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We aimed to unravel the mechanisms connecting adiposity to type 2 diabetes. We used MR-Clust to cluster independent genetic variants associated with body fat percentage (388 variants) and BMI (540 variants) based on their impact on type 2 diabetes. We identified five clusters of adiposity-increasing alleles associated with higher type 2 diabetes risk (unfavorable adiposity) and three clusters associated with lower risk (favorable adiposity). We then characterized each cluster based on various biomarkers, metabolites, and MRI-based measures of fat distribution and muscle quality. Analyzing the metabolic signatures of these clusters revealed two primary mechanisms connecting higher adiposity to reduced type 2 diabetes risk. The first involves higher adiposity in subcutaneous tissues (abdomen and thigh), lower liver fat, improved insulin sensitivity, and decreased risk of cardiometabolic diseases and diabetes complications. The second mechanism is characterized by increased body size and enhanced muscle quality, with no impact on cardiometabolic outcomes. Furthermore, our findings unveil diverse mechanisms linking higher adiposity to higher disease risk, such as cholesterol pathways or inflammation. These results reinforce the existence of adiposity-related mechanisms that may act as protective factors against type 2 diabetes and its complications, especially when accompanied by reduced ectopic liver fat., (© 2024 by the American Diabetes Association.)

Introduction: Magnetic resonance imaging (MRI) enables direct measurements of muscle volume and quality, allowing for an in-depth understanding of their associations with anthropometric traits, and health conditions. However, it is unclear which muscle volume measurements: total muscle volume, regional measurements, measurements of muscle quality: intermuscular adipose tissue (IMAT) or proton density fat fraction (PDFF), are most informative and associate with relevant health conditions such as dynapenia and frailty. Methods: We have measured image-derived phenotypes (IDPs) including total and regional muscle volumes and measures of muscle quality, derived from the neck-to-knee Dixon images in 44,520 UK Biobank participants. We further segmented paraspinal muscle from 2D quantitative MRI to quantify muscle PDFF and iron concentration. We defined dynapenia based on grip strength below sex-specific cut-off points and frailty based on five criteria (weight loss, exhaustion, grip strength, low physical activity and slow walking pace). We used logistic regression to investigate the association between muscle volume and quality measurements and dynapenia and frailty. Results: Muscle volumes were significantly higher in male compared with female participants, even after correcting for height while, IMAT (corrected for muscle volume) and paraspinal muscle PDFF were significantly higher in female compared with male participants. From the overall cohort, 7.6% (N = 3,261) were identified with dynapenia, and 1.1% (N = 455) with frailty. Dynapenia and frailty were positively associated with age and negatively associated with physical activity levels. Additionally, reduced muscle volume and quality measurements were associated with both dynapenia and frailty. In dynapenia, muscle volume IDPs were most informative, particularly total muscle exhibiting odds ratios (OR) of 0.392, while for frailty, muscle quality was found to be most informative, in particular thigh IMAT volume indexed to height squared (OR = 1.396), both with p -values below the Bonferroni-corrected threshold ( p < 8.8 × 10 - 5 ). Conclusion: Our fully automated method enables the quantification of muscle volumes and quality suitable for large population-based studies. For dynapenia, muscle volumes particularly those including greater body coverage such as total muscle are the most informative, whilst, for frailty, markers of muscle quality were the most informative IDPs. These results suggest that different measurements may have varying diagnostic values for different health conditions., Competing Interests: MC, RS, and ES are employees of Calico Life Sciences LLC. YL is a former employee of Calico Life Sciences LLC. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Thanaj, Basty, Whitcher, Sorokin, Liu, Srinivasan, Cule, Thomas and Bell.)

Background: Morphometric image analysis enables the quantification of differences in the shape and size of organs between individuals., Methods: Here we have applied morphometric methods to the study of the liver by constructing surface meshes from liver segmentations from abdominal MRI images in 33,434 participants in the UK Biobank. Based on these three dimensional mesh vertices, we evaluated local shape variations and modelled their association with anthropometric, phenotypic and clinical conditions, including liver disease and type-2 diabetes., Results: We found that age, body mass index, hepatic fat and iron content, as well as, health traits were significantly associated with regional liver shape and size. Interaction models in groups with specific clinical conditions showed that the presence of type-2 diabetes accelerates age-related changes in the liver, while presence of liver fat further increased shape variations in both type-2 diabetes and liver disease., Conclusions: The results suggest that this novel approach may greatly benefit studies aiming at better categorisation of pathologies associated with acute and chronic clinical conditions., (© 2023. The Author(s).)

