ABSTRACT Interindividual variation of the _IGF2-INS-TH_ region influences risk of a variety of diseases and complex traits. Previous studies identified a haplotype (designated

_IGF2-INS-TH_*5 and tagged by allele A of _IGF2 ApaI_, allele 9 of _TH01_ and class I alleles of _INS_ VNTR) associated with low body mass index (BMI) in a cohort of UK men. We aimed here

both to study whether previous findings relating *5 with weight are replicated in a different cohort of men (East Hertfordshire) characterised in more phenotypic detail and to test the

effect of this haplotype on related subphenotypes. The PHASE program was used to identify *5 and not*5 haplotypes. A total of 490 haplotypes were derived from 131 men and 114 women, the

_P_<0.001). This haplotype also marks nearly two-fold lower 120 min insulin (_P_=0.004) as well as low baseline insulin (−11.02 pmol/l, _P_=0.043) and low 30 min insulin (−64.44 pmol/l,

_P_=0.072) in a glucose tolerance test. No association between *5 and these traits was found in women. Our results, taken together with other data on IGFII levels and TH activity, point to

the importance of *5 as an integrated polygenic haplotype relevant to obesity and insulin response to glucose in men. SIMILAR CONTENT BEING VIEWED BY OTHERS UNDERSTANDING THE GENETIC

ARCHITECTURE OF THE METABOLICALLY UNHEALTHY NORMAL WEIGHT AND METABOLICALLY HEALTHY OBESE PHENOTYPES IN A KOREAN POPULATION Article Open access 26 January 2021 DISSECTING THE CLINICAL

RELEVANCE OF POLYGENIC RISK SCORE FOR OBESITY—A CROSS-SECTIONAL, LONGITUDINAL ANALYSIS Article 25 June 2022 EXPLORING THE GENETIC INTERSECTION BETWEEN OBESITY-ASSOCIATED GENETIC VARIANTS AND

INSULIN SENSITIVITY INDICES Article Open access 06 May 2025 INTRODUCTION Adult obesity is a common multifactorial disorder, which causes or exacerbates many health problems including type

II diabetes, coronary heart disease, hyperlipidaemia, hypertension, certain forms of cancer, respiratory complications and osteoarthritis of large and small joints.1, 2 Body mass index

(BMI), waist circumference (WC) and waist–hip ratio (WHR) are the most frequently used indicators of obesity and higher levels significantly reduce life expectancy.2, 3 While BMI reflects

obesity in general, WC and WHR are related to central obesity, that is, excess of body fat in the abdomen.4 It is well established that body weight and composition are substantially

determined by genetic factors that are likely to be multiple and interacting, with most single variants producing only a moderate effect.5 Estimates of heritability for obesity, measured for

BMI, have been found to be between 40 and 55% in most studies, although with estimates of up to >80% in twin studies.6 Sex differences in heritability for BMI and evidence of

sex-specific effects in BMI have been reported in a study of approximately 37 000 complete twin pairs, suggesting that there may be differences between men and women in the genetic factors

that influence variation of this trait.7 Over 600 genes, markers and chromosomal regions have been associated or linked with human obesity phenotypes.8 One such region is the

_IGF2_-_INS_-_TH_ gene cluster on human chromosome 11p15. We have previously detected a polymorphic variant of _IGF2_ in humans that associates with 10% differences in circulating levels of

IGFII and is associated with adiposity in the Northwick Park Heart Study II (NPHSII), a cohort of unrelated UK Caucasian men.9 More detailed analyses of the most common microsatellite loci

tagging haplotypes of the _IGF2_-_INS_-_TH_ cluster as defined by a set of SNPs identified in _IGF2_,10 _TH01_ alleles11 and _INS_ VNTR class I subclasses12 has identified an extended

haplotype designated _IGF2_-_INS_-_TH_*5 (hereafter *5), consisting of allele A of _IGF2 ApaI_, allele 9 of _TH01_ and a subset of class I alleles of _INS_ VNTR, which is associated with

lower BMI and fat mass in the NPHSII cohort.13 _In vitro_ functional studies (references in Rodríguez _et al_13) are also consistent with any gene of the _IGF2_-_INS_-_TH_ cluster

