Genome-wide association study of CNVs in 16,000 cases of eight common diseases and 3,000 shared controls

A Bibliometric Analysis of GWAS on Rheumatoid Arthritis from 2002 to 2024

INTRODUCTION

Rheumatoid arthritis (RA) has become a serious threat to human health and quality of life worldwide. Previous studies have demonstrated that genetic factors play a crucial role in the onset and progression of RA. Due to the rapid development of genome-wide association study (GWAS) and large-scale genetic analysis, GWAS research on RA has received widespread attention in recent years. Therefore, we conducted a comprehensive visualization and bibliometric analysis of publications to identify hotspots and future trends in GWAS research on RA.

METHODS

Literature on RA and GWAS published between 2002 and 2024 was extracted from the Web of Science Core Collection database by strategic screening. Collected data were further analyzed by using VOSviewer, CiteSpace, and Excel. The collaborations networks of countries, authors, institutions, and the co-citation networks of publications were visualized. Finally, research hotspots and fronts were examined.

RESULTS

A total of 713 publications with 45,773 citations were identified. The number of publications and citations has had a significant surge since 2007. The United States contributed the most publications globally. Okada, Yukinori, was the most influential author. The most productive institution in this field was the University of Manchester. The analysis of keywords revealed that "mendelian randomization analysis", "association", "innate", "instruments", "bias", "pathogenesis", and "genome-wide association study" are likely to be the frontiers of research in this field.

CONCLUSION

This study can be used to predict future research advances in the fields of GWAS on RA and helps to promote academic collaboration among scholars.

Genome-wide association testing beyond SNPs

Decades of genetic association testing in human cohorts have provided important insights into the genetic architecture and biological underpinnings of complex traits and diseases. However, for certain traits, genome-wide association studies (GWAS) for common SNPs are approaching signal saturation, which underscores the need to explore other types of genetic variation to understand the genetic basis of traits and diseases. Copy number variation (CNV) is an important source of heritability that is well known to functionally affect human traits. Recent technological and computational advances enable the large-scale, genome-wide evaluation of CNVs, with implications for downstream applications such as polygenic risk scoring and drug target identification. Here, we review the current state of CNV-GWAS, discuss current limitations in resource infrastructure that need to be overcome to enable the wider uptake of CNV-GWAS results, highlight emerging opportunities and suggest guidelines and standards for future GWAS for genetic variation beyond SNPs at scale.

Unveiling the Genetic Landscape of Coronary Artery Disease Through Common and Rare Structural Variants

BACKGROUND

Genome-wide association studies have identified several hundred susceptibility single nucleotide variants for coronary artery disease (CAD). Despite single nucleotide variant-based genome-wide association studies improving our understanding of the genetics of CAD, the contribution of structural variants (SVs) to the risk of CAD remains largely unclear.

METHOD AND RESULTS

We leveraged SVs detected from high-coverage whole genome sequencing data in a diverse group of participants from the National Heart Lung and Blood Institute's Trans-Omics for Precision Medicine program. Single variant tests were performed on 58 706 SVs in a study sample of 11 556 CAD cases and 42 907 controls. Additionally, aggregate tests using sliding windows were performed to examine rare SVs. One genome-wide significant association was identified for a common biallelic intergenic duplication on chromosome 6q21 (P=1.54E-09, odds ratio=1.34). The sliding window-based aggregate tests found 1 region on chromosome 17q25.3, overlapping USP36, to be significantly associated with coronary artery disease (P=1.03E-10). USP36 is highly expressed in arterial and adipose tissues while broadly affecting several cardiometabolic traits.

CONCLUSIONS

Our results suggest that SVs, both common and rare, may influence the risk of coronary artery disease.

Understanding and applying gene-environment interactions: a guide for nutrition professionals with an emphasis on integration in African research settings

Noncommunicable diseases (NCDs) are influenced by the interplay between genetics and environmental exposures, particularly diet. However, many healthcare professionals, including nutritionists and dietitians, have limited genetic background and, therefore, they may lack understanding of gene-environment interactions (GxEs) studies. Even researchers deeply involved in nutrition studies, but with a focus elsewhere, can struggle to interpret, evaluate, and conduct GxE studies. There is an urgent need to study African populations that bear a heavy burden of NCDs, demonstrate unique genetic variability, and have cultural practices resulting in distinctive environmental exposures compared with Europeans or Americans, who are studied more. Although diverse and rapidly changing environments, as well as the high genetic variability of Africans and difference in linkage disequilibrium (ie, certain gene variants are inherited together more often than expected by chance), provide unparalleled potential to investigate the omics fields, only a small percentage of studies come from Africa. Furthermore, research evidence lags behind the practices of companies offering genetic testing for personalized medicine and nutrition. We need to generate more evidence on GxEs that also considers continental African populations to be able to prevent unethical practices and enable tailored treatments. This review aims to introduce nutrition professionals to genetics terms and valid methods to investigate GxEs and their challenges, and proposes ways to improve quality and reproducibility. The review also provides insight into the potential contributions of nutrigenetics and nutrigenomics to the healthcare sphere, addresses direct-to-consumer genetic testing, and concludes by offering insights into the field's future, including advanced technologies like artificial intelligence and machine learning.

Diversity and consequences of structural variation in the human genome

The biomedical community is increasingly invested in capturing all genetic variants across human genomes, interpreting their functional consequences and translating these findings to the clinic. A crucial component of this endeavour is the discovery and characterization of structural variants (SVs), which are ubiquitous in the human population, heterogeneous in their mutational processes, key substrates for evolution and adaptation, and profound drivers of human disease. The recent emergence of new technologies and the remarkable scale of sequence-based population studies have begun to crystalize our understanding of SVs as a mutational class and their widespread influence across phenotypes. In this Review, we summarize recent discoveries and new insights into SVs in the human genome in terms of their mutational patterns, population genetics, functional consequences, and impact on human traits and disease. We conclude by outlining three frontiers to be explored by the field over the next decade.

Optimizing a CRISPR-Cas13d Gene Circuit for Tunable Target RNA Downregulation with Minimal Collateral RNA Cutting

The invention of RNA-guided DNA cutting systems has revolutionized biotechnology. More recently, RNA-guided RNA cutting by Cas13d entered the scene as a highly promising alternative to RNA interference to engineer cellular transcriptomes for biotechnological and therapeutic purposes. Unfortunately, "collateral damage" by indiscriminate off-target cutting tampered enthusiasm for these systems. Yet, how collateral activity, or even RNA target reduction depends on Cas13d and guide RNA abundance has remained unclear due to the lack of expression-tuning studies to address this question. Here we use precise expression-tuning gene circuits to show that both nonspecific and specific, on-target RNA reduction depend on Cas13d and guide RNA levels, and that nonspecific RNA cutting from trans cleavage might contribute to on-target RNA reduction. Using RNA-level control techniques, we develop new Multi-Level Optimized Negative-Autoregulated Cas13d and crRNA Hybrid (MONARCH) gene circuits that achieve a high dynamic range with low basal on-target RNA reduction while minimizing collateral activity in human kidney cells and green monkey cells most frequently used in human virology. MONARCH should bring RNA-guided RNA cutting systems to the forefront, as easily applicable, programmable tools for transcriptome engineering in biotechnological and medical applications.

