Single Nucleotide Polymorphisms Research Articles

Localization and discrimination of GG mismatch in duplex DNA by synthetic ligand-enhanced protein nanopore analysis.

Mismatched base pairs in DNA are the basis of single-nucleotide polymorphism, one of the major issues in genetic diseases. However, the changes of physical and chemical properties of DNA caused by single-site mismatches are often influenced by the sequence and the structural flexibility of the whole duplex, resulting in a challenge of direct detection of the types and location of mismatches sensitively. In this work, we proposed a synthetic ligand-enhanced protein nanopore analysis of GG mismatch on DNA fragment, inspired by in silico investigation of the specific binding of naphthyridine dimer (ND) on GG mismatch. We demonstrated that both the importing and unzipping processes of the ligand-bound DNA duplex can be efficiently slowed down in α-hemolysin nanopore. This ligand-binding induced slow-down effect of DNA in nanopore is also sensitive to the relative location of the mismatch on DNA duplex. Especially, the GG mismatch close to the end of a DNA fragment, which is hard to be detected by either routine nanopore analysis or tedious nanopore sequencing, can be well differentiated by our ND-enhanced nanopore experiment. These findings provide a promising strategy to localize and discriminate base mismatches in duplex form directly at the single-molecule level.

Archaeogenetic Data Mining Supports a Uralic–Minoan Homeland in the Danube Basin

Four types of archaeogenetic data mining are used to investigate the origin of the Minoans and the Uralic peoples: (1) six SNP mutations related to eye, hair, and skin phenotypes; (2) whole-genome admixture analysis using the G25 system; (3) an analysis of the history of the U5 mitochondrial DNA haplogroup; and (4) an analysis of the origin of each currently known Minoan mitochondrial and y-DNA haplotypes. The uniform result of these analyses is that the Minoans and the Uralic peoples had a common homeland in the lower and middle Danube Basin, as well as the Black Sea coastal regions. This new result helps to reconcile archaeogenetics with linguistics, which have shown that the Minoan language belongs to the Uralic language family.

Association of polymorphisms in the HTRA1 gene with myopia

PurposeTo evaluate the associations of single-nucleotide polymorphisms (SNPs) in the high-temperature requirement protease A 1 (HTRA1) gene with myopia.Methods25 SNPs in HTRA1 were selected, including 23 haplotype-tagging SNPs, SNP rs2142308...

Comparison of commercial targeted amplicon sequencing assays for human remains identification casework.

Targeted amplicon sequencing (TAS) facilitates the genotyping of forensically informative single nucleotide polymorphisms (SNPs) using massively parallel sequencing (MPS). For human remains identification, where any extracted DNA is likely to be degraded, TAS may succeed when short tandem repeat (STR) profiling using capillary electrophoresis fails. Further, as well as yielding identity information, SNPs can provide information about ancestry, phenotype, kinship and paternal lineage (Y chromosome haplotypes). Two TAS platforms were compared in this study: Ion AmpliSeq™ panels coupled with Ion Torrent sequencing on an Ion GeneStudio™ S5 Plus System, manufactured by Thermo Fisher Scientific, and the ForenSeq® Kintelligence Kit coupled with Illumina sequencing on the MiSeq FGx® Sequencing System, manufactured by QIAGEN. Four Ion AmpliSeq™ panels (Precision ID Identity, Precision ID Ancestry, DNA Phenotyping and HID Y-SNP) share 177 SNPs with the ForenSeq® Kintelligence Kit and all five were used to profile the DNA extracted from the petrous part of the temporal bone from six skeletonised cadavers. Of the 6 × 177 = 1,062 SNP genotype comparisons, 1,055 (99%) were concordant between the Ion AmpliSeq™ panels and Kintelligence Kit. Of the seven (< 1%) non-concordant SNPs, only three of them (0.3%) would have resulted in erroneous genotypes being reported as a result of allele dropout by either assay, using our optimised relative variant frequency windows for allele calling. We conclude that both the Ion AmpliSeq™ panels and the ForenSeq® Kintelligence Kit were suitable for TAS applied to the human remains in this study.

Genetic overlap between idiopathic scoliosis and schizophrenia in the general population.