influencing weight. However, replication of genetic association in independent samples is important.14 In addition, significant results observed on related subphenotypes of a complex disease

may provide further insight into possible mechanism.15 We present here a follow-up analysis of _IGF2_-_INS_-_TH_*5 haplotype in an independent cohort of unrelated Caucasian individuals in

which weight association and relevant subphenotypes including response to glucose tolerance test (GTT) are examined. MATERIALS AND METHODS STUDY DESIGN The identification of the *5 haplotype

was carried out as previously described.13 In brief, we used the PHASE program version 2.016 in order to determine, with a predefined level of confidence set at ≥90%, the two haplotypes

resulting from the combination of the _TH01_ microsatellite and the SNPs _IGF2 ApaI_ and _INS HphI_ for each one of the individuals analysed. We have previously shown that the resulting

haplotypes tag the most common haplotypes of 14 polymorphisms spanning this gene cluster, giving haplotypic analyses with an increased power (due to fewer missing data) and a reduced risk of

false positive findings related to low-frequency haplotypes.13 The _IGF2 ApaI_, _INS HphI_ and _TH01_ sites were genotyped as previously described (Rodríguez _et al_13 and references

therein) from a sample of 245 unrelated UK Caucasian individuals (131 men and 114 women) from the East Hertfordshire cohort (EH). These subjects were selected from among all births in the

county of Hertfordshire UK during 1911–1930, who were followed forward and found to be alive and still resident there in 1990 to 1995. All births in Hertfordshire, from 1911 onward were

reported by the attending midwife and were recorded in ledgers. Health visitors saw the babies throughout infancy, and at 1 year of age, the babies were weighed. We computerised the ledger

entries for these subjects. Using the National Health Service Central Register (NHSCR) at Southport, we traced the cohort. Twins, triplets, and singletons who died during childhood, and boys

and girls for whom data on weight at birth and at 1 year of age were missing, were excluded. Data on many boys born in 1911–1923 were not submitted for tracing because forename, necessary

for tracing, was not recorded. We could not trace girls born before 1923 because the new names on many who married could not be determined. Ledger details were insufficient to enable NHSCR

to trace 15% of the boys and 27% of the girls.17 The subset selected for detailed evaluation of obesity-related phenotypes comprised those willing to undergo an oral GTT, they did not differ

significantly from the larger group in regard to birthweight or socioeconomic status. Both genders were nearly equally represented (53.5% of men _vs_ 46.5% of women), with similar age

distributions: age ranging in men from 59 to 70.3 years (mean±SE=64.09±0.19); and in women, from 60.3 to 71.5 years (mean±SE=64.00±0.18). The 21 traits analysed were: birthweight, weight at

1 year, weight, height, BMI, WC, hip circumference, WHR, plasma triglycerides, systolic blood pressure, diastolic blood pressure, fasting plasma concentrations of proinsulin, traits related

to oral GTT (plasma concentrations of insulin and glucose at baseline, at 30 and at 120 min after an oral load of 75 g of glucose, and insulin area under the curve during the GTT), and two

homeostatic model assessment (HOMA) variables. The two HOMA variables analysed were HOMA-%_β_ and HOMA-%S. Both models allow the deduction of _β_-cell function (%_β_) and insulin sensitivity

(or resistance) (%S), and have been validated against a variety of physiological methods.18 HOMA-%_β_ and HOMA-%S were calculated from pairs of fasting glucose and insulin measurements as

previously described.19, 20 In addition, we analyse an overall variable of the metabolic syndrome, which was obtained as described in the Adult Treatment Panel III (ATP III) report.21 In

short, five risk factors for metabolic syndrome were defined as present or absent for each individual according to established thresholds (see Table 8 from NCEP Expert Panel21). The

diagnosis of metabolic syndrome was made when three or more risk factors were present in a given individual. All subjects gave informed written consent, and permission to conduct the study

was granted by the EH ethical committee. STATISTICAL ANALYSIS As previously,13 we followed an additive haplotype-based model in this study. In keeping with the approach used in haplotype

trend regression (HTR)22 and discussed more generally,23 each individual's phenotype (e.g. weight) was used twice, once for each observed (by inference) haplotype possessed. This is

valid when Hardy–Weinberg equilibrium holds.22 The effect of the *5 haplotype on each trait was tested separately for men and women. Given prior hypothesis suggesting that *5 haplotype has

an effect on weight,13 we compared, for each trait, the effect of this haplotype with the effect of the remaining haplotypes pooled together (defined here as not*5). The differences in the

mean values observed for each trait between *5 and not*5 were compared using the Student's _t_-test. One tailed test was used for replication test of *5 haplotype–BMI association.

