Non-synonymous Single Nucleotide Variants Research Articles

Clinico-genomic findings, molecular docking, and mutational spectrum in an understudied population with breast cancer patients from KP, Pakistan

In this study, we report the mutational profiles, pathogenicity, and their association with different clinicopathologic and sociogenetic factors in patients with Pashtun ethnicity for the first time. A total of 19 FFPE blocks of invasive ductal carcinoma (IDC) from the Breast Cancer (BC) tissue and 6 normal FFPE blocks were analyzed by whole-exome sequencing (WES). Various somatic and germline mutations were identified in cancer-related genes, i.e., ATM, CHEK2, PALB2, and XRCC2. Among a total of 18 mutations, 14 mutations were somatic and 4 were germline. The ATM gene exhibited the maximum number of mutations (11/18), followed by CHEK2 (3/18), PALB2 (3/18), and XRCC2 (1/18). Except one frameshift deletion, all other 17 mutations were nonsynonymous single-nucleotide variants (SNVs). SIFT prediction revealed 7/18 (38.8%) mutations as deleterious. PolyPhen-2 and MutationTaster identified 5/18 (27.7%) mutations as probably damaging and 10/18 (55.5%) mutations as disease-causing, respectively. Mutations like PALB2 p.Q559R (6/19; 31.5%), XRCC2 p.R188H (5/19; 26.31%), and ATM p.D1853N (4/19; 21.05%) were recurrent mutations and proposed to have a biomarker potential. The protein network prediction was performed using GeneMANIA and STRING. ISPRED-SEQ indicated three interaction site mutations which were further used for molecular dynamic simulation. An average increase in the radius of gyration was observed in all three mutated proteins revealing their perturbed folding behavior. Obtained SNVs were further correlated with various parameters related to the clinicopathological status of the tumors. Three mutation positions (ATMp. D1853N, CHEK2 p.M314I, and PALB2 p.T1029S) were found to be highly conserved. Finally, the wild- and mutant-type proteins were screened for two drugs: elagolix (DrugBank ID: DB11979) and LTS0102038 (a triterpenoid, isolated from the anticancer medicinal plant Fagonia indica). Comparatively, a higher number of interactions were noted for normal ATM with both compounds, as compared to mutants.

Pilot Study on the Prevalence of Diamine Oxidase Gene Variants in Patients with Symptoms of Histamine Intolerance.

A retrospective pilot study was carried out to investigate the prevalence of four variants of the diamine oxidase (DAO) encoding gene (AOC1) in Caucasian adults with symptoms of histamine intolerance. In a cohort of 100 patients and 100 healthy individuals, DAO-encoding gene non-synonymous Single Nucleotide Variations (SNVs) were genotyped by multiplex single-nucleotide primer extension (SNPE) and capillary electrophoresis, and serum DAO activity was analyzed with a radio-extraction assay. The study found that 79% of individuals with symptoms of histamine intolerance harbored one or more of the four SNVs associated with reduced DAO activity. No significant differences were found in the prevalence of any variant between the group of patients and healthy controls. However, when considering the status of the alleles associated with DAO deficiency, more homozygous alleles were observed in histamine-intolerant patients. Moreover, a slightly but statistically higher percentage of patients had a high genetic risk score, reflecting the cumulative effect of carrying multiple DAO deficiency-associated gene variants and a high load of risk alleles (homozygous). A relationship between serum DAO activity and the genetic load of one specific SNV was observed, with DAO activity being significantly lower in patients homozygous for rs2052129. These results potentially support that carrying multiple DAO deficiency-associated gene variants and a high load of risk alleles (homozygous) is more relevant than the mere presence of one or more SNVs. Further studies are needed to determine the predictive value of these DAO-encoding gene variants.

Abstract 1622: Characterization of the phylogenetic relationships in bilateral breast angiosarcoma

