Strongly SiO
2
-undersaturated alkalic rocks (Mg# > 50, SiO
2
≤ 45 wt%, Na
2
O + K
2
O ≥ 3 wt%) occur in three early-stage (Sarnu-Dandali, Mundwara, Bhuj) and one late-stage (Murud-Janjira) ...rift-associated volcanic complexes in the Cretaceous-Paleogene Deccan Traps flood basalt province of India. Thermobarometry based on clinopyroxene-liquid equilibrium suggests that they mostly crystallized beneath the Moho at ~ 15 kbar/1270 °C to ~ 11–12 kbar/1115–1156 °C pressures and temperatures. Primary magma compositions in equilibrium with lherzolite were estimated through reverse fractionation calculations by incrementally adding equilibrium phases to the rocks in olivine:clinopyroxene:spinel:phlogopite = 12:68:20:15 proportions at low temperatures followed by olivine:clinopyroxene:spinel = 12:68:20 proportions at higher temperatures. A comparison of the primary magmas with experimentally generated melts shows that their compositions are consistent with an origin from garnet lherzolite sources with < 1 wt% H
2
O and CO
2
. Hornblendite, pyroxenite (except for some Bhuj rocks) and carbonated eclogite are unlikely sources for the Deccan alkalic rocks. The Sarnu-Dandali and Bhuj alkalic rocks and the Murud-Janjira lamprophyres probably originated by < 5% melting of ~ 1.3 times Ti-enriched lherzolitic sources compared to primitive mantle. The primary magmas of the Murud-Janjira basanites calculated through reverse assimilation-fractional crystallization by assimilating lower crustal and mantle xenoliths found in younger lamprophyre dikes of the same area indicate that contamination by the Indian lithosphere was unlikely during their ascent. The basanites evolved by mixing with phonotephritic melts, and they probably originated from a Ti-poor (0.7 times) lherzolite source. The temperature of the melts at the base of the lithosphere was ~ 1325 °C beneath Sarnu-Dandali and ~ 1285 °C beneath Bhuj and Murud-Janjira.
Mendelian randomization (MR) has emerged as a major tool for the investigation of causal relationship among traits, utilizing results from large-scale genome-wide association studies. Bias due to ...horizontal pleiotropy, however, remains a major concern. We propose a novel approach for robust and efficient MR analysis using large number of genetic instruments, based on a novel spike-detection algorithm under a normal-mixture model for underlying effect-size distributions. Simulations show that the new method, MRMix, provides nearly unbiased or/and less biased estimates of causal effects compared to alternative methods and can achieve higher efficiency than comparably robust estimators. Application of MRMix to publicly available datasets leads to notable observations, including identification of causal effects of BMI and age-at-menarche on the risk of breast cancer; no causal effect of HDL and triglycerides on the risk of coronary artery disease; a strong detrimental effect of BMI on the risk of major depressive disorder.
There is increasing evidence that pleiotropy, the association of multiple traits with the same genetic variants/loci, is a very common phenomenon. Cross-phenotype association tests are often used to ...jointly analyze multiple traits from a genome-wide association study (GWAS). The underlying methods, however, are often designed to test the global null hypothesis that there is no association of a genetic variant with any of the traits, the rejection of which does not implicate pleiotropy. In this article, we propose a new statistical approach, PLACO, for specifically detecting pleiotropic loci between two traits by considering an underlying composite null hypothesis that a variant is associated with none or only one of the traits. We propose testing the null hypothesis based on the product of the Z-statistics of the genetic variants across two studies and derive a null distribution of the test statistic in the form of a mixture distribution that allows for fractions of variants to be associated with none or only one of the traits. We borrow approaches from the statistical literature on mediation analysis that allow asymptotic approximation of the null distribution avoiding estimation of nuisance parameters related to mixture proportions and variance components. Simulation studies demonstrate that the proposed method can maintain type I error and can achieve major power gain over alternative simpler methods that are typically used for testing pleiotropy. PLACO allows correlation in summary statistics between studies that may arise due to sharing of controls between disease traits. Application of PLACO to publicly available summary data from two large case-control GWAS of Type 2 Diabetes and of Prostate Cancer implicated a number of novel shared genetic regions: 3q23 (ZBTB38), 6q25.3 (RGS17), 9p22.1 (HAUS6), 9p13.3 (UBAP2), 11p11.2 (RAPSN), 14q12 (AKAP6), 15q15 (KNL1) and 18q23 (ZNF236).
