The gut microbiota plays a crucial role in human health, but its impact on lipid metabolism remains unclear. Understanding the causal relationship between gut bacteria and lipid profiles is essential for developing strategies to prevent and treat dyslipidemia and cardiovascular diseases. This study aimed to assess this relationship using two-sample Mendelian randomization (MR). Data for both exposure and outcomes were obtained from the IEU-GWAS database, with lipid profile data sourced from a publication. Genome-wide significant single nucleotide polymorphisms (SNPs), which were independent of outcome factors but correlated with exposure variables, were identified as instrumental variables. Several MR methods, including weighted analysis, maximum likelihood, inverse variance weighting (IVW), MR-Egger, and weighted median, were applied. Colocalization analysis further validated the findings. The analysis revealed microbial groups with causal relationships to ApoA1, ApoB, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, total cholesterol, and triglycerides. Reverse MR and colocalization analysis provided additional confirmation of these results. This study offers new evidence of the causal link between gut microbiota and lipid profiles, providing insights for improving lipid profiles and reducing cardiovascular disease risk.

The comorbidity between bipolar disorder (BD) and high body mass index (BMI) is well-documented, but their shared genetic architecture remains unclear. Our study aimed to explore this genetic correlation and potential causality.

Utilizing large-scale genome-wide association study (GWAS) summary statistics, we quantified global and local genetic correlations between BD and BMI using linkage disequilibrium score regression (LDSC) and Heritability Estimation from Summary Statistics. Stratified LDSC characterized genetic overlap across functional categories. Cross-trait meta-analyses identified shared risk single nucleotide polymorphisms (SNPs), followed by colocalization analysis using Coloc. Bi-directional Mendelian randomization (MR) assessed causality, while tissue-level SNP heritability enrichment for BD and BMI was evaluated using LDSC-specific expressed genes and Multi-marker Analysis of Genomic Annotation.

We found a genetic correlation between BD and BMI, especially in localized genomic regions. Cross-trait meta-analysis identified 46 significant SNPs shared between BD and BMI, including three novel shared risk SNPs. Colocalization analysis verified two novel SNPs with shared causal variants linked to ITIH1 and TM6SF2 genes. MR analysis demonstrated a causal effect of BD on BMI, but not the reverse. Gene expression data revealed genetic correlation enrichment in five specific brain regions.

This study comprehensively analyzes the genetic correlation between BD and BMI, uncovering shared genetic architecture and identifying novel risk loci. These findings provide new insights into the interplay between BD and BMI, informing the development of diagnostic tools and therapeutic strategies.

Obesity is a complex, chronic condition characterised by excess adiposity. Rates of obesity in childhood and adolescence are increasing worldwide, with a corresponding increase in adulthood. The aetiology of obesity is multifactorial and results from a combination of endocrine, genetic, environmental and societal factors. Population level approaches to reduce the prevalence of childhood obesity worldwide are urgently needed. There are wide-ranging complications from excess weight affecting every system in the body, which lead to significant morbidity and reduced life expectancy. Treatment of obesity and its complications requires a multi-faceted, biopsychosocial approach incorporating dietary, exercise and psychological treatments. Pharmacological treatments for treating childhood obesity have recently become available, and there is further development of new anti-obesity medications in the pipeline. In addition, bariatric surgery is being increasingly recognised as a treatment option for obesity in adolescence providing the potential to reverse complications related to excess weight. In this review, we present an update on the prevalence, aetiology, complications and treatment of childhood obesity.

Diet is an important determinant of body weight and may modulate genetic susceptibility to obesity.

This systematic review and meta-analysis aimed to synthesize evidence related to interactions between polygenic risk and nutrient intakes on obesity outcomes.

MEDLINE, EMBASE, Web of Science, and Cochrane Library were systematically searched to identify observational studies that assessed interactions between polygenic risk and nutrient intakes on obesity-related outcomes. Random effects meta-analyses were performed for pooled polygenic risk score (PRS)-total fat intake and PRS-protein intake interaction coefficients on body mass index (BMI).

Twenty-six publications were retrieved with studies conducted among European, Asian, and African samples. Dietary fats (saturated fat, omega-3, and trans fat) and energy intake were most frequently reported to interact with PRS on obesity outcomes, but the total number of studies available was low. No significant interactions were identified in meta-analyses of PRS interactions with total fat intake and protein intake on BMI. Several studies were rated as low quality, heterogeneity was high, and although study samples were racially diverse, PRSs tended to be based on samples of European ancestry.

