scholarly journals Evidence of polygenic adaptation at height-associated loci in mainland Europeans and Sardinians

2019 ◽  
Author(s):  
Minhui Chen ◽  
Carlo Sidore ◽  
Masato Akiyama ◽  
Kazuyoshi Ishigaki ◽  
Yoichiro Kamatani ◽  
...  
Keyword(s):  
Large Scale ◽  
Adult Height ◽  
Genetic Difference ◽  
Asian Population ◽  
Effect Sizes ◽  
Summary Statistics ◽  
Polygenic Adaptation ◽  
Robust Adaptive ◽  
Open Question ◽  
European Populations

AbstractAdult height was one of the earliest putative examples of polygenic adaptation in human. By constructing polygenic height scores using effect sizes and frequencies from hundreds of genomic loci robustly associated with height, it was reported that Northern Europeans were genetically taller than Southern Europeans beyond neutral expectation. However, this inference was recently challenged. Sohail et al. and Berg et al. showed that the polygenic signature disappeared if summary statistics from UK Biobank (UKB) were used in the analysis, suggesting that residual uncorrected stratification from large-scale consortium studies was responsible for the previously noted genetic difference. It thus remains an open question whether height loci exhibit signals of polygenic adaptation in any human population. In the present study, we re-examined this question, focusing on one of the shortest European populations, the Sardinians, as well as on the mainland European populations in general. We found that summary statistics from UKB significantly correlate with population structure in Europe. To further alleviate concerns of biased ascertainment of GWAS loci, we examined height-associated loci from the Biobank of Japan (BBJ). Applying frequency-based inference over these height-associated loci, we showed that the Sardinians remain significantly shorter than expected (~ 0.35 standard deviation shorter than CEU based on polygenic height scores, P = 1.95e-6). We also found the trajectory of polygenic height scores decreased over at least the last 10,000 years when compared to the British population (P = 0.0123), consistent with a signature of polygenic adaptation at height-associated loci. Although the same approach showed a much subtler signature in mainland European populations, we found a clear and robust adaptive signature in UK population using a haplotype-based statistic, tSDS, driven by the height-increasing alleles (P = 4.8e-4). In summary, by examining frequencies at height loci ascertained in a distant East Asian population, we further supported the evidence of polygenic adaptation at height-associated loci among the Sardinians. In mainland Europeans, we also found an adaptive signature, although becoming more pronounced only in haplotype-based analysis.

scholarly journals Causal Inference between Rheumatoid Arthritis and Breast Cancer in East Asian and European Population: A Two-Sample Mendelian Randomization

Cancers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3272
Author(s):  
Choonghyun Ahn ◽  
Sangjun Lee ◽  
Sue K. Park
Keyword(s):  
Breast Cancer ◽  
Rheumatoid Arthritis ◽  
Large Scale ◽  
Mendelian Randomization ◽  
Association Studies ◽  
East Asian ◽  
Asian Population ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Causal Association

Previous studies have been reported that the association between rheumatoid arthritis (RA) and breast cancer remains inconclusive. A two-sample Mendelian randomization (MR) analysis can reveal the potential causal association between exposure and outcome. A two-sample MR analysis using the penalized robust inverse variance weighted (PRIVW) method was performed to analyze the association between RA and breast cancer risk based on the summary statistics of six genome-wide association studies (GWAS) targeting RA in an East Asian population along with summary statistics of the BioBank Japan (BBJ), Breast Cancer Association Consortium (BCAC), and Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) targeting breast cancer. We found that the direction of the effect of RA on breast cancer varied among GWAS-summary data from BBJ, BCAC, and CIMBA. Significant horizontal pleiotropy based on a penalized robust MR-Egger regression was observed only for BBJ and CIMBA BRCA2 carriers. As the results of the two-sample MR analyses were inconsistent, the causal association between RA and breast cancer was inconclusive. The biological mechanisms explaining the relationship between RA and breast cancer were unclear in Asian as well as in Caucasians. Further studies using large-scale patient cohorts are required for the validation of these results.

Identification of and Correction for Publication Bias: Comment

2019 ◽  
Author(s):  
Amanda Kvarven ◽  
Eirik Strømland ◽  
Magnus Johannesson
Keyword(s):  
Publication Bias ◽  
False Positive ◽  
Large Scale ◽  
Meta Analysis ◽  
False Positive Rate ◽  
Effect Sizes ◽  
Replication Studies ◽  
Moderate Reduction ◽  
Positive Rate ◽  
Meta Analyses

Andrews & Kasy (2019) propose an approach for adjusting effect sizes in meta-analysis for publication bias. We use the Andrews-Kasy estimator to adjust the result of 15 meta-analyses and compare the adjusted results to 15 large-scale multiple labs replication studies estimating the same effects. The pre-registered replications provide precisely estimated effect sizes, which do not suffer from publication bias. The Andrews-Kasy approach leads to a moderate reduction of the inflated effect sizes in the meta-analyses. However, the approach still overestimates effect sizes by a factor of about two or more and has an estimated false positive rate of between 57% and 100%.

