Trans-ancestral dissection of urate- and gout-associated major loci SLC2A9 and ABCG2 reveals primate-specific regulatory effects.

Gout is a complex inflammatory arthritis affecting ~20% of people with an elevated serum urate level (hyperuricemia). Gout and hyperuricemia are essentially specific to humans and other higher primates, with varied prevalence across ancestral groups. SLC2A9 and ABCG2 are major loci associated with both urate and gout in multiple ancestral groups. However, fine mapping has been challenging due to extensive linkage disequilibrium underlying the associated regions. We used trans-ancestral fine mapping integrated with primate-specific genomic information to address this challenge. Trans-ancestral meta-analyses of GWAS cohorts of either European (EUR) or East Asian (EAS) ancestry resulted in single-variant resolution mappings for SLC2A9 (rs3775948 for urate and rs4697701 for gout) and ABCG2 (rs2622621 for gout). Tests of colocalization of variants in both urate and gout suggested existence of a shared candidate causal variant for SLC2A9 only in EUR and for ABCG2 only in EAS. The fine-mapped gout variant rs4697701 was within an ancient enhancer, whereas rs2622621 was within a primate-specific transposable element, both supported by functional evidence from the Roadmap Epigenomics project in human primary tissues relevant to urate and gout. Additional primate-specific elements were found near both loci and those adjacent to SLC2A9 overlapped with known statistical epistatic interactions associated with urate as well as multiple super-enhancers identified in urate-relevant tissues. We conclude that by leveraging ancestral differences trans-ancestral fine mapping has identified ancestral and functional variants for SLC2A9 or ABCG2 with primate-specific regulatory effects on urate and gout.

Detecting epistasis in human complex traits.

Genome-wide association studies (GWASs) have become the focus of the statistical analysis of complex traits in humans, successfully shedding light on several aspects of genetic architecture and biological aetiology. Single-nucleotide polymorphisms (SNPs) are usually modelled as having additive, cumulative and independent effects on the phenotype. Although evidently a useful approach, it is often argued that this is not a realistic biological model and that epistasis (that is, the statistical interaction between SNPs) should be included. The purpose of this Review is to summarize recent directions in methodology for detecting epistasis and to discuss evidence of the role of epistasis in human complex trait variation. We also discuss the relevance of epistasis in the context of GWASs and potential hazards in the interpretation of statistical interaction terms.

Author Correction: Genotypic variability-based genome-wide association study identifies non-additive loci HLA-C and IL12B for psoriasis.

This article was originally published under a CC BY-NC-SA License, but has now been made available under a CC BY 4.0 License.

Dyslexia associated functional variants in Europeans are not associated with dyslexia in Chinese.

Genome-wide association studies (GWAS) of developmental dyslexia (DD) often used European samples and identified only a handful associations with moderate or weak effects. This study aims to identify DD functional variants by integrating the GWAS associations with tissue-specific functional data and test the variants in a Chinese DD study cohort named READ. We colocalized associations from nine DD related GWAS with expression quantitative trait loci (eQTL) derived from brain tissues and identified two eSNPs rs349045 and rs201605. Both eSNPs had supportive evidence of chromatin interactions observed in human hippocampus tissues and their respective target genes ZNF45 and DNAH9 both had lower expression in brain tissues in schizophrenia patients than controls. In contrast, an eSNP rs4234898 previously identified based on eQTL from the lymphoblastic cell lines of dyslexic children had no chromatin interaction with its target gene SLC2A3 in hippocampus tissues and SLC2A3 expressed higher in the schizophrenia patients than controls. We genotyped the three eSNPs in the READ cohort of 372 cases and 354 controls and discovered only weak associations in rs201605 and rs4234898 with three DD symptoms (p < .05). The lack of associations could be due to low power in READ but could also implicate different etiology of DD in Chinese.

Genotypic variability-based genome-wide association study identifies non-additive loci HLA-C and IL12B for psoriasis.

