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- Fang, Li Tai, et al.
(författare)
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Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing
- 2021
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Ingår i: Nature Biotechnology. - : Springer Nature. - 1087-0156 .- 1546-1696. ; 39:9, s. 1151-1160
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Tidskriftsartikel (refereegranskat)abstract
- Tumor-normal paired DNA samples from a breast cancer cell line and a matched lymphoblastoid cell line enable calibration of clinical sequencing pipelines and benchmarking 'tumor-only' or 'matched tumor-normal' analyses. The lack of samples for generating standardized DNA datasets for setting up a sequencing pipeline or benchmarking the performance of different algorithms limits the implementation and uptake of cancer genomics. Here, we describe reference call sets obtained from paired tumor-normal genomic DNA (gDNA) samples derived from a breast cancer cell line-which is highly heterogeneous, with an aneuploid genome, and enriched in somatic alterations-and a matched lymphoblastoid cell line. We partially validated both somatic mutations and germline variants in these call sets via whole-exome sequencing (WES) with different sequencing platforms and targeted sequencing with >2,000-fold coverage, spanning 82% of genomic regions with high confidence. Although the gDNA reference samples are not representative of primary cancer cells from a clinical sample, when setting up a sequencing pipeline, they not only minimize potential biases from technologies, assays and informatics but also provide a unique resource for benchmarking 'tumor-only' or 'matched tumor-normal' analyses.
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- Glasbey, JC, et al.
(författare)
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- 2021
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swepub:Mat__t
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- Sun, Ryan, et al.
(författare)
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Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer
- 2021
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Ingår i: Genetic Epidemiology. - : John Wiley & Sons. - 0741-0395 .- 1098-2272. ; 45:1, s. 99-114
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Tidskriftsartikel (refereegranskat)abstract
- Clinical trial results have recently demonstrated that inhibiting inflammation by targeting the interleukin-1 beta pathway can offer a significant reduction in lung cancer incidence and mortality, highlighting a pressing and unmet need to understand the benefits of inflammation-focused lung cancer therapies at the genetic level. While numerous genome-wide association studies (GWAS) have explored the genetic etiology of lung cancer, there remains a large gap between the type of information that may be gleaned from an association study and the depth of understanding necessary to explain and drive translational findings. Thus, in this study we jointly model and integrate extensive multiomics data sources, utilizing a total of 40 genome-wide functional annotations that augment previously published results from the International Lung Cancer Consortium (ILCCO) GWAS, to prioritize and characterize single nucleotide polymorphisms (SNPs) that increase risk of squamous cell lung cancer through the inflammatory and immune responses. Our work bridges the gap between correlative analysis and translational follow-up research, refining GWAS association measures in an interpretable and systematic manner. In particular, reanalysis of the ILCCO data highlights the impact of highly associated SNPs from nuclear factor-kappa B signaling pathway genes as well as major histocompatibility complex mediated variation in immune responses. One consequence of prioritizing likely functional SNPs is the pruning of variants that might be selected for follow-up work by over an order of magnitude, from potentially tens of thousands to hundreds. The strategies we introduce provide informative and interpretable approaches for incorporating extensive genome-wide annotation data in analysis of genetic association studies.
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- Bayraktar, Abdulahad, et al.
(författare)
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Revealing the Molecular Mechanisms of Alzheimer's Disease Based on Network Analysis
- 2021
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Ingår i: International Journal of Molecular Sciences. - : MDPI. - 1661-6596 .- 1422-0067. ; 22:21
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Tidskriftsartikel (refereegranskat)abstract
- The complex pathology of Alzheimer's disease (AD) emphasises the need for comprehensive modelling of the disease, which may lead to the development of efficient treatment strategies. To address this challenge, we analysed transcriptome data of post-mortem human brain samples of healthy elders and individuals with late-onset AD from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP) and Mayo Clinic (MayoRNAseq) studies in the AMP-AD consortium. In this context, we conducted several bioinformatics and systems medicine analyses including the construction of AD-specific co-expression networks and genome-scale metabolic modelling of the brain in AD patients to identify key genes, metabolites and pathways involved in the progression of AD. We identified AMIGO1 and GRPRASP2 as examples of commonly altered marker genes in AD patients. Moreover, we found alterations in energy metabolism, represented by reduced oxidative phosphorylation and ATPase activity, as well as the depletion of hexanoyl-CoA, pentanoyl-CoA, (2E)-hexenoyl-CoA and numerous other unsaturated fatty acids in the brain. We also observed that neuroprotective metabolites (e.g., vitamins, retinoids and unsaturated fatty acids) tend to be depleted in the AD brain, while neurotoxic metabolites (e.g., beta-alanine, bilirubin) were more abundant. In summary, we systematically revealed the key genes and pathways related to the progression of AD, gained insight into the crucial mechanisms of AD and identified some possible targets that could be used in the treatment of AD.
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- Faxen, U. L., et al.
(författare)
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Generalizability of HFA-PEFF and H2FPEF Diagnostic Algorithms and Associations With Heart Failure Indices and Proteomic Biomarkers: Insights From PROMIS-HFpEF
- 2021
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Ingår i: Journal of Cardiac Failure. - : Elsevier BV. - 1071-9164 .- 1532-8414. ; 27:7, s. 756-765
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Tidskriftsartikel (refereegranskat)abstract
- Background: Diagnosing heart failure with preserved ejection fraction (HFpEF) remains challenging. We aimed to evaluate the generalizability of the HFA-PEFF (Heart Failure Association Pre-test assessment, Echocardiography & natriuretic peptide, Functional testing, Final etiology) and weighted H2FPEF (Heavy, 2 or more Hypertensive drugs, atrial Fibrillation, Pulmonary hypertension, Elder age > 60, elevated Filling pressures) diagnostic algorithms and associations with HF severity, coronary microvascular dysfunction and proteomic biomarkers. Methods and Results: Diagnostic likelihood of HFpEF was calculated in the prospective, multinational PROMIS-HFpEF (Prevalence of microvascular dysfunction in HFpEF) cohort using current European Society of Cardiology recommendations, HFA-PEFF and H2FPEF algorithms. Associations between the 2 algorithms and left atrial function, Doppler-based coronary flow reserve, 6-minute walk test, quality of life, and proteomic biomarkers were investigated. Of 181 patients with an EF of >= 50%, 129 (71%) and 94 (52%) fulfilled criteria for high likelihood HFpEF as per HFA-PEFF and H2FPEF, and 28% and 46% were classified as intermediate likelihood, requiring additional hemodynamic testing. High likelihood HFpEF patients were older with higher prevalence of atrial fibrillation and lower global longitudinal strain and left atrial reservoir strain (P<.001 for all variables). left atrial reservoir strain and global longitudinal strain were inversely associated with both HFA-PEFF and H2FPEF scores (TauB = -0.35 and -0.46 and -0.21 and -0.31; P<.001 for all). There were no associations between scoring and 6-minute walk test, quality of life, and coronary flow reserve. Both scores were associated with biomarkers related to inflammation, oxidative stress, and fibrosis. Conclusions: Although the HFA-PEFF and H2FPEF scores were associated with measures of HF severity and biomarkers related to HFpEF, they demonstrated a modest and differential ability to identify HFpEF noninvasively, necessitating additional functional testing to confirm the diagnosis.
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- Lind, Lars, et al.
(författare)
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Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight NCD Risk Factor Collaboration (NCD-RisC)
- 2021
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Ingår i: eLife. - : eLife Sciences Publications Ltd. - 2050-084X. ; 10
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Tidskriftsartikel (refereegranskat)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.
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