| 1. |
- Ali, Ashfaq, et al.
(författare)
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Do Genetic Factors Modify the Relationship Between Obesity and Hypertriglyceridemia? : Findings From the GLACIER and the MDC Studies
- 2016
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Ingår i: Circulation. - 1942-325X .- 1942-3268. ; 9:2, s. 162-171
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Tidskriftsartikel (refereegranskat)abstract
- Background Obesity is a major risk factor for dyslipidemia, but this relationship is highly variable. Recently published data from 2 Danish cohorts suggest that genetic factors may underlie some of this variability.Methods and Results We tested whether established triglyceride-associated loci modify the relationship of body mass index (BMI) and triglyceride concentrations in 2 Swedish cohorts (the Gene-Lifestyle Interactions and Complex Traits Involved in Elevated Disease Risk [GLACIER Study; N=4312] and the Malmo Diet and Cancer Study [N=5352]). The genetic loci were amalgamated into a weighted genetic risk score (WGRS(TG)) by summing the triglyceride-elevating alleles (weighted by their established marginal effects) for all loci. Both BMI and the WGRS(TG) were strongly associated with triglyceride concentrations in GLACIER, with each additional BMI unit (kg/m(2)) associated with 2.8% (P=8.4x10(-84)) higher triglyceride concentration and each additional WGRS(TG) unit with 2% (P=7.6x10(-48)) higher triglyceride concentration. Each unit of the WGRS(TG) was associated with 1.5% higher triglyceride concentrations in normal weight and 2.4% higher concentrations in overweight/obese participants (P-interaction=0.056). Meta-analyses of results from the Swedish cohorts yielded a statistically significant WGRS(TG)xBMI interaction effect (P-interaction=6.0x10(-4)), which was strengthened by including data from the Danish cohorts (P-interaction=6.5x10(-7)). In the meta-analysis of the Swedish cohorts, nominal evidence of a 3-way interaction (WGRS(TG)xBMIxsex) was observed (P-interaction=0.03), where the WGRS(TG)xBMI interaction was only statistically significant in females. Using protein-protein interaction network analyses, we identified molecular interactions and pathways elucidating the metabolic relationships between BMI and triglyceride-associated loci.Conclusions Our findings provide evidence that body fatness accentuates the effects of genetic susceptibility variants in hypertriglyceridemia, effects that are most evident in females.
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| 2. |
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| 3. |
- Auffray, Charles, et al.
(författare)
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Making sense of big data in health research: Towards an EU action plan
- 2016
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Ingår i: Genome Medicine. - : BIOMED CENTRAL LTD. - 1756-994X .- 1756-994X. ; 8:71
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Tidskriftsartikel (refereegranskat)abstract
- Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health arid healthcare for all Europearis.
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| 4. |
- Brunkwall, Louise, et al.
(författare)
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Sugar-sweetened beverage consumption and genetic predisposition to obesity in 2 Swedish cohorts
- 2016
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Ingår i: American Journal of Clinical Nutrition. - : Elsevier BV. - 0002-9165 .- 1938-3207. ; 104:3, s. 809-815
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Tidskriftsartikel (refereegranskat)abstract
- Background: The consumption of sugar-sweetened beverages (SSBs), which has increased substantially during the last decades, has been associated with obesity and weight gain.Objective: Common genetic susceptibility to obesity has been shown to modify the association between SSB intake and obesity risk in 3 prospective cohorts from the United States. We aimed to replicate these findings in 2 large Swedish cohorts.Design: Data were available for 21,824 healthy participants from the Malmö Diet and Cancer study and 4902 healthy participants from the Gene-Lifestyle Interactions and Complex Traits Involved in Elevated Disease Risk Study. Self-reported SSB intake was categorized into 4 levels (seldom, low, medium, and high). Unweighted and weighted genetic risk scores (GRSs) were constructed based on 30 body mass index [(BMI) in kg/m2]-associated loci, and effect modification was assessed in linear regression equations by modeling the product and marginal effects of the GRS and SSB intake adjusted for age-, sex-, and cohort-specific covariates, with BMI as the outcome. In a secondary analysis, models were additionally adjusted for putative confounders (total energy intake, alcohol consumption, smoking status, and physical activity).Results: In an inverse variance-weighted fixed-effects meta-analysis, each SSB intake category increment was associated with a 0.18 higher BMI (SE = 0.02; P = 1.7 × 10−20; n = 26,726). In the fully adjusted model, a nominal significant interaction between SSB intake category and the unweighted GRS was observed (P-interaction = 0.03). Comparing the participants within the top and bottom quartiles of the GRS to each increment in SSB intake was associated with 0.24 (SE = 0.04; P = 2.9 × 10−8; n = 6766) and 0.15 (SE = 0.04; P = 1.3 × 10−4; n = 6835) higher BMIs, respectively.Conclusions: The interaction observed in the Swedish cohorts is similar in magnitude to the previous analysis in US cohorts and indicates that the relation of SSB intake and BMI is stronger in people genetically predisposed to obesity.
