jects (Fontbonne et al. 1989). Remnants of trig-lyceride-rich lipoproteins seem to be extremelyatherogenic (Zilversmit 1995; Karpe et al. 1995).

The LDL particle size pattern can be classi-fied by use of gradient gel electrophoresis (Aus-tin et al. 1988). Pattern A is characterised by apredominance of large buoyant LDL particles(>25.5 nm), whereas pattern B is the phenotypewith a predominance of small LDL particles,which has been associated with CHD (Stampferet al. 1996; Gardner et al. 1996; Lamarche etal.1997). The LDL particle size is both geneti-cally determined and related to lifestyle factorssuch as diet and exercise (Lamarche 1999). Smalldense LDL particles have been associated withthe individual components of the metabolic syn-drome (Haffner 1995; Austin 1996). Theproatherogenic properties of small LDL particlesmay relate to their ability to penetrate the arte-rial wall and thereby making them more suscep-tible to oxidation (Hurt-Camejo et al. 1992).

Figure 5. Age-adjusted cardiovascular death rate (per 10.000 person years) by number of risk factors in patients with and without diabetes in MRFIT (Stamler et al. 1993)

0

20

40

60

80

100

120

none one only two only all three

non-diabeticdiabetic


25

Elevated LDL cholesterol has also been as-sociated with CHD in follow-up studies (Turneret al. 1998; Forsblom et al. 1998b). Elevated LDLcholesterol predicted CHD in patients withoutmacroangiopathy at baseline indicating that el-evated LDL cholesterol becomes important afterexclusion of high-risk patients with CHD at base-line. In patients with macroangiopathy at base-line the features of the metabolic syndrome seemto be the strongest predictor of death (Forsblomet al. 1998b).

Impaired fibrinolysis and increased coagu-lability: An imbalance in the haemostatic sys-tem due to hypercoagulability or impaired fibri-nolytic function may favour the development ofvascular damage and can be involved in theatherosclerotic plaque rupture. Plasminogen ac-tivator inhibitor type 1 (PAI-1) is a potent in-hibitor of fibrinolysis. Increased levels of PAI-1have been demonstrated in survivors of acutemyocardial infarction and in patients with coro-nary artery stenosis (Hamsten et al. 1985). Epi-demiological studies have suggested links be-tween PAI-1 and the components of the meta-bolic syndrome (Juhan-Vague et al. 1993).

There are also studies indicating that fibrino-gen levels are elevated in patients with diabetesand CHD. Raised fibrinogen concentrations fa-vour coagulation and increase platelet activationand adherence to the endothelium (Ernst et al.1993). Increased levels of von Willebrand factor(Chen et al. 1995) and lipoprotein (a) have alsobeen reported in diabetic subjects (Heller et al.

1993).Microalbuminuria: Microalbuminuria and

albuminuria are markers of increased cardiovas-cular risk in both type 1 and type 2 diabetic sub-jects. In addition to being a sign of incipient re-nal damage, microalbuminuria has been sug-gested as a marker of endothelial damage andincreased transcapillary albumin leakage(Deckert et al. 1989; Jensen et al. 1995). In type2 diabetic patients microalbuminuria is a strongpredictor of cardiovascular morbidity and mor-tality (Kuusisto et al. 1995; Jensen et al. 1997;Dinneen et al. 1997; Borch-Johnsen et al. 1999).In type 1 diabetes microalbuminuria has also beenlinked to CVD due to its possible association withother cardiovascular risk factors such asdyslipidaemia (Groop et al. 1993) and hyperten-sion (Mathiesen et al. 1995). In type 2 diabetesmicroalbuminuria has been associated with in-sulin resistance and the components of the insu-lin resistance or metabolic syndrome (Groop etal.1993; Kuusisto et al. 1995).

Other risk factors: Although physical inac-tivity predicts CVD in non-diabetic individuals(Blair et al. 1996), data on diabetic patients arelimited. In a recently published study a low levelof cardiorespiratory fitness and physical inactiv-ity was associated with increased CVD mortal-ity in men with type 2 diabetes (Wei et al. 2000).Obesity, a very common feature in type 2 dia-betic patients, has not independently been asso-ciated with cardiovascular diasese in diabeticpatients (Laakso 2001).


26

Aims of the study

The aims of this study were to evaluate the following:

1. The prevalence of chronic diabetic complications in patients with maturity-onset diabetes inthe young (MODY3) from five large Finnish families (I).

2. The prevalence of chronic diabetic complications in patients with slowly progressingautoimmune type 1 diabetes (LADA) and compare them to findings in type 1 and type 2diabetic patients from the same region (II).

3. The prevalence of the metabolic syndrome and its components and to study thecardiovascular morbidity and mortality associated with the metabolic syndrome (III).

4. The impact of different features of the metabolic syndrome on chronic diabeticcomplications in patients with type 2 diabetes (IV).

27

Subjects and study design

The characteristics of the patients includedin the studies are shown in Table 8. The patientswith MODY3 diabetes (Study I), patients withslowly progressing autoimmune type 1 diabetes(LADA) and their controls (Study II) as well asthe patients with and without the metabolic syn-drome (Study IV) were recruited from the BotniaStudy in western Finland. The Botnia Study rep-resents a large family study in Finland and Swe-den that was initiated in 1990 with the aim toidentify early metabolic defects in families withtype 2 diabetes (Groop et al.1996a). Type 1 dia-betic patients, were recruited as consecutive pa-tients from the outpatient clinic of JakobstadHospital, Jakobstad, Finland. Type 1 diabetes wasdefined as onset of diabetes before the age of 35,a history of ketoacidosis and immediate need ofinsulin treatment. In addition, for the ophthal-mologic comparison in study I, data fromHelsingborg, Sweden (38 patients with type 1 and38 with type 2 diabetes) were used.

All subjects gave their informed consent be-fore entering the studies, and the study protocolsof the Botnia Study have been approved by localEthics Committees.

1. Chronic diabetic complica-tions in patients with MODY3diabetes (I)

57 patients with MODY3 diabetes from 5large Finnish families were examined for thepresence of diabetic complications. Forty-ninepatients from four families shared the same in-sertion mutation of exon 4 in the HNF-1α genewhereas eight patients from the fifth family hada missense mutation in the HNF-1α gene (LehtoM et al. 1997). The clinical characteristics of theMODY3 patients and type 1 (N=111) and type2 (N=159) diabetic patients matched for dura-tion of diabetes and glycaemic control are shown

in Table 8. The prevalence of diabetic complica-tions in patients with MODY3 diabetes was com-pared between the three groups. By use of multi-ple logistic regression analysis risk factors fordiabetic complications were analysed.

2. Chronic complications inpatients with slowly progressingautoimmune type 1 diabetes(LADA) (II)

The LADA patients were recruited from theBotnia study in Western Finland (Groop et al.1996a). Of 1122 patients given a diagnosis oftype 2 diabetes, 104 (9.3%) were positive forGADA (Tuomi et al. 1999). Among them weidentified 90 GADA positive patients who atonset of diabetes were over 35 years old and hadno signs of ketoacidosis. 16 patients (18%) haddied since their first participation in the Botniastudy, and 15 patients were not available for ex-amination. The remaining 59 LADA patientswere examined for the presence of diabetic com-plications and compared with 59 GADA nega-tive type 2 diabetic patients from the Botnia study,matched for age, sex and duration of diabeteswith the LADA patients. The findings in theLADA patients were also compared with type 1diabetic patients (n=111) representing consecu-tive patients from the outpatient clinic of theJakobstad Hospital (Jakobstad, Finland).

3. Cardiovascular morbidityand mortality associated withthe metabolic syndrome (III)

From a total of 6645 persons participating inthe Botnia study all subjects aged 35-70 years(n=4483) were included in this study. Patients

28

with GADA (Tuomi et al.1999) and MODY veri-fied by DNA analysis (Lehto M et al. 1997), wereexcluded.

Glucose tolerance was assessed according tothe new ADA/WHO criteria using a 75 g oralglucose tolerance test (OGTT) (Alberti et al.1998). Of the subjects studied 1697 had diabe-tes, 798 had abnormal glucose tolerance, whichincluded both impaired fasting glucose (IFG) andIGT whereas 1988 subjects had a normal glu-cose tolerance (NGT). For the definition of themetabolic syndrome the WHO proposal from1998 was used (Alberti et al. 1998) (Table 3).The prevalence of the metabolic syndrome andthe components of the syndrome and the associ-ated cardiovascular risk were assessed in the dif-ferent groups of glucose tolerance.

Total and cardiovascular mortality was as-sessed in 3606 subjects from the original Botniacentres in western Finland with a median fol-low-up of 6.9 years. Mortality data were obtainedfrom a central death-certificate registry.

4. The impact of different fea-tures of the metabolic syndromeon chronic complications in type2 diabetes (IV)

The diabetic patients were recruited from theBotnia Study. We studied a random sample of 85patients who fulfilled the criteria for the meta-bolic syndrome (Alberti et al. 1998) and com-pared them to 85 patients, matched for age, sexand duration of diabetes, who did not fulfil thecriteria for the syndrome. The definition of themetabolic syndrome was modified regarding thecriteria for central obesity (cutoff for WHR: >1.0in males; >0.9 in females) according to the dis-tribution of obesity in a Scandinavian popula-tion (Study III). Patients with MODY were ex-cluded by genetic characterisation (Lehto M etal. 1997). Patients with GADA were also ex-cluded (Tuomi et al. 1999). Risk factors for dia-betic complications were analysed by multiplelogistic regression analysis.

