Individual Single Nucleotide Polymorphisms Research Articles

The Frailty Index and colon cancer: a 2-sample Mendelian-randomization study.

Frailty is closely related to cancer. Previous research has shown that cancer patients are prone to frailty, and frailty increases the risk of adverse outcomes in cancer patients. However, it is unclear whether frailty increases the risk of cancer. This 2-sample Mendelian-randomization (MR) study sought to analyze the relationship between frailty and the risk of colon cancer. The database was extracted from the Medical Research Council Integrative Epidemiology Unit (MRC-IEU) in 2021. The genome-wide association study (GWAS) data related to colon cancer was obtained from the GWAS website (http://gwas.mrcieu.ac.uk/datasets), involving 462,933 individuals' gene information. Single-nucleotide polymorphisms (SNPs) were defined as the instrumental variables (IVs). The SNPs closely associated with the Frailty Index at a genome-wide significance level were selected. To further screen the IVs, we selected the confounding factors using the PhenoScanner (http://www.phenoscanner.medschl.cam.ac.uk/phenoscanner). To estimate the causal effect of the Frailty Index on colon cancer, the MR-Egger regression, weighted median (WM1), inverse-variance weighted (IVW), and weight mode (WM2) methods were applied to calculate the SNP-frailty index and the SNP-cancer estimates. Cochran's Q statistic was used to estimate heterogeneity. The two-sample Mendelian randomization (TSMR) analysis was performed using the "TwoSampleMR" and "plyr" packages. All the statistical tests were 2-tailed, and a P value <0.05 was considered statistically significant. We selected 8 SNPs as the IVs. The results of the IVW analysis [odds ratio (OR) =0.995, 95% confidence interval (CI): 0.990-1.001, P=0.052] showed that the genetic changes in the Frailty Index were not statistically associated with the risk of colon cancer, and no significant heterogeneity between these 8 genes was observed (Q =7.382, P=0.184). The MR-Egger (OR =0.987, 95% CI: 0.945-1.031, P=0.581), WM1 (OR =0.995, 95% CI: 0.990-1.001, P=0.118), WM2 (OR =0.996, 95% CI: 0.988-1.004, P=0.356), and SM (OR =0.996, 95% CI: 0.987-1.005, P=0.449) results were also consistent with each other. The sensitivity analysis based on the leave-one-out method showed that the individual SNPs did not affect the robustness of the results. Frailty might have no effect on the risk of colon cancer.

Interactions of SNPs in Folate Metabolism Related Genes on Prostate Cancer Aggressiveness in European Americans and African Americans.

Studies showed that folate and related single nucleotide polymorphisms (SNPs) could predict prostate cancer (PCa) risk. However, little is known about the interactions of folate-related SNPs associated with PCa aggressiveness. The study's objective is to evaluate SNP-SNP interactions among the DHFR 19-bp polymorphism and 10 SNPs in folate metabolism and the one-carbon metabolism pathway associated with PCa aggressiveness. We evaluated 1294 PCa patients, including 690 European Americans (EAs) and 604 African Americans (AAs). Both individual SNP effects and pairwise SNP-SNP interactions were analyzed. None of the 11 individual polymorphisms were significant for EAs and AAs. Three SNP-SNP interaction pairs can predict PCa aggressiveness with a medium to large effect size. For the EA PCa patients, the interaction between rs1801133 (MTHFR) and rs2236225 (MTHFD1), and rs1801131 (MTHFR) and rs7587117 (SLC4A5) were significantly associated with aggressive PCa. For the AA PCa patients, the interaction of DHFR-19bp polymorphism and rs4652 (LGALS3) was significantly associated with aggressive PCa. These SNP-SNP interactions in the folate metabolism-related genes have a larger impact than SNP individual effects on tumor aggressiveness for EA and AA PCa patients. These findings can provide valuable information for potential biological mechanisms of PCa aggressiveness.

Intergenic Interactions of SBNO1, NFAT5 and GLT8D1 Determine the Susceptibility to Knee Osteoarthritis among Europeans of Russia.