Genome-wide association studies (GWASs) have identified a number of loci for psoriasis but largely ignored non-additive effects. We report a genotypic variability-based GWAS (vGWAS) that can prioritize non-additive loci without requiring prior knowledge of interaction types or interacting factors in two steps, using a mixed model to partition dichotomous phenotypes into an additive component and non-additive environmental residuals on the liability scale and then the Levene's (Brown-Forsythe) test to assess equality of the residual variances across genotype groups genome widely. The vGWAS identified two genome-wide significant (P < 5.0e-08) non-additive loci HLA-C and IL12B that were also genome-wide significant in an accompanying GWAS in the discovery cohort. Both loci were statistically replicated in vGWAS of an independent cohort with a small sample size. HLA-C and IL12B were reported in moderate gene-gene and/or gene-environment interactions in several occasions. We found a moderate interaction with age-of-onset of psoriasis, which was replicated indirectly. The vGWAS also revealed five suggestive loci (P < 6.76e-05) including FUT2 that was associated with psoriasis with environmental aspects triggered by virus infection and/or metabolic factors. Replication and functional investigation are needed to validate the suggestive vGWAS loci.

Abundant local interactions in the 4p16.1 region suggest functional mechanisms underlying SLC2A9 associations with human serum uric acid.

Human serum uric acid concentration (SUA) is a complex trait. A recent meta-analysis of multiple genome-wide association studies (GWAS) identified 28 loci associated with SUA jointly explaining only 7.7% of the SUA variance, with 3.4% explained by two major loci (SLC2A9 and ABCG2). Here we examined whether gene-gene interactions had any roles in regulating SUA using two large GWAS cohorts included in the meta-analysis [the Atherosclerosis Risk in Communities study cohort (ARIC) and the Framingham Heart Study cohort (FHS)]. We found abundant genome-wide significant local interactions in ARIC in the 4p16.1 region located mostly in an intergenic area near SLC2A9 that were not driven by linkage disequilibrium and were replicated in FHS. Taking the forward selection approach, we constructed a model of five SNPs with marginal effects and three epistatic SNP pairs in ARIC-three marginal SNPs were located within SLC2A9 and the remaining SNPs were all located in the nearby intergenic area. The full model explained 1.5% more SUA variance than that explained by the lead SNP alone, but only 0.3% was contributed by the marginal and epistatic effects of the SNPs in the intergenic area. Functional analysis revealed strong evidence that the epistatically interacting SNPs in the intergenic area were unusually enriched at enhancers active in ENCODE hepatic (HepG2, P = 4.7E-05) and precursor red blood (K562, P = 5.0E-06) cells, putatively regulating transcription of WDR1 and SLC2A9. These results suggest that exploring epistatic interactions is valuable in uncovering the complex functional mechanisms underlying the 4p16.1 region.

BiForce Toolbox: powerful high-throughput computational analysis of gene-gene interactions in genome-wide association studies.

Genome-wide association studies (GWAS) have discovered many loci associated with common disease and quantitative traits. However, most GWAS have not studied the gene-gene interactions (epistasis) that could be important in complex trait genetics. A major challenge in analysing epistasis in GWAS is the enormous computational demands of analysing billions of SNP combinations. Several methods have been developed recently to address this, some using computers equipped with particular graphical processing units, most restricted to binary disease traits and all poorly suited to general usage on the most widely used operating systems. We have developed the BiForce Toolbox to address the demand for high-throughput analysis of pairwise epistasis in GWAS of quantitative and disease traits across all commonly used computer systems. BiForce Toolbox is a stand-alone Java program that integrates bitwise computing with multithreaded parallelization and thus allows rapid full pairwise genome scans via a graphical user interface or the command line. Furthermore, BiForce Toolbox incorporates additional tests of interactions involving SNPs with significant marginal effects, potentially increasing the power of detection of epistasis. BiForce Toolbox is easy to use and has been applied in multiple studies of epistasis in large GWAS data sets, identifying interesting interaction signals and pathways.

Human-specific insights into candidate genes and boosted discoveries of novel loci illuminate roles of neuroglia in reading disorders.

