Using GWAS and Machine Learning to Identify and Predict Genetic Variants Associated with Foodborne Bacteria Phenotypic Traits.

One of the main challenges in food microbiology is to prevent the risk of outbreaks by avoiding the distribution of food contaminated by bacteria. This requires constant monitoring of the circulating strains throughout the food production chain. Bacterial genomes contain signatures of natural evolution and adaptive markers that can be exploited to better understand the behavior of pathogen in the food industry. The monitoring of foodborne strains can therefore be facilitated by the use of these genomic markers capable of rapidly providing essential information on isolated strains, such as the source of contamination, risk of illness, potential for biofilm formation, and tolerance or resistance to biocides. The increasing availability of large genome datasets is enhancing the understanding of the genetic basis of complex traits such as host adaptation, virulence, and persistence. Genome-wide association studies have shown very promising results in the discovery of genomic markers that can be integrated into rapid detection tools. In addition, machine learning has successfully predicted phenotypes and classified important traits. Genome-wide association and machine learning tools have therefore the potential to support decision-making circuits intending at reducing the burden of foodborne diseases. The aim of this chapter review is to provide knowledge on the use of these two methods in food microbiology and to recommend their use in the field.

Assessing the causal relationship between non-small cell lung cancer and sepsis: a Mendelian randomization study.

BACKGROUND: A Two-sample Mendelian randomization (MR) Analysis was used to assess the causal relationship between non-small cell lung cancer (NSCLC) and sepsis. METHOD: Single nucleotide polymorphisms (SNPs) closely associated with NSCLC were utilized as instrumental variables (IVs) in this study. The Inverse Variance Weighted (IVW) method was used as the primary method for MR analysis, supplemented by the Weighted median, Weighted model, and MR-Egger regression method. Sensitivity analysis was conducted to improve result robustness, and data from various sources were validated and integrated. Bonferroni tests were applied to adjust for multiple comparisons. RESULTS: After Bonferroni tests correcting the combined results, MR analysis revealed a significant association between genetically predicted NSCLC and an increased susceptibility to sepsis (odds ratios [OR]: 1.140, 95% confidence interval [CI]: 1.085-1.199, P = 2.61 × 10- 7). The combined results demonstrated that NSCLC is associated with a heightened risk of sepsis in patients under 75 years of age (OR: 1.085, 95%CI: 1.037-1.353, P = 3.84 × 10- 4). Furthermore, lung adenocarcinoma (LUAD) was found to be potentially associated with an increased susceptibility to sepsis (OR: 1.040, 95% CI: 1.009-1.073, P = 1.16 × 10- 2). These results withstood multiple sensitivity analyses, demonstrating their robustness. CONCLUSION: This study confirms that NSCLC can significantly increase susceptibility to sepsis at the genetic level, providing valuable insights for the early identification of individuals at risk for sepsis.

New insights on genetic background of major diabetic vascular complications.

BACKGROUND: By 2045, it is expected that 693 million individuals worldwide will have diabetes and with greater risk of morbidity, mortality, loss of vision, renal failure, and a decreased quality of life due to the devastating effects of macro- and microvascular complications. As such, clinical variables and glycemic control alone cannot predict the onset of vascular problems. An increasing body of research points to the importance of genetic predisposition in the onset of both diabetes and diabetic vascular complications. OBJECTIVES: Purpose of this article is to review these approaches and narrow down genetic findings for Diabetic Mellitus and its consequences, highlighting the gaps in the literature necessary to further genomic discovery. MATERIAL AND METHODS: In the past, studies looking for genetic risk factors for diabetes complications relied on methods such as candidate gene studies, which were rife with false positives, and underpowered genome-wide association studies, which were constrained by small sample sizes. RESULTS: The number of genetic findings for diabetes and diabetic complications has over doubled due to the discovery of novel genomics data, including bioinformatics and the aggregation of global cohort studies. Using genetic analysis to determine whether diabetes individuals are at the most risk for developing diabetic vascular complications (DVC) might lead to the development of more accurate early diagnostic biomarkers and the customization of care plans. CONCLUSIONS: A newer method that uses extensive evaluation of single nucleotide polymorphisms (SNP) in big datasets is Genome-Wide Association Studies (GWAS).

