| 21. |
- Speliotes, Elizabeth K., et al.
(författare)
-
Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index
- 2010
-
Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 42:11, s. 937-948
-
Tidskriftsartikel (refereegranskat)abstract
- Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ~2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10−8), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.
|
|
| 22. |
- Tedersoo, L., et al.
(författare)
-
The Global Soil Mycobiome consortium dataset for boosting fungal diversity research
- 2021
-
Ingår i: Fungal Diversity. - : Springer Science and Business Media LLC. - 1560-2745 .- 1878-9129. ; 111, s. 573-588
-
Tidskriftsartikel (refereegranskat)abstract
- Fungi are highly important biotic components of terrestrial ecosystems, but we still have a very limited understanding about their diversity and distribution. This data article releases a global soil fungal dataset of the Global Soil Mycobiome consortium (GSMc) to boost further research in fungal diversity, biogeography and macroecology. The dataset comprises 722,682 fungal operational taxonomic units (OTUs) derived from PacBio sequencing of full-length ITS and 18S-V9 variable regions from 3200 plots in 108 countries on all continents. The plots are supplied with geographical and edaphic metadata. The OTUs are taxonomically and functionally assigned to guilds and other functional groups. The entire dataset has been corrected by excluding chimeras, index-switch artefacts and potential contamination. The dataset is more inclusive in terms of geographical breadth and phylogenetic diversity of fungi than previously published data. The GSMc dataset is available over the PlutoF repository.
|
|
| 23. |
- Tobias, Deirdre K, et al.
(författare)
-
Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine
- 2023
-
Ingår i: Nature Medicine. - 1546-170X. ; 29:10, s. 2438-2457
-
Forskningsöversikt (refereegranskat)abstract
- Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.
|
|
| 24. |
- van Zuydam, NR, et al.
(författare)
-
A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes
- 2018
-
Ingår i: Diabetes. - : American Diabetes Association. - 1939-327X .- 0012-1797. ; 67:7, s. 1414-1427
-
Tidskriftsartikel (refereegranskat)abstract
- Identification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 × 10−8) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk variant discovery for DKD.
|
|
| 25. |
|
|
| 26. |
- Ahlqvist, E., et al.
(författare)
-
Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables
- 2018
-
Ingår i: Lancet Diabetes & Endocrinology. - : Elsevier BV. - 2213-8587. ; 6:5, s. 361-369
-
Tidskriftsartikel (refereegranskat)abstract
- Background Diabetes is presently classified into two main forms, type 1 and type 2 diabetes, but type 2 diabetes in particular is highly heterogeneous. A refined classification could provide a powerful tool to individualise treatment regimens and identify individuals with increased risk of complications at diagnosis. Methods We did data-driven cluster analysis (k-means and hierarchical clustering) in patients with newly diagnosed diabetes (n=8980) from the Swedish All New Diabetics in Scania cohort. Clusters were based on six variables (glutamate decarboxylase antibodies, age at diagnosis, BMI, HbA(1c), and homoeostatic model assessment 2 estimates of beta-cell function and insulin resistance), and were related to prospective data from patient records on development of complications and prescription of medication. Replication was done in three independent cohorts: the Scania Diabetes Registry (n=1466), All New Diabetics in Uppsala (n=844), and Diabetes Registry Vaasa (n=3485). Cox regression and logistic regression were used to compare time to medication, time to reaching the treatment goal, and risk of diabetic complications and genetic associations. Findings We identified five replicable clusters of patients with diabetes, which had significantly different patient characteristics and risk of diabetic complications. In particular, individuals in cluster 3 (most resistant to insulin) had significantly higher risk of diabetic kidney disease than individuals in clusters 4 and 5, but had been prescribed similar diabetes treatment. Cluster 2 (insulin deficient) had the highest risk of retinopathy. In support of the clustering, genetic associations in the clusters differed from those seen in traditional type 2 diabetes. Interpretation We stratified patients into five subgroups with differing disease progression and risk of diabetic complications. This new substratification might eventually help to tailor and target early treatment to patients who would benefit most, thereby representing a first step towards precision medicine in diabetes.
|
|
| 27. |
|
|
| 28. |
|
|
| 29. |
- Flannick, Jason, et al.
(författare)
-
Data Descriptor : Sequence data and association statistics from 12,940 type 2 diabetes cases and controls
- 2017
-
Ingår i: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 4
-
Tidskriftsartikel (refereegranskat)abstract
- To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (> 80% of low-frequency coding variants in similar to ~82 K Europeans via the exome chip, and similar to ~90% of low-frequency non-coding variants in similar to ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
|
|
| 30. |
- Florez, J C, et al.
(författare)
-
Association testing of the protein tyrosine phosphatase 1B gene (PTPN1) with type 2 diabetes in 7,883 people
- 2005
-
Ingår i: Diabetes. - 1939-327X. ; 54:6, s. 1884-1891
-
Tidskriftsartikel (refereegranskat)abstract
- Protein tyrosine phosphatase (PTP)-1B, encoded by the PTPN1 gene, inactivates the insulin signal transduction cascade by dephosphorylating phosphotyrosine residues in insulin signaling molecules. Due to its chromosomal location under a chromosome 20 linkage peak and the metabolic effects of its absence in knockout mice, it is a candidate gene for type 2 diabetes. Recent studies have associated common sequence variants in PTPN1 with type 2 diabetes and diabetes-related phenotypes. We sought to replicate the association of common single nucleotide polymorphisms (SNPs) and haplotypes in PTPN1 with type 2 diabetes, fasting plasma glucose, and insulin sensitivity in a large collection of subjects. We assessed linkage disequilibrium, selected tag SNPs, and typed these markers in 3,347 cases of type 2 diabetes and 3,347 control subjects as well as 1,189 siblings discordant for type 2 diabetes. Despite power estimated at > 95% to replicate the previously reported associations, no statistically significant evidence of association was observed between PTPN1 SNPs or common haplotypes with type 2 diabetes or with diabetic phenotypes.
|
|