Reading disorders (RD) are human-specific neuropsychological conditions associated with decoding printed words and/or reading comprehension. So far only a handful of candidate genes segregated in families and 42 loci from genome-wide association study (GWAS) have been identified that jointly provided little clues of pathophysiology. Leveraging human-specific genomic information, we critically assessed the RD candidates for the first time and found substantial human-specific features within. The GWAS candidates (i.e., population signals) were distinct from the familial counterparts and were more likely pleiotropic in neuropsychiatric traits and to harbor human-specific regulatory elements (HSREs). Candidate genes associated with human cortical morphology indeed showed human-specific expression in adult brain cortices, particularly in neuroglia likely regulated by HSREs. Expression levels of candidate genes across human brain developmental stages showed a clear pattern of uplifted expression in early brain development crucial to RD development. Following the new insights and loci pleiotropic in cognitive traits, we identified four novel genes from the GWAS sub-significant associations (i.e., FOXO3, MAPT, KMT2E and HTT) and the Semaphorin gene family with functional priors (i.e., SEMA3A, SEMA3E and SEMA5B). These novel genes were related to neuronal plasticity and disorders, mostly conserved the pattern of uplifted expression in early brain development and had evident expression in cortical neuroglial cells. Our findings jointly illuminated the association of RD with neuroglia regulation-an emerging hotspot in studying neurodevelopmental disorders, and highlighted the need of improving RD phenotyping to avoid jeopardizing future genetic studies of RD.

High-throughput analysis of epistasis in genome-wide association studies with BiForce.

MOTIVATION: Gene-gene interactions (epistasis) are thought to be important in shaping complex traits, but they have been under-explored in genome-wide association studies (GWAS) due to the computational challenge of enumerating billions of single nucleotide polymorphism (SNP) combinations. Fast screening tools are needed to make epistasis analysis routinely available in GWAS. RESULTS: We present BiForce to support high-throughput analysis of epistasis in GWAS for either quantitative or binary disease (case-control) traits. BiForce achieves great computational efficiency by using memory efficient data structures, Boolean bitwise operations and multithreaded parallelization. It performs a full pair-wise genome scan to detect interactions involving SNPs with or without significant marginal effects using appropriate Bonferroni-corrected significance thresholds. We show that BiForce is more powerful and significantly faster than published tools for both binary and quantitative traits in a series of performance tests on simulated and real datasets. We demonstrate BiForce in analysing eight metabolic traits in a GWAS cohort (323 697 SNPs, >4500 individuals) and two disease traits in another (>340 000 SNPs, >1750 cases and 1500 controls) on a 32-node computing cluster. BiForce completed analyses of the eight metabolic traits within 1 day, identified nine epistatic pairs of SNPs in five metabolic traits and 18 SNP pairs in two disease traits. BiForce can make the analysis of epistasis a routine exercise in GWAS and thus improve our understanding of the role of epistasis in the genetic regulation of complex traits. AVAILABILITY AND IMPLEMENTATION: The software is free and can be downloaded from http://bioinfo.utu.fi/BiForce/. CONTACT: wenhua.wei@igmm.ed.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Leveraging primate-specific genomic information for genetic studies of complex diseases.

Genomic changes specific to higher primates are regarded as primate-specific genomic information (PSI). Using PSI to inform genetic studies is highly desirable but hampered by three factors: heterogeneity among PSI studies, lack of integrated profiles of the identified PSI elements and dearth of relevant functional information. We report a database of 19,767 PSI elements collated from nine types of brain-related studies, which form 19,473 non-overlapping PSI regions that distribute unevenly but jointly cover only 0.81% of the genome. About 2.5% of the PSI regions colocalized with variants identified in genome-wide association studies, with disease loci more likely colocalized than quantitative trait loci (p = 1.6 × 10-5), particularly in regions without obvious regulatory roles. We further showed an LRP4 exemplar region with PSI elements orchestrated with common and rare disease variants and other functional elements. Our results render PSI elements as a valuable source to inform genetic studies of complex diseases.

Dissecting the complexity of pediatric blood transfusions and risk of adverse reactions in Aotearoa New Zealand.