Adolescent idiopathic scoliosis (AIS) and schizophrenia (SCZ) are two distinct conditions with poorly understood aetiologies that both emerge in otherwise healthy young adolescents. One rare genetic condition associated with both phenotypic outcomes is the 22q11.2 deletion (22q11DS). This microdeletion, encompassing 47 genes, occurs in approximately 1 in 2,148 live births and confers a 20-fold higher risk for both AIS and schizophrenia compared to the general population. In the general population (non-22q11DS carriers), AIS and SCZ have also been reported to be related and genetic studies suggest the involvement of genetic variants implicated in the central nervous functioning. In this study, our objective was to further investigate genetic overlaps between these conditions in the general population. Specifically, we aimed to explore the role of genes within the 22q11.2 region, not only in terms of common variants but also their potential impact on gene networks and biopathways. We used summary statistics from three genome-wide association studies (GWAS): two focused on AIS (n = 11,210), and one on schizophrenia (n = 36,989). To explore potential overlaps between the two conditions, we conducted a comparative analysis on the significance-based ranked single nucleotide polymorphisms (SNPs) that are associated with both AIS and SCZ. Next, we employed in silico analyses to assess gene-networks enrichment for the most significant SNPs and investigate the contribution of genes within the 22q11.2 region. Post-hoc analysis was conducted to explore the biological pathways correlated with SNPs significantly associated with both AIS and SCZ. The in silico analyses revealed a significant (adjusted-p < 0.05) genetic overlap between SCZ and both AIS cohorts. The top 3% of the most significant SNPs associated with both conditions exhibited a distinct enrichment cluster which is unlikely to be a result of chance (p < 3e-04). The gene-networks analyses showed a significant overlap of 26-41% with the ones involving genes in the 22q11DS region. However, there was no overlap between SNPs in this region and the most significant SNPs identified in the GWAS. This study revealed compelling evidence that beyond the shared association with 22q11DS as a rare genetic variant, AIS and SCZ exhibit common genetic risk variants and an overlap of important genes. The gene networks enriched by the most significant SNPs for both conditions also intersect with the ones involving genes in the 22q11DS region. However, SNPs within this region were not overrepresented among the most significant SNPs from GWAS for both conditions. Notably, gene networks linked to the risk for both conditions suggest an involvement of biopathways related to cellular signaling and neuronal development.

The genetics of severe depression.

Genome-wide association studies (GWASs) of major depressive disorder (MDD) have recently achieved extremely large sample sizes and yielded substantial numbers of genome-wide significant loci. Because of the approach to ascertainment and assessment in many of these studies, some of these loci appear to be associated with dysphoria rather than with MDD, potentially decreasing the clinical relevance of the findings. An alternative approach to MDD GWAS is to focus on the most severe forms of MDD, with the hope that this will enrich for loci of larger effect, rendering their identification plausible, and providing potentially more clinically actionable findings. Here we review the genetics of severe depression by using clinical markers of severity including: age of onset, recurrence, degree of impairment, and treatment with ECT. There is evidence for increased family-based and Single Nucleotide Polymorphism (SNP)-based estimates of heritability in recurrent and early-onset illness as well as severe functional impariment. GWAS have been performed looking at severe forms of MDD and a few genome-wide loci have been identified. Several whole exome sequencing studies have also been performed, identifying associated rare variants. Although these findings have not yet been rigorously replicated, the elevated heritability seen in severe MDD phenotypes suggests the value of pursuing additional genome-wide interrogation of samples from this population. The challenge now is generating a cohort of adequate size with consistent phenotyping that will allow for careful and robust classifications and distinctions to be made. We are currently pursuing such a strategy in our 50-site worldwide Gen-ECT-ics consortium.

Genome-wide association studies in a diverse strawberry collection unveil loci controlling agronomic and fruit quality traits.

