Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

The GWAS candidate far upstream element binding protein 3 (FUBP3) is required for normal skeletal growth, and adult bone mass and strength in mice

Bone mineral density (BMD) and height are highly heritable traits for which hundreds of genetic loci have been linked through genome wide association studies (GWAS). FUBP3 is a DNA and RNA binding protein best characterised as a transcriptional regulator of c-Myc, but little is known about its role in vivo. Single nucleotide polymorphisms in FUBP3 at the 9q34.11 locus have been associated with BMD, fracture and height in multiple GWAS, but FUBP3 has no previously established role in the skeleton. We analysed Fubp3-deficient mice to determine the consequence of FUBP3 deficiency in vivo. Mice lacking Fubp3 had reduced survival to adulthood and impaired skeletal growth. Bone mass was decreased, most strikingly in the vertebrae, with altered trabecular micro-architecture. Fubp3 deficient bones were also weak. These data provide the first functional demonstration that Fubp3 is required for normal skeletal growth and development and maintenance of adult bone structure and strength, indicating that FUBP3 contributes to the GWAS association of 9q34.11 with variation in height, BMD and fracture.

Causal relationship between metabolic dysfunction-associated fatty liver disease and endotoxin biomarkers: A Mendelian randomization study

Although the relationship among lipopolysaccharides (LPS), LPS-binding proteins, and metabolic dysfunction-associated fatty liver disease (MAFLD) is widely studied, no conclusive evidence is available. In this study, we used mendelian randomization (MR) to study the causal relationship of LPS, LPS-binding proteins, and MAFLD. Using bidirectional two-sample MR method, we evaluated data from the genome wide association study; for this analysis, nonalcoholic fatty liver disease (NAFLD), liver fat percentage, and other metabolic syndromes were employed as outcomes. Furthermore, MR analysis mainly involved the inverse variance weighted method. Heterogeneity and pleiotropy tests were also conducted. LPS was found to have a causal relationship with NAFLD, obesity, high density lipoprotein cholesterol, and TG levels. Furthermore, TG levels and LBP had significant causal relationships. This study mainly concluded that LPS is a risk factor for NAFLD, obesity, high density lipoprotein cholesterol, and TG, corroborating it's the LPS role in MAFLD pathogenesis. Hence, optimizing the gut microbiota using proper diet, probiotics, or fecal microbiota transplantation may help to reduce inflammation and (IR), thereby improving lipid and glucose metabolism disorders. Although a causal relationship between TG and LBP was observed, further studies are required to determine a specific mechanism.

Glucose-dependent insulinotropic polypeptide (GIP)

BACKGROUND

Glucose-dependent insulinotropic polypeptide (GIP) was the first incretin identified and plays an essential role in the maintenance of glucose tolerance in healthy humans. Until recently GIP had not been developed as a therapeutic and thus has been overshadowed by the other incretin, glucagon-like peptide 1 (GLP-1), which is the basis for several successful drugs to treat diabetes and obesity. However, there has been a rekindling of interest in GIP biology in recent years, in great part due to pharmacology demonstrating that both GIPR agonism and antagonism may be beneficial in treating obesity and diabetes. This apparent paradox has reinvigorated the field, led to new lines of investigation, and deeper understanding of GIP.

SCOPE OF REVIEW

In this review, we provide a detailed overview on the multifaceted nature of GIP biology and discuss the therapeutic implications of GIPR signal modification on various diseases.

MAJOR CONCLUSIONS

Following its classification as an incretin hormone, GIP has emerged as a pleiotropic hormone with a variety of metabolic effects outside the endocrine pancreas. The numerous beneficial effects of GIPR signal modification render the peptide an interesting candidate for the development of pharmacotherapies to treat obesity, diabetes, drug-induced nausea and both bone and neurodegenerative disorders.

Novel Genetic Risk Variants Associated with Oral Tongue Squamous Cell Carcinoma

PURPOSE

Limited data from genome-wide association studies (GWAS) focusing on oral tongue squamous cell carcinoma (OTSCC) are available. The present study was conducted to explore genetic associations for OTSCC.

METHODS

A GWAS on 376 cases of OTSCC was conducted using the FinnGen Data Freeze-12 dataset. The case-cohort included 205 males and 171 females. Cases with malignancies involving the base of the tongue or lingual tonsil were excluded from the case-cohort. Individuals with no recorded history of malignancy were used as controls (n = 407,067). A Phenome-wide association study (PheWAS) was performed for the lead variants to assess their co-associations with other cancers.

RESULTS

GWAS analysis identified three genome-wide significant loci associated with OTSCC (p < 5 × 10-8), located at 5p15.33 (rs27067 near gene LINC01511), 10q24 (rs1007771191 near RPS3AP36), and 20p12.3 (rs1438070080 near PLCB1), respectively. PheWAS showed associations of rs27067 mainly with prostate cancer (OR = 1.06, p = 5.41 × 10-7), and seborrheic keratosis (OR = 1.11, p = 1.51 × 10-11). A co-directional effect with melanoma was also observed (OR = 0.93, p = 6.24 × 10-5).

CONCLUSION

The GWAS detected two novel genetic associations with OTSCC. Further research is needed to identify the genes at these loci that contribute to the molecular pathogenesis of OTSCC.

Whole genome sequencing analysis of body mass index identifies novel African ancestry-specific risk allele

Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals (P < 5 × 10-9), including two secondary signals. Notably, we identified and replicated a novel low-frequency single nucleotide polymorphism (SNP) in MTMR3 that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the POC5 and DMD loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine.

THE CAUSAL ASSOCIATION OF CARDIOMETABOLIC DISEASES AND SEPSIS-RELATED OUTCOMES: A MENDELIAN RANDOMIZATION AND POPULATION STUDY

ABSTRACT

Objective: The causality between cardiometabolic disease (CMD) and sepsis has remained largely unknown. To elucidate this, we conducted a Mendelian randomization (MR) and population study. Methods: First, we used univariable and multivariable MR analyses to investigate causal associations between CMD and sepsis-related outcomes. We obtained genome-wide association study summary from both the MRC Integrative Epidemiology Unit and the FinnGen consortium. Subsequently, a two-step mediation MR analysis was performed to explore mediators. Afterward, we conducted an observational study using the Medical Information Mart for Intensive Care IV database, in which multivariable logistic regression models were utilized to examine the relationship between CMD and sepsis-related outcomes. Results: In the MR study, type 2 diabetes mellitus (OR = 1.058, 95% CI = 1.017-1.100, P = 0.005), obesity (OR = 1.113, 95% CI = 1.057-1.172, P < 0.001), and heart failure (HF) (OR = 1.178, 95% CI = 1.063-1.305, P = 0.002) were independently causally related to sepsis. Obesity (OR = 1.215, 95% CI = 1.027-1.437, P = 0.023) and HF (OR = 1.494, 95% CI = 1.080-2.065, P = 0.015) also showed independent causal associations with sepsis critical care admission. Mediation MR analysis identified 23 blood metabolites potentially causally linked to sepsis ( P < 0.05), yet none mediated the relationship between CMD and sepsis. In the observational study, we found associations between sepsis and several conditions including type 2 diabetes mellitus, obesity, hypertension, stroke, HF, and hyperlipidemia after adjusting for confounding factors. Moreover, hypertension, stroke, HF, coronary artery disease, and hyperlipidemia were linked to sepsis critical care admission. Conclusion: This study has, for the first time, revealed indicative evidence of a causal relationship between CMD and sepsis through observational and genetic evidence. Taken together, clinical attention to sepsis may be warranted among patients with CMD.

Interaction between genetic risk score and dietary carbohydrate intake on high-density lipoprotein cholesterol levels: Findings from the study of obesity, nutrition, genes and social factors (SONGS)

BACKGROUND & AIMS

Cardiometabolic traits are complex interrelated traits that result from a combination of genetic and lifestyle factors. This study aimed to assess the interaction between genetic variants and dietary macronutrient intake on cardiometabolic traits [body mass index, waist circumference, total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, triacylglycerol, systolic blood pressure, diastolic blood pressure, fasting serum glucose, fasting serum insulin, and glycated haemoglobin].

METHODS

This cross-sectional study consisted of 468 urban young adults aged 20 ± 1 years, and it was conducted as part of the Study of Obesity, Nutrition, Genes and Social factors (SONGS) project, a sub-study of the Young Lives study. Thirty-nine single nucleotide polymorphisms (SNPs) known to be associated with cardiometabolic traits at a genome-wide significance level (P < 5 × 10-8) were used to construct a genetic risk score (GRS).

RESULTS

There were no significant associations between the GRS and any of the cardiometabolic traits. However, a significant interaction was observed between the GRS and carbohydrate intake on HDL-C concentration (Pinteraction = 0.0007). In the first tertile of carbohydrate intake (≤327 g/day), participants with a high GRS (>37 risk alleles) had a higher concentration of HDL-C than those with a low GRS (≤37 risk alleles) [Beta = 0.06 mmol/L, 95 % confidence interval (CI), 0.01-0.10; P = 0.018]. In the third tertile of carbohydrate intake (>452 g/day), participants with a high GRS had a lower concentration of HDL-C than those with a low GRS (Beta = -0.04 mmol/L, 95 % CI -0.01 to -0.09; P = 0.027). A significant interaction was also observed between the GRS and glycaemic load (GL) on the concentration of HDL-C (Pinteraction = 0.002). For participants with a high GRS, there were lower concentrations of HDL-C across tertiles of GL (Ptrend = 0.017). There was no significant interaction between the GRS and glycaemic index on the concentration of HDL-C, and none of the other GRS∗macronutrient interactions were significant.

