Association analysis of the CCL3L1 copy number locus by paralogue ratio test in Norwegian rheumatoid arthritis patients and healthy controls

Identification of systemic biomarkers and potential drug targets for age-related macular degeneration

Purpose

Since age-related macular degeneration (AMD) is tightly associated with aging and cellular senescence, objective of this study was to investigate the association between plasma levels of senescence-related proteins (SRPs) and risk of AMD.

Design

The whole study was based on two-sample Mendelian randomization (MR) analysis.

Methods

For MR analysis, the primary approach for MR analysis was the inverse-variance weighted (IVW) method and the heterogeneity and pleiotropy of results were tested. The instrumental single-nucleotide polymorphisms (SNPs) associated with 110 SRPs were filtered and selected from a large genome-wide association study (GWAS) for plasma proteome involving 35,559 participants. The GWAS data of AMD was obtained from FinnGen consortium (6,157 AMD cases and 288,237 controls) and further validated by using data from UK Biobank consortium (3,553 AMD cases and 147,089 controls).

Results

The MR results at both discovery and validation stages supported the causality (IVW-P < 0.00045) between plasma levels of 4 SRPs (C3b, CTNNB1, CCL1, and CCL3L1) and the risk of AMD and supported potential causality (IVW-P < 0.05) between other 10 SRPs and risk of AMD. No heterogeneity or pleiotropy in these results was detected.

Conclusion

Our findings supported that high plasma levels of C3b, CTNNB1, CCL1, and CCL3L1 were associated with increased risk of AMD, thereby highlighting the role of systemic inflammation in AMD pathogenesis and providing the rationale for developing new preventative and therapeutic strategies.

Copy number variation of CCL3L1 among three major ethnic groups in Malaysia

Background

C-C motif Chemokine Ligand 3 Like 1 (CCL3L1) is a multiallelic copy number variable, which plays a crucial role in immunoregulatory and hosts defense through the production of macrophage inflammatory protein (MIP)-1α. Variable range of the CCL3L1 copies from 0 to 14 copies have been documented in several different populations. However, there is still lack of report on the range of CCL3L1 copy number exclusively among Malaysians who are a multi-ethnic population. Thus, this study aims to extensively examine the distribution of CCL3L1 copy number in the three major populations from Malaysia namely Malay, Chinese and Indian. A diploid copy number of CCL3L1 for 393 Malaysians (Malay = 178, Indian = 90, and Chinese = 125) was quantified using Paralogue Ratio Tests (PRTs) and then validated with microsatellites analysis.

Results

To our knowledge, this is the first report on the CCL3L1 copy number that has been attempted among Malaysians and the Chinese ethnic group exhibits a diverse pattern of CCL3L1 distribution copy number from the Malay and Indian (p < 0.0001). The CCL3L1 ranged from 0 to 8 copies for both the Malay and Indian ethnic groups while 0 to 10 copies for the Chinese ethnic. Consequently, the CCL3L1 copy number among major ethnic groups in the Malaysian population is found to be significantly varied when compared to the European population (p < 0.0001). The mean/median reported for the Malay, Chinese, Indian, and European are 2.759/2.869, 3.453/3.290, 2.437/1.970 and 2.001/1.940 respectively.

Conclusion

This study reveals the existence of genetic variation of CCL3L1 in the Malaysian population, and suggests by examining genetic diversity on the ethnicity, and specific geographical region could help in reconstructing human evolutionary history and for the prediction of disease risk related to the CCL3L1 copy number.

Population-wide copy number variation calling using variant call format files from 6,898 individuals

Copy number variants (CNVs) play an important role in a number of human diseases, but the accurate calling of CNVs remains challenging. Most current approaches to CNV detection use raw read alignments, which are computationally intensive to process. We use a regression tree-based approach to call germline CNVs from whole-genome sequencing (WGS, >18x) variant call sets in 6,898 samples across four European cohorts, and describe a rich large variation landscape comprising 1,320 CNVs. Eighty-one percent of detected events have been previously reported in the Database of Genomic Variants. Twenty-three percent of high-quality deletions affect entire genes, and we recapitulate known events such as the GSTM1 and RHD gene deletions. We test for association between the detected deletions and 275 protein levels in 1,457 individuals to assess the potential clinical impact of the detected CNVs. We describe complex CNV patterns underlying an association with levels of the CCL3 protein (MAF = 0.15, p = 3.6x10^-12 ) at the CCL3L3 locus, and a novel cis-association between a low-frequency NOMO1 deletion and NOMO1 protein levels (MAF = 0.02, p = 2.2x10^-7 ). This study demonstrates that existing population-wide WGS call sets can be mined for germline CNVs with minimal computational overhead, delivering insight into a less well-studied, yet potentially impactful class of genetic variant.

SRBreak: A Read-Depth and Split-Read Framework to Identify Breakpoints of Different Events Inside Simple Copy-Number Variable Regions

Copy-number variation (CNV) has been associated with increased risk of complex diseases. High-throughput sequencing (HTS) technologies facilitate the detection of copy-number variable regions (CNVRs) and their breakpoints. This helps in understanding genome structure as well as their evolution process. Various approaches have been proposed for detecting CNV breakpoints, but currently it is still challenging for tools based on a single analysis method to identify breakpoints of CNVs. It has been shown, however, that pipelines which integrate multiple approaches are able to report more reliable breakpoints. Here, based on HTS data, we have developed a pipeline to identify approximate breakpoints (±10 bp) relating to different ancestral events within a specific CNVR. The pipeline combines read-depth and split-read information to infer breakpoints, using information from multiple samples to allow an imputation approach to be taken. The main steps involve using a normal mixture model to cluster samples into different groups, followed by simple kernel-based approaches to maximize information obtained from read-depth and split-read approaches, after which common breakpoints of groups are inferred. The pipeline uses split-read information directly from CIGAR strings of BAM files, without using a re-alignment step. On simulated data sets, it was able to report breakpoints for very low-coverage samples including those for which only single-end reads were available. When applied to three loci from existing human resequencing data sets (NEGR1, LCE3, IRGM) the pipeline obtained good concordance with results from the 1000 Genomes Project (92, 100, and 82%, respectively). The package is available at https://github.com/hoangtn/SRBreak, and also as a docker-based application at https://registry.hub.docker.com/u/hoangtn/srbreak/.