Abstract Background: Breast angiosarcoma represents around 20% of all angiosarcomas, and often spread to lung, liver, and bones. Driver mutations of angiosarcoma, specifically PTPRB, and PLCG1, are well-known as reported previously. Notably, contralateral breast is another metastatic site of the breast angiosarcoma, where an unusual location for other soft tissue sarcomas. However, it remains uncertain whether the contralateral disease originates from the primary tumor or emerges independently. Here, we present a 75-year-old woman with bilateral breast angiosarcomas to investigate the genetic relationship between the tumors. Methods: Irregular and heterogeneous masses were synchronously detected through breast sonography. Whole genome sequencing (WGS) was conducted at 60X coverage using bilateral total mastectomies, along with a matched normal blood sample (n=1). Single nucleotide variants (SNVs) and small indels were identified using Strelka2 and Varscan2. Subsequent filtering was performed using custom Python scripts to establish high-confidence variants. A phylogenetic tree was then reconstructed based on SNVs to trace clonal evolution and distinguish between de novo primary and metastasis. Following this, COSMIC mutational signatures were analyzed to characterize the genomic profile. Results: For the left breast angiosarcoma, we found 1,086 SNVs and 101 indels, while the right breast angiosarcoma had 921 SNVs and 92 indels. Despite their small size (<1.0 cm) and low FNCLCC grade (G1), these two cancers shared 600 SNVs and 135 indels as “truncal events”, indicating that one side metastasized from the other. According to the phylogenetic tree and the molecular clock of the two angiosarcomas, we estimated that the metastasis occurred during the middle stages of cancer evolution. Additionally, we identified 7 nonsynonymous SNVs (ADAMTS7, RPS15, CYP2A6, OR1S2, ARHGAP23, GNAQ, UGT2B7), five of which were shared. Remarkably, the GNAQ driver mutation exhibited a mutation at codon 209, a hotspot mutation not previously reported in breast angiosarcoma. The dominant Cosmic mutational signatures were SBS1/5 and ID1/2, all of which were associated with aging. Conclusion: Our findings demonstrate that bilateral breast angiosarcomas metastasized from one side to the other, as evidenced by the WGS data. This study underscores that the capability of WGS to distinguish between oligometastatic disease and multiple primary cancers, which has implications for predicting patients’ prognosis. Citation Format: Minju Kim, Jeonghwan Youk, Soyeon Kim, Miso Kim, Bhumsuk Keam, Tae Min Kim, Dong-Wan Kim, Myung Geun Song, Jiwon Koh, Jeong Mo Bae, Hyeong-Gon Moon, Seock-Ah Im. Characterization of the phylogenetic relationships in bilateral breast angiosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1622.

Abstract 2522: Predictive value of tumor mutational burden (TMB) in patients with metastatic microsatellite-stable (MSS) colorectal cancer (CRC) given first-line oxaliplatin-based chemotherapy and immune checkpoint blockade (ICB)

Abstract Purpose: Most CRC patients harbor primarily non-immunogenic MSS tumor. The randomized METIMMOX trial (NCT03388190) examined if patients with previously untreated, unresectable abdominal metastases from MSS-CRC may achieve therapeutic efficacy from short-course oxaliplatin-based chemotherapy (FLOX) and sequential ICB (nivolumab) repeatedly. Half of study patients assigned to this experimental treatment had significantly extended progression-free survival (PFS) while the other half had shortened PFS, compared to the control-group patients given standard FLOX chemotherapy with median PFS 9.3 months. Here we explored if somatic mutations (mut) unveiled by next-generation sequencing might provide insights into responsiveness to the METIMMOX regimen. Procedures: Patients had MSS-CRC with infradiaphragmatic metastases deemed unresectable and were eligible for first-line oxaliplatin-based therapy. They were randomly assigned to the control group of FLOX (oxaliplatin, 5-fluorouracil, folinic acid) Q2W or the experimental group of alternating 2 cycles each of FLOX Q2W and nivolumab Q2W, with prespecified break periods. Radiologic response assessment was done every 8 weeks with PFS as the primary endpoint. Diagnostic tumor biopsies and baseline metastasis biopsies were sequenced with the TruSight Oncology 500 assay. TMB was calculated using only coding, non-synonymous single-nucleotide variants and insertions/deletions with variant allele frequency ≥5% and sequencing depth ≥50 ×, applying the effective panel size as the megabases (Mb) denominator. Results: Sequencing data were acquired from 20 experimental-group patients with median PFS 7.9 months (minimum 2.0, maximum 41.6). Median TMB was 5.1 mut/Mb (minimum 0.8, maximum 11.8), concordant in patient-paired primary tumor and metastasis specimens. The TMB was associated with treatment outcome; the higher TMB, the better PFS with hazard ratio 0.83 (95% confidence interval (CI) 0.70-0.98; p = 0.026, Cox regression) for a PFS event with increasing TMB. TMB cut-off as low as 5.0 mut/Mb distinguished between patient groups (p = 0.007, log-rank test) with median PFS 34.9 months (95% CI 10.6-59.2; TMB>5, n = 10) and median PFS 4.6 months (95% CI 2.7-6.5; TMB≤5, n = 10). In the TMB>5 group, 8/10 were KRAS- or BRAF-mutant cases. In the TMB≤5 group, 9/10 metastasis specimens were RAS/BRAF-wildtype cases. Conclusions: TMB >5 mut/Mb was associated with tumor KRAS or BRAF driver mutation and remarkably long PFS in first-line treatment of patients with abdominal metastases from MSS-CRC with alternating short-course oxaliplatin-based chemotherapy and ICB. Citation Format: Anne Hansen Ree, Paula A. Bousquet, Hilde L. Nilsen, Torben Lüders, Shixiong Wang, Tina Visnovska, Diana L. Bordin, Eirik Høye, Hanne M. Hamre, Christian Kersten, Eva Hofsli, Marianne G. Guren, Halfdan Sorbye, Kjersti Flatmark, Sebastian Meltzer. Predictive value of tumor mutational burden (TMB) in patients with metastatic microsatellite-stable (MSS) colorectal cancer (CRC) given first-line oxaliplatin-based chemotherapy and immune checkpoint blockade (ICB) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2522.