Association of a composite trait for anthropometrics, adiposity and energy expenditure with cardiometabolic diseases: An age-stratified cohort and genetic risk score analysis.

AIM: Various anthropometric measures capture distinct as well as overlapping characteristics of an individual's body composition. To characterize independent body composition measures, we aimed to reduce easily-obtainable individual measures reflecting adiposity, anthropometrics and energy expenditure into fewer independent constructs, and to assess their potential sex- and age-specific relation with cardiometabolic diseases. METHODS: Analyses were performed within European ancestry participants from UK Biobank (N = 418,963, mean age 58.0 years, 56% women). Principal components (PC) analyses were used for the dimension reduction of 11 measures of adiposity, anthropometrics and energy expenditure. PCs were studied in relation to incident type 2 diabetes mellitus (T2D) and coronary artery disease (CAD). Multivariable-adjusted Cox regression analyses, adjusted for confounding factors, were performed in all and stratified by age. Genome-wide association studies were performed in half of the cohort (N = 156,295) to identify genetic variants as instrumental variables. Genetic risk score analyses were performed in the other half of the cohort stratified by age of disease onset (N = 156,295). RESULTS: We identified two PCs, of which PC1 reflected lower overall adiposity (negatively correlated with all adiposity aspects) and PC2 reflected more central adiposity (mainly correlated with higher waist-hip ratio, but with lower total body fat) and increased height, collectively capturing 87.8% of the total variance. Similar to that observed in the multivariable-adjusted regression analyses, we found associations between the PC1 genetic risk score and lower risks of CAD and T2D [CAD cases <50 years, odds ratio: 0.91 (95% confidence interval 0.87, 0.94) per SD; T2D cases <50 years, odds ratio: 0.76 (0.72, 0.81)], which attenuated with higher age (p-values 8.13E-4 and 2.41E-6, respectively). No associations were found for PC2. CONCLUSIONS: The consistently observed weaker associations of the composite traits with cardiometabolic disease suggests the need for age-specific cardiometabolic disease prevention strategies.

Bidirectional two-sample Mendelian randomization analysis investigates causal associations between cathepsins and inflammatory bowel disease.

Background: Cathepsins, key regulators of the pathology of gastrointestinal disorders such as inflammatory bowel disease (IBD), are a target protease that has attracted much attention in recent years. IBD is a chronic and relapsing inflammatory disorder of the gut. Traditional studies have shown a correlation between cathepsin and the risk of IBD, while the causal relationship remains unclear. Methods: This study utilized Mendelian randomization techniques to evaluate the causal relationships between eleven cathepsins and the subtypes of IBD, such as ulcerative colitis (UC) and Crohn's disease (CD). We also performed a series of sensitivity analyses to validate the primary Mendelian randomization (MR) results, including Cochran's Q test, the MR-PRESSO global test, and the MR pleiotropy test. Results: The forward MR analyses showed no significant association between cathepsins and IBD. Reverse Mendelian randomization analyses suggested that UC might lead to elevated cathepsin G levels [inverse-variance weighted (IVW): p = 0.038, b = 9.966], and CD might cause a decrease in cathepsin B levels [IVW: p = 0.002, b = -10.525] and cathepsin L1 levels [IVW: p = 0.045, b = -4.742]. Conclusions: Our findings offer novel and comprehensive evidence on the impact of UC or CD on cathepsins, potentially providing valuable insights into the treatment and prognosis of IBD.

Corrigendum: Genome-wide association study identifying variants related to performance and injury in high-performance athletes.

[This corrects the article DOI: 10.1177/15353702231198068.].

A genome-wide Association study of the Count of Codeine prescriptions.