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| 5. |
- Ding, Ming, et al.
(författare)
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Dairy consumption, systolic blood pressure, and risk of hypertension : Mendelian randomization study
- 2017
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Ingår i: The BMJ. - : BMJ Publishing Group Ltd. - 1756-1833 .- 0959-8138. ; 356
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE To examine whether previous observed inverse associations of dairy intake with systolic blood pressure and risk of hypertension were causal. DESIGN Mendelian randomization study using the single nucleotide polymorphism rs4988235 related to lactase persistence as an instrumental variable. SETTING CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium. PARTICIPANTS Data from 22 studies with 171 213 participants, and an additional 10 published prospective studies with 26 119 participants included in the observational analysis. MAIN OUTCOME MEASURES The instrumental variable estimation was conducted using the ratio of coefficients approach. Using metaanalysis, an additional eight published randomized clinical trials on the association of dairy consumption with systolic blood pressure were summarized. RESULTS Compared with the CC genotype (CC is associated with complete lactase deficiency), the CT/TT genotype (TT is associated with lactose persistence, and CT is associated with certain lactase deficiency) of LCT-13910 (lactase persistence gene) rs4988235 was associated with higher dairy consumption (0.23 (about 55 g/day), 95% confidence interval 0.17 to 0.29) serving/day; P<0.001) and was not associated with systolic blood pressure (0.31, 95% confidence interval -0.05 to 0.68 mm Hg; P=0.09) or risk of hypertension (odds ratio 1.01, 95% confidence interval 0.97 to 1.05; P=0.27). Using LCT-13910 rs4988235 as the instrumental variable, genetically determined dairy consumption was not associated with systolic blood pressure (beta=1.35, 95% confidence interval -0.28 to 2.97 mm Hg for each serving/day) or risk of hypertension (odds ratio 1.04, 0.88 to 1.24). Moreover, meta-analysis of the published clinical trials showed that higher dairy intake has no significant effect on change in systolic blood pressure for interventions over one month to 12 months (intervention compared with control groups: beta=-0.21, 95% confidence interval -0.98 to 0.57 mm Hg). In observational analysis, each serving/day increase in dairy consumption was associated with -0.11 (95% confidence interval -0.20 to -0.02 mm Hg; P=0.02) lower systolic blood pressure but not risk of hypertension (odds ratio 0.98, 0.97 to 1.00; P=0.11). CONCLUSION The weak inverse association between dairy intake and systolic blood pressure in observational studies was not supported by a comprehensive instrumental variable analysis and systematic review of existing clinical trials.
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| 6. |
- Flannick, Jason, et al.
(författare)
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Data Descriptor : Sequence data and association statistics from 12,940 type 2 diabetes cases and controls
- 2017
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Ingår i: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 4
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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.
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| 7. |
- Fuchsberger, Christian, et al.
