Genome-wide Genotyping Research Articles

Genetic drivers of human plasma metabolites that determine mortality in heart failure patients with reduced ejection fraction.

Heart failure with reduced ejection fraction (HFrEF) remains a significant public health issue, with the disease advancing despite neurohormonal antagonism. Energetic dysfunction is a likely contributor to residual disease progression, and we have previously reported a strong association of plasma metabolite profiles with survival among patients with HFrEF. However, the genetic and biologic mechanisms that underlie the metabolite-survival association in HFrEF were uncertain. We performed genetic mapping of the key metabolite parameters, followed by mediation analyses of metabolites and genotypes on survival, and genetic pathway analyses. Patients with HFrEF (n = 1,003) in the Henry Ford Pharmacogenomic Registry (HFPGR; 500 self-reported Black/African race patients [AA], 503 self-reported White/European race patients [EA], and 249 deaths over a median of 2.7 years) with genome-wide genotyping and targeted metabolomic profiling of plasma were included. We tested genome-wide association (GWA) of single nucleotide polymorphisms (SNPs) with the prognostic metabolite profile (PMP) and its components; first stratified by race, and then combined via meta-analysis for the entire cohort. Seven independent loci were identified as GWA significant hits in AA patients (3 for PMP and 4 for individual metabolites), one of which was also significant in the entire cohort (rs944469). No genome wide significant hits were found in White/EA patients. Among these SNPs, only rs35792152, (a hit for 3.HBA) tended to be associated with mortality in standard survival analysis (HR = 1.436, p = 0.052). The mediation analyses indicated several significant associations between SNPs, metabolites, and mortality in AA patients. Functional annotation mapping (FUMA) implicated inflammation, DNA metabolic, and mRNA splicing processes. GWAS of key metabolites and survival along with FUMA pathway analysis revealed new candidate genes which unveiled molecular pathways that contribute to HF disease progression via metabolic and energetic abnormalities.

Genotyping-by-sequencing targets genic regions and improves resolution of genome-wide association studies in autotetraploid potato

Key messageDe novo genotyping in potato using methylation-sensitive GBS discovers SNPs largely confined to genic or gene-associated regions and displays enhanced effectiveness in estimating LD decay rates, population structure and detecting GWAS associations over ‘fixed’ SNP genotyping platform. Study also reports the genetic architectures including robust sequence-tagged marker–trait associations for sixteen important potato traits potentially carrying higher transferability across a wider range of germplasm.This study deploys recent advancements in polyploid analytical approaches to perform complex trait analyses in cultivated tetraploid potato. The study employs a ‘fixed’ SNP Infinium array platform and a ‘flexible and open’ genome complexity reduction-based sequencing method (GBS, genotyping-by-sequencing) to perform genome-wide association studies (GWAS) for several key potato traits including the assessment of population structure and linkage disequilibrium (LD) in the studied population. GBS SNPs discovered here were largely confined (~ 90%) to genic or gene-associated regions of the genome demonstrating the utility of using a methylation-sensitive restriction enzyme (PstI) for library construction. As compared to Infinium array SNPs, GBS SNPs displayed enhanced effectiveness in estimating LD decay rates and discriminating population subgroups. GWAS using a combined set of 30,363 SNPs identified 189 unique QTL marker–trait associations (QTL-MTAs) covering all studied traits. The majority of the QTL-MTAs were from GBS SNPs potentially illustrating the effectiveness of marker-dense de novo genotyping platforms in overcoming ascertainment bias and providing a more accurate correction for different levels of relatedness in GWAS models. GWAS also detected QTL ‘hotspots’ for several traits at previously known as well as newly identified genomic locations. Due to the current study exploiting genome-wide genotyping and de novo SNP discovery simultaneously on a large tetraploid panel representing a greater diversity of the cultivated potato gene pool, the reported sequence-tagged MTAs are likely to have higher transferability across a wider range of potato germplasm and increased utility for expediting genomics-assisted breeding for the several complex traits studied.

The Causal Relationship Between Skin Microbiota and Facial Aging: A Mendelian Randomization Study.

Facial aging is a complex process influenced by environmental factors, genetics, and lifestyle. The contribution of the skin microbiota to this process remains poorly understood. This two-sample Mendelian randomization (MR) study was performed using genome-wide genotype data from the UK Biobank and previously published studies on skin microbiota. The primary approach for MR analyses included inverse-variance weighting (IVW), MR-Egger regression, simple mode, weighted median, and weighted mode methods. Sensitivity analyses were performed to assess heterogeneity and pleiotropy, and reverse-direction MR analyses were performed to evaluate potential reverse causation. The MR analysis identified ten skin microbiotas with potential causal relationships with facial aging. Protective skin microbiotas included Genus Finegoldia, ASV011 [Staphylococcus (unc.)], ASV008 [Staphylococcus (unc.)], phylum Firmicutes, Family Rhodobacteraceae, and ASV021 [Micrococcus (unc.)], which were negatively associated with facial aging. Conversely, Order Pseudomonadales, Family Moraxellaceae, ASV039 [Acinetobacter (unc.)], and phylum Bacteroidetes were positively associated with facial aging, indicating a risk factor for accelerated aging. Sensitivity analyses confirmed the robustness of these findings, and reverse-direction MR analyses did not suggest any reverse causation. This study identified specific skin microbial that may influence facial aging and offered new insights into the rejuvenation strategies. This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

