| 1. |
- Wagh, Rucha, et al.
(författare)
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Twins in Guinea-Bissau have a 'thin-fat' body composition compared to singletons
- 2022
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Ingår i: Journal of Developmental Origins of Health and Disease. - 2040-1744. ; 13:6, s. 787-793
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Tidskriftsartikel (refereegranskat)abstract
- The 'thrifty phenotype' hypothesis proposed that fetal undernutrition increases risk of diabetes in later life. Undernourished low birthweight Indian babies are paradoxically more adipose compared to well-nourished European babies, and are at higher risk of diabetes in later life. Twin pregnancies are an example of in utero growth restrictive environment due to shared maternal nutrition. There are few studies of body composition in twins. We performed secondary analysis of anthropometric body composition of twins and singletons in Guinea-Bissau, an economically deprived African country. Anthropometric data were available on 7-34 year-old twins (n = 209, 97 males) and singletons (n = 182, 86 males) in the Guinea-Bissau Twin Registry at the Bandim Health Project. Twins had lower birthweight (2420 vs 3100 g, p < 0.001); and at follow-up, lower height (HAZ mean Z-score difference, -0.21, p = 0.055), weight (WAZ -0.73, p = 0.024) and BMI (BAZ -0.22, p = 0.079) compared to singletons but higher adiposity (skinfolds: +0.33 SD, p = 0.001). Twins also had higher fasting (+0.38 SD, p < 0.001) and 2-hour OGTT glucose concentrations (+0.29 SD, p < 0.05). Linear mixed-effect model accounting for intrapair correlations and interactions confirmed that twins were thinner but fatter across the age range. Data on maternal morbidity and prematurity were not available in this cohort. African populations are known to have a muscular (less adipose) body composition. Demonstration of a thin-fat phenotype in twins in a low socio-economic African country supports the thesis that it could be a manifestation of early life undernutrition and not exclusive to Indians. This phenotype could increase risk of diabetes and related conditions.
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| 2. |
- Mahajan, Anubha, et al.
(författare)
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Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes
- 2018
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Ingår i: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 50:4, s. 559-571
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Tidskriftsartikel (refereegranskat)abstract
- We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10−7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent ‘false leads’ with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.
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