Network medicine-based epistasis detection in complex diseases: ready for quantum computing

Most heritable diseases are polygenic. To comprehend the underlying genetic architecture, it is crucial to discover the clinically relevant epistatic interactions (EIs) between genomic single nucleotide polymorphisms (SNPs) (1-3). Existing statistical computational methods for EI detection are mostly limited to pairs of SNPs due to the combinatorial explosion of higher-order EIs. With NeEDL (network-based epistasis detection via local search), we leverage network medicine to inform the selection of EIs that are an order of magnitude more statistically significant compared to existing tools and consist, on average, of five SNPs. We further show that this computationally demanding task can be substantially accelerated once quantum computing hardware becomes available. We apply NeEDL to eight different diseases and discover genes (affected by EIs of SNPs) that are partly known to affect the disease, additionally, these results are reproducible across independent cohorts. EIs for these eight diseases can be interactively explored in the Epistasis Disease Atlas (https://epistasis-disease-atlas.com). In summary, NeEDL demonstrates the potential of seamlessly integrated quantum computing techniques to accelerate biomedical research. Our network medicine approach detects higher-order EIs with unprecedented statistical and biological evidence, yielding unique insights into polygenic diseases and providing a basis for the development of improved risk scores and combination therapies.

Advancements and progress in juvenile idiopathic arthritis: A Review of pathophysiology and treatment

Juvenile idiopathic arthritis (JIA) is a chronic clinical condition characterized by arthritic features in children under the age of 16, with at least 6 weeks of active symptoms. The etiology of JIA remains unknown, and it is associated with prolonged synovial inflammation and structural joint damage influenced by environmental and genetic factors. This review aims to enhance the understanding of JIA by comprehensively analyzing relevant literature. The focus lies on current diagnostic and therapeutic approaches and investigations into the pathoaetiologies using diverse research modalities, including in vivo animal models and large-scale genome-wide studies. We aim to elucidate the multifactorial nature of JIA with a strong focus towards genetic predilection, while proposing potential strategies to improve therapeutic outcomes and enhance diagnostic risk stratification in light of recent advancements. This review underscores the need for further research due to the idiopathic nature of JIA, its heterogeneous phenotype, and the challenges associated with biomarkers and diagnostic criteria. Ultimately, this contribution seeks to advance the knowledge and promote effective management strategies in JIA.

Molecular Regulation and Oncogenic Functions of TSPAN8

Tetraspanins, a superfamily of small integral membrane proteins, are characterized by four transmembrane domains and conserved protein motifs that are configured into a unique molecular topology and structure in the plasma membrane. They act as key organizers of the plasma membrane, orchestrating the formation of specialized microdomains called "tetraspanin-enriched microdomains (TEMs)" or "tetraspanin nanodomains" that are essential for mediating diverse biological processes. TSPAN8 is one of the earliest identified tetraspanin members. It is known to interact with a wide range of molecular partners in different cellular contexts and regulate diverse molecular and cellular events at the plasma membrane, including cell adhesion, migration, invasion, signal transduction, and exosome biogenesis. The functions of cell-surface TSPAN8 are governed by ER targeting, modifications at the Golgi apparatus and dynamic trafficking. Intriguingly, limited evidence shows that TSPAN8 can translocate to the nucleus to act as a transcriptional regulator. The transcription of TSPAN8 is tightly regulated and restricted to defined cell lineages, where it can serve as a molecular marker of stem/progenitor cells in certain normal tissues as well as tumors. Importantly, the oncogenic roles of TSPAN8 in tumor development and cancer metastasis have gained prominence in recent decades. Here, we comprehensively review the current knowledge on the molecular characteristics and regulatory mechanisms defining TSPAN8 functions, and discuss the potential and significance of TSPAN8 as a biomarker and therapeutic target across various epithelial cancers.

GASOLINE: detecting germline and somatic structural variants from long-reads data

Long-read sequencing allows analyses of single nucleic-acid molecules and produces sequences in the order of tens to hundreds kilobases. Its application to whole-genome analyses allows identification of complex genomic structural-variants (SVs) with unprecedented resolution. SV identification, however, requires complex computational methods, based on either read-depth or intra- and inter-alignment signatures approaches, which are limited by size or type of SVs. Moreover, most currently available tools only detect germline variants, thus requiring separate computation of sample pairs for comparative analyses. To overcome these limits, we developed a novel tool (Germline And SOmatic structuraL varIants detectioN and gEnotyping; GASOLINE) that groups SV signatures using a sophisticated clustering procedure based on a modified reciprocal overlap criterion, and is designed to identify germline SVs, from single samples, and somatic SVs from paired test and control samples. GASOLINE is a collection of Perl, R and Fortran codes, it analyzes aligned data in BAM format and produces VCF files with statistically significant somatic SVs. Germline or somatic analysis of 30[Formula: see text] sequencing coverage experiments requires 4-5 h with 20 threads. GASOLINE outperformed currently available methods in the detection of both germline and somatic SVs in synthetic and real long-reads datasets. Notably, when applied on a pair of metastatic melanoma and matched-normal sample, GASOLINE identified five genuine somatic SVs that were missed using five different sequencing technologies and state-of-the art SV calling approaches. Thus, GASOLINE identifies germline and somatic SVs with unprecedented accuracy and resolution, outperforming currently available state-of-the-art WGS long-reads computational methods.

Network medicine-based epistasis detection in complex diseases: ready for quantum computing

Most heritable diseases are polygenic. To comprehend the underlying genetic architecture, it is crucial to discover the clinically relevant epistatic interactions (EIs) between genomic single nucleotide polymorphisms (SNPs)1-3. Existing statistical computational methods for EI detection are mostly limited to pairs of SNPs due to the combinatorial explosion of higher-order EIs. With NeEDL (network-based epistasis detection via local search), we leverage network medicine to inform the selection of EIs that are an order of magnitude more statistically significant compared to existing tools and consist, on average, of five SNPs. We further show that this computationally demanding task can be substantially accelerated once quantum computing hardware becomes available. We apply NeEDL to eight different diseases and discover genes (affected by EIs of SNPs) that are partly known to affect the disease, additionally, these results are reproducible across independent cohorts. EIs for these eight diseases can be interactively explored in the Epistasis Disease Atlas (https://epistasis-disease-atlas.com). In summary, NeEDL is the first application that demonstrates the potential of seamlessly integrated quantum computing techniques to accelerate biomedical research. Our network medicine approach detects higher-order EIs with unprecedented statistical and biological evidence, yielding unique insights into polygenic diseases and providing a basis for the development of improved risk scores and combination therapies.

The ortholog of human ssDNA-binding protein SSBP3 influences neurodevelopment and autism-like behaviors in Drosophila melanogaster

1p32.3 microdeletion/duplication is implicated in many neurodevelopmental disorders-like phenotypes such as developmental delay, intellectual disability, autism, macro/microcephaly, and dysmorphic features. The 1p32.3 chromosomal region harbors several genes critical for development; however, their validation and characterization remain inadequate. One such gene is the single-stranded DNA-binding protein 3 (SSBP3) and its Drosophila melanogaster ortholog is called sequence-specific single-stranded DNA-binding protein (Ssdp). Here, we investigated consequences of Ssdp manipulations on neurodevelopment, gene expression, physiological function, and autism-associated behaviors using Drosophila models. We found that SSBP3 and Ssdp are expressed in excitatory neurons in the brain. Ssdp overexpression caused morphological alterations in Drosophila wing, mechanosensory bristles, and head. Ssdp manipulations also affected the neuropil brain volume and glial cell number in larvae and adult flies. Moreover, Ssdp overexpression led to differential changes in synaptic density in specific brain regions. We observed decreased levels of armadillo in the heads of Ssdp overexpressing flies, as well as a decrease in armadillo and wingless expression in the larval wing discs, implicating the involvement of the canonical Wnt signaling pathway in Ssdp functionality. RNA sequencing revealed perturbation of oxidative stress-related pathways in heads of Ssdp overexpressing flies. Furthermore, Ssdp overexpressing brains showed enhanced reactive oxygen species (ROS), altered neuronal mitochondrial morphology, and up-regulated fission and fusion genes. Flies with elevated levels of Ssdp exhibited heightened anxiety-like behavior, altered decisiveness, defective sensory perception and habituation, abnormal social interaction, and feeding defects, which were phenocopied in the pan-neuronal Ssdp knockdown flies, suggesting that Ssdp is dosage sensitive. Partial rescue of behavioral defects was observed upon normalization of Ssdp levels. Notably, Ssdp knockdown exclusively in adult flies did not produce behavioral and functional defects. Finally, we show that optogenetic manipulation of Ssdp-expressing neurons altered autism-associated behaviors. Collectively, our findings provide evidence that Ssdp, a dosage-sensitive gene in the 1p32.3 chromosomal region, is associated with various anatomical, physiological, and behavioral defects, which may be relevant to neurodevelopmental disorders like autism. Our study proposes SSBP3 as a critical gene in the 1p32.3 microdeletion/duplication genomic region and sheds light on the functional role of Ssdp in neurodevelopmental processes in Drosophila.