scholarly journals Large-scale variation in seismic anisotropy in the crust and upper mantle beneath Anatolia, Turkey

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Cédric P. Legendre ◽  
Li Zhao ◽  
Tai-Lin Tseng
Keyword(s):  
Upper Mantle ◽  
Large Scale ◽  
Seismic Anisotropy ◽  
Crust And Upper Mantle ◽  
Wave Splitting ◽  
Mantle Processes ◽  
Open Question ◽  
Subduction System ◽  
Anisotropic Phase ◽  
Regional Tectonics

AbstractThe average anisotropy beneath Anatolia is very strong and is well constrained by shear-wave splitting measurements. However, the vertical layering of anisotropy and the contribution of each layer to the overall pattern is still an open question. Here, we construct anisotropic phase-velocity maps of fundamental-mode Rayleigh waves for the Anatolia region using ambient noise seismology and records from several regional seismic stations. We find that the anisotropy patterns in the crust, lithosphere and asthenosphere beneath Anatolia have limited amplitudes and are generally consistent with regional tectonics and mantle processes dominated by the collision between Eurasia and Arabia and the Aegean/Anatolian subduction system. The anisotropy of these layers in the crust and upper mantle are, however, not consistent with the strong average anisotropy measured in this area. We therefore suggest that the main contribution to overall anisotropy likely originates from a deep and highly anisotropic region round the mantle transition zone.

scholarly journals From lithium to sodium: cell chemistry of room temperature sodium–air and sodium–sulfur batteries

2015 ◽  
Vol 6 ◽  
pp. 1016-1055 ◽  
Author(s):  
Philipp Adelhelm ◽  
Pascal Hartmann ◽  
Conrad L Bender ◽  
Martin Busche ◽  
Christine Eufinger ◽  
...  
Keyword(s):  
Energy Density ◽  
Large Scale ◽  
Room Temperature ◽  
Low Cost ◽  
Strong Impact ◽  
Performance Improvements ◽  
Key Issues ◽  
Lithium Oxygen Batteries ◽  
Open Question ◽  
Lithium Sulfur

Research devoted to room temperature lithium–sulfur (Li/S8) and lithium–oxygen (Li/O2) batteries has significantly increased over the past ten years. The race to develop such cell systems is mainly motivated by the very high theoretical energy density and the abundance of sulfur and oxygen. The cell chemistry, however, is complex, and progress toward practical device development remains hampered by some fundamental key issues, which are currently being tackled by numerous approaches. Quite surprisingly, not much is known about the analogous sodium-based battery systems, although the already commercialized, high-temperature Na/S8 and Na/NiCl2 batteries suggest that a rechargeable battery based on sodium is feasible on a large scale. Moreover, the natural abundance of sodium is an attractive benefit for the development of batteries based on low cost components. This review provides a summary of the state-of-the-art knowledge on lithium–sulfur and lithium–oxygen batteries and a direct comparison with the analogous sodium systems. The general properties, major benefits and challenges, recent strategies for performance improvements and general guidelines for further development are summarized and critically discussed. In general, the substitution of lithium for sodium has a strong impact on the overall properties of the cell reaction and differences in ion transport, phase stability, electrode potential, energy density, etc. can be thus expected. Whether these differences will benefit a more reversible cell chemistry is still an open question, but some of the first reports on room temperature Na/S8 and Na/O2 cells already show some exciting differences as compared to the established Li/S8 and Li/O2 systems.

scholarly journals Estimating Effect Sizes and Expected Replication Probabilities from GWAS Summary Statistics

2016 ◽  
Vol 7 ◽  
Author(s):  
Dominic Holland ◽  
Yunpeng Wang ◽  
Wesley K. Thompson ◽  
Andrew Schork ◽  
Chi-Hua Chen ◽  
...  
Keyword(s):  
Effect Sizes ◽  
Summary Statistics

scholarly journals Estimating Effect Sizes and Expected Replication Probabilities from GWAS Summary Statistics

2015 ◽  
Author(s):  
Dominic Holland ◽  
Yunpeng Wang ◽  
Wesley K Thompson ◽  
Andrew Schork ◽  
Chi-Hua Chen ◽  
...  
Keyword(s):  
Association Studies ◽  
Significant Snps ◽  
Effect Sizes ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Sample Sizes ◽  
Genetic Components ◽  
Complex Phenotypes ◽  
Genome Wide ◽  
Z Scores

