Biology subjects

Mahajan, A.

Publications and source records attributed to Mahajan, A..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

Genetic regulation of the human plasma proteome in 54,306 UK Biobank participants

The UK Biobank Pharma Proteomics Project (UKB-PPP) is a collaboration between the UK Biobank (UKB) and thirteen biopharmaceutical companies characterising the plasma proteomic profiles of 54,306 UKB participants. Here, we describe results from the first phase of UKB-PPP, including protein quantitative trait loci (pQTL) mapping of 1,463 proteins that identifies 10,248 primary genetic associations, of which 85% are newly discovered. We also identify independent secondary associations in 92% of cis and 29% of trans loci, expanding the catalogue of genetic instruments for downstream analyses. The study provides an updated characterisation of the genetic architecture of the plasma proteome, leveraging population-scale proteomics to provide novel, extensive insights into trans pQTLs across multiple biological domains. We highlight genetic influences on ligand-receptor interactions and pathway perturbations across a diverse collection of cytokines and complement proteins, and illustrate long-range epistatic effects of ABO blood group and FUT2 secretor status on proteins with gastrointestinal tissue-enriched expression. We demonstrate the utility of these data for drug target discovery by extending the genetic proxied effect of PCSK9 levels on lipid concentrations, cardio- and cerebro-vascular diseases, and additionally disentangle specific genes and proteins perturbed at COVID-19 susceptibility loci. This public-private partnership provides the scientific community with an open-access proteomics resource of unprecedented breadth and depth to help elucidate biological mechanisms underlying genetic discoveries and accelerate the development of novel biomarkers and therapeutics.

genetics↗

bioRxiv2022

Loss of RREB1 in pancreatic beta cells reduces cellular insulin content and affects endocrine cell gene expression

Aims/hypothesisGenome-wide studies have uncovered multiple independent signals at the RREB1 locus associated with altered type 2 diabetes risk and related glycemic traits. However, little is known about the function of the zinc finger transcription factor RREB1 in glucose homeostasis or how changes in its expression and/or function influence diabetes risk. MethodsA zebrafish model lacking rreb1a and rreb1b was used to study the effect of RREB1 loss in vivo. Using transcriptomic and cellular phenotyping of a human beta cell model (EndoC-{beta}H1) and human induced pluripotent stem cell (hiPSC)-derived beta-like cells, we investigated how loss of RREB1 expression and activity affects pancreatic endocrine cell development and function. Ex vivo measurements of human islet function were performed in donor islets from carriers of RREB1 T2D-risk alleles. ResultsCRISPR-Cas9-mediated loss of rreb1a and rreb1b function in zebrafish supports an in vivo role for the transcription factor in beta cell mass, beta cell insulin expression, and glucose levels. Loss of RREB1 reduced insulin gene expression and cellular insulin content in EndoC-{beta}H1 cells, and impaired insulin secretion under prolonged stimulation. Transcriptomic analysis of RREB1 knockdown and knockout EndoC-{beta}H1 cells supports RREB1 as a novel regulator of genes involved in insulin secretion. In vitro differentiation of RREB1KO/KO hiPSCs revealed a dysregulation of pro-endocrine cell genes, including RFX family members, suggesting that RREB1 also regulates genes involved in endocrine cell development. Human donor islets from carriers of T2D-risk alleles in RREB1 have altered glucose-stimulated insulin secretion ex vivo, consistent with RREB1 regulating islet cell function. Conclusions/interpretationTogether, our results indicate that RREB1 regulates beta cell function by transcriptionally regulating the expression of genes involved in beta cell development and function. Research in contextO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LIHuman genetic variation in RREB1 is associated with altered diabetes risk, variation in glycemic, and anthropometric traits C_LIO_LIRREB1 is a transcription factor that binds to Ras-responsive elements and is expressed in multiple diabetes relevant tissues, including pancreatic islets C_LI What is the key question?O_LIHow does altered expression or function of RREB1 influence diabetes risk? C_LI What are the new findings?O_LIKnockdown and knockout of RREB1 in mature human EndoC-{beta}H1 cells reduces expression of insulin transcript and cellular content, as well as insulin secretion under prolonged stress C_LIO_LICarriers of the T2D-risk RREB1 coding allele trend towards reduced insulin content, but have improved glucose-stimulated insulin secretion C_LIO_LIA loss-of-function zebrafish model suggests that RREB1 is required for insulin expression C_LI How might this impact on clinical practice in the foreseeable future?O_LIRREB1 controls beta cell function and whole-body glucose homeostasis by transcriptionally regulating the development and function of pancreatic beta cells C_LI

