The genetics and epidemiology of N- and O-immunoglobulin A glycomics.

BACKGROUND: Immunoglobulin (Ig) glycosylation modulates the immune response and plays a critical role in ageing and diseases. Studies have mainly focused on IgG glycosylation, and little is known about the genetics and epidemiology of IgA glycosylation. METHODS: We generated, using a novel liquid chromatography-mass spectrometry method, the first large-scale IgA glycomics dataset in serum from 2423 twins, encompassing 71 N- and O-glycan species. RESULTS: We showed that, despite the lack of a direct genetic template, glycosylation is highly heritable, and that glycopeptide structures are sex-specific, and undergo substantial changes with ageing. We observe extensive correlations between the IgA and IgG glycomes, and, exploiting the twin design, show that they are predominantly influenced by shared genetic factors. A genome-wide association study identified eight loci associated with both the IgA and IgG glycomes (ST6GAL1, ELL2, B4GALT1, ABCF2, TMEM121, SLC38A10, SMARCB1, and MGAT3) and two novel loci specifically modulating IgA O-glycosylation (C1GALT1 and ST3GAL1). Validation of our findings in an independent cohort of 320 individuals from Qatar showed that the underlying genetic architecture is conserved across ancestries. CONCLUSIONS: Our study delineates the genetic landscape of IgA glycosylation and provides novel potential functional links with the aetiology of complex immune diseases, including genetic factors involved in IgA nephropathy risk.

A roadmap to the molecular human linking multiomics with population traits and diabetes subtypes.

In-depth multiomic phenotyping provides molecular insights into complex physiological processes and their pathologies. Here, we report on integrating 18 diverse deep molecular phenotyping (omics-) technologies applied to urine, blood, and saliva samples from 391 participants of the multiethnic diabetes Qatar Metabolomics Study of Diabetes (QMDiab). Using 6,304 quantitative molecular traits with 1,221,345 genetic variants, methylation at 470,837 DNA CpG sites, and gene expression of 57,000 transcripts, we determine (1) within-platform partial correlations, (2) between-platform mutual best correlations, and (3) genome-, epigenome-, transcriptome-, and phenome-wide associations. Combined into a molecular network of > 34,000 statistically significant trait-trait links in biofluids, our study portrays "The Molecular Human". We describe the variances explained by each omics in the phenotypes (age, sex, BMI, and diabetes state), platform complementarity, and the inherent correlation structures of multiomics data. Further, we construct multi-molecular network of diabetes subtypes. Finally, we generated an open-access web interface to "The Molecular Human" ( http://comics.metabolomix.com ), providing interactive data exploration and hypotheses generation possibilities.

Assessing the implications of sentinel lymph node removal in cervical cancer: an immunogenetic perspective - a SENTICOL ancillary study.

BACKGROUND: Cervical cancer's lymphatic spread primarily begins from the sentinel lymph nodes (SLNs), underlining their pivotal role in disease metastasis. However, these nodes' immune gene expression profiles and immunoregulation mechanisms have yet to be explored. METHODS: Our study aimed to elucidate the immune cell populations and their roles in the immune gene expression profile of negative SLNs compared with positive SLNs and non-SLNs using Nanostring RNA seq analysis. We performed a principal component analysis on the log2 normalized expression of 685 endogenous genes in the nCounter PanCancer Immune Profiling Panel, followed by an assessment of the differential expression of genes and immune cell type abundance. RESULTS: We found significant variations in gene expression among the groups, with negative SLNs displaying overexpression of genes related to tumor-infiltrating immune cells, specifically innate cell populations. They also demonstrated the upregulation of genes involved in antigen presentation and T-cell priming. In contrast, positive SLNs were enriched in regulatory networks, suggesting their potential role in immune evasion. A comparison of negative SLNs and non-SLNs revealed increased innate and adaptive immune cell types, underscoring the ongoing T cell response to tumor antigens. CONCLUSION: Our findings underscore a specific immunogenetic phenotype profile in negative SLNs, emphasizing their crucial role in the initial anticancer response, immunosurveillance, and the propagation of immune tolerance from the primary cervical tumor. These results highlight the potential of SLNs as a novel target for immunotherapy strategies and underscore the importance of new imaging methods for accurately identifying SLN status without removal. Future investigations are needed to understand further the immunological interplay within SLNs and their influence on cervical cancer progression.

