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Bridget A Knight

Publications and source records attributed to Bridget A Knight.

3 recordsLinked to original sources

Assessing newborn body composition using principal components analysis: differences in the determinants of fat and skeletal size.

BACKGROUND: Birth weight is a composite of skeletal size and soft tissue. These components are likely to have different growth patterns. The aim of this paper is to investigate the association between established determinants of birth weight and these separate components. METHODS: Weight, length, crown-rump, knee-heel, head circumference, arm circumference, and skinfold thicknesses were measured at birth in 699 healthy, term, UK babies recruited as part of the Exeter Family Study of Childhood Health. Corresponding measurements were taken on both parents. Principal components analysis with varimax rotation was used to reduce these measurements to two independent components each for mother, father and baby: one highly correlated with measures of fat, the other with skeletal size. RESULTS: Gestational age was significantly related to skeletal size, in both boys and girls (r = 0.41 and 0.52), but not fat. Skeletal size at birth was also associated with parental skeletal size (maternal: r = 0.24 (boys), r = 0.39 (girls) ; paternal: r = 0.16 (boys), r = 0.25 (girls)), and maternal smoking (0.4 SD reduction in boys, 0.6 SD reduction in girls). Fat was associated with parity (first borns smaller by 0.45 SD in boys; 0.31 SD in girls), maternal glucose (r = 0.18 (boys); r = 0.27 (girls)) and maternal fat (r = 0.16 (boys); r = 0.36 (girls)). CONCLUSION: Principal components analysis with varimax rotation provides a useful method for reducing birth weight to two more meaningful components: skeletal size and fat. These components have different associations with known determinants of birth weight, suggesting fat and skeletal size may have different regulatory mechanisms, which would be important to consider when studying the associations of birth weight with later adult disease.

Adiposity↗

Assessment of the role of common genetic variation in the transient neonatal diabetes mellitus (TNDM) region in type 2 diabetes: a comparative genomic and tagging single nucleotide polymorphism approach.

Recent evidence supports the strong overlap between genes implicated in monogenic diabetes and susceptibility to type 2 diabetes. Transient neonatal diabetes mellitus (TNDM) is a rare disorder associated with overexpression of genes at a paternally expressed imprinted locus on chromosome 6q24. There are two overlapping genes in this region: the transcription factor zinc finger protein associated with cell cycle control and apoptosis (ZAC also known as PLAGL1) and HYMA1, which encodes an untranslated mRNA. Several type 2 diabetes linkage studies have reported linkage to chromosome 6q22-25. We hypothesized that common genetic variation at this TNDM region influences type 2 diabetes susceptibility. In addition to the coding regions, we used comparative genomic analysis to identify conserved noncoding regions, which were resequenced for single nucleotide polymorphism (SNP) discovery in 47 individuals. Twenty-six SNPs were identified. Fifteen tag SNPs (tSNPs) were successfully genotyped in a large case-control (n = 3,594) and family-based (n = 1,654) study. We did not find any evidence of association or overtransmission of any tSNP to affected offspring or of a parent-of-origin effect. Using a study sufficiently powered to detect odds ratios of <1.2, we conclude that common variation in the TNDM region does not play an important role in the genetic susceptibility to type 2 diabetes.

Alleles↗

Large-scale association studies of variants in genes encoding the pancreatic beta-cell KATP channel subunits Kir6.2 (KCNJ11) and SUR1 (ABCC8) confirm that the KCNJ11 E23K variant is associated with type 2 diabetes.

The genes ABCC8 and KCNJ11, which encode the subunits sulfonylurea receptor 1 (SUR1) and inwardly rectifying potassium channel (Kir6.2) of the beta-cell ATP-sensitive potassium (K(ATP)) channel, control insulin secretion. Common polymorphisms in these genes (ABCC8 exon 16-3t/c, exon 18 T/C, KCNJ11 E23K) have been variably associated with type 2 diabetes, but no large ( approximately 2,000 subjects) case-control studies have been performed. We evaluated the role of these three variants by studying 2,486 U.K. subjects: 854 with type 2 diabetes, 1,182 population control subjects, and 150 parent-offspring type 2 diabetic trios. The E23K allele was associated with diabetes in the case-control study (odds ratio [OR] 1.18 [95% CI 1.04-1.34], P = 0.01) but did not show familial association with diabetes. Neither the exon 16 nor the exon 18 ABCC8 variants were associated with diabetes (1.04 [0.91-1.18], P = 0.57; 0.93 [0.71-1.23], P = 0.63, respectively). Meta-analysis of all case-control data showed that the E23K allele was associated with type 2 diabetes (K allele OR 1.23 [1.12-1.36], P = 0.000015; KK genotype 1.65 [1.34-2.02], P = 0.000002); but the ABCC8 variants were not associated. Our results confirm that E23K increases risk of type 2 diabetes and show that large-scale association studies are important for the identification of diabetes susceptibility alleles.

ATP-Binding Cassette Transporters↗