We wish to use the ALSPAC study to investigate the effects of type 2 diabetes susceptibility variants at the KCNQ1 locus on fetal growth, growth in childhood and intermediate traits related to type 2 diabetes.

Recently, two genome-wide association (GWA) studies of East Asian subjects simultaneously reported a strong association between variants in the KCNQ1 gene and the odds of type 2 diabetes [1, 2]. The effect size estimates were large (OR 1.3-1.4) and the associations were robust, exceeding stringent criteria for statistical significance appropriate to GWA studies (Pless than 5x10-8).

This association had not been identified previously in European GWA studies due to the lower allele frequency (5% vs 40%) and consequently reduced power [3]. However associations were observed in European samples following the East Asian GWA studies, and the effect size estimates were consistent [1-3]. The index SNP, rs2237895, has also shown detectable effects on beta cell function in Europeans [4].

The associations with type 2 diabetes and beta cell function make the KCNQ1 locus an excellent candidate for influencing early growth. A variant that predisposes to reduced insulin secretion and diabetes in adulthood may also influence insulin secretion/action in utero, and thereby reduce birth weight [5]. Our preliminary data on the CDKAL1 and HHEX loci support this (PLoS Med, under review). Maternal diabetes genes may additionally influence birth weight through their effects on the intrauterine environment [6]. We have observed that the maternal risk alleles for fasting glucose and type 2 diabetes at GCK and TCF7L2, respectively, are associated with higher offspring birth weight [7, 8].

The KCNQ1 locus is of additional interest in relation to early growth because the locus is imprinted and may harbour elements that influence the imprinting of neighbouring genes [9, 10]. The region is implicated in Beckwith-Wiedemann syndrome and Silver-Russell syndrome, rare neonatal disorders of fetal overgrowth and growth restriction, respectively.

We therefore propose to analyse the polymorphisms in ALSPAC to test the following hypotheses:

1. Fetal genotype and maternal genotype are associated with fetal growth.

2. Fetal genotype and maternal genotype are associated with growth phenotypes (height, BMI, growth velocity) in childhood

3. Offspring genotype is associated with diabetes-related traits in childhood including fasting insulin, fasting glucose and insulin secretion (in the subset of offspring with OGTT data), triglycerides, HDL, LDL and total cholesterol, anthropometric measures including BMI, lean/fat body mass, WHR, waist circumference, skin folds where available.

4. Due to imprinting, association between the risk allele in the offspring and early growth is dependent upon the parent of origin (we will be able to assess this using informative mother-offspring pairs).

Whether the results are negative or positive they will help our understanding of how the KCNQ1 variants function and, if positive, provide important insights into growth and other diabetes-related phenotypes.

To do this we would like to genotype (at Kbiosciences) all ~20,000 ALSPAC samples. We will need the following phenotypes to test our hypotheses (a detailed list is in the next section):

1. Birth weight, length and head circumference

2. Growth measures in childhood (height, weight and BMI aged 7-11)

3. Covariates of birth weight to check if genotype is acting through them: gestational age, maternal age, maternal BMI, smoking , parity, twin status to exclude non-singletons, ethnicity as genotype frequency may alter with ethnic origin and confound analyses.

4. Type 2 diabetes-related intermediate traits including fasting insulin, fasting glucose and insulin secretion (in the subset of offspring with OGTT data), triglycerides, HDL, LDL and total cholesterol, anthropometric measures including BMI, lean/fat body mass, WHR, waist circumference, skin folds where available.

Plans for meta-analysis:

ALSPAC will provide the largest European-ethnicity dataset for association studies with fetal growth. However, we have access, through our own studies and extensive collaborations to samples from the Exeter family study (950 population based parent-newborn trios), the Northern Finland 1966 Birth Cohort (4600 individuals with own birth measures) and the Hyperglycemia and Adverse Pregnancy Outcomes study (4000 European mother-offspring pairs; 2000 Thai/Chinese mother-offspring pairs; 1250 African-Caribbean mother-offspring pairs; 2500 other ethnicity). We hypothesize that real genetic associations will be consistent across all of these studies - i.e. even if individually studies show only nominal significance, a meta-analysis of all studies will provide highly significant results.