A genome-wide association study of mass spectrometry proteomics using the Seer Proteograph platform.

Genome-wide association studies (GWAS) with proteomics are essential tools for drug discovery. To date, most studies have used affinity proteomics platforms, which have limited discovery to protein panels covered by the available affinity binders. Furthermore, it is not clear to which extent protein epitope changing variants interfere with the detection of protein quantitative trait loci (pQTLs). Mass spectrometry-based (MS) proteomics can overcome some of these limitations. Here we report a GWAS using the MS-based Seer Proteograph™ platform with blood samples from a discovery cohort of 1,260 American participants and a replication in 325 individuals from Asia, with diverse ethnic backgrounds. We analysed 1,980 proteins quantified in at least 80% of the samples, out of 5,753 proteins quantified across the discovery cohort. We identified 252 and replicated 90 pQTLs, where 30 of the replicated pQTLs have not been reported before. We further investigated 200 of the strongest associated cis-pQTLs previously identified using the SOMAscan and the Olink platforms and found that up to one third of the affinity proteomics pQTLs may be affected by epitope effects, while another third were confirmed by MS proteomics to be consistent with the hypothesis that genetic variants induce changes in protein expression. The present study demonstrates the complementarity of the different proteomics approaches and reports pQTLs not accessible to affinity proteomics, suggesting that many more pQTLs remain to be discovered using MS-based platforms.

Loss of the TRPM4 channel in humans causes immune dysregulation with defective monocyte migration.

BACKGROUND: TRPM4 is a broadly expressed, calcium-activated, monovalent cation channel that regulates immune cell function in mice and cell lines. Clinically, however, partial loss- or gain-of-function mutations in TRPM4 lead to arrhythmia and heart disease, with no documentation of immunologic disorders. OBJECTIVE: To characterize functional cellular mechanisms underlying the immune dysregulation phenotype in a proband with a mutated TRPM4 gene. METHODS: We employed a combination of biochemical, cell biological, imaging, omics analyses, flow cytometry, and gene editing approaches. RESULTS: We report the first human cases to our knowledge with complete loss of the TRPM4 channel, leading to immune dysregulation with frequent bacterial and fungal infections. Single-cell and bulk RNA sequencing point to altered expression of genes affecting cell migration, specifically in monocytes. Inhibition of TRPM4 in T cells and the THP-1 monocyte cell line reduces migration. More importantly, primary T cells and monocytes from TRPM4 patients migrate poorly. Finally, CRISPR knockout of TRPM4 in THP-1 cells greatly reduces their migration potential. CONCLUSION: Our results demonstrate that TRPM4 plays a critical role in regulating immune cell migration, leading to increased susceptibility to infections.

Nanoparticle enrichment mass-spectrometry proteomics identifies protein-altering variants for precise pQTL mapping.

Proteogenomics studies generate hypotheses on protein function and provide genetic evidence for drug target prioritization. Most previous work has been conducted using affinity-based proteomics approaches. These technologies face challenges, such as uncertainty regarding target identity, non-specific binding, and handling of variants that affect epitope affinity binding. Mass spectrometry-based proteomics can overcome some of these challenges. Here we report a pQTL study using the Proteograph™ Product Suite workflow (Seer, Inc.) where we quantify over 18,000 unique peptides from nearly 3000 proteins in more than 320 blood samples from a multi-ethnic cohort in a bottom-up, peptide-centric, mass spectrometry-based proteomics approach. We identify 184 protein-altering variants in 137 genes that are significantly associated with their corresponding variant peptides, confirming target specificity of co-associated affinity binders, identifying putatively causal cis-encoded proteins and providing experimental evidence for their presence in blood, including proteins that may be inaccessible to affinity-based proteomics.

Retinal nerve fibre layer thinning and corneal nerve loss in patients with Bardet-Biedl syndrome.