Opioid prescription records in existing electronic health record (EHR) databases are a potentially useful, high-fidelity data source for opioid use-related risk phenotyping in genetic analyses. Prescriptions for codeine derived from EHR records were used as targeting traits by screening 16 million patient-level medication records. Genome-wide association analyses were then conducted to identify genomic loci and candidate genes associated with different count patterns of codeine prescriptions. Both low- and high-prescription counts were captured by developing 8 types of phenotypes with selected ranges of prescription numbers to reflect potentially different levels of opioid risk severity. We identified one significant locus associated with low-count codeine prescriptions (1, 2 or 3 prescriptions), while up to 7 loci were identified for higher counts (≥ 4, ≥ 5, ≥6, or ≥ 7 prescriptions), with a strong overlap across different thresholds. We identified 9 significant genomic loci with all-count phenotype. Further, using the polygenic risk approach, we identified a significant correlation (Tau = 0.67, p = 0.01) between an externally derived polygenic risk score for opioid use disorder and numbers of codeine prescriptions. As a proof-of-concept study, our research provides a novel and generalizable phenotyping pipeline for the genomic study of opioid-related risk traits.

Development of genomic and genetic resources facilitating molecular genetic studies on untapped Myanmar rice germplasms.

To counteract the growing population and climate changes, resilient varieties adapted to regional environmental changes are required. Landraces are valuable genetic resources for achieving this goal. Recent advances in sequencing technology have enabled national seed/gene banks to share genomic and genetic information from their collections including landraces, promoting the more efficient utilization of germplasms. In this study, we developed genomic and genetic resources for Myanmar rice germplasms. First, we assembled a diversity panel consisting of 250 accessions representing the genetic diversity of Myanmar indica varieties, including an elite lowland variety, Inn Ma Yebaw (IMY). Our population genetic analyses illustrated that the diversity panel represented Myanmar indica varieties well without any apparent population structure. Second, de novo genome assembly of IMY was conducted. The IMY assembly was constructed by anchoring 2888 contigs, which were assembled from 30× coverage of long reads, into 12 chromosomes. Although many gaps existed in the IMY genome assembly, our quality assessments indicated high completeness in the gene-coding regions, identical to other near-gap-free assemblies. Together with dense variant information, the diversity panel and IMY genome assembly will facilitate deeper genetic research and breeding projects that utilize the untapped Myanmar rice germplasms.

Identification of Key Genes Controlling Sugar and Organic Acid Accumulation in Wampee Fruit (Clausena lansium) via Genome Assembly and Genome-wide Association Analysis.

Wampee (Clausena lansium) is an economically significant subtropical fruit tree widely cultivated in Southern China. To provide high-quality genomic resources for C. lansium, we report a chromosome-level genome sequence for the "JinFeng" cultivar. The 297.1 Mb C. lansium genome contained nine chromosomes with a scaffold N50 of 29.2 Mb and encoded 23,468 protein-coding genes. Selective sweep analysis between sweet and sour C. lansium varieties and genome-wide association analysis identified 14 candidate genes putatively involved in sugar and acid accumulation. ClERF061, encoding an ethylene response factor, and ClSWEET7, encoding a Sugars Will Eventually be Exported Transporters (SWEET) family protein, were proposed as key regulators of the sweet and sour tastes of the wampee fruit. ClERF061 and ClSWEET7 overexpression in tomatoes increased the total sugar and acid content in fruits. ClSWEET7 promoter activation by ClERF061 was confirmed via Nicotiana benthamiana transient expression. Our study provides valuable genomic resources for C. lansium genetics and breeding.

Genome-wide association study of cassava brown streak disease resistance in cassava germplasm conserved in South America.

Cassava (Manihot esculenta Crantz) is a vital carbohydrate source for over 800 million people globally, yet its production in East Africa is severely affected by cassava brown streak disease (CBSD). Genebanks, through ex-situ conservation, play a pivotal role in preserving crop diversity, providing crucial resources for breeding resilient and disease-resistant crops. This study genotyped 234 South American cassava accessions conserved at the CIAT genebank, previously phenotyped for CBSD resistance by an independent group, to perform a genome-wide association analysis (GWAS) to identify genetic variants associated with CBSD resistance. Our GWAS identified 35 single nucleotide polymorphism (SNP) markers distributed across various chromosomes, associated with disease severity or the presence/absence of viral infection. Markers were annotated within or near genes previously identified with functions related to pathogen recognition and immune response activation. Using the SNP candidates, we screened the world's largest cassava collection for accessions with a higher frequency of favorable genotypes, proposing 35 accessions with potential resistance to CBSD. Our results provide insights into the genetics of CBSD resistance and highlight the importance of genetic resources to equip breeders with the raw materials needed to develop new crop varieties resistant to pests and diseases.