Background: Organ measurements derived from magnetic resonance imaging (MRI) have the potential to enhance our understanding of the precise phenotypic variations underlying many clinical conditions., Methods: We applied morphometric methods to study the kidneys by constructing surface meshes from kidney segmentations from abdominal MRI data in 38,868 participants in the UK Biobank. Using mesh-based analysis techniques based on statistical parametric maps (SPMs), we were able to detect variations in specific regions of the kidney and associate those with anthropometric traits as well as disease states including chronic kidney disease (CKD), type-2 diabetes (T2D), and hypertension. Statistical shape analysis (SSA) based on principal component analysis was also used within the disease population and the principal component scores were used to assess the risk of disease events., Results: We show that CKD, T2D and hypertension were associated with kidney shape. Age was associated with kidney shape consistently across disease groups. Body mass index (BMI) and waist-to-hip ratio (WHR) were also associated with kidney shape for the participants with T2D. Using SSA, we were able to capture kidney shape variations, relative to size, angle, straightness, width, length, and thickness of the kidneys, within disease populations. We identified significant associations between both left and right kidney length and width and incidence of CKD (hazard ratio (HR): 0.74, 95% CI: 0.61-0.90, p < 0.05, in the left kidney; HR: 0.76, 95% CI: 0.63-0.92, p < 0.05, in the right kidney) and hypertension (HR: 1.16, 95% CI: 1.03-1.29, p < 0.05, in the left kidney; HR: 0.87, 95% CI: 0.79-0.96, p < 0.05, in the right kidney)., Conclusions: The results suggest that shape-based analysis of the kidneys can augment studies aiming at the better categorisation of pathologies associated with chronic kidney conditions., (© 2023. The Author(s).)

Peripheral artery disease (PAD) is a form of atherosclerotic cardiovascular disease, affecting ∼8 million Americans, and is known to have racial and ethnic disparities. PAD has been reported to have a significantly higher prevalence in African Americans (AAs) compared to non-Hispanic European Americans (EAs). Hispanic/Latinos (HLs) have been reported to have lower or similar rates of PAD compared to EAs, despite having a paradoxically high burden of PAD risk factors; however, recent work suggests prevalence may differ between sub-groups. Here, we examined a large cohort of diverse adults in the Bio Me biobank in New York City. We observed the prevalence of PAD at 1.7% in EAs vs. 8.5% and 9.4% in AAs and HLs, respectively, and among HL sub-groups, the prevalence was found at 11.4% and 11.5% in Puerto Rican and Dominican populations, respectively. Follow-up analysis that adjusted for common risk factors demonstrated that Dominicans had the highest increased risk for PAD relative to EAs [OR = 3.15 (95% CI 2.33-4.25), p < 6.44 × 10 -14 ]. To investigate whether genetic factors may explain this increased risk, we performed admixture mapping by testing the association between local ancestry and PAD in Dominican Bio Me participants (N = 1,813) separately from European, African, and Native American (NAT) continental ancestry tracts. The top association with PAD was an NAT ancestry tract at chromosome 2q35 [OR = 1.96 (SE = 0.16), p < 2.75 × 10 -05 ) with 22.6% vs. 12.9% PAD prevalence in heterozygous NAT tract carriers versus non-carriers, respectively. Fine-mapping at this locus implicated tag SNP rs78529201 located within a long intergenic non-coding RNA (lincRNA) LINC00607 , a gene expression regulator of key genes related to thrombosis and extracellular remodeling of endothelial cells, suggesting a putative link of the 2q35 locus to PAD etiology. Efforts to reproduce the signal in other Hispanic cohorts were unsuccessful. In summary, we showed how leveraging health system data helped understand nuances of PAD risk across HL sub-groups and admixture mapping approaches elucidated a putative risk locus in a Dominican population., Competing Interests: EK received personal fees from Illumina, 23andMe, Allelica, and Regeneron Pharmaceuticals, received research funding from Allelica, and serves as a scientific advisory board member for Encompass Bio, Foresite Labs, and Galateo Bio. NA-H is an employee and equity holder of 23andMe; serves as a scientific advisory board member for Allelica; received personal fees from Genentech, Allelica, and 23andMe; received research funding from Akcea; and was previously employed by Regeneron Pharmaceuticals. ES is an employee of Calico Life Sciences LLC. SA received consulting fees from Variant Bio and Biogen Inc. CG owns stock in 23andMe and serves as an advisory board member for Encompass Bio. DK serve as scientific advisor to Bitterroot Bio, Inc. SMD receives research support from RenalytixAI and Novo Nordisk, outside the scope of the current research. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Cullina, Wojcik, Shemirani, Klarin, Gorman, Sorokin, Gignoux, Belbin, Pyarajan, Asgari, Tsao, Damrauer, Abul-Husn and Kenny.)