BACKGROUND: Bardet-Biedl syndrome (BBS) is an autosomal recessive, genetically heterogeneous, pleiotropic disorder caused by variants in genes involved in the function of the primary cilium. We have harnessed genomics to identify BBS and ophthalmic technologies to describe novel features of BBS. CASE PRESENTATION: A patient with an unclear diagnosis of syndromic type 2 diabetes mellitus, another affected sibling and unaffected siblings and parents were sequenced using DNA extracted from saliva samples. Corneal confocal microscopy (CCM) and retinal spectral domain optical coherence tomography (SD-OCT) were used to identify novel ophthalmic features in these patients. The two affected individuals had a homozygous variant in C8orf37 (p.Trp185*). SD-OCT and CCM demonstrated a marked and patchy reduction in the retinal nerve fiber layer thickness and loss of corneal nerve fibers, respectively. CONCLUSION: This report highlights the use of ophthalmic imaging to identify novel retinal and corneal abnormalities that extend the phenotype of BBS in a patient with syndromic type 2 diabetes.

Proteomic analysis of 92 circulating proteins and their effects in cardiometabolic diseases.

BACKGROUND: Human plasma contains a wide variety of circulating proteins. These proteins can be important clinical biomarkers in disease and also possible drug targets. Large scale genomics studies of circulating proteins can identify genetic variants that lead to relative protein abundance. METHODS: We conducted a meta-analysis on genome-wide association studies of autosomal chromosomes in 22,997 individuals of primarily European ancestry across 12 cohorts to identify protein quantitative trait loci (pQTL) for 92 cardiometabolic associated plasma proteins. RESULTS: We identified 503 (337 cis and 166 trans) conditionally independent pQTLs, including several novel variants not reported in the literature. We conducted a sex-stratified analysis and found that 118 (23.5%) of pQTLs demonstrated heterogeneity between sexes. The direction of effect was preserved but there were differences in effect size and significance. Additionally, we annotate trans-pQTLs with nearest genes and report plausible biological relationships. Using Mendelian randomization, we identified causal associations for 18 proteins across 19 phenotypes, of which 10 have additional genetic colocalization evidence. We highlight proteins associated with a constellation of cardiometabolic traits including angiopoietin-related protein 7 (ANGPTL7) and Semaphorin 3F (SEMA3F). CONCLUSION: Through large-scale analysis of protein quantitative trait loci, we provide a comprehensive overview of common variants associated with plasma proteins. We highlight possible biological relationships which may serve as a basis for further investigation into possible causal roles in cardiometabolic diseases.

Standardization and Interpretation of RNA-sequencing for Transplantation.

RNA-sequencing (RNA-seq) is a technique to determine the order of nucleotides in an RNA segment. Modern sequencing platforms simultaneously sequence millions of RNA molecules. Advances in bioinformatics have allowed us to collect, store, analyze, and disseminate data from RNA-seq experiments and decipher biological insights from large sequencing datasets. Although bulk RNA-seq has significantly advanced our understanding of tissue-specific gene expression and regulation, recent advances in single-cell RNA-seq have allowed such information to be mapped to individual cells, thus remarkably enhancing our insight into discrete cellular functions within a biospecimen. These different RNA-seq experimental approaches require specialized computational tools. Herein, we will first review the RNA-seq experimental workflow, discuss the common terminologies used in RNA-seq, and suggest approaches for standardization across multiple studies. Next, we will provide an up-to-date appraisal of the applications of bulk RNA-seq and single-cell/nucleus RNA-seq in preclinical and clinical research on kidney transplantation, as well as typical bioinformatic workflows utilized in such analysis. Lastly, we will deliberate on the limitations of this technology in transplantation research and briefly summarize newer technologies that could be combined with RNA-seq to permit more powerful dissections of biological functions. Because each step in RNA-seq workflow has numerous variations and could potentially impact the results, as conscientious citizens of the research community, we must strive to continuously modernize our analytical pipelines and exhaustively report their technical details.

Identification of PCSK9-like human gene knockouts using metabolomics, proteomics, and whole-genome sequencing in a consanguineous population.