Immune cell traits and causal relationships with cholecystitis: a mendelian randomization analysis.

Cholecystitis, characterized by inflammation of the gallbladder, is intricately linked to immune cells and the cytokines they produce. Despite this association, the specific contributions of immune cells to the onset and progression of cholecystitis remain to be fully understood. To delineate this relationship, we utilized the Mendelian randomization (MR) method to scrutinize the causal connections between 731 immune cell phenotypes and cholecystitis. By conducting MR analysis on 731 immune cell markers from public datasets, this study seeks to understand their potential impact on the risk of cholecystitis. It aims to elucidate the interactions between immune phenotypes and the disease, aiming to lay the groundwork for advancing precision medicine and developing effective treatment strategies for cholecystitis. Taking immune cell phenotypes as the exposure factor and cholecystitis as the outcome event, this study used single nucleotide polymorphisms (SNPs) closely associated with both immune cell phenotypes and cholecystitis as genetic instrumental variables. We conducted a two-sample MR analysis on genome-wide association studies (GWAS) data. Our research thoroughly examined 731 immune cell markers, to determine potential causal relationships with susceptibility to cholecystitis. Sensitivity analyses were performed to ensure the robustness of our findings, excluding the potential impacts of heterogeneity and pleiotropy. To avoid reverse causality, we conducted reverse MR analyses with cholecystitis as the exposure factor and immune cell phenotypes as the outcome event. Among the 731 immune phenotypes, our study identified 21 phenotypes with a causal relationship to cholecystitis (P < 0.05). Of these, eight immune phenotypes exhibited a protective effect against cholecystitis (odds ratio (OR) < 1), while the other 13 immune phenotypes were associated with an increased risk of developing cholecystitis (OR > 1). Additionally, employing the false discovery rate (FDR) method at a significance level of 0.2, no significant causal relationship was found between cholecystitis and immune phenotypes. Our research has uncovered a significant causal relationship between immune cell phenotypes and cholecystitis. This discovery not only enhances our understanding of the role of immune cells in the onset and progression of cholecystitis but also establishes a foundation for developing more precise biomarkers and targeted therapeutic strategies. It provides a scientific basis for more effective and personalized treatments in the future. These findings are expected to substantially improve the quality of life for patients with cholecystitis and mitigate the impact of the disease on patients and their families.

Genetic interactions and pleiotropy in metabolic diseases: Insights from a comprehensive GWAS analysis.

This study offers insights into the genetic and biological connections between nine common metabolic diseases using data from genome-wide association studies. Our goal is to unravel the genetic interactions and biological pathways of these complex diseases, enhancing our understanding of their genetic architecture. We employed a range of advanced analytical techniques to explore the genetic correlations and shared genetic variants of these diseases. These methods include Linked Disequilibrium Score Regression, High-Definition Likelihood (HDL), genetic analysis combining multiplicity and annotation (GPA), two-sample Mendelian randomization analyses, analysis under the multiplicity-complex null hypothesis (PLACO), and Functional mapping and annotation of genetic associations (FUMA). Additionally, Bayesian co-localization analyses were used to examine associations of specific loci across traits. Our study discovered significant genomic correlations and shared loci, indicating complex genetic interactions among these metabolic diseases. We found several shared single nucleotide variants and risk loci, notably highlighting the role of the immune system and endocrine pathways in these diseases. Particularly, rs2476601 and its associated gene PTPN22 appear to play a crucial role in the connection between type 2 diabetes mellitus, hypothyroidism/mucous oedema and hypoglycaemia. These findings enhance our understanding of the genetic underpinnings of these diseases and open new potential avenues for targeted therapeutic and preventive strategies. The results underscore the importance of considering pleiotropic effects in deciphering the genetic architecture of complex diseases, especially metabolic ones.

Causal links between immune cells and asthma: Insights from a Mendelian Randomization analysis.