physiology↗

bioRxiv2022

A chemomechanical model of sperm locomotion reveals two modes of swimming

The propulsion of mammalian spermatozoa during reproduction relies on the spontaneous periodic oscillation of their flagella. These oscillations are driven internally by the coordinated action of ATP-powered dynein motors that exert active sliding forces between microtubule doublets, resulting in bending waves that propagate along the flagellum and enable locomotion of the cell through the viscous medium. In this work, we present a chemomechanical model of a freely swimming spermatozoon that uses a sliding-control model of the flagellar axoneme capturing the coupling of motor kinetics with elastic deformations and accounts for the effect of non-local hydrodynamic interactions between the sperm head and flagellum. Nonlinear simulations of the model equations are shown to produce realistic beating patterns and swimming trajectories, which we analyze as a function of sperm number and motor activity. Our results demonstrate that the swimming velocity does not vary monotonically with dynein activity, but instead displays two local maxima corresponding to distinct modes of swimming, each characterized by qualitatively different waveforms and trajectories.

biophysics↗

bioRxiv2022

Euchromatin activity enhances segregation and compaction of heterochromatin in the cell nucleus

The large-scale organization of the genome inside the cell nucleus is critical for the cells function. Chromatin - the functional form of DNA in cells - serves as a substrate for active nuclear processes such as transcription, replication and DNA repair. Chromatins spatial organization directly affects its accessibility by ATP-powered enzymes, e.g., RNA polymerase II in the case of transcription. In differentiated cells, chromatin is spatially segregated into compartments - euchromatin and heterochromatin - the former being largely transcriptionally active and loosely packed, the latter containing mostly silent genes and densely compacted. The euchromatin/heterochromatin segregation is crucial for proper genomic function, yet the physical principles behind it are far from understood. Here, we model the nucleus as filled with hydrodynamically interacting active Zimm chains - chromosomes - and investigate how large heterochromatic regions form and segregate from euchromatin through their complex interactions. Each chromosome presents a block copolymer composed of heterochromatic blocks, capable of crosslinking that increases chromatins local compaction, and euchromatic blocks, subjected to stochastic force dipoles that capture the microscopic stresses exerted by nuclear ATPases. These active stresses lead to a dynamic self-organization of the genome, with its coherent motions driving the mixing of chromosome territories as well as large-scale heterochromatic segregation through crosslinking of distant genomic regions. We study the stresses and flows that arise in the nucleus during the heterochromatic segregation, and identify their signatures in Hi-C proximity maps. Our results reveal the fundamental role of active mechanical processes and hydrodynamic interactions in the kinetics of chromatin compartmentalization and in the emergent large-scale organization of the nucleus.

biophysics↗

bioRxiv2021

Re-convolving the compositional landscape of primary and recurrent glioblastoma using single nucleus RNA sequencing

Glioblastoma (GBM) is an aggressive diffusely infiltrating neoplasm that spreads beyond surgical resection margins, where it intermingles with non-neoplastic brain cells. This complex microenvironment harboring infiltrating glioma and non-neoplastic brain cells is the origin of tumor recurrence. Thus, understanding the cellular and molecular features of the glioma microenvironment is therapeutically and prognostically important. We used single-nucleus RNA sequencing (snRNAseq) to determine the cellular composition and transcriptional states in primary and recurrent glioma and identified three compositional tissue-states defined by the observed patterns of cohabitation between neoplastic and non-neoplastic brain cells. These comprise states enriched in A) neurons and non-neoplastic glia, B) reactive astrocytes and inflammatory cells, and C) proliferating tumor cells. The tissue states also showed distinct associations with the different transcriptional states of GBM cells. Spatial transcriptomics revealed that the cell-types/transcriptional-states associated with each tissue state colocalize in space. Tissue states are clinically significant because they correlate with radiographic, histopathologic, and prognostic features. Importantly, we found that our compositionally-defined tissue states are enriched in distinct metabolic pathways. One such pathway is fatty acid biosynthesis, which was enriched in tissue state B - a state enriched in recurrent glioblastoma and associated with shorter overall survival- and composed of astrocyte-like/mesenchymal glioma cells, reactive astrocytes, and monocyte-like myeloid cells. We showed that treating acute slices of GBM with a fatty acid synthesis inhibitor is sufficient to deplete the transcriptional signature of tissue state B. Our findings define a novel compositional approach to analyze glioma-infiltrated tissue which allows us to discover prognostic and targetable features, paving the way to new mechanistic and therapeutic discoveries.