Prediction of Deleterious Single Amino Acid Polymorphisms with a Consensus Holdout Sampler

Background: Single Amino Acid Polymorphisms (SAPs) or nonsynonymous Single Nucleotide Variants (nsSNVs) are the most common genetic variations. They result from missense mutations where a single base pair substitution changes the genetic code in such a way that the triplet of bases (codon) at a given position is coding a different amino acid. Since genetic mutations sometimes cause genetic diseases, it is important to comprehend and foresee which variations are harmful and which ones are neutral (not causing changes in the phenotype). This can be posed as a classification problem. Methods: Computational methods using machine intelligence are gradually replacing repetitive and exceedingly overpriced mutagenic tests. By and large, uneven quality, deficiencies, and irregularities of nsSNVs datasets debase the convenience of artificial intelligence-based methods. Subsequently, strong and more exact approaches are needed to address these problems. In the present work paper, we show a consensus classifier built on the holdout sampler, which appears strong and precise and outflanks all other popular methods. objective: Roughly a half of known disease-related mutations are due to non-synonymous variants [8-9], expressed as amino-acid mutations. Therefore, it is important to unravel the links between nonsynonymous Single Nucleotide Variants and associated diseases to discriminate between pathogenic and neutral substitutions. It has been found that these substitutions could be directly related to pathological effects such as Parkinson’s or Alzheimer’s diseases, or to the involvement in complex diseases, such as cancer development. Results: We produced 100 holdouts to test the structures and diverse classification variables of diverse classifiers during the training phase. The finest performing holdouts were chosen to develop a consensus classifier and tested using a k-fold (1 ≤ k ≤5) cross-validation method. We also examined which protein properties have the biggest impact on the precise prediction of the effects of nsSNVs. Conclusion: Our Consensus Holdout Sampler outflanks other popular algorithms, and gives excellent results, highly accurate with low standard deviation. The advantage of our method emerges from using a tree of holdouts, where diverse LM/AI-based programs are sampled in diverse ways.

Rare CRHR2 and GRM8 variants identified as candidate factors associated with eating disorders in Japanese patients by whole exome sequencing

Eating disorders (EDs) are a type of psychiatric disorder characterized by pathological eating and related behavior and considered to be highly heritable. The purpose of this study was to explore rare variants expected to display biological functions associated with the etiology of EDs. We performed whole exome sequencing (WES) of affected sib-pairs corresponding to disease subtype through their lifetime and their parents. From those results, rare single nucleotide variants (SNVs) concordant with sib-pairs were extracted and estimated to be most deleterious in the examined families. Two non-synonymous SNVs located on corticotropin-releasing hormone receptor 2 (CRHR2) and glutamate metabotropic receptor 8 (GRM8) were identified as candidate disease susceptibility factors. The SNV of CRHR2 was included within the cholesterol binding motif of the transmembrane helices region, while the SNV of GRM8 was found to contribute to hydrogen bonds for an α-helix structure. CRHR2 plays important roles in the serotoninergic system of dorsal raphe nuclei, which is involved with feeding and stress-coping behavior, whereas GRM8 modulates glutamatergic neurotransmission. Moreover, GRM8 modulates glutamatergic neurotransmission, and is also considered to have effects on dopaminergic and adrenergic neurotransmission. Thus, identification of rare and deleterious variants in this study is expected to increase understanding and treatment of affected individuals. Further investigation regarding the biological function of these variants may provide an opportunity for elucidate the pathogenesis of EDs.

Compound heterozygous WNT10A missense variations exacerbated the tooth agenesis caused by hypohidrotic ectodermal dysplasia

