Top 10 Biorxiv Papers Today
Dense genotype data and thousands of phenotypes from large biobanks, coupled with increasingly accessible summary association statistics from genome-wide association studies (GWAS), provide great opportunities to dissect the complex relationships among human traits and diseases. We introduce BADGERS, a powerful method to perform polygenic score-based biobank-wide scans for disease-trait associations. Compared to traditional regression approaches, BADGERS uses GWAS summary statistics as input and does not require multiple traits to be measured on the same cohort. We applied BADGERS to two independent datasets for Alzheimer's disease (AD; N=61,212). Among the polygenic risk scores (PRS) for 1,738 traits in the UK Biobank, we identified 48 significant trait PRSs associated with AD after adjusting for multiple testing. Family history, high cholesterol, and numerous traits related to intelligence and education showed strong and independent associations with AD. Further, we identified 41 significant PRSs associated with AD...
Biobank-wide association scan identifies risk factors for late-onset #Alzheimer's disease and endophenotypes https://t.co/KFfTEgdj6K @uk_biobank #PM101 #PRS
Family history and high cholesterol are the downers, but may be bufffered by high educational achievement and cognition.
Biobank-wide association scan identifies risk factors for late-onset Alzheimer's disease and endophenotypes https://t.co/3swrBcQSa7 #bioRxiv
Biobank-wide association scan identifies risk factors for late-onset Alzheimer's disease and endophenotypes https://t.co/3lvweHXb9V https://t.co/iD8vY26Vsd
"We introduce BADGERS, a powerful method to perform polygenic score-based biobank-wide scans for disease-trait associations."
Biobank-wide association scan identifies risk factors for late-onset Alzheimer's disease and endophenotypes https://t.co/DU2KVeEpUP
Biobank-wide association scan identifies risk factors for late-onset Alzheimer's disease and endophenotypes https://t.co/SJ8G3wX16X #biorxiv_genetic
Adjusting my afternoon plans to include more cheese intake https://t.co/8a29Wwbicr
New preprint from us! We introduce BADGERS (guess I'm a true Wisconsinian now), a method for PRS-based biobank-wide association scans using GWAS sumstats. One of our leading authors Donghui Yan is an undergrad(!). Don't miss his grad school application! https://t.co/9bQ4LBHpYu
@BlairBraverman the dogs are onto something. See figure 2. Cheese intake negatively correlated with Alzheimer’s risk. Why they are so smart 😀🐶 https://t.co/EgjAVE2BH5
Biobank-wide association scan identifies risk factors for late-onset Alzheimer's disease and endophenotypes https://t.co/scIw73GqI2
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Till F. M. Andlauer,
Maria Jose Gonzalez,
Susana Gil Flores,
Francisco J. Cabaleiro Fabeiro,
Francisco del Rio Noriega,
Fermin Perez Perez,
Jesus Haro Gonzalez,
Guillermo Orozco Diaz,
Jerome Clifford Foo,
Stephanie H. Witt,
Bipolar Disorder Working Group of the Psychiatric Genomics Consortium,
Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium,
Andreas J Forstner,
Multiplex families with a high prevalence of a psychiatric disorder are often examined to identify rare genetic variants with large effect sizes. In the present study, we analysed whether the risk for bipolar disorder (BD) in BD multiplex families is influenced by common genetic variants. Furthermore, we investigated whether this risk is conferred mainly by BD-specific risk variants or by variants also associated with the susceptibility to schizophrenia or major depression. In total, 395 individuals from 33 Andalusian BD multiplex families as well as 438 subjects from an independent, sporadic BD case-control cohort were analysed. Polygenic risk scores (PRS) for BD, schizophrenia, and major depression were calculated and compared between the cohorts. Both the familial BD cases and unaffected family members had significantly higher PRS for all three psychiatric disorders than the independent controls, suggesting a high baseline risk for several psychiatric disorders in the families. Moreover, familial BD cases showed significantly...