pathology↗

bioRxiv2020

A multi-omic integrative scheme characterizes tissues of action at loci associated with type 2 diabetes

Resolving the molecular processes that mediate genetic risk remains a challenge as most disease-associated variants are non-coding and functional and bioinformatic characterization of these signals requires knowledge of the specific tissues and cell-types in which they operate. To address this challenge, we developed a framework for integrating tissue-specific gene expression and epigenomic maps (primarily from tissues involved in insulin secretion and action) to obtain tissue-of-action (TOA) scores for each association signal by systematically partitioning posterior probabilities from Bayesian fine-mapping. We applied this scheme to credible set variants for 380 association signals from a recent GWAS meta-analysis of type 2 diabetes (T2D) in Europeans. The resulting tissue profiles underscored a predominant role for pancreatic islets and, to a lesser extent, subcutaneous adipose and liver, that was largely attributable to enhancer elements and transcribed regions, particularly among signals with greater fine-mapping resolution. We incorporated resulting TOA scores into a rule-based classifier, and validated the tissue assignments through comparison with data from cis-eQTL enrichment, functional fine-mapping, RNA co-expression, and patterns of physiological association. In addition to implicating signals with a single tissue-of-action, we also found evidence for signals with shared effects in multiple tissues as well as distinct tissue profiles between independent signals within heterogeneous loci. Lastly, we demonstrated that TOA scores can be directly coupled with eQTL colocalization to further resolve effector transcripts at T2D signals. This framework guides mechanistic inference by directing functional validation studies to the most relevant tissues and can gain power as fine-mapping resolution and cell-specific annotations become richer. This method is generalizable to all complex traits with relevant annotation data and is made available as an R package.

genetics↗

bioRxiv2020

Divergent genetic effects for type 1 and type 2 diabetes at overlapping association signals

Aims/hypothesisGiven the potential shared aetiology between type 1 and type 2 diabetes, we aimed to identify any genetic regions associated with both diseases. For associations where there is a shared signal and the allele that increases risk to one disease also increases risk to the other, inference about shared aetiology could be made, with the potential to develop therapeutic strategies to treat or prevent both diseases simultaneously. Alternatively, if a genetic signal colocalises with divergent effect directions, it could provide valuable biological insight into how the association affects the two diseases differently. MethodsUsing publicly available type 2 diabetes summary statistics from a genomewide association study (GWAS) meta-analysis of European ancestry individuals (74,124 cases and 824,006 controls) and type 1 diabetes GWAS summary statistics from a meta-analysis of studies on individuals from the UK and Sardinia (7,467 cases and 10,218 controls), we identified all regions of 0.5 Mb that contained variants associated with both diseases (false discovery rate<0.01). In each region, we performed forward stepwise logistic regression to identify independent association signals, then examined colocalisation of each type 1 diabetes signal with each type 2 diabetes signal using coloc. Any association with a colocalisation posterior probability of [≥]0.9 was considered a genuine shared association with both diseases. ResultsOf the 81 association signals from 42 genetic regions that showed association with both type 1 and type 2 diabetes, four association signals colocalised between both diseases (posterior probability [≥]0.9): (i) chromosome 16q23.1, near Chymotripsinogen B1 (CTRB1) / Breast Cancer Anti-Estrogen Resistance Protein 1 (BCAR1), which has been previously identified; (ii) chromosome 11p15.5, near the Insulin (INS) gene; (iii) chromosome 4p16.3, near Transmembrane protein 129 (TMEM129), and (iv) chromosome 1p31.3, near Phosphoglucomutase 1 (PGM1). In each of these regions, the effect of genetic variants on type 1 diabetes was in the opposite direction to the effect on type 2 diabetes. Use of additional datasets also supported the previously identified colocalisation on chromosome 9p24.2, near the GLIS Family Zinc Finger Protein 3 (GLIS3) gene, in this case with a concordant direction of effect. Conclusions/interpretationThat four of five association signals that colocalise between type 1 diabetes and type 2 diabetes are in opposite directions suggests a complex genetic relationship between the two diseases. Research in ContextWhat is already known about this subject? O_LIOther than insulin, there are currently no treatments for both type 1 and type 2 diabetes. C_LIO_LIFindings that genetic variants near the GLIS3 gene increase risk of both type 1 and type 2 diabetes have indicated shared genetic mechanisms at the level of the pancreatic {beta} cell. C_LI What is the key question? O_LIBy examining chromosome regions associated with both diseases, are there any more variants that affect risk of both diseases and could support common mechanisms and repositioning of therapeutics between the diseases? C_LI What are the new findings? O_LIAt current sample sizes, there is evidence that five genetic variants in different chromosome regions impact risk of developing both diseases. C_LIO_LIHowever, four of these variants have the opposite direction of effect in type 1 diabetes compared to type 2 diabetes, with only one, near GLIS3, having a concordant direction of effect. C_LI How might this impact on clinical practise in the foreseeable future? O_LIGenetic findings have furthered research in type 1 and type 2 diabetes independently, and suggest therapeutic strategies. However, our current investigation into their shared genetics suggests that repositioning of current type 2 diabetes treatments into type 1 diabetes may not be straightforward. C_LI