The main drivers of COVID-19 disease severity and the impact of COVID-19 on long-term health after recovery are yet to be fully understood. Medical imaging studies investigating COVID-19 to date have mostly been limited to small datasets and post-hoc analyses of severe cases. The UK Biobank recruited recovered SARS-CoV-2 positive individuals (n = 967) and matched controls (n = 913) who were extensively imaged prior to the pandemic and underwent follow-up scanning. In this study, we investigated longitudinal changes in body composition, as well as the associations of pre-pandemic image-derived phenotypes with COVID-19 severity. Our longitudinal analysis, in a population of mostly mild cases, associated a decrease in lung volume with SARS-CoV-2 positivity. We also observed that increased visceral adipose tissue and liver fat, and reduced muscle volume, prior to COVID-19, were associated with COVID-19 disease severity. Finally, we trained a machine classifier with demographic, anthropometric and imaging traits, and showed that visceral fat, liver fat and muscle volume have prognostic value for COVID-19 disease severity beyond the standard demographic and anthropometric measurements. This combination of image-derived phenotypes from abdominal MRI scans and ensemble learning to predict risk may have future clinical utility in identifying populations at-risk for a severe COVID-19 outcome., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: EPS, RS, and MC are employees of Calico Life Sciences LLC. NB, BW, JDB, MT, and ELT have no competing interests., (Copyright: © 2023 Basty et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Peripheral artery disease (PAD) is a form of atherosclerotic cardiovascular disease, affecting ∼8 million Americans, and is known to have racial and ethnic disparities. PAD has been reported to have significantly higher prevalence in African Americans (AAs) compared to non-Hispanic European Americans (EAs). Hispanic/Latinos (HLs) have been reported to have lower or similar rates of PAD compared to EAs, despite having a paradoxically high burden of PAD risk factors, however recent work suggests prevalence may differ between sub-groups. Here we examined a large cohort of diverse adults in the Bio Me biobank in New York City (NYC). We observed the prevalence of PAD at 1.7% in EAs vs 8.5% and 9.4% in AAs and HLs, respectively; and among HL sub-groups, at 11.4% and 11.5% in Puerto Rican and Dominican populations, respectively. Follow-up analysis that adjusted for common risk factors demonstrated that Dominicans had the highest increased risk for PAD relative to EAs (OR=3.15 (95% CI 2.33-4.25), P <6.44×10 -14 ). To investigate whether genetic factors may explain this increased risk, we performed admixture mapping by testing the association between local ancestry (LA) and PAD in Dominican Bio Me participants (N=1,940) separately for European (EUR), African (AFR) and Native American (NAT) continental ancestry tracts. We identified a NAT ancestry tract at chromosome 2q35 that was significantly associated with PAD (OR=2.05 (95% CI 1.51-2.78), P <4.06×10 -6 ) with 22.5% vs 12.5% PAD prevalence in heterozygous NAT tract carriers versus non-carriers, respectively. Fine-mapping at this locus implicated tag SNP rs78529201 located within a long intergenic non-coding RNA (lincRNA) LINC00607 , a gene expression regulator of key genes related to thrombosis and extracellular remodeling of endothelial cells, suggesting a putative link of the 2q35 locus to PAD etiology. In summary, we showed how leveraging health systems data helped understand nuances of PAD risk across HL sub-groups and admixture mapping approaches elucidated a novel risk locus in a Dominican population.