Adjustments for covariates were also performed using multiple regression analyses. We performed adjustments for age for analyses of all variables, and adjustments for WHR for obesity-related

phenotypes. Noting a recently published claim relating the _TH01_ microsatellite with tobacco dependence24, 25 and in order to correct for possible effects of this exposure on the

phenotypes analysed, we also adjusted for smoking status in multiple regression analyses. The overall variable of metabolic syndrome (as defined by ATP III21) was crosstabulated against the

presence/absence of the *5 haplotype, and the association tested by a standard contingency table _χ_2 test (Pearson _χ_2). The following variables were log-transformed before statistical

analyses and then retransformed for table presentation: plasma triglycerides, fasting plasma concentrations of proinsulin, insulin and glucose at baseline, plasma concentrations of insulin

and glucose at 30 and at 120 min after an oral load of 75 g of glucose, insulin area under the curve during the GTT, HOMA-%_β_ and HOMA-%S. The distributions of *5 and not*5 haplotypes were

tested for normality for all phenotypes using the Kolmogorov–Smirnov goodness-of-fit test in order to check for the presence of possible outliers. The nonparametric Kruskal–Wallis test was

also computed in order to check for concordance with the results obtained by multiple regression. The statistical analyses were conducted using SPSS (Windows version 10). RESULTS Individual

markers were all in Hardy–Weinberg equilibrium (data not shown). Tables 1 and 2 show the results obtained for *5 and for not*5 haplotypes in men and women, respectively. All 21 phenotypes

were normally distributed for both groups tested (*5 and not*5) both in men and in women (_P_>0.05 in the Kolmogorov–Smirnov goodness-of-fit test). No significant differences were

observed between *5 and not*5 in women (Table 2). In men, however, *5 associated with several traits (Table 1 and Figure 1). In accordance with previous evidence,13 haplotype *5 was found to

show a significantly lower BMI when compared with not*5 in men (_P_=0.0045). There is 1.81 unit BMI difference, whereas in the NPHSII study, *5 group averaged 0.84 units lighter than not*5

group. The corresponding mean reduction in weight observed for *5 in EH was 5 kg (2.4 kg in NPHSII). The results obtained from other obesity indicators confirm that *5 has a significant

protective effect against obesity in men. *5 shows lower WC by 6.3 cm and lower WHR by 5% (Table 1). The differences between *5 and not*5 are highly significant for BMI, WC and WHR even

after adjustments for age and smoking in multiple regression analyses (Table 1). Our results also suggest that *5 has an effect on plasma proinsulin levels, and on plasma insulin and glucose

levels both at baseline and after an oral GTT in men. A significant 1.5-fold reduction in plasma proinsulin levels was observed for *5 relative to not*5 (Table 1). However, this significant

difference depends to some extent on weight, since the _P_-value is 0.131 after adjusting for WHR in multiple regression analysis. Plasma insulin levels after the glucose load in the oral

GTT were also significantly lower for *5, the 120 min plasma insulin value remaining significant after adjustment for WHR (Table 1). The magnitudes of the differences observed in the oral

GTT between *5 and not*5 for plasma insulin levels were as follows: lower values were found for *5 in baseline levels of insulin (−11.0 pmol/l), and in plasma insulin levels after 30 min

(−64.4 pmol/l) and after 120 min (−64.1 pmol/l). These differences translate into a 1.4-fold lower insulin area under the curve during the oral GTT (_P_=0.015, Table 1). The differences in

plasma glucose levels during the oral GTT between *5 and not*5 were marginally significant: 0.41 mmol/l for baseline glucose, 0.82 mmol/l for glucose after 30 min and 0.87 mmol/l for glucose

after 120 min, _P_-values respectively 0.056, 0.030 and 0.076. In addition, the results from multiple regression analysis also showed dependence of plasma glucose levels on WHR (Table 1).

