Post hoc Analysis for Detecting Individual Rare Variant Risk Associations Using Probit Regression Bayesian Variable Selection Methods in Case‐Control Sequencing Studies
ABSTRACTRare variants (RVs) have been shown to be significant contributors to complex disease risk. By definition, these variants have very low minor allele frequencies and traditional single‐marker methods for statistical analysis are underpowered for typical sequencing study sample sizes. Multimarker burden‐type approaches attempt to identify aggregation of RVs across case‐control status by analyzing relatively small partitions of the genome, such as genes. However, it is generally the case that the aggregative measure would be a mixture of causal and neutral variants, and these omnibus tests do not directly provide any indication of which RVs may be driving a given association. Recently, Bayesian variable selection approaches have been proposed to identify RV associations from a large set of RVs under consideration. Although these approaches have been shown to be powerful at detecting associations at the RV level, there are often computational limitations on the total quantity of RVs under consideration and compromises are necessary for large‐scale application. Here, we propose a computationally efficient alternative formulation of this method using a probit regression approach specifically capable of simultaneously analyzing hundreds to thousands of RVs. We evaluate our approach to detect causal variation on simulated data and examine sensitivity and specificity in instances of high RV dimensionality as well as apply it to pathway‐level RV analysis results from a prostate cancer (PC) risk case‐control sequencing study. Finally, we discuss potential extensions and future directions of this work.
Targeting Sequence Domain: A Captain at the Helm Precisely Steering DNMT1 through Maintenance Methylation?
ABSTRACTIntravenous immunoglobulin [IVIg], plasma exchange [PE], and corticosteroids are efficacious treatment in chronic inflammatory demyelinating polyneuropathy [CIDP]. IVIg is effective in multifocal motor neuropathy [MMN]. NIS, NIS‐weakness, sum scores of raw amplitudes of motor fiber (CMAPs) amplitudes, and Dyck/Rankin score provided reliable measures to detect and scale abnormality and reflect change; they are therefore ideal for office management of response‐based immunotherapy (R‐IRx) of CIDP. Using efficacious R‐IRx, a large early and late therapeutic response (≥ one‐fourth were in remission or had recovered) was demonstrated in CIDP. In MMN only an early improvement with late non‐significant worsening was observed. The difference in immunotherapy response supports a fundamental difference between CIDP (immune attack on Schwann cells and myelin) and MMN (attack on nodes of Ranvier and axons). Muscle Nerve 52: 488–497, 2015
Polyneuropathy improvement following autologous stem cell transplantation for POEMS syndrome