genetics↗

bioRxiv2020

Bacterial flagella disrupt host cell membranes and interact with cytoskeletal components

Bacterial flagella have many established roles beyond swimming motility. Despite clear evidence of flagella-dependent adherence, the specificity of ligands and mechanisms of binding are still debated. In this study, the molecular basis of E. coli O157:H7 and S. Typhimurium flagella binding to epithelial cell cultures was investigated. Flagella interactions with host cell surfaces were intimate and crossed cellular boundaries as demarcated by actin and membrane labelling. SEM revealed flagella disappearing into cellular surfaces and TEM of S. Typhiumurium indicated host membrane deformation and disruption in proximity to flagella. Motor mutants of E. coli O157:H7 and S. Typhimurium caused reduced haemolysis compared to wild-type, indicating that membrane disruption was in part due to flagella rotation. Flagella from E. coli O157 (H7), EPEC O127 (H6), and S. Typhimurium (P1 & P2 flagella) were shown to bind to purified intracellular components of the actin cytoskeleton and directly increase in vitro actin polymerisation rates.

microbiology↗

bioRxiv2019

Deep learning models predict regulatory variants in pancreatic islets and refine type 2 diabetes association signals

Genome-wide association analyses have uncovered multiple genomic regions associated with T2D, but identification of the causal variants at these remains a challenge. There is growing interest in the potential of deep learning models - which predict epigenome features from DNA sequence - to support inference concerning the regulatory effects of disease-associated variants. Here, we evaluate the advantages of training convolutional neural network (CNN) models on a broad set of epigenomic features collected in a single disease-relevant tissue - pancreatic islets in the case of type 2 diabetes (T2D) - as opposed to models trained on multiple human tissues. We report convergence of CNN-based metrics of regulatory function with conventional approaches to variant prioritization - genetic fine-mapping and regulatory annotation enrichment. We demonstrate that CNN-based analyses can refine association signals at T2D-associated loci and provide experimental validation for one such signal. We anticipate that these approaches will become routine in downstream analyses of GWAS.

bioinformatics↗

bioRxiv2019

The orphan nuclear receptor estrogen-related receptor beta (ERRβ) in triple-negative breast cancer

PurposeTriple negative breast cancer (TNBC)/ basal-like breast cancer (BLBC) is a highly aggressive form of breast cancer prevalent in African-American (AA) women. We previously reported that a small molecule agonist ligand for the orphan nuclear receptor estrogen-related receptor beta (ERR{beta} or ESRRB) has growth inhibitory and anti-mitotic activity in TNBC cell lines. In this study, we evaluate the association of ESRRB mRNA, copy number levels, and protein expression with demographic, clinicopathological, and gene expression features in breast tumor clinical specimens.\n\nMethodsESRRB mRNA level expression and clinical associations were analyzed using RNAseq data. Array-based comparative genomic hybridization determined ESRRB copy number in AA and Caucasian women. Transcription factor activity was measured using promoter-reporter luciferase assays in TNBC cell lines. Semi-automatic quantification of immunohistochemistry measured ERR{beta} protein expression on a 150-patient tissue microarray series.\n\nResultsESRRB mRNA expression is significantly lower in TNBC/BLBC vs. other breast cancer subtypes. There is no evidence of ESRRB copy number loss. ESRRB mRNA expression is correlated with the expression of genes associated with neuroactive ligand-receptor interaction, metabolic pathways, and deafness. These genes contain G/C-rich transcription factor binding motifs. The ESRRB message is alternatively spliced into three isoforms, which we show have different transcription factor activity in basal-like vs. other TNBC cell lines. We further show that the ERR{beta}2 and ERR{beta}sf isoforms are broadly expressed in breast tumors at the protein level.\n\nConclusionsDecreased ESRRB mRNA expression, and distinct patterns of ERR{beta} isoform subcellular localization and transcription factor activity are key features in TNBC/BLBC.