*5 associated also significantly with HOMA-%S, the magnitude of the effect observed being a reduction of 31% compared with the mean HOMA-%S value observed for not*5 haplotypes. Again, this

significant association was dependent on WHR (Table 1). The percentage of the variation explained for each trait, as measured by _R_2, varied from 1.2 to 5.9% (Table 1). Although _R_2

comparisons are difficult because they depend on the precision to which varables are measured (e.g. being more precise for plasma glucose and insulin levels than for WHR), these results

suggest that the effects of *5 on WHR, WC and plasma insulin 120 min may be larger than for the remaining variables (Table 1). No significant differences between *5 and not*5 were observed

for birthweight, weight at 1 year, height, plasma TG, systolic BP, diastolic BP or HOMA-%_β_ in men (Table 1). The nonparametric Kruskal–Wallis test confirmed all results obtained by

parametric regression (Tables 1 and 2). On the other hand, there were no significant over- or under-representations of metabolic syndrome (as defined by ATP III21) for *5 or not*5 haplotypes

either in men or in women. The percentages of metabolic syndrome observed in men for each haplotypic group were 7.8% (*5) and 8.5% (not*5); the figures observed in women were 10% (*5) and

7.8% (not*5). DISCUSSION This study describes the effects of _IGF2_-_INS_-_TH_*5 haplotype on two traits of clinical relevance: obesity and response to glucose. It both replicates evidence

of the protective effect of *5 against obesity in men and extends detail on a range of relevant subphenotypes. The observed effect of *5 on BMI is similar in both cohorts of men. The finding

presented here for the first time that WC and WHR are significantly lower for *5 suggests that the reduction in BMI conferred by this haplotype occurs mainly via reduction of visceral

obesity. The absence of association between *5 and obesity-related phenotypes in women is in accordance with previous evidence suggesting differences between both sexes in the genetic

factors influencing weight.7 The *5 haplotype seems not to be associated with metabolic syndrome (as defined by ATP III21). This however does not argue against our results, since we have

shown that *5 associates with two out of the five risk factors established by ATP III,21 and this definition of metabolic syndrome assumes the presence of at least three of such risk

factors. The replication found in this study used a smaller sample size relative to our previous work.13 It has been suggested that the effect sizes may often be smaller in replication

studies than in the initial study in which association has been reported.26 However, for this replication study, a simple dichotomy focused on the presence _vs_ absence of *5 haplotype

reduced 10-fold the need for Bonferroni correction (when considering haplotypes *1 to *10), and justifiable one-sided test represented a more powerful test. In fact, the effect size was also

larger. It could be argued that the multiple phenotypes examined would require a Bonferroni correction for 21 independent tests. However, many of the traits are interrelated (e.g. all the

weight-related traits, all the GTT related traits, and systolic and diastolic BP), which reduces the number of independent tests conducted. A more realistic Bonferroni correction of 5 would

leave most signals significant. In addition, it seems unlikely that a statistical artifact led to consistency both of significance and direction of haplotypic effects of *5 for two

independent cohorts. On the contrary, the BMI findings and other trait features, taken together with our previous findings13 support that the associations found have a biological basis and

argues against type-I error or possible biases of the sampling scheme followed (the later supported also by the fact that all 21 phenotypes were normally distributed for *5 and not*5

haplotypes). The replication found in this work has greater relevance given the high risk of false negative results expected for SNP and haplotype studies27 and the low replication rate

reported for association studies of obesity.28 The recently reported association of an individual SNP in _IGF2_ with BMI, WC and fat percentage in 538 males from 92 extended Finnish

families29 also points to an effect of _IGF2_, although the SNPs studied have not been related to our *1 to *10 haplotype classification.13 Other literature also suggests that the