Strawberries (Fragaria sp.) are cherished for their organoleptic properties and nutritional value. However, breeding new cultivars involves the simultaneous selection of many agronomic and fruit quality traits, including fruit firmness and extended postharvest life. The strawberry germplasm collection here studied exhibited extensive phenotypic variation in 26 agronomic and fruit quality traits across three consecutive seasons. Phenotypic correlations and principal component analysis revealed relationships among traits and accessions, emphasizing the impact of plant breeding on fruit weight and firmness to the detriment of sugar or vitamin C content. Genetic diversity analysis on 124 accessions using 44,408 markers denoted a population structure divided into six subpopulations still retaining considerable diversity. Genome-wide association studies for the 26 traits unveiled 121 significant marker-trait associations distributed across 95 quantitative trait loci (QTLs). Multiple associations were detected for fruit firmness, a key breeding target, including a prominent locus on chromosome 6A. The candidate gene FaPG1, controlling fruit softening and postharvest shelf life, was identified within this QTL region. Differential expression of FaPG1 confirmed its role as the primary contributor to natural variation in fruit firmness. A kompetitive allele-specific PCR assay based on the single nucleotide polymorphism (SNP) AX-184242253, associated with the 6A QTL, predicts a substantial increase in fruit firmness, validating its utility for marker-assisted selection. In essence, this comprehensive study provides insights into the phenotypic and genetic landscape of the strawberry collection and lays a robust foundation for propelling the development of superior strawberry cultivars through precision breeding.

Machine learning-driven polygenic risk scores for bipolar disorder, depression, and panic disorder

Polygenic Risk Score (PRS) is a computational tech- nique that uses various genomic data to simultaneously analyze an individ- ual’s genetic risk for particular illnesses or traits. However, the traditional PRS computation has a few weaknesses, including its limited capacity to account for just a portion of trait variance, susceptibility to overfitting, and insufficient ability to discriminate among the larger population. Machine Learning (ML) methods offer a promising alternative to the traditional method by avoiding the problem of overfitting and improving accuracy. This study aims to develop an ML model for improved PRS calculation. We used the summary statistics for three mentals diseases, bipolar, depression, and panic disorder, from the Psychiatric Genomics Consortium (PGC) as a disease reference. We also obtained actual genotype data of individuals from OpenSNP, which includes both case and control samples. This data is used for predicting scores. The suggested approach, called Polygenic Risk Score Neural Network (PRSNN), calculates the PRS using weight vectors that estimate the relevance of each single nucleotide polymorphism (SNP) with a particular phenotype by deep learning model as an alternative to the traditional method. This study aims to develop a machine learning model, called PRSNN, for improved calculation of Polygenic Risk Scores (PRS). The PRSNN method outperforms the conventional method in identifying individuals at risk of mental disease. A novel deep-learning approach, named as PRSNN, is proposed for generating PRSs. The results demonstrate that it outperforms the traditional method of computing PRS for complex diseases. Further upgrades for this tool are required to overcome the current limitations, including lack of validation with external data from different ancestries, which may limit the applicability of the PRSNN method across diverse populations, and the small sample size, which may affect the results.

A new computational method to estimate adaptation time in Avicennia by using divergence time

Evolutionary studies of plant groups which are distributed in vast geographical regions and face different ecological and environmental conditions are important as they through light on different mechanisms of local adaptation and species divergence through time. The genus Avicennia is one of these plant groups which inspire of few species show interesting geographical distribution with some degree of species-specific geographical isolations. In general, very limited molecular phylogenetic investigations have been carried out in the genus Avicennia, and therefore we conducted the present study with the following aims:To estimate the species divergence time based on different nuclear and chloroplast DNA regions, separately. This will illustrate how different genetic regions evolved in this genus,To identify the sequences with potential adaptive value against geographical variable by latent factor mixed models (LFMM) analysis,To illustrate the phylogenetic signal of these DNA regions and their role in speciation within the genus and,To introducing a new computational strategy for estimating adaptive time for the sequences. The results showed that different genetic regions may produce different species divergent time, both the nuclear ribosomal internal transcribed spacer (ITS) region and chloroplast DNA sequences, contained potentially adaptive single nucleotide polymorphisms (SNPs).We could present a suggestive time for these adaptive sequences for the first time. In conclusion both local adaptation and independent mutations seem to have played role in Avicennia speciation and evolution.

Genome of Russian Snow-White Chicken Reveals Genetic Features Associated with Adaptations to Cold and Diseases.