Table 8 : Characteristics of subjects included in the studies. Study Patients Number (M/F) Age

(years) Duration (years)

HbA1cb (%)

Design

I MODY3 Type 1 DM Type 2 DM Type 1 DMa

Type 2 DMa

57 (29/28) 111 (67/44) 159 (63/96) 38 (20/18) 38 (25/13)

44±16 39±12 69±12 34±13 59±12

17±13 23±12 23±6 16±13 15±12

7.3±1.6 7.7±1.5 7.6±1.9 6.9±1.3 7.1±1.3

cross-sectional

II LADA Type 1 DM Type 2 DM

59 (26/33) 111 (67/44) 59 (26/33)

70±11 39±12 69±10

13±6 23±12 12±6

8.3±1.5 8.8±1.5 8.2±1.4

cross-sectional

III NGT IGT Type 2 DM

1988 (1133/855) 798 (397/401) 1697 (804/893)

50±10 53±10 59±8

NA NA 8±7

ND ND 8.0±1.6

cross-sectional, prospective

IV MSDR+ MSDR-

85 (53/32) 85 (53/32)

59±9 61±7

8±6 9±6

7.9±1.6 7.5±1.4

cross-sectional

NA: not applicable, ND: not done. a Patients (Helsingborg, Sweden) for the ophthalomologic comparison, matched with the MODY3 patients for duration and HbA1c. b HbA1c was measured by a method with lower reference values (Kyoto Daichii, Kyoto, Japan) in study I, whereas an other method (Diamat, Hercules, CA) was used in the other studies.

Subjects and study design

29

Methods

1. Assessment of diabetic com-plications

Retinopathy: The diagnosis of retinopathywas based upon fundus photography. Colour fun-dus photographs were obtained after pharmaco-logical mydriasis at an angle of 45-60 degreeswith a Topcon TRC NW5 fundus camera (TopconOptical Co. Ltd, Tokyo, Japan) or a Canon CF-60U fundus camera (Canon, Tokyo, Japan). Thephotographs covered fields 1-3 of the seven stand-ard fields, with stereo pairs of the macula (field2). The alternative classification of the Wiscon-sin Epidemiological Study of Diabetic Retinopa-thy was used to define the retinopathy level (Kleinet al. 1986).

The patient´s retinopathy level was derivedby giving the eye with the higher level a greaterweight (Table 9). This scheme provides an 11-step scale: 10/10, 21/10, 21/21, 31/<31, 31/31,41/<41, 41/41, 51/<51, 51/51, 60+/<60+, 60+/60+. Based upon this scale the retinopathy lev-els of the patients were divided into 4 groups; noDR (level 10/10), mild DR (levels 21/10 - 31/31), moderate DR (levels 41/<41 - 51/<51), and

severe NPDR or PDR (level 51/51 - 60+/60+).Macular oedema was defined as presence of

hard exudates and/or retinal thickening withinone disc diameter of the centre of the maculaand was considered present if at least one eyewas affected.

Photographs were viewed against light boardsusing Donaldson´s stereo viewer (5x magnifica-tion) and assessed by an independent grader. Inthe type 1 diabetic patients (n=111) the classifi-cation of retinopathy was based upon photogra-phy (n=62) or clinical data from hospital records.Two blind MODY3 patients (study I) were ex-cluded from photography because of media opaci-ties. In study IV the classification of retinopathywas based upon (ophthalmologic) hospitalrecords in 3 patients and on ophthalmoscopy inone patient.

Nephropathy and microalbuminuria:Microalbuminuria was considered to be presentif AER in overnight urine exceeded 20 µg/minand macroalbuminuria if AER exceeded 200 µg/min (Mogensen et al. 1995). Overnight urine wasnot available in 8% and 6%, respectively, of thepatients in study II and IV and the albumin-to-creatinine ratio (ACR) in the morning urine wasused. An ACR exceeding 2.5 mg/mmol in malesand 3.5 mg/mmol in females was considered asabnormal (Mogensen et al. 1995). In study IIIurine for the measurement of AER was collectedeither during the OGTT (n=1082) or overnight(n=1579). AER measured overnight correlatedwith AER during OGTT (r=0.605, p<0.001; N= 442).

In study IV two patients who fulfilled othercriteria of the metabolic syndrome had chronicglomerulonephritis of non-diabetic origin andwere excluded from the analysis of nephropathy.

Neuropathy: The diagnosis of distal sensory

Table 9: Grading of retinopathy. Level Characteristic findings 10 no diabetic retinopathy 21 microaneurysms only or blot haemorrhages

or soft exudates in the absence of microaneurysms

31 hard exudates or mild retinal haemorrhages 41 soft exudates or intraretinal microvascular

abnormalities (IRMA) 51 severe retinal haemorrhages or IRMA or

venous bending in at least one field 60+ all levels of PDR, with or without laser

treatment

30

neuropathy was based upon a clinical examina-tion and a symptom score (Young et al. 1993).

The clinical examination consisted of meas-urements of:

1) achilles tendon reflexes graded 0-2 for eachside (normal=0, present with reinforcement = 1and absent = 2), giving a maximum score of 4 ifboth sides were affected,

2) vibration sensation by a 128 Hz vibrationfork at the hallux, graded 0-1 for each side (nor-mal = 0, absent = 1) giving a maximum score of2,

3) sensory perception by a 10 g Semmes-Weinstein monofilament at three sites on eachfoot, graded 0 -2 for each side (normal = 0, ab-sent on one site = 1, absent on 2 or 3 sites = 2 )giving a maximum score of 4.

The maximum score for the clinical exami-nation was 10. A score of 3-5 was regarded asevidence for mild signs, a score of 6-8 for mod-erate signs and a score of 9-10 for severe signsof distal neuropathy. The clinical examinationwas performed by one examiner (B.I.).

For the subjective symptom score the patientanswered a questionnaire (Young et al. 1993). Ifthe patient described burning, numbness or tin-gling a score of 2 was assigned; fatigue, cramp-ing or aching was scored 1. The presence ofsymptoms in the feet was assigned a score of 2,in the calves 1 and elsewhere a score of 0. Noc-turnal exacerbation of symptoms scored 2 vs 1for both day and night and 0 for daytime only. Ascore of 1 was added if the symptoms had wokenthe patient from sleep. The patients were askedwhich manoeuvre reduced the symptoms: walk-ing was assigned a score of 2, standing of 1 andlying down was scored 0. A symptom score of 3-4 indicated mild symptoms, a score of 5-6 mod-erate and a score of 7-9 severe symptoms of distalneuropathy. The minimum criteria for the diag-nosis of distal sensory neuropathy were moder-ate signs with or without symptoms or mild signswith moderate symptoms.

In study I and II neuropathy was also assessedby measuring the vibration threshold at the an-kle with a Biothesiometer (Biomedical Instru-ments, Ohio, USA). As control, vibration per-ception threshold was also measured in 58 per-

sons with NGT and without clinical signs orsymptoms of neuropathy. An age-correlatedthreshold was calculated and a value exceeding2 SD above the mean was considered abnormal.There was a strong positive correlation betweenthe Biothesiometer measurements and the clini-cal neuropathy score (r=0.82; p<0.0001, N=36,Study I: MODY3 patients), while there was aweaker correlation between the Biothesiometermeasurements and the subjective symptom score(r=0.49, p=0.003, N=36).

In study IV the vibration perception thresh-old at the ankle was assessed with a Vibrameter(Somatomedic productions AB, Sollentuna, Swe-den) in 138 of the patients (68 with and 76 with-out the metabolic syndrome). As control, the vi-bration perception threshold was also measuredin 45 subjects aged 35-70 years with NGT andno clinical signs of neuropathy. The vibrationperception correlated to height and therefore aheight-adjusted threshold was calculated and avalue exceeding 3.3 µm (corresponding to the95th percentile) was considered abnormal. In thetype 2 diabetic patients the height-adjusted vi-bration threshold correlated with the score fromthe neurological examination (r=0.49, p<0.001,n=138) but not with the symptom score (r=-0.01,p=0.92, n=138).

Coronary heart disease: In study I, II andIV a history of myocardial infarction or strokewas based upon information in hospital records.Also, a diagnosis of CHD was based upon hospi-tal records or use of nitroglycerine and patho-logical findings in resting electrocardiogram(ECG). The ECGs were coded using the Minne-sota codes 1.1-3, 4.1-4, 5.1-3 (Rose et al. 1968)by one examiner (B.I.). In study III a standard-ised health questionnaire was completed by spe-cially trained nurses. CHD was defined as use ofnitroglycerine or typical chest pain or a historyof previous myocardial infarction. This informa-tion was validated against ECG changes accord-ing to the Minnesota code compatible withischaemic heart disease (Rose et al. 1968) in allsubjects from one of the centres (N=555). Myo-cardial infarction, defined in accordance with theWHO MONICA criteria (Tunstall-Pedoe et al.

Methods

31

1994) and stroke (including both ischemic andhaemorrhagic stroke) were defined as events re-quiring hospitalisation; this information wasverified from local hospital records.

Peripheral vascular disease: The diagnosisof peripheral vascular disease was based uponhospital records, palpation of foot pulses, clini-cal symptoms of claudication and measurementof ABI. Ankle systolic pressure was measuredafter 5 min. of rest in the supine position using aDoppler device (Multi-Doplex II, HuntleighTechnology, Cardiff, UK). A standard blood pres-sure cuff was placed around the right ankle andthe blood flow in the posterior tibial artery wasregistered. The mean from two measurementswas used and related to the auscultatory meas-urement of systolic pressure in the right arm.An ABI less than 0.9 was considered diagnosticfor peripheral vascular disease (Leng et al. 1996).