Chemical-shift encoded MRI (CSE-MRI) is a widely used technique for the study of body composition and metabolic disorders, where derived fat and water signals enable the quantification of adipose tissue and muscle. The UK Biobank is acquiring whole-body Dixon MRI (a specific implementation of CSE-MRI) for over 100,000 participants. Current processing methods associated with large whole-body volumes are time intensive and prone to artifacts during fat-water separation performed by the scanner, making quantitative analysis challenging. The most common artifacts are fat-water swaps, where the labels are inverted at the voxel level. It is common for researchers to discard swapped data (generally around 10%), which is wasteful and may lead to unintended biases. Given the large number of whole-body Dixon MRI acquisitions in the UK Biobank, thousands of swaps are expected to be present in the fat and water volumes from image reconstruction performed on the scanner. If they go undetected, errors will propagate into processes such as organ segmentation, and dilute the results in population-based analyses. There is a clear need for a robust method to accurately separate fat and water volumes in big data collections like the UK Biobank. We formulate fat-water separation as a style transfer problem, where swap-free fat and water volumes are predicted from the acquired Dixon MRI data using a conditional generative adversarial network, and introduce a new loss function for the generator model. Our method is able to predict highly accurate fat and water volumes free from artifacts in the UK Biobank. We show that our model separates fat and water volumes using either single input (in-phase only) or dual input (in-phase and opposed-phase) data, with the latter producing superior results. Our proposed method enables faster and more accurate downstream analysis of body composition from Dixon MRI in population studies by eliminating the need for visual inspection or discarding data due to fat-water swaps., Supplementary Information: The online version contains supplementary material available at 10.1186/s40537-022-00677-1., Competing Interests: Competing interestsMC and EPS are employees of Calico Life Sciences LLC. YL is a former employee of Calico Life Sciences LLC. BW, MT, NB, JDB and ELT declare no competing interests., (© The Author(s) 2023.)

The spleen plays a key role in iron homeostasis. It is the largest filter of the blood and performs iron reuptake from old or damaged erythrocytes. Despite this role, spleen iron concentration has not been measured in a large, population-based cohort. In this study, we quantify spleen iron in 41,764 participants of the UK Biobank by using magnetic resonance imaging and provide a reference range for spleen iron in an unselected population. Through genome-wide association study, we identify associations between spleen iron and regulatory variation at two hereditary spherocytosis genes, ANK1 and SPTA1. Spherocytosis-causing coding mutations in these genes are associated with lower reticulocyte volume and increased reticulocyte percentage, while these common alleles are associated with increased expression of ANK1 and SPTA1 in blood and with larger reticulocyte volume and reduced reticulocyte percentage. As genetic modifiers, these common alleles may explain mild spherocytosis phenotypes that have been observed clinically. Our genetic study also identifies a signal that co-localizes with a splicing quantitative trait locus for MS4A7, and we show this gene is abundantly expressed in the spleen and in macrophages. The combination of deep learning and efficient image processing enables non-invasive measurement of spleen iron and, in turn, characterization of genetic factors related to the lytic phase of the erythrocyte life cycle and iron reuptake in the spleen., Competing Interests: Declaration of interests E.P.S., R.L.C., and M.C. are employees of Calico Life Sciences LLC. Y.L. is a former employee of Calico Life Sciences LLC., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Longitudinal studies provide unique insights into the impact of environmental factors and lifespan issues on health and disease. Here we investigate changes in body composition in 3088 free-living participants, part of the UK Biobank in-depth imaging study. All participants underwent neck-to-knee MRI scans at the first imaging visit and after approximately two years (second imaging visit). Image-derived phenotypes for each participant were extracted using a fully-automated image processing pipeline, including volumes of several tissues and organs: liver, pancreas, spleen, kidneys, total skeletal muscle, iliopsoas muscle, visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue, as well as fat and iron content in liver, pancreas and spleen. Overall, no significant changes were observed in BMI, body weight, or waist circumference over the scanning interval, despite some large individual changes. A significant decrease in grip strength was observed, coupled to small, but statistically significant, decrease in all skeletal muscle measurements. Significant increases in VAT and intermuscular fat in the thighs were also detected in the absence of changes in BMI, waist circumference and ectopic-fat deposition. Adjusting for disease status at the first imaging visit did not have an additional impact on the changes observed. In summary, we show that even after a relatively short period of time significant changes in body composition can take place, probably reflecting the obesogenic environment currently inhabited by most of the general population in the United Kingdom., (© 2022. The Author(s).)