Characterization of copy number variants for CCL3L1 gene in rheumatoid arthritis for French trio families and Tunisian cases and controls

Analyses of copy number variants (CNVs) for candidate genes in complex diseases are currently a promising research field. CNVs of C-C chemokine ligand 3-like 1 (CCL3L1) gene are candidate genomic factors in rheumatoid arthritis (RA). We investigated CCL3L1 CNVs association with a case-control study in Tunisians and a transmission analysis in French trio families. Relative copy number (rCN) of CCL3L1 gene was quantified by droplet digital PCR (ddPCR) in 100 French trio families (RA patients and their two parents) and in 166 RA cases and 102 healthy controls from Tunisia. We calculated odds ratio (OR) to investigate association risk for CCL3L1 CNVs in RA. rCN identified varied from 0 to 4 in the French population and from 0 to 7 in the Tunisian population. A significant difference was observed in the distribution of these rCNs between the two populations (p = 2.34 × 10(-10)), as when rCN from French and Tunisian RA patients were compared (p = 2.83 × 10(-5)). CNVs transmission in French RA trios allowed the characterization of genotypes with the presence of tandem duplication and triplication on the same chromosome. RA association tests highlighted a protective effect of rCN = 5 for CCL3L1 gene in the Tunisian population (OR = 0.056; CI 95 % [0.01-0.46]). Characterization of CCL3L1 CNVs with ddPCR methodology highlighted specific CN genotypes in a French family sample. A copy number polymorphism of a RA candidate gene was quantified, and its significant association with RA was revealed in a Tunisian sample.

Complex and multi-allelic copy number variation in human disease

Hundreds of copy number variants are complex and multi-allelic, in that they have many structural alleles and have rearranged multiple times in the ancestors who contributed chromosomes to current humans. Not only are the relationships of these multi-allelic CNVs (mCNVs) to phenotypes generally unknown, but many mCNVs have not yet been described at the basic levels—alleles, allele frequencies, structural features—that support genetic investigation. To date, most reported disease associations to these variants have been ascertained through candidate gene studies. However, only a few associations have reached the level of acceptance defined by durable replications in many cohorts. This likely stems from longstanding challenges in making precise molecular measurements of the alleles individuals have at these loci. However, approaches for mCNV analysis are improving quickly, and some of the unique characteristics of mCNVs may assist future association studies. Their various structural alleles are likely to have different magnitudes of effect, creating a natural allelic series of growing phenotypic impact and giving investigators a set of natural predictions and testable hypotheses about the extent to which each allele of an mCNV predisposes to a phenotype. Also, mCNVs’ low-to-modest correlation to individual single-nucleotide polymorphisms (SNPs) may make it easier to distinguish between mCNVs and nearby SNPs as the drivers of an association signal, and perhaps, make it possible to preliminarily screen candidate loci, or the entire genome, for the many mCNV–disease relationships that remain to be discovered.

Human gene copy number variation and infectious disease

Variability in the susceptibility to infectious disease and its clinical manifestation can be determined by variation in the environment and by genetic variation in the pathogen and the host. Despite several successes based on candidate gene studies, defining the host variation affecting infectious disease has not been as successful as for other multifactorial diseases. Both single nucleotide variation and copy number variation (CNV) of the host contribute to the host's susceptibility to infectious disease. In this review we focus on CNV, particularly on complex multiallelic CNV that is often not well characterised either directly by hybridisation methods or indirectly by analysis of genotypes and flanking single nucleotide variants. We summarise the well-known examples, such as α-globin deletion and susceptibility to severe malaria, as well as more recent controversies, such as the extensive CNV of the chemokine gene CCL3L1 and HIV infection. We discuss the potential biological mechanisms that could underly any genetic association and reflect on the extensive complexity and functional variation generated by a combination of CNV and sequence variation, as illustrated by the Fc gamma receptor genes FCGR3A, FCGR3B and FCGR2C. We also highlight some understudied areas that might prove fruitful areas for further research.

Rapid and accurate large-scale genotyping of duplicated genes and discovery of interlocus gene conversions

Over 900 genes have been annotated within duplicated regions of the human genome, yet their functions and potential roles in disease remain largely unknown. One major obstacle has been the inability to accurately and comprehensively assay genetic variation for these genes in a high-throughput manner. We developed a sequencing-based method for rapid and high-throughput genotyping of duplicated genes using molecular inversion probes designed to target unique paralogous sequence variants. We applied this method to genotype all members of two gene families, SRGAP2 and RH, among a diversity panel of 1,056 humans. The approach could accurately distinguish copy number in paralogs having up to ∼99.6% sequence identity, identify small gene-disruptive deletions, detect single-nucleotide variants, define breakpoints of unequal crossover and discover regions of interlocus gene conversion. The ability to rapidly and accurately genotype multiple gene families in thousands of individuals at low cost enables the development of genome-wide gene conversion maps and 'unlocks' many previously inaccessible duplicated genes for association with human traits.