Russian Snow White (RSW) chickens are characterized by high egg production, extreme resistance to low temperatures, disease resistance, and by the snow-white color of the day-old chicks. Studying the genome of this unique chicken breed will reveal its evolutionary history and help to understand the molecular genetic mechanisms underlying the unique characteristics of this breed, which will open new breeding opportunities and support future studies. We have sequenced and made a de novo assembly of the whole RSW genome using deep sequencing (250×) by the short reads. The genome consists of 40 chromosomes with a total length of 1.1 billion nucleotide pairs. Phylogenetic analysis placed the RSW near the White Leghorn, Fayoumi, and Houdan breeds. Comparison with other chicken breeds revealed a wide pool of mutations unique to the RSW. The functional annotation of these mutations showed the adaptation of genes associated with the development of the nervous system, thermoreceptors, purine receptors, and the TGF-beta pathway, probably caused by selection for low temperatures. We also found adaptation of the immune system genes, likely driven by selection for resistance to viral diseases. Integration with previous genome-wide association studies (GWAS) suggested several causal single nucleotide polymorphisms (SNPs). Specifically, we identified an RSW-specific missense mutation in the RALYL gene, presumably causing the snow-white color of the day-old chicks, and an RSW-specific missense mutation in the TLL1 gene, presumably affecting the egg weight.

KBG Syndrome in 16 Indian Individuals.

We aimed to describe the clinical and genetic characteristics of 16 individuals with KBG syndrome (KBGS) from 13 Indian families. We retrospectively analyzed the clinical details of individuals with KBGS harboring a likely pathogenic/pathogenic variant in ANKRD11. We also analyzed their facial gestalt using Face2Gene and recorded the top three differential disorders suggested by the application. The most frequent clinical features observed in our cohort were as follows: learning and intellectual disability-14/15 (93%), skeletal abnormalities-14/15 (93%), postnatal short stature-13/15 (87%), brachydactyly-11/15 (73%), and characteristic facial appearance-13/15 (87%). We identified 12 single nucleotide variants (SNVs), including six recurrent and six novel variants, and a copy number variant in the 16q24.3 region encompassing ANKRD11 gene. The novel variants were as follows: p.(Gln1236Ter), p.(Asp884ThrfsTer93), p.(Arg1466GlyfsTer87), p.(Tyr2056Ter), p.(Leu955TrpfsTer22), and p.(Lys766ArgfsTer10). The identified SNVs in ANKRD11 clustered around exon 9. We observed a high concordance of Face2Gene in predicting KBGS.

Genetic Biomarkers in Heart Failure: From Gene Panels to Polygenic Risk Scores.

This review aims to provide a comprehensive overview of the current understanding of genetic markers associated with heart failure (HF) and its underlying causative diseases, such as cardiomyopathies. It highlights the relevance of genetic biomarkers in diagnosing HF, predicting prognosis, potentially identifying its preclinical stages and identifying targets to enable the implementation of individualized medicine approaches. The prevalence of HF is increasing due to an aging population but with greater access to disease-modifying therapies. Advanced diagnostic tools such as cardiac magnetic resonance, nuclear imaging, and AI-enabled diagnostic testing are now being utilized to further characterize HF patients. Additionally, the importance of genetic testing in HF diagnosis and management is increasingly being recognized. Genetic biomarkers, including single nucleotide polymorphisms (SNPs) and rare genetic variants, are emerging as crucial tools for diagnosing HF substrates, determining prognosis and increasingly directing therapy. These genetic insights are key to optimizing HF management and delivering personalized treatment tailored to individual patients. HF is a complex syndrome affecting millions globally, characterized by high mortality and significant economic burden. Understanding the underlying etiologies of HF is essential for improving management and clinical outcomes. Recent advances highlight the use of multimodal assessments, including AI-enabled diagnostics and genetic testing, to better characterize and manage HF. Genetic biomarkers are particularly promising in identifying preclinical HF stages and providing personalized treatment options. The genetic contribution to HF is heterogeneous, with both monogenic and polygenic bases playing a role. These developments underscore the shift towards personalized medicine in HF management.

