| 1. |
- Borén, Jan, 1963, et al.
(författare)
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Effects of pnpla3 i148m on hepatic lipid and very low-density lipoprotein metabolism in humans.
- 2022
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Ingår i: Journal of internal medicine. - : Wiley. - 1365-2796 .- 0954-6820. ; 291:2, s. 218-223
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Tidskriftsartikel (refereegranskat)abstract
- The PNPLA3-148M variant is associated with liver steatosis but its influence on metabolism of triglyceride-rich lipoproteins remains unclear. Here we investigated the kinetics of large, triglyceride-rich VLDL1 and smaller VLDL2 in homozygotes for the PNPLA3-148M variant.The kinetics of apoB100 and triglyceride in VLDL subfractions was analysed in nine subjects homozygous for PNPLA3-148M and nine subjects homozygous for PNPLA3-148I (controls). Liver fat was >3-fold higher in the 148M subjects. Production rates for apoB100 and triglyceride in VLDL1 did not differ significantly between the two groups. Likewise, production rates for VLDL2 -apoB100 and -triglyceride, and fractional clearance rates for both apoB100 and triglyceride in VLDL1 and VLDL2 , were not significantly different.Despite the higher liver fat content in PNPLA3-148M homozygotes, there was no increase in VLDL production. Equally, VLDL production was maintained at normal levels despite the putative impairment in cytosolic lipid hydrolysis in these subjects. This article is protected by copyright. All rights reserved.
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| 2. |
- Borén, Jan, 1963, et al.
(författare)
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Effects of TM6SF2 E167K on hepatic lipid and very low-density lipoprotein metabolism in humans.
- 2020
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Ingår i: JCI insight. - : American Society for Clinical Investigation. - 2379-3708. ; 5:24
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Tidskriftsartikel (refereegranskat)abstract
- Non-alcoholic fatty liver disease (NAFLD) is characterized by hepatic lipid accumulation. The transmembrane 6 superfamily member 2 (TM6SF2) E167K genetic variant associates with NAFLD and with reduced plasma triglyceride levels in humans. However, the molecular mechanisms underlying these associations remain unclear. We hypothesized that TM6SF2 E167K affects hepatic very low-density lipoprotein (VLDL) secretion, and studied the kinetics of apolipoprotein B100 (apoB100) and triglyceride metabolism in VLDL in homozygous subjects. In 10 homozygote TM6SF2 E167K carriers and 10 matched controls, we employed stable-isotope tracer and compartmental modeling techniques to determine apoB100 and triglyceride kinetics in the two major VLDL subfractions: large triglyceride-rich VLDL1 and smaller, less triglyceride-rich VLDL2. VLDL1-apoB100 production was markedly reduced in homozygote TM6SF2 E167K carriers compared to controls. Likewise, VLDL1-triglyceride production was 35% lower in the TM6SF2 E167K carriers. In contrast, the direct production rates for VLDL2-apoB100 and triglyceride were not different between carriers and controls. In conclusion, the TM6SF2 E167K genetic variant was linked to a specific reduction in hepatic secretion of large triglyceride-rich VLDL1. The impaired secretion of VLDL1 explains the reduced plasma triglyceride concentration, and provides a basis for understanding the lower risk of cardiovascular disease associated with the TM6SF2 E167K genetic variant.Trial registration: Clinical Trials NCT04209816.
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| 3. |
- Ollila, Hanna M., et al.
(författare)
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Nightmares share genetic risk factors with sleep and psychiatric traits
- 2024
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Ingår i: Translational Psychiatry. - : Springer Nature. - 2158-3188. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Nightmares are vivid, extended, and emotionally negative or negative dreams that awaken the dreamer. While sporadic nightmares and bad dreams are common and generally harmless, frequent nightmares often reflect underlying pathologies of emotional regulation. Indeed, insomnia, depression, anxiety, or alcohol use have been associated with nightmares in epidemiological and clinical studies. However, the connection between nightmares and their comorbidities are poorly understood. Our goal was to examine the genetic risk factors for nightmares and estimate correlation or causality between nightmares and comorbidities. We performed a genome-wide association study (GWAS) in 45,255 individuals using a questionnaire-based assessment on the frequency of nightmares during the past month and genome-wide genotyping data. While the GWAS did not reveal individual risk variants, heritability was estimated at 5%. In addition, the genetic correlation analysis showed a robust correlation (rg > 0.4) of nightmares with anxiety (rg = 0.671, p = 7.507e−06), depressive (rg = 0.562, p = 1.282e−07) and posttraumatic stress disorders (rg = 0.4083, p = 0.0152), and personality trait neuroticism (rg = 0.667, p = 4.516e−07). Furthermore, Mendelian randomization suggested causality from insomnia to nightmares (beta = 0.027, p = 0.0002). Our findings suggest that nightmares share genetic background with psychiatric traits and that insomnia may increase an individual’s liability to experience frequent nightmares. Given the significant correlations with psychiatric and psychological traits, it is essential to grow awareness of how nightmares affect health and disease and systematically collect information about nightmares, especially from clinical samples and larger cohorts.