Evidence of interactions between polygenic risk and nutrient intakes on obesity outcomes is limited and inconsistent. Further research addressing limitations related to study quality and polygenic risk characterization is needed.

Heart failure with preserved ejection fraction (HFpEF) is an increasingly prevalent clinical syndrome with high morbidity and mortality. Although HFpEF frequently coexists with cardiometabolic diseases, the causal mechanisms and potential mediators remain poorly understood.

This study aimed to identify cardiometabolic risk factors specifically driving HFpEF and to determine their underlying circulating mediators.

We used two-sample Mendelian Randomization (MR) to analyze the effects of obesity, Type 2 diabetes, hypertension, chronic kidney disease (CKD), and dyslipidemia on HFpEF and heart failure with reduced ejection fraction (HFrEF) in large European-ancestry GWAS datasets. We then performed mediation MR to identify plasma proteins and metabolites that mediate the transition from each cardiometabolic disease to HFpEF, respectively. We applied multivariable MR to assess the impact of risk confounding on the results. Bioinformatic analyses were conducted to delineate mechanisms.

Cardiometabolic diseases had heterogeneous effects on HFpEF and HFrEF. Obesity and type 2 diabetes showed adjusted causal effects with HFpEF, hypertension showed potential relevance to HFpEF, whereas dyslipidemia and CKD did not. MR analysis identified 5 proteins that mediate obesity to HFpEF; 5 proteins that mediate type 2 diabetes to HFpEF. Further mediation MR analysis of obesity and T2D on HFrEF revealed heterogeneity in circulating mediators between metabolic HFpEF and HFrEF. Comprehensive bioinformatics analyses showed that IL1R1, together with other proteins such as TP53 and FGF19, orchestrates the inflammatory and fibrotic processes underlying HFpEF.

These findings suggest that metabolic HFpEF has distinct etiological features compared with HFrEF and is driven by complex, condition-specific mediators. IL1R1 mediates HFpEF in multiple metabolic risk states, suggesting a potential therapeutic target. Further translational studies are warranted to evaluate anti-inflammatory strategies targeting IL1R1 in HFpEF.

This study aimed to investigate the association between maternal smoking around birth and the incidence of offspring constipation.

Genome-wide association study (GWAS) data for maternal smoking around birth and offspring constipation were obtained from the Mendelian randomization (MR) Base platform. Single nucleotide polymorphisms (SNPs) significantly associated with maternal smoking around birth were utilized as instrumental variables in two-sample MR analyses to explore the relationship between maternal smoking and offspring constipation. The analytical methods employed included the inverse-variance weighted (IVW) method, weighted median estimator, and MR-Egger regression.

Twenty SNPs significantly associated with maternal smoking around birth (p<5×10-8; linkage disequilibrium r2<0.001) were identified. Across the different methods, a consistent positive association was observed between maternal smoking around birth and an increased risk of constipation in offspring (IVW: OR=4.35; 95% CI: 1.81-10.45; weighted median estimator: OR=4.23; 95% CI: 1.22-14.75; MR-Egger: OR=0.92; 95% CI: 0.01-122.07), suggesting that higher frequency of maternal smoking is associated with an elevated risk of constipation in offspring. However, we did not detect any potential effect of genetic liability to constipation risk on maternal smoking.

This study provides evidence suggesting that increased maternal smoking around the time of birth may be linked to a higher risk of constipation in offspring.

