| 1. |
- Zillikens, M. C., et al.
(författare)
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Large meta-analysis of genome-wide association studies identifies five loci for lean body mass
- 2017
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p < 5 x 10(-8)) or suggestively genome wide (p < 2.3 x 10(-6)). Replication in 63,475 (47,227 of European ancestry) individuals from 33 cohorts for whole body lean body mass and in 45,090 (42,360 of European ancestry) subjects from 25 cohorts for appendicular lean body mass was successful for five single-nucleotide polymorphisms in/ near HSD17B11, VCAN, ADAMTSL3, IRS1, and FTO for total lean body mass and for three single-nucleotide polymorphisms in/ near VCAN, ADAMTSL3, and IRS1 for appendicular lean body mass. Our findings provide new insight into the genetics of lean body mass.
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| 2. |
- Bar, N., et al.
(författare)
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A reference map of potential determinants for the human serum metabolome
- 2020
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Ingår i: Nature. - : Nature Research. - 0028-0836 .- 1476-4687. ; 588:7836, s. 135-140
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Tidskriftsartikel (refereegranskat)abstract
- The serum metabolome contains a plethora of biomarkers and causative agents of various diseases, some of which are endogenously produced and some that have been taken up from the environment1. The origins of specific compounds are known, including metabolites that are highly heritable2,3, or those that are influenced by the gut microbiome4, by lifestyle choices such as smoking5, or by diet6. However, the key determinants of most metabolites are still poorly understood. Here we measured the levels of 1,251 metabolites in serum samples from a unique and deeply phenotyped healthy human cohort of 491 individuals. We applied machine-learning algorithms to predict metabolite levels in held-out individuals on the basis of host genetics, gut microbiome, clinical parameters, diet, lifestyle and anthropometric measurements, and obtained statistically significant predictions for more than 76% of the profiled metabolites. Diet and microbiome had the strongest predictive power, and each explained hundreds of metabolites—in some cases, explaining more than 50% of the observed variance. We further validated microbiome-related predictions by showing a high replication rate in two geographically independent cohorts7,8 that were not available to us when we trained the algorithms. We used feature attribution analysis9 to reveal specific dietary and bacterial interactions. We further demonstrate that some of these interactions might be causal, as some metabolites that we predicted to be positively associated with bread were found to increase after a randomized clinical trial of bread intervention. Overall, our results reveal potential determinants of more than 800 metabolites, paving the way towards a mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating the levels of circulating metabolites.
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| 3. |
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| 4. |
- Cederberg, B., et al.
(författare)
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Tvåvingar
- 2010
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Ingår i: Rödlistade arter i Sverige 2010. - 9789188506351 ; , s. 185-202
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Abstract is not available
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| 5. |
- Andersen, Gregers Stig Tig, et al.
(författare)
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The DEXLIFE study methods : identifying novel candidate biomarkers that predict progression to type 2 diabetes in high risk individuals
- 2014
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Ingår i: Diabetes Research and Clinical Practice. - : Elsevier. - 0168-8227 .- 1872-8227. ; 106:2, s. 383-389
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Tidskriftsartikel (refereegranskat)abstract
- The incidence of type 2 diabetes (T2D) is rapidly increasing worldwide and T2D is likely to affect 592 million people in 2035 if the current rate of progression is continued. Today, patients are diagnosed with T2D based on elevated blood glucose, either directly or indirectly (HbA1c). However, the information on disease progression is limited. Therefore, there is a need to identify novel early markers of glucose intolerance that reflect the underlying biology and the overall physiological, metabolic and clinical characteristics of progression towards diabetes. In the DEXLIFE study, several clinical cohorts provide the basis for a series of clinical, physiological and mechanistic investigations in combination with a range of--omic technologies to construct a detailed metabolic profile of high-risk individuals across multiple cohorts. In addition, an exercise and dietary intervention study is conducted, that will assess the impact on both plasma biomarkers and specific functional tissue-based markers. The DEXLIFE study will provide novel diagnostic and predictive biomarkers which may not only effectively detect the progression towards diabetes in high risk individuals but also predict responsiveness to lifestyle interventions known to be effective in the prevention of diabetes.
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| 6. |
- Cederberg, Margareta, et al.
(författare)
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Kunskapsstöd för socialt arbete i skolan - en exemplifierande överblick
- 2011
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Denna rapport har utarbetats på uppdrag av Malmö stadskontor. Forskningsöversikten gör inte anspråk på att vara heltäckande. Uppdraget har varit att söka forskningsstöd för olika former av huvudmannaskap för socialarbetare med placering i skolan. Ytterligare fokus har varit att närmare undersöka forskningsstöd för Socialt nätverksarbete i skolan, Elevcoach i skolan och Familjeklass. I uppdraget ingick även att översiktligt söka forskningsstöd för vad som beskrivs som goda metoder, internationellt och nationellt, för socialt arbete i skolan. Studien har genomförts av fil dr Margareta Cederberg, fil dr Ingegerd Ericsson och fil dr Nanny Hartsmar, Malmö högskola och fil dr Lars B. Ohlsson, Lunds universitet. I rapporten svarar forskarna självständigt för innehåll och slutsatser. Varje kapitel avslutas med en sammanfattning. I slutet av rapporten finns en avslutande kommentar där även evidensproblematiken lyfts fram. Rapporten vänder sig till tjänstemän, personal inom socialtjänst och skola, forskare, forskarstuderande, samt till studerande vid socionom- och lärarutbildningar. Det är vår förhoppning att rapporten kan stimulera till fortsatt forskning och diskussioner om socialt arbete i skolan och om samverkan skola och socialtjänst. Uppdraget har finansierats av Malmö stad och genomförts under hösten 2010.
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| 7. |
- Gudmundsdottir, Valborg, et al.
(författare)
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Whole blood co-expression modules associate with metabolic traits and type 2 diabetes : an IMI-DIRECT study
- 2020
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Ingår i: Genome Medicine. - : BioMed Central. - 1756-994X .- 1756-994X. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D.Methods: Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts.Results: We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling.Conclusions: Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.
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