2. Assessment of mortality

In Study II total and cardiovascular mortal-ity was assessed in 90 GADA-positive patientsand 929 type 2 diabetic patients during a me-dian follow-up of 5.7 years. In study III total andcardiovascular mortality was assessed in 3606subjects from the original Botnia centres in west-ern Finland with a median follow-up of 6.9 years.Mortality data were obtained from a centraldeath-certificate registry. Cardiovascular mortal-ity was classified using the ninth revision of theInternational Classification of Diseases (ICD-9,cardiovascular diagnosis codes 390-459) before1997 and ICD-10 (codes I 00 -I 99) thereafter.

3. Assessment of glucose tole-rance

The diagnosis of diabetes was either basedupon use of antidiabetic medication or existingcriteria. In Study I the diagnosis of diabetes wasbased on the WHO criteria (WHO 1985) and inthe other studies the new ADA/WHO criteria(Alberti et al. 1998). Thus, subjects with a fast-

ing plasma glucose ≥7.0 mmol/l and/or 2-hplasma glucose ≥11.1 mmol/l during an OGTTwere considered to have diabetes, subjects witha fasting plasma glucose 6.1-6.9 mmol/l and/ora 2-h plasma glucose 7.8 -11.0 mmol/l were con-sidered to have abnormal glucose tolerance,which included both IFG and IGT. The glucosetolerance was considered normal (NGT) if fast-ing plasma glucose was <6.1 mmol/l and 2-h glu-cose <7.8 mmol/l.

4. Anthropometric measure-ments and blood pressure

Body weight and height were measured withsubjects in light clothing without shoes and bodymass index (BMI) was calculated. Waist circum-ference was measured with a soft tape on stand-ing subjects midway between the lowest rib andthe iliac crest. Hip circumference was measuredover the widest part of the gluteal region, andwaist-to-hip ratio (WHR) as a measure of cen-tral obesity was calculated. Two blood pressurerecordings were obtained from the right arm of asitting person after 30 min of rest at 5-min inter-vals, and their mean value was calculated. Instudy I and II hypertension was consideredpresent if the patient used antihypertensive drugsor had a blood pressure over 160/95 mmHg. Instudy III and IV the cutoff for the blood pressurewas 160/90 according to the WHO proposal forthe definition of the metabolic syndrome (Albertiet al. 1998).

5. Assays

Plasma glucose was measured with a glu-cose oxidase method using a Beckman GlucoseAnalyzer II (Beckman Instruments, Fullerton,CA). Serum insulin concentrationswere measured with radioimmunoassay(Pharmacia&Upjohn, Uppsala, Sweden) with aninterassay coefficient of variation (CV) of 5 %.Fasting serum C-peptide concentrations weremeasured by a radioimmunoassay (Linco Re-search, St. Charles, MO, USA) with an interassay

Methods

32

CV of 9%.GAD antibodies were determined by a modi-

fied radiobinding assay using 35 S-labeledrecombinant human GAD65 (Tuomi et al. 1999).The antibody titre is expressed in relative units(RU). The cut-off limit for positivity was set at 5RU, which represents the mean +3 SD of 296Finnish healthy control subjects.

Lipids and lipoproteins: Serum total cho-lesterol, HDL cholesterol subfractions (after pre-cipitation), and triglyceride concentrations weremeasured on a Cobas Mira analyser (HoffmanLaRoche, Basel, Switzerland). The LDL choles-terol concentrations were calculated using theFriedewald formula (Friedewald et al. 1972). Theformula was not used if serum triglyceride con-centration exceeded 4.0 mmol/l. ApolipoproteinA-I and A-II were determined withimmunoturbidimetric methods using commer-cially available kits (Boehringer Mannheim,Mannheim, Germany), while apolipoprotein Bconcentration was measured by animmunochemical assay (Orion Diagnostica,Espoo, Finland). The interassay CV forapolipoprotein A-I, A-II and B were 3.6, 2.1 and4.9 %, respectively.

LDL particle size: The LDL particle size(study IV) was determined by electrophoresis ongradient polyacrylamide gel (Lahdenperä et al.1995). The particle size of two isolated LDL sam-ples were used as reference, and their size wasmeasured by electron microscopy. The calculatedmean diameters of LDL standards were 27.9 and23.9 nm. The mean particle diameter of the ma-jor LDL peak was determined by comparing themobility of the sample to the mobility of the cali-brated LDL preparation run on each gel. The CVfor the intergel precision of the control samplethat was used, was 1.4 %. Small LDL particleswere defined as a particle size smaller than 25.5nm (Austin et al. 1988).

Urinary albumin concentration was meas-ured by radioimmunoassay (Pharmacia&Upjohn,Uppsala, Sweden) with a detection limit of 2 mg/l and an interassay CV of 5 %.

Estimation of insulin resistance: In studyIII we applied the Homeostasis Model Assess-ment (HOMA) to obtain an estimate of insulin

resistance. The following formula was used: in-sulin resistance (HOMA-IR) = fasting insulin(µU/ml) x fasting plasma glucose (mmol/l) / 22.5(Matthews et al. 1985) In the Botnia study theHOMA-IR correlated inversely with insulin sen-sitivity measured during a euglycaemichyperinsulinaemic clamp in 35-70 year old non-diabetic subjects (r=-0.46, p<0.001, n=132).

Glycaemic control: In study I HbA1c was de-termined by a high-pressure liquid chromatog-raphy method (Kyoto Daichii, Kyoto, Japan) witha reference value < 5.5%. In study II and IVHbA1c concentrations were measured by high-performance liquid chromatography (Diamat,Hercules, CA, USA) with a reference value forthe method of 4-6 %. The most recent measure-ment of HbA1c correlated strongly with the val-ues measured during the last 5 years (MODY3patients: r=0.91, p<0.001, n=23; LADA patients:r=0.78, p<0.001, n=49) and in study I and II thelast HbA1c value was used as a measure of gly-caemic control in the analysis. In study IV themean of HbA1c measurements done during thelast 5 years (median 4 measurements, range 1-18) was used as a measure of glycaemic control.

6. Statistical analysis

The values are presented as means ±SD, oras median and range (Study II) or percentages.The significance of differences between groupmeans has been tested with t-test or one-wayanalysis of variance after logarithmic transfor-mation of variables not showing a normal distri-bution or with the Mann-Whitney U-test (studyI). Adjustments for age and BMI have been donewhere appropriate. Differences between groupfrequencies were tested with Chi-squared orFisher´s exact test. Correlations were tested us-ing the Spearman rank correlation coefficients.The relationship between dependent variables,such as neuropathy, retinopathy,microalbuminuria, CHD and cardiovascularmortality, and independent variables were testedwith multiple logistic regression analysis usingan SPSS program for Windows. In study III amultiple logistic regression analysis was carried

Methods

33

out with CHD, previous myocardial infarctionor stroke as dependent variable and age, sex andthe metabolic syndrome or its components as in-dependent variables. In all analyses of diabeticcomplications (study I, II and IV) we used HbA1c

and duration of diabetes as continuous variablesand male sex as categorical variable. A p-valueless than 0.05 was considered statistically sig-nificant.

Methods

34

Results

1. Complications in patientswith MODY3 diabetes (I)

The MODY3 patients are compared with type1 and type 2 diabetic patients in Table 10. Twenty(53%) of the 38 MODY3 patients who took partin the ophthalmological examination had nosigns of retinopathy, 13 (34%) had mild NPDRand 5 patients (13%) had severe NPDR or PDR.There was no significant difference in the preva-lence of retinopathy among MODY3 and type 1and type 2 diabetic patients matched for dura-tion of diabetes and glycaemic control.

Distal neuropathy was found in 29% of theMODY3 patients compared to 13% in the type 1diabetic patients (p<0.001). The prevalence ofmicroalbuminuria was 19% in the MODY3 pa-tients, which did not differ from the prevalencein type 1 and type 2 diabetic patients (24 and

23%). Four MODY3 patients hadmacroalbuminuria and one was being treated foruraemia. The prevalence of hypertension wassimilar in MODY3 and type 1 diabetic patients(24.5 % vs 19 %), but lower than in type 2 dia-betic patients (53.7%, p<0.001).

Coronary heart disease was more often seenin MODY3 than in type 1 diabetic patients (16vs 4.5%), but less frequently than in the oldertype 2 diabetic patients (16 vs 33.3 %). One ofthe MODY 3 patients had a history of ischemicstroke with a persisting defect in visual fields.None of the MODY3 patients had signs of pe-ripheral vascular disease, i.e. ABI was higherthan 0.9 in all patients.

In a multiple logistic regression analysis withthe different diabetic complications as depend-ent variables, poor glycaemic control was asso-ciated with retinopathy (RR 3.1, p=0.03),microalbuminuria (RR 2.3, p=0.04) and elevatedvibration threshold (RR 5.0, p=0.03)(Table 11).

Table 10: Comparison between MODY3, type 1 and type 2 diabetic patients.