Natural human knockouts of genes associated with desirable outcomes, such as PCSK9 with low levels of LDL-cholesterol, can lead to the discovery of new drug targets and treatments. Rare loss-of-function variants are more likely to be found in the homozygous state in consanguineous populations, and deep molecular phenotyping of blood samples from homozygous carriers can help to discriminate between silent and functional variants. Here, we combined whole-genome sequencing with proteomics and metabolomics for 2,935 individuals from the Qatar Biobank (QBB) to evaluate the power of this approach for finding genes of clinical and pharmaceutical interest. As proof-of-concept, we identified a homozygous carrier of a very rare PCSK9 variant with extremely low circulating PCSK9 levels and low LDL. Our study demonstrates that the chances of finding such variants are about 168 times higher in QBB compared with GnomAD and emphasizes the potential of consanguineous populations for drug discovery.

Differences and commonalities in the genetic architecture of protein quantitative trait loci in European and Arab populations.

Polygenic scores (PGS) can identify individuals at risk of adverse health events and guide genetics-based personalized medicine. However, it is not clear how well PGS translate between different populations, limiting their application to well-studied ethnicities. Proteins are intermediate traits linking genetic predisposition and environmental factors to disease, with numerous blood circulating protein levels representing functional readouts of disease-related processes. We hypothesized that studying the genetic architecture of a comprehensive set of blood-circulating proteins between a European and an Arab population could shed fresh light on the translatability of PGS to understudied populations. We therefore conducted a genome-wide association study with whole-genome sequencing data using 1301 proteins measured on the SOMAscan aptamer-based affinity proteomics platform in 2935 samples of Qatar Biobank and evaluated the replication of protein quantitative traits (pQTLs) from European studies in an Arab population. Then, we investigated the colocalization of shared pQTL signals between the two populations. Finally, we compared the performance of protein PGS derived from a Caucasian population in a European and an Arab cohort. We found that the majority of shared pQTL signals (81.8%) colocalized between both populations. About one-third of the genetic protein heritability was explained by protein PGS derived from a European cohort, with protein PGS performing ~20% better in Europeans when compared to Arabs. Our results are relevant for the translation of PGS to non-Caucasian populations, as well as for future efforts to extend genetic research to understudied populations.

Development and characterization of microsatellite primers for Triops granarius (Branchiopoda: Notostraca) using MiSeq technology.

BACKGROUND: Next-generation sequencing technology has allowed for the rapid development of microsatellites, neutral polymorphic markers that can be used for the analysis of population structure. METHODS AND RESULTS: In this study, we performed whole-genome sequencing using the Illumina MiSeq system and de novo assembly to design microsatellite primers for Triops granarius populations in Qatar. The developed microsatellites are suitable for future studies of genetic structuring among geographically isolated freshwater pools. A total of 23 different primer pairs produced typical microsatellite results, with each pair successfully amplified in up to 40 individuals. Only five of the loci produced a significant departure from Hardy-Weinberg equilibrium. CONCLUSIONS: Some of the underlying mechanisms regarding the few loci that deviated from HWE may be further investigated to determine the source of deviation. As T. granarius is the most widely distributed species of the family, the development of these molecular markers would be useful for conducting population genetics and biogeographical studies broadly.

Ratios of Acetaminophen Metabolites Identify New Loci of Pharmacogenetic Relevance in a Genome-Wide Association Study.

Genome-wide association studies (GWAS) with non-targeted metabolomics have identified many genetic loci of biomedical interest. However, metabolites with a high degree of missingness, such as drug metabolites and xenobiotics, are often excluded from such studies due to a lack of statistical power and higher uncertainty in their quantification. Here we propose ratios between related drug metabolites as GWAS phenotypes that can drastically increase power to detect genetic associations between pairs of biochemically related molecules. As a proof-of-concept we conducted a GWAS with 520 individuals from the Qatar Biobank for who at least five of the nine available acetaminophen metabolites have been detected. We identified compelling evidence for genetic variance in acetaminophen glucuronidation and methylation by UGT2A15 and COMT, respectively. Based on the metabolite ratio association profiles of these two loci we hypothesized the chemical structure of one of their products or substrates as being 3-methoxyacetaminophen, which we then confirmed experimentally. Taken together, our study suggests a novel approach to analyze metabolites with a high degree of missingness in a GWAS setting with ratios, and it also demonstrates how pharmacological pathways can be mapped out using non-targeted metabolomics measurements in large population-based studies.

Detection of infiltrating fibroblasts by single-cell transcriptomics in human kidney allografts.

