Synthetic CT Generation from MRI Using Improved DualGAN

Synthetic CT image generation from MRI scan is necessary to create radiotherapy plans without the need of co-registered MRI and CT scans. The chosen baseline adversarial model with cycle consistency permits unpaired image-to-image translation. Perceptual loss function term and coordinate convolutional layer were added to improve the quality of translated images. The proposed architecture was tested on paired MRI-CT dataset, where the synthetic CTs were compared to corresponding original CT images. The MAE between the synthetic CT images and the real CT scans is 61 HU computed inside of the true CTs body shape

Genetic landscape of chronic obstructive pulmonary disease identifies heterogeneous cell-type and phenotype associations

Chronic obstructive pulmonary disease (COPD) is the leading cause of respiratory mortality worldwide. Genetic risk loci provide new insights into disease pathogenesis. We performed a genome-wide association study in 35,735 cases and 222,076 controls from the UK Biobank and additional studies from the International COPD Genetics Consortium. We identified 82 loci associated with P < 5 × 10; 47 of these were previously described in association with either COPD or population-based measures of lung function. Of the remaining 35 new loci, 13 were associated with lung function in 79,055 individuals from the SpiroMeta consortium. Using gene expression and regulation data, we identified functional enrichment of COPD risk loci in lung tissue, smooth muscle, and several lung cell types. We found 14 COPD loci shared with either asthma or pulmonary fibrosis. COPD genetic risk loci clustered into groups based on associations with quantitative imaging features and comorbidities. Our analyses provide further support for the genetic susceptibility and heterogeneity of COPD

INTERACTIONS BETWEEN ANXIETY LEVELS AND LIFE HABITS CHANGES IN GENERAL POPULATION DURING THE PANDEMIC LOCKDOWN: DECREASED PHYSICAL ACTIVITY, FALLING ASLEEP LATE AND INTERNET BROWSING ABOUT COVID-19 ARE RISK FACTORS FOR ANXIETY, WHEREAS SOCIAL MEDIA USE IS NOT

Background. The COVID-19 pandemic has substantially contributed to increased anxiety rates among the general population worldwide. Pandemic-related health anxiety and worries about getting COVID-19 can lead to generalized anxiety and anxiety somatization, which, together with insalubrious daily life habits, are risk factors of worsening somatic health in people with SARS-Cov-2 infection. Subjects and methods: The current study is a part of the COMET-G project (40 countries, n=55589; approved by the Ethics Committee of the Aristotle University of Thessaloniki), which represents an intermediate analysis of data collected anonymously via online links from a national sample of the Russian general population (n=9936, 31.09±12.16 y.o., 58.7% females) to estimate anxiety using STAI-S and self-reported changes in anxiety and life habits (physical activity, nutrition and weight, internet use, sleep) during the lockdown. All statistical calculations (descriptive statistics, between group comparisons using chi-square test, MANOVA, ANOVA, significant at p<0.05) were performed with IBM SPSS 27. Results: Overall STAI-S scores were 29+- 5.4, a subjective feeling of anxiety increase was reported in 40.3% of respondents (43.9% significantly > in females), worsening to clinical anxiety in 2.1% (2.4% > in females). 54.2% of respondents reported decreased physical activity, 33.1% gained weight, 72% used internet more often, 52.6% experienced worries related to the information about COVID-19 (56.8% > in females). 88% experienced worsened sleep quality, 69.2% stayed up until late, 23.2% took sleeping pills, and 31% had nightmares in which they felt trapped. To ANOVA, such life habits as reduced physical activity during the lockdown, increased time spent online, internet browsing about COVID-19, tendency to stay up late, use of sleeping pills and disturbing dreams with scenario of being trapped were significantly related to worsening of clinical anxiety. However, eating behaviour, weight changes, and social media use did not contribute to the clinical anxiety increase. Conclusions: Factors of decreased physical activity and sleep disturbances related to the lockdown, as well as excessive internet browsing for information about COVID-19, emerged as risk factors for increased anxiety, more notably in women than in men. Preventive measures should be targeted against relevant factors imparting anxiety in the vulnerable population

INTERACTIONS BETWEEN ANXIETY LEVELS AND LIFE HABITS CHANGES IN GENERAL POPULATION DURING THE PANDEMIC LOCKDOWN: DECREASED PHYSICAL ACTIVITY, FALLING ASLEEP LATE AND INTERNET BROWSING ABOUT COVID-19 ARE RISK FACTORS FOR ANXIETY, WHEREAS SOCIAL MEDIA USE IS NOT