This study was conducted to examine the associations between genome-wide association studies (GWAS)-important single nucleotide polymorphisms (SNPs) and knee osteoarthritis (KOA) among Europeans of Russia. The present replicative study ("patient-control" design has been used) was carried out on 1000 DNA samples from KOA (n = 500) and KOA-free (n = 500) participants. Ten GWAS-important for KOA SNPs of eight candidate genes (LYPLAL1, GNL3, GLT8D1, SBNO1, WWP2, NFAT5, TGFA, GDF5) were studied. To assess the link between SNPs and KOA susceptibility, logistic regression (to establish independent SNP effects) and MB-MDR (to identify SNP-SNP interactions) were used. As a result of this genetic analysis, the associations of individual SNPs with KOA have not been proven. Eight loci out of ten tested SNPs interacted with each other (within twelve genetic models) and determined susceptibility to KOA. The greatest contribution to the disease development were made by three polymorphisms/genes such as rs6976 (C>T) GLT8D1, rs56116847 (G>A) SBNO1, rs6499244 (T>A) NFAT5 (each was included in 2/3 [8 out 12] KOA-responsible genetic interaction models). A two-locus epistatic interaction of rs56116847 (G >A) SBNO1 × rs6499244 (T>A) NFAT5 determined the maximum percentage (0.86%) of KOA entropy. KOA-associated SNPs are regulatory polymorphisms that affect the expression/splicing level, epigenetic modification of 72 genes in KOA-pathogenetically significant organs such as skeletal muscles, tibial arteries/nerves, thyroid, adipose tissue, etc. These putative KOA-effector genes are mainly involved in the organization/activity of the exoribonuclease complex and antigen processing/presentation pathways. In conclusion, KOA susceptibility among Europeans of Russia is mediated by intergenic interactions (but not the main effects) of GWAS-important SNPs.

Genetic variants of glucose metabolism and exposure to smoking in African American breast cancer.

Insulin resistance (IR) is a well-established risk factor for breast cancer (BC) development in African American (AA) postmenopausal women. While obesity and IR are more prevalent in AA than in white women, they are under-represented in genome-wide studies for systemic regulation of IR. By examining 780 genome-wide IR single-nucleotide polymorphisms (SNPs) available in our data, we tested 4689 AA women in a Random Survival Forest framework. With 37 BC-associated lifestyle factors, we conducted a gene-environment interaction analysis to estimate risk prediction for BC with the most influential genetic and behavioral factors and evaluated their combined and joint effects on BC risk. By accounting for variations of individual SNPs in BC in the prediction model, we detected four fasting glucose-associated SNPs in PCSK1, SPC25, ADCY5, and MTNR1B and three lifestyle factors (smoking, oral contraceptive use, and age at menopause) as the most predictive markers for BC risk. Our joint analysis of risk genotypes and lifestyle with smoking revealed a synergistic effect on the increased risk of BC, particularly estrogen/progesterone positive (ER/PR+) BC, in a gene-lifestyle dose-dependent manner. The joint effect of smoking was more substantial in women with prolonged exposure to cigarette smoking and female hormones. The top genome-wide association-SNPs associated with metabolic biomarkers in combination with lifestyles synergistically increase the predictability of invasive ER/PR+ BC risk among AA women. Our findings highlight generically targeted preventive interventions for women who carry particular risk genotypes and lifestyles.

Association of Single Nucleotide Polymorphisms in KCNA10 and SLC13A3 Genes with the Susceptibility to Chronic Kidney Disease of Unknown Etiology in Central Indian Patients.