Reducing COVID-19 burden for populations will require equitable and effective risk-based allocations of scarce preventive resources, including vaccinations
. To aid in this effort, we developed a ...general population risk calculator for COVID-19 mortality based on various sociodemographic factors and pre-existing conditions for the US population, combining information from the UK-based OpenSAFELY study with mortality rates by age and ethnicity across US states. We tailored the tool to produce absolute risk estimates in future time frames by incorporating information on pandemic dynamics at the community level. We applied the model to data on risk factor distribution from a variety of sources to project risk for the general adult population across 477 US cities and for the Medicare population aged 65 years and older across 3,113 US counties, respectively. Validation analyses using 54,444 deaths from 7 June to 1 October 2020 show that the model is well calibrated for the US population. Projections show that the model can identify relatively small fractions of the population (for example 4.3%) that might experience a disproportionately large number of deaths (for example 48.7%), but there is wide variation in risk across communities. We provide a web-based risk calculator and interactive maps for viewing community-level risks.
Genome-wide association studies have shown that pleiotropy is a common phenomenon that can potentially be exploited for enhanced detection of susceptibility loci. We propose heritability informed ...power optimization (HIPO) for conducting powerful pleiotropic analysis using summary-level association statistics. We find optimal linear combinations of association coefficients across traits that are expected to maximize non-centrality parameter for the underlying test statistics, taking into account estimates of heritability, sample size variations and overlaps across the traits. Simulation studies show that the proposed method has correct type I error, robust to population stratification and leads to desired genome-wide enrichment of association signals. Application of the proposed method to publicly available data for three groups of genetically related traits, lipids (N = 188,577), psychiatric diseases (Ncase = 33,332, Ncontrol = 27,888) and social science traits (N ranging between 161,460 to 298,420 across individual traits) increased the number of genome-wide significant loci by 12%, 200% and 50%, respectively, compared to those found by analysis of individual traits. Evidence of replication is present for many of these loci in subsequent larger studies for individual traits. HIPO can potentially be extended to high-dimensional phenotypes as a way of dimension reduction to maximize power for subsequent genetic association testing.
Many complex human diseases, such as type 2 diabetes, are characterized by multiple underlying traits/phenotypes that have substantially shared genetic architecture. Multivariate analysis of ...correlated traits has the potential to increase the power of detecting underlying common genetic loci. Several cross-phenotype association methods have been proposed-some require individual-level data on traits and genotypes, while the others require only summary-level data. In this article, we explore whether non-normality of multivariate trait distribution affects the inference from some of the existing multi-trait methods and how that effect is dependent on the allele count of the genetic variant being tested. We find that most of these tests are susceptible to biases that lead to spurious association signals. Even after controlling for confounders that may contribute to non-normality and then applying inverse normal transformation on the residuals of each trait, these tests may have inflated type I errors for variants with low minor allele counts (MACs). A likelihood ratio test of association based on the ordinal regression of individual-level genotype conditional on the traits seems to be the least biased and can maintain type I error when the MAC is reasonably large (e.g., MAC > 30). Application of these methods to publicly available summary statistics of eight amino acid traits on European samples seem to exhibit systematic inflation (especially for variants with low MAC), which is consistent with our findings from simulation experiments.
Breast cancer (BC) risk prediction allows systematic identification of individuals at highest and lowest risk. We extend the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation ...Algorithm (BOADICEA) risk model to incorporate the effects of polygenic risk scores (PRS) and other risk factors (RFs).
BOADICEA incorporates the effects of truncating variants in BRCA1, BRCA2, PALB2, CHEK2, and ATM; a PRS based on 313 single-nucleotide polymorphisms (SNPs) explaining 20% of BC polygenic variance; a residual polygenic component accounting for other genetic/familial effects; known lifestyle/hormonal/reproductive RFs; and mammographic density, while allowing for missing information.