MODY3

Type 1 DM

Type 2 DM

Number (M/F) 57 (29/28) 111 (67/44) 159 (63/96) Age (years) 43.7 ± 15.7 38.6 ± 12.5 69.4 ± 11.6** Duration (years) 17. ± 12.8 23.1 ± 12.0 22.9 ± 6.1 BMI (kg/m2) 24.6 ± 4.5 25.1 ± 3.2 27.5 ± 4.9** WHR 0.89 ± 0.08 ND 0.93 ± 0.08 HbA1c (%) 7.3 ± 1.6 7.7 ± 1.5 7.6 ± 1.9 Cholesterol (mmol/l) 5.3 ± 1.0 5.0 ± 0.9 5.9 ± 1.3* HDL cholesterol (mmol/l) 1.40 ± 0.21 1.45 ± 0.40 1.25 ± 0.40* Triglycerides (mmol/l) 1.53 ± 0.82++ 1.01 ± 0.50 1.86 ± 1.04* AER > 20 µg/min (%) 19 24 23 Hypertension (%) 24 19 54** Diabetes therapy - Diet alone (%) 33 0 60.3 - Oral agents (%) 30 0 31.5 - Insulin (%) 37 100 8.2 Coronary heart disease (%) 16+ 4.5 33+

Values are mean ± SD, ND: not done ; *p< 0.01, **p<0.001 vs MODY or IDDM; +p<0.02, ++p<0.001 vs IDDM.

35

Table 11: The relative risk of diabetic complications associated with 1 % increase in HbA1c in MODY3 patients.

Complication RR (95% CI) p-value

Retinopathy 3.1 (1.1 – 8.6) 0.03

Microalbuminuria 2.3 (1.05 – 5.0) 0.04

Elevated vibration threshold 5.0 (1.15 – 22.1) 0.04

Results

Table 12. Clinical characteristics of type 2, LADA and type 1 diabetic patients

Type 2 diabetes

LADA Type 1 diabetes

Number (M/F) 59 (26 / 33) 59 (26 / 33) 111 (67 / 44) Age ( years) 72 (12) 74 (12) 39 (20)‡ Duration (years) 12 (10) 13 (9) 22 (16)‡ BMI ( kg/ m2 ) 28 (6.0) 27.8 (6.3)* 24.5 (3.6)¶ WHR - male 1.00 (0.09) 0.96 (0.12)* ND WHR - female 0.90 (0.12) 0.87 (0.09)* ND C-peptide ( nmol/l ) 0.76 (0.43) 0.45 (0.71)† ND C-peptide < 0.3 nmol/l (%) 3 32† ND HbA1c ( % ) 8.4 (2.3) 8.2 (2.3) 8.5 (1.9) Hypertension (%) 75 58* 21‡ Cholesterol ( mmol/l ) 5.5 (1.1) 5.5 (1.3) 4.8 (1.3) LDL cholesterol ( mmol/l ) 3.5 (1.1) 3.4 (1.2) 3.0 (1.1) HDL cholesterol ( mmol/l ) 1.19 (0.33) 1.20 (0.46) 1.41 (0.59)¶ HDL2 cholesterol ( mmol/l ) 0.35 (0.20) 0.43 (0.30)* ND HDL3 cholesterol (mmol/l) 0.84 (0.14) 0.79 (0.24) ND Triglycerides ( mmol/l ) 1.45 (0.70) 1.29 (0.64) 0.90 (0.60)¶ Diabetes therapy - Diet alone ( % ) 20 19 0 - Oral agents ( % ) 36 27 0 - Oral agents and insulin (%) 42 14† 0 - Insulin ( % ) 3 39† 100‡

Values are median (interquartile range). ND: not done. BMI, cholesterol, LDL and HDL cholesterol and triglycerides were adjusted for age before comparison between groups. * p<0.05 vs type 2 diabetes, † p<0.001 vs type 2 diabetes, ‡ p<0.001 vs type 2 diabetes or LADA, ¶ p<0.05 vs type 2 diabetes.

36

Duration of diabetes was associated with retin-opathy (RR 1.13, p=0.03) and male sex with el-evated vibration threshold (RR 6.7, p=0.04).

2. Complications in patientswith slowly progressingautoimmune type 1 diabetes(LADA) (II)

The LADA patients had lower BMI (p=0.04),WHR (p=0.02 for men and p=0.03 for women),and fasting C-peptide concentrations (p<0.001)and higher HDL2 concentrations (p=0.04) andless hypertension (58 vs 75 %, p=0.05) than thetype 2 diabetic patients (Table 12).

The prevalence of retinopathy (51 vs 56 %),microalbuminuria (27 vs 29 %), neuropathy (29vs 27 %) and CHD (58 vs 56 %) did not differbetween the LADA and the type 2 diabetic pa-tients (Figure 6). The type 1 diabetic patients hadlower prevalence of neuropathy (13 %, p=0.02)and CHD (4.5 %, p<0.001) and higher preva-lence of retinopathy (76%, p<0.001) comparedto the other groups. In a logistic regression analy-sis with moderate or severe retinopathy as thedependent variable, both duration of diabetes (RR1.18, p=0.01) and HbA1c (RR 1.88, p=0.03) wereassociated with retinopathy in the LADA but notin the type 2 diabetic patients.

Mortality data were obtained from the LADAand type 2 diabetic patients after a median fol-low-up period of 5.7 years. During this time 16

of the 90 LADA patients (18%) had died, com-pared to 186 of 929 type 2 diabetic patients (20%).Cardiovascular mortality was slightly lower inthe LADA than in the type 2 diabetic patients(7.4 vs 12.4 %, p=0.2).

In a logistic regression analysis HbA1c (RR1.78, p=0.02) was significantly associated withCHD in LADA, while age (RR 1.09, p=0.02) andmale sex (RR 7.55, p=0.006) were independentrisk factors for CHD in the type 2 diabetic pa-tients.

3. Cardiovascular morbidityand mortality associated withthe metabolic syndrome (III)

The data from 4483 patients (NGT n=1988,IFG/IGT n=798, type 2 DM n=1697) aged 35 -70 years were used to study the prevalence of themetabolic syndrome and its components and thecardiovascular risk associated with the metabolicsyndrome. The prevalence of the metabolic syn-drome and its components are shown in Table13. The prevalence of obesity was high in allgroups, especially in males; 76 % of men withNGT and 92% of diabetic men fulfilled the cri-teria for obesity.

The prevalence of dyslipidaemia and hyper-tension were both 2-fold increased in type 2 dia-betic patients compared to subjects with NGT.The prevalence of microalbuminuria was low insubjects with NGT and IFG/IGT (3-7%), while22 % of the diabetic men and 12% of the dia-betic women had microalbuminuria; in most sub-jects it was also associated with hypertension.

The prevalence of insulin resistance, definedas the highest quartile of HOMA-IR, was 2-foldincreased in subjects with IFG/IGT and 3-foldincreased in patients with type 2 diabetes com-pared with subjects with NGT. In women withNGT the prevalence of insulin resistance in-creased from 19 % in the age-decade 40-49 yearto 35 % in the age-decade 60-69 year (p<0.001).

Using the proposed WHO criteria the preva-lence of the metabolic syndrome was more com-mon in non-diabetic males than in females, i.e.

Figure 6. Prevalence (%) of complications in LADA, type 2 and type 1 diabetic patients.

0 20 40 60 80

ABI<0.9

CHD

Neuropathy

Microalb.

Retinopathy

Type 1 DMType 2 DMLADA

%

Results

37

15 and 10%, respectively, in subjects with NGT,and 64 and 42%, respectively, in subjects withIFG/IGT (Fig. 7). The sex-specific difference wasalmost abolished in the type 2 diabetic patients,i.e. 84% and 78%, respectively. In women withNGT the prevalence of the metabolic syndromeincreased from 6 % in the youngest (40-49y) to19 % in the oldest (60-69 y) age-decade(p<0.001).

Cardiovascular disease in relation to themetabolic syndrome: The lowest prevalence ofCHD was seen in NGT subjects without the meta-bolic syndrome and the highest in type 2 dia-betic patients with the metabolic syndrome (4.1%vs 27.1 %, p<0.001) (Fig. 8). In all subjects CHD,a history of myocardial infarction and stroke wasmore common in subjects with than without themetabolic syndrome (p<0.001) (Fig. 9). In a sub-set of 555 patients in whom the presence of CHDcould be based on Minnesota coding of ECG inaddition to clinical data, the prevalence of CHDwas even further increased in patients with themetabolic syndrome (35 % vs 8 %, p<0.001).

Cardiovascular risk in relation to the meta-bolic syndrome and its components: The pres-ence of the syndrome was associated with an in-creased risk of CHD, MI and stroke in all sub-jects, i.e. RR 2.96, 2.63 and 2.27 respectively(all p<0.001) and this risk was greater than therisk associated with any of the individual com-ponents. Dyslipidaemia was associated with anincreased risk for CHD (p<0.001) particularlyamong patients with type 2 diabetes (RR 1.84;p=0.001). Hypertension was associated with in-creased risk for CHD, particularly in subjects withNGT (RR 2.33; p<0.001).

Cardiovascular mortality in relation to themetabolic syndrome: During the median follow-up of 6.9 years 360 (10.0%) of the 3606 patientshad died, of them 209 (5.8%) died from CVD.Total (18.0 vs 4.6%; p<0.001) and cardiovascu-lar (12.0 vs 2.2%; p<0.001) mortality was in-creased in subjects with compared to subjectswithout the metabolic syndrome. In a multipleregression analysis with cardiovascular mortal-ity as the dependent variable and age, male sex,LDL cholesterol, current smoking as independ-ent variables, the relative risk of the metabolicsyndrome was 1.81 (p=0.002). If the metabolicsyndrome was replaced by its components in theanalysis, microalbuminuria was the strongest riskfactor for cardiovascular death (RR 2.80,p<0.001). The survival curves for all patients andIFG/IGT patients are shown in Figure 10 (Coxregression with adjustment for age and sex).

