Assessing ST18 gene polymorphisms (rs17315309, rs2304365) in Iraqi patients with Pemphigus vulgaris.

Pemphigus vulgaris (PV) is a potentially fatal autoimmune disease characterized by blistering of the skin, mucous membranes, and oral cavity. Genetics are implicated in its etiology, with the ST18 gene identified as a potential risk factor for pemphigus in certain populations, suggesting its role as a novel molecular target for therapeutic intervention. This study aimed to detect single nucleotide polymorphisms (SNPs) rs17315309 A/G and rs2304365 C/G in the ST18 gene among Iraqi/Arabic patients with PV. A total of 90 Iraqi subjects participated in this study, including 45 patients diagnosed with PV and 45 healthy controls. SNP analysis was performed using High-Resolution Melt Analysis (HRMA) with Eva Green I Dye. For SNP rs17315309 A/G, the distribution of heterozygous genotypes showed highly significant differences between the patient and healthy groups (P = 0.005), with the mutant G-allele being significantly more prevalent in patients than in the healthy group (P = 0.001). In contrast, for SNP rs2304365 C/G, the distribution of heterozygous and mutant genotypes did not differ significantly between patients and healthy individuals (P = 0.8 and P = 0.3, respectively), with the mutant G-allele also showing no significant difference (P = 0.4). Our data indicate a significant association between PV and the rs17315309 A/G SNP in the ST18 gene among the Iraqi population of Arabic origin. However, no association was found between patients with PV and the rs2304365 C/G SNP in the same gene.

The association of TMPRSS6 gene polymorphism with iron status in Egyptian children (a pilot study).

Several studies have shown association of single nucleotide polymorphisms (SNPs) of hepcidin regulatory pathways genes with impaired iron status. The most common is in the TMPRSS6 gene. In Africa, very few studies have been reported. We aimed to investigate the correlation between the common SNPs in the transmembrane protease, serine 6 (TMPRSS6) gene and iron indicators in a sample of Egyptian children for identifying the suitable candidate for iron supplementation.Patients and methods One hundred and sixty children aged 5-13 years were included & classified into iron deficient, iron deficient anemia and normal healthy controls. All were subjected to assessment of serum iron, serum ferritin, total iron binding capacity, complete blood count, reticulocyte count, serum soluble transferrin receptor and serum hepcidin. Molecular study of TMPRSS6 genotyping polymorphisms (rs4820268, rs855791 and rs11704654) were also evaluated.Results There was an association of iron deficiency with AG of rs855791 SNP, (P = 0.01). The minor allele frequency for included children were 0.43, 0.45 & 0.17 for rs4820268, rs855791 & rs11704654 respectively. Genotype GG of rs4820268 expressed the highest hepcidin gene expression fold, the lowest serum ferroportin & iron store compared to AA and AG genotypes (p = 0.05, p = 0.05, p = 0.03 respectively). GG of rs855791 had lower serum ferritin than AA (p = 0.04), lowest iron store & highest serum hepcidin compared to AA and AG genotypes (p = 0.04, p = 0.01 respectively). Children having CC of rs11704654 had lower level of hemoglobin, serum ferritin and serum hepcidin compared with CT genotype (p = 0.01, p = 0.01, p = 0.02) respectively.Conclusion Possible contribution of SNPs (rs855791, rs4820268 and rs11704654) to low iron status.

Mitochondrial point heteroplasmy: insights from deep-sequencing of human replicate samples.