_IGF2_-_INS_-_TH_ region may be important in obesity.30, 31, 32, 33, 34, 35, 36, 37, 38 The confirmation of *5 as a weight-lowering haplotype in men and our findings on related phenotypes

suggest that the _IGF2_-_INS_-_TH_ region harbours causal site(s) influencing obesity and insulin response to glucose. Haplotype association analyses _per se_ do not permit estimation either

of the physical location of a causal genetic variant or its support interval. However, the extended haplotype used, which combines multiallelic microsatellite information with SNPs, has

proved to be more powerful than the analysis of each of its single constituents, since we have not found significant associations for _IGF2 ApaI_, _INS HphI_ and _TH01_ in this data set

(data not shown). Other approaches to determination of causal SNPs (e.g. Maniatis _et al_39) may determine the presence of one or more causal sites on this haplotype. Our results, however,

permit speculation about possible functional element(s) of *5. There is evidence in the literature involving all three genes, _IGF2_, _INS_ and _TH_, in the regulation of body weight. It is

known that insulin is a very efficient inhibitor of free fatty acid mobilisation. Insulin decreases the release of free fatty acids from adipose tissue by inhibiting hormone-sensitive lipase

and stimulates triacylglycerol uptake into adipose tissue by activating lipoprotein lipase.33 Thus, a gradual decline in insulin secretion stimulates free fatty acid release from the

adipose tissue.38 Therefore, a low expressor haplotype of insulin could be a primary determinant of lower weight. Indeed, we have observed in this work lower proinsulin and lower baseline

plasma insulin levels in association with *5. However, it is also known that increase of insulin secretion in proportion to accumulated fat counteracts insulin resistance and protects

individuals from hyperglycemia.40 Therefore, it is also possible that the lower insulin levels after an oral GTT found for *5 could be secondary to the lesser insulin resistance of lean

individuals. In this case (see below), _IGF2_ could contain the haplotypic determinants of the leanness. Multiple regression results suggest that most of the insulin and glucose effects

observed for *5 are substantially dependent on WHR, a statistical pointer that the insulin and glucose associations of *5 may be secondary to its weight effects. The same applies to the

results we obtained for insulin sensitivity (or resistance) as measured by HOMA-%S. However, the fact that plasma insulin levels 120 min after the oral GTT are significantly lower for *5

after adjustment for WHR, suggests a dual role of this haplotype on both phenotypes. Longitudinal studies may resolve these possibilities. Previous evidence has related variation in the

_INS_ VNTR with control of insulin expression. However, the results obtained have been mutually inconsistent, some studies relating class I alleles with higher insulin levels,40, 41, 42 some

showing association of class III alleles with increased insulin levels,43, 44, 45 and others reporting no effect of this VNTR on insulin level variation.46, 47 The *5 haplotype contains

_INS_ VNTR class I alleles. However, it is not the only haplotype containing class I alleles (so do *1, *2, *3, *7, *9, *10) whereas these haplotypes tested individually do not show weight

effect (Rodríguez _et al_13 and this study) nor GTT effects (this study, data not shown). Indeed, our data suggest that the _INS_ VNTR may not be the potential single causal site for the

associations with weight and insulin response observed in the present study. This, however, does not exclude that the *5 haplotype harbours a causal site determining expression of insulin

and the shorter lengths of the small subclass of class I alleles associated with *5 haplotypes could be relevant.48 Complete resequencing of this haplotype together with functional studies

at the level of insulin expression may be necessary to search for such a putative causal site. Association of class III homozygotes at the _INS_ VNTR with greater birth weight has been

reported,49 although more recent studies in Hertfordshire men,50 in other UK cohorts51 and in a large Finnish birth cohort,52 did not corroborate this association. Neither did

_IGF2-INS-TH_*5 haplotype associate with birth weight or weight at 1 year in Hertfordshire men in this analysis. *5 haplotype does not represent class III _vs_ class I but is associated with

the subset of smallest class I alleles. Of additional note, *5 haplotype associated strongly with much lower 120 min insulin levels in a GTT (Table 1), whereas no major difference was

observed comparing class I and class III homozygotes (data not shown). The functional element(s) of *5, which determine the weight effect, could also reside in the _TH_ and/or _IGF2_ genes.

