Author Correction: Imaging and clinical data archive for head and neck squamous cell carcinoma patients treated with radiotherapy

Grossberg, Aaron J.; Mohamed, A.S.R.; Elhalawani, Hesham; Bennett, William; Smith, Kirk E.; Nolan, Tracy S.; Williams, Bowman; Chamchod, Sasikarn; Heukelom, J.; Kantor, Michael; Browne, Theodora; Hutcheson, Katherine A.; Gunn, G. Brandon; Garden, Adam S.; Morrison, William H.; Frank, Steven J.; Rosenthal, D.I.; Freymann, John; Fuller, Clifton D.

doi:10.1038/s41597-018-0002-5

Cited by 173 publications

(115 citation statements)

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“…An overview of the post-mortem brain samples used in our analysis pipeline is provided in S1 and S2 Tables. Details on post-mortem brain sample collection, tissue and RNA preparation, sequencing, and sample quality control can be found in published work related to each cohort [12][13][14]. Multiple variables, such as sex, age of death, and sequencing batch effects were used as covariates in the normalization process to remove possible confounding factors across cohorts (Methods) [15].…”

Section: Description Of Post-mortem Transcriptome Study Populationsmentioning

confidence: 99%

Transcriptomic stratification of late-onset Alzheimer's cases reveals novel genetic modifiers of disease pathology

et al. 2020

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Late-Onset Alzheimer's disease (LOAD) is a common, complex genetic disorder wellknown for its heterogeneous pathology. The genetic heterogeneity underlying common, complex diseases poses a major challenge for targeted therapies and the identification of novel disease-associated variants. Case-control approaches are often limited to examining a specific outcome in a group of heterogenous patients with different clinical characteristics. Here, we developed a novel approach to define relevant transcriptomic endophenotypes and stratify decedents based on molecular profiles in three independent human LOAD cohorts. By integrating post-mortem brain gene co-expression data from 2114 human samples with LOAD, we developed a novel quantitative, composite phenotype that can better account for the heterogeneity in genetic architecture underlying the disease. We used iterative weighted gene co-expression network analysis (WGCNA) to reduce data dimensionality and to isolate gene sets that are highly co-expressed within disease subtypes and represent specific molecular pathways. We then performed single variant association testing using whole genome-sequencing data for the novel composite phenotype in order to identify genetic loci that contribute to disease heterogeneity. Distinct LOAD subtypes were identified for all three study cohorts (two in ROSMAP, three in Mayo Clinic, and two in Mount Sinai Brain Bank). Single variant association analysis identified a genome-wide significant variant in TMEM106B (p-value < 5×10 −8 , rs1990620 G) in the ROSMAP cohort that confers protection from the inflammatory LOAD subtype. Taken together, our novel approach can be used to stratify LOAD into distinct molecular subtypes based on affected disease pathways.

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Section: Description Of Post-mortem Transcriptome Study Populationsmentioning

confidence: 99%

Transcriptomic stratification of late-onset Alzheimer's cases reveals novel genetic modifiers of disease pathology

et al. 2020

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“…The climatic variables are composed of 19 bioclimatic variables of current temperature and precipitation obtained from CHELSA (Climatologies at High Resolution for the Earth's Land Surface Areas) database (http://chelsa-climate.org/), which provides up to date information with grid cells of 1km resolution layers [70]. The topographic variables are composed of altitude and slope (Fig 2A), obtained for cells of 1km of resolution from the earthenv database (http://www.earthenv.org/ topography; [71]). The percentage of soil cover by native vegetation in 2016 was obtained from the MapBiomas database (http://mapbiomas.org), considering a buffer of 1km for each point.…”

Section: Environmental Anthropogenic and Spatial Datamentioning

confidence: 99%

Stream fish metacommunity organisation across a Neotropical ecoregion: The role of environment, anthropogenic impact and dispersal-based processes