We tested the hypothesis that single-cell RNA-sequencing (scRNA-seq) analysis of human kidney allograft biopsies will reveal distinct cell types and states and yield insights to decipher the complex heterogeneity of alloimmune injury. We selected 3 biopsies of kidney cortex from 3 individuals for scRNA-seq and processed them fresh using an identical protocol on the 10x Chromium platform; (i) HK: native kidney biopsy from a living donor, (ii) AK1: allograft kidney with transplant glomerulopathy, tubulointerstitial fibrosis, and worsening graft function, and (iii) AK2: allograft kidney after successful treatment of active antibody-mediated rejection. We did not study T-cell-mediated rejections. We generated 7217 high-quality single cell transcriptomes. Taking advantage of the recipient-donor sex mismatches revealed by X and Y chromosome autosomal gene expression, we determined that in AK1 with fibrosis, 42 months after transplantation, more than half of the kidney allograft fibroblasts were recipient-derived and therefore likely migratory and graft infiltrative, whereas in AK2 without fibrosis, 84 months after transplantation, most fibroblasts were donor-organ-derived. Furthermore, AK1 was enriched for tubular progenitor cells overexpressing profibrotic extracellular matrix genes. AK2, eight months after successful treatment of rejection, contained plasmablast cells with high expression of immunoglobulins, endothelial cell elaboration of T cell chemoattractant cytokines, and persistent presence of cytotoxic T cells. In addition to these key findings, our analysis revealed unique cell types and states in the kidney. Altogether, single-cell transcriptomics yielded novel mechanistic insights, which could pave the way for individualizing the care of transplant recipients.

Defining the landscape of metabolic dysregulations in cancer metastasis.

Metastasis is the primary cause of cancer related deaths due to the limited number of efficient druggable targets. Signatures of dysregulated cancer metabolism could serve as a roadmap for the determination of new treatment strategies. However, the metabolic signatures of metastatic cells remain vastly elusive. Our aim was to determine metabolic dysregulations associated with high metastatic potential in breast cancer cell lines. We have selected 5 triple negative breast cancer (TNBC) cell lines including three with high metastatic potential (HMP) (MDA-MB-231, MDA-MB-436, MDA-MB-468) and two with low metastatic potential (LMP) (BT549, HCC1143). The normal epithelial breast cell line (hTERT-HME1) was also investigated. The untargeted metabolic profiling of cells and growth media was conducted and total of 479 metabolites were quantified. First we characterized metabolic features differentiating TNBC cell lines from normal cells as well as identified cell line specific metabolic fingerprints. Next, we determined 92 metabolites in cells and 22 in growth medium that display significant differences between LMP and HMP. The HMP cell lines had elevated level of molecules involved in glycolysis, TCA cycle and lipid metabolism. We identified metabolic advantages of cell lines with HMP beyond enhanced glycolysis by pinpointing the role of branched chain amino acids (BCAA) catabolism as well as molecules supporting coagulation and platelet activation as important contributors to the metastatic cascade. The landscape of metabolic dysregulations, characterized in our study, could serve as a roadmap for the identification of treatment strategies targeting cancer cells with enhanced metastatic potential.

Systems biology analysis of human genomes points to key pathways conferring spina bifida risk.

Spina bifida (SB) is a debilitating birth defect caused by multiple gene and environment interactions. Though SB shows non-Mendelian inheritance, genetic factors contribute to an estimated 70% of cases. Nevertheless, identifying human mutations conferring SB risk is challenging due to its relative rarity, genetic heterogeneity, incomplete penetrance, and environmental influences that hamper genome-wide association studies approaches to untargeted discovery. Thus, SB genetic studies may suffer from population substructure and/or selection bias introduced by typical candidate gene searches. We report a population based, ancestry-matched whole-genome sequence analysis of SB genetic predisposition using a systems biology strategy to interrogate 298 case-control subject genomes (149 pairs). Genes that were enriched in likely gene disrupting (LGD), rare protein-coding variants were subjected to machine learning analysis to identify genes in which LGD variants occur with a different frequency in cases versus controls and so discriminate between these groups. Those genes with high discriminatory potential for SB significantly enriched pathways pertaining to carbon metabolism, inflammation, innate immunity, cytoskeletal regulation, and essential transcriptional regulation consistent with their having impact on the pathogenesis of human SB. Additionally, an interrogation of conserved noncoding sequences identified robust variant enrichment in regulatory regions of several transcription factors critical to embryonic development. This genome-wide perspective offers an effective approach to the interrogation of coding and noncoding sequence variant contributions to rare complex genetic disorders.