cancer biology↗

bioRxiv2019

Multi-ancestry GWAS of the electrocardiographic PR interval identifies 210 loci underlying cardiac conduction

The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality1,2. We performed multi-ancestry (N=293,051) and European only (N=271,570) genome-wide association (GWAS) meta-analyses for the PR interval, discovering 210 loci of which 149 are novel. Variants at all loci nearly doubled the percentage of heritability explained, from 33.5% to 62.6%. We observed enrichment for genes involved in cardiac muscle development/contraction and the cytoskeleton highlighting key regulation processes for atrioventricular conduction. Additionally, 19 novel loci harbour genes underlying inherited monogenic heart diseases suggesting the role of these genes in cardiovascular pathology in the general population. We showed that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease risk, including distal conduction disease, AF, atrioventricular pre-excitation, non-ischemic cardiomyopathy, and coronary heart disease. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.

genetics↗

bioRxiv2019

CD8+ T-cell-mediated immunoediting influences genomic evolution and immune evasion in murine gliomas

Cancer immunoediting shapes tumor progression by the selection of tumor cell variants that can evade immune recognition. Given the immune evasion and intra-tumor heterogeneity intrinsic to gliomas, we hypothesized that CD8+ T-cells mediate immunoediting in these tumors. We evaluated glioma progression in the absence of CD8+ T-cells by depleting this immune cell population in transgenic murine gliomas. Upon transplantation, gliomas that developed in the absence of CD8+ T-cells engrafted poorly in recipients with intact immunity but engrafted well in those with CD8+ T-cell depletion. Gliomas developed in absence of CD8+ T-cells exhibited increased chromosomal instability, MAPK signaling, gene fusions, and macrophage/microglial infiltration. MAPK activation correlated with macrophage/microglial recruitment in this model and in the human disease. Our results indicate that CD8+ T-cells mediate immunoediting during gliomagenesis, influencing the genomic stability of glioma and its microenvironment, leading to immune evasion.\n\nSignificanceImmune evasion renders cancer resistant to anti-tumoral immunity. Therapeutic intervention often fails for gliomas because of the plasticity of tumor cell variants that resist immune surveillance. Our results demonstrate a mechanism of immune evasion in gliomas that derives from CD8+ T-cells during the development and progression of this disease.

cancer biology↗

bioRxiv2019

Identification of type 2 diabetes loci in 433,540 East Asian individuals

Meta-analyses of genome-wide association studies (GWAS) have identified >240 loci associated with type 2 diabetes (T2D), however most loci have been identified in analyses of European-ancestry individuals. To examine T2D risk in East Asian individuals, we meta-analyzed GWAS data in 77,418 cases and 356,122 controls. In the main analysis, we identified 298 distinct association signals at 178 loci, and across T2D association models with and without consideration of body mass index and sex, we identified 56 loci newly implicated in T2D predisposition. Common variants associated with T2D in both East Asian and European populations exhibited strongly correlated effect sizes. New associations include signals in/near GDAP1, PTF1A, SIX3, ALDH2, a microRNA cluster, and genes that affect muscle and adipose differentiation. At another locus, eQTLs at two overlapping T2D signals act through two genes, NKX6-3 and ANK1, in different tissues. Association studies in diverse populations identify additional loci and elucidate disease genes, biology, and pathways.\n\nType 2 diabetes (T2D) is a common metabolic disease primarily caused by insufficient insulin production and/or secretion by the pancreatic {beta} cells and insulin resistance in peripheral tissues1. Most genetic loci associated with T2D have been identified in populations of European (EUR) ancestry, including a recent meta-analysis of genome-wide association studies (GWAS) of nearly 900,000 individuals of European ancestry that identified >240 loci influencing the risk of T2D2. Differences in allele frequency between ancestries affect the power to detect associations within a population, particularly among variants rare or monomorphic in one population but more frequent in another3,4. Although smaller than studies in European populations, a recent T2D meta-analysis in almost 200,000 Japanese individuals identified 28 additional loci4. The relative contributions of different pathways to the pathophysiology of T2D may also differ between ancestry groups. For example, in East Asian (EAS) populations, T2D prevalence is greater than in European populations among people of similar body mass index (BMI) or waist circumference5. We performed the largest meta-analysis of East Asian individuals to identify new genetic associations and provide insight into T2D pathogenesis.