Global rise in the prevalence of endemic chronic kidney disease of unknown etiology (CKDu) possess major health issues. The prevalence of CKDu is also rising in the Indian population. Besides environmental factors, genetic factors play an important role in the predisposition to CKDu. In the present study, we have analyzed the association of single nucleotide polymorphisms (SNPs) in three genes with the susceptibility to CKDu. This was a case-control study with a total of 180 adult subjects (CKD = 60, CKDu = 60, Healthy = 60) from central India. We performed KASP genotyping assay to determine the allele frequency of SNP genotypes. We used the odds ratio (OR) to assess the association of individual SNPs, rs34970857 of KCNA10, rs6066043 of SLC13A3, and rs2910164 of miR-146a with CKDu and CKD susceptibility. In the case of rs34970857 of the KCNA10 gene, we noted a significantly increased OR for CKDu versus healthy control (Dominant model; CKDu versus control, CT + CC versus TT, OR = 3.96, p = 0.004). In the recessive and homozygous model, we observed significantly increased OR for rs6066043 of SLC13A3 gene, CKDu versus healthy control {(Recessive model; CKDu versus control, GG versus AA + GA, OR = 2.41, p = 0.03; homozygous model, GG versus AA, OR = 3.54, p = 0.04)}. CC genotype of rs34970857 of the KCNA10 gene and the GG genotype of the SLC13A3 gene are significantly associated with the susceptibility of CKDu.

Genome-wide association study of agronomical and root-related traits in spring barley collection grown under field conditions.

The root system is a key component for plant survival and productivity. In particular, under stress conditions, developing plants with a better root architecture can ensure productivity. The objectives of this study were to investigate the phenotypic variation of selected root- and yield-related traits in a diverse panel of spring barley genotypes. By performing a genome-wide association study (GWAS), we identified several associations underlying the variations occurring in root- and yield-related traits in response to natural variations in soil moisture. Here, we report the results of the GWAS based on both individual single-nucleotide polymorphism markers and linkage disequilibrium (LD) blocks of markers for 11 phenotypic traits related to plant morphology, grain quality, and root system in a group of spring barley accessions grown under field conditions. We also evaluated the root structure of these accessions by using a nondestructive method based on electrical capacitance. The results showed the importance of two LD-based blocks on chromosomes 2H and 7H in the expression of root architecture and yield-related traits. Our results revealed the importance of the region on the short arm of chromosome 2H in the expression of root- and yield-related traits. This study emphasized the pleiotropic effect of this region with respect to heading time and other important agronomic traits, including root architecture. Furthermore, this investigation provides new insights into the roles played by root traits in the yield performance of barley plants grown under natural conditions with daily variations in soil moisture content.

Plasma Cytokine Levels and Cytokine Genetic Polymorphisms in Patients with Metastatic Breast Cancer Receiving High-Dose Chemotherapy

Differences in the baseline levels of serum cytokines or in single-nucleotide polymorphisms (SNPs) in cytokine genes may be useful to predict outcomes for patients being treated for metastatic breast cancer. We have measured the plasma levels and characterized individual SNPs for IL-1RA, IL-1β, IL-2, IL-6 and TNFα in 130 patients with metastatic breast cancer treated with high-dose chemotherapy. Patients were treated with high-dose cyclophosphamide (Group 1, 74 patients) or high-dose paclitaxel-containing regimens (Group 2, 56 patients). A high plasma level of IL-1RA and a SNP in the IL-1RA gene indicated a better prognosis for patients in Group 1 (but not Group 2). However, the level of plasma IL-1RA did not correlate with the SNP genotype. A high plasma level of IL-6 or TNFα indicated a poorer outcome for patients in Group 1 although the SNP genotypes for the IL-6 and TNFα SNPs were not associated with differences in outcome. The plasma levels of IL-1β and IL-2 and the genotype of the IL-1β SNPs did not indicate differences in outcome. Although, individually, plasma levels of cytokine or “risk” SNP genotypes may not indicate outcome, in combination there was an increased trend to predict outcome for patients treated with high-dose cyclophosphamide but not high-dose paclitaxel. These results suggest that the immune cytokines may be useful as prognostic biomarkers in the treatment of patients with metastatic breast cancer treated with different types of chemotherapy.

Causal relationship between moderate to vigorous physical activity and venous thromboembolism.