OBJECTIVES: Recent studies suggest immunophenotypes may play a role in asthma, but their causal relationship has not been thoroughly examined. METHODS: We used single nucleotide polymorphism (SNP)-derived instrumental variables. Summary data from 731 immune cell profiles and asthma cases were analyzed from genome-wide association studies (GWAS) of European populations. Mendelian Randomization (MR) analyses included inverse variance weighted (IVW), weighted median, and MR-Egger methods. Pleiotropy was assessed using the MR-Egger intercept and MR pleiotropy residual sum and outlier (MR-PRESSO) tests. Reverse MR analysis explored bidirectional causation between asthma and immunophenotypes. All statistical analyses were conducted using R software. RESULTS: MR analysis identified 108 immune signatures potentially contributing to asthma. Two immunophenotypes were significantly associated with asthma risk: CD4+ secreting Treg cells in allergic asthma (ORIVW = 1.078; 95% CI: 1.036-1.122; PIVW = 0.0002) and IgD + CD38- %lymphocyte cells in non-allergic asthma (ORIVW = 1.123; 95% CI: 1.057-1.194; PIVW = 0.0002). CONCLUSIONS: This study highlights the causal associations between specific immunophenotypes and asthma risk, providing new insights into asthma pathogenesis.

Potential causal link between dietary intake and epilepsy: a bidirectional and multivariable Mendelian randomization study.

Background: Epilepsy is a common neurological disease, and dietary intake has been suggested as a potential modifiable risk factor. However, the causality of associations between dietary intake and epilepsy remains uncertain. This study aimed to investigate the potential causal relationships between various dietary intakes and epilepsy using Mendelian randomization (MR) analysis. Methods: A two-sample MR approach was employed, utilizing genetic variants associated with dietary factors as instrumental variables (IVs). Genome-Wide Association Study (GWAS) summary data on dietary intakes were obtained from the UK Biobank, while data on epilepsy were sourced from the European Bioinformatics Institute. The number of genetic variants used as IVs varied for each dietary factor. Inverse-variance weighted (IVW), weighted median, MR-Egger, and Bayesian weighted MR (BWMR) methods were used to assess causality. Multivariable MR (MVMR) was performed, adjusting for potential confounders. Sensitivity analyses were conducted to evaluate the robustness of the findings. Results: The study identified a significant inverse association between non-oily fish intake and epilepsy risk (OR = 0.281, 95% CI: 0.099-0.801, p = 0.018) using the IVW method. This finding was corroborated by the BWMR analysis (OR = 0.277, 95% CI: 0.094-0.814, p = 0.020). The MVMR analysis further confirmed the protective effect of non-oily fish intake on epilepsy risk after adjusting for potential confounders. In the reverse MR analysis, epilepsy was associated with reduced water intake (OR = 0.989, 95% CI: 0.980-0.997, p = 0.011). Conclusion: The present MR study provides evidence of a causal, protective relationship between non-oily fish intake and reduced epilepsy risk. Additionally, the findings suggest that epilepsy may influence water intake patterns. These results contribute to our understanding of the role of dietary factors in epilepsy and may inform dietary recommendations for the management and prevention of this condition.

Association between sleep traits and risk of colorectal cancer: a bidirectional Mendelian randomization study.

Background: Sleep traits have been linked to diseases; particularly, their impact on cancer has received increasing attention. This study aimed to investigate whether sleep traits have a causal relationship with colorectal cancer (CRC) using two-sample Mendelian randomization (TSMR). Methods: Genetic instrumental variables (IVs) for seven sleep traits (sleep duration, ease of getting up in the morning, morning chronotype, daytime napping, insomnia symptoms, snoring, and daytime dozing) were selected from pooled data from published genome-wide association studies (GSWSs). Two-sample multivariate Mendelian randomization (MR) analyses were conducted to assess the causal association between sleep traits and CRC. Reverse MR analyses were performed to determine the causal relationship between CRC and sleep traits. Inverse variance weighted (IVW), MR-Egger, and weighted medians were calculated for all MR analyses. Results: The multivariable MR (MVMR) analysis found that appropriate sleep duration [odds ratio (OR) =0.989; 95% confidence interval (CI): 0.980, 0.999; P=0.04] and ease of getting up in the morning (OR =0.990; 95% CI: 0.980, 1.000; P=0.04) were protective factors for CRC. Snoring (OR =1.021; 95% CI: 1.002, 1.041; P=0.03) was associated with the risk of CRC. Ease of getting up in the morning (OR =0.990; 95% CI: 0.983, 0.997; P=0.003) was associated with reduced risk of colon cancer. Morning chronotype (OR =1.004; 95% CI: 1.000, 1.007; P=0.04) was associated with the risk of colon cancer. Insomnia symptoms (OR =0.995; 95% CI: 0.990, 0.999; P=0.03) were a protective factor for rectal cancer. There was no evidence found for a causal association between other sleep traits and CRC, colon, or rectal cancer. Conclusions: Proper sleep duration and ease of getting up in the morning may be protective factors against CRC, and snoring may increase the risk of CRC.