BACKGROUND: Human mitochondrial heteroplasmy is an extensively investigated phenomenon in the context of medical diagnostics, forensic identification and molecular evolution. However, technical limitations of high-throughput sequencing hinder reliable determination of point heteroplasmies (PHPs) with minor allele frequencies (MAFs) within the noise threshold. RESULTS: To investigate the PHP landscape at an MAF threshold down to 0.1%, we sequenced whole mitochondrial genomes at approximately 7.700x coverage, in multiple technical and biological replicates of longitudinal blood and buccal swab samples from 11 human donors (159 libraries in total). The results obtained by two independent sequencing platforms and bioinformatics pipelines indicate distinctive PHP patterns below and above the 1% MAF cut-off. We found a high inter-individual prevalence of low-level PHPs (MAF < 1%) at polymorphic positions of the mitochondrial DNA control region (CR), their tissue preference, and a tissue-specific minor allele linkage. We also established the position-dependent potential of minor allele expansion in PHPs, and short-term PHP instability in a mitotically active tissue. We demonstrate that the increase in sensitivity of PHP detection to minor allele frequencies below 1% within a robust experimental and analytical pipeline, provides new information with potential applicative value. CONCLUSIONS: Our findings reliably show different mutational loads between tissues at sub-1% allele frequencies, which may serve as an informative medical biomarker of time-dependent, tissue-specific mutational burden, or help discriminate forensically relevant tissues in a single person, close maternal relatives or unrelated individuals of similar phylogenetic background.

Reference genome choice and filtering thresholds jointly influence phylogenomic analyses.

Molecular phylogenies are a cornerstone of modern comparative biology and are commonly employed to investigate a range of biological phenomena, such as diversification rates, patterns in trait evolution, biogeography, and community assembly. Recent work has demonstrated that significant biases may be introduced into downstream phylogenetic analyses from processing genomic data; however, it remains unclear whether there are interactions among bioinformatic parameters or biases introduced through the choice of reference genome for sequence alignment and variant-calling. We address these knowledge gaps by employing a combination of simulated and empirical data sets to investigate to what extent the choice of reference genome in upstream bioinformatic processing of genomic data influences phylogenetic inference, as well as the way that reference genome choice interacts with bioinformatic filtering choices and phylogenetic inference method. We demonstrate that more stringent minor allele filters bias inferred trees away from the true species tree topology, and that these biased trees tend to be more imbalanced and have a higher center of gravity than the true trees. We find greatest topological accuracy when filtering sites for minor allele count >3-4 in our 51-taxa data sets, while tree center of gravity was closest to the true value when filtering for sites with minor allele count >1-2. In contrast, filtering for missing data increased accuracy in the inferred topologies; however, this effect was small in comparison to the effect of minor allele filters and may be undesirable due to a subsequent mutation spectrum distortion. The bias introduced by these filters differs based on the reference genome used in short read alignment, providing further support that choosing a reference genome for alignment is an important bioinformatic decision with implications for downstream analyses. These results demonstrate that attributes of the study system and dataset (and their interaction) add important nuance for how best to assemble and filter short read genomic data for phylogenetic inference.

Clinical Impact of Single Nucleotide Polymorphism in CD-19 on Treatment Outcome in FMC63-CAR-T Cell Therapy.

Chimeric antigen receptor (CAR)-T cell therapy is effective in patients with relapsed or refractory diffuse large B-cell lymphoma (r/r DLBCL) with response rates of 63-84% and complete response observed in 43-54%. Common germline variants of the target antigen CD19 may elicit different responses to CAR-T cell therapy. The CD19 gene single nucleotide polymorphism rs2904880 encoding leucine or valine at amino acid position 174 of the CD19 antigen was prevalent in 51% of the studied DLBCL patients. In a retrospective comparative analysis of clinical outcome, there were significant differences in CD19 L174 versus V174 carriers: the median time of progression-free survival was 22 vs. 6 months (p = 0.06), overall survival was 37 vs. 8 months (p = 0.11), complete response rates were 51% vs. 30% (p = 0.05), and refractory disease rates were 14% vs. 32% (p = 0.04). The single nucleotide polymorphism in CD19 was shown to influence the treatment outcome in FMC63-anti-CD19-CAR-T cell therapy, and the CD19 minor allele L174 predicted a favorable treatment outcome.

Peroxisome Proliferator-Activated Receptor α and γ Gene Polymorphisms among South Indian Patients with Diabetic Dyslipidaemia.