Previous studies have shown conflicting results about the impact of moderate to vigorous physical activity on the risk of venous thromboembolism (VTE). Using Mendelian randomization, we assessed whether moderate to vigorous physical activity causally affects VTE from genetic level. Genetic instruments associated with moderate to vigorous physical activity at the genome-wide significance level (P < 5×10- 8) were selected from the UK Biobank. Summary-level data for VTE were obtained from the FinnGen consortium. Univariable and multivariable Mendelian randomization analyses were conducted. Genetically predicted moderate to vigorous physical activity had no effect on VTE [odds ratio (OR) = 1.08; 95% confidence interval (CI) 0.66-1.78; P = 0.75] under a multiplicative random-effects inverse-variance weighted model. MR-Egger (OR = 0.20; 95% CI 0.01-4.70; P = 0.33), weighted median (OR = 1.08; 95% CI 0.52-2.25; P = 0.84), simple mode (OR = 2.53; 95% CI 0.59-10.92; P = 0.23), weighted mode (OR = 2.21; 95% CI 0.50-9.74; P = 0.31), and multivariable Mendelian randomization (OR = 0.74; 95% CI 0.46-1.19; P = 0.22) also yielded no significant association. The overall estimate was not influenced by individual single nucleotide polymorphism. No evidence of heterogeneity or horizontal pleiotropy was observed. Therefore, moderate to vigorous physical activity had no causal association with VTE in the general population.

Association of surfactant protein A2 with acute respiratory failure in children.

Interactions among single nucleotide polymorphisms (SNPs) of surfactant protein (SP) are associated with acute respiratory failure (ARF) and its short-term outcome, pulmonary dysfunction at discharge (PDAD) in children. However, genetic association studies using individual SNPs have not been conducted before. We hypothesize that SP genetic variants are associated with pediatric ARF and its short-term complications by themselves. We used available genotype and clinical data in the Floros biobank consisting of 248 children aged ≤24 months with ARF; 86 developed PDAD. A logistic regression analysis was performed for each of the 14 selected SNPs, SP-A1 and SP-A2 genotypes. A p-value less than the Bonferroni correction threshold was considered significant. A likelihood ratio test was done to compare two models (one with demographic data and another with genetic variants). Before Bonferroni correction, female sex is associated with a decreased risk of ARF. Black race and the rs721917 of the SFTPD are associated with increased risk of ARF. After Bonferroni correction, the 1A0 1A1 genotype of SFTPA2 was associated with decreased risk of ARF. The likelihood ratio test showed that the model of the genotype information with demographic data was a better fit to predict ARF risk. None of the SP SNPs and SP-A1, SP-A2 genotypes were associated with PDAD. Our results indicate that SNPs and genotypes of SPs involved in innate immunity and host defense play an important role in ARF and, in the future, may be used as biomarkers.

Abstract PR008: Development and testing of a polygenic risk score for breast cancer. Aggressiveness

Abstract Background: Aggressive breast cancers have increased proliferation or metastatic potential and portend a poor prognosis. The ability to identify women at elevated risk of aggressive cancers could have major implications for screening and prevention, yet there are no available tools for predicting aggressive cancer risk. We sought to construct a polygenic risk score (PRS) for aggressive breast cancers by leveraging the associations of single nucleotide polymorphisms (SNPs) with tumor gene expression. We used as our measure of aggressiveness the risk of recurrence score weighted on proliferation (ROR-P), a validated tumor prognostic signature. We hypothesized that known breast cancer susceptibility SNPs would have differential associations with ROR-P, which could then be used to construct a PRS for ROR-P. Methods: We developed our PRS in a case-only analysis of 3 studies containing SNP genotypes and tumor gene expression: The Cancer Genome Atlas, METABRIC, and the I-SPY 2 TRIAL (total n=2,363). We used linear regression models to evaluate individual SNP associations with ROR-P, adjusted for genetic ancestry and study. We then constructed PRS using varying p-value thresholds and used cross-validation to identify the PRS with highest model r2. To assess whether the ROR-P PRS was associated with poor prognosis, we performed survival analysis in two longitudinal cohorts of breast cancer patients: the UK Biobank (women with incident invasive cancers only) and the Pathways Study. These studies included 10,196 total cases with 785 deaths. We built Cox proportional hazards models to evaluate the association between the ROR-P PRS (adjusted for genetic ancestry) and breast cancer-specific survival (BCSS) in both studies. We then performed meta-analysis of the Cox model results. We also constructed joint models containing the ROR-P PRS and a PRS representing the case-case risk of ER-negative vs. ER-positive cancer, PRSER-/ER+. Results: We tested the associations between 226 breast cancer susceptibility SNPs and ROR-P. The best-performing PRS contained 76 SNPs and had a cross-validated r2 of 0.051. In the UK Biobank and Pathways Study, higher ROR-P PRS was associated with worse BCSS, with nearly identical effects observed in each study, HR per standard deviation of 1.13 (95% CI 1.05-1.21, p=9.0x10-4) in meta-analysis. The ROR-P PRS’s effect was minimally attenuated when adjusted for PRSER-/ER+, suggesting that the ROR-P PRS was providing additional prognostic information beyond ER status. Conclusions: We used breast cancer susceptibility SNPs to construct a PRS for ROR-P, a prognostic signature recapitulating aggressiveness, and found the ROR-P PRS to be associated with worse BCSS. Our findings represent an improvement on current PRS for overall breast cancer risk, which preferentially predict cancers with favorable prognosis. Given that aggressive cancers are more likely to present as advanced cancers even among women undergoing routine screening, our findings could potentially identify women who may benefit from more intensive screening. Citation Format: Yiwey Shieh, Jacquelyn Roger, Christina Yau, Denise Wolf, Gillian Hirst, Lamorna Swigart, Scott Huntsman, Donglei Hu, Jovia Nierenberg, Pooja Middha, Rachel Heise, Linda Kachuri, Qianqian Zhu, Song Yao, Christine Ambrosone, Marilyn Kwan, Bette Caan, John Witte, Lawrence Kushi, Laura van ’T. Veer, Laura Esserman, Elad Ziv. Development and testing of a polygenic risk score for breast cancer. Aggressiveness. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr PR008.