Functional characterization of human genomic variation linked to polygenic diseases

The burden of human disease lies predominantly in polygenic diseases. Since the early 2000s, genome-wide association studies (GWAS) have identified genetic variants and loci associated with complex traits. These have ranged from variants in coding sequences to mutations in regulatory regions, such as promoters and enhancers, as well as mutations affecting mediators of mRNA stability and other downstream regulators, such as 5' and 3'-untranslated regions (UTRs), long noncoding RNA (lncRNA), and miRNA. Recent research advances in genetics have utilized a combination of computational techniques, high-throughput in vitro and in vivo screening modalities, and precise genome editing to impute the function of diverse classes of genetic variants identified through GWAS. In this review, we highlight the vastness of genomic variants associated with polygenic disease risk and address recent advances in how genetic tools can be used to functionally characterize them.

A crowdsourcing database for the copy-number variation of the Spanish population

BACKGROUND

Despite being a very common type of genetic variation, the distribution of copy-number variations (CNVs) in the population is still poorly understood. The knowledge of the genetic variability, especially at the level of the local population, is a critical factor for distinguishing pathogenic from non-pathogenic variation in the discovery of new disease variants.

RESULTS

Here, we present the SPAnish Copy Number Alterations Collaborative Server (SPACNACS), which currently contains copy number variation profiles obtained from more than 400 genomes and exomes of unrelated Spanish individuals. By means of a collaborative crowdsourcing effort whole genome and whole exome sequencing data, produced by local genomic projects and for other purposes, is continuously collected. Once checked both, the Spanish ancestry and the lack of kinship with other individuals in the SPACNACS, the CNVs are inferred for these sequences and they are used to populate the database. A web interface allows querying the database with different filters that include ICD10 upper categories. This allows discarding samples from the disease under study and obtaining pseudo-control CNV profiles from the local population. We also show here additional studies on the local impact of CNVs in some phenotypes and on pharmacogenomic variants. SPACNACS can be accessed at: http://csvs.clinbioinfosspa.es/spacnacs/ .

CONCLUSION

SPACNACS facilitates disease gene discovery by providing detailed information of the local variability of the population and exemplifies how to reuse genomic data produced for other purposes to build a local reference database.

Copy Number Variation and Structural Genomic Findings in 116 Cases of Sudden Unexplained Death between 1 and 28 Months of Age

In sudden unexplained death in pediatrics (SUDP) the cause of death is unknown despite an autopsy and investigation. The role of copy number variations (CNVs) in SUDP has not been well-studied. Chromosomal microarray (CMA) data are generated for 116 SUDP cases with age at death between 1 and 28 months. CNVs are classified using the American College of Medical Genetics and Genomics guidelines and CNVs in our cohort are compared to an autism spectrum disorder (ASD) cohort, and to a control cohort. Pathogenic CNVs are identified in 5 of 116 cases (4.3%). Variants of uncertain significance (VUS) favoring pathogenic CNVs are identified in 9 cases (7.8%). Several CNVs are associated with neurodevelopmental phenotypes including seizures, ASD, developmental delay, and schizophrenia. The structural variant 47,XXY is identified in two cases (2/69 boys, 2.9%) not previously diagnosed with Klinefelter syndrome. Pathogenicity scores for deletions are significantly elevated in the SUDP cohort versus controls (p = 0.007) and are not significantly different from the ASD cohort. The finding of pathogenic or VUS favoring pathogenic CNVs, or structural variants, in 12.1% of cases, combined with the observation of higher pathogenicity scores for deletions in SUDP versus controls, suggests that CMA should be included in the genetic evaluation of SUDP.

Genome-wide association studies for thyroid physiology and diseases

Genetic factors are involved in the etiology of most diseases, but prior to 2000, the methods for identifying such factors were very limited. Genome-wide association study (GWAS), developed in the 2000s, is an analytical method that can be applied to most diseases, including endocrine disorders. GWAS has provided a wealth of information on disease risks and the molecular pathogenesis of many human diseases. This review summarizes key findings from GWAS for thyroid physiology and diseases, and illustrates how GWAS is a powerful research tool to elucidate the molecular mechanisms of the diseases.

Frequent copy number variants in a cohort of Mexican-Mestizo individuals

BACKGROUND

The human genome presents variation at distinct levels, copy number variants (CNVs) are DNA segments of variable lengths that range from several base pairs to megabases and are present at a variable number of copies in human genomes. Common CNVs have no apparent influence on the phenotype; however, some rare CNVs have been associated with phenotypic traits, depending on their size and gene content. CNVs are detected by microarrays of different densities and are generally visualized, and their frequencies analysed using the HapMap as default reference population. Nevertheless, this default reference is inadequate when the samples analysed are from people from Mexico, since population with a Hispanic genetic background are minimally represented. In this work, we describe the variation in the frequencies of four common CNVs in Mexican-Mestizo individuals.

RESULTS

In a cohort of 147 unrelated Mexican-Mestizo individuals, we found that the common CNVs 2p11.2 (99.6%), 8p11.22 (54.5%), 14q32.33 (100%), and 15q11.2 (71.1%) appeared with unexpectedly high frequencies when contrasted with the HapMap reference (ChAS). Yet, while when comparing to an ethnically related reference population, these differences were significantly reduced or even disappeared.

CONCLUSION

The findings in this work contribute to (1) a better description of the CNVs characteristics of the Mexican Mestizo population and enhance the knowledge of genome variation in different ethnic groups. (2) emphasize the importance of contrasting CNVs identified in studied individuals against a reference group that-as best as possible-share the same ethnicity while keeping this relevant information in mind when conducting CNV studies at the population or clinical level.

The missing link between genetic association and regulatory function

The genetic basis of most traits is highly polygenic and dominated by non-coding alleles. It is widely assumed that such alleles exert small regulatory effects on the expression of cis-linked genes. However, despite the availability of gene expression and epigenomic datasets, few variant-to-gene links have emerged. It is unclear whether these sparse results are due to limitations in available data and methods, or to deficiencies in the underlying assumed model. To better distinguish between these possibilities, we identified 220 gene-trait pairs in which protein-coding variants influence a complex trait or its Mendelian cognate. Despite the presence of expression quantitative trait loci near most GWAS associations, by applying a gene-based approach we found limited evidence that the baseline expression of trait-related genes explains GWAS associations, whether using colocalization methods (8% of genes implicated), transcription-wide association (2% of genes implicated), or a combination of regulatory annotations and distance (4% of genes implicated). These results contradict the hypothesis that most complex trait-associated variants coincide with homeostatic expression QTLs, suggesting that better models are needed. The field must confront this deficit and pursue this 'missing regulation.'