O-136 A comprehensive evaluation of spermatogenesis-related genes identifies novel common and rare risk loci for idiopathic severe spermatogenic failure

Abstract Study question Can genome-wide genotyping data be analysed in a hypothesis-driven fashion to better understand the genetic component of male infertility due to severe spermatogenic failure (SPGF)? Summary answer We revealed that both common and rare genetic variants in genomic regions involved in spermatogenesis contribute to the development of idiopathic SPGF. What is known already Spermatogenesis is a tightly regulated process involving the controlled expression of over 2,000 genes. Mutations in spermatogenesis-related genes have been associated with SPGF development. Next-generation sequencing methods are useful for identifying rare mutations that explain monogenic forms of this condition. Additionally, genome-wide association studies (GWAS) have provided valuable insights into the role of common polymorphisms in complex forms of SPGF. Interestingly, novel methods have shown that GWAS datasets can be used to infer rare coding variants that are causal for male infertility phenotypes, but this approach has never been applied to characterise the genetic component of a whole case-control cohort. Study design, size, duration We conducted a thorough examination of both common (minor allele frequency, MAF > 0.01) and rare (MAF < 0.01) genetic variation within a set of 1,797 spermatogenesis genes. This gene panel was meticulously curated through an exhaustive search in the literature and in different databases of male infertility genetics. The genotype data were obtained from a previously published GWAS in Europeans, encompassing over 6 million polymorphisms. Participants/materials, setting, methods We analysed a cohort that included 1,274 SPGF patients and 1,951 unaffected controls with European ancestry. Three independent approaches were follow: (1) variant-wise analysis using logistic regression models followed by a meta-analysis of the study cohorts; (2) gene-wise analysis using a Combined Multivariate and Collapsing (CMC) burden test; and (3) identification and characterisation of highly damaging rare coding variants in homozygosity. Multiple testing correction was applied to determine statistical significance Main results and the role of chance Our results suggested a potential association between SPGF and the rs12347237*T variant of the SHOC1 gene in the GWAS population (P = 3.17E-05, OR = 2.94). This association was subsequently validated in an independent Iberian cohort (Pcombined = 6.992E-06, OR = 2.61). Furthermore, our gene-wise analysis showed putative associations through the cumulative effect of some rare and low-frequency variants in SHOC1 (P = 4.9E-03), PCSK4 (P = 1E-04), AP3B1 (P = 5E-04), and DLK1 (P = 5E-04). Remarkably, the rare and common variants identified in SHOC1 are part of the same haplotype block, impacting both coding and non-coding regions. Additionally, we identified 35 individuals carrying 32 very rare and potentially pathogenic variants in homozygosity within the coding regions of the selected genes. Limitations, reasons for caution The analysis of low-frequency variants presents challenges in achieving sufficient statistical power to detect genetic associations. Consequently, independent studies involving large sample sets are essential to replicate our findings. In addition, the specific role of the identified variants in the pathogenic mechanisms of SPGF should be assessed using functional experiments. Wider implications of the findings The discovery of novel genetic risk factors for SPGF and the elucidation of the genetic causes underlying both monogenic and complex forms of SPGF provide new perspectives for personalized medicine and reproductive counselling. Trial registration number not applicable

P-055 Influence of a dynamic exposome on the genetic component of male infertility