Objective: Fat content and volume of liver and pancreas are associated with risk of diabetes in observational studies; whether these associations are causal is unknown. We conducted a Mendelian randomization (MR) study to examine causality of such associations., Research Design and Methods: We used genetic variants associated (P < 5 × 10-8) with the exposures (liver and pancreas volume and fat content) using MRI scans of UK Biobank participants (n = 32,859). We obtained summary-level data for risk of type 1 (9,358 cases) and type 2 (55,005 cases) diabetes from the largest available genome-wide association studies. We performed inverse-variance weighted MR as main analysis and several sensitivity analyses to assess pleiotropy and to exclude variants with potential pleiotropic effects., Results: Observationally, liver fat and volume were associated with type 2 diabetes (odds ratio per 1 SD higher exposure 2.16 [2.02, 2.31] and 2.11 [1.96, 2.27], respectively). Pancreatic fat was associated with type 2 diabetes (1.42 [1.34, 1.51]) but not type 1 diabetes, and pancreas volume was negatively associated with type 1 diabetes (0.42 [0.36, 0.48]) and type 2 diabetes (0.73 [0.68, 0.78]). MR analysis provided evidence only for a causal role of liver fat and pancreas volume in risk of type 2 diabetes (1.27 [1.08, 1.49] or 27% increased risk and 0.76 [0.62, 0.94] or 24% decreased risk per 1SD, respectively) and no causal associations with type 1 diabetes., Conclusions: Our findings assist in understanding the causal role of ectopic fat in the liver and pancreas and of organ volume in the pathophysiology of type 1 and type 2 diabetes., (© 2022 by the American Diabetes Association.)

Cardiometabolic diseases are an increasing global health burden. While socioeconomic, environmental, behavioural, and genetic risk factors have been identified, a better understanding of the underlying mechanisms is required to develop more effective interventions. Magnetic resonance imaging (MRI) has been used to assess organ health, but biobank-scale studies are still in their infancy. Using over 38,000 abdominal MRI scans in the UK Biobank, we used deep learning to quantify volume, fat, and iron in seven organs and tissues, and demonstrate that imaging-derived phenotypes reflect health status. We show that these traits have a substantial heritable component (8-44%) and identify 93 independent genome-wide significant associations, including four associations with liver traits that have not previously been reported. Our work demonstrates the tractability of deep learning to systematically quantify health parameters from high-throughput MRI across a range of organs and tissues, and use the largest-ever study of its kind to generate new insights into the genetic architecture of these traits., Competing Interests: YL, Nv, MC Employee, Calico Life Sciences LLC. This work was funded by Calico Life Sciences LLC. NB, BW, JB, ET No competing interests declared, ES Employee, Calico Life Sciences LLC.This work was funded by Calico Life Sciences LLC., (© 2021, Liu et al.)