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| 4. |
- Widén, Elisabeth, et al.
(författare)
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How Communicating Polygenic and Clinical Risk for Atherosclerotic Cardiovascular Disease Impacts Health Behavior : an Observational Follow-up Study
- 2022
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Ingår i: Circulation: Genomic and Precision Medicine. - 2574-8300. ; 15:2, s. 003459-003459
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Tidskriftsartikel (refereegranskat)abstract
- Background: Prediction tools that combine polygenic risk scores with clinical factors provide a new opportunity for improved prediction and prevention of atherosclerotic cardiovascular disease, but the clinical utility of polygenic risk score has remained unclear. Methods: We collected a prospective cohort of 7342 individuals (64% women, mean age 56 years) and estimated their 10-year risk for atherosclerotic cardiovascular disease both by a traditional risk score and a composite score combining the effect of a polygenic risk score and clinical risk factors. We then tested how returning the personal risk information with an interactive web-tool impacted on the participants' health behavior. Results: When reassessed after 1.5 years by a clinical visit and questionnaires, 20.8% of individuals at high (>10%) 10-year atherosclerotic cardiovascular disease risk had seen a doctor, 12.4% reported weight loss, 14.2% of smokers had quit smoking, and 15.4% had signed up for health coaching online. Altogether, 42.6% of persons at high risk had made one or more health behavioral changes versus 33.5% of persons at low/average risk such that higher baseline risk predicted a favorable change (OR [CI], 1.53 [1.37-1.72] for persons at high risk versus the rest, P<0.001), with both high clinical (P<0.001) and genomic risk (OR [CI], 1.10 [1.03-1.17], P=0.003) contributing independently. Conclusions: Web-based communication of personal atherosclerotic cardiovascular disease risk-data including polygenic risk to middle-aged persons motivates positive changes in health behavior and the propensity to seek care. It supports integration of genomic information into clinical risk calculators as a feasible approach to enhance disease prevention.
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| 5. |
- Ahuja, Vasudha, et al.
(författare)
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Accuracy of 1-Hour Plasma Glucose During the Oral Glucose Tolerance Test in Diagnosis of Type 2 Diabetes in Adults : A Meta-analysis
- 2021
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Ingår i: Diabetes Care. - : American Diabetes Association. - 1935-5548 .- 0149-5992. ; 44:4, s. 1062-1069
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Forskningsöversikt (refereegranskat)abstract
- OBJECTIVE: One-hour plasma glucose (1-h PG) during the oral glucose tolerance test (OGTT) is an accurate predictor of type 2 diabetes. We performed a meta-analysis to determine the optimum cutoff of 1-h PG for detection of type 2 diabetes using 2-h PG as the gold standard. RESEARCH DESIGN AND METHODS: We included 15 studies with 35,551 participants from multiple ethnic groups (53.8% Caucasian) and 2,705 newly detected cases of diabetes based on 2-h PG during OGTT. We excluded cases identified only by elevated fasting plasma glucose and/or HbA1c. We determined the optimal 1-h PG threshold and its accuracy at this cutoff for detection of diabetes (2-h PG ≥11.1 mmol/L) using a mixed linear effects regression model with different weights to sensitivity/specificity (2/3, 1/2, and 1/3). RESULTS: Three cutoffs of 1-h PG, at 10.6 mmol/L, 11.6 mmol/L, and 12.5 mmol/L, had sensitivities of 0.95, 0.92, and 0.87 and specificities of 0.86, 0.91, and 0.94 at weights 2/3, 1/2, and 1/3, respectively. The cutoff of 11.6 mmol/L (95% CI 10.6, 12.6) had a sensitivity of 0.92 (0.87, 0.95), specificity of 0.91 (0.88, 0.93), area under the curve 0.939 (95% confidence region for sensitivity at a given specificity: 0.904, 0.946), and a positive predictive value of 45%. CONCLUSIONS: The 1-h PG of ≥11.6 mmol/L during OGTT has a good sensitivity and specificity for detecting type 2 diabetes. Prescreening with a diabetes-specific risk calculator to identify high-risk individuals is suggested to decrease the proportion of false-positive cases. Studies including other ethnic groups and assessing complication risk are warranted.
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| 6. |
- Dai, Qile, et al.
(författare)
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OTTERS: a powerful TWAS framework leveraging summary-level reference data
- 2023
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Most existing TWAS tools require individual-level eQTL reference data and thus are not applicable to summary-level reference eQTL datasets. The development of TWAS methods that can harness summary-level reference data is valuable to enable TWAS in broader settings and enhance power due to increased reference sample size. Thus, we develop a TWAS framework called OTTERS (Omnibus Transcriptome Test using Expression Reference Summary data) that adapts multiple polygenic risk score (PRS) methods to estimate eQTL weights from summary-level eQTL reference data and conducts an omnibus TWAS. We show that OTTERS is a practical and powerful TWAS tool by both simulations and application studies.