Abstract Study question Do the genetic factors associated with idiopathic severe spermatogenic failure (SPGF) differ across age groups due to evolving environmental exposures over generations? Summary answer Dynamic changes in environmental exposures have the potential to reshape the genetic predisposition to idiopathic SPGF. What is known already Accumulating evidence suggests that the idiopathic form of SPGF may represent a complex trait with a multifactorial aetiology, wherein environmental factors influence the predisposition and development of the disease through their interaction with genetic polymorphisms. In a recent genome-wide association study (GWAS) of SPGF conducted in a European population, we identified genetic variants associated with this condition in immune and spermatogenesis-related genes. However, while GWASs serve as valuable tools for identifying susceptibility risk loci, our understanding of the influence of environmental factors and their specific impact on the genetic architecture of these conditions remains limited. Study design, size, duration Genome-wide genotype data from 912 SPGF cases and 1,360 unaffected controls from the Iberian Peninsula and Germany were analysed considering age as a proxy to assess exposure to varying environmental factors across generations. An in silico functional prioritisation of associated genomic regions was also performed to comprehensively evaluate the gene-environment relationships influencing the disease. Participants/materials, setting, methods The study cohort was stratified into two age groups: individuals aged 40 or older in 2023 (452 cases and 965 controls) and those under 40 in 2023 (460 cases and 424 controls). SPGF comprised individuals with non-obstructive azoospermia (n = 547) or non-obstructive oligozoospermia (n = 365). Logistic regression models were used for the case-control analysis, with the generation included as a covariate. Bioinformatic approaches involved the examination of functional annotations of the genome sourced from different public databases. Main results and the role of chance Thirteen genetic loci were found to be associated with idiopathic SPGF, assuming generation-dependent effects. Five of them showed a correlation with an increased susceptibility to SPGF in the youngest age group (rs72818509: P = 2.19E−05, rs57701320: P = 5.20E−05, rs79733930: P = 7.81E−05, rs77137582: P = 1.04E−04, rs75938373: P = 3.56E−05), while the remaining eight were specifically associated with the disease in the oldest age group (rs144324356: P = 2.37E−05, rs3763812: P = 8.61E−05, rs61997636: P = 1.00E−04, rs111364930: P = 9.63E−05, rs115408081: P = 5.77E-05, rs142908940: P = 1.76E−04, rs144031067: P = 1.76E-04, rs74514513: P = 1.76E-04). These associations were primarily attributed to the interaction between each lead variant and the age group. Additionally, associations were established between the identified genomic risk loci and various environmental factors, including toxic habits (such as smoking or alcohol consumption), diet-related traits (such as cholesterol levels, type 2 diabetes, and body mass index), respiratory disorders (such as asthma or COVID-19), autoimmune diseases (including systemic lupus erythematosus), and educational attainment. Our findings suggest that changes in environmental factors across generations could alter the genetic basis of idiopathic SPGF over time. Limitations, reasons for caution Despite the overall statistical power of our study cohort being suitable for detecting the expected effects, further independent studies comprising extensive cohorts across diverse ethnic populations are needed to validate the outcomes of our research. Wider implications of the findings Using a novel approach assess the potential impact of varying environmental factors on the genetic susceptibility to complex diseases, we gained insights into the intricate mechanisms underlying onset and progression of idiopathic SPGF. Understanding the etiological causes of multifactorial human disorders would help in developing personalized healthcare strategies. Trial registration number Not applicable

Proteomic prediction of diverse incident diseases: a machine learning-guided biomarker discovery study using data from a prospective cohort study

Broad-capture proteomic technologies have the potential to improve disease prediction, enabling targeted prevention and management, but studies have so far been limited to very few selected diseases and have not evaluated predictive performance across multiple conditions. We aimed to evaluate the potential of serum proteins to improve risk prediction over and above health-derived information and polygenic risk scores across a diverse set of 24 outcomes. We designed multiple case-cohorts nested in the EPIC-Norfolk prospective study, from participants with available serum samples and genome-wide genotype data, with more than 32 974 person-years of follow-up. Participants were middle-aged individuals (aged 40-79 years at baseline) of European ancestry who were recruited from the general population of Norfolk, England, between March, 1993 and December, 1997. We selected participants who developed one of ten less common diseases within 10 years of follow-up; we also subsampled a randomly drawn control subcohort, which also served to investigate 14 more common outcomes (n>70), including all-cause premature mortality (death before the age of 75 years; case numbers 71-437; controls 608-1556). Individuals were excluded from the current study owing to failed genotyping or proteomic quality control, relatedness, or missing information on age, sex, BMI, or smoking status. We used a machine learning framework to derive sparse predictive protein models for the onset of the the 23 individual diseases and all-cause premature mortality, and to derive a single common sparse multimorbidity signature that was predictive across multiple diseases from 2923 serum proteins. Participants who developed one of ten less common diseases within 10 years of follow-up included 482 women and 507 men, with a mean age at baseline of 64·56 years (8·08). The random subcohort included 990 women and 769 men, with a mean age of 58·79 years (9·31). As few as five proteins alone outperformed polygenic risk scores for 17 of 23 outcomes (median dfference in concordance index [C-index] 0·13 [0·10-0·17]) and improved predictive performance when added over basic patient-derived information models for seven outcomes, achieving a median C-index of 0·82 (IQR 0·77-0·82). This included diseases with poor prognosis such as lung cancer (C-index 0·85 [+/- cross-validation error 0·83-0·87]), for which we identified unreported biomarkers such as C-X-C motif chemokine ligand 17. A sparse multimorbidity signature of ten proteins improved prediction across seven outcomes over patient-derived information models, achieving performances (median C-index 0·81 [IQR 0·80-0·82]) similar to those of disease-specific signatures. We show the value of broad-capture proteomic biomarker discovery studies across multiple diseases of diverse causes, pointing to those that might benefit the most from proteomic approaches, and the potential to derive common sparse biomarker panels for prediction of multiple diseases at once. This framework could enable follow-up studies to explore the generalisability of proteomic models and to benchmark these against clinical assays, which are required to understand the translational potential of these findings. Medical Research Council, Health Data Research UK, UK Research and Innovation-National Institute for Health and Care Research, Cancer Research UK, and Wellcome Trust.