Understanding population health disparities is an essential component of equitable precision health efforts. Epidemiology research often relies on definitions of race and ethnicity, but these population labels may not adequately capture disease burdens and environmental factors impacting specific sub-populations. Here, we propose a framework for repurposing data from electronic health records (EHRs) in concert with genomic data to explore the demographic ties that can impact disease burdens. Using data from a diverse biobank in New York City, we identified 17 communities sharing recent genetic ancestry. We observed 1,177 health outcomes that were statistically associated with a specific group and demonstrated significant differences in the segregation of genetic variants contributing to Mendelian diseases. We also demonstrated that fine-scale population structure can impact the prediction of complex disease risk within groups. This work reinforces the utility of linking genomic data to EHRs and provides a framework toward fine-scale monitoring of population health., Competing Interests: Declaration of interests N.S.A.-H. was previously employed by Regeneron Pharmaceuticals and has received a speaker honorarium from Genentech. E.E.K. has received speaker honoraria from Illumina and Regeneron Pharmaceuticals. S.W. is currently employed at Tempus. A.M. is currently employed at Regeneron. E.P.S. is currently employed at Calico. D.S.P. is currently employed at Ancestry. A.A. is currently employed at 23&Me. The remaining authors declare no competing interests., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background & Aims: The Ile138Met variant (rs738409) in the PNPLA3 gene has the largest effect on non-alcoholic fatty liver disease (NAFLD), increasing the risk of progression to severe forms of liver disease. It remains unknown if the variant plays a role in age of NAFLD onset. We aimed to determine if rs738409 impacts on the age of NAFLD diagnosis., Methods: We applied a novel natural language processing (NLP) algorithm to a longitudinal electronic health records (EHR) dataset of >27,000 individuals with genetic data from a multi-ethnic biobank, defining NAFLD cases (n = 1,703) and confirming controls (n = 8,119). We conducted i) a survival analysis to determine if age at diagnosis differed by rs738409 genotype, ii) a receiver operating characteristics analysis to assess the utility of the rs738409 genotype in discriminating NAFLD cases from controls, and iii) a phenome-wide association study (PheWAS) between rs738409 and 10,095 EHR-derived disease diagnoses., Results: The PNPLA3 G risk allele was associated with: i) earlier age of NAFLD diagnosis, with the strongest effect in Hispanics (hazard ratio 1.33; 95% CI 1.15-1.53; p <0.0001) among whom a NAFLD diagnosis was 15% more likely in risk allele carriers vs. non-carriers; ii) increased NAFLD risk (odds ratio 1.61; 95% CI 1.349-1.73; p <0.0001), with the strongest effect among Hispanics (odds ratio 1.43; 95% CI 1.28-1.59; p <0.0001); iii) additional liver diseases in a PheWAS (p <4.95 × 10 -6 ) where the risk variant also associated with earlier age of diagnosis., Conclusion: Given the role of the rs738409 in NAFLD diagnosis age, our results suggest that stratifying risk within populations known to have an enhanced risk of liver disease, such as Hispanic carriers of the rs738409 variant, would be effective in earlier identification of those who would benefit most from early NAFLD prevention and treatment strategies., Lay Summary: Despite clear associations between the PNPLA3 rs738409 variant and elevated risk of progression from non-alcoholic fatty liver disease (NAFLD) to more severe forms of liver disease, it remains unknown if PNPLA3 rs738409 plays a role in the age of NAFLD onset. Herein, we found that this risk variant is associated with an earlier age of NAFLD and other liver disease diagnoses; an observation most pronounced in Hispanic Americans. We conclude that PNPLA3 rs738409 could be used to better understand liver disease risk within vulnerable populations and identify patients that may benefit from early prevention strategies., Competing Interests: Conflict of interest The authors declare no conflicts of interest that pertain to this work. Please refer to the accompanying ICMJE disclosure forms for further details., (Copyright © 2020 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.)

Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry 1-3 . In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific 4-10 . Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations 11,12 . Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions 13 -the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.

The Clinical Genome Resource (ClinGen) Ancestry and Diversity Working Group highlights the need to develop guidance on race, ethnicity, and ancestry (REA) data collection and use in clinical genomics. We present quantitative and qualitative evidence to characterize: (1) acquisition of REA data via clinical laboratory requisition forms, and (2) information disparity across populations in the Genome Aggregation Database (gnomAD) at clinically relevant sites ascertained from annotations in ClinVar. Our requisition form analysis showed substantial heterogeneity in clinical laboratory ascertainment of REA, as well as marked incongruity among terms used to define REA categories. There was also striking disparity across REA populations in the amount of information available about clinically relevant variants in gnomAD. European ancestral populations constituted the majority of observations (55.8%), allele counts (59.7%), and private alleles (56.1%) in gnomAD at 550 loci with "pathogenic" and "likely pathogenic" expert-reviewed variants in ClinVar. Our findings highlight the importance of implementing and supporting programs to increase diversity in genome sequencing and clinical genomics, as well as measuring uncertainty around population-level datasets that are used in variant interpretation. Finally, we suggest the need for a standardized REA data collection framework to be developed through partnerships and collaborations and adopted across clinical genomics., (© 2018 Wiley Periodicals, Inc.)