Association of ADIPOQ Single Nucleotide Polymorphisms (SNPs) with Obesity Risk in Different Populations: A Systematic Review and Analysis

Background: Thirty-two single nucleotide polymorphisms (SNPs) are commonly found in ADIPOQ. APN levels are decreased in obesity, and SNPs of the ADIPOQ gene affecting APN have varying associations with the development of obesity in different populations. This systematic review and meta-analysis aimed to investigate the association of SNPs in ADIPOQ with the risk of obesity development in various populations. Methods: A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist date up to Feb 2023. We used the Newcastle–Ottawa scale to find out if a study fit the main criteria for submission and to assess the data quality of the articles included in the systematic review and meta-analysis. Odds ratios (OR) and 95% confidence intervals (CI) were calculated via Review Manager (RM) V.5.4 to estimate the connection between ADIPOQ polymorphic qualities of a gene and the risk of developing obesity. Results: The present study analysed the association between ADIPOQ polymorphisms (rs1501299, rs2241766, rs266729, rs822393, and rs822396) and obesity risk and suggested that APN is partially responsible for the emergence of obesity and increases its risk. Conclusion: It is important to take into account several limitations of this meta-analysis when evaluating the findings. First off, even though we looked through numerous databases for all relevant papers, there is a chance we overlooked some. Our capacity to arrive at more firm conclusions was further hampered by the small number of papers that made up our meta-analysis. The most current data, however, are presented in this study since it used newly published data to perform a meta-analysis and evaluate the relationship between ADIPOQ polymorphisms and obesity.

Sex differences in genotype frequency and the risk of polycythemia associated with rs13419896 and rs2790859 among Tibetan highlanders living in Tsarang, Mustang, Nepal

BackgroundTibetan highlanders have adapted to hypoxic environments through genetic mechanisms that avoid hemoglobin concentration increases and prevent polycythemia. Recently, sex differences in hemoglobin dynamics with age have been reported among Tibetan highlanders living in Tsarang. Additionally, concerns have been raised that dietary changes associated with modernization may increase the risk of polycythemia and lifestyle-related diseases among Tibetan highlanders. However, the relationship between genetic polymorphisms and the risk of lifestyle-related diseases in Tibetan highlanders has been investigated in only a few regions. This study aims to elucidate whether polymorphisms in genes related to hypoxic adaptation are associated with the incidence of lifestyle-related diseases and polycythemia and whether these polymorphisms affect hemoglobin dynamics in the residents of Tsarang, Mustang, Nepal.MethodsHealth checkup data from individuals living in Tsarang in Mustang District, Nepal, collected in 2017, were used to determine the prevalence of obesity, hypertension, diabetes, hypoxemia, and polycythemia. DNA was extracted from whole-blood samples, and data for the single-nucleotide polymorphisms (SNPs) rs13419896 (EPAS1), rs12619696 (EPAS1), and rs2790859 (EGLN1) were obtained using real-time PCR. The health checkup data were statistically analyzed to determine the associations of these diseases with polymorphisms in genes related to hypoxic adaptation.ResultsA total of 168 participants, comprising 78 males and 90 females, were included in the final analysis. In terms of the prevalence of each disease, only the prevalence of polycythemia significantly differed between sexes (p < 0.01). Additionally, among the three analyzed SNPs, significant sex differences in genotype frequency were observed for rs13419896 and rs2790859. For rs2790859 in females, Tibetan highlanders with the adaptive genotype had a significantly lower incidence of polycythemia (p < 0.01) and significantly lower hemoglobin concentrations (p < 0.01).ConclusionsThis study revealed that there are sex differences in the genotype frequency of gene-related hypoxic adaptations among the residents of Tsarang. The findings also suggested that the rs2790859 polymorphism might be involved in the recent incidence of polycythemia among Tsarang residents. If the frequency of non-Tibetan genotypes increases due to intermixing with other populations in the Mustang District, polycythemia may emerge as a modern disease. It is essential to continue investigating the health status of Mustang residents to elucidate various aspects of hypoxic adaptation and disease susceptibility.

A novel classification framework for genome-wide association study of whole brain MRI images using deep learning.