A rare missense p.C125Y mutation in the TNFRSF1A gene identified in a Chinese family with tumor necrosis factor receptor-associated periodic fever syndrome.

Tumor necrosis factor receptor-associated periodic syndrome (TRAPS) is a rare autosomal dominant disorder with a low incidence in Asia. The most frequent clinical manifestations include fever, rash, myalgia, joint pain and abdominal pain. Misdiagnosis rates are high because of the clinical and genetic variability of the disease. The pathogenesis of TRAPS is complex and yet to be fully defined. Early genetic diagnosis is the key to precise treatment. In this study, a Chinese family with suspected TRAPS were analyzed by genome-wide SNP genotyping, linkage analysis and targeted sequencing for identification of mutations in causative genes. To study the pathogenicity of the identified gene mutation, we performed a conservation analysis of the mutation site and protein structure analysis. Flow cytometry was used to detect TNFRSF1A shedding and quantitative real-time PCR were used to assess the activation of unfolded protein response (UPR) in the mutation carriers and healthy individuals. A typical TRAPS family history, with a pattern of autosomal dominant inheritance, led to the identification of a rare mutation in the TNFRSF1A gene (c.G374A [p.Cys125Tyr]) with unknown significance. The patient responded well to corticosteroids, and long-term therapy with colchicine effectively reduced the inflammatory attacks. No amyloid complications occurred during the 6-year follow-up. In silico protein analysis showed that the mutation site is highly conversed and the mutation prevents the formation of intrachain disulfide bonds in the protein. Despite a normal shedding of the TNFRSF1A protein from stimulated monocytes in the TRAPS patients with p.C125Y mutation, the expression of CHOP and the splicing of XBP1 was significantly higher than healthy controls, suggesting the presence of an activation UPR. This is the first report of a Chinese family with the rare p.C125Y mutation in TNFRSF1A. The p.C125Y mutation does not result in aberrant receptor shedding, but instead is associated with an activated UPR in these TRAPS patients, which may provide new insights into the pathogenesis of this rare mutation in TRAPS.

Common genetic variants associated with urinary phthalate levels in children: A genome-wide study

IntroductionPhthalates, or dieters of phthalic acid, are a ubiquitous type of plasticizer used in a variety of common consumer and industrial products. They act as endocrine disruptors and are associated with increased risk for several diseases. Once in the body, phthalates are metabolized through partially known mechanisms, involving phase I and phase II enzymes. ObjectiveIn this study we aimed to identify common single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) associated with the metabolism of phthalate compounds in children through genome-wide association studies (GWAS). MethodsThe study used data from 1,044 children with European ancestry from the Human Early Life Exposome (HELIX) cohort. Ten phthalate metabolites were assessed in a two-void pooled urine collected at the mean age of 8 years. Six ratios between secondary and primary phthalate metabolites were calculated. Genome-wide genotyping was done with the Infinium Global Screening Array (GSA) and imputation with the Haplotype Reference Consortium (HRC) panel. PennCNV was used to estimate copy number variants (CNVs) and CNVRanger to identify consensus regions. GWAS of SNPs and CNVs were conducted using PLINK and SNPassoc, respectively. Subsequently, functional annotation of suggestive SNPs (p-value < 1E-05) was done with the FUMA web-tool. ResultsWe identified four genome-wide significant (p-value < 5E-08) loci at chromosome (chr) 3 (FECHP1 for oxo-MiNP_oh-MiNP ratio), chr6 (SLC17A1 for MECPP_MEHHP ratio), chr9 (RAPGEF1 for MBzP), and chr10 (CYP2C9 for MECPP_MEHHP ratio). Moreover, 115 additional loci were found at suggestive significance (p-value < 1E-05). Two CNVs located at chr11 (MRGPRX1 for oh-MiNP and SLC35F2 for MEP) were also identified. Functional annotation pointed to genes involved in phase I and phase II detoxification, molecular transfer across membranes, and renal excretion. ConclusionThrough genome-wide screenings we identified known and novel loci implicated in phthalate metabolism in children. Genes annotated to these loci participate in detoxification, transmembrane transfer, and renal excretion.

A comprehensive tandem repeat catalog of the human genome.