Semi-Thermal Asymmetric Reverse PCR (STARP) Genotyping.

PCR-based individual Single nucleotide polymorphism (SNP) genotyping methods are preferred due to their flexibility, high-throughput, and improved accuracy. Semi-thermal asymmetric reverse PCR (STARP) is one of the SNP genotyping methods developed to reduce operational cost with improved platform compatibility. STARP is a unique method which can be used either as a gel-free SNP genotyping by detection of fluorescent signals or polyacrylamide gel-based size separation. SNP assay designing using sequence information and detection methods of STARP are described in detail.

Impact of cognition-related single nucleotide polymorphisms on brain imaging phenotype in Parkinson's disease.

Multiple single nucleotide polymorphisms may contribute to cognitive decline in Parkinson's disease. However, the mechanism by which these single nucleotide polymorphisms modify brain imaging phenotype remains unclear. The aim of this study was to investigate the potential effects of multiple single nucleotide polymorphisms on brain imaging phenotype in Parkinson's disease. Forty-eight Parkinson's disease patients and 39 matched healthy controls underwent genotyping and 7T magnetic resonance imaging. A cognitive-weighted polygenic risk score model was designed, in which the effect sizes were determined individually for 36 single nucleotide polymorphisms. The correlations between polygenic risk score, neuroimaging features, and clinical data were analyzed. Furthermore, individual single nucleotide polymorphism analysis was performed to explore the main effects of genotypes and their interactive effects with Parkinson's disease diagnosis. We found that, in Parkinson's disease, the polygenic risk score was correlated with the neural activity of the hippocampus, parahippocampus, and fusiform gyrus, and with hippocampal-prefrontal and fusiform-temporal connectivity, as well as with gray matter alterations in the orbitofrontal cortex. In addition, we found that single nucleotide polymorphisms in α-synuclein (SNCA) were associated with white matter microstructural changes in the superior corona radiata, corpus callosum, and external capsule. A single nucleotide polymorphism in catechol-O-methyltransferase was associated with the neural activities of the lingual, fusiform, and occipital gyri, which are involved in visual cognitive dysfunction. Furthermore, DRD3 was associated with frontal and temporal lobe function and structure. In conclusion, imaging genetics is useful for providing a better understanding of the genetic pathways involved in the pathophysiologic processes underlying Parkinson's disease. This study provides evidence of an association between genetic factors, cognitive functions, and multi-modality neuroimaging biomarkers in Parkinson's disease.