Genome-wide association studies (GWASs) have been widely applied in the neuroimaging field to discover genetic variants associated with brain-related traits. So far, almost all GWASs conducted in neuroimaging genetics are performed on univariate quantitative features summarized from brain images. On the other hand, powerful deep learning technologies have dramatically improved our ability to classify images. In this study, we proposed and implemented a novel machine learning strategy for systematically identifying genetic variants that lead to detectable nuances on Magnetic Resonance Images (MRI). For a specific single nucleotide polymorphism (SNP), if MRI images labeled by genotypes of this SNP can be reliably distinguished using machine learning, we then hypothesized that this SNP is likely to be associated with brain anatomy or function which is manifested in MRI brain images. We applied this strategy to a catalog of MRI image and genotype data collected by the Alzheimer's Disease Neuroimaging Initiative (ADNI) consortium. From the results, we identified novel variants that show strong association to brain phenotypes.

Elucidating the role of MLL1 nsSNPs: Structural and functional alterations and their contribution to leukemia development.

The Mixed lineage leukemia 1 (MLL1) gene, located on chromosome 11q23, plays a pivotal role in histone lysine-specific methylation and is consistently associated with various types of leukemia. Non-synonymous Single Nucleotide Polymorphisms (nsSNPs) have been tied to numerous diseases, including cancers, and have become valuable cancer biomarkers. There's a notable gap in studies probing the influence of SNPs on MLL1 protein structure, function, and subsequent modifications. We utilized an array of bioinformatics tools, including PredictSNP, InterPro, ConSurf, I-Mutant2.0, MUpro, Musitedeep, Project HOPE, RegulomeDB, Mutpred2, and both CScape and CScape Somatic, to meticulously analyze the consequences of nsSNPs in the MLL1 gene. Out of 2,097 nsSNPs analyzed, 62 were determined to be significantly pathogenic by the PredictSNP tool, with ten crucial MLL1 functional domains identified using InterPro. Additionally, 50 of these nsSNPs had high conservation scores, hinting at potential effects on protein structure and function, while 32 were found to undermine MLL1 protein stability. Notably, four nsSNPs were deemed oncogenic, with two identified as cancer drivers. The nsSNP, D2724G, between the MLL1 protein's FY-rich domains, could disrupt proteolytic cleavage, altering gene expression patterns and potentially promoting cancer. Our research provides a comprehensive assessment of nsSNPs' impact in the MLL1 protein structure and function and consequently on leukemia development, suggesting potential avenues for personalized treatment, early detection, improved prognosis, and a deeper understanding of hematological malignancy genesis.

Global characterization of somatic mutations and DNA methylation changes during vegetative propagation in strawberries.

Somatic mutations arise and accumulate during tissue culture and vegetative propagation, potentially affecting various traits in horticultural crops, but their characteristics are still unclear. Here, somatic mutations in regenerated woodland strawberry derived from tissue culture of shoot tips under different conditions and 12 cultivated strawberry individuals are analyzed by whole genome sequencing. The mutation frequency of single nucleotide variants is significantly increased with increased hormone levels or prolonged culture time in the range of 3.3 × 10-8-3.0 × 10-6 mutations per site. CG methylation shows a stable reduction (0.71%-8.03%) in regenerated plants, and hypoCG-DMRs are more heritable after sexual reproduction. A high-quality haplotype-resolved genome is assembled for the strawberry cultivar "Beni hoppe." The 12 "Beni hoppe" individuals randomly selected from different locations show 4731-6005 mutations relative to the reference genome, and the mutation frequency varies among the subgenomes. Our study has systematically characterized the genetic and epigenetic variants in regenerated woodland strawberry plants and different individuals of the same strawberry cultivar, providing an accurate assessment of somatic mutations at the genomic scale and nucleotide resolution in plants.

Prospective associations of genetic susceptibility to high blood pressure and muscle strength with incident cardiovascular disease outcomes.