With the increasing availability of long-read sequencing data, high-quality human genome assemblies, and software for fully characterizing tandem repeats, genome-wide genotyping of tandem repeat loci on a population scale becomes more feasible. Such efforts not only expand our knowledge of the tandem repeat landscape in the human genome but also enhance our ability to differentiate pathogenic tandem repeat mutations from benign polymorphisms. To this end, we analyzed 272 genomes assembled using datasets from three public initiatives that employed different long-read sequencing technologies. Here, we report a catalog of over 18 million tandem repeat loci, many of which were previously unannotated. Some of these loci are highly polymorphic, and many of them reside within coding sequences.

Genetic variation near GRB10 associated with bone growth and osteosarcoma risk in canine and human populations

BackgroundCanine and human osteosarcoma are similar in clinical presentation and tumor genomics. Giant breed dogs experience elevated osteosarcoma incidence, and taller stature remains a consistent risk factor for human osteosarcoma. Whether evolutionarily conserved genes contribute to both human and canine osteosarcoma predisposition merits evaluation. MethodsA multi-center sample of childhood osteosarcoma patients and controls underwent genome-wide genotyping and imputation. Ancestry-adjusted SNP associations were calculated within each dataset using logistic regression, then meta-analyzed across the three datasets, totaling 1091 patients and 3026 controls. Ten regions previously associated with canine osteosarcoma risk were mapped to the human genome, spanning ∼6 Mb. We prioritized association testing of 5985 human SNPs mapping to candidate osteosarcoma risk regions detected in Irish wolfhounds, the largest dog breed studied. Secondary analyses explored 6289 additional human SNPs mapping to candidate osteosarcoma risk regions identified in Rottweilers and greyhounds. ResultsFourteen SNPs were associated with human osteosarcoma risk after adjustment for multiple comparisons, all within a 42 kb region of human Chromosome 7p12.1. The lead variant was rs17454681 (OR=1.25, 95 %CI: 1.12–1.39; P=4.1×10−5), and independent risk variants were not observed in conditional analyses. While the associated region spanned 2.1 Mb and contained eight genes in Irish wolfhounds, associations were localized to a 50-fold smaller region of the human genome and strongly implicate GRB10 (growth factor receptor-bound protein 10) in canine and human osteosarcoma predisposition. PheWAS analysis in UK Biobank data identified noteworthy associations of the rs17454681 risk allele with varied measures of height and pubertal timing. ConclusionsOur comparative oncology analysis identified a novel human osteosarcoma risk allele near GRB10, a growth inhibitor that suppresses activated receptor tyrosine kinases including IGF1R, PDGFRB, and EGFR. Epidemiologists may benefit from leveraging cross-species comparisons to identify haplotypes in highly susceptible but genetically homogenous populations of domesticated animals, then fine-mapping these associations in diverse human populations.

Cohort Profile: Guangzhou Nutrition and Health Study (GNHS): A Population-based Multi-omics Study.

The Guangzhou Nutrition and Health Study (GNHS) aims to assess the determinants of metabolic disease in nutritional aspects, as well as other environmental and genetic factors, and explore possible biomarkers and mechanisms with multi-omics integration. The population-based sample of adults in Guangzhou, China (baseline: 40-83 years old; n = 5,118) was followed up about every 3 years. All are tracked via on-site follow-up and health information systems. We assessed detailed information on lifestyle factors, physical activities, dietary assessments, psychological health, cognitive function, body measurements, and muscle function. Instrument tests included dual-energy X-ray absorptiometry scanning, carotid artery and liver ultrasonography evaluations, vascular endothelial function evaluation, upper-abdomen and brain magnetic resonance imaging, and 14-day real-time continuous glucose monitoring tests. We also measured multi-omics, including host genome-wide genotyping, serum metabolome and proteome, gut microbiome (16S rRNA sequencing, metagenome, and internal transcribed spacer 2 sequencing), and fecal metabolome and proteome. The baseline surveys were conducted from 2008 to 2015. Now, we have completed 3 waves. The 3rd and 4th follow-ups have started but have yet to end. A total of 5,118 participants aged 40-83 took part in the study. The median age at baseline was approximately 59.0 years and the proportion of female participants was about 69.4%. Among all the participants, 3,628 (71%) completed at least one on-site follow-up, with a median duration of 9.48 years. The cohort will provide data that will be influential in establishing the role of nutrition in metabolic diseases with multi-omics.