Background. The COVID-19 pandemic has substantially contributed to increased anxiety rates among the general population worldwide. Pandemic-related health anxiety and worries about getting COVID-19 can lead to generalized anxiety and anxiety somatization, which, together with insalubrious daily life habits, are risk factors of worsening somatic health in people with SARS-Cov-2 infection. Subjects and methods: The current study is a part of the COMET-G project (40 countries, n=55589; approved by the Ethics Committee of the Aristotle University of Thessaloniki), which represents an intermediate analysis of data collected anonymously via online links from a national sample of the Russian general population (n=9936, 31.09±12.16 y.o., 58.7% females) to estimate anxiety using STAI-S and self-reported changes in anxiety and life habits (physical activity, nutrition and weight, internet use, sleep) during the lockdown. All statistical calculations (descriptive statistics, between group comparisons using chi-square test, MANOVA, ANOVA, significant at p<0.05) were performed with IBM SPSS 27. Results: Overall STAI-S scores were 29+- 5.4, a subjective feeling of anxiety increase was reported in 40.3% of respondents (43.9% significantly > in females), worsening to clinical anxiety in 2.1% (2.4% > in females). 54.2% of respondents reported decreased physical activity, 33.1% gained weight, 72% used internet more often, 52.6% experienced worries related to the information about COVID-19 (56.8% > in females). 88% experienced worsened sleep quality, 69.2% stayed up until late, 23.2% took sleeping pills, and 31% had nightmares in which they felt trapped. To ANOVA, such life habits as reduced physical activity during the lockdown, increased time spent online, internet browsing about COVID-19, tendency to stay up late, use of sleeping pills and disturbing dreams with scenario of being trapped were significantly related to worsening of clinical anxiety. However, eating behaviour, weight changes, and social media use did not contribute to the clinical anxiety increase. Conclusions: Factors of decreased physical activity and sleep disturbances related to the lockdown, as well as excessive internet browsing for information about COVID-19, emerged as risk factors for increased anxiety, more notably in women than in men. Preventive measures should be targeted against relevant factors imparting anxiety in the vulnerable population

‘Location, Location, Location’: a spatial approach for rare variant analysis and an application to a study on non-syndromic cleft lip with or without cleft palate

Motivation: For the analysis of rare variants in sequence data, numerous approaches have been suggested. Fixed and flexible threshold approaches collapse the rare variant information of a genomic region into a test statistic with reduced dimensionality. Alternatively, the rare variant information can be combined in statistical frameworks that are based on suitable regression models, machine learning, etc. Although the existing approaches provide powerful tests that can incorporate information on allele frequencies and prior biological knowledge, differences in the spatial clustering of rare variants between cases and controls cannot be incorporated. Based on the assumption that deleterious variants and protective variants cluster or occur in different parts of the genomic region of interest, we propose a testing strategy for rare variants that builds on spatial cluster methodology and that guides the identification of the biological relevant segments of the region. Our approach does not require any assumption about the directions of the genetic effects. Results: In simulation studies, we assess the power of the clustering approach and compare it with existing methodology. Our simulation results suggest that the clustering approach for rare variants is well powered, even in situations that are ideal for standard methods. The efficiency of our spatial clustering approach is not affected by the presence of rare variants that have opposite effect size directions. An application to a sequencing study for non-syndromic cleft lip with or without cleft palate (NSCL/P) demonstrates its practical relevance. The proposed testing strategy is applied to a genomic region on chromosome 15q13.3 that was implicated in NSCL/P etiology in a previous genome-wide association study, and its results are compared with standard approaches. Availability: Source code and documentation for the implementation in R will be provided online. Currently, the R-implementation only supports genotype data. We currently are working on an extension for VCF files. Contact: [email protected]

Region-Based Analysis of Rare Genomic Variants in Whole-Genome Sequencing Datasets Reveal Two Novel Alzheimer’s Disease-Associated Genes: \u3cem\u3eDTNB\u3c/em\u3e and \u3cem\u3eDLG2\u3c/em\u3e

Alzheimer’s disease (AD) is a genetically complex disease for which nearly 40 loci have now been identified via genome-wide association studies (GWAS). We attempted to identify groups of rare variants (alternate allele frequency \u3c0.01) associated with AD in a region-based, whole-genome sequencing (WGS) association study (rvGWAS) of two independent AD family datasets (NIMH/NIA; 2247 individuals; 605 families). Employing a sliding window approach across the genome, we identified several regions that achieved association p values \u3c10−6, using the burden test or the SKAT statistic. The genomic region around the dystobrevin beta (DTNB) gene was identified with the burden and SKAT test and replicated in case/control samples from the ADSP study reaching genome-wide significance after meta-analysis (pmeta= 4.74 × 10−8 ). SKAT analysis also revealed region-based association around the Discs large homolog 2 (DLG2) gene and replicated in case/control samples from the ADSP study (pmeta = 1 × 10−6 ). In conclusion, in a region-based rvGWAS of AD we identified two novel AD genes, DLG2 and DTNB, based on association with rare variants