BackgroundThe aim of this study was to analyse the differences in the phenotypes of missing teeth between a pair of brothers with hypohidrotic ectodermal dysplasia (HED) and to investigate the underlying mechanism by comparing the mutated gene loci between the brothers with whole-exome sequencing.MethodsThe clinical data of the patients and their mother were collected, and genomic DNA was extracted from peripheral blood samples. By Whole-exome sequencing filtered for a minor allele frequency (MAF) ≤0.05 non-synonymous single-nucleotide variations and insertions/deletions variations in genes previously associated with tooth agenesis, and variations considered as potentially pathogenic were assessed by SIFT, Polyphen-2, CADD and ACMG. Sanger sequencing was performed to detect gene variations. The secondary and tertiary structures of the mutated proteins were predicted by PsiPred 4.0 and AlphaFold 2.ResultsBoth brothers were clinically diagnosed with HED, but the younger brother had more teeth than the elder brother. An EDA variation (c.878 T > G) was identified in both brothers. Additionally, compound heterozygous variations of WNT10A (c.511C > T and c.637G > A) were identified in the elder brother. Digenic variations in EDA (c.878 T > G) and WNT10A (c.511C > T and c.637G > A) in the same patient have not been reported previously. The secondary structure of the variant WNT10A protein showed changes in the number and position of α-helices and β-folds compared to the wild-type protein. The tertiary structure of the WNT10A variant and molecular simulation docking showed that the site and direction where WNT10A binds to FZD5 was changed.ConclusionsCompound heterozygous WNT10A missense variations may exacerbate the number of missing teeth in HED caused by EDA variation.

Integrated rules classifier for predicting pathogenic non-synonymous single nucleotide variants in human

The most prevalent kind of genetic variants in humans are non-synonymous single nucleotide variants (nsSNVs). Several prediction tools have been launched to forecast the effect of amino acid substitutes on human protein function. These tools sort variants as pathogenic or neutral. We developed an Integrated Rules Classifier (Integration Score through JRip “ISTJRip”), which integrates the four individual tools that are publicly available; iFish, Mutation Assessor, FATHMM, and SIFT-based on the JRip machine learning technique. Additionally, we compared the ISTJRip approach with the other three created integration classifiers; Integration Score through J48 “ISTJ48”, Integration Score through RF “ISTRF”, and Integration Score through SVM “ISTSVM” using a VaribenchSelectedPure dataset character from the standard dataset “Varibench”. The proposed integrated rules classifier “ISTJRip” and the other three integration classifiers, ISTJ48, ISTRF, and ISTSVM register 92.41 %, 92.26 %, 91.70 %, and 90.62 % ACC on VaribenchSelectedPure, respectively. Finally, we demonstrated that the integrated rules classifier outperforms other integration classifiers and highlights the benefits of JRip machine learning technique in the integration process for multiple tools.

Exploratory analysis of biomarkers of response to durvalumab in advanced HER2-negative oesophago-gastric adenocarcinoma within a phase 2 clinical trial.

384 Background: Advanced oesophago-gastric cancers have showcased varied responses to immunotherapy based on biomarkers such as tumour mutational burden, microsatellite instability, and PD-L1 expression. However, these markers may not fully capture tumour heterogeneity and evolutionary dynamics. Hence, understanding the intricate relationship between immune selection, specifically immune dN/dS,1 and tumour evolution is vital for devising personalized therapeutic strategies. Methods: In our phase 2 open label, multicentre, randomised PLATFORM trial (NCT02678182), patients received maintenance durvalumab post first-line chemotherapy. A survival advantage was not seen with maintenance durvalumab compared to surveillance and exploratory analysis of PD-L1 expression was not associated with improved survival outcomes.2 However, a subset of patients treated with durvalumab experienced durable responses and some experienced incremental radiological responses. A pilot substudy on a selected cohort (n=24) of these patients was designed to explore the potential of immunogenomics evolutionary-based metrics, notably dN/dS, as predictive biomarkers. DNA and RNA from FFPE baseline tumour samples underwent analysis, examining genomic factors including tumour mutational burden, indel signatures, PDL1 status, and immune evasion mechanisms. Furthermore, the evolutionary metric, immune dN/dS, which has implications in tumour immunoediting and its response to immunotherapies, was scrutinized. Results: A dominant indel mutational signature emerged from the analysis. The majority of patients displayed a significantly higher number of indel variants, compared to non-synonymous and synonymous single-nucleotide variants. A recurring observation was dN/dS values consistently above 1, indicating positive selection for non-synonymous somatic variants. Additionally, hypermutation in driver genes, notably TP53 and XIRP2, was detected. One patient, with a unique dN/dS < 1, showcased survival beyond four years without liver metastases. Immune dN/dS > 1 and no evidence of liver metastases displayed the best prognosis after treatment in contrast with those that have immune dN/dS < 1 with or without liver metastases. Conclusions: Immune dN/dS emerges as a promising tool to decode tumour evolutionary mechanisms, providing profound insights into the dynamics of tumour evolution in advanced HER2 negative oesophago-gastric cancer patients receiving durvalumab immunotherapy. This pilot study underscores the potential of this novel immunogenomic approach in improving patient stratification and tailoring therapeutic strategies in cancer immunotherapy. 1. Zapata et al, Nature Genetics, 2023. 2. Fong et al, J Clin Oncol, 2021. Clinical trial information: NCT02678182 .

A Comprehensive Analysis of 3 Moroccan Genomes Revealed Contributions From Both African and European Ancestries.