genetics↗

bioRxiv2019

Multifaceted genome-wide study identifies novel regulatory loci for body mass index in Indians

Obesity, a risk factor for various human diseases originates through complex interactions between genes and prevailing environment that varies across populations. Indians exhibit a unique obesity phenotype likely attributed by specific gene pool and environmental factors. Here, we present genome-wide association study (GWAS) of 7,259 Indians to understand the genetic architecture of body mass index (BMI) in the population. Our study revealed novel association of variants in BAI3 (rs6913677) and SLC22A11 (rs2078267) at GWAS significance, and of ZNF45 (rs8100011) with near GWAS significance. As genetic loci may dictate the phenotype through modulation of epigenetic processes, we overlapped discovered genetic signatures with DNA methylation patterns of 236 Indian individuals, and analyzed expression of the candidate genes using publicly available data. The variants in BAI3 and SLC22A11 were found to dictate methylation patterns at unique CpGs harboring critical cis- regulatory elements. Further, BAI3, SLC22A11 and ZNF45 variants were found to overlie repressive chromatin, active enhancer, and active chromatin regions, in that order, in human subcutaneous adipose tissue in ENCODE database. Besides, the identified genomic regions represented potential binding sites for key transcription factors implicated in obesity and/or metabolic disorders. Interestingly, rs8100011 (ZNF45) acted as a robust cis-expression quantitative trait locus (cis-eQTL) in subcutaneous adipose tissue in GTEx portal, and ZNF45 gene expression showed an inverse correlation with BMI in skeletal muscle of Indian subjects. Further, gene-based GWAS analysis revealed CPS1 and UPP2 as additional leads regulating BMI in Indians. Our study decodes potential genomic mechanisms underlying obesity phenotype in Indians.

genomics↗

bioRxiv2019

Interaction between DNA damage response, translation and apoptosome determines cancer susceptibility to TOP2 poisons

Topoisomerase II poisons are one of the most common class of chemotherapeutics used in cancer. We show that glioblastoma (GBM), the most malignant of all primary brain tumors in adults is responsive to TOP2 poisons. To identify genes that confer susceptibility to this drug in gliomas, we performed a genome-scale CRISPR knockout screen with etoposide. Genes involved in protein synthesis and DNA damage were implicated in etoposide susceptibility. To define potential biomarkers for TOP2 poisons, CRISPR hits were overlapped with genes whose expression correlates with susceptibility to this drug across glioma cell lines, revealing ribosomal protein subunit RPS11, 16, 18 as putative biomarkers for response to TOP2 poisons. Loss of RPS11 impaired the induction of pro-apoptotic gene APAF1 following etoposide treatment, and led to resistance to this drug and doxorubicin. The expression of these ribosomal subunits was also associated with susceptibility to TOP2 poisons across cell lines from multiple cancers.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC=\"FIGDIR/small/614024v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (14K):\norg.highwire.dtl.DTLVardef@310f7org.highwire.dtl.DTLVardef@14ed578org.highwire.dtl.DTLVardef@a0d9c0org.highwire.dtl.DTLVardef@37f59a_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2019

Elevated risk of invasive group A streptococcal disease and host genetic variation in the human leukocyte antigen locus

Invasive group A streptococcal (GAS) disease is uncommon but carries a high case-fatality rate relative to other infectious diseases. Given the ubiquity of mild GAS infections, it remains unclear why healthy individuals will occasionally develop life-threatening infections, raising the possibility of host genetic predisposition. Here, we present the results of a case-control study including 43 invasive GAS cases and 1,540 controls. Using HLA imputation and linear mixed-models, we find each copy of the HLA-DQA1*01:03 allele associates with a two-fold increased risk of disease (odds ratio 2.3, 95% confidence interval 1.3-4.4, P=0.009), an association which persists with classical HLA typing of a subset of cases and analysis with an alternative large control dataset with validated HLA data. Moreover, we propose the association is driven by the allele itself rather than the background haplotype. Overall this finding provides impetus for further investigation of the immunogenetic basis of this devastating bacterial disease.