CONCLUSIONS

Our results suggest that young adults who consume a higher carbohydrate diet and have a higher GRS have a lower HDL-C concentration, which in turn is linked to cardiovascular diseases, and indicate that personalised nutrition strategies targeting a reduction in carbohydrate intake might be beneficial for these individuals.

Cell-free DNA from clinical testing as a resource of population genetic analysis

As a noninvasive biomarker, cell-free DNA (cfDNA) has achieved remarkable success in clinical applications. Notably, cfDNA is essentially DNA, and conducting whole-genome sequencing (WGS) can yield a wealth of genetic information. These invaluable data should not be confined to one-time use; instead, they should be leveraged for more comprehensive population genetic analysis, including genetic variation spectrum, population structure and genetic selection, and genome-wide association studies (GWASs), among others. Such research findings can, in turn, facilitate clinical practice, enabling more advanced and accurate disease predictions. This review explores the advantages, challenges, and current research areas of cfDNA in population genetics. We hope that this review can serve as a new chapter in the repurposing of cfDNA sequence data generated from clinical testing in population genetics.

Establishing the relationships between obesity and genetically predicted serum micronutrient levels: a multivariable Mendelian randomization analysis

BACKGROUND

Previous observational studies have indicated that circulating micronutrients may influence obesity risk. This study aimed to explore the causal relationship between micronutrient levels and obesity through multivariable Mendelian randomization (MR) analysis.

METHODS

Single nucleotide polymorphisms (SNPs) significantly associated with 15 micronutrients (selenium, zinc, copper, calcium, beta-carotene, folate, iron, magnesium, potassium, and vitamins A, B6, B12, C, D, and E) from published genome-wide association studies (GWAS) were used as instrumental variables (IVs). Three obesity-related datasets were obtained from the GWAS. Inverse variance weighted (IVW) is the main method used for MR analysis. Leave-one-out analysis, MR-Pleiotropy Residual Sum and Outlier method (MR-PRESSO), weighted median, and MR-Egger method were used to assess pleiotropy and heterogeneity.

RESULTS

Genetically predicted levels of circulating selenium and calcium are causally related to the risk of obesity (calcium odds ratio [OR]: 1.478, 95% confidence interval [CI] 1.128-1.935, p = 0.005; selenium OR: 1.478, 95% CI 1.128-1.935, p = 0.005). Multivariate MR analysis suggested a causal relationship between circulating selenium and calcium levels and obesity risk (calcium OR: 1.625, 95% CI 1.260-2.097; selenium OR: 1.080, 95% CI 1.003-1.163, p = 0.041). The p-value obtained in the Cochrane Q test, MR-Egger intercept test, and MR-PRESSO were > 0.05, suggesting no significant evidence of pleiotropy or heterogeneity.

CONCLUSION

Our study revealed, for the first time, a positive correlation between elevated circulating calcium and selenium levels and an increased obesity risk. These findings provide valuable insights into obesity's underlying mechanisms. Nevertheless, further large-scale clinical studies are required to confirm our results.

LEVEL OF EVIDENCE

Level III, Mendelian randomization.

Identification of a new genetic locus associated with atrial fibrillation in the Taiwanese population by genome-wide and transcriptome-wide association studies

AIMS

Genome-wide association studies (GWASs) identified common single-nucleotide polymorphisms (SNPs) in more than 100 genomic regions associated with atrial fibrillation (AF). We aimed to identify novel AF genes in Taiwanese population by multi-stage GWAS.

METHODS AND RESULTS

In exploratory stage, we did GWAS with whole-genome genotypes (4 512 191 SNPs) in 516 patients with AF from the National Taiwan University AF Registry and 5160 normal sinus rhythm controls from the Taiwan Biobank. Significant loci were replicated in 1002 independent patients and 2003 controls and in the UK Biobank. Expression quantitative trait locus (eQTL) mapping and transcriptome-wide association study (TWAS) were performed to implicate functional significance. Stage I GWAS revealed three loci associated with AF with a genome-wide significance level, including one close to PITX2 gene (chromosome 4q25, rs2723329, minor allele frequency [MAF] 0.50 vs. 0.41, P = 1.53 × 10-10), another close to RAP1A gene (also to previous KCND3; chromosome 1p13.2, rs7525578, MAF 0.17 vs. 0.07, P = 1.24 × 10-26), and one novel locus close to HNF4G gene (chromosome 8q21.13, rs2980218, MAF 0.44 vs. 0.35, P = 2.19 × 10-9). They were validated in Stage II population. The eQTL analyses showed significant colocalization of 1p13.2 locus with RAP1A gene expression in fibroblasts and 8q21.13 locus with HNF4G expression in lymphocytes. There is a significant association of RAP1A gene expression in fibroblasts and HNF4G in lymphocytes and brain with AF in TWAS.

CONCLUSION

Genome-wide association study in Taiwan revealed PITX2 and RAP1A/KCND3 loci and novel AF locus (HNF4G) with the most significant locus in the RAP1A locus. RAP1A and HNF4G genes may implicate fibrosis, metabolic, and neurogenic pathways in pathogenesis of AF.

Integrative proteomic and lipidomic analysis of GNB1 and SCARB2 knockdown in human subcutaneous adipocytes

Obesity, a global public health concern, is influenced by various factors, including genetic predispositions. Although many obesity-associated genes have been identified through genome-wide association studies (GWAS), the molecular mechanisms linking these genes to adipose tissue function remain largely unexplored. This study integrates proteomic data on adipocyte fat accumulation with GWAS data on obesity to unravel the roles of the identified key candidate genes - G protein subunit beta 1 (GNB1) and scavenger receptor class B member 2 (SCARB2) - involved in fat accumulation. We utilized RNA interference to knock down GNB1 and SCARB2 in human subcutaneous adipocytes, followed by lipidome and proteome analyses using mass spectrometry. Knockdown of these genes resulted in a reduction in lipid droplet accumulation, indicating their role in adipocyte lipid storage. Digital PCR confirmed effective gene knockdown, with GNB1 and SCARB2 mRNA levels significantly reduced. In total, the lipidomic analysis identified 96 lipid species with significant alterations. GNB1 knockdown resulted in a decrease in cholesterol esters and an increase in phosphatidylcholines, phosphatidylinositols, and ceramides. SCARB2 knockdown also led to an increase in phosphatidylcholines, with a trend towards decreased triacylglycerols. Proteomic analysis revealed significant changes in proteins involved in lipid metabolism and adipocyte function, including PLPP1 and CDH13, which were upregulated following GNB1 knockdown, and HSPA8, which was downregulated. Conversely, SCARB2 knockdown resulted in the downregulation of PLPP1 and METTL7A, and the upregulation of PLIN2, HSPA8, NPC2, and SQSTM1. Our findings highlight the significant roles of GNB1 and SCARB2 in lipid metabolism and adipocyte function, providing insights that could inform therapeutic strategies targeting these regulatory genes in obesity.

GPR139, an Ancient Receptor and an Emerging Target for Neuropsychiatric and Behavioral Disorders

GPR139 is an orphan G-protein-coupled receptor that is predominantly expressed in several midbrain regions, e.g., the habenula, striatum, and hypothalamus. GPR139 gene is highly conserved across vertebrate phylogenetic taxa, suggesting its fundamental importance in neurophysiology. Evidence from both animal studies and human genetic association studies has demonstrated that dysregulation of GPR139 expression and function is linked to aberrant behaviors, cognitive deficits, alterations in sleep and alertness, and substance abuse and withdrawal. Animal knockout models suggest that GPR139 plays an anti-opioid role by modulating the signaling activity of the μ-opioid receptor (MOR), as well as the intensity of withdrawal symptoms and nociception in behavioral paradigms. Modulation of GPR139 activity by surrogate agonists such as TAK-041 and JNJ-63533054 has shown promising results in experimental models; however, the use of TAK-041 in clinical trials has produced heterogeneous effects and has not met the intended primary endpoint. Here, we highlight current in vitro and in vivo studies of GPR139, its potential physiological roles, and therapeutic potential in the pathophysiology of neuropsychiatric and behavioral disorders. This review aims to focus on the current knowledge gaps to facilitate future studies that will contribute to the understanding of GPR139 as a therapeutic target for neuropsychiatric and behavioral disorders.

Distinct Roles of Common Genetic Variants and Their Contributions to Diabetes: MODY and Uncontrolled T2DM

Type 2 diabetes mellitus (T2DM) encompasses a range of clinical manifestations, with uncontrolled diabetes leading to progressive or irreversible damage to various organs. Numerous genes associated with monogenic diabetes, exhibiting classical patterns of inheritance (autosomal dominant or recessive), have been identified. Additionally, genes involved in complex diabetes, which interact with environmental factors to trigger the disease, have also been discovered. These genetic findings have raised hopes that genetic testing could enhance diagnostics, disease surveillance, treatment selection, and family counseling. However, the accurate interpretation of genetic data remains a significant challenge, as variants may not always be definitively classified as either benign or pathogenic. Research to date, however, indicates that periodic reevaluation of genetic variants in diabetes has led to more consistent findings, with biases being steadily eliminated. This has improved the interpretation of variants across diverse ethnicities. Clinical studies suggest that genetic risk information may motivate patients to adopt behaviors that promote the prevention or management of T2DM. Given that the clinical features of certain monogenic diabetes types overlap with T2DM, and considering the significant role of genetic variants in diabetes, healthcare providers caring for prediabetic patients should consider genetic testing as part of the diagnostic process. This review summarizes current knowledge of the most common genetic variants associated with T2DM, explores novel therapeutic targets, and discusses recent advancements in the pharmaceutical management of uncontrolled T2DM.