Genetic variations in the human genome represent the differences in DNA sequence within individuals. This highlights the important role of whole human genome sequencing which has become the keystone for precision medicine and disease prediction. Morocco is an important hub for studying human population migration and mixing history. This study presents the analysis of 3 Moroccan genomes; the variant analysis revealed 6 379 606 single nucleotide variants (SNVs) and 1 050 577 small InDels. Of those identified SNVs, 219 152 were novel, with 1233 occurring in coding regions, and 5580 non-synonymous single nucleotide variants (nsSNP) variants were predicted to affect protein functions. The InDels produced 1055 coding variants and 454 non-3n length variants, and their size ranged from -49 and 49 bp. We further analysed the gene pathways of 8 novel coding variants found in the 3 genomes and revealed 5 genes involved in various diseases and biological pathways. We found that the Moroccan genomes share 92.78% of African ancestry, and 92.86% of Non-Finnish European ancestry, according to the gnomAD database. Then, population structure inference, by admixture analysis and network-based approach, revealed that the studied genomes form a mixed population structure, highlighting the increased genetic diversity in Morocco.

Predisposing deleterious variants in the cancer-associated human kinases in the global populations.

Human kinases play essential and diverse roles in the cellular activities of maintaining homeostasis and growth. Genetic mutations in the genes encoding the kinases (or phosphotransferases) have been linked with various types of cancers. In this study, we cataloged mutations in 500 kinases genes in >65,000 individuals of global populations from the Human Genetic Diversity Project (HGDP) and ExAC databases, and assessed their potentially deleterious impact by using the in silico tools SIFT, Polyphen2, and CADD. The analysis highlighted 35 deleterious non-synonymous SNVs in the ExAC and 5 SNVs in the HGDP project. Notably, a higher number of deleterious mutations was observed in the Non-Finnish Europeans (26 SNVs), followed by the Africans (14 SNVs), East Asians (13 SNVs), and South Asians (12 SNVs). The gene set enrichment analysis highlighted NTRK1 and FGFR3 being most significantly enriched among the kinases. The gene expression analysis revealed over-expression of NTRK1 in liver cancer, whereas, FGFR3 was found over-expressed in lung, breast, and liver cancers compared to their expression in the respective normal tissues. Also, 13 potential drugs were identified that target the NTRK1 protein, whereas 6 potential drugs for the FGFR3 target were identified. Taken together, the study provides a framework for exploring the predisposing germline mutations in kinases to suggest the underlying pathogenic mechanisms in cancers. The potential drugs are also suggested for personalized cancer management.

The Extent of Edgetic Perturbations in the Human Interactome Caused by Population-Specific Mutations.

Until recently, efforts in population genetics have been focused primarily on people of European ancestry. To attenuate this bias, global population studies, such as the 1000 Genomes Project, have revealed differences in genetic variation across ethnic groups. How many of these differences can be attributed to population-specific traits? To answer this question, the mutation data must be linked with functional outcomes. A new "edgotype" concept has been proposed, which emphasizes the interaction-specific, "edgetic", perturbations caused by mutations in the interacting proteins. In this work, we performed systematic in silico edgetic profiling of ~50,000 non-synonymous SNVs (nsSNVs) from the 1000 Genomes Project by leveraging our semi-supervised learning approach SNP-IN tool on a comprehensive set of over 10,000 protein interaction complexes. We interrogated the functional roles of the variants and their impact on the human interactome and compared the results with the pathogenic variants disrupting PPIs in the same interactome. Our results demonstrated that a considerable number of nsSNVs from healthy populations could rewire the interactome. We also showed that the proteins enriched with interaction-disrupting mutations were associated with diverse functions and had implications in a broad spectrum of diseases. Further analysis indicated that distinct gene edgetic profiles among major populations could shed light on the molecular mechanisms behind the population phenotypic variances. Finally, the network analysis revealed that the disease-associated modules surprisingly harbored a higher density of interaction-disrupting mutations from healthy populations. The variation in the cumulative network damage within these modules could potentially account for the observed disparities in disease susceptibility, which are distinctly specific to certain populations. Our work demonstrates the feasibility of a large-scale in silico edgetic study, and reveals insights into the orchestrated play of population-specific mutations in the human interactome.