BACKGROUND: Children have different clinical and physiological drivers for transfusion from adult recipients. However, adverse transfusion reactions (ATRs) in pediatric patients are usually reported using the same criteria as for adults. Broad assessments of pediatric ATRs neglect substantial variation in different developmental stages. MATERIALS AND METHODS: This retrospective study included 342,950 patients, ~2.43 million transfusions, and 5,540 ATR reports collated from New Zealand hospitals between 2005 and 2021. Using 16 years as the upper age limit, 138,856 pediatric transfusions and 402 pediatric ATR reports were identified and dissected at three levels: pediatric as a whole, pediatric developmental stage (i.e., neonate, infant, preschool, and school), and chronological age to identify patients at high risk of ATRs. Multivariate logistic regression analysis was followed to quantify risk factors. RESULTS: Pediatric recipients had a higher ATR risk than adults (p=6.9-07) but the high risk was associated mainly with children older than 2 years. Neonates and infants accounted for 75.0% of pediatric recipients but had much lower ATR rates than adults. Pediatric transfusion recipients showed a clear male bias prior to age 11 years and then a female bias. However, gender difference in experiencing ATRs was significant only after age 13 years (p=2.3-04). Analyses focusing on the high-risk group revealed allergic reactions being the cause of the elevated risk and identified the main risk factors of number of transfusions (p=4.5-10) and multiple types of components transfused (p=2.0-13). DISCUSSION: The identified ATR risk factors signal linkage with the biological drivers for transfusion. Low ATR rates in infancy could also be attributed to use of neonatal components, low transfusions per patient, and less developed immunity. The relative increase in female recipients from age 11 may be associated with increased red blood cell demand following puberty.

A critical assessment of dose effects of post-thaw CD34 on autologous stem cell transplantation treatment of haematological malignancies.

A consensus threshold of pre-cryopreservation CD34-positive cells (CD34s) has been used as the minimum dose to initiate autologous stem cell transplantation (ASCT). Advances in cryopreservation posed a debate whether post-thaw CD34s might be a superior surrogate instead. We addressed the debate in this retrospective study of 217 adult ASCTs in five different haematological malignancies treated at a single centre. We showed that post-thaw CD34s was highly correlated with pre-cryopreservation CD34s (r = 0.97) and explained ∼2.2% (p = 0.003) of the variation of the post-thaw total nucleated cell viability that however had no power to predict engraftment outcomes. After stratifying the ASCT cases into four dose groups based on post-thaw CD34s reinfused, stepwise multivariate regression analyses detected significant effects in dose group and interactions with diseases for neutrophil and platelet recovery respectively. The significant dose effects and interactions were triggered by two technical outliers in the low dose group, and disappeared in the repeated regressions after exclusion of the outliers where disease and age were the significant predictors remained. Our data clearly support the validity of the consensus threshold in ASCT applications but also highlight neglected conditions where monitoring post-thaw CD34s and clinical attributes are valuable.

Novel risk patterns of vasovagal reactions in NZ blood donations complicated by COVID-19 restrictions.

Introduction: Vasovagal reactions (VVRs) are common but complex donor adverse reactions (DAEs) in blood donations. VVRs have been extensively studied with a multitude of risk factors identified including young age, female gender and first-time donor status. How they may interplay remains obscure. Methods: A total of 1,984,116 blood donations and 27,952 immediate VVRs (iVVRs) and 1,365 delayed VVRs (dVVRs) reported between 2011 and 2021 in NZ were used in multivariate logistic regression analyses each concerning donations with iVVRs as cases and those free of DAEs as controls. For each analysis stepwise selection was used to identify the best model and risk factors carrying significant main effects and/or interactions. Identified interactions informed further in-depth regression analyses to dissect iVVR risk patterns. Results: Over 95% of VVRs were iVVRs that had lower female preponderance and deferrals than dVVRs. iVVRs had a school seasonal pattern in whole blood donations driven by first-time donors from schools/colleges, and interactions between gender and age group differentiating the first-time from repeat donations. Subsequent regression analyses identified the known and novel risk factors of year and mobile collection sites and their interactions. iVVR rates were roundly elevated in 2020 and 2021 probably because of COVID-19 restrictions like facemask wearing. Exclusion of the 2020 and 2021 data removed the interactions with year, but confirmed interactions of gender with mobile collection sites (p = 6.2e-07) in first-time donations only and with age group in repeat donations only (p < 2.2e-16), together indicating young female donors at the highest risk of iVVRs. Our results also revealed that donation policy changes contributed to the year effects; donors had a lower iVVR risk at mobile sites than well-medicalized donation centers probably because of under-reporting. Conclusion: Modeling statistical interactions is valuable in identifying odds and revealing novel iVVR risk patterns and insights into blood donations.