Achieving confidence in the causality of a disease locus is a complex task that often requires supporting data from both statistical genetics and clinical genomics. Here we describe a combined approach to identify and characterize a genetic disorder that leverages distantly related patients in a health system and population-scale mapping. We utilize genomic data to uncover components of distant pedigrees, in the absence of recorded pedigree information, in the multi-ethnic Bio Me biobank in New York City. By linking to medical records, we discover a locus associated with both elevated genetic relatedness and extreme short stature. We link the gene, COL27A1 , with a little-known genetic disease, previously thought to be rare and recessive. We demonstrate that disease manifests in both heterozygotes and homozygotes, indicating a common collagen disorder impacting up to 2% of individuals of Puerto Rican ancestry, leading to a better understanding of the continuum of complex and Mendelian disease.

Genetic studies of complex traits have mainly identified associations with noncoding variants. To further determine the contribution of regulatory variation, we combined whole-genome and transcriptome data for 624 individuals from Sardinia to identify common and rare variants that influence gene expression and splicing. We identified 21,183 expression quantitative trait loci (eQTLs) and 6,768 splicing quantitative trait loci (sQTLs), including 619 new QTLs. We identified high-frequency QTLs and found evidence of selection near genes involved in malarial resistance and increased multiple sclerosis risk, reflecting the epidemiological history of Sardinia. Using family relationships, we identified 809 segregating expression outliers (median z score of 2.97), averaging 13.3 genes per individual. Outlier genes were enriched for proximal rare variants, providing a new approach to study large-effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.

In the structure of pelvic bone injuries, acetabular fractures are the most complex type and, according to different authors, account for up to 20% [1]. The severity of these injuries is confirmed by the fact that early descriptions of acetabular fracture were based only on the results of autopsies of patients who had suffered a combined injury. Thus, as early as 1788, Callisen reported an acetabular fracture, but without a detailed description of the nature of the injury. In 1909, Schroeder provided a detailed report of 49 cases of acetabular fractures reported in the literature. Most of them were described during autopsies of patients who died from complications associated with hemorrhagic shock or the onset of sepsis [2]. Fractures of the acetabulum in most observations are the result of high-energy impacts, usually as a result of traffic accidents; therefore, the mechanism of injury determines the combined and multiple nature of the injuries in the victims. A significant proportion of acetabular fractures (up to 60%) are accompanied by fragment displacement and dislocation of the femoral head, in which the most severe tissue changes occur [3].

Background Currently, one of the causes of high morbidity and mortality is injuries. Predict the outcome of injuries - it is an important task of the treating physician. Trauma is a stress factor so to predict the outcome, you can use markers of stress, the most accessible ofwhich is blood glucose., The Aim: to reveal the dynamics of the relationship between blood glucose levels and the outlook for the life ofpatients with thoracoabdominal injuries., Materials and Methods: A retrospective analysis of medical records of hospitalized patients were divided into two groups, depending on the outlook for the life of (favorable or unfavorable), and each of the groups - into two subgroups according to the presence or absence of signs of intoxication at admission. The subgroups were calculated and compared the mean blood glucose levels at different hours of hospital treatment., Results: It was found that the average blood glucose levels at various hours of hospital stay were significantly higher in patients with poor outcome. The most noticeable was the difference in the first days of hospital treatment. Signs of intoxication was associated with lower values of glucose and a tendency to hypoglycaemia. In addition, among patients with high blood glucose ( 8 mg / dL) was observed over deaths in the first day of hospital stay., Conclusion: High blood glucose levels ( 8,0 mmol / L) in the first day of hospital treatment is a predictor ofpoor outcome in patients with thoracoabdominal injuries.

In multicellular organisms, genetic programs guide cells to adopt cell fates as tissues are formed during development, maintained in adults, and repaired after injury. Here we explore how a small molecule in the environment can switch a genetic program from one fate to another. Wild-type Caenorhabditis elegans XX adult hermaphrodites make oocytes continuously, but certain mutant XX adults make sperm instead in an otherwise hermaphrodite soma. Thus, puf-8; lip-1 XX adults make only sperm, but they can be switched from sperm to oocyte production by treatment with a small-molecule MEK inhibitor. To ask whether this chemical reprogramming is common, we tested six XX sperm-only mutants, but found only one other capable of cell fate switching, fbf-1; lip-1. Therefore, reprogramming competence relies on genotype, with only certain mutants capable of responding to the MEK inhibitor with a cell fate change. To gain insight into the molecular basis of competence for chemical reprogramming, we compared polyadenylated transcriptomes of competent and noncompetent XX sperm-only mutants in the absence of the MEK inhibitor and hence in the absence of cell fate reprogramming. Despite their cellular production of sperm, competent mutants were enriched for oogenic messenger RNAs relative to mutants lacking competence for chemical reprogramming. In addition, competent mutants expressed the oocyte-specific protein RME-2, whereas those lacking competence did not. Therefore, mutants competent for reprogramming possess an intersexual molecular profile at both RNA and protein levels. We suggest that this intersexual molecular signature is diagnostic of an intermediate network state that poises the germline tissue for changing its cellular fate in response to environmental cues., (Copyright © 2014 by the Genetics Society of America.)

