UNASSIGNED: Recent research linked changes in the gut microbiota and serum metabolite concentrations to intracerebral hemorrhage (ICH). However, the potential causal relationship remained unclear. Therefore, the current study aims to estimate the effects of genetically predicted causality between gut microbiota, serum metabolites, and ICH.
UNASSIGNED: Summary data from genome-wide association studies (GWAS) of gut microbiota, serum metabolites, and ICH were obtained separately. Gut microbiota GWAS (N = 18,340) were acquired from the MiBioGen study, serum metabolites GWAS (N = 7,824) from the TwinsUK and KORA studies, and GWAS summary-level data for ICH from the FinnGen R9 (ICH, 3,749 cases; 339,914 controls). A two-sample Mendelian randomization (MR) study was conducted to explore the causal effects between gut microbiota, serum metabolites, and ICH. The random-effects inverse variance-weighted (IVW) MR analyses were performed as the primary results, together with a series of sensitivity analyses to assess the robustness of the results. Besides, a reverse MR was conducted to evaluate the possibility of reverse causation. To validate the relevant findings, we further selected data from the UK Biobank for analysis.
UNASSIGNED: MR analysis results revealed a nominal association (p < 0.05) between 17 gut microbial taxa, 31 serum metabolites, and ICH. Among gut microbiota, the higher level of genus Eubacterium xylanophilum (odds ratio (OR): 1.327, 95% confidence interval (CI):1.154-1.526; Bonferroni-corrected p = 7.28 × 10-5) retained a strong causal relationship with a higher risk of ICH after the Bonferroni corrected test. Concurrently, the genus Senegalimassilia (OR: 0.843, 95% CI: 0.778-0.915; Bonferroni-corrected p = 4.10 × 10-5) was associated with lower ICH risk. Moreover, after Bonferroni correction, only two serum metabolites remained out of the initial 31 serum metabolites. One of the serum metabolites, Isovalerate (OR: 7.130, 95% CI: 2.648-19.199; Bonferroni-corrected p = 1.01 × 10-4) showed a very strong causal relationship with a higher risk of ICH, whereas the other metabolite was unidentified and excluded from further analysis. Various sensitivity analyses yielded similar results, with no heterogeneity or directional pleiotropy observed.
UNASSIGNED: This two-sample MR study revealed the significant influence of gut microbiota and serum metabolites on the risk of ICH. The specific bacterial taxa and metabolites engaged in ICH development were identified. Further research is required in the future to delve deeper into the mechanisms behind these findings.

Premature coronary artery disease (CAD) is endemic in India. Global Burden of Diseases study has reported that it led to 286,000 deaths in 2019 in India. Many of these patients have standard risk factors but a third have none. Clinical risk algorithms and imaging provide limited risk information in premature CAD. CAD is multifactorial and studies have now focused on the predictive capability of clusters of genes and single nucleotide polymorphisms (SNPs) using gene risk score (GRS). Older studies combined data from 10 to 12 genes and 100-500 SNPs to calculate GRS, however, following the advent of genome-wide association studies (GWAS), millions of SNPs have been incorporated. Studies have reported that GWAS-based GRS may be more discriminative than conventional tools. Recent studies, especially among South Asians, have reported that GRS improves net reclassification by 15% (12-19%) for younger individuals. Aggressive lifestyle interventions and lipid-lowering therapies can ameliorate risk in high-GRS individuals and potentially prevent premature CAD.

