Genetic overlap between Parkinson disease and inflammatory bowel disease

Importance Parkinson disease (PD) and inflammatory bowel disease (IBD) have been associated, implying shared pathophysiology. Characterizing genetic pleiotropy between the two conditions aids the exploration of common etiology. Objective To estimate the genetic correlation between PD and IBD and to identify specific loci influencing both conditions. Design Genetic study with applications of high definition likelihood and conditional false discovery rate (FDR) framework. Setting The study was based on summary statistics of genome-wide association studies (GWAS). Participants The PD GWAS comprised 37,688 cases and 981,372 controls, and the IBD GWAS included 25,042 cases and 34,915 controls. Participants were of mixed ethnicity. Exposures None. Main Outcomes and Measures The main outcomes were a set of single nucleotide polymorphisms (SNPs) identified by conditional FDR analysis as jointly associated with PD and IBD. Results Weak but statistically significant genetic correlations were detected for PD with both Crohn's disease (CD) and ulcerative colitis (UC), the two main subtypes of IBD. A total of 1333 SNPs in 28 genomic loci and 1915 SNPs in 22 loci were jointly associated with PD-CD and PD-UC, respectively, at conjunctional FDR under 0.01. The pleiotropic loci appeared distinctive for PD-CD and PD-UC, are mostly novel and comprise loci with either same or opposing genetic effects on the two phenotypes. Positional and eQTL mapping prioritized 316 PD-CD and 303 PD-UC genes, among which only <10% are differentially expressed in both colon and substantia nigra. The KEGG pathways enriched by all prioritized genes were highly concordant between PD-CD and PD-UC, with the majority being related to immune and/or autoimmune dysfunction. Conclusions and Relevance Overall, we found robust evidence for a genetic link between PD and each subtype of IBD. The identified genetic overlap is complex at the locus and gene levels, indicating the presence of both common etiology and antagonistic pleiotropy. At the functional level, our results highlighted a central role of host immunity and/or autoimmunity in the PD-IBD relationship.

Improving Machine Learning Prediction of ADHD Using Gene Set Polygenic Risk Scores and Risk Scores from Genetically Correlated Phenotypes

Background: Polygenic risk scores (PRSs), which sum the effects of SNPs throughout the genome to measure risk afforded by common genetic variants, have improved our ability to estimate disorder risk for Attention-Deficit/Hyperactivity Disorder (ADHD) but the accuracy of risk prediction is rarely investigated. Methods: With the goal of improving risk prediction, we performed gene set analysis of GWAS data to select gene sets associated with ADHD within a training subset. For each selected gene set, we generated gene set polygenic risk scores (gsPRSs), which sum the effects of SNPs for each selected gene set. We created gsPRS for ADHD and for phenotypes having a high genetic correlation with ADHD. These gsPRS were added to the standard PRS as input to machine learning models predicting ADHD. We used feature importance scores to select gsPRS for a final model and to generate a ranking of the most consistently predictive gsPRS. Results: For a test subset that had not been used for training or validation, a random forest (RF) model using PRSs from ADHD and genetically correlated phenotypes and an optimized group of 20 gsPRS had an area under the receiving operating characteristic curve (AUC) of 0.72 (95% CI: 0.70 to 0.74). This AUC was a statistically significant improvement over logistic regression models and RF models using only PRS from ADHD and genetically correlated phenotypes. Conclusions: Summing risk at the gene set level and incorporating genetic risk from disorders with high genetic correlations with ADHD improved the accuracy of predicting ADHD. Learning curves suggest that additional improvements would be expected with larger study sizes. Our study suggests that better accounting of genetic risk and the genetic context of allelic differences results in more predictive models.

Genetic Variation in Drought-Tolerance Traits and Their Relationships to Growth in Pinus radiata D. Don Under Water Stress

The selection of drought-tolerant genotypes is globally recognized as an effective strategy to maintain the growth and survival of commercial tree species exposed to future drought periods. New genomic selection tools that reduce the time of progeny trials are required to substitute traditional tree breeding programs. We investigated the genetic variation of water stress tolerance in New Zealand-grown Pinus radiata D. Don using 622 commercially-used genotypes from 63 families. We used quantitative pedigree-based (Genomic Best Linear Unbiased Prediction or ABLUP) and genomic-based (Genomic Best Linear Unbiased Prediction or GBLUP) approaches to examine the heritability estimates associated with water stress tolerance in P. radiata. Tree seedling growth traits, foliar carbon isotope composition (δ13C), and dark-adapted chlorophyll fluorescence (Y) were monitored before, during and after 10 months of water stress. Height growth showed a constant and moderate heritability level, while the heritability estimate for diameter growth and δ13C decreased with water stress. In contrast, chlorophyll fluorescence exhibited low heritability after 5 and 10 months of water stress. The GBLUP approach provided less breeding value accuracy than ABLUP, however, the relative selection efficiency of GBLUP was greater compared with ABLUP selection techniques. Although there was no significant relationship directly between δ13C and Y, the genetic correlations were significant and stronger for GBLUP. The positive genetic correlations between δ13C and tree biomass traits under water stress indicated that intraspecific variation in δ13C was likely driven by differences in the genotype’s photosynthetic capacity. The results show that foliar δ13C can predict P. radiata genotype tolerance to water stress using ABLUP and GBLUP approaches and that such approaches can provide a faster screening and selection of drought-tolerant genotypes for forestry breeding programs.

