dbSNP: the NCBI database of genetic variation

Computational screening of pathogenic missense nsSNPs in heme oxygenase 1 (HMOX1) gene and their structural and functional consequences

Heme Oxygenase 1 (HMOX1) is a cytoprotective enzyme, exhibiting the highest activity in the spleen, catalyzing the heme ring breakdown into products of biological significance- biliverdin, CO, and Fe2+. In vascular cells, HMOX1 possesses strong anti-apoptotic, antioxidant, anti-proliferative, anti-inflammatory, and immunomodulatory actions. The majority of these activities are crucial for the prevention of atherogenesis. Single amino acid substitutions in proteins generated by missense non-synonymous single nucleotide polymorphism (nsSNPs) in the protein-encoding regions of genes are potent enough to cause significant medical challenges due to the alteration of protein structure and function. The current study aimed at characterizing and analyzing high-risk nsSNPs associated with the human HMOX1 gene. Preliminary screening of the total available 288 missense SNPs was performed through the lens of deleteriousness and stability prediction tools. Finally, a total of seven nsSNPs (Y58D, A131T, Y134H, F166S, F167S, R183S and M186V) were found to be most deleterious by all tools that are present at highly conserved positions. Molecular dynamics simulations (MDS) analysis explained the mutational effects on the dynamic action of the wild-type and mutant proteins. In a nutshell, R183S (rs749644285) was identified as a highly detrimental mutation that could significantly render the enzymatic activity of HMOX1. The finding of this computational analysis might help subject the experimental confirmatory analysis to characterize the role of nsSNPs in HMOX1.Communicated by Ramaswamy H. Sarma.

A deep intronic variant in MME causes autosomal recessive Charcot-Marie-Tooth neuropathy through aberrant splicing

BACKGROUND

Loss-of-function variants in MME (membrane metalloendopeptidase) are a known cause of recessive Charcot-Marie-Tooth Neuropathy (CMT). A deep intronic variant, MME c.1188+428A>G (NM_000902.5), was identified through whole genome sequencing (WGS) of two Australian families with recessive inheritance of axonal CMT using the seqr platform. MME c.1188+428A>G was detected in a homozygous state in Family 1, and in a compound heterozygous state with a known pathogenic MME variant (c.467del; p.Pro156Leufs*14) in Family 2.

AIMS

We aimed to determine the pathogenicity of the MME c.1188+428A>G variant through segregation and splicing analysis.

METHODS

The splicing impact of the deep intronic MME variant c.1188+428A>G was assessed using an in vitro exon-trapping assay.

RESULTS

The exon-trapping assay demonstrated that the MME c.1188+428A>G variant created a novel splice donor site resulting in the inclusion of an 83 bp pseudoexon between MME exons 12 and 13. The incorporation of the pseudoexon into MME transcript is predicted to lead to a coding frameshift and premature termination codon (PTC) in MME exon 14 (p.Ala397ProfsTer47). This PTC is likely to result in nonsense mediated decay (NMD) of MME transcript leading to a pathogenic loss-of-function.

INTERPRETATION

To our knowledge, this is the first report of a pathogenic deep intronic MME variant causing CMT. This is of significance as deep intronic variants are missed using whole exome sequencing screening methods. Individuals with CMT should be reassessed for deep intronic variants, with splicing impacts being considered in relation to the potential pathogenicity of variants.

Genetic variants affecting mitochondrial function provide further insights for kidney disease

BACKGROUND

Chronic kidney disease (CKD) is a complex disorder that has become a high prevalence global health problem, with diabetes being its predominant pathophysiologic driver. Autosomal genetic variation only explains some of the predisposition to kidney disease. Variations in the mitochondrial genome (mtDNA) and nuclear-encoded mitochondrial genes (NEMG) are implicated in susceptibility to kidney disease and CKD progression, but they have not been thoroughly explored. Our aim was to investigate the association of variation in both mtDNA and NEMG with CKD (and related traits), with a particular focus on diabetes.

METHODS

We used the UK Biobank (UKB) and UK-ROI, an independent collection of individuals with type 1 diabetes mellitus (T1DM) patients.

RESULTS

Fourteen mitochondrial variants were associated with estimated glomerular filtration rate (eGFR) in UKB. Mitochondrial variants and haplogroups U, H and J were associated with eGFR and serum variables. Mitochondrial haplogroup H was associated with all the serum variables regardless of the presence of diabetes. Mitochondrial haplogroup X was associated with end-stage kidney disease (ESKD) in UKB. We confirmed the influence of several known NEMG on kidney disease and function and found novel associations for SLC39A13, CFL1, ACP2 or ATP5G1 with serum variables and kidney damage, and for SLC4A1, NUP210 and MYH14 with ESKD. The G allele of TBC1D32-rs113987180 was associated with higher risk of ESKD in patients with diabetes (OR:9.879; CI95%:4.440-21.980; P = 2.0E-08). In UK-ROI, AGXT2-rs71615838 and SURF1-rs183853102 were associated with diabetic nephropathies, and TFB1M-rs869120 with eGFR.

CONCLUSIONS

We identified novel variants both in mtDNA and NEMG which may explain some of the missing heritability for CKD and kidney phenotypes. We confirmed the role of MT-ND5 and mitochondrial haplogroup H on renal disease (serum variables), and identified the MT-ND5-rs41535848G variant, along with mitochondrial haplogroup X, associated with higher risk of ESKD. Despite most of the associations were independent of diabetes, we also showed potential roles for NEMG in T1DM.

Prediction of adverse drug reactions due to genetic predisposition using deep neural networks

Drug development is a long and costly process, often limited by the toxicity and adverse drug reactions (ADRs) caused by drug candidates. Even on the market, some drugs can cause strong ADRs that can vary depending on an individual polymorphism. The development of Genome-wide association studies (GWAS) allowed the discovery of genetic variants of interest that may cause these effects. In this study, the objective was to investigate a deep learning approach to predict genetic variations potentially related to ADRs. We used single nucleotide polymorphisms (SNPs) information from dbSNP to create a network based on ADR-drug-target-mutations and extracted matrixes of interaction to build deep Neural Networks (DNN) models. Considering only information about mutations known to impact drug efficacy and drug safety from PharmGKB and drug adverse reactions based on the MedDRA System Organ Classes (SOCs), these DNN models reached a balanced accuracy of 0.61 in average. Including molecular fingerprints representing structural features of the drugs did not improve the performance of the models. To our knowledge, this is the first model that exploits DNN to predict ADR-drug-target-mutations. Although some improvements are suggested, these models can be of interest to analyze multiple compounds over all of the genes and polymorphisms information accessible and thus pave the way in precision medicine.

Human genetics of face recognition: discovery of MCTP2 mutations in humans with face blindness (congenital prosopagnosia)

Face recognition is important for both visual and social cognition. While prosopagnosia or face blindness has been known for seven decades and face-specific neurons for half a century, the molecular genetic mechanism is not clear. Here we report results after 17 years of research with classic genetics and modern genomics. From a large family with 18 congenital prosopagnosia (CP) members with obvious difficulties in face recognition in daily life, we uncovered a fully cosegregating private mutation in the MCTP2 gene which encodes a calcium binding transmembrane protein expressed in the brain. After screening through cohorts of 6589, we found more CPs and their families, allowing detection of more CP associated mutations in MCTP2. Face recognition differences were detected between 14 carriers with the frameshift mutation S80fs in MCTP2 and 19 noncarrying volunteers. Six families including one with 10 members showed the S80fs-CP correlation. Functional magnetic resonance imaging found association of impaired recognition of individual faces by MCTP2 mutant CPs with reduced repetition suppression to repeated facial identities in the right fusiform face area. Our results have revealed genetic predisposition of MCTP2 mutations in CP, 76 years after the initial report of prosopagnosia and 47 years after the report of the first CP. This is the first time a gene required for a higher form of visual social cognition was found in humans.

A de novo dominant-negative variant is associated with OTULIN-related autoinflammatory syndrome

OTULIN-related autoinflammatory syndrome (ORAS), a severe autoinflammatory disease, is caused by biallelic pathogenic variants of OTULIN, a linear ubiquitin-specific deubiquitinating enzyme. Loss of OTULIN attenuates linear ubiquitination by inhibiting the linear ubiquitin chain assembly complex (LUBAC). Here, we report a patient who harbors two rare heterozygous variants of OTULIN (p.P152L and p.R306Q). We demonstrated accumulation of linear ubiquitin chains upon TNF stimulation and augmented TNF-induced cell death in mesenchymal stem cells differentiated from patient-derived iPS cells, which confirms that the patient has ORAS. However, although the de novo p.R306Q variant exhibits attenuated deubiquitination activity without reducing the amount of OTULIN, the deubiquitination activity of the p.P152L variant inherited from the mother was equivalent to that of the wild-type. Patient-derived MSCs in which the p.P152L variant was replaced with wild-type also exhibited augmented TNF-induced cell death and accumulation of linear chains. The finding that ORAS can be caused by a dominant-negative p.R306Q variant of OTULIN furthers our understanding of disease pathogenesis.