Genomewide association studies have associated >100 genetic loci with atrial fibrillation (AF), but establishing causal genes contributing to AF remains challenging.
The purpose of this study was to determine candidate novel causal genes and mechanistic pathways associated with AF risk loci by incorporating gene expression and coexpression analyses and to provide a resource for functional studies and targeting of AF-associated genes.
Cis-expression quantitative trait loci were identified for candidate genes near AF risk variants in human left atrial tissues. Coexpression partners were identified for each candidate gene. Weighted gene coexpression network analysis (WGCNA) identified modules and modules with overrepresentation of candidate AF genes. Ingenuity pathway analysis (IPA) was applied to the coexpression partners of each candidate gene. IPA and gene set over representation analysis were applied to each WGCNA module.
One hundred sixty-six AF-risk single nucleotide polymorphisms were located in 135 loci. Eighty-one novel genes not previously annotated as putative AF risk genes were identified. IPA identified mitochondrial dysfunction, oxidative stress, epithelial adherens junction signaling, and sirtuin signaling as the most frequent significant pathways. WGCNA characterized 64 modules (candidate AF genes overrepresented in 8), represented by cell injury, death, stress, developmental, metabolic/mitochondrial, transcription/translation, and immune activation/inflammation regulatory pathways.
Candidate gene coexpression analyses suggest significant roles for cellular stress and remodeling in AF, supporting a dual risk model for AF: Genetic susceptibility to AF may not manifest until later in life, when cellular stressors overwhelm adaptive responses. These analyses also provide a novel resource to guide functional studies on potential causal AF genes.

A complex disease such as periodontitis is the sum of environmental and genetic effects. The personal genetic constitution interacts with the effects of internal and external risk factors like smoking, oral hygiene, malnutrition, emotional stress, and age. Accordingly, individuals who live in the same environmental context and share comparable lifestyle habits have different disease risks. Genetic research offers the identification of DNA sequence variants that have a causal role in disease etiology and allows the identification of disease relevant immune and metabolic pathways that contribute to disease susceptibility and pathogenesis in specific situations. Real advances have been made in genetic medical research in the last years. Starting from candidate gene association studies, new approaches were employed that have expanded the study design of genomewide association studies to genomewide meta-analyses and gene x environment interaction studies. Cost efficient whole-exome and whole-genome sequencing of patients with rare severe forms of periodontitis has the potential to identify genes and pathways with a direct role in the pathogenesis of common forms. In parallel, animal models were developed that use genetically highly diverse mouse lines to identify risk genes of human diseases. This chapter presents the main studies and the identified susceptibility genes that have clear statistical evidence. In addition, it describes pioneering studies that used advanced methods in experimental dental research, opening up new avenues of research. Although the knowledge of the genetic architecture of periodontitis is still in its infancy, genetic research is building the basis for future works with the potential to advance dental medicine in ways that will determine the various causes of periodontal diseases. This knowledge may eventually allow making predictions about disease risk for individual patients and leading to diagnosis and treatments that do not treat the symptoms but heal the disease.

Human adult height reflects the outcome of childhood skeletal growth. Growth plate (epiphyseal) chondrocytes are key determinants of height. As epiphyseal chondrocytes mature and proliferate, they pass through three developmental stages, which are organized into three distinct layers in the growth plate: (i) resting (round), (ii) proliferative (flat), and (iii) hypertrophic. Recent genomewide association studies (GWASs) of human height identified numerous associated loci, which are enriched for genes expressed in growth plate chondrocytes. However, it remains unclear which specific genes expressed in which layers of the growth plate regulate skeletal growth and human height. To connect the genetics of height and growth plate biology, we analyzed GWAS data through the lens of gene expression in the three dissected layers of murine newborn tibial growth plate. For each gene, we derived a specificity score for each growth plate layer and regressed these scores against gene-level p values from recent height GWAS data. We found that specificity for expression in the round cell layer, which contains chondrocytes early in maturation, is significantly associated with height GWAS p values (p = 8.5 × 10-9 ); this association remains after conditioning on specificity for the other cell layers. The association also remains after conditioning on membership in an \"Online Mendelian Inheritance in Man (OMIM) gene set\" (genes known to cause monogenic skeletal growth disorders, p < 9.7 × 10-6 ). We replicated the association in RNA-sequencing (RNA-seq) data from maturing chondrocytes sampled at early and late time points during differentiation in vitro: we found that expression early in differentiation is significantly associated with p values from height GWASs (p = 6.1 × 10-10 ) and that this association remains after conditioning on expression at 10 days in culture and on the OMIM gene set (p < 0.006). These findings newly implicate genes highlighted by GWASs of height and specifically expressed in the round cell layer as being potentially important regulators of skeletal biology. © 2021 American Society for Bone and Mineral Research (ASBMR).