Identification of quantitative trait loci of pod dehiscence in a collection of soybean grown in the southeast of Kazakhstan.

Soybean [Glycine max (L.) Merr.] is one of the important crops that are constantly increasing their cultivation area in Kazakhstan. It is particularly significant in the southeastern regions of the country, which are currently predominant areas for cultivating this crop. One negative trait reducing yield in these dry areas is pod dehiscence (PD). Therefore, it is essential to understand the genetic control of PD to breed new cultivars with high yield potential. In this study, we evaluated 273 soybean accessions from different regions of the world for PD resistance in the conditions of southeastern regions of Kazakhstan in 2019 and 2021. The field data for PD suggested that 12 accessions were susceptible to PD in both studied years, and 32 accessions, in one of the two studied years. The genotyping of the collection using a DNA marker for the Pdh1 gene, a major gene for PD, revealed that 244 accessions had the homozygous R (resistant) allele, 14 had the homozygous S (susceptible) allele, and 15 accessions showed heterozygosity. To identify additional quantitative trait loci (QTLs), we applied an association mapping study using a 6K SNP Illumina iSelect array. The results suggested that in addition to major QTL on chromosome 16, linked to the physical location of Pdh1, two minor QTLs were identified on chromosomes 10 and 13. Both minor QTLs for PD were associated with calmodulin-binding protein, which presumably plays an important role in regulating PD in dry areas. Thus, the current study provided additional insight into PD regulation in soybean. The identified QTLs for PD can be efficiently employed in breeding for high-yield soybean cultivars.

Causal association of sex hormone-binding globulin on gestational hypertension and pre-eclampsia: a two-sample Mendelian randomization study.

OBJECTIVES: Pre-eclampsia (PE) and gestational hypertension (GH) are two different categories of hypertensive disorders of pregnancy. Given earlier observational research, the relationship between sex hormone-binding globulin (SHBG) and a higher risk of GH/PE is still up for dispute. Hence, the present investigation aimed to examine the possible link between SHBG and the likelihood of GH/PE. METHODS: As a first stage, single nucleotide polymorphisms from summary-level genome-wide association studies were tightly screened using quality-control techniques. Afterward, we utilized a two-sample Mendelian randomization (MR) study to examine the causal impact of SHBG on the likelihood of GH/PE. There was no indication of a relationship between blood SHBG level (n = 214,989) and GH/PE (1864 cases and 461,069 controls) in the initial study. Consensus results were obtained from the replicated analysis, which utilized MR estimates based on serum SHBG level(n = 214,989) for GH (4255 cases and 114,735 controls). RESULTS: The findings did not indicate any proof of a cause-and-effect connection between SHBG and the likelihood of GH/PE (odds ratio [OR] = 0.99, 95% confidence interval [CI] = 0.999 - 1.00, p = .34). Replicate analysis also revealed similar patterns (OR = 0.92, 95%CI = 0.82-1.05, p = .21). The above findings were demonstrated to have a strong level of robustness. CONCLUSIONS: The findings of this research did not offer definitive proof to endorse the idea that SHBG has a direct causal impact on the likelihood of GH/PE, which goes against numerous widely accepted observational studies. To ascertain the potential processes behind the relationships seen in observational studies, more investigation is needed.

Identification of Sweetness Preference-Related Single-Nucleotide Polymorphisms for Polygenic Risk Scores Associated with Obesity.