Identification of novel rare variants for anxiety: an exome-wide association study in the UK Biobank

BackgroundRare variants are believed to play a substantial role in the genetic architecture of mental disorders, particularly in coding regions. However, limited evidence supports the impact of rare variants on anxiety. MethodsUsing whole-exome sequencing data from 200,643 participants in the UK Biobank, we investigated the contribution of rare variants to anxiety. Firstly, we computed genetic risk score (GRS) of anxiety utilizing genotype data and summary data from a genome-wide association study (GWAS) on anxiety disorder. Subsequently, we identified individuals within the lowest 50% GRS, a subgroup more likely to carry pathogenic rare variants. Within this subgroup, we classified individuals with the highest 10% 7-item Generalized Anxiety Disorder scale (GAD-7) score as cases (N = 1869), and those with the lowest 10% GAD-7 score were designated as controls (N = 1869). Finally, we conducted gene-based burden tests and single-variant association analyses to assess the relationship between rare variants and anxiety. ResultsTotally, 47,800 variants with MAF ≤0.01 were annotated as non-benign coding variants, consisting of 42,698 nonsynonymous SNVs, 489 nonframeshift substitution, 236 frameshift substitution, 617 stop-gain and 40 stop-loss variants. After variation aggregation, 5066 genes were included in gene-based association analysis. Totally, 11 candidate genes were detected in burden test, such as RNF123 (PBonferroni adjusted = 3.40 × 10−6), MOAP1(PBonferroni adjusted = 4.35 × 10−4), CCDC110 (PBonferroni adjusted = 5.83 × 10−4). Single-variant test detected 9 rare variants, such as rs35726701(RNF123)(PBonferroni adjusted = 3.16 × 10−10) and rs16942615(CAMTA2) (PBonferroni adjusted = 4.04 × 10−4). Notably, RNF123, CCDC110, DNAH2, and CSKMT gene were identified in both tests. ConclusionsOur study identified novel candidate genes for anxiety in protein-coding regions, revealing the contribution of rare variants to anxiety.

Genetic stability of Mycobacterium abscessus during antibiotic treatment

Genetic changes in Mycobacterium abscessus during antibiotic treatment are not fully understood. This study aimed to investigate the genetic changes in M. abscessus in patients receiving antibiotic treatment, and their clinical implications. Pretreatment and 12-month post-treatment M. abscessus isolates were obtained from patients with M. abscessus pulmonary disease. Isolates from each time point were separated into six groups based on their distinctive morphological characteristics. Twenty-four isolates, comprising 12 from patient A exhibiting progressive disease and 12 from patient B demonstrating stable disease, underwent sequencing. Subsequently, minimal inhibitory concentrations (MICs) for the administered antibiotics were measured. Persistent infection with a single strain was observed in patients A and B. During 12 months of treatment, MICs for administered drugs did not generally change over time in either patient and single nucleotide variations (SNV) associated with antimicrobial resistance (rrl, rrs, erm(41), gyrA, gyrB, whiB7 and hflX) were not mutated. Although not significant, 47 and 52 non-synonymous SNVs occurred in M. abscessus from patients A and B, respectively, and the accumulation of these SNVs differed in patients A and B, except for five SNVs. The most variable positions were within a probable NADH-dependent glutamate synthase gene and a putative YrbE family protein gene in patients A and B, respectively. Persistent infections by a single strain of M. abscessus were observed in two patients with different clinical courses. Genetic changes in M. abscessus during antibiotic treatment were relatively stable in these patients. NCT01616745 (ClinicalTrials.gov ID).

Presence of Recurrent Somatic Mutations in Mesenchymal Stromal Cell Fractions Isolated from Acute Myeloid Leukemia As an Evidence of Clonality