Mendelian randomization (MR) is a widely used method for assessing causal relationships between risk factors and outcomes using genetic variants as instrumental variables (IVs). While traditional MR assumes uni-directional causality, bi-directional MR aims to identify the true causal direction. In uni-directional MR, invalid IVs due to pleiotropy can violate assumptions and introduce biases. In bi-directional MR, traditional MR can be performed separately for each direction, but the presence of invalid IVs poses even greater challenges. We introduce a new bi-directional MR method incorporating stepwise selection (Bidir-SW) designed to address these challenges. Our approach leverages public genome-wide association study (GWAS) datasets for two traits and uses model selection criteria to identify invalid IVs iteratively by stepwise selection. This method accounts for potential bi-directional causality in the presence of common invalid IVs for both directions, even if only GWAS summary statistics are provided. Through simulation studies, we demonstrate that our method outperforms traditional MR techniques, such as MR-Egger and inverse-variance weighted (IVW), with uncorrelated SNPs. We also provide simulations to compare our approach with existing transcriptome-wide association study (TWAS) to show its effectiveness. Finally, we apply the proposed method to genetic traits such as CRP levels and BMI to explore possible bi-directional relationships among these traits. We also used the proposed method to discover causal protein biomarkers. Our findings suggest that the Bidir-SW approach is a powerful tool for bi-directional MR or TWAS, which can provide a valuable framework for future genetic epidemiology studies.

Excess cholesterol accumulation contributes to fibrogenesis in metabolic dysfunction-associated steatohepatitis (MASH), but how hepatic cholesterol metabolism becomes dysregulated in MASH is not completely understood. We show that human fibrotic MASH livers have decreased EH-domain-binding protein 1 (EHBP1), a genome-wide association study (GWAS) locus associated with low-density lipoprotein (LDL) cholesterol, and that EHBP1 loss- and gain-of-function increase and decrease MASH fibrosis in mice, respectively. Mechanistic studies reveal that EHBP1 promotes sortilin-mediated PCSK9 secretion, leading to LDL receptor (LDLR) degradation, decreased LDL uptake, and reduced TAZ, a fibrogenic effector. At a cellular level, EHBP1 deficiency affects the intracellular localization of retromer, a protein complex required for sortilin stabilization. Our therapeutic approach to stabilizing retromer is effective in mitigating MASH fibrosis. Moreover, we show that the tumor necrosis factor alpha (TNF-α)/peroxisome proliferator-activated receptor alpha (PPARα) pathway suppresses EHBP1 in MASH. These data not only provide mechanistic insights into the role of EHBP1 in cholesterol metabolism and MASH fibrosis but also elucidate an interplay between inflammation and EHBP1-mediated cholesterol metabolism.

Pelvic organ prolapse (POP), whose etiology is influenced by genetic and clinical risk factors, considerably impacts women's quality of life. However, the genetic underpinnings in non-European populations and comprehensive risk models integrating genetic and clinical factors remain underexplored. This study constructed the first polygenic risk score (PRS) for POP in the Chinese population by utilizing 20 disease-associated variants from the largest existing genome-wide association study. We analyzed a discovery cohort of 576 cases and 623 controls and a validation cohort of 264 cases and 200 controls. Results showed that the case group exhibited a significantly higher PRS than the control group. Moreover, the odds ratio of the top 10% risk group was 2.6 times higher than that of the bottom 10%. A high PRS was significantly correlated with POP occurrence in women older than 50 years old and in those with one or no childbirths. As far as we know, the integrated prediction model, which combined PRS and clinical risk factors, demonstrated better predictive accuracy than other existing PRS models. This combined risk assessment model serves as a robust tool for POP risk prediction and stratification, thereby offering insights into individualized preventive measures and treatment strategies in future clinical practice.

The C-terminal binding protein 2 (CTBP2) gene (translational isoforms: CTBP2-L/S, RIBEYE) had been identified by a cross-trait analysis of genome-wide association studies for anorexia nervosa (AN) and body mass index (BMI). Here, we did a mutation analysis in CTBP2 by performing polymerase chain reactions with subsequent Sanger-sequencing to identify variants relevant for AN and body weight regulation and ensued functional studies. Analysis of the coding regions of CTBP2 in 462 female patients with AN (acute or recovered), 490 children and adolescents with severe obesity, 445 healthy-lean adult individuals and 168 healthy adult individuals with normal body weight detected 24 variants located in the specific exon of RIBEYE. In the initial analysis, three of these were rare non-synonymous variants (NSVs) detected heterozygously in patients with AN (p.Arg72Trp - rs146900874; p.Val289Met -rs375685611 and p.Gly362Arg - rs202010294). Four NSVs and one heterozygous frameshift variant were exclusively detected in children and adolescents with severe obesity (p.Pro53Ser - rs150867595; p.Gln175ArgfsTer45 - rs141864737; p.Leu310Val - rs769811964; p.Pro397Ala - rs76134089 and p.Pro402Ser - rs113477585). Ribeye mRNA was detected in mouse hypothalamus. No effect of fasting or overfeeding on murine hypothalamic Ribeye expression was determined. Yet, increased Ribeye expression was detected in hypothalami of leptin-treated Lepob/ob mice. This increase was not related to reduced food intake and leptin-induced weight loss. We detected rare and frequent variants in the RIBEYE specific exon in both patients with AN and in children and adolescents with severe obesity. Our data suggest RIBEYE as a relevant gene for weight regulation.