The Genetic Structure of Pain in Depression Patients: A Genome-Wide Association Study and Proteome-Wide Association Study

Background Pain symptoms are common in the patients with depression. Comparing with the general population, the pain in depression patients has more complex biological mechanism. We aim to explore the etiological mechanism of pain in depression patients from the perspective of genetics. Methods Utilizing the UK Biobank samples with self-reported depression status or PHQ score ≥10, we conducted genome-wide association study (GWAS) of seven pain traits (N=1,133-58,349). The GWAS summary were then integrated with two different reference protein weights (ROS/MAP and Banner) for proteome-wide association study (PWAS) using the FUSION pipeline. Additionally, LDSC analysis was performed to explore the genetic correlation between pain traits in depression patients and common psychiatry disorders. And biological processes and functions that related to pain associated genes in depression patients were analyzed by gene set enrichment analysis. Results GWAS identified 3 significant genes associated with different pain traits in depression patients, including TRIOBP (PGWAS= 4.48× 10−8) for stomach or abdominal pain, SLC9A9(PGWAS= 2.77× 10−8) for multisite chronic pain (MCP) and ADGRF1 (PGWAS= 1.51× 10−8) for neck or shoulder pain. PWAS also identified multiple candidate genes associated with different pain traits in depression patients, such as TPRG1L (permutation-based PPWAS−Banner= 3.38× 10−2) and SIRPA (permutation-based PPWAS−Banner= 3.65×10−2) for MCP etc. LDSC analysis results showed that MCP was positively correlated with attention-deficit hyperactivity disorder (ADHD) (genetic correlation(rg) = 0.123, PLDSC = 0.039) and post-traumatic stress disorder (PTSD) (rg = 0.217, PLDSC = 0.029). Conclusions We reported multiple novel candidate genes and genetic correlations for pain traits in depression patients, providing novel clues for understanding the genetic mechanisms underlying the pain in depression patients.

Genetic factors of functional traits

Selection of functional traits is a challenge for researchers, but an increasingly necessary objective due to the growing concern regarding animal welfare and overcoming the problems of reducing antibiotic use in rabbit production without undermining the animals’ productivity. The aim of this review is to discuss the genetic control of resistance to diseases, longevity and variability of birth weight within a litter, or litter size variability at birth within doe, describing the selection programmes and the first results from a multi-omics analysis of resistance/susceptibility to diseases. The heritability is around 0.13 for longevity, 0.01 for uniformity in birth weight, 0.09 for litter size variability and around 0.11 for disease resistance. Genetic correlations between functional traits and production traits are mostly no different from zero, or are moderately favourable in some cases. Six selection programmes developed in three countries are reviewed. Line foundation with high pressure for selection or divergent selection experiments are different methodologies used, and favourable responses to selection have been achieved. Genomics studies have revealed associations in regions related to immune system functionality and stress in lines selected for litter size variability. Knowledge of the role of gut microbiota in the rabbit’s immune response is very limited. A multi-omics approach can help determine the microbial mechanisms in regulation immunity genes of the host.

Clinical and Genetic Correlations of Inherital Retinal Disease with Mutations in the ABCA4 Gene by Patients of the Russian Population

Aim: to study genotype-phenotype correlations in patients with inherited retinal diseases with mutations in ABCA4 gene in Russian Federation.Patients and methods. 21 patients from Russian population aged from 7 to 51 years old (mean age 20 ± 11 years with best-corrected visual acuity from 0,02 to 0,6 (0,14 ± 0,11) with ABCA4-associated retinopathy, verified by molecular genetics methods. All patients besides standard ophthalmic examination and photodocumentation were performed Spectral-Domain OCT and fundus autofluorescence on Spectralis ®HRA+OCT (Heidelberg Engineering, Germany). Full-field electroretinogram (ERG), 30-Hz flicker ERG and macular chromatic ERG (MERG) to red stimulus were recorded on electroretinographic system MBN (MBN, Russia). (Russia) Molecular genetic studies were performed using Next Generation Sequencing (NGS) and Sandger direct sequencing. Results: In ABCA4-associated Stargardt disease 1 type (STGD1) genotype [p.L541P, p.A1038V] of «frequent» mutations was revealed in 9 patients, in 2 cases in was associated another “frequent” mutation p.G1961E. In 4 patients with genotype [p.L541P, p.A1038V] “severe” phenotype of Stargardt disease was found: with large defect of the ellipsoid zone and large zone of central reduced autofluorescence, severely subnormal macular ERG (MERG) to red stimulus and subnormal 30 Hz flicker and full-field maximal ERG. In one patient with these mutations in homozygous state ABCA4-associated cone-rod dystrophy (CORD3, clinically looking alike secondary retinal dystrophy is diagnosed. In 2 patients with genotype [p.L541P, p.A1038V] and mutation p.G1961E was found mild phenotype. One patient with homozygous mutation p.R653C autosomal recessive ABCA4-associated retinitis pigmentosa (RP19) was diagnosed. Clinical picture and autofluorescence were polymorphic in all patients.Conclusions. Our study with ophthalmological, molecular genetics and instrumental methods widens the spectrum of clinical signs of inherited eye diseases associated with mutations in АВСА4 gene, widens the spectrum mutations in Russian Federation and reveals clinicо-genetic genotype-phenotype correlations.

