Biology subjects

Xinli Hu

Publications and source records attributed to Xinli Hu.

2 recordsLinked to original sources

bioRxiv2015

Using genotype data to distinguish pleiotropy from heterogeneity: deciphering coheritability in autoimmune and neuropsychiatric diseases

Shared genetic architecture between phenotypes may be driven by a common genetic basis (pleiotropy) or a subset of genetically similar individuals (heterogeneity). We developed BUHMBOX, a well-powered statistical method to distinguish pleiotropy from heterogeneity using genotype data. We observed a shared genetic basis between 11 of 17 tested autoimmune diseases and type I diabetes (T1D, p<10-12) and 11 of 17 tested autoimmune diseases and rheumatoid arthritis (RA, p<10-7). This sharing could not be explained by heterogeneity (corrected pBUHMBOX>0.2 using 6,670 T1D cases and 7,279 RA cases), suggesting that shared genetic features in autoimmunity are due to pleiotropy. We observed a shared genetic basis between seronegative and seropostive RA (p<10-22), explained by heterogeneity (pBUHMBOX=0.008 in 2,406 seronegative RA cases). Consistent with previous observations, we observed genetic sharing between major depressive disorder (MDD) and schizophrenia (p<10-9). This sharing is not explained by heterogeneity (pBUHMBOX=0.28 in 9,238 MDD cases).

Genomics↗

bioRxiv2014

Disentangling effects of colocalizing genomic annotations to functionally prioritize non-coding variants within complex trait loci

Identifying genomic annotations that differentiate causal from associated variants is critical to fine-map disease loci. While many studies have identified non-coding annotations overlapping disease variants, these annotations colocalize, complicating fine-mapping efforts. We demonstrate that conventional enrichment tests are inflated and cannot distinguish causal effects from colocalizing annotations. We developed a sensitive and specific statistical approach that is able to identify independent effects from colocalizing annotations. We first confirm that gene regulatory variants map to DNase-I hypersensitive sites (DHS) near transcription start sites. We then show that (1) 15-35% of causal variants within disease loci map to DHS independent of other annotations; (2) breast cancer and rheumatoid arthritis loci harbor potentially causal variants near the summits of histone marks rather than full peak bodies; and (3) variants associated with height are highly enriched for embryonic stem cell DHS sites. We highlight specific loci where we can most effectively prioritize causal variation.

Genomics↗