Background: Peroxisome proliferator-activated receptors (PPAR) α and γ genes play an important role in dyslipidaemia of T2DM. Aims: To estimate the frequency distribution of PPAR α and γ gene polymorphisms in South Indian T2DM patients with dyslipidaemia compared to healthy controls. Normative frequencies of SNPs were established and compared with data for 1000 genome populations. Methods: Eligible 382 cases and 336 age and sex-matched controls were enrolled. Six SNPs in PPARα [rs1800206 C>G (Leu162Val), rs4253778 G>C, rs135542 T>C] and PPARγ [rs3856806 (C>T), rs10865710 (C>G), rs1805192 C>G (Pro12Ala)] genes were selected for genotyping. Results: The allele and gene frequencies did not significantly differ between the diabetic dyslipidaemia cases and healthy controls. However, they were significantly different from that of 1000 genome populations except for rs1800206 C>G (Leu162Val) and rs1805192 C>G (Pro12Ala). Conclusion: The studied polymorphisms in PPARα and PPARγ genes are not associated with diabetic dyslipidaemia among South Indian patients.

High producer variant of lipoprotein lipase may protect from hepatocellular carcinoma in alcohol-associated cirrhosis.

Background & Aims: Progression of alcohol-associated liver disease (ALD) is driven by genetic predisposition. The rs13702 variant in the lipoprotein lipase (LPL) gene is linked to non-alcoholic fatty liver disease. We aimed at clarifying its role in ALD. Methods: Patients with alcohol-associated cirrhosis, with (n = 385) and without hepatocellular carcinoma (HCC) (n = 656), with HCC attributable to viral hepatitis C (n = 280), controls with alcohol abuse without liver damage (n = 366), and healthy controls (n = 277) were genotyped regarding the LPL rs13702 polymorphism. Furthermore, the UK Biobank cohort was analysed. LPL expression was investigated in human liver specimens and in liver cell lines. Results: Frequency of the LPL rs13702 CC genotype was lower in ALD with HCC in comparison to ALD without HCC both in the initial (3.9% vs. 9.3%) and the validation cohort (4.7% vs. 9.5%; p <0.05 each) and compared with patients with viral HCC (11.4%), alcohol misuse without cirrhosis (8.7%), or healthy controls (9.0%). This protective effect (odds ratio [OR] = 0.5) was confirmed in multivariate analysis including age (OR = 1.1/year), male sex (OR = 3.0), diabetes (OR = 1.8), and carriage of the PNPLA3 I148M risk variant (OR = 2.0). In the UK Biobank cohort, the LPL rs13702 C allele was replicated as a risk factor for HCC. Liver expression of LPL mRNA was dependent on LPL rs13702 genotype and significantly higher in patients with ALD cirrhosis compared with controls and alcohol-associated HCC. Although hepatocyte cell lines showed negligible LPL protein expression, hepatic stellate cells and liver sinusoidal endothelial cells expressed LPL. Conclusions: LPL is upregulated in the liver of patients with alcohol-associated cirrhosis. The LPL rs13702 high producer variant confers protection against HCC in ALD, which might help to stratify people for HCC risk. Impact and implications: Hepatocellular carcinoma is a severe complication of liver cirrhosis influenced by genetic predisposition. We found that a genetic variant in the gene encoding lipoprotein lipase reduces the risk for hepatocellular carcinoma in alcohol-associated cirrhosis. This genetic variation may directly affect the liver, because, unlike in healthy adult liver, lipoprotein lipase is produced from liver cells in alcohol-associated cirrhosis.

Impact of genetic variants involved in the lipid metabolism pathway on progression free survival in patients receiving bevacizumab-based chemotherapy in metastatic colorectal cancer: a retrospective analysis of FIRE-3 and MAVERICC trials.