Bipolar multiplex families have an increased burden of common risk variants for psychiatric disorders https://t.co/ZzdBp7RUM7 #bioRxiv
Bipolar multiplex families have an increased burden of common risk variants for psychiatric disorders https://t.co/HRsbqXbJPn https://t.co/DWVLnh9NYP
Welcome to @f_streit as an newly active tweeter. Fabian is a key researcher in the @PGCgenetics MDD group and highly productive in the BOMA studies. Read his latest pre-print here https://t.co/GbHbuxCGma
Bipolar multiplex families have an increased burden of common risk variants for psychiatric disorders https://t.co/HSd0OfOawj #biorxiv_genetic
Bipolar multiplex families have an increased burden of common risk variants for psychiatric disorders #BD #bipolar https://t.co/L2WyblRR2c
New preprint out, showing polygenic risk for psychiatric disorders is increased in bipolar multiplex families #pgcgenetics https://t.co/dCWo8acmIm
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Testing for Hardy-Weinberg Equilibrium (HWE) is a common practice for quality control in genetic studies. Variable sites violating HWE may be identified as technical errors in the sequencing or genotyping process, or they may be of special evolutionary interest. Large-scale genetic studies based on next-generation sequencing (NGS) methods have become more prevalent as cost is decreasing but these methods are still associated with statistical uncertainty. The large-scale studies usually consist of samples from diverse ancestries that make the existence of some degree of population structure almost inevitable. Precautions are therefore needed when analyzing these datasets, as population structure causes deviations from HWE. Here we propose a method that takes population structure into account in the testing for HWE, such that other factors causing deviations from HWE can be detected. We show the effectiveness of our method in NGS data, as well as in genotype data, for both simulated and real datasets, where the use of genotype...
Testing for Hardy-Weinberg Equilibrium in Structured Populations using NGS Data https://t.co/aXFl1o382z #genetics
"Testing for Hardy-Weinberg Equilibrium in Structured Populations using NGS Data [NEW RESULTS]" https://t.co/HXXQ53v5pp
Testing for Hardy-Weinberg Equilibrium in Structured Populations using NGS Data: https://t.co/fxjINzkONH
RT @razibkhan: Testing for Hardy-Weinberg Equilibrium in Structured Populations using NGS Data https://t.co/aXFl1o382z #genetics
RT @razibkhan: Testing for Hardy-Weinberg Equilibrium in Structured Populations using NGS Data https://t.co/aXFl1o382z #genetics
Framework for analyzing low depth NGS data in heterogeneous populations using PCA.
Open Issues: 2
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Fabiola Del Greco M,
Jana van Vliet Ostaptchouk,
We investigated by Mendelian Randomisation (MR) analyses the causal effect of adult height on coronary artery disease (CAD) (23,755 cases, 425,339 controls) and type 2 diabetes (T2D) (29,427 cases, 416,908 controls) in UK Biobank. We then examined whether such effects are mediated via known cardiometabolic risk factors including body mass index (BMI), glycaemic traits, lipid levels and blood pressure. We further cross-checked our findings by two-sample MR and Multivariate MR analyses with publicly available summary statistics data. One standard deviation (SD) higher genetically determined height (~6.5 cm) was causally associated with a 14% decrease in CAD risk (OR= 0.86, 95% CI= 0.79-0.94). This causal association remained significant after performing sensitivity analyses relaxing pleiotropy assumptions. The causal effect of height on CAD risk appeared to be independent of risk factors such as lipid levels, blood pressure and BMI; association was reduced by only 1-3% after adjustment for potential mediators. We observed no direct...
The role of glycaemic, lipid, blood pressure and obesity risk factors as mediators of the effect of height on Coronary Artery Disease and Type 2 Diabetes Mellitus: A Mendelian Randomisation Study. https://t.co/WgFkdGaa4S #bioRxiv
The role of glycaemic, lipid, blood pressure and obesity risk factors as mediators of the effect of height on Coronary Artery ... https://t.co/jy6iHlGHth #biorxiv_genetic
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Genetic studies of metabolites have identified thousands of variants many of which are associated with downstream metabolic and obesogenic disorders. However, these studies have relied on univariate analyses, reducing power and limiting context specific understanding. Here we aim to provide an integrated perspective of the genetic basis of metabolites by leveraging the Finnish Metabolic Syndrome In Men (METSIM) cohort, a unique genetic resource which contains metabolic measurements across distinct timepoints as well as detailed information on statin usage. We increase effective sample size by an average of two-fold by applying the Covariates for Multi-phenotype Studies (CMS) approach, identifying 588 significant SNP-metabolite associations, including 248 novel associations. We further show that many of these SNPs are master metabolic regulators, balancing the relative proportion of dozens of metabolite levels. We then identify the first associations to changes in metabolic levels across time as well as evidence of genetic...