The nematode Caenorhabditis elegans is an important model for studies of germ cell biology, including the meiotic cell cycle, gamete specification as sperm or oocyte, and gamete development. Fundamental to those studies is a genome-level knowledge of the germline transcriptome. Here, we use RNA-Seq to identify genes expressed in isolated XX gonads, which are approximately 95% germline and 5% somatic gonadal tissue. We generate data from mutants making either sperm [fem-3(q96)] or oocytes [fog-2(q71)], both grown at 22°. Our dataset identifies a total of 10,754 mRNAs in the polyadenylated transcriptome of XX gonads, with 2748 enriched in spermatogenic gonads, 1732 enriched in oogenic gonads, and the remaining 6274 not enriched in either. These spermatogenic, oogenic, and gender-neutral gene datasets compare well with those of previous studies, but double the number of genes identified. A comparison of the additional genes found in our study with in situ hybridization patterns in the Kohara database suggests that most are expressed in the germline. We also query our RNA-Seq data for differential exon usage and find 351 mRNAs with sex-enriched isoforms. We suggest that this new dataset will prove useful for studies focusing on C. elegans germ cell biology., (Copyright © 2014 Ortiz et al.)

Among bacterial topoisomerase I enzymes, a conserved methionine residue is found at the active site next to the nucleophilic tyrosine. Substitution of this methionine residue with arginine in recombinant Yersinia pestis topoisomerase I (YTOP) was the only substitution at this position found to induce the SOS response in Escherichia coli. Overexpression of the M326R mutant YTOP resulted in approximately 4 log loss of viability. Biochemical analysis of purified Y. pestis and E. coli mutant topoisomerase I showed that the Met to Arg substitution affected the DNA religation step of the catalytic cycle. The introduction of an additional positive charge into the active site region of the mutant E. coli topoisomerase I activity shifted the pH for optimal activity and decreased the Mg(2+) binding affinity. This study demonstrated that a substitution outside the TOPRIM motif, which binds Mg(2+)directly, can nonetheless inhibit Mg(2+) binding and DNA religation by the enzyme, increasing the accumulation of covalent cleavage complex, with bactericidal consequence. Small molecules that can inhibit Mg(2+) dependent religation by bacterial topoisomerase I specifically could be developed into useful new antibacterial compounds. This approach would be similar to the inhibition of divalent ion dependent strand transfer by HIV integrase in antiviral therapy.

The TOPRIM DXDXXG residues of type IA and II topoisomerases are involved in Mg(II) binding and the cleavage-rejoining of DNA. Mutation of the strictly conserved glycine to serine in Yersinia pestis and Escherichia coli topoisomerase I results in bacterial cell killing due to inhibition of DNA religation after DNA cleavage. In this study, all other substitutions at the TOPRIM glycine of Y. pestis topoisomerase I were examined. While the Gly to Ala substitution allowed both DNA cleavage and religation, other mutations abolished DNA cleavage. DNA cleavage activity retained by the Gly to Ser mutant could be significantly enhanced by a second mutation of the methionine residue adjacent to the active site tyrosine. Induction of mutant topoisomerase with both the TOPRIM glycine and active site region methionine mutations resulted in up to 40-fold higher cell killing rate when compared with the single TOPRIM Gly to Ser mutant. Bacterial type IA topoisomerases are potential targets for discovery of novel antibiotics. These results suggest that compounds that interact simultaneously with the TOPRIM motif and the molecular surface around the active site tyrosine could be highly efficient topoisomerase poisons through both enhancement of DNA cleavage and inhibition of DNA rejoining.