Pinyin Is an Effective Proxy for Early Screening for Mandarin-Speaking Children at Risk of Reading Disorders.

Reading disorders (RD) are common and complex neuropsychological conditions associated with decoding printed words and/or reading comprehension. Early identification of children at risk of RD is critical to allow timely interventions before mental suffering and reading impairment take place. Chinese is a unique medium for studying RD because of extra efforts required in reading acquisition of characters based on meaning rather than phonology. Pinyin, an alphabetic coding system mapping Mandarin sounds to characters, is important to develop oral language skills and a promising candidate for early screening for RD. In this pilot study, we used a cohort of 100 students (50 each in Grades 1 and 2) to derive novel profiles of applying Pinyin to identify early schoolers at risk of RD. Each student had comprehensive reading related measures in two consecutive years, including Pinyin reading and reading comprehension tested in the first and second year, respectively. We showed that Pinyin reading was mainly determined by phonological awareness, was well developed in Grade 1 and the top predictor of reading comprehension (explaining ∼30% of variance, p < 1.0e-05). Further, students who performed poorly in Pinyin reading [e.g. 1 standard deviation (SD) below the average, counting 14% in Grade 1 and 10% in Grade 2], tended to perform poorly in future reading comprehension tests, including all four individuals in Grade 1 (two out of three in Grade 2) who scored 1.5 SDs below the average. Pinyin is therefore an effective proxy for early screening for Mandarin-speaking children at risk of RD.

Mouse models for human hyperuricaemia: a critical review.

Hyperuricaemia (increased serum urate concentration) occurs mainly in higher primates, including in humans, because of inactivation of the gene encoding uricase during primate evolution. Individuals with hyperuricaemia might develop gout - a painful inflammatory arthritis caused by monosodium urate crystal deposition in articular structures. Hyperuricaemia is also associated with common chronic diseases, including hypertension, chronic kidney disease, type 2 diabetes and cardiovascular disease. Many mouse models have been developed to investigate the causal mechanisms for hyperuricaemia. These models are highly diverse and can be divided into two broad categories: mice with genetic modifications (genetically induced models) and mice exposed to certain environmental factors (environmentally induced models; for example, pharmaceutical or dietary induction). This Review provides an overview of the mouse models of hyperuricaemia and the relevance of these models to human hyperuricaemia, with an emphasis on those models generated through genetic modifications. The challenges in developing and comparing mouse models of hyperuricaemia and future research directions are also outlined.

Population genetic structure of Diaphorina citri Kuwayama (Hemiptera: Liviidae): host-driven genetic differentiation in China.

The Asian citrus psyllid Diaphorina citri Kuwayama is a major pest in citrus production, transmitting Candidatus Liberibacter asiaticus. It has spread widely across eastern and southern China. Unfortunately, little is known about the genetic diversity and population structure of D. citri, making pest control difficult. In this study, nine specifically developed SSR markers and three known mitochondrial DNA were used for population genetics study of D. citri using 225 samples collected from all 7 distribution regions in China. Based on the SSR data, D. citri was found highly diverse with a mean observed heterozygosity of 0.50, and three subgroups were structured by host plant: (i) Shatangju, NF mandarin and Ponkan; (ii) Murraya paniculata and Lemon; (iii) Citrus unshiu, Bingtangcheng, Summer orange and Navel. No significant genetic differences were found with mtDNA data. We suggested the host-associated divergence is likely to have occurred very recently. A unimodal distribution of paired differences, the negative and significant Tajima's D and Fu's F S parameters among mtDNA suggested a recent demographic expansion. The extensive citrus cultivation and increased suitable living habitat was recommended as a key for this expansion event.

