An Excess of Risk-Increasing Low-Frequency Variants Can Be a Signal of Polygenic Inheritance in Complex Diseases

In most complex diseases, much of the heritability remains unaccounted for by common variants. It has been postulated that lower-frequency variants contribute to the remaining heritability. Here, we describe a method to test for polygenic inheritance from lower-frequency variants by using GWAS summary association statistics. We explored scenarios with many causal low-frequency variants and showed that there is more power to detect risk variants than to detect protective variants, resulting in an increase in the ratio of detected risk to protective variants (R/P ratio). Such an excess can also occur if risk variants are present and kept at lower frequencies because of negative selection. The R/P ratio can be falsely elevated because of reasons unrelated to polygenic inheritance, such as uneven sample sizes or asymmetric population stratification, so precautions to correct for these confounders are essential. We tested our method on published GWAS results and observed a strong signal in some diseases (schizophrenia and type 2 diabetes) but not others. We also explored the shared genetic component in overlapping phenotypes related to inflammatory bowel disease (Crohn disease [CD] and ulcerative colitis [UC]) and diabetic nephropathy (macroalbuminuria and end-stage renal disease [ESRD]). Although the signal was still present when both CD and UC were jointly analyzed, the signal was lost when macroalbuminuria and ESRD were jointly analyzed, suggesting that these phenotypes should best be studied separately. Thus, our method may also help guide the design of future genetic studies of various traits and diseases.

Variable selection via RIVAL and its application in nuclear material detection

In many situations, the number of data points is fixed, and the asymptotic convergence results of popular model selection tools may not be useful. A new algorithm for model selection, RIVAL (removing irrelevant variables amidst Lasso iterations), is presented and shown to be particularly effective for a large but fixed number of data points. The algorithm is motivated by an application of nuclear material detection where all unknown parameters are to be non-negative. Thus, positive Lasso and its variants are analyzed. Then, RIVAL is proposed and is shown to have some desirable properties, namely the number of data points needed to have convergence is smaller than existing methods.

Generalized Selection Combining in Cognitive MIMO Relay Networks

We propose transmit antenna selection with receive generalized selection combining (TAS/GSC) in dual-hop cognitive decode-and-forward (DF) relay networks for reliability enhancement and interference relaxation. In this paradigm, a single antenna which maximizes the receive signal-to-noise ratio (SNR) is selected at the secondary transmitter and a subset of receive antennas with the highest SNRs are combined at the secondary receiver. To demonstrate the impact of multiple primary users on the cognitive relay network, we derive new closed-form expressions for the exact and asymptotic outage probability with TAS/GSC in the secondary network. Several important design insights are reached. We corroborate that the full diversity gain is achieved, which is entirely determined by the total number of antennas in the secondary network. The negative impact of the primary network on the secondary network is reflected in the SNR gain.

Clinical end points for drug treatment trials in BCR-ABL1-negative classic myeloproliferative neoplasms: consensus statements from European LeukemiaNET (ELN) and Internation Working Group-Myeloproliferative Neoplasms Research and Treatment (IWG-MRT)

The discovery of somatic mutations, primarily JAK2V617F and CALR, in classic BCR-ABL1-negative myeloproliferative neoplasms (MPNs) has generated interest in the development of molecularly targeted therapies, whose accurate assessment requires a standardized framework. A working group, comprised of members from European LeukemiaNet (ELN) and International Working Group for MPN Research and Treatment (IWG-MRT), prepared consensus-based recommendations regarding trial design, patient selection and definition of relevant end points. Accordingly, a response able to capture the long-term effect of the drug should be selected as the end point of phase II trials aimed at developing new drugs for MPNs. A time-to-event, such as overall survival, or progression-free survival or both, as co-primary end points, should measure efficacy in phase III studies. New drugs should be tested for preventing disease progression in myelofibrosis patients with early disease in randomized studies, and a time to event, such as progression-free or event-free survival should be the primary end point. Phase III trials aimed at preventing vascular events in polycythemia vera and essential thrombocythemia should be based on a selection of the target population based on new prognostic factors, including JAK2 mutation. In conclusion, we recommended a format for clinical trials in MPNs that facilitates communication between academic investigators, regulatory agencies and drug companies.