Background: Antiangiogenic drug (AAD)-triggered oxygen and nutrient depletion through suppression of angiogenesis switches glucose-dependent to lipid-dependent metabolism. Blocking fatty acid oxidation can enhance AAD-mediated anti-tumor effects in colorectal cancer (CRC). Therefore, we hypothesised that genetic variants in the lipid metabolism pathway may predict clinical outcomes [overall response rate (ORR), overall survival (OS) and progression-free survival (PFS)] in metastatic CRC (mCRC) patients receiving bevacizumab-based first-line treatment. Methods: Genomic DNA from blood samples of patients enrolled in FIRE-3 (a global, randomised, open-label, phase 3 trial, between 2007-6-23 and 2012-9-19, discovery cohort: FOLFIRI/bevacizumab arm, n = 107; control cohort: FOLFIRI/cetuximab arm, n = 129) and MAVERICC (a global, randomised, open-label, phase II study, between 2011-8 and 2015-7, in United States, Canada, Estonia, Ireland, Switzerland, Norway, and Portugal. Validation cohort: FOLFIRI/bevacizumab arm, n = 163) trials, was genotyped using the OncoArray-500 K beadchip panel. The impact on OS and PFS of 17 selected SNPs in 7 genes involved in the lipid metabolism pathway (CD36, FABP4, LPCAT1/2, CPT1A, FASN, ACACA) was analysed using Kaplan-Meier curves, the log-rank test for univariate analyses and likelihood ratio tests of Cox proportional hazards regression parameters for multivariable analyses. ORR and SNP associations were evaluated using Chi-square or Fisher's exact tests. Findings: In the discovery cohort, patients with FASN rs4485435 any C allele (n = 21) showed significantly shorter PFS (median PFS: 8.69 vs 13.48 months) compared to carriers of G/G (n = 62) in multivariable (HR = 2.87; 95%CI 1.4-5.9; p = 0.00675) analysis. These data were confirmed in the validation cohort in multivariable analysis (HR = 2.07, 95%CI: 1.15-3.74; p = 0.02), but no association was observed in the cetuximab cohort of FIRE-3. In the comparison of bevacizumab vs cetuximab arm in FIRE-3, a significant interaction was shown with FASN rs4485435 (p = 0.017) on PFS. Interpretation: Our study demonstrates for the first time, to our knowledge, that FASN polymorphisms may predict outcome of bevacizumab-based treatment in patients with mCRC. These findings support a possible role of the lipid metabolism pathway in contributing to resistance to anti-VEGF treatment. Funding: This work was supported by the National Cancer Institute [P30CA 014089 to H.-J.L.], Gloria Borges WunderGlo Foundation, Dhont Family Foundation, Victoria and Philip Wilson Research Fund, San Pedro Peninsula Cancer Guild, Ming Hsieh Research Fund, Eddie Mahoney Memorial Research Fund, Shanghai Sailing Program (22YF1407000), China National Postdoctoral Program for Innovative Talents (BX20220084), China Postdoctoral Science Foundation (2022M710768), National Natural Science Foundation of China (82202892).

Identifying Novel Genes and Variants in Immune and Coagulation Pathways Associated with Macular Degeneration.

Purpose: To select individuals and families with a low genetic burden for age-related macular degeneration (AMD), to inform the clinical diagnosis of macular disorders, and to find novel genetic variants associated with maculopathies. Design: Genetic association study based on targeted and whole-exome sequencing. Participants: A total of 758 subjects (481 individuals with maculopathy and 277 controls), including 316 individuals in 72 families. Methods: We focused on 150 genes involved in the complement, coagulation, and inflammatory pathways. Single-variant tests were performed on 7755 variants shared among ≥ 5 subjects using logistic regression. Gene-based tests were used to evaluate aggregate effects from rare and low-frequency variants (at minor allele frequency [MAF] ≤ 5% or ≤ 1%) in a gene using burden tests. For families whose affected members had a low burden of genetic risk based on known common and rare variants related to AMD, we searched for rare variants (MAF < 0.001) whose risk alleles occurred in ≥ 80% of affected individuals but not in controls. Immunohistochemistry was performed to determine the protein expression of a novel gene (coagulation factor II thrombin receptor-like 2 [F2RL2]) in retinal tissues. Main Outcome Measures: Genotypes and phenotypes of macular degeneration. Results: We confirmed the association of a synonymous variant in complement factor H (Ala473, rs2274700, proxy to intronic rs1410996, r 2  = 1) with maculopathy (odds ratio, 0.64; P = 4.5 × 10-4). Higher AMD polygenic risk scores (PRSs) were associated with intermediate and advanced AMD. Among families with low PRSs and no known rare variants for maculopathy, we identified 2 novel, highly penetrant missense rare variants in ADAM15, A disintegrin and metalloprotease, metallopeptidase domain 15 (p.Arg288Cys) and F2RL2 (p.Leu289Arg). Immunohistochemistry analyses revealed F2RL2 protein expression in cone photoreceptor outer segments and Müller glia cells of human and pig retinas. Coagulation factor II thrombin receptor-like 2 expression appeared increased in fibrotic areas in advanced AMD samples with neovascularization, suggesting that F2RL2 may play a role in the progression to advanced macular disease. Conclusions: New missense rare variants in the genes ADAM15 and F2RL2 were associated with maculopathies. Results suggest that novel genes related to the coagulation and immune pathways may be involved in the pathogenesis of macular diseases.