Figure 7. Prevalence (%) of the metabolic syndrome in 35-70 year old male and female subjects with normal (NGT), impaired (IFG/IGT) and diabetic glucose tolerance .

0

10

20

30

40

50

60

70

80

90

NGT IFG/IGT Type 2 DM

malefemale

%

Results

Table 13: Prevalence (%) of the components of the metabolic syndrome in males and females, aged 35-70 years, with NGT, IFG/IGT and type 2 diabetes.

NGT IFG/IGT Type 2 DM M F M F M F Obesity 76 36 86 51 92 78 Dyslipidaemia 29 16 45 31 54 56 Hypertension 23 24 31 35 55 59 Microalbuminuria 4 3 7 6 22 12 Insulin resistance* 25 25 58 59 87 89 * as the highest quartile of HOMA-IR

38

4. Complications in patientswith the metabolic syndrome(IV)

The patients with and without the metabolicsyndrome were matched for age, sex, duration ofdiabetes and glycaemic control. Neither was thereany difference in total cholesterol, LDL choles-terol concentrations nor in current smoking be-tween the groups. The patients with the meta-bolic syndrome had, as expected, higher BMI,WHR, fasting C-peptide, triglyceride (all p-val-ues <0.001) and apoB concentrations (p=0.009)

as well as lower total HDL cholesterol (p<0.001),HDL2 (p=0.008) and HDL3 cholesterol (p<0.001)concentrations. The prevalence of hypertensionwas also higher in the patients with than with-out the metabolic syndrome (81 % vs 27 %,p=0.001). The LDL particle size was smaller inthe patients with than without the metabolic syn-drome (25.4±1.4 vs 26.4±1.1 nm, p<0.001).

The prevalence of diabetic complications isseen in Table 14. To be able to study the role ofthe metabolic syndrome in the prediction of mi-cro- or macroalbuminuria, we excludedmicroalbuminuria from the definition of themetabolic syndrome for this analysis. The pa-tients with the metabolic syndrome had a higher

Figure 9. Prevalence (%) of cardiovascular disease in relation to the metabolic syndrome in all subjects.

0

5

10

15

20

25

CHD Prev. MI Prev. Stroke

MSDR+

MSDR-

%

Figure 8. Prevalence (%) of coronary heart disease in relation to the metabolic syndrome.

0

5

10

15

20

25

30

35

NGT IFG/IGT type 2DM

Allsubjects

SubjectswithECG

MSDR+MSDR-

%

Results

Follow-up (years)

1086420

Cum

Sur

viva

l

1,00

,99

,98

,97

,96

Follow-up (years)

1086420

Cum

Sur

viva

l

1,000

,998

,996

,994

,992

,990

All subjects

Figure 10. Cardiovascular mortality in relation to the metabolic syndrome in all subjects and in subjects with IFG/IGT.

Subjects with IFG/IGT

MSDR-

MSDR+

MSDR-

MSDR+ p<0.0001

p=0.10

39

prevalence of CVD (52 vs 21 %, p<0.001), mi-cro- or macroalbuminuria (23 vs 7%, p=0.003)and distal neuropathy (16 vs 6 %, p=0.048). In-terestingly, severe retinopathy was only seen inpatients with the metabolic syndrome.

Risk factors for complications: In a multi-ple logistic regression analysis (Table 15) withthe different complications as the dependent vari-able the metabolic syndrome was associated withCHD (RR 3.84, p<0.001) and microalbuminuria(RR 3.99, p=0.01), whereas glycaemic control

(mean of HbA1c

during the last 5 years) was re-lated to neuropathy (RR 1.69, p=0.04), retinopa-thy (RR 1.53, p=0.002) and microalbuminuria(RR 1.54, p=0.01). LDL particle size was inde-pendently of peripheral vascular disease associ-ated with neuropathy (RR 0.58, p=0.04). Whenthe metabolic syndrome was replaced with itscomponents in the regression analysis hyperten-sion was related to retinopathy (RR 2.24, p=0.04)and microalbuminuria (RR 5.39, p=0.005),whereas dyslipidaemia was associated with CHD(RR 2.81, p<0.001).

Table 15: Risk factors for diabetic complications in 170 type 2 diabetic patients ( Study IV)

Risk factor Coronary heart disease

Neuropathy Retinopathy Micro-albuminuria

HbA1c 0 + ++ +

Duration 0 0 + 0

Metabolic syndrome

++ 0 0 +

Male sex 0 0 0 +

Small LDL 0 + 0 0

0 = not significant, + = p<0.05, ++ = p<0.01

Results

Table 14: Chronic complications in diabetic patients with and without the metabolic syndrome.

MSDR+ MSDR- P-value Number (M/F) 85 (53/32) 85 (53/32) Retinopathy (%) - none - mild - moderate - severe

52 36 4 8

59 38 4 0

0.44 0.01

Macular edema (%) 6 8 0.77 AER >20µg/min (%)* 23 7 0.003 Distal neuropathy (%) Elevated vibration threshold (%)

16 45

6 38

0.048 0.49

Cardiovascular disease (%) 52 21 <0.001 Coronary heart d isease (%) - myocardial infarction (%)

46 12

18 2

<0.001 0.03

Cerebrovascular disease (%) 6 1 0.21 Peripheral vascular disease (%) 12 5 0.16 * AER excluded from the definition of the metabolic syndrome.

40

Discussion

1. Subjects and methods

1.1. Subjects

In Study I and II all available known MODY3and GADA-positive diabetic subjects from theBotnia Study in western Finland were included.The type 1 diabetic control subjects (Study I-II)were consecutive patients, representing morethan 90 % of the type 1 diabetic patients fromthe outpatient clinic at Jakobstad Hospital, wherethe majority of type 1 diabetic patients from thatregion are followed. The type 2 diabetic sub-jects in Study IV represented a random sample(aged 35-70 years) of type 2 diabetic patients fromthe Botnia Study. Thus, all patients (excludingthose used for ophthalmological comparisons)were from the same geographic region in west-ern Finland. The subjects in study III, includingall 35-70 year-old subjects from the Botnia Studyin Finland and Sweden, should be representa-tive for a Scandinavian population. Accordingto the results from the Botnia study the hetero-geneity of diabetes can be depicted as in Figure11. In addition to the subgroups described in thecurrent study there seems to be interaction be-tween type 1 and type 2 diabetes with possibleimpact on the phenotype of diabetes (Li et al.2000).

It is not always possible to exclude a selec-tion bias in cross-sectional studies (Study I, IIand IV). This could result in selection of surviv-ing patients if patients with complications dieprematurely. This is a particular problem in pa-tients with high age (Study II). Some additionalavailable information was used to address thisissue. First, the prevalence of CHD was similarin LADA and type 2 diabetic patients below 60years of age (36% vs. 36%). Second, total mor-

tality during a median follow-up of 5.7 years wassimilar in patients with LADA and type 2 diabe-tes (17% and 20%). Third, a subgroup of LADAand type 2 diabetic patients with short durationand lower age did not show any differences inprevalence of CHD. There was, however, a ten-dency for lower cardiovascular mortality in theLADA than in the type 2 diabetic patients (7.4%vs. 12.4%), that could imply that LADA patientshave a higher mortality from other diabetic com-plications. Obviously prospective studies areneeded to clarify this issue.

The limited number of patients in the studygroups is of course a problem when studying rarediseases (Study I). However, the results of thestudy are in line with other recently publishedstudies on complications in MODY3 (Velho etal. 1996; Doria et al. 1999). A prospective fol-low-up of MODY3 patients could further illus-trate the natural course of this subgroup of dia-betes.

1.2. Methods

Retinopathy: The diagnosis of DR was prin-cipally based upon fundus photography and thewell validated alternative classification of theWisconsin Epidemiological Study of DiabeticRetinopathy (Klein et al. 1986). In the type 1diabetic patients the classification was based upon(ophthalmologic) hospital records and photog-raphy, which did not allow a precise classifica-tion, and we chose to combine mild and moder-ate retinopathy into one group in contrast to se-vere retinopathy. Although the methods are notcompletely compatible, the method used in thetype 1 diabetic patients should give a reliableprevalence of any or severe retinopathy.

Microalbuminuria: In Study I, II and IV theassessment of AER was based upon albumin ex-cretion in overnight urine. If overnight urine wasnot available (< 10 %), the ACR in morning urine

41

was used. In Study III urine for the measurementof AER was collected either during the OGTT(n=1082) or overnight (n=1579). AER measuredovernight correlated with AER during the OGTT(r=0.605, p<0.001, n=442). For the comparisonof the two methods subjects brought in overnighturine on the morning of the OGTT. If we com-pare the prevalence of microalbuminuria, meas-ured overnight or during the OGTT, the preva-lence in the different groups are virtually thesame. Only in diabetic patients was the preva-lence of microalbuminuria lower using the AERduring the OGTT rather than overnight urine,which most likely can be explained by the factthat the OGTT was performed in diabetic pa-tients only if their fasting blood glucose concen-tration was < 10 mmol/l. When available (75%of the diabetic patients) we used AER from over-night urine.