PS-P02-8: HOST GENOMIC INFLUENCE ON THE GUT MICROBIAL METABOLITE-BLOOD PRESSURE RELATIONSHIP

Objective: The human metabolic profile is affected by host genetic, microbiome, environmental/lifestyle, and dietary factors which may all influence human raised blood pressure (BP). We aim to delineate metabolite-BP relationships by evaluating the effect of single-nucleotide polymorphisms (SNPs) mapped to enzyme-coding genes involved in metabolic pathways on this association. We specifically focus on human commensal urinary gut microbial co-metabolites. Design and Method: Two cross-sectional datasets of over 4,000 individuals in total were used in a two-stage design. The first cohort uses two timed 24-hr urine samples for the discovery and replication of urinary metabolites associated with BP. The second cohort uses spot urine samples to validate the associations and subsequently investigates the influence of BP and other metabolic syndrome-related SNPs on these associations. Urine samples from both cohorts were measured with 600 MHz 1H Nuclear Magnetic Resonance spectroscopy. The SNPs were mapped to metabolites using a bioinformatic approach, which also incorporates the microbiome in establishing the metabolic distance between SNPs and metabolites through biochemical reactions and pathways. Results: 11 urinary metabolites, replicated within the first cohort and validated in the second cohort (adjusted P-values 1.68 × 10–15 to 1.08 × 10–4) were associated with systolic BP (SBP); 9 of these were also associated with diastolic BP (DBP) in both cohorts as well as 2 further metabolites with DBP only (adjusted P-values 9.18 × 10–13 to 1.23 × 10–4). The analysis of the host-genomic (SNPs linked to GLYAT, KYAT3 and SULT13A genes) effect on gut microbial co-metabolites phenylacetylglutamine, hippurate and 4-cresylsulfate and their association with BP revealed a significant contribution of SNPs on the metabolite-BP association (P-values 1.08 × 10–133 to 2.87 × 10–29). Other metabolite-BP associations, such as for amino acids tyrosine, glycine, lysine, and leucine, also demonstrated a significant effect of individual SNPs (P-values 1.54 × 10–303 to 2.04 × 10–8) on the relationship. These associations were validated with null models of random SNPs with the same minor allele frequency also mapping to enzyme-coding genes, as well as a null model demonstrating that these metabolites have more SNPs linked to them than other metabolites with similar network topologies in other metabolic pathways. Conclusions: We have shown that human commensal urinary gut microbial co-metabolites are reliably associated with BP differences in two cohorts, and we demonstrated a significant host-genetic component that contributes to these associations. These relationships indicate potential complex mechanisms involving host genetics, the gut microbiome, and metabolic changes associated with BP that may lead to new ways to prevent high BP.

Polygenic risk scores for complex diseases: Where are we now?

Polygenic risk scores for complex diseases: Where are we now?

Pleiotropy Structures Plant Height and Seed Weight Scaling in Barley despite Long History of Domestication and Breeding Selection.

Size scaling describes the relative growth rates of different body parts of an organism following a positive correlation. Domestication and crop breeding often target the scaling traits in the opposite directions. The genetic mechanism of the size scaling influencing the pattern of size scaling remains unexplored. Here, we revisited a diverse barley (Hordeum vulgare L.) panel with genome-wide single-nucleotide polymorphisms (SNPs) profile and the measurement of their plant height and seed weight to explore the possible genetic mechanisms that may lead to a correlation of the two traits and the influence of domestication and breeding selection on the size scaling. Plant height and seed weight are heritable and remain positively correlated in domesticated barley regardless of growth type and habit. Genomic structural equation modeling systematically evaluated the pleiotropic effect of individual SNP on the plant height and seed weight within a trait correlation network. We discovered seventeen novel SNPs (quantitative trait locus) conferring pleiotropic effect on plant height and seed weight, involving genes with function in diverse traits related to plant growth and development. Linkage disequilibrium decay analysis revealed that a considerable proportion of genetic markers associated with either plant height or seed weight are closely linked in the chromosome. We conclude that pleiotropy and genetic linkage likely form the genetic bases of plant height and seed weight scaling in barley. Our findings contribute to understanding the heritability and genetic basis of size scaling and open a new venue for seeking the underlying mechanism of allometric scaling in plants.