Genome-wide Association Study of Axial Length in Population-based Cohorts in Japan: The Tohoku Medical Megabank Organization Eye Study.

Purpose: To elucidate the differences in ocular biometric parameters by generation and gender and to identify axial length (AL)-associated genetic variants in Japanese individuals, we analyzed Tohoku Medical Megabank Organization (ToMMo) Eye Study data. Design: We designed the ToMMo Eye Study, examined AL variations, and conducted genome-wide association studies (GWASs). Participants: In total, 33 483 participants aged > 18 years who were recruited into the community-based cohort (CommCohort) and the birth and three-generation cohort (BirThree Cohort) of the ToMMo Eye Study were examined. Methods: Each participant was screened with an interview, ophthalmic examinations, and a microarray analysis. The GWASs were performed in 22 379 participants in the CommCohort (discovery stage) and 11 104 participants in the BirThree Cohort (replication stage). We evaluated the associations of single nucleotide polymorphisms (SNPs) with AL using a genome-wide significance threshold (5 × 10-8) in each stage of the study and in the subsequent meta-analysis. Main Outcome Measures: We identified the association of SNPs with AL and distributions of AL in right and left eyes and individuals of different sexes and ages. Results: In the discovery stage, the mean AL of the right eye (23.99 mm) was significantly greater than that of the left eye (23.95 mm). This difference was reproducible across sexes and ages. The GWASs revealed 703 and 215 AL-associated SNPs with genome-wide significance in the discovery and validation stages, respectively, and many of the SNPs in the discovery stage were replicated in the validation stage. Validated SNPs and their associated loci were meta-analyzed for statistical significance (P < 5 × 10-8). This study identified 1478 SNPs spread over 31 loci. Of the 31 loci, 5 are known AL loci, 15 are known refractive-error loci, 4 are known corneal-curvature loci, and 7 loci are newly identified loci that are not known to be associated with AL. Of note, some of them shared functional relationships with previously identified loci. Conclusions: Our large-scale GWASs exploiting ToMMo Eye Study data identified 31 loci linked to variations in AL, 7 of which are newly reported in this article. The results revealed genetic heterogeneity and similarity in SNPs related to ethnic variations in AL.

NGS allele counts versus called genotypes for testing genetic association.

RNA sequence data are commonly summarized as read counts. By contrast, so far there is no alternative to genotype calling for investigating the relationship between genetic variants determined by next-generation sequencing (NGS) and a phenotype of interest. Here we propose and evaluate the direct analysis of allele counts for genetic association tests. Specifically, we assess the potential advantage of the ratio of alternative allele counts to the total number of reads aligned at a specific position of the genome (coverage) over called genotypes. We simulated association studies based on NGS data from HapMap individuals. Genotype quality scores and allele counts were simulated using NGS data from the Personal Genome Project. Real data from the 1000 Genomes Project was also used to compare the two competing approaches. The average proportions of probability values lower or equal to 0.05 amounted to 0.0496 for called genotypes and 0.0485 for the ratio of alternative allele counts to coverage in the null scenario, and to 0.69 for called genotypes and 0.75 for the ratio of alternative allele counts to coverage in the alternative scenario (9% power increase). The advantage in statistical power of the novel approach increased with decreasing coverage, with decreasing genotype quality and with decreasing allele frequency - 124% power increase for variants with a minor allele frequency lower than 0.05. We provide computer code in R to implement the novel approach, which does not preclude the use of complementary data quality filters before or after identification of the most promising association signals. Author summary: Genetic association tests usually rely on called genotypes. We postulate here that the direct analysis of allele counts from sequence data improves the quality of statistical inference. To evaluate this hypothesis, we investigate simulated and real data using distinct statistical approaches. We demonstrate that association tests based on allele counts rather than called genotypes achieve higher statistical power with controlled type I error rates.