APOBEC3A /B deletion polymorphism and endometrial cancer risk

BACKGROUND

A common 30 kb deletion affecting the APOBEC3A and APOBEC3B genes has been linked to increased APOBEC activity and APOBEC-related mutational signatures in human cancers. The role of this deletion as a cancer risk factor remains controversial.

MATERIALS AND METHODS

We genotyped the APOBEC3A/B deletion in a sample of 1,470 Norwegian endometrial cancer cases and compared to 1,918 healthy controls. For assessment across Caucasian populations, we mined genotypes of the SNP rs12628403, which is in strong linkage disequilibrium with the deletion, in a GWAS dataset of 4,274 cases and 18,125 healthy controls, through the ECAC consortium.

RESULTS

We found the APOBEC3A/B deletion variant to be significantly associated with reduced risk of endometrial cancer among Norwegian women (OR = 0.75; 95% CI = 0.62-0.91; p = 0.003; dominant model). Similar results were found in the subgroup of endometrioid endometrial cancer (OR = 0.64; 95% CI = 0.51-0.79; p = 3.6 × 10^-5 ; dominant model). The observed risk reduction was particularly strong among individuals in the range of 50-60 years of age (OR = 0.51; 95% CI = 0.33-0.78; p = 0.002; dominant model). In the different populations included in the ECAC dataset, the ORs varied from 0.85 to 1.05. Although five out of six populations revealed ORs <1.0, the overall estimate was nonsignificant and, as such, did not formally validate the findings in the Norwegian cohort.

CONCLUSION

The APOBEC3A/B deletion polymorphism is associated with a decreased risk of endometrial cancer in the Norwegian population.

Copy Number Variants Are Ovarian Cancer Risk Alleles at Known and Novel Risk Loci

BACKGROUND

Known risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort.

METHODS

Single nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer-related cell types.

RESULTS

We identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types.

CONCLUSIONS

CNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.

The missing heritability in type 1 diabetes

Type 1 diabetes (T1D) is a complex autoimmune disease characterized by an absolute deficiency of insulin. It affects more than 20 million people worldwide and imposes an enormous financial burden on patients. The underlying pathogenic mechanisms of T1D are still obscure, but it is widely accepted that both genetics and the environment play an important role in its onset and development. Previous studies have identified more than 60 susceptible loci associated with T1D, explaining approximately 80%-85% of the heritability. However, most identified variants confer only small increases in risk, which restricts their potential clinical application. In addition, there is still a so-called 'missing heritability' phenomenon. While the gap between known heritability and true heritability in T1D is small compared with that in other complex traits and disorders, further elucidation of T1D genetics has the potential to bring novel insights into its aetiology and provide new therapeutic targets. Many hypotheses have been proposed to explain the missing heritability, including variants remaining to be found (variants with small effect sizes, rare variants and structural variants) and interactions (gene-gene and gene-environment interactions; e.g. epigenetic effects). In the following review, we introduce the possible sources of missing heritability and discuss the existing related knowledge in the context of T1D.

Investigating immunoregulatory effects of myeloid cell autophagy in acute and chronic inflammation

Studies have highlighted a critical role for autophagy in the regulation of multiple cytokines. Autophagy inhibits the release of interleukin (IL)‐1 family cytokines, including IL‐1α, IL‐1β and IL‐18, by myeloid cells. This, in turn, impacts the release of other cytokines by myeloid cells, as well as other cells of the immune system, including IL‐22, IL‐23, IL‐17 and interferon‐γ. Here, we assessed the impact of genetic depletion of the autophagy gene Atg7 in myeloid cells on acute and chronic inflammation. In a model of acute lipopolysaccharide‐induced endotoxemia, loss of autophagy in myeloid cells resulted in increased release of proinflammatory cytokines, both locally and systemically. By contrast, loss of Atg7 in myeloid cells in the Lyn^−/− model of lupus‐like autoimmunity resulted in reduced systemic release of IL‐6 and IL‐10, with no effects on other cytokines observed. In addition, Lyn^−/− mice with autophagy‐deficient myeloid cells showed reduced expression of autoantibodies relevant to systemic lupus erythematosus, including anti‐histone and anti‐Smith protein. In vitro, loss of autophagy, through pharmacological inhibition or small interfering RNA against Becn1, inhibited IL‐10 release by human and mouse myeloid cells. This effect was evident at the level of Il10 messenger RNA expression. Our data highlight potentially important differences in the role of myeloid cell autophagy in acute and chronic inflammation and demonstrate a direct role for autophagy in the production and release of IL‐10 by macrophages.

Novel copy number variations within SYCE1 caused meiotic arrest and non-obstructive azoospermia

Background

Non-obstructive azoospermia (NOA) is the most severe disease in male infertility, but the genetic causes for majority of NOA remain unknown.

Methods

Two Chinese NOA-affected patients were recruited to identify the genetic causal factor of infertility. Whole-exome sequencing (WES) was conducted in the two patients with NOA. Sanger sequencing and CNV array were used to ascertain the WES results. Hematoxylin and eosin (H&E) staining and immunofluorescence (IF) were carried out to evaluate the stage of spermatogenesis arrested in the affected cases.

Results

Novel heterozygous deletion (LOH) within SYCE1 (seq[GRCh37] del(10)(10q26.3)chr10:g.135111754_135427143del) and heterozygous loss of function (LoF) variant in SYCE1 (NM_001143763: c.689_690 del:p.F230fs) were identified in one NOA-affected patient. While homozygous deletion within SYCE1 (seq[GRCh37] del(10)(10q26.3)chr10:g.135340247_135379115del) was detected in the other patient with meiotic arrest. H&E and IF staining demonstrated that the spermatogenesis was arrested at pachytene stage in the two patients with NOA, suggesting these two novel CNVs within SYCE1 could lead to meiotic defect and NOA.

Conclusions

We identified that two novel CNVs within SYCE1 are associated with meiotic arrest and male infertility. Thus, our study expands the knowledge of variants in SYCE1 and provides a new insight to understand the genetic etiologies of NOA.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01288-8.

Can adult polygenic scores improve prediction of body mass index in childhood?

BACKGROUND/OBJECTIVES

Modelling genetic pre-disposition may identify children at risk of obesity. However, most polygenic scores (PGSs) have been derived in adults, and lack validation during childhood. This study compared the utility of existing large-scale adult-derived PGSs to predict common anthropometric traits (body mass index (BMI), waist circumference, and body fat) in children and adults, and examined whether childhood BMI prediction could be improved by combining PGSs and non-genetic factors (maternal and earlier child BMI).

SUBJECTS/METHODS

Participants (n = 1365 children, and n = 2094 adults made up of their parents) were drawn from the Longitudinal Study of Australian Children. Children were weighed and measured every two years from 0-1 to 12-13 years, and adults were measured or self-reported measurements were obtained concurrently (average analysed). Participants were genotyped from blood or oral samples, and PGSs were derived based on published genome-wide association studies. We used linear regression to compare the relative utility of these PGSs to predict their respective traits at different ages.

RESULTS

BMI PGSs explained up to 12% of child BMI z-score variance in 10-13 year olds, compared with up to 15% in adults. PGSs for waist circumference and body fat explained less variance (up to 8%). An interaction between BMI PGSs and puberty (p = 0.001-0.002) suggests the effect of some variants may differ across the life course. Individual BMI measures across childhood predicted 10-60% of the variance in BMI at 12-13 years, and maternal BMI and BMI PGS each added 1-9% above this.

CONCLUSION

Adult-derived PGSs for BMI, particularly those derived by modelling between-variant interactions, may be useful for predicting BMI during adolescence with similar accuracy to that obtained in adulthood. The level of precision presented here to predict BMI during childhood may be relevant to public health, but is likely to be less useful for individual clinical purposes.