STAC3 disorder: a common cause of congenital hypotonia in Southern African patients

STAC3 disorder, or Native American myopathy, is characterised by congenital myopathy, hypotonia, musculoskeletal and palatal anomalies, and susceptibility to malignant hyperthermia. A STAC3 c.851 G > C (p.Trp284Ser) pathogenic variant, common in the Lumbee Native American tribe, has been identified in other populations worldwide, including patients of African ancestry. We report on the frequency of STAC3 c.851 G > C in a cohort of 127 patients presenting with congenital hypotonia that tested negative for spinal muscular atrophy and/or Prader-Willi syndrome. We present a clinical retrospective, descriptive review on 31 Southern African patients homozygous for STAC3 c.851 G > C. The frequencies of various phenotypic characteristics were calculated. In total, 25/127 (20%) laboratory-based samples were homozygous for STAC3 c.851 G > C. A carrier rate of 1/56 and a predicted birth rate of 1/12 500 was estimated from a healthy cohort. A common haplotype spanning STAC3 was identified in four patients. Of the clinical group, 93% had a palatal abnormality, 52% a spinal anomaly, 59% had talipes equinovarus deformity/deformities, 38% had arthrogryposis multiplex congenita, and 22% had a history suggestive of malignant hyperthermia. The novel finding that STAC3 disorder is a common African myopathy has important clinical implications for the diagnosis, treatment and genetic counselling of individuals, with neonatal and/or childhood hypotonia with or without arthrogryposis multiplex congenita, and their families. The spread of this variant worldwide and the allele frequency higher in the African/African-American ancestry than the Admixed Americans, strongly indicates that the STAC3 c.851 G > C variant has an African origin which may be due to an ancient mutation with migration and population bottlenecks.

Identification and analysis of oncogenic non-synonymous single nucleotide polymorphisms in the human NRAS gene: An exclusive in silico study

BACKGROUND

N-ras protein is encoded by the NRAS gene and operates as GDP-GTP-controlled on/off switching. N-ras interacts with cellular signaling networks that regulate various cellular activities including cell proliferation and survival. The nonsynonymous single nucleotide polymorphism (nsSNPs)-mediated alteration can substantially disrupt the structure and activity of the corresponding protein. N-ras has been reported to be associated with numerous diseases including cancers due to the nsSNPs. A comprehensive study on the NRAS gene to unveil the potentially damaging and oncogenic nsSNPs is yet to be accomplished. Hence, this extensive in silico study is intended to identify the disease-associated, specifically oncogenic nsSNPs of the NRAS gene.

RESULTS

Out of 140 missense variants, 7 nsSNPs (I55R, G60E, G60R, Y64D, L79F, D119G, and V152F) were identified to be damaging utilizing 10 computational tools that works based on different algorithms with high accuracy. Among those, G60E, G60R, and D119G variants were further filtered considering their location in the highly conserved region and later identified as oncogenic variants. Interestingly, G60E and G60R variants were revealed to be particularly associated with lung adenocarcinoma, rhabdomyosarcoma, and prostate adenocarcinoma. Therefore, D119G could be subjected to detailed investigation for identifying its association with specific cancer.

CONCLUSION

This in silico study identified the deleterious and oncogenic missense variants of the human NRAS gene that could be utilized for designing further experimental investigation. The outcomes of this study would be worthwhile in future research for developing personalized medicine.

The interaction between magnesium intake, the genetic variant INSR rs1799817 and colorectal cancer risk in a Korean population: a case-control study

Magnesium may have a significant impact on the development of cancer. However, the relationship between magnesium intake and the risk of colorectal cancer (CRC) is unclear. Therefore, we evaluated the association between magnesium intake and the risk of CRC, and we investigated how the insulin receptor (INSR) rs1799817 variant impacts this relationship. Data from 1,420 CRC patients and 2,840 controls from the Korean National Cancer Centre were analysed. A higher intake of magnesium was associated with a reduced risk of CRC in the total population (odds ratio (OR) = 0.65, 95% confidence interval (CI) = 0.52-0.81). We found that G + carriers of INSR rs1799817 with higher magnesium intake had a significantly lower risk of CRC (p for interaction = 0.003). Our findings indicated that high magnesium intake could be associated with a decreased risk of CRC, and this association could be modified by the INSR rs1799817 variant.

The Use of Precision Epigenetic Methods for the Diagnosis and Care of Stable Coronary Heart Disease Reduces Healthcare Costs

INTRODUCTION

The cost of secondary prevention of coronary heart disease (CHD) is continuing to increase, with a substantial portion of this acceleration being driven by the expense of confirmatory diagnostic testing. Conceivably, newly developed precision epigenetic technologies could drive down these costs. However, at the current time, their impact on overall expense for CHD care is poorly understood. We hypothesized that the use of a newly developed, highly sensitive, and specific epigenetic test, PrecisionCHD, could decrease the costs of secondary prevention.

METHODS

To test this hypothesis, we constructed a budget impact analysis using a cost calculation model that examined the effects of substituting PrecisionCHD for conventional CHD diagnostic tests on the expenses of the initial evaluation and first year of care of stable CHD using a 1-year time horizon with no discounting.

RESULTS

The model projected that for a commercial insurer with one million members, full adoption of PrecisionCHD as the primary method of initial CHD assessment would save approximately $113.6 million dollars in the initial year.

CONCLUSION

These analyses support the use of precision epigenetic methods as part of the initial diagnosis and care of stable CHD and can meaningfully reduce cost. Real-world pilots to test the reliability of these analyses are indicated.

Identification of a Novel Homozygous Mutation in MTMR2 Gene Causes Very Rare Charcot-Marie-Tooth Disease Type 4B1

Background

Charcot-Marie-Tooth disease (CMT) is a heterogeneous group of disorders involving peripheral nervous system. Charcot-Marie-Tooth disease 4B1 (CMT4B1) is a rare subtype of CMT. CMT4B1 is an axonal demyelinating polyneuropathy with an autosomal recessive mode of inheritance. Patients with CMT4B1 usually manifested with dysfunction of the motor and sensory systems which leads to gradual and progressive muscular weakness and atrophy, starting from the peroneal muscles and finally affecting the distal muscles. Germline mutations in MTMR2 gene causes CMT4B1.

Material and Methods

In this study, we investigated a 4-year-old Chinese boy with gradual and progressive weakness and atrophy of both proximal and distal muscles. The proband's parents did not show any abnormalities. Whole-exome sequencing and Sanger sequencing were performed.

Results

Whole-exome sequencing identified a novel homozygous nonsense mutation (c.118A>T; p.Lys40*) in exon 2 of MTMR2 gene in the proband. This novel mutation leads to the formation of a truncated MTMR2 protein of 39 amino acids instead of the wild- type MTMR2 protein of 643 amino acids. This mutation is predicted to cause the complete loss of the PH-GRAM domain, phosphatase domain, coiled-coil domain, and PDZ-binding motif of the MTMR2 protein. Sanger sequencing revealed that the proband's parents carried the mutation in a heterozygous state. This mutation was absent in 100 healthy control individuals.

Conclusion

This study reports the first mutation in MTMR2 associated with CMT4B1 in a Chinese population. Our study also showed the importance of whole-exome sequencing in identifying candidate genes and disease-causing variants in patients with CMT4B1.

Knockout mice with pituitary malformations help identify human cases of hypopituitarism

BACKGROUND

Congenital hypopituitarism (CH) and its associated syndromes, septo-optic dysplasia (SOD) and holoprosencephaly (HPE), are midline defects that cause significant morbidity for affected people. Variants in 67 genes are associated with CH, but a vast majority of CH cases lack a genetic diagnosis. Whole exome and whole genome sequencing of CH patients identifies sequence variants in genes known to cause CH, and in new candidate genes, but many of these are variants of uncertain significance (VUS).

METHODS

The International Mouse Phenotyping Consortium (IMPC) is an effort to establish gene function by knocking-out all genes in the mouse genome and generating corresponding phenotype data. We used mouse embryonic imaging data generated by the Deciphering Mechanisms of Developmental Disorders (DMDD) project to screen 209 embryonic lethal and sub-viable knockout mouse lines for pituitary malformations.