Among all factors considered, the predicted UK BC risk distribution is widest for the PRS, followed by mammographic density. The highest BC risk stratification is achieved when all genetic and lifestyle/hormonal/reproductive/anthropomorphic factors are considered jointly. With all factors, the predicted lifetime risks for women in the UK population vary from 2.8% for the 1st percentile to 30.6% for the 99th percentile, with 14.7% of women predicted to have a lifetime risk of ≥17-<30% (moderate risk according to National Institute for Health and Care Excellence NICE guidelines) and 1.1% a lifetime risk of ≥30% (high risk).
This comprehensive model should enable high levels of BC risk stratification in the general population and women with family history, and facilitate individualized, informed decision-making on prevention therapies and screening.
Despite appreciable advances in carnivore ecology, studies on small cats remain limited with carnivore research in India being skewed towards large cats. Small cats are more specialized than their ...larger cousins in terms of resource selection. Studies on small cat population and habitat preference are critical to evaluate their status to ensure better management and conservation. We estimated abundance of two widespread small cats, the jungle cat, and the rusty-spotted cat, and investigated their habitat associations based on camera trap captures from a central Indian tiger reserve. We predicted fine-scale habitat segregation between these sympatric species as a driver of coexistence. We used an extension of the spatial count model in a Bayesian framework approach to estimate the population density of jungle cat and rusty-spotted cat and used generalized linear models to explore their habitat associations. Densities of rusty-spotted cat and jungle cat were estimated as 6.67 (95% CI 4.07-10.74) and 4.01 (95% CI 2.65-6.12) individuals/100 km.sup.2 respectively. Forest cover and evapotranspiration were positively associated with rusty-spotted cat occurrence whereas both factors had a significant negative relation with jungle cat occurrence. The results directed habitat segregation between these small cats with affinities of rusty-spotted cat and jungle cat towards well-forested and open scrubland areas respectively. Our estimates highlight the widespread applicability of this model for density estimation of species with no individual identification. Moreover, the study outcomes can aid in targeted management decisions and serve as the baseline for species conservation as these models allow robust population estimation of elusive species along with predicting their habitat preferences.
Ultrahigh-pressure (UHP) rocks such as the coesite-bearing eclogites, occurring as boudins within felsic gneisses of the Tso Morari dome in northwestern Himalayas, originated through subduction of ...the northern continental margin of India during its early Eocene collision with the Kohistan–Ladakh arc. These rocks are believed to be exhumed through a low-viscosity channel along the top surface of the subducting slab. However, details of the exhumation mechanism are poorly known. We present new constraints on the
P
–
T
evolution of hydrous and carbonate-rich samples of the Tso Morari eclogite between 2.2–2.3 GPa/400–425 °C and ~0.4 GPa/450 °C using thermobarometry and calculated
P
–
T
–
M
CO
2
phase equilibria. Our results indicate that the eclogites were strongly heated at high pressures from 400–425 °C at 2.2–2.3 GPa to 670–720 °C at 1.8–1.9 GPa during the early stages of exhumation. Diffusion modeling of Ca variation across the core–rim interface of garnet indicates that the heating stage lasted only <0.1 Myr, in accordance with geochronological constraints and fast exhumation rates. Our
P
–
T
path is at odds with exhumation of the eclogites along a subduction channel as model calculations indicate that the intermediate
P
–
T
conditions of 1.8–1.9 GPa/670–720 °C are not achieved along the subducting slab. Instead, the constrained
P
–
T
conditions are consistent with heating within the mantle wedge overlying the subducting slab. Therefore, we conclude that the Tso Morari eclogites were possibly exhumed as part of a low-density, felsic diapir rising through the mantle wedge. Based on low viscosity values (1.7 × 10
19
–5.0 × 10
19
Pa s) of mantle wedges associated with modern subduction zones, the calculated exhumation rate for the Tso Morari eclogite is extremely fast (29–147 mm/yr) and at par with that constrained for other northwestern Himalayan UHP rocks.
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