RNA Therapies in Cardio-Kidney-Metabolic Syndrome: Advancing Disease Management

Cardio-Kidney-Metabolic (CKM) Syndrome involves metabolic, kidney, and cardiovascular dysfunction, disproportionately affecting disadvantaged groups. Its staging (0-4) highlights the importance of early intervention. While current management targets hypertension, heart failure, dyslipidemia, and diabetes, RNA-based therapies offer innovative solutions by addressing molecular mechanisms of CKM Syndrome. Emerging RNA treatments, including antisense oligonucleotides (ASOs) and small interfering RNAs (siRNAs), show promise in slowing disease progression across CKM stages. For example, ASOs and siRNAs targeting ApoC-III and ANGPTL3 reduce triglycerides and LDL cholesterol, while siRNAs improve blood pressure control by targeting the renin-angiotensin-aldosterone system. Obesity treatments leveraging miRNAs and circRNAs tackle a key CKM risk factor. In heart failure and diabetes, RNA-based therapies improve cardiac function and glucose control, while early kidney disease trials show potential for RNAi in acute injury. Further research is essential to refine these therapies and ensure equitable access.

Genome-Wide Association Study to Identify Genetic Variants Associated With Diabetic Maculopathy

Purpose

Diabetic maculopathy (including diabetic macular edema [DME]) is the leading cause of vision loss in people with diabetes. We aimed to identify the genetic determinants of diabetic maculopathy.

Methods

We conducted a genome-wide association study (GWAS) in two cohorts with a meta-analysis. The Australian cohort comprised 551 cases of DME and 599 controls recruited from the states of South Australia and Tasmania. The Scottish cohort comprised 1951 cases of diabetic maculopathy and 6541 controls from the Genetics of Diabetes Audit and Research in Tayside Scotland study (GoDARTS). Genotyping, imputation, and association analysis using logistic regression were conducted in each cohort, before combining summary statistics in a meta-analysis using the GWAMA package.

Results

A locus on chromosome 7 reached genome-wide significance in GoDARTS but showed the opposite direction of effect in the Australian cohort. The meta-analysis identified two suggestive associations (P < 5 × 10-6) for diabetic maculopathy risk with similar effect direction; one at chromosome 1 close to the RNU5E-1 gene and one at chromosome 13 upstream of the ERICH6B gene. The two loci were evaluated in silico for potential functional links to diabetic maculopathy. Both are located in regulatory regions and have annotations indicating regulatory functions. They are also expression quantitative trait locus (eQTLs) for genes plausibly involved in diabetic maculopathy pathogenesis, with links to folate metabolism and the regulation of VEGF.

Conclusions

The study suggests several promising SNPs and genes related to diabetic maculopathy risk. Despite being the largest genetic study of diabetic maculopathy to date, larger, homogeneous cohorts will be required to identify robust genetic risk loci for the disease.

Effect of fat distribution on left ventricular structure and function in different sexes: a Mendelian randomization study

Background

Although there is an interaction between sex, body fat distribution, and cardiac structure and function, these relationships have not been fully elucidated yet. This study aims to reveal the causal relationship between genetic determinants of fat distribution pattern and function of the left ventricular structure in different sexes.

Methods

Genetic variants for waist circumference, hip circumference, waist-to-hip ratio (WHR), and body mass index (BMI) were selected from genome-wide association studies conducted in European samples. The dataset for left ventricular (LV) parameters was obtained from over 35,000 European samples in the UK Biobank Cardiovascular Magnetic Resonance sub-study. Two-sample Mendelian randomization (MR) analysis was employed to explore causal relationships.

Results

After adjusting for BMI, WHR shows a positive causal relationship with LV hypertrophy and a significant negative causal relationship with LV volume and diastolic function. In further subgroup analysis, we only found similar results in WHR among the female population (FWHR), while in the male population, there was no significant causal relationship between MWHR and LV hypertrophy and diastolic function. Additionally, in our MR analysis, no causal relationship was found between WHR and LVEF.

Conclusions

This study indicates that the fat distribution pattern has unique effects on the structure and function of the LV, and these effects vary by sex. This study provides evidence for a causal relationship between fat distribution and LV structure and function across both sexes.

Phenome-Wide Investigation of the Causal Associations Between Pre-Pregnancy Obesity Traits and Gestational Diabetes: A Two-Sample Mendelian Randomization Analyses

Pre-pregnancy obesity was associated with gestational diabetes in observational studies, but whether this relationship is causal remains to be determined. To evaluate whether pre-pregnancy obesity traits causally affect gestational diabetes risk, a two-sample Mendelian randomization (MR) analysis was performed utilizing summary-level statistics from published genome-wide association studies (GWAS). Obesity-related traits included body mass index (BMI), overweight, obesity, obesity class 1, obesity class 2, obesity class 3, childhood obesity, waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), percent liver fat, visceral adipose tissue volume, abdominal subcutaneous adipose tissue volume. Effect estimates were evaluated using the inverse-variance weighting method. Weighted median, MR-Egger, simple mode, and weighted mode were performed as sensitivity analyses. Genetically predicted pre-pregnancy BMI [odds ratio (OR) = 1.68; 95% confidence interval (CI): 1.45-1.95; P = 9.13 × 10-12], overweight (OR = 1.49; 95% CI: 1.21-1.85; P = 2.06 × 10-4), obesity (OR = 1.25; 95% CI: 1.18-1.33; P = 8.01 × 10-13), obesity class 1 (OR = 1.31; 95% CI: 1.17-1.46; P = 1.49 × 10-6), obesity class 2 (OR = 1.26; 95% CI: 1.16-1.37; P = 5.23 × 10-8), childhood obesity (OR = 1.33; 95% CI: 1.23-1.44; P = 4.06 × 10-12), and WHR (OR = 2.35; 95% CI: 1.44-3.83; P = 5.89 × 10-4) were associated with increased risk of gestational diabetes. No significant association was observed with obesity class 3, WC, HC, percent liver fat, visceral adipose tissue volume, or abdominal subcutaneous adipose tissue volume. Similar results were observed in sensitivity analyses. Therefore, genetically predicted pre-pregnancy obesity traits may increase the risk of gestational diabetes. Weight control before pregnancy may be beneficial to prevent gestational diabetes.

Casual correlation between overweight, obesity, and severe COVID-19 infection with respiratory failure: A two-sample Mendelian randomization

This study aimed to detect the causal association of overweight and obesity on severe COVID-19 infection with respiratory failure through a two-sample Mendelian randomization (MR) method based on the genome-wide association studies datasets. All genome-wide association studies summary data of exposures and outcome used in this study were obtained from the IEU database derived from Europeans. The study mainly used the inverse variance weighted method to test causal relationship. Simultaneously, MR-PRESSO and MR-EGGER were used to detect the pleiotropy, and sensitivity analysis was performed using leave-one-out analysis. In the inverse variance weighted analyses, we found no causal association between obesity (e.g., OR = 1.15, 95% CIs = 0.96-1.37, P = .13 for obesity-ebi-a-GCST90000255), obesity subtypes (e.g., OR = 1.93, 95% CIs = 0.90-4.14, P = .10 for obesity and other hyperalimentation) as well as overweight (OR = 0.90, 95% CIs = 0.64-1.27, P = .54) and severe COVID-19 infection with respiratory failure. The findings showed no causal association between obesity or overweight and severe COVID-19 infection with respiratory failure. Further validation is needed regarding whether obesity or overweight is a risk factor for it.

Exploring risk factors for endocrine-related immune-related adverse events: Insights from meta-analysis and Mendelian randomization

This study utilized meta-analysis and Mendelian randomization (MR) to identify risk factors for endocrine-related immune-related adverse events (EirAEs) and to ascertain whether EirAEs confer better prognosis of immunotherapy. The meta-analysis identified several risk factors for EirAEs, including elevated baseline TSH (OR = 1.30, 95% CI 1.10-1.53), positive TgAb (OR = 14.23, p < .001), positive TPOAb (OR = 3.75, p < .001), prior thyroid-related medical history (OR = 4.19), increased BMI (OR = 1.11), combination immune checkpoint inhibitors (ICIs) therapy with targeted treatment (OR = 2.71, 95% CI 2.11-3.47), and dual ICI therapy (OR = 3.26, 95% CI 2.22-4.79). MR analysis further supported causalities between extreme BMI, hypothyroidism, and irAEs from a genetic perspective. In addition, cancer patients who experienced EirAEs exhibited significantly prolonged PFS (HR = 0.84, 95% CI 0.73-0.97) and OS (HR = 0.59, 95% CI 0.45-0.76) compared to those without. These findings provide valuable insights for clinical decision-making among healthcare professionals and offer direction for future research in this field.

Exome-wide comparative analyses revealed differentiating genomic regions for performance traits in Indian native buffaloes

In India, 20 breeds of buffalo have been identified and registered, yet limited studies have been conducted to explore the performance potential of these breeds, especially in the Indian native breeds. This study is a maiden attempt to delineate the important variants and unique genes through exome sequencing for milk yield, milk composition, fertility, and adaptation traits in Indian local breeds of buffalo. In the present study, whole exome sequencing was performed on Chhattisgarhi (n = 3), Chilika (n = 4), Gojri (n = 3), and Murrah (n = 4) buffalo breeds and after stringent quality control, 4333, 6829, 4130, and 4854 InDels were revealed, respectively. Exome-wide FST along 100-kb sliding windows detected 27, 98, 38, and 35 outlier windows in Chhattisgarhi, Chilika, Gojri, and Murrah, respectively. The comparative exome analysis of InDels and subsequent gene ontology revealed unique breed specific genes for milk yield (CAMSAP3), milk composition (CLCN1, NUDT3), fertility (PTGER3) and adaptation (KCNA3, TH) traits. Study provides insight into mechanism of how these breeds have evolved under natural selection, the impact of these events on their respective genomes, and their importance in maintaining purity of these breeds for the traits under study. Additionally, this result will underwrite to the genetic acquaintance of these breeds for breeding application, and in understanding of evolution of these Indian local breeds.