RESULTS

Of the 209 knockout mouse lines, we identified 51 that have embryonic pituitary malformations. These genes not only represent new candidates for CH, but also reveal new molecular pathways not previously associated with pituitary organogenesis. We used this list of candidate genes to mine whole exome sequencing data of a cohort of patients with CH, and we identified variants in two unrelated cases for two genes, MORC2 and SETD5, with CH and other syndromic features.

CONCLUSIONS

The screening and analysis of IMPC phenotyping data provide proof-of-principle that recessive lethal mouse mutants generated by the knockout mouse project are an excellent source of candidate genes for congenital hypopituitarism in children.

CD59 gene: 143 haplotypes of 22,718 nucleotides length by computational phasing in 113 individuals from different ethnicities

BACKGROUND

CD59 deficiency due to rare germline variants in the CD59 gene causes disabilities, ischemic strokes, neuropathy, and hemolysis. CD59 deficiency due to common somatic variants in the PIG-A gene in hematopoietic stem cells causes paroxysmal nocturnal hemoglobinuria. The ISBT database lists one nonsense and three missense germline variants that are associated with the CD59-null phenotype. To analyze the genetic diversity of the CD59 gene, we determined long-range CD59 haplotypes among individuals from different ethnicities.

METHODS

We determined a 22.7 kb genomic fragment of the CD59 gene in 113 individuals using next-generation sequencing (NGS), which covered the whole NM_203330.2 mRNA transcript of 7796 base pairs. Samples came from an FDA reference repository and our Ethiopia study cohorts. The raw genotype data were computationally phased into individual haplotype sequences.

RESULTS

Nucleotide sequencing of the CD59 gene of 226 chromosomes identified 216 positions with single nucleotide variants. Only three haplotypes were observed in homozygous form, which allowed us to assign them unambiguously as experimentally verified CD59 haplotypes. They were also the most frequent haplotypes among both cohorts. An additional 140 haplotypes were imputed computationally.

DISCUSSION

We provided a large set of haplotypes and proposed three verified long-range CD59 reference sequences, based on a population approach, using a generalizable rationale for our choice. Correct long-range haplotypes are useful as template sequences for allele calling in high-throughput NGS and precision medicine approaches, thus enhancing the reliability of clinical diagnostics. Long-range haplotypes can also be used to evaluate the influence of genetic variation on the risk of transfusion reactions or diseases.

CanCellVar: A database for single-cell variants map in human cancer

Numerous variants, including both single-nucleotide variants (SNVs) in DNA and A>G RNA edits in mRNA as essential drivers of cellular proliferation and tumorigenesis, are commonly associated with cancer progression and growth. Thus, mining and summarizing single-cell variants will provide a refined and higher-resolution view of cancer and further contribute to precision medicine. Here, we established a database, CanCellVar, which aims to provide and visualize the comprehensive atlas of single-cell variants in tumor microenvironment. The current CanCellVar identified ∼3 million variants (∼1.4 million SNVs and ∼1.4 million A>G RNA edits) involved in 2,754,531 cells of 5 major cell types across 37 cancer types. CanCellVar provides the basic annotation information as well as cellular and molecular function properties of variants. In addition, the clinical relevance of variants can be obtained including tumor grade, treatment, metastasis, and others. Several flexible tools were also developed to aid retrieval and to analyze cell-cell interactions, gene expression, cell-development trajectories, regulation, and molecular structure affected by variants. Collectively, CanCellVar will serve as a valuable resource for investigating the functions and characteristics of single-cell variations and their roles in human tumor evolution and treatment.

Single nucleotide polymorphisms in the cannabinoid CB2 receptor: Molecular pharmacology and disease associations

Preclinical evidence implicating cannabinoid receptor 2 (CB2) in various diseases has led researchers to question whether CB2 genetics influence aetiology or progression. Associations between conditions and genetic loci are often studied via single nucleotide polymorphism (SNP) prevalence in case versus control populations. In the CNR2 coding exon, ~36 SNPs have high overall population prevalence (minor allele frequencies [MAF] ~37%), including non-synonymous SNP (ns-SNP) rs2501432 encoding CB2 63Q/R. Interspersed are ~27 lower frequency SNPs, four being ns-SNPs. CNR2 introns also harbour numerous SNPs. This review summarises CB2 ns-SNP molecular pharmacology and evaluates evidence from ~70 studies investigating CB2 genetic variants with proposed linkage to disease. Although CNR2 genetic variation has been associated with a wide variety of conditions, including osteoporosis, immune-related disorders, and mental illnesses, further work is required to robustly validate CNR2 disease links and clarify specific mechanisms linking CNR2 genetic variation to disease pathophysiology and potential drug responses.

Massively parallel characterization of regulatory elements in the developing human cortex

Nucleotide changes in gene regulatory elements are important determinants of neuronal development and diseases. Using massively parallel reporter assays in primary human cells from mid-gestation cortex and cerebral organoids, we interrogated the cis-regulatory activity of 102,767 open chromatin regions, including thousands of sequences with cell type-specific accessibility and variants associated with brain gene regulation. In primary cells, we identified 46,802 active enhancer sequences and 164 variants that alter enhancer activity. Activity was comparable in organoids and primary cells, suggesting that organoids provide an adequate model for the developing cortex. Using deep learning we decoded the sequence basis and upstream regulators of enhancer activity. This work establishes a comprehensive catalog of functional gene regulatory elements and variants in human neuronal development.

CytoSIP: an annotated structural atlas for interactions involving cytokines or cytokine receptors

Therapeutic agents targeting cytokine-cytokine receptor (CK-CKR) interactions lead to the disruption in cellular signaling and are effective in treating many diseases including tumors. However, a lack of universal and quick access to annotated structural surface regions on CK/CKR has limited the progress of a structure-driven approach in developing targeted macromolecular drugs and precision medicine therapeutics. Herein we develop CytoSIP (Single nucleotide polymorphisms (SNPs), Interface, and Phenotype), a rich internet application based on a database of atomic interactions around hotspots in experimentally determined CK/CKR structural complexes. CytoSIP contains: (1) SNPs on CK/CKR; (2) interactions involving CK/CKR domains, including CK/CKR interfaces, oligomeric interfaces, epitopes, or other drug targeting surfaces; and (3) diseases and phenotypes associated with CK/CKR or SNPs. The database framework introduces a unique tri-level SIP data model to bridge genetic variants (atomic level) to disease phenotypes (organism level) using protein structure (complexes) as an underlying framework (molecule level). Customized screening tools are implemented to retrieve relevant CK/CKR subset, which reduces the time and resources needed to interrogate large datasets involving CK/CKR surface hotspots and associated pathologies. CytoSIP portal is publicly accessible at https://CytoSIP.biocloud.top , facilitating the panoramic investigation of the context-dependent crosstalk between CK/CKR and the development of targeted therapeutic agents.

Regional-specific calibration enables application of computational evidence for clinical classification of 5' cis-regulatory variants in Mendelian disease

To date, clinical genetic testing for Mendelian disease variants has focused heavily on exonic coding and intronic gene regions. This multi-step study was undertaken to provide an evidence base for selecting and applying computational approaches for use in clinical classification of 5' cis-regulatory region variants. Curated datasets of clinically reported disease-causing 5' cis-regulatory region variants and variants from matched genomic regions in population controls were used to calibrate six bioinformatic tools as predictors of variant pathogenicity. Likelihood ratio estimates were aligned to code weights following ClinGen recommendations for application of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) classification scheme. Considering code assignment across all reference dataset variants, performance was best for CADD (81.2%) and REMM (81.5%). Optimized thresholds provided moderate evidence toward pathogenicity (CADD, REMM) and moderate (CADD) or supporting (REMM) evidence against pathogenicity. Both sensitivity and specificity of prediction were improved when further categorizing variants based on location in an EPDnew-defined promoter region. Combining predictions (CADD, REMM, and location in a promoter region) increased specificity at the expense of sensitivity. Importantly, the optimal CADD thresholds for assigning ACMG/AMP codes PP3 (≥10) and BP4 (≤8) were vastly different from recommendations for protein-coding variants (PP3 ≥25.3; BP4 ≤22.7); CADD <22.7 would incorrectly assign BP4 for >90% of reported disease-causing cis-regulatory region variants. Our results demonstrate the need to consider a tiered approach and tailored score thresholds to optimize bioinformatic impact prediction for clinical classification of 5' cis-regulatory region variants.