Obesity has been associated with onset and progression of chronic kidney disease (CKD) but causal relationship remains uncertain. This study investigated how obesity causally affects estimated glomerular filtration rate.

Cross-sectional and magnetic resonance imaging (MRI) data analyses were performed within the Prospective Investigation of Obesity, Energy, and Metabolism (POEM) study (502 participants, all aged 50 years). Additionally Mendelian randomization was performed using published summary data. Outcomes were creatinine- and cystatin C-based eGFR. Body mass index (BMI) and waist circumference (WC) were used as exposure variables in the cross-sectional and Mendelian randomization analyses. In the imaging data analyses, eGFR was regressed non-parametrically on tissue volume for each 3D voxel and visualized as a correlation "Imiomics" map.

Negative correlations were shown between cystatin C-based eGFR and BMI [beta = -0.190 (95% CI: -0.280 to -0.100)] and WC [beta = -0.160 (95% CI: -0.250 to -0.060)] in an adjusted model. In contrast, a positive association was found for creatinine-based eGFR [BMI beta = 1.20 (95% CI: 0.030 to 0.210) and WC beta = 0.160 (95% CI: 0.070 to 0.260)]. Similar patterns were found using MRI analysis (Imiomics map). Mendelian randomization implied a negative causal effect of obesity-related measures on cystatin C-based eGFR [BMI beta = -0.031 (95% CI: -0.037 to -0.026) and WC beta = -0.038 (95% CI: -0.045 to -0.031)], but no statistically significant effect was found for creatinine-based eGFR.

This study suggests a causal negative effect of obesity on cystatin C-based, but not creatinine-based eGFR. These findings warrant further research regarding estimations of kidney function when assessing obesity and CKD.

Genetic predisposition to adiposity is associated with type 2 diabetes (T2D), even in the absence of phenotypic adiposity (obesity and central obesity). We aimed to quantify the overall contribution of obesity and modifiable lifestyle factors to the association between genetic predisposition to adiposity and the development of T2D.

This prospective cohort study involved 220 703 White British participants from the UK Biobank. It examined the associations between genetic predisposition to adiposity [body mass index polygenic risk (BMI-PRS) and waist-hip ratio polygenic risk (WHR-PRS)] and incident T2D, as well as interactions and mediation via lifestyle factors (diet quality, physical activity levels, total energy intake, sleep duration, and smoking and alcohol intake) and phenotypic adiposity.

People with high phenotypic adiposity and high adiposity PRS values (>1 SD above the mean) had the highest risk of incident T2D (versus non-obese/central obese and non-high PRS). This was the case for BMI-PRS [hazard ratio (HR) = 3.72] and WHR-PRS (HR = 4.17). Lifestyle factors explained 30.5% of the BMI-PRS/T2D association (2.0% mediation; 28.5% effect modification), and lifestyle and obesity together explained 92.1% (78.8% mediation; 13.3% effect modification). Lifestyle factors explained 20.4% of the WHR-PRS/T2D association (3.4% mediation; 17.0% effect modification), and lifestyle and central obesity together explained 72.8% (41.1% mediation; 31.7% effect modification).

Whilst phenotypic adiposity explains a large proportion of the association between BMI-PRS/WHR-PRS and T2D, modifiable lifestyle factors also make contributions. Promoting healthy lifestyles among people prone to adiposity is important in reducing the global burden of T2D.

Until recently, the association between circulating adiponectin (ADPN) levels and the risk of Alzheimer's disease (AD) and Parkinson's disease (PD) remained unclear.

We utilized public data from the IEU GWAS database to conduct a two-sample bidirectional Mendelian randomization (MR) analysis and multiple sensitivity analyses. The MR analysis was performed using the aggregated data, with the genetic risk score (GRS) serving as an instrumental variable.