et al. 2020

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Understanding how assemblages are structured in space and the factors promoting their distributions is one of the main goals in Ecology, however, studies regarding the distribution of organisms at larger scales remain biased towards terrestrial groups. We attempt to understand if the structure of stream fish metacommunities across a Neotropical ecoregion (Upper Paraná-drainage area of 820,000 km 2) are affected by environmental variables, describing natural environmental gradient, anthropogenic impacts and spatial predictors. For this, we obtained 586 sampling points of fish assemblages in the ecoregion and data on environmental and spatial predictors that potentially affect fish assemblages. We calculated the local beta diversity (Local Contribution to Beta Diversity, LCBD) and alpha diversity from the species list, to be used as response variables in the partial regression models, while the anthropogenic impacts, environmental gradient and spatial factors were used as predictors. We found a high total beta diversity for the ecoregion (0.41) where the greatest values for each site sampled were located at the edges of the ecoregion, while richer communities were found more centrally. All sets of predictors explained the LCBD and alpha diversity, but the most important was dispersal variables, followed by the natural environmental gradient and anthropogenic impact. However, we found an increase in the models' prediction power through the shared effect. Results suggest that environmental filters (i.e. environmental variables such as climate, hydrology and anthropogenic impact) and dispersal limitation together shape fish assemblages of the Upper Paraná ecoregion, showing the importance of using multiple sets of predictors to understand the processes structuring biodiversity distribution.

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“…A total of 41 studies were included in this review, with different methodologies: one systematic review (16), one consensus paper (17), one data descriptor (18), nine randomized trials (6, 11, 19–25), 12 cohort studies (3, 7–9, 15, 26–32), three randomized controlled trials (4, 5, 33), three cross-sectional studies (34–36), two prospective non-randomized trials (37, 38), eight retrospective studies (10, 12–14, 39–42), and one case-control study (43).…”

Section: Resultsmentioning

confidence: 99%

“…In two studies, the chosen method was both BIA and DXA (27, 28). CT/ positron-emission tomography-CT (PET-CT) was applied in 11 studies (10, 12–15, 18, 32, 39–42) and one also included MRI (39). In two studies, body composition was assessed with skinfold measures alone (35, 38), one of which also used circumferences (35) and one study only used BIVA (37).…”

Section: Resultsmentioning

confidence: 99%

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Body Composition Evaluation in Head and Neck Cancer Patients: A Review

et al. 2019

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Introduction: Head and neck cancer (HNC) patients show a high risk of malnutrition due to the lifestyle habits adopted prior to the diagnosis as well as to the compromising impact of both the anatomical location of the tumor and the treatment modalities on food intake. Weight change, measurement of skinfold thickness, biochemical parameters, bioelectrical impedance analysis (BIA), computed tomography (CT), magnetic resonance (MRI), or dual-energy x-ray absorptiometry (DXA) are available techniques to evaluate nutritional status and/or body composition in the clinical practice. Evaluating body composition alterations in HNC patients is essential to be able to offer the best therapeutical interventions. In this paper, we review the existing literature regarding body composition evaluation in HNC patients to determine, which is the most suitable method for this population, regarding availability in the day-to-day practice, patient burden, cost, sensibility, and specificity.Methodology: A literature search for relevant papers indexed in MEDLINE, Cochrane Library and Scielo was conducted, with no publication date restriction and for all published articles until the 31 January, 2019. All the papers written in English, with interventions in humans, exclusively considering HNC patients were selected.Results: A total of 41 studies with different methodologies were included in this review. In 15 studies BIA was the used assessment method and three of them also evaluated skinfold thickness and one was a bioelectric impedance vector analysis (BIVA). Body composition assessment was made with DXA in eight studies, one of which also included muscle biopsies. In two studies the chosen method was both BIA and DXA. CT/ positron emission tomography-CT was applied in 11 studies and one also included MRI. In two studies body composition was assessed with skinfold measurements alone and one study only used BIVA.Conclusions: Despite the different existing body composition assessment tools, it seems that skeletal muscle mass (SMM) measurement at the level of cervical spine C3 vertebra may be a reliable method for SMM assessment as it strongly correlates with cross-sectional area measures at the level of L3 and it allows a cost-effective body composition assessment without the need for additional radiation exposure.

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Author Correction: Imaging and clinical data archive for head and neck squamous cell carcinoma patients treated with radiotherapy

Abstract: In the original version of the Data Descriptor the surname of author Hesham Elhalawani was misspelled. This has now been corrected in the HTML and PDF versions.

Cited by 173 publications

References 0 publications

Transcriptomic stratification of late-onset Alzheimer's cases reveals novel genetic modifiers of disease pathology

Transcriptomic stratification of late-onset Alzheimer's cases reveals novel genetic modifiers of disease pathology

Stream fish metacommunity organisation across a Neotropical ecoregion: The role of environment, anthropogenic impact and dispersal-based processes

Body Composition Evaluation in Head and Neck Cancer Patients: A Review

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