Deep sequencing of DNA from urine of kidney allograft recipients to estimate donor/recipient-specific DNA fractions.

Kidney transplantation is the treatment of choice for patients with end-stage kidney failure, but transplanted allograft could be affected by viral and bacterial infections and by immune rejection. The standard test for the diagnosis of acute pathologies in kidney transplants is kidney biopsy. However, noninvasive tests would be desirable. Various methods using different techniques have been developed by the transplantation community. But these methods require improvements. We present here a cost-effective method for kidney rejection diagnosis that estimates donor/recipient-specific DNA fraction in recipient urine by sequencing urinary cell DNA. We hypothesized that in the no-pathology stage, the largest tissue types present in recipient urine are donor kidney cells, and in case of rejection, a larger number of recipient immune cells would be observed. Extensive in-silico simulation was used to tune the sequencing parameters: number of variants and depth of coverage. Sequencing of DNA mixture from 2 healthy individuals showed the method is highly predictive (maximum error < 0.04). We then demonstrated the insignificant impact of familial relationship and ethnicity using an in-house and public database. Lastly, we performed deep DNA sequencing of urinary cell pellets from 32 biopsy-matched samples representing two pathology groups: acute rejection (AR, 11 samples) and acute tubular injury (ATI, 12 samples) and 9 samples with no pathology. We found a significant association between the donor/recipient-specific DNA fraction in the two pathology groups compared to no pathology (P = 0.0064 for AR and P = 0.026 for ATI). We conclude that deep DNA sequencing of urinary cells from kidney allograft recipients offers a noninvasive means of diagnosing acute pathologies in the human kidney allograft.

Genome-wide investigation identifies a rare copy-number variant burden associated with human spina bifida.

PURPOSE: Next-generation sequencing has implicated some risk variants for human spina bifida (SB), but the genome-wide contribution of structural variation to this complex genetic disorder remains largely unknown. We examined copy-number variant (CNV) participation in the genetic architecture underlying SB risk. METHODS: A high-confidence ensemble approach to genome sequences (GS) was benchmarked and employed for systematic detection of common and rare CNVs in two separate ancestry-matched SB case-control cohorts. RESULTS: SB cases were enriched with exon disruptive rare CNVs, 44% of which were under 10 kb, in both ancestral populations (P = 6.75 × 10-7; P = 7.59 × 10-4). Genes containing these disruptive CNVs fall into molecular pathways, supporting a role for these genes in SB. Our results expand the catalog of variants and genes with potential contribution to genetic and gene-environment interactions that interfere with neurulation, useful for further functional characterization. CONCLUSION: This study underscores the need for genome-wide investigation and extends our previous threshold model of exonic, single-nucleotide variation toward human SB risk to include structural variation. Since GS data afford detection of CNVs with greater resolution than microarray methods, our results have important implications toward a more comprehensive understanding of the genetic risk and mechanisms underlying neural tube defect pathogenesis.

Whole genome sequencing in the Middle Eastern Qatari population identifies genetic associations with 45 clinically relevant traits.

Clinical laboratory tests play a pivotal role in medical decision making, but little is known about their genetic variability between populations. We report a genome-wide association study with 45 clinically relevant traits from the population of Qatar using a whole genome sequencing approach in a discovery set of 6218 individuals and replication in 7768 subjects. Trait heritability is more similar between Qatari and European populations (r = 0.81) than with Africans (r = 0.44). We identify 281 distinct variant-trait-associations at genome wide significance that replicate known associations. Allele frequencies for replicated loci show higher correlations with European (r = 0.94) than with African (r = 0.85) or Japanese (r = 0.80) populations. We find differences in linkage disequilibrium patterns and in effect sizes of the replicated loci compared to previous reports. We also report 17 novel and Qatari-predominate signals providing insights into the biological pathways regulating these traits. We observe that European-derived polygenic scores (PGS) have reduced predictive performance in the Qatari population which could have implications for the translation of PGS between populations and their future application in precision medicine.