Severe COVID-19 May Impact Hepatic Fibrosis /Hepatic Stellate Cells Activation as Indicated by a Pathway and Population Genetic Study.

Coronavirus disease 19 (COVID-19) has affected over 112 million people and killed more than 2.5 million worldwide. When the pandemic was declared, Spain and Italy accounted for 29% of the total COVID-19 related deaths in Europe, while most infected patients did not present severe illness. We hypothesised that shared genomic characteristics, distinct from the rest of Europe, could be a contributor factor to a poor prognosis in these two populations. To identify pathways related to COVID-19 severity, we shortlisted 437 candidate genes associated with host viral intake and immune evasion from SARS-like viruses. From these, 21 were associated specifically with clinically aggressive COVID-19. To determine the potential mechanism of viral infections, we performed signalling pathway analysis with either the full list (n = 437) or the subset group (n = 21) of genes. Four pathways were significantly associated with the full gene list (Caveolar-mediated Endocytosis and the MSP-RON Signalling) or with the aggressive gene list (Hepatic Fibrosis/Hepatic Stellate Cell (HSC) Activation and the Communication between Innate and Adaptive Immune Cells). Single nucleotide polymorphisms (SNPs) from the ±1 Mb window of all genes related to these four pathways were retrieved from the dbSNP database. We then performed Principal Component analysis for these SNPs in individuals from the 1000 Genomes of European ancestry. Only the Hepatic Fibrosis/HSC Activation pathway showed population-specific segregation. The Spanish and Italian populations clustered together and away from the rest of the European ancestries, with the first segregating further from the rest. Additional in silico analysis identified potential genetic markers and clinically actionable therapeutic targets in this pathway, that may explain the severe disease.

Genetic variation in the dopamine system is associated with mixed-strategy decision-making in patients with Parkinson's disease.

Decision-making during mixed-strategy games requires flexibly adapting choice strategies in response to others' actions and dynamically tracking outcomes. Such decisions involve diverse cognitive processes, including reinforcement learning, which are affected by disruptions to the striatal dopamine system. We therefore investigated how genetic variation in dopamine function affected mixed-strategy decision-making in Parkinson's disease (PD), which involves striatal dopamine pathology. Sixty-six PD patients (ages 49-85, Hoehn and Yahr Stages 1-3) and 22 healthy controls (ages 54-75) competed in a mixed-strategy game where successful performance depended on minimizing choice biases (i.e., flexibly adapting choices trial by trial). Participants also completed a fixed-strategy task that was matched for sensory input, motor outputs and overall reward rate. Factor analyses were used to disentangle cognitive from motor aspects within both tasks. Using a within-subject, multi-centre design, patients were examined on and off dopaminergic therapy, and genetic variation was examined via a multilocus genetic profile score representing the additive effects of three single nucleotide polymorphisms (SNPs) that influence dopamine transmission: rs4680 (COMT Val158 Met), rs6277 (C957T) and rs907094 (encoding DARPP-32). PD and control participants displayed comparable mixed-strategy choice behaviour (overall); however, PD patients with genetic profile scores indicating higher dopamine transmission showed improved performance relative to those with low scores. Exploratory follow-up tests across individual SNPs revealed better performance in individuals with the C957T polymorphism, reflecting higher striatal D2/D3 receptor density. Importantly, genetic variation modulated cognitive aspects of performance, above and beyond motor function, suggesting that genetic variation in dopamine signalling may underlie individual differences in cognitive function in PD.