Relationships of dietary habits with prostate cancer risk: results from Mendelian randomization analyses and the National Health and Nutrition Examination Survey

Background: Prior investigations identified correlations between dietary habits and the risk of prostate cancer (PCa); however, the causative dynamics are unclear. Methods: Utilizing the Mendelian randomization (MR) framework, we investigated the causal links between dietary habits, daily nutrient intakes, and risk of PCa (79 148 cases and 61 106 controls). Exposure and outcome data were obtained from the UK Biobank and the Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome (PRACTICAL) consortium, respectively. Univariable and multivariable MR analyses were employed. Sensitivity analyses were performed to detect outliers, evaluate heterogeneity, and discern potential pleiotropic effects. Utilizing data from the National Health and Nutrition Examination Survey (NHANES) database (2009-2010), we selected 1294 and 1778 men aged ≥40 years from a pool of 10 537 participants, ensuring no missing information. Regression analyses examined the associations between leafy/lettuce salad intake, daily nutrient intake, and the odds of PCa. Results: Univariable MR (UVMR) analysis reveals that the intake of pork and salad/raw vegetable correlated with an elevated PCa risk. Subsequent to confounder adjustment via multivariable MR (MVMR) analysis, a causal link was established between salad/raw vegetable intake and an increased risk of PCa (odds ratio [OR]: 1.658, 95% confidence interval [95% CI]: 1.037-2.644, P = 0.046). The analysis based on NHANES datasets demonstrated a link between leafy/lettuce salad intake and heightened odds of PCa (OR: 1.025, 95% CI: 1.003-1.049, P = 0.038). Increased daily intakes of β-carotene (original OR: 1.00006, 95% CI: 1.00001-1.00011, P = 0.024) and vitamin B1 (OR: 1.474, 95% CI: 1.104-1.967, P = 0.014) were associated with a higher likelihood of PCa. Conclusions: These MR analyses substantiate the causal nexus between salad/raw vegetable intake and PCa risk. Similarly, leafy/lettuce salad intake and the odds of PCa were significantly correlated in the cross-sectional observational study. Moreover, higher daily intakes of β-carotene and vitamin B1 were linked to an increased likelihood of PCa. These findings provide practical dietary recommendations for PCa prevention and enhance early identification and diagnosis.

A proteomics approach to study mouse long bones: examining baseline differences and mechanical loading-induced bone formation in young-adult and old mice

With aging, bone mass declines and the anabolic effects of skeletal loading diminish. While much research has focused on gene transcription, how bone ages and loses its mechanoresponsiveness at the protein level remains unclear. We developed a novel proteomics approach and performed a paired mass spectrometry and RNA-seq analysis on tibias from young-adult (5-month) and old (22-month) mice. We report the first correlation estimate between the bone proteome and transcriptome (Spearman ρ = 0.40), which is in line with other tissues but indicates that a relatively low amount of variation in protein levels is explained by the variation in transcript levels. Of 71 shared targets that differed with age, eight were associated with bone mineral density in previous GWAS, including understudied targets Asrgl1 and Timp2. We used complementary RNA in situ hybridization to confirm that Asrgl1 and Timp2 had reduced expression in osteoblasts/osteocytes in old bones. We also found evidence for reduced TGF-beta signaling with aging, in particular Tgfb2. Next, we defined proteomic changes following mechanical loading. At the protein level, bone differed more with age than with loading, and aged bone had fewer loading-induced changes. Overall, our findings underscore the need for complementary protein-level assays in skeletal biology research.

Tirzepatide, GIP(1-42) and GIP(1-30) display unique signaling profiles at two common GIP receptor variants, E354 and Q354

Type 2 diabetes (T2D) and obesity are prevalent metabolic disorders affecting millions of individuals worldwide. A new effective therapeutic drug called tirzepatide for the treatment of obesity and T2D is a dual agonist of the GIP receptor and GLP-1 receptor. Tirzepatide is clinically more effective than GLP-1 receptor agonists but the reasons why are not well understood. Tirzepatide reportedly stimulates the GIP receptor more potently than the GLP-1 receptor. However, tirzepatide signaling has not been thoroughly investigated at the E354 (wildtype) or Q354 (E354Q) GIP receptor variants. The E354Q variant is associated increased risk of T2D and lower body mass index. To better understand GIP receptor signaling we characterized the activity of endogenous agonists and tirzepatide at both GIP receptor variants. Using Cos7 cells we examined wildtype and E354Q GIP receptor signaling, analyzing cAMP and IP1 accumulation as well as AKT, ERK1/2 and CREB phosphorylation. GIP(1-42) and GIP(1-30)NH2 displayed equipotent effects on these pathways excluding CREB phosphorylation where GIP(1-30)NH2 was more potent than GIP(1-42) at the E354Q GIP receptor. Tirzepatide favored cAMP signaling at both variants. These findings indicate that tirzepatide is a biased agonist towards Gαs signaling and suggests it equally activates the wildtype and E354Q GIP receptor variants. We also observed differences between the pharmacology of the GIP receptor variants with endogenous peptides, which may help to explain differences in phenotype. These findings contribute to a comprehensive understanding of GIP receptor signaling, and will aid development of therapies combating T2D and obesity.

Joint testing of rare variant burden scores using non-negative least squares

Gene-based burden tests are a popular and powerful approach for analysis of exome-wide association studies. These approaches combine sets of variants within a gene into a single burden score that is then tested for association. Typically, a range of burden scores are calculated and tested across a range of annotation classes and frequency bins. Correlation between these tests can complicate the multiple testing correction and hamper interpretation of the results. We introduce a method called the sparse burden association test (SBAT) that tests the joint set of burden scores under the assumption that causal burden scores act in the same effect direction. The method simultaneously assesses the significance of the model fit and selects the set of burden scores that best explain the association at the same time. Using simulated data, we show that the method is well calibrated and highlight scenarios where the test outperforms existing gene-based tests. We apply the method to 73 quantitative traits from the UK Biobank, showing that SBAT is a valuable additional gene-based test when combined with other existing approaches. This test is implemented in the REGENIE software.

Relation Between Obesity and Type 2 Diabetes: Evolutionary Insights, Perspectives and Controversies

PURPOSE OF REVIEW

Since the mid-twentieth century, obesity and its related comorbidities, notably insulin resistance (IR) and type 2 diabetes (T2D), have surged. Nevertheless, their underlying mechanisms remain elusive. Evolutionary medicine (EM) sheds light on these issues by examining how evolutionary processes shape traits and diseases, offering insights for medical practice. This review summarizes the pathogenesis and genetics of obesity-related IR and T2D. Subsequently, delving into their evolutionary connections. Addressing limitations and proposing future research directions aims to enhance our understanding of these conditions, paving the way for improved treatments and prevention strategies.

RECENT FINDINGS

Several evolutionary hypotheses have been proposed to unmask the origin of obesity-related IR and T2D, e.g., the "thrifty genotype" hypothesis suggests that certain "thrifty genes" that helped hunter-gatherer populations efficiently store energy as fat during feast-famine cycles are now maladaptive in our modern obesogenic environment. The "drifty genotype" theory suggests that if thrifty genes were advantageous, they would have spread widely, but proposes genetic drift instead. The "behavioral switch" and "carnivore connection" hypotheses propose insulin resistance as an adaptation for a brain-dependent, low-carbohydrate lifestyle. The thrifty phenotype theory suggests various metabolic outcomes shaped by genes and environment during development. However, the majority of these hypotheses lack experimental validation. Understanding why ancestral advantages now predispose us to diseases may aid in drug development and prevention of disease. EM helps us to understand the evolutionary relation between obesity-related IR and T2D. But still gaps and contradictions persist. Further interdisciplinary research is required to elucidate complete mechanisms.

Reduced Mn uptake of pleiotropic ZIP8 SNP is caused by its loss of Mn-responsive accumulation on the cell-surface

Zrt/Irt-like protein 8 (ZIP8), which is a Zn transporter, plays a pivotal role as a Mn transporter. Recent studies have shown that a ZIP8 SNP (rs13107325 C→T, A391T) is associated with multiple diseases, likely by causing systemic Mn deficiency. However, the underlying molecular mechanisms remain unclear. We attempted to address this issue in cell-based experiments using Madin-Darby canine kidney cells stably expressing ZIP8 WT or the A391T SNP mutant under the control of the Tet-regulatable promoter. We showed that the A391T mutant lost the property of Mn-responsive accumulation on the cell surface, which was observed in WT ZIP8. We also showed that the loss of Mn-responsive accumulation of A391T mutant was associated with its reduced Mn uptake, compared with WT ZIP8, in the Mn uptake assay using the radioisotope 54Mn. Our results potentially explain how the ZIP8 A391T substitution is associated with disease pathogenesis caused by Mn deficiency.

Relationship between serum vitamin C and serum uric acid in people with different BMIs: results from the NHANES 2017-2018 and Mendelian randomization study

Objective

To examine the association of overweight/obesity and serum vitamin C (serum VC) with serum uric acid (SUA) and to assess causality using Mendelian randomization (MR).

Methods

4,772 participants from the National Health and Nutrition Examination Survey (NHANES), 2017-2018 were included in this study. Multivariate linear regression, variance inflation factor and quantile regression were used to analyze the relationships between overweight/obesity and serum VC and SUA levels. Secondly, Mendelian randomization (MR) was utilized to mitigate bias and prevent reverse causality in the observational study. Genetic variants associated with obesity (N = 13,848), vitamin C levels (N = 64,979) and serum uric acid levels (N = 343,836) were sourced from the most extensive genome-wide association studies (GWAS). The primary analytical method employed was inverse variance weighted (IVW).