The magnitude of all therapeutic responses is significantly determined by genome structure, variation, and functional interactions. This determination occurs at many levels which are discussed in the current review. Well-established examples of structural variation between individuals are known to dictate an individual\'s response to numerous drugs, as clearly illustrated by warfarin. The exponential rate of genomic-based interrogation is coupled with an expanding repertoire of genomic technologies and applications. This is leading to an ever more sophisticated appreciation of how structural variation, regulation of transcription and genomic structure, both individually and collectively, define cell therapeutic responses.

Biomarkers diagnose, predict or assess the risk of disease, and studies of the effects of genetic variation on biomarker phenotypes in the general population complement studies on patients diagnosed with disease. This paper traces the evolution of studies on biomarker genetics over the past 40 years through examples drawn from the work of Professor Martin and his colleagues.

Although genomewide association studies (GWASs) have identified many genetic variants underlying complex traits, a large fraction of heritability still remains unexplained. Integrative analysis that incorporates additional information, such as expression quantitativetrait locus (eQTL) data into sequencing studies (denoted as transcriptomewide association study [TWAS]), can aid the discovery of trait-associated genetic variants. However, general TWAS methods only incorporate one eQTL-derived weight (e.g., cis-effect), and thus can suffer a substantial loss of power when the single estimated cis-effect is not predictive for the effect size of a genetic variant or when there are estimation errors in the estimated cis-effect, or if the data are not consistent with the model assumption. In this study, we propose an omnibus test (OT) which utilizes a Cauchy association test to integrate association evidence demonstrated by three different traditional tests (burden test, quadratic test, and adaptive test) using GWAS summary data with multiple eQTL-derived weights. The p value of the proposed test can be calculated analytically, and thus it is fast and efficient. We applied our proposed test to two schizophrenia (SCZ) GWAS summary data sets and two lipids trait (HDL) GWAS summary data sets. Compared with the three traditional tests, our proposed OT can identify more trait-associated genes.

Bamaxiang pig is from Guangxi province in China, characterized by its small body size and two-end black coat colour. It is an important indigenous breed for local pork market and excellent animal model for biomedical research. In this study, we performed genomewide association studies (GWAS) on 43 growth and carcass traits in 315 purebred Bamaxiang pigs based on a 1.4 million SNP array. We observed considerable phenotypic variability in the growth and carcass traits in the Bamaxiang pigs. The corresponding SNP based heritability varied greatly across the 43 traits and ranged from 9.0% to 88%. Through a conditional GWAS, we identified 53 significant associations for 35 traits at p value threshold of 10-6 . Among which, 26 associations on chromosome 3, 7, 14 and X passed a genomewide significance threshold of 5 × 10-8 . The most remarkable loci were at around 30.6 Mb on chromosome 7, which had growth stage-dependent effects on body lengths and cannon circumferences and showed large effects on multiple carcass traits. We discussed HMGA1 NUDT3, EIF2AK1, TMEM132C and AFF2 that near the lead SNP of significant loci as plausible candidate genes for corresponding traits. We also showed that including phenotypic covariate in GWAS can help to reveal additional significant loci for the target traits. The results provide insight into the genetic architecture of growth and carcass traits in Bamaxiang pigs.

Traits with a common genetic basis frequently display correlated phenotypic responses to selection or environmental conditions. In Drosophila melanogaster, pigmentation of the abdomen and a trident-shaped region on the thorax are genetically correlated. Here, we used a pooled replicated genomewide association approach (Pool-GWAS) to identify the genetic basis of variation in thoracic trident pigmentation in two Drosophila melanogaster populations. We confirmed the previously reported large effect of ebony and the association of the cosmopolitan inversion In(3R)Payne. For the first time, we identified tan as another major locus contributing to variation in trident pigmentation. Intriguingly, the regulatory variants of tan that were most strongly associated with female abdominal pigmentation also showed a strong association with trident pigmentation. We validated this common genetic basis in transgenic assays and found qualitatively similar effects on trident and abdominal pigmentation. Further work is required to determine whether this genetic correlation is favoured by natural selection or reflects a neutral by-product of a shared regulatory architecture.