Smoking-informed methylation and expression QTLs in human brain and colocalization with smoking-associated genetic loci

Smoking is a leading cause of preventable morbidity and mortality. Smoking is heritable, and genome-wide association studies (GWASs) of smoking behaviors have identified hundreds of significant loci. Most GWAS-identified variants are noncoding with unknown neurobiological effects. We used genome-wide genotype, DNA methylation, and RNA sequencing data in postmortem human nucleus accumbens (NAc) to identify cis-methylation/expression quantitative trait loci (meQTLs/eQTLs), investigate variant-by-cigarette smoking interactions across the genome, and overlay QTL evidence at smoking GWAS-identified loci to evaluate their regulatory potential. Active smokers (N = 52) and nonsmokers (N = 171) were defined based on cotinine biomarker levels and next-of-kin reporting. We simultaneously tested variant and variant-by-smoking interaction effects on methylation and expression, separately, adjusting for biological and technical covariates and correcting for multiple testing using a two-stage procedure. We found >2 million significant meQTL variants (padj < 0.05) corresponding to 41,695 unique CpGs. Results were largely driven by main effects, and five meQTLs, mapping to NUDT12, FAM53B, RNF39, and ADRA1B, showed a significant interaction with smoking. We found 57,683 significant eQTL variants for 958 unique eGenes (padj < 0.05) and no smoking interactions. Colocalization analyses identified loci with smoking-associated GWAS variants that overlapped meQTLs/eQTLs, suggesting that these heritable factors may influence smoking behaviors through functional effects on methylation/expression. One locus containing MUSTN1 and ITIH4 colocalized across all data types (GWAS, meQTL, and eQTL). In this first genome-wide meQTL map in the human NAc, the enriched overlap with smoking GWAS-identified genetic loci provides evidence that gene regulation in the brain helps explain the neurobiology of smoking behaviors.

Breast cancer polygenic risk score and patient survival outcomes in the Pathways study.

10502 Background: Many common, low-penetrance variants have been identified for breast cancer risk through genome-wide association studies, leading to the development of polygenic scores (PGS) to aggregate the effects of individual variants for risk prediction. Much less is known about genetic determinants of breast cancer-related outcomes. We hypothesized that breast cancer patients with high breast cancer PGS are at risk of a second breast-related adverse event, such as recurrence, contralateral breast cancer, or death. Methods: The Pathways Study is a prospective cohort study of breast cancer survivors enrolled shortly after diagnosis in 2006-2013 at Kaiser Permanente Northern California, with ongoing follow-up. Genome-wide genotype data were available from 3,995 patients for calculation of 4 PGS, including PGS313, PGS4k, PGS5k, and PGS6m. Scores were categorized into tertiles to investigate their associations with 7 survival outcomes including recurrence, contralateral second primary breast cancer, other second primary cancer, and death. Hazard ratios (HR) and 95% confidence intervals (CI) were derived from multivariable Cox proportional hazards regression models. Results: The median age at diagnosis was 60 (23.6-94.8) years, and most (68%) self-identified as White. Many women had estrogen receptor (ER)+ (83.4%), stage I and II tumors (89%), with 13.3% HER2+ tumors. The majority (60%) received lumpectomy and some type of adjuvant therapy (44.3% radiotherapy, 47.0% chemotherapy, and 74.6% received hormonal therapy). By December 31, 2021, the median follow-up time was 10.5 (0.2-14.2) years, with 504 recurrences, 419 total second primary cancers, 146 contralateral second primary breast cancers, 237 non-breast second primary cancers, and 762 deaths (352 breast cancer-specific deaths) observed. In Table 1, patients with medium (T2) and high (T3) PGS313 had higher risk of recurrence, but not contralateral breast cancer or other second primary cancer. They also had higher risk of all-cause death, breast cancer-specific death, total breast cancer event, and invasive disease. The other 3 PGS were not associated with survival outcomes examined. Conclusions: Our study reveals that breast cancer patients with higher PGS313 had higher risk of recurrence, total breast cancer and invasive breast cancer events, and death. These findings highlight a potential role of breast cancer PGS for prognosis, warranting further exploration. [Table: see text]

TWINGEN: protocol for an observational clinical biobank recall and biomarker cohort study to identify Finnish individuals with high risk of Alzheimer’s disease

IntroductionA better understanding of the earliest stages of Alzheimer’s disease (AD) could expedite the development or administration of treatments. Large population biobanks hold the promise to identify individuals at an...

Screening embryos for polygenic disease risk: a review of epidemiological, clinical, and ethical considerations.