It is known that visceral fat is more lipolytic in response to catecholamine stimulation than is subcutaneous fat.35 Also known is that the _TH01_ microsatellite located in intron 1 of the

_TH_ gene has a role in the transcription of this gene, which encodes the rate-limiting enzyme in catecholamine biosynthesis, transcription appearing to be inhibited in proportion to the

number of repeats from 3 to 8 and with a counteracted effect for alleles above eight repeats.53 The lower visceral fat associated with *5 could reflect an increased lipolysis of visceral fat

stimulated by catecholamines via a comparatively increased expression of _TH_ conferred by the *5 constituent _TH01_ allele 9 (with a core of 9 repeats). However, it should be pointed out

that haplotype *9 (containing _TH01_ allele 9) as well as haplotypes *3, *4 and *6 (all containing allele 9.3) do not show a weight-lowering effect.13 Recent studies of IGFII suggest that

this major fetal growth factor with effects on fetal skeletal muscle growth and development, which is also expressed in adult life, may be associated with lipid metabolism and obesity. The

expression of an _Igf2_ transgene in adult skin reduces the amount of body fat,30 whereas low plasma IGFII concentrations predict weight gain and obesity.54 Homozygotes for allele A at _IGF2

ApaI_ site in the 3′ noncoding region show a mean body weight 3.3 kg lighter and show higher mean serum IGFII levels than the common (GG) homozygotes.9 It is plausible, therefore, that *5

predicts high IGFII levels and that this high expressor status is a primary protection against obesity. However, previous evidence showing that haplotype *6, which also contains _IGF2 ApaI_

A allele, does not show a weight-lowering effect,13 indicates that the _ApaI_ site either has no functional effect or has effect conditional to other haplotypic elements. In conclusion, our

haplotypic analyses confirm that *5 has a protective effect against obesity in men and the investigation, for the first time, of its effect on related phenotypes, suggests that *5 may also

be relevant to variation of insulin levels in GTT in men. _IGF2_, _INS_ and _TH_ are certainly haplotypically coupled and may conceivably be functionally (evolutionarily) coupled in their

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thanked for support. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Human Genetics Division, University of Southampton, School of Medicine, Duthie Building (MP 808), Southampton General

Hospital, Tremona Road, Southampton, UK Santiago Rodríguez, Tom R Gaunt, Xiao-he Chen & Ian N M Day * Fetal Origins of Adult Disease Division, MRC Environmental Epidemiology Unit, School

of Medicine, Southampton University Hospital, Tremona Road, Southampton, UK Elaine Dennison, Holly E Syddall, David I W Phillips & Cyrus Cooper Authors * Santiago Rodríguez View author

publications You can also search for this author inPubMed Google Scholar * Tom R Gaunt View author publications You can also search for this author inPubMed Google Scholar * Elaine Dennison

View author publications You can also search for this author inPubMed Google Scholar * Xiao-he Chen View author publications You can also search for this author inPubMed Google Scholar *

Holly E Syddall View author publications You can also search for this author inPubMed Google Scholar * David I W Phillips View author publications You can also search for this author

inPubMed Google Scholar * Cyrus Cooper View author publications You can also search for this author inPubMed Google Scholar * Ian N M Day View author publications You can also search for

this author inPubMed Google Scholar CORRESPONDING AUTHOR Correspondence to Ian N M Day. RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Rodríguez, S.,

Gaunt, T., Dennison, E. _et al._ Replication of _IGF2-INS-TH_*5 haplotype effect on obesity in older men and study of related phenotypes. _Eur J Hum Genet_ 14, 109–116 (2006).

https://doi.org/10.1038/sj.ejhg.5201505 Download citation * Received: 06 January 2005 * Revised: 29 July 2005 * Accepted: 16 September 2005 * Published: 26 October 2005 * Issue Date: January

2006 * DOI: https://doi.org/10.1038/sj.ejhg.5201505 SHARE THIS ARTICLE Anyone you share the following link with will be able to read this content: Get shareable link Sorry, a shareable link

is not currently available for this article. Copy to clipboard Provided by the Springer Nature SharedIt content-sharing initiative KEYWORDS * obesity * _IGF2-INS-TH_ genomic region *

genetic association * replication * haplotype