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Single nucleotide polymorphisms (SNPs) contribute small increases in risk for late-onset Alzheimer's disease (LOAD). LOAD SNPs cluster around genes with similar biological functions (pathways). Polygenic risk scores (PRS) aggregate the effect of SNPs genome-wide. However, this approach has not been widely used for SNPs within specific pathways.
We investigated whether pathway-specific PRS were significant predictors of LOAD case/control status.
We mapped SNPs to genes within 8 pathways implicated in LOAD. For our polygenic analysis, the discovery sample comprised 13,831 LOAD cases and 29,877 controls. LOAD risk alleles for SNPs in our 8 pathways were identified at a P-value threshold of 0.5. Pathway-specific PRS were calculated in a target sample of 3332 cases and 9832 controls. The genetic data were pruned with R2 > 0.2 while retaining the SNPs most significantly associated with AD. We tested whether pathway-specific PRS were associated with LOAD using logistic regression, adjusting for age, sex, country, and principal components. We report the proportion of variance in liability explained by each pathway.
The most strongly associated pathways were the immune response (NSNPs = 9304, = 5.63 × 10−19, R2 = 0.04) and hemostasis (NSNPs = 7832, P = 5.47 × 10−7, R2 = 0.015). Regulation of endocytosis, hematopoietic cell lineage, cholesterol transport, clathrin and protein folding were also significantly associated but accounted for less than 1% of the variance. With APOE excluded, all pathways remained significant except proteasome-ubiquitin activity and protein folding.
Genetic risk for LOAD can be split into contributions from different biological pathways. These offer a means to explore disease mechanisms and to stratify patients.
Disclosure of interest
The authors have not supplied their declaration of competing interest.
This book chapter compares civil litigation in the courts of first and second instances in Taiwan in 2010–2015 with that in U.S. federal courts in 2010–2013. The two judicial systems, as expected, are different in many ways. Settlement rates in Taiwan, even broadly defined, were below 25%; in U.S. federal court, they exceed 70%. In Taiwan, summary judgments were basically non-existent; in U.S. federal court, they represent nearly a third of merits judgments. Rates of appeal in Taiwan are nearly 10 times higher (27% versus 3%) than in the U.S. federal courts. And yet judges in Taiwan, at least those in the court of first instance, handled cases more quickly than their colleagues in the U.S. federal courts—indeed, twice as fast. Yet, the two judicial systems respond similarly when encountering simple debt collection cases. These cases, large in number in both systems, fail to settle as standard theories would predict. Instead, these disputes are frequently resolved through default judgments. This chapter provides cautionary lessons for future empirical comparative civil procedure studies.
The Indian Supreme Court has been called “the most powerful court in the world” for its wide jurisdiction, its expansive understanding of its own powers, and the billion plus people under its authority. Yet scholars and policy makers have a very uneven picture of the court’s functioning: deep knowledge about the more visible, “high-profile” cases but very little about more mundane, but far more numerous and potentially equally important, decisions. This chapter aims to address this imbalance with a rigorous, empirical account of the Court’s decisions from 2010 to 2015. We use the most extensive original dataset of Indian Supreme Court opinions yet created to provide a broad, quantitative overview of the social identity of the litigants that approach the court, the types of matters they bring to the court, the levels of success that different groups of litigants have before the Court, and the opinion-writing patterns of the various judges of the Supreme Court. This analysis provides foundational facts for the study of the Court and its role in progressive social change.
We review our current understanding of the interior structure and thermal evolution of Saturn, with a focus on recent results in the Cassini era. There has been important progress in understanding physical inputs, including equations of state of planetary materials and their mixtures, physical parameters like the gravity field and rotation rate, and constraints on Saturnian free oscillations. At the same time, new methods of calculation, including work on the gravity field of rotating fluid bodies, and the role of interior composition gradients, should help to better constrain the state of Saturn’s interior, now and earlier in its history. However, a better appreciation of modeling uncertainties and degeneracies, along with a greater exploration of modeling phase space, still leave great uncertainties in our understanding of Saturn’s interior. Further analysis of Cassini data sets, as well as precise gravity field measurements from the Cassini Grand Finale orbits, will further revolutionize our understanding of Saturn’s interior over the next few years.