The genetic composition of embryos generated by in vitro fertilization (IVF) can be examined with preimplantation genetic testing (PGT). Until recently, PGT was limited to detecting single-gene, high-risk pathogenic variants, large structural variants, and aneuploidy. Recent advances have made genome-wide genotyping of IVF embryos feasible and affordable, raising the possibility of screening embryos for their risk of polygenic diseases such as breast cancer, hypertension, diabetes, or schizophrenia. Despite a heated debate around this new technology, called polygenic embryo screening (PES; also PGT-P), it is already available to IVF patients in some countries. Several articles have studied epidemiological, clinical, and ethical perspectives on PES; however, a comprehensive, principled review of this emerging field is missing. This review has four main goals. First, given the interdisciplinary nature of PES studies, we aim to provide a self-contained educational background about PES to reproductive specialists interested in the subject. Second, we provide a comprehensive and critical review of arguments for and against the introduction of PES, crystallizing and prioritizing the key issues. We also cover the attitudes of IVF patients, clinicians, and the public towards PES. Third, we distinguish between possible future groups of PES patients, highlighting the benefits and harms pertaining to each group. Finally, our review, which is supported by ESHRE, is intended to aid healthcare professionals and policymakers in decision-making regarding whether to introduce PES in the clinic, and if so, how, and to whom. We searched for PubMed-indexed articles published between 1/1/2003 and 1/3/2024 using the terms 'polygenic embryo screening', 'polygenic preimplantation', and 'PGT-P'. We limited the review to primary research papers in English whose main focus was PES for medical conditions. We also included papers that did not appear in the search but were deemed relevant. The main theoretical benefit of PES is a reduction in lifetime polygenic disease risk for children born after screening. The magnitude of the risk reduction has been predicted based on statistical modelling, simulations, and sibling pair analyses. Results based on all methods suggest that under the best-case scenario, large relative risk reductions are possible for one or more diseases. However, as these models abstract several practical limitations, the realized benefits may be smaller, particularly due to a limited number of embryos and unclear future accuracy of the risk estimates. PES may negatively impact patients and their future children, as well as society. The main personal harms are an unindicated IVF treatment, a possible reduction in IVF success rates, and patient confusion, incomplete counselling, and choice overload. The main possible societal harms include discarded embryos, an increasing demand for 'designer babies', overemphasis of the genetic determinants of disease, unequal access, and lower utility in people of non-European ancestries. Benefits and harms will vary across the main potential patient groups, comprising patients already requiring IVF, fertile people with a history of a severe polygenic disease, and fertile healthy people. In the United States, the attitudes of IVF patients and the public towards PES seem positive, while healthcare professionals are cautious, sceptical about clinical utility, and concerned about patient counselling. The theoretical potential of PES to reduce risk across multiple polygenic diseases requires further research into its benefits and harms. Given the large number of practical limitations and possible harms, particularly unnecessary IVF treatments and discarded viable embryos, PES should be offered only within a research context before further clarity is achieved regarding its balance of benefits and harms. The gap in attitudes between healthcare professionals and the public needs to be narrowed by expanding public and patient education and providing resources for informative and unbiased genetic counselling.

Landscape of TPMT and NUDT15 Pharmacogenetic Variation in a Cohort of Canadian Pediatric Inflammatory Bowel Disease Patients.

Patients with inflammatory bowel disease (IBD) exhibit considerable interindividual variability in medication response, highlighting the need for precision medicine approaches to optimize and tailor treatment. Pharmacogenetics (PGx) offers the ability to individualize dosing by examining genetic factors underlying the metabolism of medications such as thiopurines. Pharmacogenetic testing can identify individuals who may be at risk for thiopurine dose-dependent adverse reactions including myelosuppression. We aimed to evaluate PGx variation in genes supported by clinical guidelines that inform dosing of thiopurines and characterize differences in the distribution of actionable PGx variation among diverse ancestral groups. Pharmacogenetic variation in TPMT and NUDT15 was captured by genome-wide genotyping of 1083 pediatric IBD patients from a diverse Canadian cohort. Genetic ancestry was inferred using principal component analysis. The proportion of PGx variation and associated metabolizer status phenotypes was compared across 5 genetic ancestral groups within the cohort (Admixed American, African, East Asian, European, and South Asian) and to prior global estimates from corresponding populations. Collectively, 11% of the cohort was categorized as intermediate or poor metabolizers of thiopurines, which would warrant a significant dose reduction or selection of alternate therapy. Clinically actionable variation in TPMT was more prevalent in participants of European and Admixed American/Latino ancestry (8.7% and 7.5%, respectively), whereas variation in NUDT15 was more prevalent in participants of East Asian and Admixed American/Latino ancestry (16% and 15% respectively). These findings demonstrate the considerable interpopulation variability in PGx variation underlying thiopurine metabolism, which should be factored into testing diverse patient populations.

Novel Genetic Risk Marker for Paranoid Schizophrenia in the Chromosomal Region 9q21.13 in Tatars: A Genome-Wide Association Analysis

Schizophrenia, the most common severe mental illness, leads to a serious decrease in higher functions, mainly to a change in cognitive functions and perception of reality. Both genetic and environmental factors are involved in its pathogenesis; however, its genetic component still needs to be studied. The aim of the study was to identify genetic markers of paranoid schizophrenia in Tatars from the Republic of Bashkortostan. Genome-wide genotyping of DNA samples was carried out on the PsychChip biochip, which included 610,000 single nucleotide polymorphic variants (SNPs). The studied sample consisted of 357 patients with paranoid schizophrenia and 383 healthy individuals of Tatar ethnicity. As a result of the study, the association of the SNP rs12376586 of the MAMDC2 gene located in the region 9q21.13 with the development of paranoid schizophrenia in Tatars living in the Republic of Bashkortostan was established for the first time.