NAToRA, a relatedness-pruning method to minimize the loss of dataset size in genetic and omics analyses.

Genetic and omics analyses frequently require independent observations, which is not guaranteed in real datasets. When relatedness cannot be accounted for, solutions involve removing related individuals (or observations) and, consequently, a reduction of available data. We developed a network-based relatedness-pruning method that minimizes dataset reduction while removing unwanted relationships in a dataset. It uses node degree centrality metric to identify highly connected nodes (or individuals) and implements heuristics that approximate the minimal reduction of a dataset to allow its application to complex datasets. When compared with two other popular population genetics methodologies (PLINK and KING), NAToRA shows the best combination of removing all relatives while keeping the largest possible number of individuals in all datasets tested and also, with similar effects on the allele frequency spectrum and Principal Component Analysis than PLINK and KING. NAToRA is freely available, both as a standalone tool that can be easily incorporated as part of a pipeline, and as a graphical web tool that allows visualization of the relatedness networks. NAToRA also accepts a variety of relationship metrics as input, which facilitates its use. We also release a genealogies simulator software used for different tests performed in this study.

Assessing accuracy of genotype imputation in the Afrikaner and Brahman cattle breeds of South Africa.

Imputation may be used to rescue genomic data from animals that would otherwise be eliminated due to a lower than desired call rate. The aim of this study was to compare the accuracy of genotype imputation for Afrikaner, Brahman, and Brangus cattle of South Africa using within- and multiple-breed reference populations. A total of 373, 309, and 101 Afrikaner, Brahman, and Brangus cattle, respectively, were genotyped using the GeneSeek Genomic Profiler 150 K panel that contained 141,746 markers. Markers with MAF ≤ 0.02 and call rates ≤ 0.95 or that deviated from Hardy Weinberg Equilibrium frequency with a probability of ≤ 0.0001 were excluded from the data as were animals with a call rate ≤ 0.90. The remaining data included 99,086 SNPs and 360 Afrikaner, 75,291 SNPs and 288 animals Brahman, and 97,897 SNPs and 99 Brangus animals. A total of 7986, 7002, and 7000 SNP from 50 Afrikaner and Brahman and 30 Brangus cattle, respectively, were masked and then imputed using BEAGLE v3 and FImpute v2. The within-breed imputation yielded accuracies ranging from 89.9 to 96.6% for the three breeds. The multiple-breed imputation yielded corresponding accuracies from 69.21 to 88.35%. The results showed that population homogeneity and numerical representation for within and across breed strategies, respectively, are crucial components for improving imputation accuracies.

Prediction ability for growth and maternal traits using SNP arrays based on different marker densities in Nellore cattle using the ssGBLUP.

This study aimed to investigate the prediction ability for growth and maternal traits using different low-density customized SNP arrays selected by informativeness and distribution of markers across the genome employing single-step genomic BLUP (ssGBLUP). Phenotypic records for adjusted weight at 210 and 450 days of age were utilized. A total of 945 animals were genotyped with high-density chip, and 267 individuals born after 2008 were selected as validation population. We evaluated 11 scenarios using five customized density arrays (40 k, 20 k, 10 k, 5 k and 2 k) and the HD array was used as desirable scenario. The GEBV predictions and BIF (Beef Improvement Federation) accuracy were obtained with BLUPF90 family programs. Linear regression was used to evaluate the prediction ability, inflation, and bias of GEBV of each customized array. An overestimation of partial GEBVs in contrast with complete GEBVs and increase of BIF accuracy with the density arrays diminished were observed. For all traits, the prediction ability was higher as the array density increased and it was similar with customized arrays higher than 10 k SNPs. Level of inflation was lower as the density array increased of and was higher for MW210 effect. The bias was susceptible to overestimation of GEBVs when the density customized arrays decreased. These results revealed that the BIF accuracy is sensible to overestimation using low-density customized arrays while the prediction ability with least 10,000 informative SNPs obtained from the Illumina BovineHD BeadChip shows accurate and less biased predictions. Low-density customized arrays under ssGBLUP method could be feasible and cost-effective in genomic selection.