The individual and global impact of copy-number variants on complex human traits

The impact of copy-number variations (CNVs) on complex human traits remains understudied. We called CNVs in 331,522 UK Biobank participants and performed genome-wide association studies (GWASs) between the copy number of CNV-proxy probes and 57 continuous traits, revealing 131 signals spanning 47 phenotypes. Our analysis recapitulated well-known associations (e.g., 1q21 and height), revealed the pleiotropy of recurrent CNVs (e.g., 26 and 16 traits for 16p11.2-BP4-BP5 and 22q11.21, respectively), and suggested gene functionalities (e.g., MARF1 in female reproduction). Forty-eight CNV signals (38%) overlapped with single-nucleotide polymorphism (SNP)-GWASs signals for the same trait. For instance, deletion of PDZK1, which encodes a urate transporter scaffold protein, decreased serum urate levels, while deletion of RHD, which encodes the Rhesus blood group D antigen, associated with hematological traits. Other signals overlapped Mendelian disorder regions, suggesting variable expressivity and broad impact of these loci, as illustrated by signals mapping to Rotor syndrome (SLCO1B1/3), renal cysts and diabetes syndrome (HNF1B), or Charcot-Marie-Tooth (PMP22) loci. Total CNV burden negatively impacted 35 traits, leading to increased adiposity, liver/kidney damage, and decreased intelligence and physical capacity. Thirty traits remained burden associated after correcting for CNV-GWAS signals, pointing to a polygenic CNV architecture. The burden negatively correlated with socio-economic indicators, parental lifespan, and age (survivorship proxy), suggesting a contribution to decreased longevity. Together, our results showcase how studying CNVs can expand biological insights, emphasizing the critical role of this mutational class in shaping human traits and arguing in favor of a continuum between Mendelian and complex diseases.

Admixture Mapping of Sepsis in European Individuals With African Ancestries

Sepsis is a severe systemic inflammatory response to infections that is accompanied by organ dysfunction. Although the ancestral genetic background is a relevant factor for sepsis susceptibility, there is a lack of studies using the genetic singularities of a recently admixed population to identify loci involved in sepsis susceptibility. Here we aimed to discover new sepsis loci by completing the first admixture mapping study of sepsis in Canary Islanders, leveraging their distinctive genetic makeup as a mixture of Europeans and African ancestries. We used a case-control approach and inferred local ancestry blocks from genome-wide data from 113,414 polymorphisms genotyped in 343 patients with sepsis and 410 unrelated controls, all ascertained for grandparental origin in the Canary Islands (Spain). Deviations in local ancestries between cases and controls were tested using logistic regressions, followed by fine-mapping analyses based on imputed genotypes, in silico functional assessments, and gene expression analysis centered on the region of interest. The admixture mapping analysis detected that local European ancestry in a locus spanning 1.2 megabases of chromosome 8p23.1 was associated with sepsis (lowest p = 1.37 × 10⁻⁴; Odds Ratio [OR] = 0.51; 95%CI = 0.40–0.66). Fine-mapping studies prioritized the variant rs13249564 within intron 1 of MFHAS1 gene associated with sepsis (p = 9.94 × 10⁻⁴; OR = 0.65; 95%CI = 0.50–0.84). Functional and gene expression analyses focused on 8p23.1 allowed us to identify alternative genes with possible biological plausibility such as defensins, which are well-known effector molecules of innate immunity. By completing the first admixture mapping study of sepsis, our results revealed a new genetic locus (8p23.1) harboring a number of genes with plausible implications in sepsis susceptibility.

Positive selection acts on regulatory genetic variants in populations of European ancestry that affect ALDH2 gene expression

ALDH2 is a key enzyme in alcohol metabolism that protects cells from acetaldehyde toxicity. Using iHS, iSAFE and FST statistics, we identified regulatory acting variants affecting ALDH2 gene expression under positive selection in populations of European ancestry. Several SNPs (rs3184504, rs4766578, rs10774625, rs597808, rs653178, rs847892, rs2013002) that function as eQTLs for ALDH2 in various tissues showed evidence of strong positive selection. Very large pairwise FST values indicated high genetic differentiation at these loci between populations of European ancestry and populations of other global ancestries. Estimating the timing of positive selection on the beneficial alleles suggests that these variants were recently adapted approximately 3000-3700 years ago. The derived beneficial alleles are in complete linkage disequilibrium with the derived ALDH2 promoter variant rs886205, which is associated with higher transcriptional activity. The SNPs rs4766578 and rs847892 are located in binding sequences for the transcription factor HNF4A, which is an important regulatory element of ALDH2 gene expression. In contrast to the missense variant ALDH2 rs671 (ALDH2*2), which is common only in East Asian populations and is associated with greatly reduced enzyme activity and alcohol intolerance, the beneficial alleles of the regulatory variants identified in this study are associated with increased expression of ALDH2. This suggests adaptation of Europeans to higher alcohol consumption.

Speeding up Monte Carlo simulations for the adaptive sum of powered score test with importance sampling

A central but challenging problem in genetic studies is to test for (usually weak) associations between a complex trait (e.g., a disease status) and sets of multiple genetic variants. Due to the lack of a uniformly most powerful test, data-adaptive tests, such as the adaptive sum of powered score (aSPU) test, are advantageous in maintaining high power against a wide range of alternatives. However, there is often no closed-form to accurately and analytically calculate the p-values of many adaptive tests like aSPU, thus Monte Carlo (MC) simulations are often used, which can be time consuming to achieve a stringent significance level (e.g., 5e-8) used in genome-wide association studies (GWAS). To estimate such a small p-value, we need a huge number of MC simulations (e.g., 1e+10). As an alternative, we propose using importance sampling to speed up such calculations. We develop some theory to motivate a proposed algorithm for the aSPU test, and show that the proposed method is computationally more efficient than the standard MC simulations. Using both simulated and real data, we demonstrate the superior performance of the new method over the standard MC simulations.

Drug repurposing for rheumatoid arthritis: Identification of new drug candidates via bioinformatics and text mining analysis

Rheumatoid arthritis (RA) is an autoimmune disease that results in the destruction of tissue by attacks on the patient by his or her own immune system. Current treatment strategies are not sufficient to overcome RA. In the present study, various transcriptomic data from synovial fluids, synovial fluid-derived macrophages, and blood samples from patients with RA were analysed using bioinformatics approaches to identify tissue-specific repurposing drug candidates for RA. Differentially expressed genes (DEGs) were identified by integrating datasets for each tissue and comparing diseased to healthy samples. Tissue-specific protein-protein interaction (PPI) networks were generated and topologically prominent proteins were selected. Transcription-regulating biomolecules for each tissue type were determined from protein-DNA interaction data. Common DEGs and reporter biomolecules were used to identify drug candidates for repurposing using the hypergeometric test. As a result of bioinformatic analyses, 19 drugs were identified as repurposing candidates for RA, and text mining analyses supported our findings. We hypothesize that the FDA-approved drugs momelotinib, ibrutinib, and sodium butyrate may be promising candidates for RA. In addition, CHEMBL306380, Compound 19a (CHEMBL3116050), ME-344, XL-019, TG100801, JNJ-26483327, and NV-128 were identified as novel repurposing candidates for the treatment of RA. Preclinical and further validation of these drugs may provide new treatment options for RA.