Introduction: Acute myeloid leukemia (AML) involves somatic mutations in hematopoietic stem cells (HSCs). Recent evidence suggests the bone marrow microenvironment, particularly mesenchymal stromal cells (MSCs), also influences AML development. Abnormalities in MSCs from AML patients have been observed (von der Heide et al., 2016), potentially impacting leukemia progression. This study aims to identify MSC somatic mutations and their consequences, further exploring their role in AML. Understanding MSCs' impact on the leukemic microenvironment may shed light on AML pathophysiology and guide targeted therapies, particularly benefiting patients with adverse risk disease. Methods: A total of 28 bone marrow cases were collected from AML patients with adverse risk, including those with complex karyotype, monosomy karyotype, chromosome 5/7/17 abnormalities, TP53 mutation, or relapsed/refractory AML. From these cases, 14 paired MSC and leukemic cell (LC) fractions were analyzed and are presented here. Magnetic bead sorting was used to isolate CD33+ LCs, while the plastic adherence method was employed for MSC culture. Following magnetic isolation, CD33- cells were plated in DMEM-LG with FBS and pen/strep, and MSC colonies formed within 48 hours. Contaminating cells were removed through media changes, and passaging was performed at 70-80% confluency. Flow cytometry at passage 3 characterized MSCs based on cell surface expression of CD105, CD73, and CD90, in accordance with the ISCT guideline. DNA and RNA were extracted from MSCs at passage 3 and subjected to whole exome sequencing (WES) using the Illumina platform, along with the LC fractions. WES aimed for 200X depth for the paired DNA samples. A standard bioinformatics pipeline was used for sequence alignment and variant calling, with variants requiring sufficient read depth (≥30x) and variant allele frequency in the case (>5%) and in the control (<5%). Synonymous variants were filtered out, and gene ontology and pathway enrichment analyses explored the biological significance and potential involvement in leukemogenesis of the identified mutations. Whole transcriptomics for gene expression analyses was also conducted for both MSC and LC fractions. Results: In 14 analyzed cases, a total of 548 somatic variants were identified in the MSC fraction, affecting 480 genes, including 518 nonsynonymous single nucleotide variants (SNVs), 7 stop-gain SNVs, 1 stoploss, 1 non-frameshift insertion, 2 frameshift deletions, 1 frameshift insertion, and 2 non-frameshift deletions, with 16 unknown variants. The average read depth was 75 (range: 15 - 887), and the average variant allele frequency was 50% (range: 11% - 90%). On average, 38 genes were mutated per MSC case, with 8 genes detected in at least 3 cases, 25 in exactly 2 cases, and 447 genes found in only one case. In the leukemic fraction, 686 somatic variants in 595 genes were identified, with an average read depth of approximately 75 (range: 10 - 2596) and an average variant allele frequency of 47% (range: 8% - 85%). On average, 48 mutations were detected per leukemic case, with 12 mutations found in at least 3 cases, 40 in 2 cases, and 543 in only one case. Among the 14 cases, 10 cases (71%) had mutations in known driver genes for AML ( FLT3, NPM1, IDH1, IDH2, DNMT3A, RUNX1, TP53) exclusively in the leukemic fraction. As seen in Figure 1., of the 480 genes mutated in the MSC fraction, 69 overlapped with the 595 genes mutated in the leukemic fraction, while 411 genes were uniquely mutated in the MSC fraction. Further analysis is ongoing, and pathway analysis will be conducted once the remaining 14 cases are processed. Conclusions: This study identifies distinct somatic mutations in AML patients' MSC and leukemic cell fractions, revealing genomic complexity and crosstalk impacting leukemia progression. Understanding the functional implications of these mutations is crucial for unraveling their roles in leukemogenesis and developing personalized therapeutic interventions targeting MSC somatic mutations.

Identification of causative gene variants for patients with known monogenic diabetes using a targeted next-generation sequencing panel in a single-center study.

We aimed to verify the usefulness of targeted next-generation sequencing (NGS) technology for diagnosing monogenic diabetes in a single center. We designed an amplicon-based NGS panel targeting 34 genes associated with known monogenic diabetes and performed resequencing in 56 patients with autoantibody-negative diabetes mellitus diagnosed at < 50years who had not been highly obese. By bioinformatic analysis, we filtered significant variants based on allele frequency (< 0.005 in East Asians) and functional prediction. We estimated the pathogenicity of each variant upon considering the family history. Overall, 16 candidate causative variants were identified in 16 patients. Among them, two previously known heterozygous nonsynonymous single-nucleotide variants associated with monogenic diabetes were confirmed as causative variants: one each in the GCK and WFS1 genes. The former was found in two independent diabetes-affected families. Two novel putatively deleterious heterozygous variants were also assumed to be causative from the family history: one frameshift and one nonsynonymous single-nucleotide variant in the HNF4A gene. Twelve variants remained as candidates associated with the development of diabetes. Targeted NGS panel testing was useful to diagnose various forms of monogenic diabetes in combination with familial analysis, but additional ingenuity would be needed for practice. The online version contains supplementary material available at 10.1007/s13340-023-00669-3.

Mutational Landscape and In-Silico Analysis of TP53, PIK3CA, and PTEN in Patients with Breast Cancer from Khyber Pakhtunkhwa.