In-silico analysis of nonsynonymous genomic variants within CCM2 gene reaffirm the existence of dual cores within typical PTB domain.

PURPOSE: The objective of this study is to validate the existence of dual cores within the typical phosphotyrosine binding (PTB) domain and to identify potentially damaging and pathogenic nonsynonymous coding single nuclear polymorphisms (nsSNPs) in the canonical PTB domain of the CCM2 gene that causes cerebral cavernous malformations (CCMs). METHODS: The nsSNPs within the coding sequence for PTB domain of human CCM2 gene, retrieved from exclusive database searches, were analyzed for their functional and structural impact using a series of bioinformatic tools. The effects of mutations on the tertiary structure of the PTB domain in human CCM2 protein were predicted to examine the effect of nsSNPs on the tertiary structure of PTB Cores. RESULTS: Our mutation analysis, through alignment of protein structures between wildtype CCM2 and mutant, predicted that the structural impacts of pathogenic nsSNPs is biophysically limited to only the spatially adjacent substituted amino acid site with minimal structural influence on the adjacent core of the PTB domain, suggesting both cores are independently functional and essential for proper CCM2 PTB function. CONCLUSION: Utilizing a combination of protein conservation and structure-based analysis, we analyzed the structural effects of inherited pathogenic mutations within the CCM2 PTB domain. Our results predicted that the pathogenic amino acid substitutions lead to only subtle changes locally, confined to the surrounding tertiary structure of the PTB core within which it resides, while no structural disturbance to the neighboring PTB core was observed, reaffirming the presence of independently functional dual cores in the CCM2 typical PTB domain.

Dissecting the contribution of single nucleotide polymorphisms in CCR9 and CCL25 genomic regions to the celiac disease phenotype.

PURPOSE AND OBJECTIVES: Given their role in homing immune cells to the intestine, CC motif chemokine receptor 9 (CCR9) and its specific ligand CC motif chemokine ligand 25 (CCL25) are interesting candidate genes for celiac disease. These genes are located in regions previously shown to be associated with or linked to celiac disease, but no investigations on their association with various celiac disease phenotypes have so far been conducted. Here we studied such associations of both genotyped and imputed single nucleotide polymorphisms (SNPs) with either regulatory function or exonic location of the CCR9 and CCL25 loci. RESULTS: Exploiting a carefully phenotyped cohort of 625 celiac disease patients and 1817 non-celiac controls, we identified that multiple SNPs with predicted regulatory function (RegulomeDB score ≤3a and/or eQTL effect) located between 100 kB upstream and downstream of CCR9 and CCL25 are associated with celiac disease and/or selected phenotypes. Of the genotyped SNPs in the CCR9 loci, rs213360 with an eQTL effect on CCR9 expression in blood was associated with celiac disease and all investigated phenotypes except high HLA risk. Rs1545985 with an eQTL on CCR9 expression and rs7652331 and rs12493471, both with RegulomeDB score ≤3a, were all associated with gastrointestinal symptoms and malabsorption and the latter additionally with anemia. The genotyped CCL25 SNPs rs952444 and rs882951, with RegulomeDB scores 1d and 1f respectively and eQTL effect on CCL25 expression in small intestine, were associated with gastrointestinal symptoms and malabsorption. The CCL25 SNP rs2303165 identified in sequencing followed by imputation was associated with partial villous atrophy. However, the association did not pass the permutation based multiple testing correction (PEMP2 > 0.05). CONCLUSIONS: We conclude that SNPs in the region of CCR9 and CCL25 with predicted functional effect or exonic localization likely contribute only modestly to various celiac disease phenotypes.