An Update Evolving View of Copy Number Variations in Autoimmune Diseases

Autoimmune diseases (AIDs) usually share possible common mechanisms, i.e., a defect in the immune tolerance exists due to diverse causes from central and peripheral tolerance mechanisms. Some genetic variations including copy number variations (CNVs) are known to link to several AIDs and are of importance in the susceptibility to AIDs and the potential therapeutic responses to medicines. As an important source of genetic variants, DNA CNVs have been shown to be very common in AIDs, implying these AIDs may possess possible common mechanisms. In addition, some CNVs are differently distributed in various diseases in different ethnic populations, suggesting that AIDs may have their own different phenotypes and different genetic and/or environmental backgrounds among diverse populations. Due to the continuous advancement in genotyping technology, such as high-throughput whole-genome sequencing method, more susceptible variants have been found. Moreover, further replication studies should be conducted to confirm the results of studies with different ethnic cohorts and independent populations. In this review, we aim to summarize the most relevant data that emerged in the past few decades on the relationship of CNVs and AIDs and gain some new insights into the issue.

Genome-wide analysis of copy number variants and normal facial variation in a large cohort of Bantu Africans

Similarity in facial characteristics between relatives suggests a strong genetic component underlies facial variation. While there have been numerous studies of the genetics of facial abnormalities and, more recently, single nucleotide polymorphism (SNP) genome-wide association studies (GWASs) of normal facial variation, little is known about the role of genetic structural variation in determining facial shape. In a sample of Bantu African children, we found that only 9% of common copy number variants (CNVs) and 10-kb CNV analysis windows are well tagged by SNPs (r2 ≥ 0.8), indicating that associations with our internally called CNVs were not captured by previous SNP-based GWASs. Here, we present a GWAS and gene set analysis of the relationship between normal facial variation and CNVs in a sample of Bantu African children. We report the top five regions, which had p values ≤ 9.35 × 10-6 and find nominal evidence of independent CNV association (p < 0.05) in three regions previously identified in SNP-based GWASs. The CNV region with strongest association (p = 1.16 × 10-6, 55 losses and seven gains) contains NFATC1, which has been linked to facial morphogenesis and Cherubism, a syndrome involving abnormal lower facial development. Genomic loss in the region is associated with smaller average lower facial depth. Importantly, new loci identified here were not identified in a SNP-based GWAS, suggesting that CNVs are likely involved in determining facial shape variation. Given the plethora of SNP-based GWASs, calling CNVs from existing data may be a relatively inexpensive way to aid in the study of complex traits.

Homoeologous chromosome exchange explains the creation of a QTL affecting soil-borne pathogen resistance in tobacco

Crop plant partial resistance to plant pathogens controlled by quantitative trait loci (QTL) is desirable in cultivar development programmes because of its increased durability. Mechanisms underlying such resistance are difficult to study. We performed RNA-seq analyses for tobacco (Nicotiana tabacum) nearly isogenic lines (NILs) with and without favourable allele(s) at Phn7.1, a major QTL influencing partial resistance to the soil-borne pathogens Phytophthora nicotianae and Ralstonia solanacearum. Based upon combined analyses of transcriptome-based sequence variation and gene expression profiles, we concluded that allelic variability at the Phn7.1 locus was likely generated from homoeologous exchange, which led to deletion of low-expressing members of the SAR8.2 gene family and duplication of high-expressing SAR8.2 genes from a different subgenome of allotetraploid tobacco. The high expression of endogenous Phn7.1-associated SAR8.2 genes was correlated with observed resistance to P. nicotianae. Our findings suggest a role for genomic rearrangements in the generation of favourable genetic variability affecting resistance to pathogens in plants.

Low-frequency somatic copy number alterations in normal human lymphocytes revealed by large-scale single-cell whole-genome profiling

Genomic-scale somatic copy number alterations in healthy humans are difficult to investigate because of low occurrence rates and the structural variations’ stochastic natures. Using a Tn5-transposase-assisted single-cell whole-genome sequencing method, we sequenced over 20,000 single lymphocytes from 16 individuals. Then, with the scale increased to a few thousand single cells per individual, we found that about 7.5% of the cells had large-size copy number alterations. Trisomy 21 was the most prevalent aneuploid event among all autosomal copy number alterations, whereas monosomy X occurred most frequently in over-30-yr-old females. In the monosomy X single cells from individuals with phased genomes and identified X-inactivation ratios in bulk, the inactive X Chromosomes were lost more often than the active ones.

Mutational bias in spermatogonia impacts the anatomy of regulatory sites in the human genome

Mutation in the germline is the ultimate source of genetic variation, but little is known about the influence of germline chromatin structure on mutational processes. Using ATAC-seq, we profile the open chromatin landscape of human spermatogonia, the most proliferative cell type of the germline, identifying transcription factor binding sites (TFBSs) and PRDM9 binding sites, a subset of which will initiate meiotic recombination. We observe an increase in rare structural variant (SV) breakpoints at PRDM9-bound sites, implicating meiotic recombination in the generation of structural variation. Many germline TFBSs, such as NRF1, are also associated with increased rates of SV breakpoints, apparently independent of recombination. Singleton short insertions (≥5 bp) are highly enriched at TFBSs, particularly at sites bound by testis active TFs, and their rates correlate with those of structural variant breakpoints. Short insertions often duplicate the TFBS motif, leading to clustering of motif sites near regulatory regions in this male-driven evolutionary process. Increased mutation loads at germline TFBSs disproportionately affect neural enhancers with activity in spermatogonia, potentially altering neurodevelopmental regulatory architecture. Local chromatin structure in spermatogonia is thus pervasive in shaping both evolution and disease.

GWAS for genetics of complex quantitative traits: Genome to pangenome and SNPs to SVs and k-mers

The development of improved methods for genome-wide association studies (GWAS) for genetics of quantitative traits has been an active area of research during the last 25 years. This activity initially started with the use of mixed linear model (MLM), which was variously modified. During the last decade, however, with the availability of high throughput next generation sequencing (NGS) technology, development and use of pangenomes and novel markers including structural variations (SVs) and k-mers for GWAS has taken over as a new thrust area of research. Pangenomes and SVs are now available in humans, livestock, and a number of plant species, so that these resources along with k-mers are being used in GWAS for exploring additional genetic variation that was hitherto not available for analysis. These developments have resulted in significant improvement in GWAS methodology for detection of marker-trait associations (MTAs) that are relevant to human healthcare and crop improvement.

Integrative analysis of prognostic long non-coding RNAs with copy number variation in bladder cancer

Copy number variations (CNVs), which can affect the role of long non-coding RNAs (lncRNAs), are important genetic changes seen in some malignant tumors. We analyzed lncRNAs with CNV to explore the relationship between lncRNAs and prognosis in bladder cancer (BLCA). Messenger RNA (mRNA) expression levels, DNA methylation, and DNA copy number data of 408 BLCA patients were subjected to integrative bioinformatics analysis. Cluster analysis was performed to obtain different subtypes and differently expressed lncRNAs and coding genes. Weighted gene co-expression network analysis (WGCNA) was performed to identify the co-expression gene and lncRNA modules. CNV-associated lncRNA data and their influence on cancer prognosis were assessed with Kaplan-Meier survival curve. Multi-omics integration analysis revealed five prognostic lncRNAs with CNV, namely NR2F1-AS1, LINC01138, THUMPD3-AS1, LOC101928489,and TMEM147-AS1,and a risk-score signature related to overall survival in BLCA was identified. Moreover, validated results in another independent Gene Expression Omnibus (GEO) dataset, GSE31684, were consistent with these results. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that the mitogen-activated protein kinase (MAPK) signaling pathway, focal adhesion pathway, and Janus kinase-signal transducers and activators of transcription (JAK-STAT) signaling pathway were enriched in a high-risk score pattern, suggesting that imbalance in these pathways is closely related to tumor development. We revealed the prognosis-related lncRNAs by analyzing the expression profiles of lncRNAs and CNVs, which can be used as prognostic biomarkers for BLCA.