A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context https://t.co/db7PZ4XkEo #bioRxiv
A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context https://t.co/ejz6a1GoaQ #biorxiv_genetic
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The age of large-scale genome-wide association studies (GWAS) has provided us with an unprecedented opportunity to evaluate the genetic liability of complex disease using polygenic risk scores (PRS). In this study, we have analysed 162 PRS (P<5x10-05) derived from GWAS and 551 heritable traits from the UK Biobank study (N=334,398). Findings can be investigated using a web application (http://mrcieu.mrsoftware.org/PRS_atlas/), which we envisage will help uncover both known and novel mechanisms which contribute towards disease susceptibility. To demonstrate this, we have investigated the results from a phenome-wide evaluation of schizophrenia genetic liability. Amongst findings were inverse associations with measures of cognitive function which extensive follow-up analyses using Mendelian randomization (MR) provided evidence of a causal relationship. We have also investigated the effect of multiple risk factors on disease using mediation and multivariable MR frameworks. Our atlas provides a resource for future endeavours seeking to...
@patrickaturley This. says what you say, but...: https://t.co/UzoxAFp4Dt
https://t.co/DUOcqDfhpu atlas of polygenic risk scores
An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome | bioRxiv https://t.co/W3vytQiLKf
Analysis from @mendel_random and colleagues examining 162 PRS across 551 traits in @uk_biobank including phenomewide analysis of #schizophrenia https://t.co/ryJI0EdB8g https://t.co/lAI5Ut6VRU
This atlas of 162 polygenic risk score associations with 551 traits derived from #GWAS of @uk_biobank can be used with Mendelian Randomization analysis to gain causal and biological insights. Via @biorxiv_genetic https://t.co/ZV6hnbUT9g https://t.co/GhCGYTtrCL
Is genetic risk for my trait of interest correlated with any other trait? This browser by @mendel_random et al. may answer that question: https://t.co/ts3cnSBkAV
Associated paper: https://t.co/pFaxTOUkNX https://t.co/i0JBk3qqa8
Happy to share that our atlas of polygenic risk associations is online https://t.co/Mf7Sof7w3s along with the preprint https://t.co/caVQAoLjqP. Please let me know about any bugs, hopefully people find it useful :) Big thanks to @Sean_Harrison2 @explodecomputer and @mendel_random https://t.co/UHeuYQRnEf
An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome. #causalinference
#phenome #bioRxiv #preprint https://t.co/sjYbzHCDbs
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Lucila Ines Cere,
In recent years, studies in Caenorhabditis elegans nematodes have shown that different stresses can generate multigenerational changes. Here we show that worms that grow in liquid media, and also their plate-grown progeny, are different from worms whose ancestors were grown on plates. It has been suggested that C. elegans might encounter liquid environments in nature, although actual observations in the wild are few and far between. In contrast, in the lab, growing worms in liquid is commonplace, and often used as an alternative to growing worms on agar plates, to control the composition of the worms' diet, to starve (and synchronize) worms, or to grow large populations for biochemical assays. We found that plate-grown descendants of M9 liquid media-grown worms were longer than control worms, and the heritable effects were apparent already very early in development. We tested for the involvement of different known epigenetic inheritance mechanisms, but could not find a single mutant in which these inter-generational effects are...