In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene

Single nucleotide polymorphisms (SNPs) are one of the most common determinants and potential biomarkers of human disease pathogenesis. SNPs could alter amino acid residues, leading to the loss of structural and functional integrity of the encoded protein. In humans, members of the minichromosome maintenance (MCM) family play a vital role in cell proliferation and have a significant impact on tumorigenesis. Among the MCM members, the molecular mechanism of how missense SNPs of minichromosome maintenance complex component 6 (MCM6) contribute to DNA replication and tumor pathogenesis is underexplored and needs to be elucidated. Hence, a series of sequence and structure-based computational tools were utilized to determine how mutations affect the corresponding MCM6 protein. From the dbSNP database, among 15,009 SNPs in the MCM6 gene, 642 missense SNPs (4.28%), 291 synonymous SNPs (1.94%), and 12,500 intron SNPs (83.28%) were observed. Out of the 642 missense SNPs, 33 were found to be deleterious during the SIFT analysis. Among these, 11 missense SNPs (I123S, R207C, R222C, L449F, V456M, D463G, H556Y, R602H, R633W, R658C, and P815T) were found as deleterious, probably damaging, affective and disease-associated. Then, I123S, R207C, R222C, V456M, D463G, R602H, R633W, and R658C missense SNPs were found to be highly harmful. Six missense SNPs (I123S, R207C, V456M, D463G, R602H, and R633W) had the potential to destabilize the corresponding protein as predicted by DynaMut2. Interestingly, five high-risk mutations (I123S, V456M, D463G, R602H, and R633W) were distributed in two domains (PF00493 and PF14551). During molecular dynamics simulations analysis, consistent fluctuation in RMSD and RMSF values, high Rg and hydrogen bonds in mutant proteins compared to wild-type revealed that these mutations might alter the protein structure and stability of the corresponding protein. Hence, the results from the analyses guide the exploration of the mechanism by which these missense SNPs of the MCM6 gene alter the structural integrity and functional properties of the protein, which could guide the identification of ways to minimize the harmful effects of these mutations in humans.

MSA: scalable DNA methylation screening BeadChip for high-throughput trait association studies

The Infinium DNA Methylation BeadChips have significantly contributed to population-scale epigenetics research by enabling epigenome-wide trait association discoveries. Here, we design, describe, and experimentally verify a new iteration of this technology, the Methylation Screening Array (MSA), to focus on human trait screening and discovery. This array utilizes extensive data from previous Infinium platform-based epigenome-wide association studies (EWAS). It incorporates knowledge from the latest single-cell and cell type-resolution whole genome methylome profiles. The MSA is engineered to achieve scalable screening of epigenetics-trait association in an ultra-high sample throughput. Our design encompassed diverse human trait associations, including those with genetic, cellular, environmental, and demographical variables and human diseases such as genetic, neurodegenerative, cardiovascular, infectious, and immune diseases. We comprehensively evaluated this array's reproducibility, accuracy, and capacity for cell-type deconvolution and supporting 5-hydroxymethylation profiling in diverse human tissues. Our first atlas data using this platform uncovered the complex chromatin and tissue contexts of DNA modification variations and genetic variants linked to human phenotypes.

Development of multiplexed orthogonal base editor (MOBE) systems

Base editors (BEs) enable efficient, programmable installation of point mutations while avoiding the use of double-strand breaks. Simultaneous application of two or more different BEs, such as an adenine BE (which converts A·T base pairs to G·C) and a cytosine BE (which converts C·G base pairs to T·A), is not feasible because guide RNA crosstalk results in non-orthogonal editing, with all BEs modifying all target loci. Here we engineer both adenine BEs and cytosine BEs that can be orthogonally multiplexed by using RNA aptamer-coat protein systems to recruit the DNA-modifying enzymes directly to the guide RNAs. We generate four multiplexed orthogonal BE systems that enable rates of precise co-occurring edits of up to 7.1% in the same DNA strand without enrichment or selection strategies. The addition of a fluorescent enrichment strategy increases co-occurring edit rates up to 24.8% in human cells. These systems are compatible with expanded protospacer adjacent motif and high-fidelity Cas9 variants, function well in multiple cell types, have equivalent or reduced off-target propensities compared with their parental systems and can model disease-relevant point mutation combinations.

Integrating 16S rRNA profiling and in-silico analysis for an epitope-based vaccine strategy against Achromobacter xylosoxidans infection

Achromobacter xylosoxidans is an aerobic, catalase-positive, non-pigment-forming, Gram-negative, and motile bacterium. It potentially causes a wide range of human infections in cystic fibrosis and non-cystic fibrosis patients. However, developing a safe preventive or therapeutic solution against A. xylosoxidans remains challenging. This study aimed to construct an epitope-based vaccine candidate using immunoinformatic techniques. A. xylosoxidans was isolated from an auto workshop in Lahore, and its identification was confirmed through 16S rRNA amplification and bioinformatic analysis. Two protein targets with GenBank accession numbers AKP90890.1 and AKP90355.1 were selected for the vaccine construct. Both proteins exhibited antigenicity, with scores of 0.757 and 0.580, respectively and the epitopes were selected based on the IC50 value using the ANN 4.0 and NN-align 2.3 epitope prediction method for MHC I and MHC II epitopes respectively and predicted epitopes were analyzed for antigenicity, allergenicity and pathogenicity. The vaccine construct demonstrated structural stability, thermostability, solubility, and hydrophilicity. The vaccine produced 250 B-memory cells per mm3 and approximately 16,000 IgM + IgG counts, indicating an effective immune response against A. xylosoxidans. Moreover, the vaccine candidate interacted stably with toll-like receptor 5, a pattern recognition receptor, with a confidence score of 0.98. These results highlight the potency of the designed vaccine candidate, suggesting its potential to withstand rigorous in vitro and in vivo clinical trials. This epitope-based vaccine could serve as the first preventive immunotherapy against A. xylosoxidans infections, addressing this bacterium's health and financial burdens. The findings demonstrate the value of employing immunoinformatic tools in vaccine development, paving the way for more precise and tailored approaches to combating microbial threats.

MONET: a database for prediction of neoantigens derived from microsatellite loci

Background

Microsatellite instability (MSI) secondary to mismatch repair (MMR) deficiency is characterized by insertions and deletions (indels) in short DNA sequences across the genome. These indels can generate neoantigens, which are ideal targets for precision immune interception. However, current neoantigen databases lack information on neoantigens arising from coding microsatellites. To address this gap, we introduce The MicrOsatellite Neoantigen Discovery Tool (MONET).

Method

MONET identifies potential mutated tumor-specific neoantigens (neoAgs) by predicting frameshift mutations in coding microsatellite sequences of the human genome. Then MONET annotates these neoAgs with key features such as binding affinity, stability, expression, frequency, and potential pathogenicity using established algorithms, tools, and public databases. A user-friendly web interface (https://monet.mdanderson.org/) facilitates access to these predictions.

Results

MONET predicts over 4 million and 15 million Class I and Class II potential frameshift neoAgs, respectively. Compared to existing databases, MONET demonstrates superior coverage (>85% vs. <25%) using a set of experimentally validated neoAgs.

Conclusion

MONET is a freely available, user-friendly web tool that leverages publicly available resources to identify neoAgs derived from microsatellite loci. This systems biology approach empowers researchers in the field of precision immune interception.

A statistical approach for identifying single nucleotide variants that affect transcription factor binding

Non-coding variants located within regulatory elements may alter gene expression by modifying transcription factor (TF) binding sites, thereby leading to functional consequences. Different TF models are being used to assess the effect of DNA sequence variants, such as single nucleotide variants (SNVs). Often existing methods are slow and do not assess statistical significance of results. We investigated the distribution of absolute maximal differential TF binding scores for general computational models that affect TF binding. We find that a modified Laplace distribution can adequately approximate the empirical distributions. A benchmark on in vitro and in vivo datasets showed that our approach improves upon an existing method in terms of performance and speed. Applications on eQTLs and on a genome-wide association study illustrate the usefulness of our statistics by highlighting cell type-specific regulators and target genes. An implementation of our approach is freely available on GitHub and as bioconda package.

Enrichment of a subset of Neanderthal polymorphisms in autistic probands and siblings

Homo sapiens and Neanderthals underwent hybridization during the Middle/Upper Paleolithic age, culminating in retention of small amounts of Neanderthal-derived DNA in the modern human genome. In the current study, we address the potential roles Neanderthal single nucleotide polymorphisms (SNP) may be playing in autism susceptibility in samples of black non-Hispanic, white Hispanic, and white non-Hispanic people using data from the Simons Foundation Powering Autism Research (SPARK), Genotype-Tissue Expression (GTEx), and 1000 Genomes (1000G) databases. We have discovered that rare variants are significantly enriched in autistic probands compared to race-matched controls. In addition, we have identified 25 rare and common SNPs that are significantly enriched in autism on different ethnic backgrounds, some of which show significant clinical associations. We have also identified other SNPs that share more specific genotype-phenotype correlations but which are not necessarily enriched in autism and yet may nevertheless play roles in comorbid phenotype expression (e.g., intellectual disability, epilepsy, and language regression). These results strongly suggest Neanderthal-derived DNA is playing a significant role in autism susceptibility across major populations in the United States.

