| 1. |
- Locke, Adam E, et al.
(author)
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Genetic studies of body mass index yield new insights for obesity biology.
- 2015
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 518:7538, s. 197-401
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Journal article (peer-reviewed)abstract
- Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
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| 2. |
- Shungin, Dmitry, et al.
(author)
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New genetic loci link adipose and insulin biology to body fat distribution.
- 2015
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 518:7538, s. 187-378
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Journal article (peer-reviewed)abstract
- Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.
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| 3. |
- Cornelis, Marilyn C, et al.
(author)
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Targeted proteomic analysis of habitual coffee consumption
- 2018
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In: Journal of Internal Medicine. - : Wiley. - 0954-6820 .- 1365-2796. ; 283:2, s. 200-211
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Journal article (peer-reviewed)abstract
- BACKGROUND: Coffee drinking has been implicated in mortality and a variety of diseases but potential mechanisms underlying these associations are unclear. Large-scale systems epidemiological approaches may offer novel insights to mechanisms underlying associations of coffee with health.OBJECTIVE: We performed an analysis of known and novel protein markers linked to cardiovascular disease and their association with habitual coffee intake in the Prospective Study of the Vasculature in Uppsala Seniors (PIVUS, n=816) and followed-up top proteins in the Uppsala Longitudinal Study of Adult Men (ULSAM, n=635) and EpiHealth (n=2418).METHODS: In PIVUS and ULSAM, coffee intake was measured by 7-day dietary records while a computer-based food frequency questionnaire was used in EpiHealth. Levels of up to 80 proteins were assessed in plasma by a proximity extension assay.RESULTS: Four protein-coffee associations adjusted for age, sex, smoking and BMI, met statistical significance in PIVUS (FDR<5%, P<2.31×10(-3) ): leptin (LEP), chitinase-3-like protein 1 (CHI3L), Tumor necrosis factor (TNF) receptor 6 and TNF-related apoptosis-inducing ligand. The inverse association between coffee intake and LEP replicated in ULSAM (β, -0.042 SD per cup of coffee, P=0.028) and EpiHealth (β, -0.025 SD per time of coffee, P=0.004). The negative coffee-CHI3L association replicated in EpiHealth (β, -0.07, P=1.15×10(-7) ), but not in ULSAM (β, -0.034, P=0.16).CONCLUSIONS: The current study supports an inverse association between coffee intake and plasma LEP and CHI3L1 levels. The coffee-CHI3L1 association is novel and warrants further investigation given links between CHI3L1 and health conditions that are also potentially influenced by coffee.
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