Genome-wide Association Studies (GWAS) result in millions of summary statistics (``z-scores'') for single nucleotide polymorphism (SNP) associations with phenotypes. These rich datasets afford deep insights into the nature and extent of genetic contributions to complex phenotypes such as psychiatric disorders, which are understood to have substantial genetic components that arise from very large numbers of SNPs. The complexity of the datasets, however, poses a significant challenge to maximizing their utility. This is reflected in a need for better understanding the landscape of z-scores, as such knowledge would enhance causal SNP and gene discovery, help elucidate mechanistic pathways, and inform future study design. Here we present a parsimonious methodology for modeling effect sizes and replication probabilities that does not require raw genotype data, relying only on summary statistics from GWAS substudies, and a scheme allowing for direct empirical validation. We show that modeling z-scores as a mixture of Gaussians is conceptually appropriate, in particular taking into account ubiquitous non-null effects that are likely in the datasets due to weak linkage disequilibrium with causal SNPs. The four-parameter model allows for estimating the degree of polygenicity of the phenotype -- the proportion of SNPs (after uniform pruning, so that large LD blocks are not over-represented) likely to be in strong LD with causal/mechanistically associated SNPs -- and predicting the proportion of chip heritability explainable by genome wide significant SNPs in future studies with larger sample sizes. We apply the model to recent GWAS of schizophrenia (N=82,315) and additionally, for purposes of illustration, putamen volume (N=12,596), with approximately 9.3 million SNP z-scores in both cases. We show that, over a broad range of z-scores and sample sizes, the model accurately predicts expectation estimates of true effect sizes and replication probabilities in multistage GWAS designs. We estimate the degree to which effect sizes are over-estimated when based on linear regression association coefficients. We estimate the polygenicity of schizophrenia to be 0.037 and the putamen to be 0.001, while the respective sample sizes required to approach fully explaining the chip heritability are 106and 105. The model can be extended to incorporate prior knowledge such as pleiotropy and SNP annotation. The current findings suggest that the model is applicable to a broad array of complex phenotypes and will enhance understanding of their genetic architectures.

scholarly journals Atlas of functional connectivity relationships across rare and common genetic variants, traits, and psychiatric conditions

2021 ◽  
Author(s):  
Clara A Moreau ◽  
Kuldeep Kumar ◽  
Annabelle Harvey ◽  
Guillaume Huguet ◽  
Sebastian Urchs ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Large Scale ◽  
Brain Connectivity ◽  
Copy Number Variants ◽  
Effect Sizes ◽  
Genomic Variants ◽  
Common Genetic Variants ◽  
Polygenic Scores ◽  
Genetic Risks ◽  
Psychiatric Conditions

Polygenicity and pleiotropy are key properties of the genomic architecture of psychiatric disorders. An optimistic interpretation of polygenicity is that genomic variants converge on a limited set of mechanisms at some level from genes to behavior. Alternatively, convergence may be minimal or absent. We took advantage of brain connectivity, measured by resting-state functional MRI (rs-fMRI), as well as rare and common genomic variants to understand the effects of polygenicity and pleiotropy on large-scale brain networks, a distal step from genes to behavior. We processed ten rs-fMRI datasets including 32,988 individuals, to examine connectome-wide effects of 16 copy number variants (CNVs), 10 polygenic scores, 6 cognitive and brain morphometry traits, and 4 idiopathic psychiatric conditions. Although effect sizes of CNVs on connectivity were correlated to cognition and number of genes, increasing polygenicity was associated with decreasing effect sizes on connectivity. Accordingly, the effect sizes of polygenic scores on connectivity were 6-fold lower compared to CNVs. Despite this heterogeneity of connectivity profiles, multivariate analysis identified convergence of genetic risks and psychiatric disorders on the thalamus and the somatomotor network. Based on spatial correlations with transcriptomic data, we hypothesize that excitatory thalamic neurons may be primary contributors to brain alteration profiles shared across genetic risks and conditions. Finally, pleiotropy measured by genetic and transcriptomic correlations between 38 pairs of conditions/traits showed significant concordance with connectomic correlations, suggesting a substantial causal genetic component for shared connectivity. Such findings open avenues to delineate general mechanisms - amenable to intervention - across conditions and genetic risks.

scholarly journals Better estimation of SNP heritability from summary statistics provides a new understanding of the genetic architecture of complex traits

2018 ◽  
Author(s):  
Doug Speed ◽  
David J Balding
Keyword(s):  
Complex Traits ◽  
Genetic Architecture ◽  
Large Scale ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Confounding Bias ◽  
Conserved Regions ◽  
Genome Wide ◽  
Variation Explained

LD Score Regression (LDSC) has been widely applied to the results of genome-wide association studies. However, its estimates of SNP heritability are derived from an unrealistic model in which each SNP is expected to contribute equal heritability. As a consequence, LDSC tends to over-estimate confounding bias, under-estimate the total phenotypic variation explained by SNPs, and provide misleading estimates of the heritability enrichment of SNP categories. Therefore, we present SumHer, software for estimating SNP heritability from summary statistics using more realistic heritability models. After demonstrating its superiority over LDSC, we apply SumHer to the results of 24 large-scale association studies (average sample size 121 000). First we show that these studies have tended to substantially over-correct for confounding, and as a result the number of genome-wide significant loci has under-reported by about 20%. Next we estimate enrichment for 24 categories of SNPs defined by functional annotations. A previous study using LDSC reported that conserved regions were 13-fold enriched, and found a further twelve categories with above 2-fold enrichment. By contrast, our analysis using SumHer finds that conserved regions are only 1.6-fold (SD 0.06) enriched, and that no category has enrichment above 1.7-fold. SumHer provides an improved understanding of the genetic architecture of complex traits, which enables more efficient analysis of future genetic data.

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