| 1. |
- Kanoni, Stavroula, et al.
(author)
-
Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.
- 2022
-
In: Genome biology. - : Springer Science and Business Media LLC. - 1474-760X .- 1465-6906 .- 1474-7596. ; 23:1
-
Journal article (peer-reviewed)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.
|
|
| 2. |
- Daelman, Bo, et al.
(author)
-
Frailty and cognitive function in middle-aged and older adults with congenital heart disease
- 2024
-
In: Journal of the American College of Cardiology. - : Elsevier. - 0735-1097 .- 1558-3597. ; 83:12, s. 1149-1159
-
Journal article (peer-reviewed)abstract
- Background: Life expectancy of patients with congenital heart disease (CHD) has increased rapidly, resulting in a growing and aging population. Recent studies have shown that older people with CHD have higher morbidity, health care use, and mortality. To maintain longevity and quality of life, understanding their evolving medical and psychosocial challenges is essential.Objectives: The authors describe the frailty and cognitive profile of middle-aged and older adults with CHD to identify predictor variables and to explore the relationship with hospital admissions and outpatient visits.Methods: Using a cross-sectional, multicentric design, we included 814 patients aged ≥40 years from 11 countries. Frailty phenotype was determined using the Fried method. Cognitive function was assessed by the Montreal Cognitive Assessment.Results: In this sample, 52.3% of patients were assessed as robust, 41.9% as prefrail, and 5.8% as frail; 38.8% had cognitive dysfunction. Multinomial regression showed that frailty was associated with older age, female sex, higher physiologic class, and comorbidities. Counterintuitively, patients with mild heart defects were more likely than those with complex lesions to be prefrail. Patients from middle-income countries displayed more prefrailty than those from higher-income countries. Logistic regression demonstrated that cognitive dysfunction was related to older age, comorbidities, and lower country-level income.Conclusions: Approximately one-half of included patients were (pre-)frail, and more than one-third experienced cognitive impairment. Frailty and cognitive dysfunction were identified in patients with mild CHD, indicating that these concerns extend beyond severe CHD. Assessing frailty and cognition routinely could offer valuable insights into this aging population.
|
|
| 3. |
|
|
| 4. |
- Kapun, Martin, et al.
(author)
-
Drosophila Evolution over Space and Time (DEST) : A New Population Genomics Resource
- 2021
-
In: Molecular biology and evolution. - : Oxford University Press (OUP). - 0737-4038 .- 1537-1719. ; 38:12, s. 5782-5805
-
Journal article (peer-reviewed)abstract
- Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome data sets from natural populations of this species have been published over the last years. A major challenge is the integration of disparate data sets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in >20 countries on four continents. Several of these locations have been sampled at different seasons across multiple years. This data set, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental metadata. A web-based genome browser and web portal provide easy access to the SNP data set. We further provide guidelines on how to use Pool-Seq data for model-based demographic inference. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan data set. Our resource will enable population geneticists to analyze spatiotemporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.
|
|
| 5. |
- Lind, Lars, et al.
(author)
-
Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight NCD Risk Factor Collaboration (NCD-RisC)
- 2021
-
In: eLife. - : eLife Sciences Publications Ltd. - 2050-084X. ; 10
-
Journal article (peer-reviewed)abstract
- From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions.
|
|
| 6. |
- Ramdas, S., et al.
(author)
-
A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids
- 2022
-
In: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 109:8, s. 1366-1387
-
Journal article (peer-reviewed)abstract
- A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.
|
|
| 7. |
|
|
| 8. |
- Amare, Azmeraw, et al.
(author)
-
Association of Polygenic Score and the involvement of Cholinergic and Glutamatergic Pathways with Lithium Treatment Response in Patients with Bipolar Disorder.
- 2023
-
In: Research square. - : Research Square Platform LLC.
-
Journal article (peer-reviewed)abstract
- Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N=2,367) and replicated in the combined PsyCourse (N=89) and BipoLife (N=102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P<����������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������.
|
|
| 9. |
- Amare, Azmeraw T, et al.
(author)
-
Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder.
- 2023
-
In: Molecular psychiatry. - 1476-5578. ; 28, s. 5251-5261
-
Journal article (peer-reviewed)abstract
- Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental healthdisorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N=2367) and replicated in the combined PsyCourse (N=89) and BipoLife (N=102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P<0.05. Li+PGS was positively associated with lithium treatment response in the ConLi+Gen cohort, in both the categorical (P=9.8×10-12, R2=1.9%) and continuous (P=6.4×10-9, R2=2.6%) outcomes. Compared to bipolar patients in the 1st decile of the risk distribution, individuals in the 10th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P=3.9×10-4, R2=0.9%), but not for the continuous outcome (P=0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li+PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment.
|
|
| 10. |
- Breznau, Nate, et al.
(author)
-
Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty
- 2022
-
In: Proceedings of the National Academy of Sciences of the United States of America. - : National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 119:44
-
Journal article (peer-reviewed)abstract
- This study explores how researchers analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each teams workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings.
|
|