Results

Based on the observational study, BMI was positively associated with SUA (β = 0.06, 95% CI: 0.05 to 0.07, p < 0.001) and serum VC was negatively associated with SUA (β = -0.14, 95% CI: -0.23 to -0.04, p = 0.005). In individuals with overweight/obesity (BMI > =25), the negative effects of serum VC on SUA enhanced with increasing serum VC. High serum VC level (Q4 level, above 1.19 mg/dL) reduced SUA (β = -0.30, 95% CI: -0.47 to -0.14, p < 0.001) in individuals with overweight/obesity compared to low serum VC level (Q1 level, below 0.54 mg/dL). IVW-MR analysis revealed a significant association between SUA levels and genetically elevated levels of VC (β = -0.03, 95% CI: -0.06 to -0.00, p = 0.029) and obesity (β = 0.06, 95% CI: 0.04 to 0.07, p < 0.001).

Conclusion

Cross-sectional observational analysis revealed that BMI exhibited a positive correlation with SUA levels and that serum VC was negatively correlated with SUA levels; moreover, moderate serum VC can reduce SUA, especially in individuals with overweight/obesity. There was evidence indicating a causal effect of VC and obesity on SUA. It highlights the importance of VC in the management of SUA levels, particularly in overweight/obese individuals. The findings might be helpful for the management of high SUA levels.

Mechanisms of action and therapeutic applications of GLP-1 and dual GIP/GLP-1 receptor agonists

Glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) are two incretins that bind to their respective receptors and activate the downstream signaling in various tissues and organs. Both GIP and GLP-1 play roles in regulating food intake by stimulating neurons in the brain's satiety center. They also stimulate insulin secretion in pancreatic β-cells, but their effects on glucagon production in pancreatic α-cells differ, with GIP having a glucagonotropic effect during hypoglycemia and GLP-1 exhibiting glucagonostatic effect during hyperglycemia. Additionally, GIP directly stimulates lipogenesis, while GLP-1 indirectly promotes lipolysis, collectively maintaining healthy adipocytes, reducing ectopic fat distribution, and increasing the production and secretion of adiponectin from adipocytes. Together, these two incretins contribute to metabolic homeostasis, preventing both hyperglycemia and hypoglycemia, mitigating dyslipidemia, and reducing the risk of cardiovascular diseases in individuals with type 2 diabetes and obesity. Several GLP-1 and dual GIP/GLP-1 receptor agonists have been developed to harness these pharmacological effects in the treatment of type 2 diabetes, with some demonstrating robust effectiveness in weight management and prevention of cardiovascular diseases. Elucidating the underlying cellular and molecular mechanisms could potentially usher in the development of new generations of incretin mimetics with enhanced efficacy and fewer adverse effects. The treatment guidelines are evolving based on clinical trial outcomes, shaping the management of metabolic and cardiovascular diseases.

Investigating grey matter volumetric trajectories through the lifespan at the individual level

Adolescents exhibit remarkable heterogeneity in the structural architecture of brain development. However, due to limited large-scale longitudinal neuroimaging studies, existing research has largely focused on population averages, and the neurobiological basis underlying individual heterogeneity remains poorly understood. Here we identify, using the IMAGEN adolescent cohort followed up over 9 years (14-23 y), three groups of adolescents characterized by distinct developmental patterns of whole-brain gray matter volume (GMV). Group 1 show continuously decreasing GMV associated with higher neurocognitive performances than the other two groups during adolescence. Group 2 exhibit a slower rate of GMV decrease and lower neurocognitive performances compared with Group 1, which was associated with epigenetic differences and greater environmental burden. Group 3 show increasing GMV and lower baseline neurocognitive performances due to a genetic variation. Using the UK Biobank, we show these differences may be attenuated in mid-to-late adulthood. Our study reveals clusters of adolescent neurodevelopment based on GMV and the potential long-term impact.

Exploring the causal relationship between body mass index and keratoconus: a Mendelian randomization study

Background

Despite reports suggesting a link between obesity and keratoconus, the causal relationship is not fully understood.

Methods

We used genome-wide association study (GWAS) data from public databases for a two-sample Mendelian randomization analysis to investigate the causal link between body mass index (BMI) and keratoconus. The primary method was inverse variance weighted (IVW), complemented by different analytical techniques and sensitivity analyses to ensure result robustness. A meta-analysis was also performed to bolster the findings' reliability.

Results

Our study identified a significant causal relationship between BMI and keratoconus. Out of 20 Mendelian randomization (MR) analyses conducted, 9 showed heterogeneity or pleiotropy. Among the 11 analyses that met all three MR assumptions, 4 demonstrated a significant causal difference between BMI and keratoconus, while the remaining 7 showed a positive trend but were not statistically significant. Meta-analysis confirmed a significant causal relationship between BMI and keratoconus.

Conclusion

There is a significant causal relationship between BMI and keratoconus, suggesting that obesity may be a risk factor for keratoconus.

Evidence of gene-nutrient interaction association with waist circumference, cross-sectional analysis

BACKGROUND AND AIMS

Waist circumference (WC) is a significant indicator of body adiposity and is associated with increased mortality and morbidity of cardiovascular diseases. Although, single nutrient intake and candidate genes were previously associated with WC. Little is known about WC association with overall diet quality, genetic risk score and gene-nutrient interaction. This study aims to investigate the influence of overall diet quality and multiple WC-associated single nucleotide polymorphisms on WC. In addition to investigating gene-nutrient interaction association with WC.

METHODS

This study explored cross-sectional data from two large sample-size studies, to provide reproducible results. As a representation of the UK population, the Airwave Health Monitoring Study (n = 6,502) and the UK-Biobank Cohort Study (n = 171,129) were explored for factors associated with WC. Diet quality was evaluated based on the Mellen Index for Dietary Approaches to Stop Hypertension (Mellen-DASH). The genetic risk score for WC (GRS-Waist) was calculated by screening the population genotype for WC-associated single nucleotide polymorphisms. Multivariate linear regression models were built to explore WC association with diet quality and genetic risk score. Gene-nutrient interaction was explored by introducing the interaction term (GRS-Waist X Mellen-DASH score) to multivariate linear regression analysis.

RESULTS

The prevalence of high WC (Female > 80 cm, Male > 94 cm) was 46.5% and 51.7% in both populations. Diet quality and genetic risk score of WC were significantly associated with WC. There was no evidence of interaction between GRS-Waist, DASH diet scores and nutrient intake on WC.

CONCLUSION

This study's findings provided reproducible results on waist circumference association with diet and genetics and tested the possibility of gene-nutrient interaction. These reproducible results are successful in building the foundation for using diet and genetics for early identification of those at risk of having high WC and WC-associated diseases. In addition, evidence on gene-diet interactions on WC is limited and lacks replication, therefore our findings may guide future research in investigating this interaction and investigating its application in precision nutrition.

Variations in the LINGO2 and GLIS3 Genes and Gene-Environment Interactions Increase Gestational Diabetes Mellitus Risk in Chinese Women

Gestational diabetes mellitus (GDM) has been found to be a common complication in pregnant women, known to escalate the risk of negative obstetric outcomes. In our study, we genotyped 1,566 Chinese pregnant women for two single nucleotide polymorphisms (SNPs) in the LINGO2 gene and one SNP in the GLIS3 gene, utilizing targeted next-generation sequencing. The impact of two interacting genes, and the interaction of genes with the environment─including exposure to particulate matter (PM2.5), ozone (O3), and variations in prepregnancy body mass index (BMI)─on the incidence of GDM were analyzed using logistic regression. Our findings identify the variants LINGO2 rs10968576 (P = 0.022, OR = 1.224) and rs1412239 (P = 0.018, OR = 1.231), as well as GLIS3 rs10814916 (P = 0.028, OR = 1.172), as risk mutations significantly linked to increased susceptibility to GDM. Further analysis underscores the crucial role of gene-gene and gene-environment interactions in the development of GDM among Chinese women (P < 0.05). Particularly, the individuals carrying the rs10968576 G-rs1412239 G-rs10814916 C haplotype exhibit increased susceptibility to GDM during the prepregnancy period when interacting with PM2.5, O3, and BMI (P = 8.004 × 10-7, OR = 1.206; P = 6.3264 × 10-11, OR = 1.280; P = 9.928 × 10-7, OR = 1.334, respectively). In conclusion, our research emphasizes the importance of the interaction between specific gene variations─LINGO2 and GLIS3─and environmental factors in influencing GDM risk. Notably, we found significant associations between these gene variations and GDM risk across various environmental exposure periods.

You are What Your Parents Expect: Height and Local Reference Points

Recent estimates are that about 150 million children under five years of age are stunted, with substantial negative consequences for their schooling, cognitive skills, health, and economic productivity. Therefore, understanding what determines such growth retardation is significant for designing public policies that aim to address this issue. We build a model for nutritional choices and health with reference-dependent preferences. Parents care about the health of their children relative to some reference population. In our empirical model, we use height as the health outcome that parents target. Reference height is an equilibrium object determined by earlier cohorts' parents' nutritional choices in the same village. We explore the exogenous variation in reference height produced by a protein-supplementation experiment in Guatemala to estimate our model's parameters. We use our model to decompose the impact of the protein intervention on height into price and reference-point effects. We find that the changes in reference points account for 65% of the height difference between two-year-old children in experimental and control villages in the sixth annual cohort born after the initiation of the intervention.