Mast cell degranulation and bradykinin-induced angioedema - searching for the missing link

Initiation of the bradykinin generation cascade is responsible for the occurrence of attacks in some types of angioedema without wheals. Hereditary angioedema due to C1 inhibitor deficiency (HAE-C1-INH) is one such clinical entity. In this paper, we explore the existing evidence that mast cells (MCs) degranulation may contribute to the activation of the kallikrein-kinin system cascade, followed by bradykinin formation and angioedema. We present the multidirectional effects of MC-derived heparin and other polyanions on the major components of the kinin-kallikrein system, particularly on the factor XII activation. Although, bradykinin- and histamine-mediated symptoms are distinct clinical phenomena, they share some common features, such as some similar triggers and a predilection to occur at sites where mast cells reside, namely the skin and mucous membranes. In addition, recent observations indicate a high incidence of hypersensitivity reactions associated with MC degranulation in the HAE-C1-INH patient population. However, not all of these can be explained by IgE-dependent mechanisms. Mast cell-related G protein-coupled receptor-X2 (MRGPRX2), which has recently attracted scientific interest, may be involved in the activation of MCs through a different pathway. Therefore, we reviewed MRGPRX2 ligands that HAE-C1-INH patients may be exposed to in their daily lives and that may affect MCs degranulation. We also discussed the known inter- and intra-individual variability in the course of HAE-C1-INH in relation to factors responsible for possible variability in the strength of the response to MRGPRX2 receptor stimulation. The above issues raise several questions for future research. It is not known to what extent a prophylactic or therapeutic intervention targeting the pathways of one mechanism (mast cell degranulation) may affect the other (bradykinin production), or whether the number of mast cells at a specific body site and their reactivity to triggers such as pressure, allergens or MRGPRX2 agonists may influence the occurrence of HAE-C1-INH attacks at that site.

Npy transcription is regulated by noncanonical STAT3 signaling in hypothalamic neurons: Implication with lipotoxicity and obesity

Neuropeptide Y (Npy) is an abundant neuropeptide expressed in the central and peripheral nervous systems. NPY-secreting neurons in the hypothalamic arcuate nucleus regulate energy homeostasis, and Npy mRNA expression is regulated by peripheral nutrient and hormonal signals like leptin, interleukin-6 (IL-6), and fatty acids. This study demonstrates that IL-6, which phosphorylates tyrosine 705 (Y705) of STAT3, decreased Npy mRNA in arcuate immortalized hypothalamic neurons. In parallel, inhibitors of STAT3-Y705 phosphorylation, stattic and cucurbitacin I, robustly upregulated Npy mRNA. Chromatin-immunoprecipitation showed high baseline total STAT3 binding to multiple regulatory regions of the Npy gene, which are decreased by IL-6 exposure. The STAT3-Npy interaction was further examined in obesity-related pathologies. Notably, in four different hypothalamic neuronal models where palmitate potently stimulated Npy mRNA, Socs3, a specific STAT3 activity marker, was downregulated and was negatively correlated with Npy mRNA levels (R2 = 0.40, p < 0.001), suggesting that disrupted STAT3 signaling is involved in lipotoxicity-mediated dysregulation of Npy. Finally, human NPY SNPs that map to human obesity or body mass index were investigated for potential STAT3 binding sites. Although none of the SNPs were linked to direct STAT3 binding, analysis show that rs17149106 (-602 G > T) is located on an upstream enhancer element of NPY, where the variant is predicted to disrupt validated binding of KLF4, a known inhibitory cofactor of STAT3 and downstream effector of leptin signaling. Collectively, this study demonstrates that STAT3 signaling negatively regulates Npy transcription, and that disruption of this interaction may contribute to metabolic disorders.

Accelerated somatic mutation calling for whole-genome and whole-exome sequencing data from heterogenous tumor samples

Accurate detection of somatic mutations in DNA sequencing data is a fundamental prerequisite for cancer research. Previous analytical challenges were overcome by consensus mutation calling from four to five popular callers. This, however, increases the already nontrivial computing time from individual callers. Here, we launch MuSE 2, powered by multistep parallelization and efficient memory allocation, to resolve the computing time bottleneck. MuSE 2 speeds up 50 times more than MuSE 1 and eight to 80 times more than other popular callers. Our benchmark study suggests combining MuSE 2 and the recently accelerated Strelka2 achieves high efficiency and accuracy in analyzing large cancer genomic data sets.

Genetic polymorphisms affecting telomere length and their association with cardiovascular disease in the Heinz-Nixdorf-Recall study

Short telomeres are associated with cardiovascular disease (CVD). We aimed to investigate, if genetically determined telomere-length effects CVD-risk in the Heinz-Nixdorf-Recall study (HNRS) population. We selected 14 single-nucleotide polymorphisms (SNPs) associated with telomere-length (p<10-8) from the literature and after exclusion 9 SNPs were included in the analyses. Additionally, a genetic risk score (GRS) using these 9 SNPs was calculated. Incident CVD was defined as fatal and non-fatal myocardial infarction, stroke, and coronary death. We included 3874 HNRS participants with available genetic data and had no known history of CVD at baseline. Cox proportional-hazards regression was used to test the association between the SNPs/GRS and incident CVD-risk adjusting for common CVD risk-factors. The analyses were further stratified by CVD risk-factors. During follow-up (12.1±4.31 years), 466 participants experienced CVD-events. No association between SNPs/GRS and CVD was observed in the adjusted analyses. However, the GRS, rs10936599, rs2487999 and rs8105767 increase the CVD-risk in current smoker. Few SNPs (rs10936599, rs2487999, and rs7675998) showed an increased CVD-risk, whereas rs10936599, rs677228 and rs4387287 a decreased CVD-risk, in further strata. The results of our study suggest different effects of SNPs/GRS on CVD-risk depending on the CVD risk-factor strata, highlighting the importance of stratified analyses in CVD risk-factors.

Common variation in a long non-coding RNA gene modulates variation of circulating TGF-β2 levels in metastatic colorectal cancer patients (Alliance)

BACKGROUND

Herein, we report results from a genome-wide study conducted to identify protein quantitative trait loci (pQTL) for circulating angiogenic and inflammatory protein markers in patients with metastatic colorectal cancer (mCRC). The study was conducted using genotype, protein marker, and baseline clinical and demographic data from CALGB/SWOG 80405 (Alliance), a randomized phase III study designed to assess outcomes of adding VEGF or EGFR inhibitors to systemic chemotherapy in mCRC patients. Germline DNA derived from blood was genotyped on whole-genome array platforms. The abundance of protein markers was quantified using a multiplex enzyme-linked immunosorbent assay from plasma derived from peripheral venous blood collected at baseline. A robust rank-based method was used to assess the statistical significance of each variant and protein pair against a strict genome-wide level. A given pQTL was tested for validation in two external datasets of prostate (CALGB 90401) and pancreatic cancer (CALGB 80303) patients. Bioinformatics analyses were conducted to further establish biological bases for these findings.

RESULTS

The final analysis was carried out based on data from 540,021 common typed genetic variants and 23 protein markers from 869 genetically estimated European patients with mCRC. Correcting for multiple testing, the analysis discovered a novel cis-pQTL in LINC02869, a long non-coding RNA gene, for circulating TGF-β2 levels (rs11118119; AAF = 0.11; P-value < 1.4e-14). This finding was validated in a cohort of 538 prostate cancer patients from CALGB 90401 (AAF = 0.10, P-value < 3.3e-25). The analysis also validated a cis-pQTL we had previously reported for VEGF-A in advanced pancreatic cancer, and additionally identified trans-pQTLs for VEGF-R3, and cis-pQTLs for CD73.

CONCLUSIONS

This study has provided evidence of a novel cis germline genetic variant that regulates circulating TGF-β2 levels in plasma of patients with advanced mCRC and prostate cancer. Moreover, the validation of previously identified pQTLs for VEGF-A, CD73, and VEGF-R3, potentiates the validity of these associations.