Disease patterns of coronary heart disease and type 2 diabetes harbored distinct and shared genetic architecture

Coronary heart disease (CHD) and type 2 diabetes (T2D) are two complex diseases with complex interrelationships. However, the genetic architecture of the two diseases is often studied independently by the individual single-nucleotide polymorphism (SNP) approach. Here, we presented a genotypic-phenotypic framework for deciphering the genetic architecture underlying the disease patterns of CHD and T2D. A data-driven SNP-set approach was performed in a genome-wide association study consisting of subpopulations with different disease patterns of CHD and T2D (comorbidity, CHD without T2D, T2D without CHD and all none). We applied nonsmooth nonnegative matrix factorization (nsNMF) clustering to generate SNP sets interacting the information of SNP and subject. Relationships between SNP sets and phenotype sets harboring different disease patterns were then assessed, and we further co-clustered the SNP sets into a genetic network to topologically elucidate the genetic architecture composed of SNP sets. We identified 23 non-identical SNP sets with significant association with CHD or T2D (SNP-set based association test, P < 3.70 × [Formula: see text]). Among them, disease patterns involving CHD and T2D were related to distinct SNP sets (Hypergeometric test, P < 2.17 × [Formula: see text]). Accordingly, numerous genes (e.g., KLKs, GRM8, SHANK2) and pathways (e.g., fatty acid metabolism) were diversely implicated in different subtypes and related pathophysiological processes. Finally, we showed that the genetic architecture for disease patterns of CHD and T2D was composed of disjoint genetic networks (heterogeneity), with common genes contributing to it (pleiotropy). The SNP-set approach deciphered the complexity of both genotype and phenotype as well as their complex relationships. Different disease patterns of CHD and T2D share distinct genetic architectures, for which lipid metabolism related to fibrosis may be an atherogenic pathway that is specifically activated by diabetes. Our findings provide new insights for exploring new biological pathways.

A Blueprint for Genetic Determinism

A Blueprint for Genetic Determinism

SNP- and haplotype-based single-step genomic predictions for body weight, wool, and reproductive traits in North American Rambouillet sheep.

Rambouillet sheep are commonly raised in extensive grazing systems in the US, mainly for wool and meat production. Genomic evaluations in US sheep breeds, including Rambouillet, are still incipient. Therefore, we aimed to evaluate the feasibility of performing genomic prediction of breeding values for various traits in Rambouillet sheep based on single nucleotide polymorphisms (SNP) or haplotypes (fitted as pseudo-SNP) under a single-step GBLUP approach. A total of 28,834 records for birth weight (BWT), 23,306 for postweaning weight (PWT), 5,832 for yearling weight (YWT), 9,880 for yearling fibre diameter (YFD), 11,872 for yearling greasy fleece weight (YGFW), and 15,984 for number of lambs born (NLB) were used in this study. Seven hundred forty-one individuals were genotyped using a moderate (50 K; n=677) or high (600 K; n=64) density SNP panel, in which 32 K SNP in common between the two SNP panels (after genotypic quality control) were used for further analyses. Single-step genomic predictions using SNP (H-BLUP) or haplotypes (HAP-BLUP) from blocks with different linkage disequilibrium (LD) thresholds (0.15, 0.35, 0.50, 0.65, and 0.80) were evaluated. We also considered different blending parameters when constructing the genomic relationship matrix used to predict the genomic-enhanced estimated breeding values (GEBV), with alpha equal to 0.95 or 0.50. The GEBV were compared to the estimated breeding values (EBV) obtained from traditional pedigree-based evaluations (A-BLUP). The mean theoretical accuracy ranged from 0.499 (A-BLUP for PWT) to 0.795 (HAP-BLUP using haplotypes from blocks with LD threshold of 0.35 and alpha equal to 0.95 for YFD). The prediction accuracies ranged from 0.143 (A-BLUP for PWT) to 0.330 (A-BLUP for YGFW) while the prediction bias ranged from -0.104 (H-BLUP for PWT) to 0.087 (HAP-BLUP using haplotypes from blocks with LD threshold of 0.15 and alpha equal to 0.95 for YGFW). The GEBV dispersion ranged from 0.428 (A-BLUP for PWT) to 1.035 (A-BLUP for YGFW). Similar results were observed for H-BLUP or HAP-BLUP, independently of the LD threshold to create the haplotypes, alpha value, or trait analysed. Using genomic information (fitting individual SNP or haplotypes) provided similar or higher prediction and theoretical accuracies and reduced the dispersion of the GEBV for body weight, wool, and reproductive traits in Rambouillet sheep. However, there were no clear improvements in the prediction bias when compared to pedigree-based predictions. The next step will be to enlarge the training populations for this breed to increase the benefits of genomic predictions.