(författare)
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The genetic architecture of type 2 diabetes
- 2016
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 536:7614, s. 41-47
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Tidskriftsartikel (refereegranskat)abstract
- The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.
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| 8. |
- Gaulton, Kyle J, et al.
(författare)
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Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.
- 2015
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 47:12, s. 1415-1415
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Tidskriftsartikel (refereegranskat)abstract
- We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.
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| 9. |
- Huang-Doran, Isabel, et al.
(författare)
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Insulin resistance uncoupled from dyslipidemia due to C-terminal PIK3R1 mutations.
- 2016
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Ingår i: JCI insight. - 2379-3708. ; 1:17
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Tidskriftsartikel (refereegranskat)abstract
- Obesity-related insulin resistance is associated with fatty liver, dyslipidemia, and low plasma adiponectin. Insulin resistance due to insulin receptor (INSR) dysfunction is associated with none of these, but when due to dysfunction of the downstream kinase AKT2 phenocopies obesity-related insulin resistance. We report 5 patients with SHORT syndrome and C-terminal mutations in PIK3R1, encoding the p85α/p55α/p50α subunits of PI3K, which act between INSR and AKT in insulin signaling. Four of 5 patients had extreme insulin resistance without dyslipidemia or hepatic steatosis. In 3 of these 4, plasma adiponectin was preserved, as in insulin receptor dysfunction. The fourth patient and her healthy mother had low plasma adiponectin associated with a potentially novel mutation, p.Asp231Ala, in adiponectin itself. Cells studied from one patient with the p.Tyr657X PIK3R1 mutation expressed abundant truncated PIK3R1 products and showed severely reduced insulin-stimulated association of mutant but not WT p85α with IRS1, but normal downstream signaling. In 3T3-L1 preadipocytes, mutant p85α overexpression attenuated insulin-induced AKT phosphorylation and adipocyte differentiation. Thus, PIK3R1 C-terminal mutations impair insulin signaling only in some cellular contexts and produce a subphenotype of insulin resistance resembling INSR dysfunction but unlike AKT2 dysfunction, implicating PI3K in the pathogenesis of key components of the metabolic syndrome.
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| 10. |
- Huang, Tao, et al.
(författare)
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Dairy Consumption and Body Mass Index Among Adults : Mendelian Randomization Analysis of 184802 Individuals from 25 Studies
- 2018
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Ingår i: Clinical Chemistry. - : Oxford University Press (OUP). - 0009-9147 .- 1530-8561. ; 64:1, s. 183-191
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Associations between dairy intake and body mass index (BMI) have been inconsistently observed in epidemiological studies, and the causal relationship remains ill defined.METHODS: We performed Mendelian randomization (MR) analysis using an established dairy intake-associated genetic polymorphism located upstream of the lactase gene (LCT-13910 C/T, rs4988235) as an instrumental variable (IV). Linear regression models were fitted to analyze associations between (a) dairy intake and BMI, (b) rs4988235 and dairy intake, and (c) rs4988235 and BMI in each study. The causal effect of dairy intake on BMI was quantified by IV estimators among 184802 participants from 25 studies.RESULTS: Higher dairy intake was associated with higher BMI (β = 0.03 kg/m2 per serving/day; 95% CI, 0.00–0.06; P = 0.04), whereas the LCT genotype with 1 or 2 T allele was significantly associated with 0.20 (95% CI, 0.14–0.25) serving/day higher dairy intake (P = 3.15 × 10−12) and 0.12 (95% CI, 0.06–0.17) kg/m2 higher BMI (P = 2.11 × 10−5). MR analysis showed that the genetically determined higher dairy intake was significantly associated with higher BMI (β = 0.60 kg/m2 per serving/day; 95% CI, 0.27–0.92; P = 3.0 × 10−4).CONCLUSIONS: The present study provides strong evidence to support a causal effect of higher dairy intake on increased BMI among adults.
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