Integrated electrophysiological and genomic profiles of single cells reveal spiking tumor cells in human glioma

Prior studies have described the complex interplay that exists between glioma cells and neurons, however, the electrophysiological properties endogenous to tumor cells remain obscure. To address this, we employed Patch-sequencing on human glioma specimens and found that one third of patched cells in IDH mutant (IDH mut ) tumors demonstrate properties of both neurons and glia by firing single, short action potentials. To define these hybrid cells (HCs) and discern if they are tumor in origin, we developed a computational tool, Single Cell Rule Association Mining (SCRAM), to annotate each cell individually. SCRAM revealed that HCs represent tumor and non-tumor cells that feature GABAergic neuron and oligodendrocyte precursor cell signatures. These studies are the first to characterize the combined electrophysiological and molecular properties of human glioma cells and describe a new cell type in human glioma with unique electrophysiological and transcriptomic properties that are likely also present in the non-tumor mammalian brain.

An Integrated Framework for Analysis and Prediction of Impact of Single Nucleotide Polymorphism Associated with Human Diseases

Single nucleotide polymorphisms are most common type of genetic variation in human genome. Analyzing genetic variants can help us better understand the genetic basis of diseases and develop predictive models which are useful to identify individuals who are at increased risk for certain diseases. Several SNP analysis tools have already been developed. For running these tools, the user needs to collect data from various databases. Secondly, often researchers have to use multiple variant analysis tools for cross validating their results and increase confidence in their findings. Extracting data from multiple databases and running multiple tools at a time, increases complexity and time required for analysis. There are some web-based tools that integrate multiple genetic variant databases and provide variant annotations for a few tools. These approaches have some limitations such as retrieving annotation information, filtering common pathogenic variants. The proposed web-based tool, namely IPSNP: An Integrated Platform for Predicting Impact of SNPs is written in Django which is a python-based framework. It uses RESTful API of MyVariant.info to extract annotation information of variants associated with a given gene, rsID, HGVS format variants specified in a VCF file for 29 tools. The results are in the form of a CSV file of predictions (1) derived from the consensus decision, (2) a file having annotations for the variants associated with the given gene, (3) a file showing variants declared as pathogenic commonly by the selected tools, and (4) a CSV file containing chromosome coordinates based on GRCh37 and GRCh38 genome assemblies, rsIDs and proteomic data, so that users may use tools of their choice and avoiding manual parameter collection for each tool. IPSNP is a valuable resource for researchers and clinicians and it can help to save time and effort in discovering the novel disease-associated variants and the development of personalized treatments.

All exons are not created equal-exon vulnerability determines the effect of exonic mutations on splicing

It is now widely accepted that aberrant splicing of constitutive exons is often caused by mutations affecting cis-acting splicing regulatory elements (SREs), but there is a misconception that all exons have an equal dependency on SREs and thus a similar vulnerability to aberrant splicing. We demonstrate that some exons are more likely to be affected by exonic splicing mutations (ESMs) due to an inherent vulnerability, which is context dependent and influenced by the strength of exon definition. We have developed VulExMap, a tool which is based on empirical data that can designate whether a constitutive exon is vulnerable. Using VulExMap, we find that only 25% of all exons can be categorized as vulnerable, whereas two-thirds of 359 previously reported ESMs in 75 disease genes are located in vulnerable exons. Because VulExMap analysis is based on empirical data on splicing of exons in their endogenous context, it includes all features important in determining the vulnerability. We believe that VulExMap will be an important tool when assessing the effect of exonic mutations by pinpointing whether they are located in exons vulnerable to ESMs.

Longitudinal molecular profiling elucidates immunometabolism dynamics in breast cancer

Although metabolic reprogramming within tumor cells and tumor microenvironment (TME) is well described in breast cancer, little is known about how the interplay of immune state and cancer metabolism evolves during treatment. Here, we characterize the immunometabolic profiles of tumor tissue samples longitudinally collected from individuals with breast cancer before, during and after neoadjuvant chemotherapy (NAC) using proteomics, genomics and histopathology. We show that the pre-, on-treatment and dynamic changes of the immune state, tumor metabolic proteins and tumor cell gene expression profiling-based metabolic phenotype are associated with treatment response. Single-cell/nucleus RNA sequencing revealed distinct tumor and immune cell states in metabolism between cold and hot tumors. Potential drivers of NAC based on above analyses were validated in vitro. In summary, the study shows that the interaction of tumor-intrinsic metabolic states and TME is associated with treatment outcome, supporting the concept of targeting tumor metabolism for immunoregulation.

Characterization of the Common Genetic Variation in the Spanish Population of Navarre

Large-scale genomic studies have significantly increased our knowledge of genetic variability across populations. Regional genetic profiling is essential for distinguishing common benign variants from disease-causing ones. To this end, we conducted a comprehensive characterization of exonic variants in the population of Navarre (Spain), utilizing whole genome sequencing data from 358 unrelated individuals of Spanish origin. Our analysis revealed 61,410 biallelic single nucleotide variants (SNV) within the Navarrese cohort, with 35% classified as common (MAF > 1%). By comparing allele frequency data from 1000 Genome Project (excluding the Iberian cohort of Spain, IBS), Genome Aggregation Database, and a Spanish cohort (including IBS individuals and data from Medical Genome Project), we identified 1069 SNVs common in Navarre but rare (MAF ≤ 1%) in all other populations. We further corroborated this observation with a second regional cohort of 239 unrelated exomes, which confirmed 676 of the 1069 SNVs as common in Navarre. In conclusion, this study highlights the importance of population-specific characterization of genetic variation to improve allele frequency filtering in sequencing data analysis to identify disease-causing variants.

An overview of autosomal STRs and identity SNPs in a Norwegian population using massively parallel sequencing

In recent years, probabilistic genotyping software has been adapted for the analysis of massively parallel sequencing (MPS) forensic data. Likelihood ratios (LR) are based on allele frequencies selected from populations of interest. This study provides an outline of sequence-based (SB) allele frequencies for autosomal short tandem repeats (aSTRs) and identity single nucleotide polymorphisms (iSNPs) in 371 individuals from Southern Norway. 27 aSTRs and 94 iSNPs were previously analysed with the ForenSeq™ DNA Signature Prep Kit (Verogen). The number of alleles with frequencies less than 0.05 for sequenced-based alleles was 4.6 times higher than for length-based alleles. Consistent with previous studies, it was observed that sequence-based data (both with and without flanks) exhibited higher allele diversity compared to length-based (LB) data; random match probabilities were lower for SB alleles confirming their advantage to discriminate between individuals. Two alleles in markers D22S1045 and Penta D were observed with SNPs in the 3´ flanking region, which have not been reported before. Also, a novel SNP with a minor allele frequency (MAF) of 0.001, was found in marker TH01. The impact of the sample size on minor allele frequency (MAF) values was studied in 88 iSNPs from Southern Norway (n = 371). The findings were then compared to a larger Norwegian population dataset (n = 15,769). The results showed that the smaller Southern Norway dataset provided similar results, and it was a representative sample. Population structure was analyzed for regions within Southern Norway; FST estimates for aSTR and iSNPs did not indicate any genetic structure. Finally, we investigated the genetic differences between Southern Norway and two other populations: Northern Norway and Denmark. Allele frequencies between these populations were compared, and we found no significant frequency differences (p-values > 0.0001). We also calculated the pairwise FST values per marker and comparisons between Southern and Northern Norway showed small differences. In contrast, the comparisons between Southern Norway and Denmark showed higher FST values for some markers, possibly driven by distinct alleles that were present in only one of the populations. In summary, we propose that allele frequencies from each population considered in this study could be used interchangeably to calculate genotype probabilities.

The association between single-nucleotide polymorphisms within type 1 interferon pathway genes and human immunodeficiency virus type 1 viral load in antiretroviral-naïve participants

BACKGROUND

Human genetic contribution to HIV progression remains inadequately explained. The type 1 interferon (IFN) pathway is important for host control of HIV and variation in type 1 IFN genes may contribute to disease progression. This study assessed the impact of variations at the gene and pathway level of type 1 IFN on HIV-1 viral load (VL).

METHODS

Two cohorts of antiretroviral (ART) naïve participants living with HIV (PLWH) with either early (START) or advanced infection (FIRST) were analysed separately. Type 1 IFN genes (n = 17) and receptor subunits (IFNAR1, IFNAR2) were examined for both cumulated type 1 IFN pathway analysis and individual gene analysis. SKAT-O was applied to detect associations between the genotype and HIV-1 study entry viral load (log10 transformed) as a proxy for set point VL; P-values were corrected using Bonferroni (P < 0.0025).

