A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers

Breast cancer (BC) risk for BRCA1 and BRCA2 mutation carriers varies by genetic and familial factors. About 50 common variants have been shown to modify BC risk for mutation carriers. All but three, were identified in general population studies. Other mutation carrier-specific susceptibility variants may exist but studies of mutation carriers have so far been underpowered. We conduct a novel case-only genome-wide association study comparing genotype frequencies between 60,212 general population BC cases and 13,007 cases with BRCA1 or BRCA2 mutations. We identify robust novel associations for 2 variants with BC for BRCA1 and 3 for BRCA2 mutation carriers, P < 10−8, at 5 loci, which are not associated with risk in the general population. They include rs60882887 at 11p11.2 where MADD, SP11 and EIF1, genes previously implicated in BC biology, are predicted as potential targets. These findings will contribute towards customising BC polygenic risk scores for BRCA1 and BRCA2 mutation carriers

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. Methods: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. Findings: The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. Interpretation: Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. Funding: Bill & Melinda Gates Foundation

Geometry- and rate-dependent adhesive failure of micropatterned surfaces

The dynamic nature of adhesive interface failure remains poorly understood, especially when the contact between the two surfaces is localized in microscopic points of adhesion. Here, we explore the dynamic failure of adhesive interfaces composed of a large number of micron-sized pillars against glass. Surprisingly, we find a large influence of the microcontact geometry; ordered arrays of these pillars exhibit significantly stronger adhesive properties than equivalent surfaces in which the pillars are disordered. This can be understood with a simple geometric argument that accounts for the number of adhesive bonds that needs to be broken simultaneously to propagate the crack front. Moreover, the adhesive strength in both cases depends largely on the velocity with which the surfaces are separated. This rate dependence is explained on the basis of a semi-phenomenological model that describes macroscopic failure as a consequence of microscopic bond-rupture events. Our results suggest that the dynamics of adhesive failure, in the limit explored here, is predominantly stress-driven and highly sensitive to local geometry effects

Stress enhancement in the delayed yielding of colloidal gels

Networks of aggregated colloidal particles are solidlike and can sustain an applied shear stress while exhibiting little or no creep; however, ultimately they will catastrophically fail. We show that the time delay for this yielding decreases in two distinct exponential regimes with applied stress. This behavior is universal and found for a variety of colloidal gel systems. We present a bond-rupture model that quantitatively describes this behavior and highlights the role of mesoscopic structures. Our result gives new insight into the nature of yielding in these soft solid materials

A physical cross-linking process of cellulose nanofibril gels with shear-controlled fibril orientation

Cellulose nanofibrils constitute the smallest fibrous components of wood, with a width of approximately 4 nm and a length in the micrometer range. They consist of aligned linear cellulose chains with crystallinity exceeding 60%, rendering stiff, high-aspect-ratio rods. These properties are advantageous in the reinforcement components of composites. Cross-linked networks of fibrils can be used as templates into which a polymer enters. In the semi-concentrated regime (i.e. slightly above the overlap concentration), carboxy methylated fibrils dispersed in water have been physically cross-linked to form a volume-spanning network (a gel) by reducing the pH or adding salt, which diminishes the electrostatic repulsion between fibrils. By applying shear during or after this gelation process, we can orient the fibrils in a preferred direction within the gel, for the purpose of fully utilizing the high stiffness and strength of the fibrils as reinforcement components. Using these gels as templates enables precise control of the spatial distribution and orientation of the dispersed phase of the composites, optimizing the potentially very large reinforcement capacity of the nanofibrils

Structures, stresses, and fluctuations in the delayed failure of colloidal gel

Sample-spanning networks of aggregated colloidal particles have a finite stiffness and deform elastically when subjected to a small shear stress. After some period of creep, these gels ultimately suffer catastrophic failure. This delayed yielding is governed by the association and dissociation dynamics of interparticle bonds and the strand structure of the gel. We derive a model which connects the kinetics of the colloids to the erosion of the strand structure and ultimately to macroscopic failure. Importantly, this model relates time-to-failure of the gel to an applied static stress. Model predictions are in quantitative agreement with experiments. It is predicted that the strand structure, characterized by its mesh size and strand coarseness, has a significant impact on delay time. Decreasing the mesh size or increasing the strand thickness makes colloidal gels more resilient to delayed yielding. The quench and flow history of gels modifies their microstructures. Our experiments show that a slow quenching increases the delay time due to the coarsening of the strands; by contrast, preshear reduces the delay time, which we explain by the increased mesh size as a result of shear-induced fracture of strands