Using a Machine Learning Approach to Identify Low-Frequency and Rare FLG Alleles Associated with Remission of Atopic Dermatitis.

Atopic dermatitis (AD) is a common relapsing inflammatory skin disease. FLG is the gene most consistently associated with AD. Loss-of-function variants in FLG have been previously associated with AD. Low-frequency and rare alleles (minor allele frequency < 5%) in this gene have been given less attention than loss-of-function variants. We fine sequenced the FLG gene in a cohort of individuals with AD. We developed a machine learning‒based algorithm to associate low-frequency and rare alleles with the disease. We then applied this algorithm to the FLG data, searching for associations between groups of low-frequency and rare FLG alleles and AD remission. A group of 46 rare and low-frequency FLG alleles was associated with increased AD remission (P = 2.76e-11). Overall, 16 of these 46 FLG variants were identified in an independent cohort and were associated with decreased AD incidence (P = 0.0007). This study presents an application of statistical methods in AD genetics and suggests that low-frequency and rare alleles may play a larger role in AD pathogenesis than previously appreciated.

Improved Estimation of Phenotypic Correlations Using Summary Association Statistics.

Estimating the phenotypic correlations between complex traits and diseases based on their genome-wide association summary statistics has been a useful technique in genetic epidemiology and statistical genetics inference. Two state-of-the-art strategies, Z-score correlation across null-effect single nucleotide polymorphisms (SNPs) and LD score regression intercept, were widely applied to estimate phenotypic correlations. Here, we propose an improved Z-score correlation strategy based on SNPs with low minor allele frequencies (MAFs), and show how this simple strategy can correct the bias generated by the current methods. The low MAF estimator improves phenotypic correlation estimation, thus it is beneficial for methods and applications using phenotypic correlations inferred from summary association statistics.

Genomic epidemiology of the first epidemic wave of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Palestine.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the novel coronavirus responsible for the COVID-19 pandemic, continues to cause a significant public-health burden and disruption globally. Genomic epidemiology approaches point to most countries in the world having experienced many independent introductions of SARS-CoV-2 during the early stages of the pandemic. However, this situation may change with local lockdown policies and restrictions on travel, leading to the emergence of more geographically structured viral populations and lineages transmitting locally. Here, we report the first SARS-CoV-2 genomes from Palestine sampled from early March 2020, when the first cases were observed, through to August of 2020. SARS-CoV-2 genomes from Palestine fall across the diversity of the global phylogeny, consistent with at least nine independent introductions into the region. We identify one locally predominant lineage in circulation represented by 50 Palestinian SARS-CoV-2, grouping with genomes generated from Israel and the UK. We estimate the age of introduction of this lineage to 05/02/2020 (16/01/2020-19/02/2020), suggesting SARS-CoV-2 was already in circulation in Palestine predating its first detection in Bethlehem in early March. Our work highlights the value of ongoing genomic surveillance and monitoring to reconstruct the epidemiology of COVID-19 at both local and global scales.

The genetic architecture of human complex phenotypes is modulated by linkage disequilibrium and heterozygosity.

We propose an extended Gaussian mixture model for the distribution of causal effects of common single nucleotide polymorphisms (SNPs) for human complex phenotypes that depends on linkage disequilibrium (LD) and heterozygosity (H), while also allowing for independent components for small and large effects. Using a precise methodology showing how genome-wide association studies (GWASs) summary statistics (z-scores) arise through LD with underlying causal SNPs, we applied the model to GWAS of multiple human phenotypes. Our findings indicated that causal effects are distributed with dependence on total LD and H, whereby SNPs with lower total LD and H are more likely to be causal with larger effects; this dependence is consistent with models of the influence of negative pressure from natural selection. Compared with the basic Gaussian mixture model it is built on, the extended model-primarily through quantification of selection pressure-reproduces with greater accuracy the empirical distributions of z-scores, thus providing better estimates of genetic quantities, such as polygenicity and heritability, that arise from the distribution of causal effects.