Neuropathy: In all the subgroups studied thediagnosis of distal neuropathy was based uponthe same clinical examination and a symptomscore (Young et al.1993), which makes compari-son of the prevalence in different groups possi-ble. The method represents a relatively simplescoring technique for symptoms and signs whichis easy to apply in clinical practice. A similarmethod has proven to be useful in previous stud-ies (Young et al. 1993; Franklin et al. 1990). Themeasurement of vibration threshold was done bytwo different devices: Biothesiometer (Biomedi-cal Instruments, Ohio, USA) in Study I-II, andVibrameter (Somatomedic Productions,

Sollentuna, Sweden) in Study IV. The resultsfrom two different control groups were used. Thecontrol group for Biothesiometer represented allages while the control group for Vibrameter sub-jects aged 35-70. The results were corrected forage (Biothesiometer) and height (Vibrameter),respectively.

Cardiovascular disease: In studies I, II andIV ischaemic changes in resting ECG (Minne-sota code) was used in addition to the medicalhistory. The prevalence of CHD is obviously un-derestimated when using only questionnaires orhospital records (Study III). Several studies haveshown a higher prevalence of abnormalities inexercise ECG and heart perfusion in middle-ageddiabetic patients (Airaksinen 2001). This isclearly a limitation of the methodology and wecannot exclude that some of the patients withoutcoronary symptoms and with normal resting ECGnevertheless had CHD. However, as the patientshad been treated in the local hospitals we alsohad access to the hospital records. The diagnosisof CHD in Study III was based upon a history oftypical chest pain or use of nitroglycerine or ahistory of previous myocardial infarction. In asubset of patients we also used ECG analysis inaddition to clinical data for the diagnosis of CHD.As expected, the prevalence of CHD increasedin this subset, especially in subjects who fulfilledthe criteria for the metabolic syndrome (35 % vs8 %), giving a RR of 3.97 (p<0.001, adjusted forage and sex) for the metabolic syndrome.

Figure 11. The heterogeneity of diabetes.

type 1 DM15 %

type 2 MSDR+50 %

type 2 MSDR-10 %

Mixed type 1 & 2

10 %

MODY5 %

LADA10 %

Discussion

42

2. Complications in diabeticsubgroups

2.1. Retinopathy

In the patients with MODY3 diabetes (StudyI) the prevalence of mild retinopathy was 34%and severe non-proliferative or proliferative retin-opathy 13%, which was similar to the prevalenceseen in type 1 and type 2 diabetic patientsmatched for duration of diabetes and HbA

1c. The

current study is in agreement with results fromother studies in MODY3 patients and shows byusing qualified methods for assessing retinopa-thy that MODY3 patients can develop severeretinopathy (Velho et al. 1996; Iwasaki et al.1998; Doria et al. 1999). The level of glycaemiccontrol was a strong determinant of retinopathy,with an increase in the risk ratio by 3.1 for each1 % increase in HbA

1c. Although this figure is

higher than that observed in Swedish type 1 dia-betic patients (1.37 with a 95% confidence in-terval of 1.14 to 1.64) (Henricsson et al. 1996),it should be kept in mind that the confidence in-terval is wide (1.1 to 8.6) due to the small numberof subjects studied. In addition to hyperglycae-mia, duration of diabetes was associated withretinopathy. Based on results from screening inMODY3 families, duration is obviously under-estimated in many patients as the disease can beundiagnosed for a long time, with possible in-fluence on the development of complications.

We observed no differences in the prevalenceof retinopathy between LADA and matched type2 diabetic patients (56 % vs 51 %). However, theprevalence was clearly lower than in type 1 dia-betic patients (76%) (Table 16). The prevalenceof retinopathy in both the type 1 and type 2 dia-betic groups were in the reported range (Klein etal. 1984a; Klein et al. 1984b; Henricsson et al.1996). Both duration and glycaemic control wererelated to retinopathy in the LADA patients, withan increase in the risk ratio of 1.88 for each per-cent increase in HbA

1c.

There was no significant difference in the

prevalence of retinopathy between patients withand without the metabolic syndrome (48 % vs.41 %) (Study IV). Interestingly, severe retinopa-thy was only seen in patients with the metabolicsyndrome. Despite this, the metabolic syndromedid not predict overall retinopathy or moderateor severe retinopathy in multiple logistic regres-sion analyses. This can, of course, be due to therelatively small number of patients with severeretinopathy. When the metabolic syndrome wasreplaced by its individual components, hyperten-sion was an independent risk factor for retinopa-thy (RR 2.24, p=0.04). In the UKPDS tight con-trol of blood pressure decreased significantly theprogression rate of retinopathy (UKPDS 1998),and the incidence of retinopathy was associatedwith higher blood pressure (Stratton et al. 2001).

2.2. Micro- and macroalbuminuria

In type 1 diabetic patients microalbuminuriahas been a strong predictor of subsequent devel-opment of diabetic nephropathy (Mogensen etal. 1984; Mathiesen et al. 1984). In patients withtype 2 diabetes elevated albumin excretion hasbeen regarded both as a marker of incipient ne-phropathy and as a marker of vascular damageand cardiovascular morbidity and mortality(Mogensen et al. 1984; Dinneen et al.1997). Inaccordance with some other studies both micro-and macroalbuminuria was observed in theMODY3 patients (Velho et al. 1996; Doria et al.1999) (Study I). Four MODY3 patients hadmacroalbuminuria, and one of them was beingtreated for uraemia. In the MODY3 patientsHbA

1c, but not the duration of the disease or hy-

pertension, was associated withmicroalbuminuria. These data and the low preva-lence of the features of the metabolic syndromestrongly support the view that MODY3 patientsare susceptible to developing nephropathy as aconsequence of elevated blood glucose levels.

In the LADA patients (Study II) male sex butnot hypertension was associated withmicroalbuminuria. This could either reflect thelower prevalence of hypertension in the LADApatients or suggest that in these patients,

Discussion

43

microalbuminuria is not part of the metabolicsyndrome as suggested for type 2 diabetes (Groopet al. 1993). Although we do not know whethermicroalbuminuria in LADA patients reflects in-cipient nephropathy or general vascular damage,the lower prevalence of the features of the meta-bolic syndrome in LADA patients supports theformer view. Also, in the LADA patientsmicroalbuminuria was associated with retinopa-thy. This association is in keeping with findingsin type 1 diabetic patients, in whom retinopathyis an almost obligate corollary ofmicroalbuminuria.

To study the role of the metabolic syndromein the prediction of micro-or macroalbuminuria,we excluded microalbuminuria from the defini-tion of the syndrome for this part of the study.The patients with the metabolic syndrome had asignificantly higher prevalence ofmicroalbuminuria or macroalbuminuria (23 %vs 7 %, p=0.003) than those without the syn-drome. In the multiple regression analysis, themetabolic syndrome (RR 3.99, p=0.01) was thestrongest predictor of albuminuria in addition tomale sex (RR 3.41, p=0.04) and the mean HbA1c

concentration (RR 1.54, p=0.01). Poor glycae-mic control (Gall et al. 1997; Forsblom et al.1998a) and male sex (Gall et al. 1997) have ear-lier been reported as risk factors formicroalbuminuria. These results support the viewthat microalbuminuria is associated with themetabolic syndrome.

2.3. Neuropathy

In all the subgroups of diabetes the samemethod was used to assess the prevalence of distalneuropathy. In the MODY3 patients (Study I)we found distal neuropathy in 24% of ourMODY3 patients compared to 13 % in the type1 diabetic patients (p<0.001). In a French studyneuropathy was diagnosed only in 1 out of 27MODY3 patients (Velho et al. 1996). However,this study based diagnosis of neuropathy on pa-tient records. For comparison, in the UK Hospi-tal Clinic Study (Young et al. 1993) almost simi-lar diagnostic criteria as used in this study gavea prevalence of 22.7% in type 1 diabetic (me-dian age of 45 years and duration of 13 years)

Table 16: Prevalence (%) of chronic c omplications in diabetic subgroups.

MODY3

n=57

LADA

n=59

Type 1

n=111

Type 2

MSDR+

n=85

Type 2

MSDR-

n=85

Age (years) 44±16 70±11 39±12 59±9 61±7

Duration (years) 17±13 13±6 23±12 8±6 9±6

HbA1c (%) 7.6±1.3 8.3±1.5 8.8±1.5 7.9±1.6 7.5±1.4

Any retinopathy

- severe

47

13

51

9

76

21

48

8

41

0

Microalbuminuria

- macroalbuminuria

19

8

27

4

24

6

23

4

7

1

Distal neuropathy 29 29 13 16 6

CHD 16 56 4.5 46 18

Discussion

44

and 32.1% in type 2 diabetic patients. If we usedthe vibration threshold measured by theBiothesiometer as the dependent variable andduration of diabetes and HbA1c as independentvariables, only HbA1c predicted sensory neuropa-thy. If we used distal neuropathy as the depend-ent variable, only duration of diabetes was weaklyassociated with neuropathy. We think that themost likely explanation for this discrepancy isthat vibration threshold represents a more stand-ardised and sensitive indicator of distal sensoryneuropathy than the clinical score.

The prevalence of distal neuropathy was 29% in the LADA and 27 % in the matched type 2diabetic patients, which seem to be in the ex-pected range (Young et al. 1993; Ziegler et al.1993). The current study, with the LADA pa-tients representing a group with lower C-pep-tide concentrations, does not confirm the resultsfrom a prospective Finnish study in which lowinsulin values predicted peripheral neuropathy(Partanen et al. 1995). Neither does it confirmthe theory that GADA could play a role in thepathogenesis of diabetic nephropathy (Kaufmanet al. 1992; Hoeldtke et al. 2000). As glutamicacid decarboxylase (GAD) is widely distributedin the nervous system, it has been suggested thatcirculating GADA could have an impact on thefunction of GAD. Another explanation could bethat GADA reflects the presence of a systemicinflammatory process with effects on both the β-cell and peripheral nervous system (Hoeldtke etal. 2000).