Integrating Genetic and Transcriptomic Data to Identify Genes Underlying Obesity Risk Loci

Genome-wide association studies (GWAS) have identified numerous body mass index (BMI) loci. However, most underlying mechanisms from risk locus to BMI remain unknown. Leveraging omics data through integrative analyses could provide more comprehensive views of biological pathways on BMI. We analyzed genotype and blood gene expression data in up to 5,619 samples from the Framingham Heart Study (FHS). Using 3,992 single nucleotide polymorphisms (SNPs) at 97 BMI loci and 20,692 transcripts within 1 Mb, we performed separate association analyses of transcript with BMI and SNP with transcript (PBMI and PSNP, respectively) and then a correlated meta-analysis between the full summary data sets (PMETA). We identified transcripts that met Bonferroni-corrected significance for each omic, were more significant in the correlated meta-analysis than each omic, and were at least nominally associated with BMI in FHS data. Among 308 significant SNP-transcript-BMI associations, we identified seven genes (NT5C2, GSTM3, SNAPC3, SPNS1, TMEM245, YPEL3, and ZNF646) in five association regions. Using an independent sample of blood gene expression data, we validated results for SNAPC3 and YPEL3. We tested for generalization of these associations in hypothalamus, nucleus accumbens, and liver and observed significant (PMETA<0.05 & PMETA Collapse

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Grants

• R01 HL143885 NHLBI NIH HHS
• R01 HL142302 NHLBI NIH HHS
• R01 HL151152 NHLBI NIH HHS
• HHSN268201500001I NHLBI NIH HHS
• R01 DK139598 NIDDK NIH HHS
• N01HC25195 NHLBI NIH HHS
• R01 HG010297 NHGRI NIH HHS
• HHSN268201500001C NHLBI NIH HHS
• R01 HL163262 NHLBI NIH HHS
• R01 HL092577 NHLBI NIH HHS
• P20 MD000170 NIMHD NIH HHS
• 75N92019D00031 NHLBI NIH HHS
• R01 HD057194 NICHD NIH HHS
• UL1 TR000371 NCATS NIH HHS
• R01 DK122503 NIDDK NIH HHS

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Affiliation(s)

Hanfei Xu Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
Shreyash Gupta Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Ian Dinsmore Department of Genomic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Abbey Kollu Department of Psychology and Neuroscience, University of North Carolina, 235 E. Cameron Avenue, Chapel Hill, NC, 27599, USA
Anne Marie Cawley Marsico Lung Institute, University of North Carolina, 125 Mason Farm Rd, Chapel Hill, NC, 27599, USA
Mohammad Y. Anwar Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
Hung-Hsin Chen Institute of Biomedical Sciences, Academia Sinica, No. 128, Section 2, Academia Rd., Taipei, Nangang District, 115201, Taiwan Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
Lauren E. Petty Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
Sudha Seshadri Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA Department of Neurology, School of Medicine, Boston University, 85 East Concord Street, Boston, MA, 02118, USA Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, UT Health San Antonio, 8300 Floyd Curl Drive, San Antonio, TX, 78229, USA
Misa Graff Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
Piper Below Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
Jennifer A. Brody Department of Medicine, Cardiovascular Health Research Unit, University of Washington, 1730 Minor Ave, Seattle, WA, 98101, USA
Geetha Chittoor Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Susan P. Fisher-Hoch Department of Epidemiology, School of Public Health, UT Health Houston, Regional Academic Health Center, One West University Blvd, Brownsville, TX, 78520, USA
Nancy L. Heard-Costa Framingham Heart Study, 73 Mt Wayte Ave, Framingham, MA, 01702, USA Department of Neurology, Chobanian & Avedisian School of Medicine, Boston University, 72 E Concord St, Boston, MA, 02118, USA
Daniel Levy Population Sciences Branch, National Heart, Lung, and Blood Institute of the National Institutes of Health, 6701 Rockledge Drive, Bethesda, MD, 20892, USA
Honghuang Lin Department of Medicine, University of Massachusetts Chan Medical School, 55 N Lake Ave, Worcester, MA, 01655, USA
Ruth JF. Loos Charles Bronfman Institute for Personalized Medicine at Mount Sinai, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY, 10029, USA Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3A, 2200, Copenhagen, Denmark
Joseph B. Mccormick Department of Epidemiology, School of Public Health, UT Health Houston, Regional Academic Health Center, One West University Blvd, Brownsville, TX, 78520, USA
Jerome I. Rotter Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, 1124 West Carson Street, Torrance, CA, 90502, USA
Tooraj Mirshahi Department of Genomic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Christopher D. Still Center for Obesity and Metabolic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Anita Destefano Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA Department of Neurology, School of Medicine, Boston University, 85 East Concord Street, Boston, MA, 02118, USA
L. Adrienne Cupples Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
Karen L Mohlke Department of Genetics, School of Medicine, University of North Carolina, Chapel Hill, NC, 27599, USA
Kari E. North Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
Anne E. Justice Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Ching-Ti Liu Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA

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Mendelian randomization unraveled: gender-specific insights into obesity-related phenotypes and colorectal cancer susceptibility

Objective

Evidence has been increasingly pointing towards a potential link between phenotypes related to obesity and the incidence of colorectal cancer. However, confirming this as a direct causal connection remains elusive. This investigation aims to elucidate the causative links between obesity-associated phenotypes and the incidence of colorectal cancer.

Methods

Employing the Two Sample Mendelian Randomization (TwoSampleMR) R package, analyses were conducted using Mendelian randomization (MR) to discern potential causative links between obesity categories sourced from both the Institute for Education and University (IEU) Open GWAS Project and Zenodo, and colorectal tumors (data obtained from IEU Open GWAS and FinnGen). For primary evaluations, the study utilized the Wald ratio and the Inverse Variance Weighting (IVW) methods, while the MR-Egger approach was integrated for sensitivity assessment. Bidirectional Mendelian Randomization (Bidirectional MR), as well as Linkage Disequilibrium (LD) Score Regression with well-imputed HapMap3 single nucleotide polymorphisms (SNPs), were additionally executed. Sensitivity assessments entailed IVW, MR-Egger methodologies to assess heterogeneity and pleiotropy, along with a leave-one-out strategy. Instrumental variables were chosen judiciously based on predetermined P-value thresholds and F-statistics.

Results

Results from MR evaluations did not identify a clear causative link between BMI and colorectal malignancy. Conversely, both measures of obesity, the Waist-Hip Ratio (WHR) and its adjusted form for BMI (WHRadjBMI), displayed a connection to increased risk of colorectal cancer, especially prominent among female subjects. Reverse MR analyses dismissed potential reverse causality between colorectal malignancies and obesity. A significant genetic interplay was observed between WHR, WHRadjBMI, and colorectal cancer instances. Ensuing MR probes spotlighted inflammatory bowel ailment as a protective factor, while salad intake was indicated as a potential risk concerning colorectal malignancies. Sensitivity reviews, which included tests for both pleiotropy and heterogeneity, validated the robustness of the MR findings.

Conclusion

Findings from this research indicate that specific obesity-related parameters, notably WHR and WHRadjBMI, carry a causal relationship with an elevated colorectal cancer risk. The impact is distinctly more evident among females. Such insights might be pivotal for public health deliberations, hinting that individuals boasting a high WHR might necessitate intensified colorectal cancer screenings.

Genetic association of glycemic traits and antihyperglycemic agent target genes with the risk of lung cancer: A Mendelian randomization study

AIMS

To evaluate the potential causal effect of glycemic traits on lung cancer and investigate the impact of antihyperglycemic agent-target genes on lung cancer risk.

METHODS

Genetic variants associated with glycemic traits, antihyperglycemic agent-target genes, and lung cancer were extracted from the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC), expression quantitative trait loci (eQTLs), protein quantitative trait loci (pQTLs), and the International Lung Cancer Consortium (ILCCO), respectively. Mendelian randomization (MR) analyses were performed to examine the associations of glycemic traits and antihyperglycemic agent-target genes with lung cancer. Mediation analysis was conducted to explore whether overweight operated as a mediator between antihyperglycemic agents and lung cancer outcomes.

RESULTS

Genetically determined glycated hemoglobin A1c levels were associated with squamous cell lung cancer (OR = 1.78; 95 % CI, 1.08-2.92; p = 0.023). The PRKAB1 gene (the target of metformin) was associated with a lower risk of developing lung adenocarcinoma (OR = 0.85; 95 % CI, 0.76-0.96; p = 0.006). Further mediation analyses did not support overweight as a mediator between PRKAB1 activation and lung adenocarcinoma.

CONCLUSION

Our analyses suggest an association of genetically determined abnormal glycemic traits with squamous cell lung cancer. The potential association between PRKAB1 activation and a reduced risk of developing lung adenocarcinoma appears to be independent of the anti-obesity effects of metformin, suggesting that PRKAB1 activation may have a direct protective effect on lung adenocarcinoma development.

Advances in Drug Treatments for Companion Animal Obesity

Companion animal obesity has emerged as a significant veterinary health concern globally, with escalating rates posing challenges for preventive and therapeutic interventions. Obesity not only leads to immediate health problems but also contributes to various comorbidities affecting animal well-being and longevity, with consequent emotional and financial burdens on owners. While past treatment strategies have shown limited success, recent breakthroughs in human medicine present new opportunities for addressing this complex issue in companion animals. Here, we discuss the potential of GLP-1 receptor agonists, specifically semaglutide and tirzepatide, already approved for human use, for addressing companion animal obesity. These drugs, originally developed to treat type 2 diabetes in humans and subsequently repurposed to treat obesity, have demonstrated remarkable weight loss effects in rodents, non-human primates and people. Additionally, newer drug combinations have shown even more promising results in clinical trials. Despite current cost and supply challenges, advancements in oral and/or extended-release formulations and increased production may make these drugs more accessible for veterinary use. Thus, these drugs may have utility in companion animal weight management, and future feasibility studies exploring their efficacy and safety in treating companion animal obesity are warranted.