Whole-genome sequencing reveals new Alzheimer's disease-associated rare variants in loci related to synaptic function and neuronal development

Introduction Genome-wide association studies have led to numerous genetic loci associated with Alzheimer's disease (AD). Whole-genome sequencing (WGS) now permits genome-wide analyses to identify rare variants contributing to AD risk. Methods We performed single-variant and spatial clustering–based testing on rare variants (minor allele frequency [MAF] ≤1%) in a family-based WGS-based association study of 2247 subjects from 605 multiplex AD families, followed by replication in 1669 unrelated individuals. Results We identified 13 new AD candidate loci that yielded consistent rare-variant signals in discovery and replication cohorts (4 from single-variant, 9 from spatial-clustering), implicating these genes: FNBP1L, SEL1L, LINC00298, PRKCH, C15ORF41, C2CD3, KIF2A, APC, LHX9, NALCN, CTNNA2, SYTL3, and CLSTN2. Discussion Downstream analyses of these novel loci highlight synaptic function, in contrast to common AD-associated variants, which implicate innate immunity and amyloid processing. These loci have not been associated previously with AD, emphasizing the ability of WGS to identify AD-associated rare variants, particularly outside of the exome

Total zinc intake may modify the glucose-raising effect of a zinc transporter (SLC30A8) variant: a 14-cohort meta-analysis.

OBJECTIVE: Many genetic variants have been associated with glucose homeostasis and type 2 diabetes in genome-wide association studies. Zinc is an essential micronutrient that is important for β-cell function and glucose homeostasis. We tested the hypothesis that zinc intake could influence the glucose-raising effect of specific variants. RESEARCH DESIGN AND METHODS: We conducted a 14-cohort meta-analysis to assess the interaction of 20 genetic variants known to be related to glycemic traits and zinc metabolism with dietary zinc intake (food sources) and a 5-cohort meta-analysis to assess the interaction with total zinc intake (food sources and supplements) on fasting glucose levels among individuals of European ancestry without diabetes. RESULTS: We observed a significant association of total zinc intake with lower fasting glucose levels (β-coefficient ± SE per 1 mg/day of zinc intake: -0.0012 ± 0.0003 mmol/L, summary P value = 0.0003), while the association of dietary zinc intake was not significant. We identified a nominally significant interaction between total zinc intake and the SLC30A8 rs11558471 variant on fasting glucose levels (β-coefficient ± SE per A allele for 1 mg/day of greater total zinc intake: -0.0017 ± 0.0006 mmol/L, summary interaction P value = 0.005); this result suggests a stronger inverse association between total zinc intake and fasting glucose in individuals carrying the glucose-raising A allele compared with individuals who do not carry it. None of the other interaction tests were statistically significant. CONCLUSIONS: Our results suggest that higher total zinc intake may attenuate the glucose-raising effect of the rs11558471 SLC30A8 (zinc transporter) variant. Our findings also support evidence for the association of higher total zinc intake with lower fasting glucose levels

Total Zinc Intake May Modify the Glucose-Raising Effect of a Zinc Transporter (SLC30A8) Variant

Objective: Many genetic variants have been associated with glucose homeostasis and type 2 diabetes in genome-wide association studies. Zinc is an essential micronutrient that is important for β-cell function and glucose homeostasis. We tested the hypothesis that zinc intake could influence the glucose-raising effect of specific variants. Research Design and Methods: We conducted a 14-cohort meta-analysis to assess the interaction of 20 genetic variants known to be related to glycemic traits and zinc metabolism with dietary zinc intake (food sources) and a 5-cohort meta-analysis to assess the interaction with total zinc intake (food sources and supplements) on fasting glucose levels among individuals of European ancestry without diabetes. Results: We observed a significant association of total zinc intake with lower fasting glucose levels (β-coefficient ± SE per 1 mg/day of zinc intake: −0.0012 ± 0.0003 mmol/L, summary P value = 0.0003), while the association of dietary zinc intake was not significant. We identified a nominally significant interaction between total zinc intake and the SLC30A8 rs11558471 variant on fasting glucose levels (β-coefficient ± SE per A allele for 1 mg/day of greater total zinc intake: −0.0017 ± 0.0006 mmol/L, summary interaction P value = 0.005); this result suggests a stronger inverse association between total zinc intake and fasting glucose in individuals carrying the glucose-raising A allele compared with individuals who do not carry it. None of the other interaction tests were statistically significant. Conclusions: Our results suggest that higher total zinc intake may attenuate the glucose-raising effect of the rs11558471 SLC30A8 (zinc transporter) variant. Our findings also support evidence for the association of higher total zinc intake with lower fasting glucose levels