The prevalence of distal neuropathy was morecommon in type 2 diabetic patients with the meta-bolic syndrome than in those without (16% vs6%; p=0.048), suggesting that the metabolic syn-drome might modify the development of neuropa-thy (Study IV). However, when duration of dia-betes, mean HbA1c and the metabolic syndromewere included in a multiple logistic regressionanalysis, only mean HbA1c was an independentrisk factor. Of note, peripheral vascular diseasewas also a strong independent predictor of neu-ropathy (RR 10.1; p=0.004). It is, however, noteasy to distinguish between symptoms and signsof peripheral vascular disease and neuropathyclinically. A low ABI signifying peripheral vas-

cular disease has previously been reported to pre-dict neuropathy (Adler et al. 1997). A novel find-ing was that the LDL particle size (but not themetabolic syndrome) was associated with neu-ropathy and that this association was independ-ent of the presence of peripheral vascular dis-ease. How could the association between smalldense LDL particles and neuropathy be recon-ciled? Oxidative stress and impaired n-6 essen-tial fatty acid metabolism contribute to impairednerve conduction velocity in diabetic rats and canbe corrected by antioxidants like γ-linolenic acidand α-lipoic acid (Van Dam et al. 1995; Cameronet al. 1998). Small dense LDL particles are vul-nerable to oxidation in the vessel wall (Steinbergand Lewis 1997), but it is not known whetherthe same is true in peripheral nerves. It is alsopossible that small dense LDL particles couldcontribute to impaired microcirculation of theperipheral nerves and thereby cause impairednerve function.

2.4. Cardiovascular disease

Coronary heart disease was seen in 16% ofthe MODY3 patients, which was higher than inthe type 1 (4.5%) but lower than in the type 2diabetic patients (33%). This figure should alsobe contrasted against a prevalence of 53 and 40%, respectively, in newly diagnosed Finnish maleand female type 2 diabetic patients aged < 50years (Uusitupa et al. 1985). One possible expla-nation for the lower frequency of hypertensionand CHD in MODY3 than in type 2 diabetic pa-tients, could be that MODY3 patients show nor-mal or even increased insulin sensitivity and fewfeatures of the metabolic syndrome (Lehto M etal. 1997; Pearson et al. 2001; Tripathy et al.2001).

The patients with the metabolic syndrome(Study IV) reported a significantly higher preva-lence of CHD and previous myocardial infarc-tion compared to the patients without the meta-bolic syndrome (Table 14). There were no dif-ferences between the patients with and withoutthe metabolic syndrome with respect to glycae-mic control, current smoking or LDL cholesterol

Discussion

45

concentration. In addition to high triglyceride andlow HDL cholesterol concentrations, the patientswith the metabolic syndrome also had smallerLDL particles compared to the patients withoutthe syndrome. Small dense LDL particles arehighly atherogenic and may explain part of theincreased cardiovascular risk associated withhigh triglycerides and low HDL cholesterol con-centrations (Gray et al. 1997; Lamarche et al.1997). A newly published study demonstrated arelationship between the metabolic syndrome (de-fined according to the WHO proposal), smallLDL particle size pattern and the occurrence ofpreclinical atherosclerosis (intima-media thick-ness) in healthy 58-year-old men (Hulthe et al.2001). The definition of dyslipidaemia(triglycerides >1.7 mmol/l or HDL cholesterol<0.9 in males or <1.0 in females) had a sensitiv-ity of 73 % and a specificity of 80 % to predictsmall dense LDL particles, defined as a particlesize smaller than 25.5 nm (Austin et al. 1988).The only risk factor for CHD identified in themultiple regression analysis was the metabolicsyndrome with a risk rate of 3.84 (p<0.001). Thisincreased risk was mainly explained by the pres-ence of dyslipidaemia (RR 2.8, p=0.007). In theregression analysis, the mean HbA1c did not comeout as a significant risk factor for CHD. Althoughthere are prospective studies (Turner et al. 1998;Lehto S 1997; Haffner 1999) suggesting an as-sociation between hyperglycaemia and CVD, thisrelationship is relatively weak and may be over-shadowed by other risk factors like the other com-ponents of the metabolic syndrome (Laakso1999). In fact, we only saw an association be-tween hyperglycaemia and CVD in the LADApatients, a subgroup with few features of themetabolic syndrome (Study II).

3. Cardiovascular risk and themetabolic syndrome

Prevalence of the metabolic syndrome: Inprevious studies the prevalence of the metabolicsyndrome has varied widely mainly due to dif-ferent definitions of the syndrome or selection ofdifferent subgroups (Rantala et al. 1999). In the

current study (Study III) the metabolic syndromewas present in about 10% of subjects with NGT,50% of subjects with IFG/IGT and 80% of sub-jects with type 2 diabetes. In a Finnish popula-tion-based study, a metabolic syndrome definedas clustering of dyslipidaemia and insulin resist-ance (defined as abnormal glucose tolerance orfasting plasma insulin ≥13 mU/l) was present in17% of non-diabetic men and 8 % of women(Vanhala et al. 1997). In the ARIC study popu-lation a combination of hypertension (blood pres-sure >140/90mmHg or use of antihypertensivetreatment) and dyslipidaemia (triglycerides >2.26mmol/l or HDL <0.9 mmol/l in men or <1.2 inwomen) was observed in 10 % of the subjects(Liese et al. 1997). In a newly published study of391 healthy 58-year old Swedish men the preva-lence of the metabolic syndrome (according tothe WHO proposal) was 16 % (Hulthe et al.2000). This is very similar to the figure of 15 %in our NGT male subjects.

The definition of the metabolic syndrome:The prevalence of the metabolic syndrome andits components is strongly dependent upon thedefinition of the different components of the syn-drome. Obesity defined by a high WHR wasclearly more common than obesity defined asBMI >30 kg/m2. Using the proposed limits forWHR of 0.9 for men and 0.85 for women 76 %of men and 36% of women with NGT would beconsidered abdominally obese whereas the cor-responding figure using only BMI >30 kg/m2

would be 10% and 14%, respectively. A highercutoff level for WHR (1.0 in male and 0.9 in fe-male subjects) increased the relative risk of CHDassociated with the syndrome in NGT subjectsfrom 1.73 (p=0.04) to 2.36 (p=0.002) but hadlittle influence on the risk in subjects with IFG/IGT and type 2 diabetes.

The criteria for dyslipidaemia were more de-pendent upon the presence ofhypertriglyceridemia than of low HDL-choles-terol, which could present a problem in patientswith type 2 diabetes, in whom elevated triglyc-eride levels may be secondary to hyperglycae-mia (Taskinen et al. 1996).

The inclusion of microalbuminuria as part of

Discussion

46

the metabolic syndrome has been questioned(Balkau et al. 1999) due to its rarity and lack ofassociation with insulin resistance in some stud-ies (Hodge et al. 1996; Zavaroni et al. 1996). Inthe current study a multiple logistic regressionanalysis with microalbuminuria as dependentfactor clearly showed that all other componentsof the syndrome, except for obesity, but includ-ing insulin resistance were associated withmicroalbuminuria (Table17). Whether insulinresistance is involved in the pathogenesis ofmicroalbuminuria may be less important than thefact that microalbuminuria indicates an advancedstage of CVD thereby is associated with a highcardiovascular mortality (Dinneen et al. 1997).

Insulin resistance and the metabolic syn-drome: As many of the components of the meta-bolic syndrome are associated with insulin re-sistance, it has been suggested that the syndromeshould be called the insulin resistance syndrome(Balkau et al. 1999). In the Bruneck Study theprevalence of insulin resistance (defined as topquintile of HOMA-IR) was 66 % in subjects withIGT and 84 % in subjects with type 2 diabetes(Bonora et al. 1998). The corresponding figurein the current study using the top quartile ofHOMA-IR were very similar, 59 % in IFG/IGTand 88 % in type 2 diabetic patients. Why is in-sulin resistance then not included as a compo-nent of the syndrome also in subjects with diabe-tes in the WHO proposal? There are several ex-planations for this. As insulin resistance definedas top quartile of HOMA is seen in about 90% ofpatients with type 2 diabetes, the prevalence of

the metabolic syndrome would not change muchif insulin resistance was included as a compo-nent in this group (males: from 84% to73%; fe-males: 78 to 71%). Secondly, much of the insu-lin resistance in type 2 diabetes may be second-ary to elevated glucose (Yki-Järvinen 1992) andfree fatty acid (FFA) levels (Randle et al. 1963;Boden 1997). It is not known whether the car-diovascular risk associated with secondary insu-lin resistance is the same as that associated withinsulin resistance in the prediabetic state. Finally,and probably the most important argumentagainst including insulin resistance as a compo-nent of the syndrome in patients with type 2 dia-betes is that it is very difficult to quantitate insu-lin resistance in a hyperglycaemic subject.

On the other hand, the finding that insulinresistance predicted CVD in subjects with IFG/IGT suggests that it may be worthwhile to con-sider it for the diagnosis of the metabolic syn-drome in this subgroup. If we included insulinresistance in the definition of the metabolic syn-drome also in the IFG/IGT group, the prevalenceof the syndrome would be 33 % in females and45 % in males compared with 42 % and 64 %without it.