Association between fatty liver index and controlled attenuation parameters as markers of metabolic dysfunction-associated fatty liver disease and bone mineral density: observational and two-sample Mendelian randomization studies

Previously observational studies did not draw a clear conclusion on the association between fatty liver diseases and bone mineral density (BMD). Our large-scale studies revealed that MAFLD and hepatic steatosis had no causal effect on BMD, while some metabolic factors were correlated with BMD. The findings have important implications for the relationship between fatty liver diseases and BMD, and may help direct the clinical management of MAFLD patients who experience osteoporosis and osteopenia.

PURPOSE

Liver and bone are active endocrine organs with several metabolic functions. However, the link between metabolic dysfunction-associated fatty liver disease (MAFLD) and bone mineral density (BMD) is contradictory.

METHODS

Using the UK Biobank and National Health and Nutrition Examination Survey (NHANES) dataset, we investigated the association between MAFLD, steatosis, and BMD in the observational analysis. We performed genome-wide association analysis to identify single-nucleotide polymorphisms associated with MAFLD. Large-scale two-sample Mendelian randomization (TSMR) analyses examined the potential causal relationship between MAFLD, hepatic steatosis, or major comorbid metabolic factors, and BMD.

RESULTS

After adjusting for demographic factors and body mass index, logistic regression analysis demonstrated a significant association between MAFLD and reduced heel BMD. However, this association disappeared after adjusting for additional metabolic factors. MAFLD was not associated with total body, femur neck, and lumbar BMD in the NHANES dataset. Magnetic resonance imaging-measured steatosis did not show significant associations with reduced total body, femur neck, and lumbar BMD in multivariate analysis. TSMR analyses indicated that MAFLD and hepatic steatosis were not associated with BMD. Among all MAFLD-related comorbid factors, overweight and type 2 diabetes showed a causal relationship with increased BMD, while waist circumference and hyperlipidemia had the opposite effect.

CONCLUSION

No causal effect of MAFLD and hepatic steatosis on BMD was observed in this study, while some metabolic factors were correlated with BMD. This has important implications for understanding the relationship between fatty liver disease and BMD, which may help direct the clinical management of MAFLD patients with osteoporosis.

Effect of the gut microbiome, plasma metabolome, peripheral cells, and inflammatory cytokines on obesity: a bidirectional two-sample Mendelian randomization study and mediation analysis

Background

Obesity is a metabolic and chronic inflammatory disease involving genetic and environmental factors. This study aimed to investigate the causal relationship among gut microbiota abundance, plasma metabolomics, peripheral cell (blood and immune cell) counts, inflammatory cytokines, and obesity.

Methods

Summary statistics of 191 gut microbiota traits (N = 18,340), 1,400 plasma metabolite traits (N = 8,299), 128 peripheral cell counts (blood cells, N = 408,112; immune cells, N = 3,757), 41 inflammatory cytokine traits (N = 8,293), and 6 obesity traits were obtained from publicly available genome-wide association studies. Two-sample Mendelian randomization (MR) analysis was applied to infer the causal links using inverse variance-weighted, maximum likelihood, MR-Egger, weighted median, weighted mode, and Wald ratio methods. Several sensitivity analyses were also utilized to ensure reliable MR results. Finally, we used mediation analysis to identify the pathway from gut microbiota to obesity mediated by plasma metabolites, peripheral cells, and inflammatory cytokines.

Results

MR revealed a causal effect of 44 gut microbiota taxa, 281 plasma metabolites, 27 peripheral cells, and 8 inflammatory cytokines on obesity. Among them, five shared causal gut microbiota taxa belonged to the phylum Actinobacteria, order Bifidobacteriales, family Bifidobacteriaceae, genus Lachnospiraceae UCG008, and species Eubacterium nodatum group. Furthermore, we screened 42 shared causal metabolites, 7 shared causal peripheral cells, and 1 shared causal inflammatory cytokine. Based on known causal metabolites, we observed that the metabolic pathways of D-arginine, D-ornithine, linoleic acid, and glycerophospholipid metabolism were closely related to obesity. Finally, mediation analysis revealed 20 mediation relationships, including the causal pathway from gut microbiota to obesity, mediated by 17 metabolites, 2 peripheral cells, and 1 inflammatory cytokine. Sensitivity analysis represented no heterogeneity or pleiotropy in this study.

Conclusion

Our findings support a causal relationship among gut microbiota, plasma metabolites, peripheral cells, inflammatory cytokines, and obesity. These biomarkers provide new insights into the mechanisms underlying obesity and contribute to its prevention, diagnosis, and treatment.

ChemRAP uncovers specific mRNA translation regulation via RNA 5' phospho-methylation

5'-end modifications play key roles in determining RNA fates. Phospho-methylation is a noncanonical cap occurring on either 5'-PPP or 5'-P ends. We used ChemRAP, in which affinity purification of cellular proteins with chemically synthesized modified RNAs is coupled to quantitative proteomics, to identify 5'-Pme "readers". We show that 5'-Pme is directly recognized by EPRS, the central subunit of the multisynthetase complex (MSC), through its linker domain, which has previously been involved in key noncanonical EPRS and MSC functions. We further determine that the 5'-Pme writer BCDIN3D regulates the binding of EPRS to specific mRNAs, either at coding regions rich in MSC codons, or around start codons. In the case of LRPPRC (leucine-rich pentatricopeptide repeat containing), a nuclear-encoded mitochondrial protein associated with the French Canadian Leigh syndrome, BCDIN3D deficiency abolishes binding of EPRS around its mRNA start codon, increases its translation but ultimately results in LRPPRC mislocalization. Overall, our results suggest that BCDIN3D may regulate the translation of specific mRNA via RNA-5'-Pme.

Maternal Age at Menarche Genes Determines Fetal Growth Restriction Risk

We aimed to explore the potential link of maternal age at menarche (mAAM) gene polymorphisms with risk of the fetal growth restriction (FGR). This case (FGR)-control (FGR free) study included 904 women (273 FGR and 631 control) in the third trimester of gestation examined/treated in the Departments of Obstetrics. For single nucleotide polymorphism (SNP) multiplex genotyping, 50 candidate loci of mAAM were chosen. The relationship of mAAM SNPs and FGR was appreciated by regression procedures (logistic/model-based multifactor dimensionality reduction [MB-MDR]) with subsequent in silico assessment of the assumed functionality pithy of FGR-related loci. Three mAAM-appertain loci were FGR-linked to genes such as KISS1 (rs7538038) (effect allele G-odds ratio (OR)allelic = 0.63/pperm = 0.0003; ORadditive = 0.61/pperm = 0.001; ORdominant = 0.56/pperm = 0.001), NKX2-1 (rs999460) (effect allele A-ORallelic = 1.37/pperm = 0.003; ORadditive = 1.45/pperm = 0.002; ORrecessive = 2.41/pperm = 0.0002), GPRC5B (rs12444979) (effect allele T-ORallelic = 1.67/pperm = 0.0003; ORdominant = 1.59/pperm = 0.011; ORadditive = 1.56/pperm = 0.009). The haplotype ACA FSHB gene (rs555621*rs11031010*rs1782507) was FRG-correlated (OR = 0.71/pperm = 0.05). Ten FGR-implicated interworking models were founded for 13 SNPs (pperm ≤ 0.001). The rs999460 NKX2-1 and rs12444979 GPRC5B interplays significantly influenced the FGR risk (these SNPs were present in 50% of models). FGR-related mAAM-appertain 15 polymorphic variants and 350 linked SNPs were functionally momentous in relation to 39 genes participating in the regulation of hormone levels, the ovulation cycle process, male gonad development and vitamin D metabolism. Thus, this study showed, for the first time, that the mAAM-appertain genes determine FGR risk.

A GIPR antagonist conjugated to GLP-1 analogues promotes weight loss with improved metabolic parameters in preclinical and phase 1 settings

Obesity is a major public health crisis. Multi-specific peptides have emerged as promising therapeutic strategies for clinical weight loss. Glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) are endogenous incretins that regulate weight through their receptors (R). AMG 133 (maridebart cafraglutide) is a bispecific molecule engineered by conjugating a fully human monoclonal anti-human GIPR antagonist antibody to two GLP-1 analogue agonist peptides using amino acid linkers. Here, we confirm the GIPR antagonist and GLP-1R agonist activities in cell-based systems and report the ability of AMG 133 to reduce body weight and improve metabolic markers in male obese mice and cynomolgus monkeys. In a phase 1, randomized, double-blind, placebo-controlled clinical study in participants with obesity ( NCT04478708 ), AMG 133 had an acceptable safety and tolerability profile along with pronounced dose-dependent weight loss. In the multiple ascending dose cohorts, weight loss was maintained for up to 150 days after the last dose. These findings support continued clinical evaluation of AMG 133.

Persistent thinness and anorexia nervosa differ on a genomic level

Thinness and anorexia nervosa are both characterised by persistent low weight. Individuals with anorexia nervosa concurrently report distorted perceptions of their body and engage in weight-loss behaviours, whereas individuals with thinness often wish to gain weight. Both conditions are heritable and share genomics with BMI, but are not genetically correlated with each other. Based on their pattern of genetic associations with other traits, we explored differences between thinness and anorexia nervosa on a genomic level. In Part 1, using publicly available data, we compared genetic correlations of persistent thinness/anorexia nervosa with eleven psychiatric disorders. In Part 2, we identified individuals with adolescent persistent thinness in the Avon Longitudinal Study of Parents and Children (ALSPAC) by latent class growth analysis of measured BMI from 10 to 24 years (n = 6594) and evaluated associations with psychiatric and anthropometric polygenic scores. In Part 1, in contrast to the positive genetic correlations of anorexia nervosa with various psychiatric disorders, persistent thinness showed negative genetic correlations with attention deficit hyperactivity disorder (rgAN = 0.08 vs. rgPT = -0.30), alcohol dependence (rgAN = 0.07 vs. rgPT = -0.44), major depressive disorder (rgAN = 0.27 vs. rgPT = -0.18) and post-traumatic stress disorder (rgAN = 0.26 vs. rgPT = -0.20). In Part 2, individuals with adolescent persistent thinness in the ALSPAC had lower borderline personality disorder polygenic scores (OR = 0.77; Q = 0.01). Overall, results suggest that genetic variants associated with thinness are negatively associated with psychiatric disorders and therefore thinness may be differentiable from anorexia nervosa on a genomic level.