Our study aimed to identify sweetness preference-associated single-nucleotide polymorphisms (SNPs), characterize the related genetic loci, and develop SNP-based polygenic risk scores (PRS) to analyze their associations with obesity. For genotyping, we utilized a pooled genome-wide association study (GWAS) dataset of 18,499 females and 10,878 males. We conducted genome-wide association analyses, functional annotation, and employed the weighted method to calculate the levels of PRS from 677 sweetness preference-related SNPs. We used Cox proportional hazards modeling with time-varying covariates to estimate age-adjusted and multivariable hazard ratios (HRs) and 95% confidence intervals (CIs) for obesity incidence. We also tested the correlation between PRS and environmental factors, including smoking and dietary components, on obesity. Our results showed that in males, the TT genotype of rs4861982 significantly increased obesity risk compared to the GG genotype in the Health Professionals Follow-up Study (HPFS) cohort (HR = 1.565; 95% CI, 1.122-2.184; p = 0.008) and in the pooled analysis (HR = 1.259; 95% CI, 1.030-1.540; p = 0.025). Protein tyrosine phosphatase receptor type O (PTPRO) was identified as strongly associated with sweetness preference, indicating a positive correlation between sweetness preference and obesity risk. Moreover, each 10 pack-year increment in smoking was significantly associated with an increased risk of obesity in the HPFS cohort (HR = 1.024; 95% CI, 1.000-1.048) in males but not in females. In conclusion, significant associations between rs4861982, sweetness preference, and obesity were identified, particularly among males, where environmental factors like smoking are also correlated with obesity risk.

Phenome-Wide Association Study of Latent Autoimmune Diabetes from a Southern Mexican Population Implicates rs7305229 with Plasmatic Anti-Glutamic Acid Decarboxylase Autoantibody (GADA) Levels.

Latent autoimmune diabetes in adults (LADA) is characterized by the presence of glutamate decarboxylase autoantibodies (GADA). LADA has intermediate features between type 1 diabetes and type 2 diabetes. In addition, genetic risk factors for both types of diabetes are present in LADA. Nonetheless, evidence about the genetics of LADA in non-European populations is scarce. This study aims to perform a genome-wide association study with a phenome-wide association study of LADA in a southeastern Mexican population. We included 59 patients diagnosed with LADA from a previous study and 3121 individuals without diabetes from the MxGDAR/ENCODAT database. We utilized the GENESIS package in R to perform the genome-wide association study (GWAS) of LADA and PLINK for the phenome-wide association study (PheWAS) of LADA features. Nine polymorphisms reach the nominal association level (1 × 10-5) in the GWAS. The PheWAS showed that rs7305229 is genome-wide and associated with serum GADA levels in our sample (p = 1.84 × 10-8). rs7305229 is located downstream of the FAIM2 gene; previous reports associate FAIM2 variants with childhood obesity, body mass index, body adiposity measures, lymphocyte CD8+ activity, and anti-thyroid peroxidase antibodies. Our findings reveal that rs7305229 affects the GADA levels in patients with LADA from southeastern Mexico. More studies are needed to determine if this risk genotype exists in other populations with LADA.

Association and causality between diabetes and activin A: a two-sample Mendelian randomization study.

Activin A, a cytokine belonging to the transforming growth factor-beta (TGF-ß) superfamily, mediates a multifunctional signaling pathway that is essential for embryonic development, cell differentiation, metabolic regulation, and physiological equilibrium. Biomedical research using diabetes-based model organisms and cellular cultures reports evidence of different activin A levels between diabetic and control groups. Activin A is highly conserved across species and universally expressed among disparate tissues. A systematic review of published literatures on human populations reveals association of plasma activin A levels with diabetic patients in some (7) but not in others (5) of the studies. With summarized data from publicly available genome-wide association studies (GWASs), a two-sample Mendelian randomization (TSMR) analysis is conducted on the causality between the exposure and the outcome. Wald ratio estimates from single instruments are predominantly non-significant. In contrast to positive controls between diabetes and plasma cholesterol levels, inverse-variance-weighted (IVW), Egger, weighted median, and weighted mode MR methods all lead to no observed causal link between diabetes (type 1 and type 2) and plasma activin A levels. Unavailability of strong instruments prevents the reversal MR analysis of activin A on diabetes. In summary, further research is needed to confirm or deny the potential association between diabetes and plasma activin A, and to elucidate the temporal incidence of these traits in human populations. At this stage, no causality has been found between diabetes and plasma activin A based on TSMR analysis.