genetics↗

bioRxiv2019

Causal relevance of obesity on the leading causes of death in women and men: A Mendelian randomization study

BackgroundObesity traits are causally implicated with risk of cardiometabolic diseases. It remains unclear whether there are similar causal effects of obesity traits on other non-communicable diseases. Also, it is largely unexplored whether there are any sex-specific differences in the causal effects of obesity traits on cardiometabolic diseases and other leading causes of death. We therefore tested associations of sex-specific genetic risk scores (GRSs) for body mass index (BMI), waist-hip-ratio (WHR), and WHR adjusted for BMI (WHRadjBMI) with leading causes of mortality, using a Mendelian randomization (MR) framework. Methods and FindingsWe constructed sex-specific GRSs for BMI, WHR, and WHRadjBMI, including 565, 324, and 338 genetic variants, respectively. These GRSs were then used as instrumental variables to assess associations between the obesity traits and leading causes of mortality using an MR design in up to 422,414 participants from the UK Biobank. We also investigated associations with potential mediators and risk factors, including smoking, glycemic and blood pressure traits. Sex-differences were subsequently assessed by Cochrans Q-test (Phet). Up to 227,717 women and 194,697 men with mean (standard deviation) age 56.6 (7.9) and 57.0 (8.1) years, body mass index 27.0 (5.1) and 27.9 (4.2) kg/m2 and waist-hip-ratio 0.82 (0.07) and 0.94 (0.07), respectively, were included. Mendelian randomization analysis showed that obesity causes coronary artery disease, stroke (particularly ischemic), chronic obstructive pulmonary disease, lung cancer, type 2 and 1 diabetes mellitus, non-alcoholic fatty liver disease, chronic liver disease, and acute and chronic renal failure. A 1 standard deviation higher body mass index led to higher risk of type 2 diabetes in women (OR 3.81; 95% CI 3.42-4.25, P=8.9x10-130) than in men (OR 2.78; 95% CI 2.57-3.02, P=1.0x10-133, Phet=5.1x10-6). Waist-hip-ratio led to a higher risk of chronic obstructive pulmonary disease (Phet=5.5x10-6) and higher risk of chronic renal failure (Phet=1.3x10-4) in men than women. A limitation of MR studies is potential bias if the genetic variants are directly associated with confounders (pleiotropy), but sensitivity analyses such as MR-Egger supported the main findings. Our study was also limited to people of European descent and results may differ in people of other ancestries. ConclusionsObesity traits have an etiological role in the majority of the leading global causes of death. Sex differences exist in the effects of obesity traits on risk of type 2 diabetes, chronic obstructive pulmonary disease, and renal failure, which may have implications on public health.

epidemiology↗

bioRxiv2018

Dextranol: A better lyoprotectant

Dextranol, a reduced dextran, prevents damage to stored dry protein samples that unmodified dextran would otherwise cause. Lyoprotectants like the polysaccharide dextran are critical for preserving dried protein samples by forming rigid a glass that protects entrapped protein molecules. Stably dried proteins are important for maintaining critical information in clinical samples like blood serum. However, we found that dextran reacts with serum proteins during storage, producing high-molecular weight Amadori-product conjugates. These conjugates appeared in a matter of days or weeks when stored at elevated temperatures (37{degrees} or 45{degrees}C), but also appeared on a timescale of months when stored at room temperature. We synthesized a less reactive dextranol by reducing dextrans anomeric carbon from an aldehyde to an alcohol. Serum samples dried in a dextranol- based matrix protected the serum proteins from forming high-molecular weight conjugates. The levels of four cancer-related serum biomarkers (prostate specific antigen, neuropilin-1, osteopontin, and metalloproteinase 7) decreased, as measured by immunoassay, when serum samples were stored for one to two weeks in dextran- based matrix. Switching to a dextran-based lyoprotection matrix slightly reduced the damage to osteopontin and completely stopped any detectable damage during storage in the other three biomarkers when for a period of two weeks at 45{degrees}C. Dextranol offers a small and easy modification to dextran that significantly improves the molecules function as a lyoprotectant by eliminating the potential for damaging protein-polysacharide conjugation.

biochemistry↗