Genome-wide search for higher order epistasis as modifiers of treatment effects on bone mineral density in childhood cancer survivors

Bone mineral density surveillance for childhood, adolescent, and young adult cancer survivors: evidence-based recommendations from the International Late Effects of Childhood Cancer Guideline Harmonization Group

Childhood, adolescent, and young adult cancer survivors are at increased risk of reduced bone mineral density. Clinical practice surveillance guidelines are important for timely diagnosis and treatment of these survivors, which could improve bone mineral density parameters and prevent fragility fractures. Discordances across current late effects guidelines necessitated international harmonisation of recommendations for bone mineral density surveillance. The International Late Effects of Childhood Cancer Guideline Harmonization Group therefore established a panel of 36 experts from ten countries, representing a range of relevant medical specialties. The evidence of risk factors for very low and low bone mineral density and fractures, surveillance modality, timing of bone mineral density surveillance, and treatment of very low and low bone mineral density were evaluated and critically appraised, and harmonised recommendations for childhood, adolescent, and young adult cancer survivors were formulated. We graded the recommendations based on the quality of evidence and balance between potential benefits and harms. Bone mineral density surveillance is recommended for survivors treated with cranial or craniospinal radiotherapy and is reasonable for survivors treated with total body irradiation. Due to insufficient evidence, no recommendation can be formulated for or against bone mineral density surveillance for survivors treated with corticosteroids. This surveillance decision should be made by the survivor and health-care provider together, after careful consideration of the potential harms and benefits and additional risk factors. We recommend to carry out bone mineral density surveillance using dual-energy x-ray absorptiometry at entry into long-term follow-up, and if normal (Z-score > -1), repeat when the survivor is aged 25 years. Between these measurements and thereafter, surveillance should be done as clinically indicated. These recommendations facilitate evidence-based care for childhood, adolescent, and young adult cancer survivors internationally.

Genome-wide Association Studies Reveal Novel Locus With Sex-/Therapy-Specific Fracture Risk Effects in Childhood Cancer Survivors

Childhood cancer survivors treated with radiation therapy (RT) and osteotoxic chemotherapies are at increased risk for fractures. However, understanding of how genetic and clinical susceptibility factors jointly contribute to fracture risk among survivors is limited. To address this gap, we conducted genome-wide association studies of fracture risk after cancer diagnosis in 2453 participants of European ancestry from the Childhood Cancer Survivor Study (CCSS) with 930 incident fractures using Cox regression models (ie, time-to-event analysis) and prioritized sex- and treatment-stratified genetic associations. We performed replication analyses in 1417 survivors of European ancestry with 652 incident fractures from the St. Jude Lifetime Cohort Study (SJLIFE). In discovery, we identified a genome-wide significant (p < 5 × 10^-8 ) fracture risk locus, 16p13.3 (HAGHL), among female CCSS survivors (n = 1289) with strong evidence of sex-specific effects (p_{sex-heterogeneity}  < 7 × 10^-6 ). Combining discovery and replication data, rs1406815 showed the strongest association (hazard ratio [HR] = 1.43, p = 8.2 × 10^-9 ; n = 1935 women) at this locus. In treatment-stratified analyses in the discovery cohort, the association between rs1406815 and fracture risk among female survivors with no RT exposures was weak (HR = 1.22, 95% confidence interval [CI] 0.95-1.57, p = 0.11) but increased substantially among those with greater head/neck RT doses (any RT: HR = 1.88, 95% CI 1.54-2.28, p = 2.4 × 10^-10 ; >36 Gray only: HR = 3.79, 95% CI 1.95-7.34, p = 8.2 × 10^-5 ). These head/neck RT-specific HAGHL single-nucleotide polymorphism (SNP) effects were replicated in female SJLIFE survivors. In silico bioinformatics analyses suggest these fracture risk alleles regulate HAGHL gene expression and related bone resorption pathways. Genetic risk profiles integrating this locus may help identify female survivors who would benefit from targeted interventions to reduce fracture risk. © 2020 American Society for Bone and Mineral Research (ASBMR).

Parallel repulsive logic regression with biological adjacency

Logic regression, an extension of generalized linear models with Boolean combinations of binary variables as predictors, is a useful tool in exploring interactions among single-nucleotide polymorphisms (SNPs) in genome-wide association studies. However, since the search space defined by all possible combinations of SNPs, their complements, and logical operators in Boolean expressions can be exceedingly large in such studies, objective function optimization is slow and likely to be trapped in many local solutions, resulting in model over-fitting. We introduce a new search algorithm, parallel repulsive logic regression (PRLR), to efficiently estimate parameters of a logic regression to find a best model within the large space of SNP interactions by incorporating: (i) relevant biological adjacency matrix between SNPs to define similarity of estimation paths or trees, which are derived from physical SNP positions on chromosomes and/or memberships in biological gene pathways; and (ii) two repulsive forces to counter the similarity between and within estimation paths considered in parallel, which are introduced as penalty terms in the objective function. We compare our method's performance for identifying biologically-meaningful SNP interactions through simulations and with real genetic-epidemiological data. PRLR's detection-accuracy measures outperform existing approaches, especially in terms of positive predictive value and sensitivity for detecting SNP-SNP interactions.

A network approach to prioritizing susceptibility genes for genome-wide association studies

The heritability of complex diseases including cancer is often attributed to multiple interacting genetic alterations. Such a non-linear, non-additive gene-gene interaction effect, that is, epistasis, renders univariable analysis methods ineffective for genome-wide association studies. In recent years, network science has seen increasing applications in modeling epistasis to characterize the complex relationships between a large number of genetic variations and the phenotypic outcome. In this study, by constructing a statistical epistasis network of colorectal cancer (CRC), we proposed to use multiple network measures to prioritize genes that influence the disease risk of CRC through synergistic interaction effects. We computed and analyzed several global and local properties of the large CRC epistasis network. We utilized topological properties of network vertices such as the edge strength, vertex centrality, and occurrence at different graphlets to identify genes that may be of potential biological relevance to CRC. We found 512 top-ranked single-nucleotide polymorphisms, among which COL22A1, RGS7, WWOX, and CELF2 were the four susceptibility genes prioritized by all described metrics as the most influential on CRC.

Genome-wide haplotype association analysis of primary biliary cholangitis risk in Japanese

Primary biliary cholangitis (PBC) susceptibility loci have largely been discovered through single SNP association testing. In this study, we report genic haplotype patterns associated with PBC risk genome-wide in two Japanese cohorts. Among the 74 genic PBC risk haplotype candidates we detected with a novel methodological approach in a discovery cohort of 1,937 Japanese, nearly two-thirds were replicated (49 haplotypes, Bonferroni-corrected P < 6.8 × 10^-4) in an independent Japanese cohort (N = 949). Along with corroborating known PBC-associated loci (TNFSF15, HLA-DRA), risk haplotypes may potentially model cis-interactions that regulate gene expression. For example, one replicated haplotype association (9q32-9q33.1, OR = 1.7, P = 3.0 × 10^-21) consists of intergenic SNPs outside of the human leukocyte antigen (HLA) region that overlap regulatory histone mark peaks in liver and blood cells, and are significantly associated with TNFSF8 expression in whole blood. We also replicated a novel haplotype association involving non-HLA SNPs mapped to UMAD1 (7p21.3; OR = 15.2, P = 3.9 × 10^-9) that overlap enhancer peaks in liver and memory T_h cells. Our analysis demonstrates the utility of haplotype association analyses in discovering and characterizing PBC susceptibility loci.