Causal inference between rheumatoid arthritis and prostate cancer

It is unclear if the association between rheumatoid arthritis (RA) and a higher risk of prostate cancer (Pca) reflects a causal relationship. We conducted a meta-analysis and used the Mendelian randomization method (MR) to evaluate the association between RA and Pca risk. A meta-analysis and subgroup analysis of the incidence of Pca in patients with RA was conducted. To determine whether genetically elevated RA levels were causally linked to Pca, two MR samples were employed. To eliminate gender-related bias, we conducted a stratified analysis of the GWAS data for RA by gender, specifically including 140,254 males. Additional MR analysis was also performed to determine potential confounding factors influencing the association between genetically susceptible RA and Pca. In total, 409,950 participants were enrolled in 20 trials to investigate the Pca risk in patients with RA. The meta-analysis suggested that RA was unrelated to the Pca risk (SIR = 1.072, 95% CI, 0.883-1.261). However, a subgroup analysis showed that low smoking rates might increase the Pca risk in patients with RA by 24%. The MR analysis showed that increased genetic susceptibility to RA was related to a high Pca risk (OR = 36.20, 95%CI = 1.24-1053.12, P = 0.037). The causality estimation of MR-Egger, Weighted mode, Simple mode, and Weighted median method were similar in direction and magnitude. Although our meta-analysis found no correlation between RA and Pca risk, MR analyses supported a causal relationship between genetic susceptibility to RA and increased prostate risk. Early attention to Pca risk in patients with RA may be important for improving prognosis and mortality in such patients. Further research is needed to determine the etiology of RA attributed to Pca and its underlying mechanisms.

Multitrait meta-analyses identify potential candidate genes for growth-related traits in Holstein heifers

Understanding the underlying pleiotropic relationships among growth and body size traits is important for refining breeding strategies in dairy cattle for optimal body size and growth rate. Therefore, we performed single-trait GWAS for monthly-recorded body weight (BW), hip height, body length, and chest girth from birth to 12 mo of age in Holstein animals, followed by stepwise multiple regression of independent or lowly-linked markers from GWAS loci using conditional and joint association analyses (COJO). Subsequently, we conducted a multitrait meta-analysis to detect pleiotropic markers. Based on the single-trait GWAS, we identified 170 significant SNPs, in which 59 of them remained significant after the COJO analyses. The most significant SNP, located at BTA7:3,676,741, explained 2.93% of the total phenotypic variance for BW6 (BW at 6 mo of age). We identified 17 SNPs with potential pleiotropic effects based on the multitrait meta-analyses, which resulted in 3 additional SNPs in comparison to those detected based on the single-trait GWAS. The identified quantitative trait loci regions overlap with genes known to influence human growth-related traits. According to positional and functional analyses, we proposed HMGA2, HNF4G, MED13L, BHLHE40, FRZB, DMP1, TRIB3, and GATAD2A as important candidate genes influencing the studied traits. The combination of single-trait GWAS and meta-analyses of GWAS results improved the efficiency of detecting associated SNPs, and provided new insights into the genetic mechanisms of growth and development in Holstein cattle.

Elucidation of genetic determinants of dyslipidaemia using a global screening array for the early detection of coronary artery disease

Dyslipidemia is a major risk factor for the development of coronary artery disease (CAD). Understanding the genetic determinants of dyslipidemia can provide valuable information on the pathogenesis of CAD and aid in the development of early detection strategies. In this study, we used a Global Screening Array (GSA) to elucidate the genetic factors associated with dyslipidemia and their potential role in the prediction of CAD. We conducted a GSA-based association study in 265 subjects to identify the genetic loci associated with dyslipidemia traits using Multiple Linear Regression (MLR) and Logistic Regression (LR), Classification and Regression Tree (CART), and Manhattan plots. We identified an association between dyslipidemia and variants identified in genes such as JCAD, GLIS3, CD38, FN1, CELSR2, MTNR1B, GIPR, DYM, APOB, APOE, ADCY5. The MLR models explained 62%, 71%, and 81% of the variability in HDL, LDL, and triglycerides, respectively. The Area Under the Curve (AUC) values in the LR models of HDL, LDL, and triglycerides were 1.00, 0.94, and 0.95, respectively. CART models identified novel gene-gene interactions influencing the risk for dyslipidemia. To conclude, we have identified the association of 12 SNVs with dyslipidemia and demonstrated their clinical utility in four different models such as MLR, LR, CART, and Manhattan plots. The identified genetic variants and associated pathways shed light on the underlying biology of dyslipidemia and offer potential avenues for precision medicine strategies in the management of CAD.

Metabolic Syndrome: An Overview on Its Genetic Associations and Gene-Diet Interactions

Metabolic syndrome (MetS) is a cluster of cardiometabolic risk factors that includes central obesity, hyperglycemia, hypertension, and dyslipidemias and whose inter-related occurrence may increase the odds of developing type 2 diabetes and cardiovascular diseases. MetS has become one of the most studied conditions, nevertheless, due to its complex etiology, this has not been fully elucidated. Recent evidence describes that both genetic and environmental factors play an important role on its development. With the advent of genomic-wide association studies, single nucleotide polymorphisms (SNPs) have gained special importance. In this review, we present an update of the genetics surrounding MetS as a single entity as well as its corresponding risk factors, considering SNPs and gene-diet interactions related to cardiometabolic markers. In this study, we focus on the conceptual aspects, diagnostic criteria, as well as the role of genetics, particularly on SNPs and polygenic risk scores (PRS) for interindividual analysis. In addition, this review highlights future perspectives of personalized nutrition with regard to the approach of MetS and how individualized multiomics approaches could improve the current outlook.

Spatiotemporal regulation of GIPR signaling impacts glucose homeostasis as revealed in studies of a common GIPR variant

OBJECTIVE

Glucose-dependent insulinotropic polypeptide (GIP) has a role in controlling postprandial metabolic tone. In humans, a GIP receptor (GIPR) variant (Q354, rs1800437) is associated with a lower body mass index (BMI) and increased risk for Type 2 Diabetes. To better understand the impacts of GIPR-Q354 on metabolism, it is necessary to study it in an isogeneic background to the predominant GIPR isoform, E354. To accomplish this objective, we used CRISPR-CAS9 editing to generate mouse models of GIPR-Q354 and GIPR-E354. Here we characterize the metabolic effects of GIPR-Q354 variant in a mouse model (GIPR-Q350).

METHODS

We generated the GIPR-Q350 mice for in vivo studies of metabolic impact of the variant. We isolated pancreatic islets from GIPR-Q350 mice to study insulin secretion ex vivo. We used a β-cell cell line to understand the impact of the GIPR-Q354 variant on the receptor traffic.

RESULTS

We found that female GIPR-Q350 mice are leaner than littermate controls, and male GIPR-Q350 mice are resistant to diet-induced obesity, in line with the association of the variant with reduced BMI in humans. GIPR-Q350 mice of both sexes are more glucose tolerant and exhibit an increased sensitivity to GIP. Postprandial GIP levels are reduced in GIPR-Q350 mice, revealing feedback regulation that balances the increased sensitivity of GIP target tissues to secretion of GIP from intestinal endocrine cells. The increased GIP sensitivity is recapitulated ex vivo during glucose stimulated insulin secretion assays in islets. Generation of cAMP in islets downstream of GIPR activation is not affected by the Q354 substitution. However, post-activation traffic of GIPR-Q354 variant in β-cells is altered, characterized by enhanced intracellular dwell time and increased localization to the Trans-Golgi Network (TGN).

CONCLUSIONS

Our data link altered intracellular traffic of the GIPR-Q354 variant with GIP control of metabolism. We propose that this change in spatiotemporal signaling underlies the physiologic effects of GIPR-Q350/4 and GIPR-E350/4 in mice and humans. These findings contribute to a more complete understanding of the impact of GIPR-Q354 variant on glucose homeostasis that could perhaps be leveraged to enhance pharmacologic targeting of GIPR for the treatment of metabolic disease.

Can polygenic risk scores help explain disease prevalence differences around the world? A worldwide investigation

Complex disorders are caused by a combination of genetic, environmental and lifestyle factors, and their prevalence can vary greatly across different populations. The extent to which genetic risk, as identified by Genome Wide Association Study (GWAS), correlates to disease prevalence in different populations has not been investigated systematically. Here, we studied 14 different complex disorders and explored whether polygenic risk scores (PRS) based on current GWAS correlate to disease prevalence within Europe and around the world. A clear variation in GWAS-based genetic risk was observed based on ancestry and we identified populations that have a higher genetic liability for developing certain disorders. We found that for four out of the 14 studied disorders, PRS significantly correlates to disease prevalence within Europe. We also found significant correlations between worldwide disease prevalence and PRS for eight of the studied disorders with Multiple Sclerosis genetic risk having the highest correlation to disease prevalence. Based on current GWAS results, the across population differences in genetic risk for certain disorders can potentially be used to understand differences in disease prevalence and identify populations with the highest genetic liability. The study highlights both the limitations of PRS based on current GWAS but also the fact that in some cases, PRS may already have high predictive power. This could be due to the genetic architecture of specific disorders or increased GWAS power in some cases.