Genotypic variability based association identifies novel non-additive loci DHCR7 and IRF4 in sero-negative rheumatoid arthritis.

Sero-negative rheumatoid arthritis (RA) is a highly heterogeneous disorder with only a few additive loci identified to date. We report a genotypic variability-based genome-wide association study (vGWAS) of six cohorts of sero-negative RA recruited in Europe and the US that were genotyped with the Immunochip. A two-stage approach was used: (1) a mixed model to partition dichotomous phenotypes into an additive component and non-additive residuals on the liability scale and (2) the Levene's test to assess equality of the residual variances across genotype groups. The vGWAS identified rs2852853 (P = 1.3e-08, DHCR7) and rs62389423 (P = 1.8e-05, near IRF4) in addition to two previously identified loci (HLA-DQB1 and ANKRD55), which were all statistically validated using cross validation. DHCR7 encodes an enzyme important in cutaneous synthesis of vitamin D and DHCR7 mutations are believed to be important for early humans to adapt to Northern Europe where residents have reduced ultraviolet-B exposure and tend to have light skin color. IRF4 is a key locus responsible for skin color, with a vitamin D receptor-binding interval. These vGWAS results together suggest that vitamin D deficiency is potentially causal of sero-negative RA and provide new insights into the pathogenesis of the disorder.

Immunochip Analyses of Epistasis in Rheumatoid Arthritis Confirm Multiple Interactions within MHC and Suggest Novel Non-MHC Epistatic Signals.

OBJECTIVE: Studying statistical gene-gene interactions (epistasis) has been limited by the difficulties in performance, both statistically and computationally, in large enough sample numbers to gain sufficient power. Three large Immunochip datasets from cohort samples recruited in the United Kingdom, United States, and Sweden with European ancestry were used to examine epistasis in rheumatoid arthritis (RA). METHODS: A full pairwise search was conducted in the UK cohort using a high-throughput tool and the resultant significant epistatic signals were tested for replication in the United States and Swedish cohorts. A forward selection approach was applied to remove redundant signals, while conditioning on the preidentified additive effects. RESULTS: We detected abundant genome-wide significant (p < 1.0e-13) epistatic signals, all within the MHC region. These signals were reduced substantially, but a proportion remained significant (p < 1.0e-03) in conditional tests. We identified 11 independent epistatic interactions across the entire MHC, each explaining on average 0.12% of the phenotypic variance, nearly all replicated in both replication cohorts. We also identified non-MHC epistatic interactions between RA susceptible loci LOC100506023 and IRF5 with Immunochip-wide significance (p < 1.1e-08) and between 2 neighboring single-nucleotide polymorphism near PTPN22 that were in low linkage disequilibrium with independent interaction (p < 1.0e-05). Both non-MHC epistatic interactions were statistically replicated with a similar interaction pattern in the US cohort only. CONCLUSION: There are multiple but relatively weak interactions independent of the additive effects in RA and a larger sample number is required to confidently assign additional non-MHC epistasis.

Major histocompatibility complex harbors widespread genotypic variability of non-additive risk of rheumatoid arthritis including epistasis.

Genotypic variability based genome-wide association studies (vGWASs) can identify potentially interacting loci without prior knowledge of the interacting factors. We report a two-stage approach to make vGWAS applicable to diseases: firstly using a mixed model approach to partition dichotomous phenotypes into additive risk and non-additive environmental residuals on the liability scale and secondly using the Levene's (Brown-Forsythe) test to assess equality of the residual variances across genotype groups per marker. We found widespread significant (P < 2.5e-05) vGWAS signals within the major histocompatibility complex (MHC) across all three study cohorts of rheumatoid arthritis. We further identified 10 epistatic interactions between the vGWAS signals independent of the MHC additive effects, each with a weak effect but jointly explained 1.9% of phenotypic variance. PTPN22 was also identified in the discovery cohort but replicated in only one independent cohort. Combining the three cohorts boosted power of vGWAS and additionally identified TYK2 and ANKRD55. Both PTPN22 and TYK2 had evidence of interactions reported elsewhere. We conclude that vGWAS can help discover interacting loci for complex diseases but require large samples to find additional signals.