Signatures of TSPAN8 variants associated with human metabolic regulation and diseases

Here, with the example of common copy number variation (CNV) in the TSPAN8 gene, we present an important piece of work in the field of CNV detection, that is, CNV association with complex human traits such as ¹H NMR metabolomic phenotypes and an example of functional characterization of CNVs among human induced pluripotent stem cells (HipSci). We report TSPAN8 exon 11 (ENSE00003720745) as a pleiotropic locus associated with metabolomic regulation and show that its biology is associated with several metabolic diseases such as type 2 diabetes (T2D) and cancer. Our results further demonstrate the power of multivariate association models over univariate methods and define metabolomic signatures for variants in TSPAN8.

Characterization of intermediate-sized insertions using whole-genome sequencing data and analysis of their functional impact on gene expression

Intermediate-sized insertions are one of the structural variants contributing to genome diversity. However, due to technical difficulties in identifying them, their importance in disease pathogenicity and gene expression regulation remains unclear. We used whole-genome sequencing data of 174 Japanese samples to characterize intermediate-sized insertions using a highly-accurate insertion calling method (IMSindel software and joint-call recovery) and obtained a catalogue of 4254 insertions. We constructed an imputation panel comprising of insertions and SNVs from all samples, and conducted imputation of intermediate-sized insertions for 82 publicly-available Japanese samples. Positive Predictive Value of imputation, evaluated using Nanopore long-read sequencing data, was 97%. Subsequent eQTL analysis predicted 128 (~ 3.0%) insertions as causative for gene expression level changes. Enrichment analysis of causal insertions for genome regulatory elements showed significant associations with CTCF-binding sites, super-enhancers, and promoters. Among 17 causal insertions found in the same causal set with GWAS hits, there were insertions associated with changes in expression of cancer-related genes such as BRCA1, ZNF222, and ABCB10. Analysis of insertions sequences revealed that 461 insertions were short tandem duplications frequently found in early-replicating regions of genome. Furthermore, comparison of functional importance of intermediate-sized insertions with that of intermediate-sized deletions detected in the same sample set in our previous study showed that insertions were more frequent in genic regions, and proportion of functional candidates was smaller in insertions. Here, we characterize a high-confidence set of intermediate-sized insertions and indicate their importance in gene expression regulation. Our results emphasize the importance of considering intermediate-sized insertions in trait association studies.

Copy number variation underlies complex phenotypes in domestic dog breeds and other canids

Extreme phenotypic diversity, a history of artificial selection, and socioeconomic value make domestic dog breeds a compelling subject for genomic research. Copy number variation (CNV) is known to account for a significant part of inter-individual genomic diversity in other systems. However, a comprehensive genome-wide study of structural variation as it relates to breed-specific phenotypes is lacking. We have generated whole genome CNV maps for more than 300 canids. Our data set extends the canine structural variation landscape to more than 100 dog breeds, including novel variants that cannot be assessed using microarray technologies. We have taken advantage of this data set to perform the first CNV-based genome-wide association study (GWAS) in canids. We identify 96 loci that display copy number differences across breeds, which are statistically associated with a previously compiled set of breed-specific morphometrics and disease susceptibilities. Among these, we highlight the discovery of a long-range interaction involving a CNV near MED13L and TBX3, which could influence breed standard height. Integration of the CNVs with chromatin interactions, long noncoding RNA expression, and single nucleotide variation highlights a subset of specific loci and genes with potential functional relevance and the prospect to explain trait variation between dog breeds.

Increased Gene Copy Number of DEFA1A3 Is Associated With the Severity of Ulcerative Colitis

INTRODUCTION

DEFA1A3 encodes human neutrophil peptides (HNPs) 1-3 and has multiple copy number variations (CNVs). HNPs are associated with innate immunity. Ulcerative colitis (UC), a chronic inflammatory gastrointestinal disorder, is a life-threatening condition, and predictive markers of UC severity are needed. This study investigated the relationship between DEFA1A3 CNV and UC severity.

METHODS

This study enrolled 165 patients with UC. The relationship between DEFA1A3 CNV and disease severity was analyzed based on Mayo score, patient characteristics, and treatment methods. In addition, serum and stimulated neutrophil-derived HNP concentrations were also measured in patients with high and low DEFA1A3 CNV.

RESULTS

DEFA1A3 CNV was significantly correlated with Mayo score and white blood cell count (R = 0.46, P < 0.0001; R = 0.29, P = 0.003, respectively), and only high copy numbers of DEFA1A3 were independent factors for severe UC (P < 0.001, odds ratio: 1.88, 95% confidence interval, 1.34-2.61). The number of severe UC patients with high DEFA1A3 CNV was significantly greater than those with low CNV. We confirmed the associations between DEFA1A3 and UC severity using a validation cohort. In addition, the HNP concentration in high-copy number patients was significantly higher after neutrophil stimulation than that in low-copy number patients.

DISCUSSION

This study demonstrated that there is a correlation between DEFA1A3 copy number and severity in patients with UC. In addition, neutrophils from UC patients with higher DEFA1A3 CNV had high reactivity of secretion of HNPs after stimulation. DEFA1A3 CNV may be a novel severity marker and a potential therapeutic target for UC.

Association of structural variation with cardiometabolic traits in Finns

The contribution of genome structural variation (SV) to quantitative traits associated with cardiometabolic diseases remains largely unknown. Here, we present the results of a study examining genetic association between SVs and cardiometabolic traits in the Finnish population. We used sensitive methods to identify and genotype 129,166 high-confidence SVs from deep whole-genome sequencing (WGS) data of 4,848 individuals. We tested the 64,572 common and low-frequency SVs for association with 116 quantitative traits and tested candidate associations using exome sequencing and array genotype data from an additional 15,205 individuals. We discovered 31 genome-wide significant associations at 15 loci, including 2 loci at which SVs have strong phenotypic effects: (1) a deletion of the ALB promoter that is greatly enriched in the Finnish population and causes decreased serum albumin level in carriers (p = 1.47 × 10-54) and is also associated with increased levels of total cholesterol (p = 1.22 × 10-28) and 14 additional cholesterol-related traits, and (2) a multi-allelic copy number variant (CNV) at PDPR that is strongly associated with pyruvate (p = 4.81 × 10-21) and alanine (p = 6.14 × 10-12) levels and resides within a structurally complex genomic region that has accumulated many rearrangements over evolutionary time. We also confirmed six previously reported associations, including five led by stronger signals in single nucleotide variants (SNVs) and one linking recurrent HP gene deletion and cholesterol levels (p = 6.24 × 10-10), which was also found to be strongly associated with increased glycoprotein level (p = 3.53 × 10-35). Our study confirms that integrating SVs in trait-mapping studies will expand our knowledge of genetic factors underlying disease risk.

The Autoantigen Repertoire and the Microbial RNP World

Although autoimmunity and autoimmune disease (AID) are relatively common, the repertoire of autoantigens is paradoxically very limited. Highly enriched in this autoantigen repertoire are nucleic acids and their binding proteins, which together form large macromolecular structures. Most of these complexes are of ancient evolutionary origin, with homologs throughout multiple kingdoms of life. Why and if these nucleic acid-protein particles drive the development of autoimmunity remains unresolved. Recent advances in our understanding of the microbiome may provide clues about the origins of autoimmunity - and the particular puzzle of why the autoantigen repertoire is so particularly enriched in ribonucleoprotein particles (RNPs). We discuss the possibility that autoimmunity to some RNPs may arise from molecular mimicry to microbial orthologs.

Genetic predictors of gene expression associated with psychiatric comorbidity in patients with inflammatory bowel disease - A pilot study

BACKGROUND

Inflammatory bowel disease (IBD) affects millions of people in North America, and patients with IBD have a high incidence of psychiatric comorbidities (PC). The genetic mechanisms underlying the link are, in general, poorly understood.