Herein, we report the mutational spectrum of three breast cancer candidate genes (TP53, PIK3CA, and PTEN) using WES for identifying potential biomarkers. The WES data were thoroughly analyzed using SAMtools for variant calling and identification of the mutations. Various bioinformatic tools (SIFT, PolyPhen-2, Mutation Taster, ISPRED-SEQ, SAAFEQ-SEQ, ConSurf, PROCHECK etc.) were used to determine the pathogenicity and nature of the SNVs. Selected interaction site (IS) mutations were visualized in PyMOL after building 3D structures in Swiss-Model. Ramachandran plots were generated by using the PROCHECK server. The selected IS mutations were subjected to molecular dynamic simulation (MDS) studies using Gromacs 4.5. STRING and GeneMANIA were used for the prediction of gene-gene interactions and pathways. Our results revealed that the luminal A molecular subtype of the breast cancer was most common, whereas a high percentage of was Her2 negatives. Moreover, the somatic mutations were more common as compared to the germline mutations in TP53, PIK3CA, and PTEN. 20% of the identified mutations are reported for the first time from Khyber Pakhtunkhwa. In the enrolled cohort, 23 mutations were nonsynonymous SNVs. The frequency of mutations was the highest in PIK3CA, followed by TP53 and PTEN. A total of 13 mutations were found to be highly pathogenic. Four novel mutations were identified on PIK3CA and one each on PTEN and TP53. SAAFEQ-SEQ predicted the destabilizing effect for all mutations. ISPRED-SEQ predicted 9 IS mutations (6 on TP53 and 3 on PIK3CA), whereas no IS mutation was predicted on PTEN. The TP53 IS mutations were TP53R43H, TP53Y73X, TP53K93Q, TP53K93R, TP53D149E, and TP53Q199X; whereas for PIK3CA, the IS mutations were PIK3CAL156V, PIK3CAM610K, and PIK3CAH1047R. Analysis from the ConSurf Web server revealed five SNVs with a highly conserved status (conservation score 9) across TP53 and PTEN. TP53P33R was found predominant in the grade 3 tumors, whereas PTENp.C65S was distributed on ER+, ER-, PR+, PR-, Her2+, and Her2- patients. TP53p.P33R mutation was found to be recurring in the 14/19 (73.6%) patients and, therefore, can be considered as a potential biomarker. Finally, these mutations were studied in the context of their potential association with different hormonal and social factors.

Cross-cohort single-nucleotide-variant profiling of gut microbiota suggests a novel gut-health assessment approach.

Most studies focused much on the change in abundance and often failed to explain the microbiome variation related to disease conditions, Herein, we argue that microbial genetic changes can precede the ecological changes associated with the host physiological changes and, thus, would offer a new information layer from metagenomic data for predictive modeling of diseases. Interestingly, we preliminarily found a few genetic biomarkers on SCFA production can cover most chronic diseases involved in the meta-analysis. In the future, it is of both scientific and clinical significance to further explore the dynamic interactions between adaptive evolution and ecology of gut microbiota associated with host health status.

Primary lipoblastic nerve sheath tumor in an inguinal lymph node mimicking metastatic tumor: a case report and literature review

Lipoblastic nerve sheath tumors of soft tissue are characterized as schwannoma tumors that exhibit adipose tissue and lipoblast-like cells with signet-ring morphology. They have been documented to arise in various anatomic locations, including the thigh, groin, shoulder, and retroperitoneum. However, to our knowledge, this tumor has not been previously reported as a lymph node primary. We present herein the first case of a benign primary lipoblastic nerve sheath tumor arising in an inguinal lymph node in a 69-year-old man. Microscopic examination revealed a multinodular tumor comprising fascicles of spindle cells, as well as adipocytic and lipoblast-like signet-ring cell component in the context of schwannoma. Despite the presence of some bizarre cells with nuclear atypia, no obvious mitotic activity or necrosis was observed. Immunohistochemical analysis showed strong and diffuse expression of S-100, SOX10, CD56, and NSE in the spindle cells as well as in the signet-ring lipoblast-like cells and the mature adipocytes. Sequencing analysis of the neoplasm identified six non-synonymous single nucleotide variant genes, specifically NF1, BRAF, ECE1, AMPD3, CRYAB, and NPHS1, as well as four nonsense mutation genes including MRE11A, CEP290, OTOA, and ALOXE3. The patient remained alive and well with no evidence of recurrence over a period of ten-year follow-up.

Clinical relevance of genetic variants in the von Willebrand factor according to in-silico methods.

Clinical interpretation of genetic variants in the context of the patient's phenotype is a time-consuming and costly process. In-silico analysis using in-silico prediction tools, and molecular modeling have been developed to predict the influence of genetic variants on the quality and/or quantity of the resulting translated protein, and in this way, to alert clinicians of disease likelihood in the absence of previous evidence. Our objectives were to evaluate the success rate of the in-silico analysis in predicting the disease-causing variants as pathogenic and the single-nucleotide variants as neutral, and to establish the reliability of in-silico analysis for determining pathogenicity or neutrality of von Willebrand factor gene-associated genetic variants. Using in-silico analysis, we studied pathogenicity in 31 disease-causing variants, and neutrality in 61 single-nucleotide variants from patients previously diagnosed as type 2 von Willebrand disease. Disease-causing variants and non-synonymous single-nucleotide variants were explored by in-silico tools that analyze the amino acidic sequence. Intronic and synonymous single-nucleotide variants were analyzed by in-silico methods that evaluate the nucleotidic sequence. We found a consistent agreement between predictions achieved by in-silico prediction tools and molecular modeling, both for defining the pathogenicity of disease-causing variants and the neutrality of single-nucleotide variants. Based on our results, the in-silico analysis would help to define the pathogenicity or neutrality in novel genetic variants observed in patients with clinical and laboratory phenotypes suggestive of von Willebrand disease.