Instability of epigenetic traits: "...while growing in liquid always leads to inter-generational changes in the worms' size, trans-generational effects were found to be variable, and in some cases the effects were gone after 1-2 generations" https://t.co/TIDvhdTNMr
Study from @OdedRechavi shows that liquid culture (cultivation conditions) changes #Celegans physiology and some changes can carry over to the progeny. https://t.co/R6u91YXTb6
Whoa- Inter-generational Consequences for Growing C. elegans in Liquid | bioRxiv https://t.co/ZgfPFJz87j
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Gregory R. Keele,
Wesley L. Crouse,
Samir N. P. Kelada,
The Collaborative Cross (CC) is a mouse genetic reference population whose range of applications includes quantitative trait loci (QTL) mapping. The design of a CC QTL mapping study involves multiple decisions, including which and how many strains to use, and how many replicates per strain to phenotype, all viewed within the context of hypothesized QTL architecture. Until now, these decisions have been informed largely by early power analyses that were based on simulated, hypothetical CC genomes. Now that more than 50 CC strains are available and more than 70 CC genomes have been observed, it is possible to characterize power based on realized CC genomes. We report power analyses based on extensive simulations and examine several key determinants of power: 1) the number of strains and biological replicates, 2) the QTL effect size, and 3) the distribution of functionally distinct alleles among the founder strains at the QTL. We also provide general power estimates to aide in the design of future experiments. All analyses were...
Designing a Collaborative Cross (CC) experiment or just need a power trip? Check out my preprint with @wescrouse. Work out of the @samir_kelada and @WilliamValdar labs.
Determinants of QTL mapping power in the realized Collaborative Cross https://t.co/JBqPBvQq2J
RT @biorxivpreprint: Determinants of QTL mapping power in the realized Collaborative Cross https://t.co/CMxgyjk25v #bioRxiv
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Prabhpreet S Bassi,
Kinga I Gawlik,
Kara M Place,
Steven A Prescott,
Evgueni A Ivakine,
Ronald D Cohn
Identification of genetic modifiers has provided critically important insights into the pathogenesis and heterogeneity of disease phenotypes in individuals affected by neuromuscular disorders (NMDs). Targeting modifier genes to improve disease phenotypes could be especially beneficial in cases where the causative genes are large, structurally complex and the mutations are heterogeneous. Here, we report a mutation-independent strategy to upregulate expression of a compensatory disease-modifying gene in Congenital Muscular Dystrophy type 1A (MDC1A) using a CRISPR/dCas9-based transcriptional activation system. MDC1A is caused by nonfunctional Laminin α2, which compromises muscle fibers stability and axon myelination in peripheral nerves. Transgenic overexpression of Lama1 , encoding a structurally similar protein Laminin α1, ameliorates muscle wasting and paralysis in the MDC1A mouse models, demonstrating its important role as a disease modifier. Yet, upregulation of Lama1 as a postnatal gene therapy is hampered by its large size,...
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A. Gregory Matera,
Amanda C. Raimer,
Casey A. Schmidt,
Jo A. Kelly,
Gaith N. Droby,
Sara ten Have,
Angus I. Lamond,
Eric J. Wagner,
Kelsey M. Gray
Spinal Muscular Atrophy (SMA) is caused by homozygous mutations in the human survival motor neuron 1 ( SMN1 ) gene. SMN protein has a well-characterized role in the biogenesis of small nuclear ribonucleoproteins (snRNPs), core components of the spliceosome. SMN is part of an oligomeric complex with core binding partners, collectively called Gemins. Biochemical and cell biological studies demonstrate that certain Gemins are required for proper snRNP assembly and transport. However, the precise functions of most Gemins are unknown. To gain a deeper understanding of the SMN complex in the context of metazoan evolution, we investigated the composition of the SMN complex in Drosophila melanogaster . Using a stable transgenic line that exclusively expresses Flag-tagged SMN from its native promoter, we previously found that Gemin2, Gemin3, Gemin5, and all nine classical Sm proteins, including Lsm10 and Lsm11, co-purify with SMN. Here, we show that CG2941 is also highly enriched in the pulldown. Reciprocal co-immunoprecipitation reveals...
Composition of the Survival Motor Neuron (SMN) complex in Drosophila melanogaster https://t.co/fNPTH22tn8 #bioRxiv
Composition of the Survival Motor Neuron (SMN) complex in Drosophila melanogaster https://t.co/akVuctwS6K #biorxiv_genetic
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