MATERIALS AND METHODS

A transcriptome-wide association study (TWAS) was performed using genetically regulated gene expression profiles imputed from the genetic profiles of 240 IBD patients in the Manitoba IBD Cohort Study. The imputation was performed using the 44 non-diseased human tissue-specific reference models from the GTEx database. Linear modeling and gene set enrichment analysis were performed to identify genes and pathways that are significantly associated with IBD patients with PC compared to IBD alone in each of the 44 non-diseased human tissues. Finally, an enrichment map was generated to investigate networks of the enriched gene sets associated with IBD patients with PC.

RESULTS

The genes RBPMS in skeletal muscle (adjusted p = 0.05), KCNA5 in the cerebellar hemisphere of the brain (adjusted p = 0.09), GSR, SMIM34A, and LIPT2 in the frontal cortex of the brain (adjusted p = 0.09 for each) were the top genetically regulated genes with a suggestive association with IBD patients with PC. We identified three gene set networks, which include gene sets and pathways with a suggestive association with IBD patients with PC: one with 7 gene sets overlapping in apolipoprotein B mRNA editing subunit genes, one with 3 gene sets including pigmentation gene sets, and the other one with 3 gene sets including peptidyl tyrosine phosphorylation regulation related gene sets.

CONCLUSIONS

Our TWAS analysis has identified genes and pathways with a suggestive association with IBD patients with PC. These findings can be potentially used for illustrating the mechanism of developing PC in the patients with IBD and developing diagnosis tool or drug targets for IBD patients with PC.

Short somatic alterations at the site of copy number variation in breast cancer

Copy number variation (CNV) is a polymorphism in the human genome involving DNA fragments larger than 1 kb. Copy number variation sites provide hotspots of somatic alterations in cancers. Herein, we examined somatic alterations at sites of CNV in DNA from 20 invasive breast cancers using a Comparative Genomic Hybridization array specifically designed to detect the genome-wide CNV status of approximately 412 000 sites. Somatic copy number alterations (CNAs) were detected in 39.9% of the CNV probes examined. The most frequently altered regions were gains of 1q21-22 (90%), 8q21-24 (85%), 1q44 (85%), and 3q11 (85%) or losses of 16q22-24 (80%). Gene ontology analyses of genes within the CNA fragments revealed that cascades related to transcription and RNA metabolism correlated significantly with human epidermal growth factor receptor 2 positivity and menopausal status. Thirteen of 20 tumors showed CNAs in more than 35% of sites examined and a high prevalence of CNAs correlated significantly with estrogen receptor (ER) negativity, higher nuclear grade (NG), and higher Ki-67 labeling index. Finally, when CNA fragments were categorized according to their size, CNAs smaller than 10 kb correlated significantly with ER positivity and lower NG, whereas CNAs exceeding 10 Mb correlated with higher NG, ER negativity, and a higher Ki-67 labeling index. Most of these findings were confirmed or supported by quantitative PCR of representative DNA fragments in 72 additional breast cancers. These results suggest that most CNAs are caused by gain or loss of large chromosomal fragments and correlate with NG and several malignant features, whereas solitary CNAs of less than 10 kb could be involved in ER-positive breast carcinogenesis.

Phylogenetic Methods for Genome-Wide Association Studies in Bacteria

Genome-wide association studies in bacteria have great potential to deliver a better understanding of the genetic basis of many biologically important phenotypes, including antibiotic resistance, pathogenicity, and host adaptation. Such studies need however to account for the specificities of bacterial genomics, especially in terms of population structure, homologous recombination, and genomic plasticity. A powerful way to tackle this challenge is to use a phylogenetic approach, which is based on long-standing methodology for the evolutionary analysis of bacterial genomic data. Here we present both the theoretical and practical aspects involved in the use of phylogenetic methods for bacterial genome-wide association studies.

The Future of Livestock Management: A Review of Real-Time Portable Sequencing Applied to Livestock

Oxford Nanopore Technologies' MinION has proven to be a valuable tool within human and microbial genetics. Its capacity to produce long reads in real time has opened up unique applications for portable sequencing. Examples include tracking the recent African swine fever outbreak in China and providing a diagnostic tool for disease in the cassava plant in Eastern Africa. Here we review the current applications of Oxford Nanopore sequencing in livestock, then focus on proposed applications in livestock agriculture for rapid diagnostics, base modification detection, reference genome assembly and genomic prediction. In particular, we propose a future application: 'crush-side genotyping' for real-time on-farm genotyping for extensive industries such as northern Australian beef production. An initial in silico experiment to assess the feasibility of crush-side genotyping demonstrated promising results. SNPs were called from simulated Nanopore data, that included the relatively high base call error rate that is characteristic of the data, and calling parameters were varied to understand the feasibility of SNP calling at low coverages in a heterozygous population. With optimised genotype calling parameters, over 85% of the 10,000 simulated SNPs were able to be correctly called with coverages as low as 6×. These results provide preliminary evidence that Oxford Nanopore sequencing has potential to be used for real-time SNP genotyping in extensive livestock operations.

Potpourri: An Epistasis Test Prioritization Algorithm via Diverse SNP Selection

Genome-wide association studies (GWAS) explain a fraction of the underlying heritability of genetic diseases. Investigating epistatic interactions between two or more loci help to close this gap. Unfortunately, the sheer number of loci combinations to process and hypotheses prohibit the process both computationally and statistically. Epistasis test prioritization algorithms rank likely epistatic single nucleotide polymorphism (SNP) pairs to limit the number of tests. However, they still suffer from very low precision. It was shown in the literature that selecting SNPs that are individually correlated with the phenotype and also diverse with respect to genomic location leads to better phenotype prediction due to genetic complementation. Here, we propose that an algorithm that pairs SNPs from such diverse regions and ranks them can improve prediction power. We propose an epistasis test prioritization algorithm that optimizes a submodular set function to select a diverse and complementary set of genomic regions that span the underlying genome. The SNP pairs from these regions are then further ranked w.r.t. their co-coverage of the case cohort. We compare our algorithm with the state of the art on three GWAS and show that (1) we substantially improve precision (from 0.003 to 0.652) while maintaining the significance of selected pairs, (2) decrease the number of tests by 25-fold, and (3) decrease the runtime by 4-fold. We also show that promoting SNPs from regulatory/coding regions improves the performance (up to 0.8). Potpourri is available at http:/ciceklab.cs.bilkent.edu.tr/potpourri.

The interesting relationship between APOBEC3 deoxycytidine deaminases and cancer: a long road ahead

Cancer is considered a group of diseases characterized by uncontrolled growth and spread of abnormal cells and is propelled by somatic mutations. Apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) family of enzymes are endogenous sources of somatic mutations found in multiple human cancers. While these enzymes normally act as an intrinsic immune defence against viruses, they can also catalyse 'off-target' cytidine deamination in genomic single-stranded DNA intermediates. The deamination of cytosine forms uracil, which is promutagenic in DNA. Key factors to trigger the APOBEC 'off-target' activity are overexpression in a non-normal cell type, nuclear localization and replication stress. The resulting uracil-induced mutations contribute to genomic variation, which may result in neutral, beneficial or harmful consequences for the cancer. This review summarizes the functional and biochemical basis of the APOBEC3 enzyme activity and highlights their relationship with the most well-studied cancers in this particular context such as breast, lung, bladder, and human papillomavirus-associated cancers. We focus on APOBEC3A, APOBEC3B and APOBEC3H haplotype I because they are the leading candidates as sources of somatic mutations in these and other cancers. Also, we discuss the prognostic value of the APOBEC3 expression in drug resistance and response to therapies.