The metabolic syndrome and cardiovascu-lar risk: The clinical importance of the meta-bolic syndrome is related to its putative impacton cardiovascular morbidity and mortality; in thepresent study (Study III) the prevalence of CHD,myocardial infarction and stroke were about 3-fold higher in subjects with than without themetabolic syndrome. Importantly, the presence

Table 17: Multiple logistic regression analysis with microalbuminuria as dependent variable and the components of the metabolic syndrome in 2414 subjects aged 35 – 70 years.

Components RR (95 % CI) p-value

Obesity 1.23 (0.78 – 1.92) 0.4

Dyslipidemia 1.54 (1.12 – 2.11) 0.007

Hypertension 2.77 (1.99 – 3.87) <0.001

Insulin resistance 2.56 (1.73 – 3.81) <0.001

Adjusted for age and sex

Discussion

47

of the metabolic syndrome was associated withan odds ratio for cardiovascular mortality of 1.8.However, the number of deaths was relativelysmall, without enough power to clearly definerisk of total and cardiovascular death in sub-groups (Figure 10). Therefore the data regard-ing mortality should only be considered sugges-tive.

Which of the components or combinationsof components are associated with the increasedcardiovascular risk? The combination of obesityand hypertension or dyslipidaemia was the mostcommon risk factor combination in subjects withIFG/IGT and diabetes. However, given the highfrequency of obesity in this population it had lit-tle influence on the relative risk of CHD in sub-jects with NGT, IFG/IGT and diabetes (1.15, 1.79and 1.48). The combination of hypertension anddyslipidaemia was the second most common riskfactor combination in subjects with NGT (8 and5% in men and women), IFG/IGT (16 and 14%)and diabetes (31 and 36%), and thereby had thegreatest influence on the CHD risk associatedwith the syndrome. While hypertension wasstrongly associated with CHD in the NGT group

(RR 2.33;p<0.001) dyslipidaemia was related toCHD in the patients with type 2 diabetes (RR1.84;p=0.001). It is also possible that treatment ofhypertension and dyslipidaemia could influencethe results. The latter is unlikely because onlyabout 1% of the patients received lipid-loweringtreatment. Antihypertensive therapy varied from15.5% in the NGT to 21.9% in the IFG/IGTgroup and 46.3% in the type 2 diabetic patients,with even distribution of different treatmentmodalities (diuretics 28%, betablockers 42%,calcium antagonists 21%, ACE inhibitors 29%).

In the current study microalbuminuria wasassociated with a markedly increased risk of car-diovascular death (RR 2.80; p < 0.001). This isin congruence with several other studies in whichmicroalbuminuria has been a strong predictor ofcardiovascular morbidity and mortality (Kuusistoet al. 1995; Jensen et al. 1997; Dinneen et al.1997; Borch-Johnsen et al. 1999).Microalbuminuria has also been related to anincreased transcapillary albumin leakage (Jensenet al. 1995), suggesting that microalbuminuriarepresents a surrogate measure of endothelial dys-function.

Discussion

48

Summary and conclusions

1. MODY3 (Study I): Diabetic retinopathy,nephropathy and neuropathy were as commonin MODY3 patients as in type 1 and type 2 dia-betic patients matched for duration and glycae-mic control and these complications were clearlydetermined by the degree of glycaemic control.As subjects with MODY3 diabetes seem to besensitive to elevated glucose levels and the dis-ease can be undiagnosed for years, screening fordiabetes in families with MODY3 diabetes shouldbe recommended to initiate early treatment andthereby prevent the development ofmicroangiopathic complications.

2. LADA (Study II): LADA patients havefewer features of the metabolic syndrome thantype 2 diabetic patients, and glycaemic controlseems to be a more important risk factor for retin-opathy and CHD in LADA than in type 2 dia-betic patients. The latter finding could be due tothe fact that fewer risk factors are operative inpatients with LADA. The tendency for lower car-diovascular mortality in the LADA comparedwith the type 2 diabetic patients has to be con-firmed in a larger prospective study.

3. The metabolic syndrome (Study III): Theclustering of cardiovascular risk factors calledthe metabolic syndrome was seen in about 10%of subjects with NGT, 50% of subjects with IFG/

IGT and 80% of subjects with type 2 diabeteswhen using a definition based on that proposedby the WHO. It confers an increased risk of car-diovascular morbidity and mortality. The identi-fication of the metabolic syndrome may there-fore be important in the risk assessment and treat-ment of patients not only with diabetes, but alsowith hypertension or obesity. The WHO proposalmay provide a useful tool for the comparison ofdata among studies.

4. Influence of the metabolic syndrome onchronic diabetic complications (Study IV): Inaddition to hyperglycaemia the risk of chronicdiabetic complications is modified by the pres-ence of some of the components of the metabolicsyndrome, i.e. hypertension increases the risk forretinopathy and albuminuria, whereas the pres-ence of small dense LDL particles seems to in-crease the risk for neuropathy. These data notonly re-emphasise the need for multifactorial in-tervention in patients with type 2 diabetes, butalso provide a putative novel target for treatmentinfluencing LDL particle size.

Taken together, the genetic, immunologicaland metabolic heterogeneity of diabetes is an im-portant determinant of the outcome of the dis-ease.

49

Acknowledgements

This work was carried out at the centres ofthe Botnia Study in western Finland, at the De-partment of Medicine at the Helsinki UniversityCentral Hospital and at the Wallenberg labora-tory at the Malmö University Hospital. I like toexpress my warmest gratitude to a number of peo-ple, who in different ways made this work possi-ble.

First of all I am greatly indebted to my super-visors, professors Leif Groop and Marja-RiittaTaskinen. Professor Leif Groop, I admire yourgreat enthusiasm, encouraging attitude andfriendly approach during all the stages of thiswork. Professor Marja-Riitta Taskinen, your greatexperience and wide knowledge in the field ofdiabetic research and your constructive advicehave been essential for this thesis.

The careful review and valuable advice of thetwo reviewers, Professor Markku Laakso andDocent Paula Summanen, had a great impact onthe final version of the manuscript. Thank youfor many valuable comments. David Laaksonenis thanked for revising the language of my the-sis.

I owe my warmest thanks to all my co-work-ers for good collaboration. I especially want tomention:

-Tiinamaija Tuomi, for valuable advice andhelp during many critical steps in this process

-Marianne Henricsson, for teaching me aboutretinopathy and its grading and for doing a lot ofwork in my studies

-Peter Almgren, for all the kind help and valu-able advice regarding statistical methods andproblems

-Carol Forsblom, for enthusiastic discussionsabout microalbuminuria, research methods andhelp with various theoretical and practical prob-lems

-Markku Lehto, for stimulating collaborationregarding MODY and related genetics

-Leena Sarelin, with whom I have conductedthese studies and travelled around the Botnia

region to study the patients. You have been es-sential for the management of the studies and Iam grateful to all the work you have done.

The Botnia Study has been the soil fromwhich these studies have grown. The membersof the Botnia Study research team have been es-sential for the accomplishment of this work. Iadmire the excellent work you do and the enthu-siasm you always have shown in your work. Iwant to thank all of you from the different BotniaCentres: Björn Forsén, Maja Häggblom andMonika Gullström in Närpes; Lisbeth Åkermanand Inga-Britt Stenback in Malax-Korsnäs; KajLahti, Susanne Salmela and Sonja Paulaharju inVasa; Björn-Olof Ehrnström, Nils Holmströmand Helena Iilahti in Korsholm; Leena Sarelinand Gudrun Eklöv in Jakobstad. I also wish tothank the Botnia-team in Helsinki with CarolaSaloranta, Seija Heikkinen, Arja Tapio, HanneleHildén and Viveka Metsäaho for good collabo-ration. I am also grateful to Toini Virkkala andBeatrice Asplund at the Central Hospital inKarleby and to the staff at the Health Centres inPerho and Lestjärvi for technical help and sup-port.

I wish to thank all the diabetic patients andtheir family members who have taken part in theBotnia Study and made this work possible. I hopethe project will produce new knowledge aboutthe pathogenesis and prevention of diabetes.

During this work I have visited theWallenberg Laboratory in Malmö many times,and I want to express my thanks to all the stafffor their kind reception. Especially I want to men-tion Marju Orho-Melander, Esa Laurila and UllaHäggström.

Inspiring teachers over the years have influ-enced my own interest in diabetes. I want to es-pecially mention Hilkka Hiekkala at the AuroraHospital in Helsinki, Christel Pakarinen at theHospital in Jakobstad and Michael Nissén at VasaCentral Hospital. Your enthusiastic concern forthe diabetic patient has always inspired me in

50

my work.My own possibilities to do research in the field

of diabetes have greatly been influenced by apositive attitude from my long-standing chiefphysician, Per-Erik Wingren at the Hospital ofJakobstad. Without your kind support, this workwould never have been possible.

The archipelago of Jakobstad has offered merecreation from this many times stressing proc-ess during the last years. Long-distance skatingin the winter and sailing and canoeing in thesummer together with good friends have givenme valuable relaxation and new energy.

Finally, I owe my deepest gratitude to my fam-ily - my wife Anne and my sons Björn, Rasmus,Anders and Ludvig - for your support and pa-tience during these years. Thank you for sharingthe joys and sorrows throughout the work on thisthesis.

This work has been financially supported bygrants from the Finska Läkaresällskapet, theLehikoinen Foundation, the Otto A. Malm Foun-dation and the Wilhelm and Else StockmannFoundation. They are all gratefully acknowl-edged.

Jakobstad, July 2001

Bo Isomaa

51

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