RESULTS

The analyses among those with early infection included 2429 individuals from five continents. The median study entry HIV VL was 14,623 (IQR 3460-45100) copies/mL. Across 673 SNPs within 19 type 1 IFN genes, no significant association with study entry VL was detected. Conversely, examining individual genes in START showed a borderline significant association between IFNW1, and study entry VL (P = 0.0025). This significance remained after separate adjustments for age, CD4+ T-cell count, CD4+/CD8+ T-cell ratio and recent infection. When controlling for population structure using linear mixed effects models (LME), in addition to principal components used in the main model, this was no longer significant (p = 0.0244). In subgroup analyses stratified by geographical region, the association between IFNW1 and study entry VL was only observed among African participants, although, the association was not significant when controlling for population structure using LME. Of the 17 SNPs within the IFNW1 region, only rs79876898 (A > G) was associated with study entry VL (p = 0.0020, beta = 0.32; G associated with higher study entry VL than A) in single SNP association analyses. The findings were not reproduced in FIRST participants.

CONCLUSION

Across 19 type 1 IFN genes, only IFNW1 was associated with HIV-1 study entry VL in a cohort of ART-naïve individuals in early stages of their infection, however, this was no longer significant in sensitivity analyses that controlled for population structures using LME.

DiSMVC: a multi-view graph collaborative learning framework for measuring disease similarity

MOTIVATION

Exploring potential associations between diseases can help in understanding pathological mechanisms of diseases and facilitating the discovery of candidate biomarkers and drug targets, thereby promoting disease diagnosis and treatment. Some computational methods have been proposed for measuring disease similarity. However, these methods describe diseases without considering their latent multi-molecule regulation and valuable supervision signal, resulting in limited biological interpretability and efficiency to capture association patterns.

RESULTS

In this study, we propose a new computational method named DiSMVC. Different from existing predictors, DiSMVC designs a supervised graph collaborative framework to measure disease similarity. Multiple bio-entity associations related to genes and miRNAs are integrated via cross-view graph contrastive learning to extract informative disease representation, and then association pattern joint learning is implemented to compute disease similarity by incorporating phenotype-annotated disease associations. The experimental results show that DiSMVC can draw discriminative characteristics for disease pairs, and outperform other state-of-the-art methods. As a result, DiSMVC is a promising method for predicting disease associations with molecular interpretability.

AVAILABILITY AND IMPLEMENTATION

Datasets and source codes are available at https://github.com/Biohang/DiSMVC.

Early Immune Remodeling Steers Clinical Response to First-Line Chemoimmunotherapy in Advanced Gastric Cancer

Adding anti-programmed cell death protein 1 (anti-PD-1) to 5-fluorouracil (5-FU)/platinum improves survival in some advanced gastroesophageal adenocarcinomas (GEA). To understand the effects of chemotherapy and immunotherapy, we conducted a phase II first-line trial (n = 47) sequentially adding pembrolizumab to 5-FU/platinum in advanced GEA. Using serial biopsy of the primary tumor at baseline, after one cycle of 5-FU/platinum, and after the addition of pembrolizumab, we transcriptionally profiled 358,067 single cells to identify evolving multicellular tumor microenvironment (TME) networks. Chemotherapy induced early on-treatment multicellular hubs with tumor-reactive T-cell and M1-like macrophage interactions in slow progressors. Faster progression featured increased MUC5A and MSLN containing treatment resistance programs in tumor cells and M2-like macrophages with immunosuppressive stromal interactions. After pembrolizumab, we observed increased CD8 T-cell infiltration and development of an immunity hub involving tumor-reactive CXCL13 T-cell program and epithelial interferon-stimulated gene programs. Strategies to drive increases in antitumor immune hub formation could expand the portion of patients benefiting from anti-PD-1 approaches.

SIGNIFICANCE

The benefit of 5-FU/platinum with anti-PD-1 in first-line advanced gastric cancer is limited to patient subgroups. Using a trial with sequential anti-PD-1, we show coordinated induction of multicellular TME hubs informs the ability of anti-PD-1 to potentiate T cell-driven responses. Differential TME hub development highlights features that underlie clinical outcomes. This article is featured in Selected Articles from This Issue, p. 695.

regionalpcs: improved discovery of DNA methylation associations with complex traits

We have developed the regional principal components (rPCs) method, a novel approach for summarizing gene-level methylation. rPCs address the challenge of deciphering complex epigenetic mechanisms in diseases like Alzheimer's disease (AD). In contrast to traditional averaging, rPCs leverage principal components analysis to capture complex methylation patterns across gene regions. Our method demonstrated a 54% improvement in sensitivity over averaging in simulations, offering a robust framework for identifying subtle epigenetic variations. Applying rPCs to the AD brain methylation data in ROSMAP, combined with cell type deconvolution, we uncovered 838 differentially methylated genes associated with neuritic plaque burden-significantly outperforming conventional methods. Integrating methylation quantitative trait loci (meQTL) with genome-wide association studies (GWAS) identified 17 genes with potential causal roles in AD, including MS4A4A and PICALM. Our approach is available in the Bioconductor package regionalpcs, opening avenues for research and facilitating a deeper understanding of the epigenetic landscape in complex diseases.

Polymorphisms in LRP2 and CUBN genes and their association with serum vitamin D levels and sleep apnea

PURPOSE

Vitamin D deficiency has been associated with the occurrence of obstructive sleep apnea syndrome (OSAS). Megalin (LRP2) and cubilin (CUBN) are implicated in vitamin D metabolism, whereas LRP2 and CUBN polymorphisms have been previously associated with variable serum vitamin D levels. The present study aimed to evaluate the role of LRP2 rs2228171 c.8614C > T and CUBN rs1801222 c.758A > G polymorphisms in OSAS susceptibility, independently or in synergy with vitamin D levels.

METHODS

Vitamin D serum concentration of consecutive individuals was measured. PCR-RFLP was used for LRP2 rs2228171 and CUBN rs1801222 genotyping.

RESULTS

A total of 176 individuals was enrolled, including 144 patients with OSAS and 32 controls. Frequency of LRP2 rs2228171 c.8614 T and CUBN rs1801222 c.758G alleles was estimated at 22.4% and 79.8%, respectively. LRP2 and CUBN polymorphisms were not associated with OSAS occurrence (rs2228171Τ allele: 22.9% in OSAS group vs. 20.3% in controls, p = 0.651; rs1801222A allele 19.4% in OSAS group vs. 23.4% in controls, p = 0.471). Frequency of CUBN rs1801222A allele carriers was increased in patients with moderate or severe OSAS compared to mild OSAS (p = 0.028). Patients with OSAS homozygous for LRP2 CC and CUBN GG genotypes had lower vitamin D serum concentration compared to controls carrying the same genotype (18.0 vs 27.0 ng/mL, p = 0.006 and 19.0 vs 27.5 ng/mL, p = 0.007, respectively).

CONCLUSION

CUBN rs1801222 polymorphism may affect OSAS severity. Among other factors, low vitamin D concentration is associated with OSAS occurrence, irrespectively of LRP2 and CUBN polymorphisms.

Nuclear export is a limiting factor in eukaryotic mRNA metabolism

The eukaryotic mRNA life cycle includes transcription, nuclear mRNA export and degradation. To quantify all these processes simultaneously, we perform thiol-linked alkylation after metabolic labeling of RNA with 4-thiouridine (4sU), followed by sequencing of RNA (SLAM-seq) in the nuclear and cytosolic compartments of human cancer cells. We develop a model that reliably quantifies mRNA-specific synthesis, nuclear export, and nuclear and cytosolic degradation rates on a genome-wide scale. We find that nuclear degradation of polyadenylated mRNA is negligible and nuclear mRNA export is slow, while cytosolic mRNA degradation is comparatively fast. Consequently, an mRNA molecule generally spends most of its life in the nucleus. We also observe large differences in the nuclear export rates of different 3'UTR transcript isoforms. Furthermore, we identify genes whose expression is abruptly induced upon metabolic labeling. These transcripts are exported substantially faster than average mRNAs, suggesting the existence of alternative export pathways. Our results highlight nuclear mRNA export as a limiting factor in mRNA metabolism and gene regulation.

Exceptional Response of BRAFV600E-Mutated Acinar Cell CUP to BRAF/MEK Inhibition

Complete remission of BRAF V600E-driven ACC CUP by BRAF/MEK inhibition underscores importance of precision oncology.