This study explored the prospective associations of genetic susceptibility to high blood pressure (BP) and muscle strength with cardiovascular disease (CVD) mortality, incident coronary heart disease (CHD) and incident stroke. This study included 349 085 white British individuals from the UK Biobank study. Genetic risk of high BP was estimated using a weighted polygenic risk score that incorporated 136 and 135 nonoverlapping single-nucleotide polymorphisms for systolic BP and diastolic BP, respectively. Muscle strength was assessed using a hand dynamometer and expressed relative to fat-free mass. Sex- and age-specific tertiles were used to classify muscle strength into three categories. Cox regressions with age as the underlying timescale were fit for CVD mortality (n = 8275), incident CHD (n = 14 503), and stroke (n = 7518). Compared with the lowest genetic risk of high BP (bottom 20%), the highest (top 20%) had greater hazards of each outcome. Low muscle strength was associated with higher hazards of CVD mortality [hazard ratio (HR): 1.51, 95% confidence interval (CI): 1.43-1.59], incident CHD (HR: 1.16, 95% CI: 1.11-1.21), and stroke (HR: 1.20, 95% CI: 1.14-1.27), independently of confounders and genetic predisposition to high BP, compared with high muscle strength. Joint analyses revealed that the estimated 10-year absolute risks of each outcome were lower for high muscle strength combined with high genetic risk, compared with low muscle strength combined with low or medium genetic risk. Individuals who are genetically predisposed to high BP but have high muscle strength could have lower risk of major CVD events, compared with those who have low or medium genetic risk but low muscle strength.

Forensic STR and SNP Genotyping of Formalin-Fixed Skeleton Samples With Illumina's ForenSeq System.

Formalin fixatives are widely used in forensics to preserve tissues. However, extracting high-quality genomic DNA from formalin-fixed samples is challenging. Traditional short tandem repeat (STR) analysis using capillary electrophoresis (CE) for forensic DNA typing frequently results in failure. Massively parallel sequencing (MPS) can handle many samples and thousands of genetic markers, usually single-nucleotide polymorphisms (SNPs) and STRs, in a single test. Thus, it is useful for assessing highly deteriorated forensic evidence. Few studies have examined the effectiveness of STRs and SNPs genotyping of formalin-fixed skeletons using MPS. In this study, 55 skeletal samples from 5 individuals that were treated under different formalin fixation times (5-75 days) were examined and sequenced using the ForenSeq DNA Signature Prep Kit on the Illumina MiSeq FGX platform. The results showed that as the duration of formalin fixation increased, the detection rates of STRs and SNPs gradually decreased. After 75 days of fixation, the average detection rates for STRs and SNPs were 4% and 10%, respectively. The cumulative discrimination power (CDP) of individual identification SNPs (iiSNPs) was >0.9999 on the 45th day. However, the CDP of STRs was 0.9930 on the 22nd day. Low detection rates were observed for six STRs (D1S1656, PentaE, D22S1045, PentaD, DX8378 and DX10103) and five SNPs (rs2920816, rs354439, rs1736442, rs338882 and rs1031825). In conclusion, DNA extracted from formalin-fixed skeletons decomposes rapidly over time, and MPS technology can be a useful tool for detecting forensic genetic markers in such samples.

ApaI Polymorphism in the Vitamin D Receptor Gene Decreases the Risk of Perianal Fistulas in Crohn’s Disease

Background: Vitamin D, through the activation of its receptor (VDR), plays an immunomodulatory role in the gastrointestinal tract. Single-nucleotide polymorphisms (SNPs) in the VDR gene have been associated with Crohn’s disease (CD) risk, and patients carrying the TaqI polymorphism in this gene run a higher risk of developing a penetrating behavior. Aims: We analyzed the association of BsmI, ApaI, TaqI, and FokI SNPs in the VDR gene with the clinical characteristics of CD. Methods: Four polymorphisms identified in the VDR gene (BsmI, FokI, ApaI, and TaqI) were genotyped in blood samples from CD patients (n = 115) by using PCR-RFLP. The disease’s location and behavior and the presence of perianal fistulas were collected from each patient. Intestinal fibroblasts from ileal resections of CD patients (n = 10) were genotyped, and the expression of fibrotic and inflammatory markers was analyzed by RT-PCR. Results: The data reveal no association between any of the polymorphisms and CD risk. A strong linkage disequilibrium was detected between TaqI and both ApaI and BsmI, which in turn were strongly associated. Homozygosis or heterozygosis for the a allele of the ApaI SNP or b allele of the BsmI SNP was significantly associated with a lower risk of a penetrating behavior, while the aa genotype was associated with a lower risk of perianal fistulas. Fibroblasts carrying the aa genotype expressed lower levels of fibrotic and inflammatory markers. Conclusion: The aa genotype of the ApaI SNP in the VDR gene is associated with a lower risk of perianal fistulas in CD and a reduced expression of fibrotic and inflammatory markers in intestinal fibroblasts.