Prediction of response to promising first-line chemotherapy in ovarian cancer patients with residual peritoneal tumors: practical biomarkers and robust multiplex models.

Platinum/taxane (TC) chemotherapy with debulking surgery stays the mainstay of the treatment in ovarian cancer patients with peritoneal metastasis, and recently its novel modality, intraperitoneal carboplatin with dose-dense paclitaxel (ddTCip), was shown to have greater therapeutic impact. Nevertheless, the response varies among patients and consequent recurrence, or relapse often occurs. Discovery of therapeutic response predictor to ddTCip and/or TC therapy is eagerly awaited to improve the treatment outcome. Using datasets in 76 participants in our ddTCip study and published databases on patients received TC therapy, we first validated a total of 75 previously suggested markers, sought out more active biomarkers through the association analyses of genome-wide transcriptome and genotyping data with progression-free survival (PFS) and adverse events, and then developed multiplex statistical prediction models for PFS and toxicity by mainly using multiple regression analysis and the classification and regression tree (CART) algorithm. The association analyses revealed that SPINK1 could be a possible biomarker of ddTCip efficacy, while ABCB1 rs1045642 and ERCC1 rs11615 would be a predictor of hematologic toxicity and peripheral neuropathy, respectively. Multiple regression analyses and CART algorithm finally provided a potent efficacy prediction model using 5 gene expression data and robust multiplex toxicity prediction models-CART models using a total of 4 genotype combinations and multiple regression models using 15 polymorphisms on 12 genes. Biomarkers and multiplex models composed here could work well in the response prediction of ddTCip and/or TC therapy, which might contribute to realize optimal selection of the key therapy.

Genome-Wide Epistatic Network Analyses of Semantic Fluency in Older Adults.

Semantic fluency impairment has been attributed to a wide range of neurocognitive and psychiatric conditions, especially in the older population. Moderate heritability estimates on semantic fluency were obtained from both twin and family-based studies suggesting genetic contributions to the observed variation across individuals. Currently, effort in identifying the genetic variants underlying the heritability estimates for this complex trait remains scarce. Using the semantic fluency scale and genome-wide SNP genotype data from the Long Life Family Study (LLFS), we performed a genome-wide association study (GWAS) and epistasis network analysis on semantic fluency in 2289 individuals aged over 60 years from the American LLFS cohorts and replicated the findings in 1129 individuals aged over 50 years from the Danish LLFS cohort. In the GWAS, two SNPs with genome-wide significance (rs3749683, p = 2.52 × 10-8; rs880179, p = 4.83 × 10-8) mapped to the CMYAS gene on chromosome 5 were detected. The epistasis network analysis identified five modules as significant (4.16 × 10-5 < p < 7.35 × 10-3), of which two were replicated (p < 3.10 × 10-3). These two modules revealed significant enrichment of tissue-specific gene expression in brain tissues and high enrichment of GWAS catalog traits, e.g., obesity-related traits, blood pressure, chronotype, sleep duration, and brain structure, that have been reported to associate with verbal performance in epidemiological studies. Our results suggest high tissue specificity of genetic regulation of gene expression in brain tissues with epistatic SNP networks functioning jointly in modifying individual verbal ability and cognitive performance.

Genetic variation and pesticide exposure influence blood DNA methylation signatures in females with early-stage Parkinson’s disease

Although sex, genetics, and exposures can individually influence risk for sporadic Parkinson’s disease (PD), the joint contributions of these factors to the epigenetic etiology of PD have not been comprehensively assessed. Here, we profiled sex-stratified genome-wide blood DNAm patterns, SNP genotype, and pesticide exposure in agricultural workers (71 early-stage PD cases, 147 controls) and explored replication in three independent samples of varying demographics (n = 218, 222, and 872). Using a region-based approach, we found more associations of blood DNAm with PD in females (69 regions) than in males (2 regions, Δβadj| ≥0.03, padj ≤ 0.05). For 48 regions in females, models including genotype or genotype and pesticide exposure substantially improved in explaining interindividual variation in DNAm (padj ≤ 0.05), and accounting for these variables decreased the estimated effect of PD on DNAm. The results suggested that genotype, and to a lesser degree, genotype-exposure interactions contributed to variation in PD-associated DNAm. Our findings should be further explored in larger study populations and in experimental systems, preferably with precise measures of exposure.