Development of a novel five-dye panel for human identification insertion/deletion (INDEL) polymorphisms

DNA analysis of forensic case samples relies on short tandem repeats (STRs), a key component of the combined DNA index system (CODIS) used to identify individuals. However, limitations arise when dealing with challenging samples, prompting the exploration of alternative markers such as single nucleotide polymorphisms (SNPs) and insertion/deletion (INDELs) polymorphisms. Unlike SNPs, INDELs can be differentiated easily by size, making them compatible with electrophoresis methods. It is possible to design small INDEL amplicons (<200 bp) to enhance recovery from degraded samples. To this end, a set of INDEL Human Identification Markers (HID) was curated from the 1000 Genomes Project, employing criteria including a fixation index (FST) ≤ 0.06, minor allele frequency (MAF) >0.2, and high allele frequency divergence. A panel of 33 INDEL-HIDs was optimized and validated following the Scientific Working Group on DNA Analysis Methods (SWGDAM) guidelines, utilizing a five-dye multiplex electrophoresis system. A small sample set (n = 79 unrelated individuals) was genotyped to assess the assay's performance. The validation studies exhibited reproducibility, inhibition tolerance, ability to detect a two-person mixture from a 4:1 to 1:6 ratio, robustness with challenging samples, and sensitivity down to 125 pg of DNA. In summary, the 33-loci INDEL-HID panel exhibited robust recovery with low-template and degraded samples and proved effective for individualization within a small sample set.

Evaluation of the pathogenic potential of germline DDX41 variants in hematopoietic neoplasms using the ACMG/AMP guidelines

Clinical use of gene panel testing for hematopoietic neoplasms in areas, such as diagnosis, prognosis prediction, and exploration of treatment options, has increased in recent years. The keys to interpreting gene variants detected in gene panel testing are to distinguish between germline and somatic variants and accurately determine whether the detected variants are pathogenic. If a variant is suspected to be a pathogenic germline variant, it is essential to confirm its consistency with the disease phenotype and gather a thorough family history. Donor eligibility must also be considered, especially if the patient's variant is also detected in the expected donor for hematopoietic stem cell transplantation. However, determining the pathogenicity of gene variants is often complicated, given the current limited availability of databases covering germline variants of hematopoietic neoplasms. This means that hematologists will frequently need to interpret gene variants themselves. Here, we outline how to assess the pathogenicity of germline variants according to criteria from the American College of Medical Genetics and Genomics/Association for Molecular Pathology standards and guidelines for the interpretation of variants using DDX41, a gene recently shown to be closely associated with myeloid neoplasms with a germline predisposition, as an example.

Transcriptome analysis of primary adult B-cell lineage acute lymphoblastic leukemia identifies pathogenic variants and gene fusions, and predicts subtypes for in depth molecular diagnosis

BACKGROUND

B-cell acute lymphoblastic leukemia (B-ALL) is classified into subgroups based on known driver oncogenes and molecular lesions, including translocations and recurrent mutations. However, the current diagnostic tests do not identify subtypes or oncogenic lesions for all B-ALL samples, creating a heterogeneous B-ALL group of unknown subtypes.

METHODS

We sorted primary adult B-ALL cells and performed transcriptome analysis by bulk RNA sequencing (RNA-seq).

RESULTS

Transcriptomic analysis of an adult B-ALL cohort allowed the classification of four patient samples with subtypes that were not previously revealed by standard gene panels. The leukemia of two patients were of the DUX4 subtype and two were CRLF2+ Ph-like B-ALL. Furthermore, single nucleotide variant analysis detected the oncogenic NRAS-G12D, KRAS-G12D, and KRAS-G13D mutations in three of the patient samples, presenting targetable mutations. Additional oncogenic variants and gene fusions were uncovered, as well as multiple variants in the PDE4DIP gene across five of the patient samples.

CONCLUSION

We demonstrate that RNA-seq is an effective tool for precision medicine in B-ALL by providing comprehensive molecular profiling of leukemia cells, identifying subtype and oncogenic lesions, and stratifying patients for appropriate therapy.

CNVoyant: A Highly Performant and Explainable Multi-Classifier Machine Learning Approach for Determining the Clinical Significance of Copy Number Variants

The precise classification of copy number variants (CNVs) presents a significant challenge in genomic medicine, primarily due to the complex nature of CNVs and their diverse impact on genetic disorders. This complexity is compounded by the limitations of existing methods in accurately distinguishing between benign, uncertain, and pathogenic CNVs. Addressing this gap, we introduce CNVoyant, a machine learning-based multi-class framework designed to enhance the clinical significance classification of CNVs. Trained on a comprehensive dataset of 52,176 ClinVar entries across pathogenic, uncertain, and benign classifications, CNVoyant incorporates a broad spectrum of genomic features, including genome position, disease-gene annotations, dosage sensitivity, and conservation scores. Models to predict the clinical significance of copy number gains and losses were trained independently. Final models were selected after testing 29 machine learning architectures and 10,000 hyperparameter combinations each for deletions and duplications via 5-fold cross-validation. We validate the performance of the CNVoyant by leveraging a comprehensive set of 21,574 CNVs from the DECIPHER database, a highly regarded resource known for its extensive catalog of chromosomal imbalances linked to clinical outcomes. Compared to alternative approaches, CNVoyant shows marked improvements in precision-recall and ROC AUC metrics for binary pathogenic classifications while going one step further, offering multi-classification of clinical significance and corresponding SHAP explainability plots. This large-scale validation demonstrates CNVoyant's superior accuracy and underscores its potential to aid genomic researchers and clinical geneticists in interpreting the clinical implications of real CNVs.

Understanding the determinants of sweet taste liking in the African and East Asian ancestry groups in the U.S.-A study protocol

BACKGROUND

The liking for sweet taste is a powerful driver for consuming added sugars, and therefore, understanding how sweet liking is formed is a critical step in devising strategies to lower added sugars consumption. However, current research on the influence of genetic and environmental factors on sweet liking is mostly based on research conducted with individuals of European ancestry. Whether these results can be generalized to people of other ancestry groups warrants investigation.

METHODS

We will determine the differences in allele frequencies in sweet-related genetic variants and their effects on sweet liking in 426 adults of either African or East Asian ancestry, who have the highest and lowest average added sugars intake, respectively, among ancestry groups in the U.S. We will collect information on participants' sweet-liking phenotype, added sugars intake (sweetness exposure), anthropometric measures, place-of-birth, and for immigrants, duration of time living in the U.S. and age when immigrated. Ancestry-specific polygenic scores of sweet liking will be computed based on the effect sizes of the sweet-related genetic variants on the sweet-liking phenotype for each ancestry group. The predictive validity of the polygenic scores will be tested using individuals of African and East Asian ancestry from the UK Biobank. We will also compare sweet liking between U.S.-born individuals and immigrants within each ancestry group to test whether differences in environmental sweetness exposure during childhood affect sweet liking in adulthood.

DISCUSSION

Expanding genetic research on taste to individuals from ancestry groups traditionally underrepresented in such research is consistent with equity goals in sensory and nutrition science. Findings from this study will help in the development of a more personalized nutrition approach for diverse populations.

TRIAL REGISTRATION

This protocol has been preregistered with the Center for Open Science (https://doi.org/10.17605/OSF.IO/WPR9E).

Syndromic ciliopathy: a taiwanese single-center study

BACKGROUND

Syndromic ciliopathies are a group of congenital disorders characterized by broad clinical and genetic overlap, including obesity, visual problems, skeletal anomalies, mental retardation, and renal diseases. The hallmark of the pathophysiology among these disorders is defective ciliary functions or formation. Many different genes have been implicated in the pathogenesis of these diseases, but some patients still remain unclear about their genotypes.

METHODS

The aim of this study was to identify the genetic causes in patients with syndromic ciliopathy. Patients suspected of or meeting clinical diagnostic criteria for any type of syndromic ciliopathy were recruited at a single diagnostic medical center in Southern Taiwan. Whole exome sequencing (WES) was employed to identify their genotypes and elucidate the mutation spectrum in Taiwanese patients with syndromic ciliopathy. Clinical information was collected at the time of patient enrollment.

RESULTS

A total of 14 cases were molecularly diagnosed with syndromic ciliopathy. Among these cases, 10 had Bardet-Biedl syndrome (BBS), comprising eight BBS2 patients and two BBS7 patients. Additionally, two cases were diagnosed with Alström syndrome, one with Oral-facial-digital syndrome type 14, and another with Joubert syndrome type 10. A total of 4 novel variants were identified. A recurrent splice site mutation, BBS2: c.534 + 1G > T, was present in all eight BBS2 patients, suggesting a founder effect. One BBS2 patient with homozygous c.534 + 1G > T mutations carried a third ciliopathic allele, TTC21B: c.264_267dupTAGA, a nonsense mutation resulting in a premature stop codon and protein truncation.

CONCLUSIONS

Whole exome sequencing (WES) assists in identifying molecular pathogenic variants in ciliopathic patients, as well as the genetic hotspot mutations in specific populations. It should be considered as the first-line genetic testing for heterogeneous disorders characterized by the involvement of multiple genes and diverse clinical manifestations.