An adaptive truncated product method for combining dependent p-values

Interpretable network-guided epistasis detection

BACKGROUND

Detecting epistatic interactions at the gene level is essential to understanding the biological mechanisms of complex diseases. Unfortunately, genome-wide interaction association studies involve many statistical challenges that make such detection hard. We propose a multi-step protocol for epistasis detection along the edges of a gene-gene co-function network. Such an approach reduces the number of tests performed and provides interpretable interactions while keeping type I error controlled. Yet, mapping gene interactions into testable single-nucleotide polymorphism (SNP)-interaction hypotheses, as well as computing gene pair association scores from SNP pair ones, is not trivial.

RESULTS

Here we compare 3 SNP-gene mappings (positional overlap, expression quantitative trait loci, and proximity in 3D structure) and use the adaptive truncated product method to compute gene pair scores. This method is non-parametric, does not require a known null distribution, and is fast to compute. We apply multiple variants of this protocol to a genome-wide association study dataset on inflammatory bowel disease. Different configurations produced different results, highlighting that various mechanisms are implicated in inflammatory bowel disease, while at the same time, results overlapped with known disease characteristics. Importantly, the proposed pipeline also differs from a conventional approach where no network is used, showing the potential for additional discoveries when prior biological knowledge is incorporated into epistasis detection.

Detecting Weak Signals by Combining Small P-Values in Genetic Association Studies

We approach the problem of combining top-ranking association statistics or P-values from a new perspective which leads to a remarkably simple and powerful method. Statistical methods, such as the rank truncated product (RTP), have been developed for combining top-ranking associations, and this general strategy proved to be useful in applications for detecting combined effects of multiple disease components. To increase power, these methods aggregate signals across top ranking single nucleotide polymorphisms (SNPs), while adjusting for their total number assessed in a study. Analytic expressions for combined top statistics or P-values tend to be unwieldy, which complicates interpretation and practical implementation and hinders further developments. Here, we propose the augmented rank truncation (ART) method that retains main characteristics of the RTP but is substantially simpler to implement. ART leads to an efficient form of the adaptive algorithm, an approach where the number of top ranking SNPs is varied to optimize power. We illustrate our methods by strengthening previously reported associations of μ-opioid receptor variants with sensitivity to pain.

Association of Kir genes with blood pressure responses to dietary sodium intervention: the GenSalt study

Blood pressure (BP) responses to dietary sodium intervention vary among individuals. The inwardly rectifying potassium channel (Kir) is a potassium-selective ion channel that allows potassium ions to move more easily into rather than out of the cell. We aimed to investigate the associations of Kir genes with BP responses to dietary sodium intervention. A 7-day low-sodium intervention followed by a 7-day high-sodium intervention was conducted among 1906 participants. BP measurements were obtained at baseline and during each dietary intervention. Both single-marker and gene-based analyses were performed to explore the associations between Kir gene variants and BP responses to dietary sodium interventions. The genetic risk score (GRS) was used to assess the cumulative effect of the variants on the BP response to the sodium interventions. During the low-sodium intervention, markers rs858009, rs2835904, and rs860795 in KCNJ6 were significantly associated with the systolic BP (SBP) response (P = 8.82 × 10^-6, 3.32 × 10^-6, and 2.39 × 10^-4, respectively), whereas rs858009 and rs2835904 were significantly correlated with the mean arterial pressure (MAP) response (P = 1.64 × 10^-4 and 2.72 × 10^-4, respectively). Marker rs2836023 showed a significant association with the SBP response (P = 5.72 × 10^-5) to the high-sodium intervention. The GRS stratified by quartile grouping or as a continuous variable was associated with the BP response to the sodium interventions. Gene-based analyses consistently revealed that KCNJ6 was significantly associated with the BP response to the sodium interventions. These findings suggest that KCNJ6 may contribute to variation of BP responses to dietary sodium interventions. Future studies are warranted to confirm these findings and to identify functional variants for salt sensitivity.