Chemical and sensory characteristics in the selection of bourbon genotypes

The evaluation of coffee quality in Brazil for commercialization is conducted mainly through sensory analysis, also known as the "cup test", in which professional tasters evaluate and score various attributes. The adoption of chemical methods could complement the sensory classification of beverages, if correlations between these chemical and sensory analyses exist, making classification less subjective. This work aimed to identify the relationships between the chemical and sensorial traits of coffee-beverage quality and to evaluate the use of these traits as criteria for the selection of Bourbon cultivars. Twenty coffee genotypes from the first three harvests across five municipalities of the state of Minas Gerais, Brazil were evaluated. The genotypic values, predicted for each genotype, were used to determine the index based on the sum of ranks from Mulamba and Mock. The genetic correlations among the evaluated traits were also estimated. The presented evaluations were not able to efficiently detect genetic and phenotypic relationships between the chemical and sensorial characteristics of drink quality, but as selection criteria for generation advancement in the beverage quality, it is possible to use these characteristics. Bourbon Amarelo LCJ 9-IAC, Bourbon Amarelo-Procafé, Bourbon Amarelo-Boa Vista, Bourbon Vermelho-São João Batista, and Bourbon Amarelo-Samambaia were the genotypes with the most promising cup quality in the studied regions. Through the selection of these five genotypes, the selection gain was 1.65% for sensory score for beverage quality, when the interaction among the studied environments was removed. The heritability was 92% for improving this trait.

Genetic and Environmental Architecture of Five Factor Model and Super-Factors: An Italian Twin Study

No previous research explored the genetic and environmental structure of Big Five dimensions of personality and higher-order factors in a single twin study, except, in part, for just one study. We used the twin design to estimate the effects of genes and environment on both Five Factor model and related second- and third-order factors (i.e., Alpha [stability], Beta [plasticity], and GFP [general factor of personality]). We analyzed data from 314 adult twins (157 pairs: 83 monozygotic, 74 dizygotic; mean age: 52 years) enrolled in the Italian Twin Register. Participants underwent clinical and instrumental evaluations, and completed a 25-adjective list drawn from the Short Adjectives Checklist to Measure Big Five (SACBIF). We applied quantitative genetic models to unravel the sources of variation and covariation for the Big Five and higher-order factors. We found a similar etiological architecture across the different levels of analysis, with moderate to substantial non-additive genetic and unique environmental influences on all the personality traits, and no shared environmental contribution for any of them. We also detected significant genetic correlations for the Big Five dimensions and the Alpha and Beta super-factors. With some limitations, our results suggest that the etiological architecture of personality may be invariant to the factor level of analysis.

Inheritance of plant height, straw yield and flag leaf area in MBB x Gaviota durum wheat (Triticum durum Desf.) cross

<p class="042abstractstekst">Plant height, straw mass and flag leaf area are recognized by physiologists as morphological markers of drought stress tolerance. Developing varieties intended for arid and semi-arid zones need to select for these traits. Understanding the genetic control of a given trait helps breeder to handle the segregating populations under study in a more efficient and consistent manner by choosing the best breeding method available to realize significant genetic advance. For this purpose, six generations: parents, F1, F2, BC1, BC2, derived from MBB x ‘Gaviota’ durum wheat (<em>Triticum durum </em>Desf.) cross were grown to investigate the nature of gene action involved in the inheritance pattern of the three traits. The results indicated that the six-parameter model fitted the best the data related to the variability present in the generation means of the studied traits. Generation mean analysis indicated that non-allelic interactions were important factors controlling the expression of these characters with complementary type of gene action governing FLA and STW inheritance. High heritability estimates, moderate to high expected responses to selection, significant genetic correlations with grain yield and greater role of non-additive effects in controlling the inheritance of the three studied traits suggested that breeding methods exploiting both fixable and non-fixable components be applied to break unfavorable linkage and to accumulate useful genes in the base population, followed by mono-trait or index based selection in late advanced generations.</p>