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| 7. |
- Kals, Mart, et al.
(författare)
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A genome-wide association study of outcome from traumatic brain injury
- 2022
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Ingår i: EBioMedicine. - : Elsevier. - 2352-3964. ; 77
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Factors such as age, pre-injury health, and injury severity, account for less than 35% of outcome variability in traumatic brain injury (TBI). While some residual outcome variability may be attributable to genetic factors, published candidate gene association studies have often been underpowered and subject to publication bias.METHODS: We performed the first genome- and transcriptome-wide association studies (GWAS, TWAS) of genetic effects on outcome in TBI. The study population consisted of 5268 patients from prospective European and US studies, who attended hospital within 24 h of TBI, and satisfied local protocols for computed tomography.FINDINGS: The estimated heritability of TBI outcome was 0·26. GWAS revealed no genetic variants with genome-wide significance (p < 5 × 10-8), but identified 83 variants in 13 independent loci which met a lower pre-specified sub-genomic statistical threshold (p < 10-5). Similarly, none of the genes tested in TWAS met tissue-wide significance. An exploratory analysis of 75 published candidate variants associated with 28 genes revealed one replicable variant (rs1800450 in the MBL2 gene) which retained significance after correction for multiple comparison (p = 5·24 × 10-4).INTERPRETATION: While multiple novel loci reached less stringent thresholds, none achieved genome-wide significance. The overall heritability estimate, however, is consistent with the hypothesis that common genetic variation substantially contributes to inter-individual variability in TBI outcome. The meta-analytic approach to the GWAS and the availability of summary data allows for a continuous extension with additional cohorts as data becomes available.FUNDING: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.
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| 8. |
- Kanoni, Stavroula, et al.
(författare)
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Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.
- 2022
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Ingår i: Genome biology. - : Springer Science and Business Media LLC. - 1474-760X .- 1465-6906 .- 1474-7596. ; 23:1
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Tidskriftsartikel (refereegranskat)abstract
- Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
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| 9. |
- Kiiskinen, Tuomo, et al.
(författare)
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Genetic predictors of lifelong medication-use patterns in cardiometabolic diseases
- 2023
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Ingår i: Nature Medicine. - : Springer Science and Business Media LLC. - 1078-8956 .- 1546-170X. ; 29:1, s. 209-218
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Tidskriftsartikel (refereegranskat)abstract
- Little is known about the genetic determinants of medication use in preventing cardiometabolic diseases. Using the Finnish nationwide drug purchase registry with follow-up since 1995, we performed genome-wide association analyses of longitudinal patterns of medication use in hyperlipidemia, hypertension and type 2 diabetes in up to 193,933 individuals (55% women) in the FinnGen study. In meta-analyses of up to 567,671 individuals combining FinnGen with the Estonian Biobank and the UK Biobank, we discovered 333 independent loci (P < 5 × 10–9) associated with medication use. Fine-mapping revealed 494 95% credible sets associated with the total number of medication purchases, changes in medication combinations or treatment discontinuation, including 46 credible sets in 40 loci not associated with the underlying treatment targets. The polygenic risk scores (PRS) for cardiometabolic risk factors were strongly associated with the medication-use behavior. A medication-use enhanced multitrait PRS for coronary artery disease matched the performance of a risk factor-based multitrait coronary artery disease PRS in an independent sample (UK Biobank, n = 343,676). In summary, we demonstrate medication-based strategies for identifying cardiometabolic risk loci and provide genome-wide tools for preventing cardiovascular diseases.
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| 10. |
- Marabita, Francesco, et al.
(författare)
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Multiomics and digital monitoring during lifestyle changes reveal independent dimensions of human biology and health
- 2022
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Ingår i: Cell Systems. - : Cell Press. - 2405-4712 .- 2405-4720. ; 13:3, s. 241-255.e7
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Tidskriftsartikel (refereegranskat)abstract
- We explored opportunities for personalized and predictive health care by collecting serial clinical measurements, health surveys, genomics, proteomics, autoantibodies, metabolomics, and gut microbiome data from 96 individuals who participated in a data-driven health coaching program over a 16-month period with continuous digital monitoring of activity and sleep. We generated a resource of >20,000 biological samples from this study and a compendium of >53 million primary data points for 558,032 distinct features. Multiomics factor analysis revealed distinct and independent molecular factors linked to obesity, diabetes, liver function, cardiovascular disease, inflammation, immunity, exercise, diet, and hormonal effects. For example, ethinyl estradiol, a common oral contraceptive, produced characteristic molecular and physiological effects, including increased levels of inflammation and impact on thyroid, cortisol levels, and pulse, that were distinct from other sources of variability observed in our study. In total, this work illustrates the value of combining deep molecular and digital monitoring of human health. A record of this paper's transparent peer review process is included in the supplemental information.
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