The MR analyses revealed no significant causal association between genetically determined ADPN levels and the risk of AD (ORIVW = 0.852, 95% confidence interval [CI]: 0.586-1.117, p = 0.235) or PD (ORIVW = 0.830, 95% CI: 0.780-1.156, p = 0.606). Conversely, neither AD nor PD demonstrated any causal association with ADPN levels. The GRS approach yielded similar results (p > 0.05). However, it exhibited a negative correlation with interleukin 1β (IL1β, βIVW = -0.31; 95% CI: -0.55 to -0.07, p = 0.011). The Cochrane's Q test and MR-PRESSO analysis revealed no evidence of pleiotropy.

Our findings provide no evidence to substantiate a causal relationship between ADPN levels and the risk of AD and PD or vice versa. However, elevated levels of ADPN may correlate with lower levels of IL1β.

Previous studies have suggested that elevated urate levels may increase the risk of asthma; however, the nature of this association remains debated. To clarify this uncertainty, we conducted a Mendelian randomization (MR) study to investigate the potential causal relationship.

Summary statistics for urate were sourced from the Global Urate Genetics Consortium (GUGC), and those for asthma were obtained from the FinnGen database. Genetic variants strongly associated with urate were selected as instrumental variables (IVs). Univariable and multivariable MR analyses were conducted to investigate the causal relationship between urate and asthma. Subsequently, network MR analyses were performed to reveal the mediating role of urate in the relationship between body mass index (BMI) and asthma.

The univariable MR analysis showed that urate was associated with an increased risk of asthma (IVW OR = 1.13, 95%CI = 1.04-1.23, p = 0.004). This causal relationship remained consistent in multivariable MR analyses, even after adjusting for potential confounders, including smoking initiation, cigarettes per day, alcohol intake frequency, BMI, allergic rhinitis, and gastroesophageal reflux disease (GERD). Furthermore, network MR analyses demonstrated that the proportion of causal effect between BMI and asthma mediated by urate was 18.05% (95%CI = 6.23%-29.88%).

Our study confirms that serum urate is associated with an increased risk of asthma, suggesting its potential as a target for both prevention and treatment. Additionally, our findings indicate that urate partially mediates the relationship between BMI and asthma, emphasizing its role in the mechanism underlying BMI-induced asthma.

Suicides among Black adults in the United States increased nationally during the COVID-19 pandemic, although limited empirical evidence documents the pathways that explain how suicide risk may develop in this population. We examined experiences of non-organizational religious involvement, gratitude, and loneliness and their relation to suicidal ideation among Black adults in the United States.

We analyzed data from a probability-based sample of 995 Black adults in the United States who completed online surveys from April through June 2022. We recruited participants from the AmeriSpeak panel at the National Opinion Research Center. We applied structural equation modeling techniques to measure direct and indirect associations among religiosity, positive psychology, and mental health variables. We tested whether non-organizational religiosity was indirectly associated with suicidal ideation via feelings of gratitude and COVID-19-specific forms of loneliness during the pandemic.

The measurement model demonstrated a good fit to the data. Structural model results indicated that non-organizational religious involvement was positively related to gratitude (β = 0.51; P < .001); in turn, feelings of gratitude were associated with reduced suicidal ideation (β = -0.12; P = .02). Moreover, COVID-19-specific forms of loneliness were positively associated with past-year suicidal ideation (β = 0.11; P = .01). Non-organizational religious involvement, however, was not directly associated with feelings of COVID-19-related loneliness or suicidal ideation.

Public health officials should account for feelings of gratitude and loneliness as mechanisms that can be leveraged to inform the development of evidence-based suicide prevention interventions for Black adults during public health emergencies such as the COVID-19 pandemic and beyond.

Obesity is a heterogeneous and multifactorial disease with a strong genetic component. While polygenic obesity accounts for most common cases, rare monogenic variants contribute, particularly in severe, early-onset obesity. Among the lesser-studied candidates are UCP3 and PCSK1, genes involved in key metabolic pathways. RECENT FINDINGS: The UCP3 p.Val192Ile (c.574G > A) and PCSK1 p.Asn221Asp (c.661 A > G) variants have been independently associated with metabolic pathways, including fatty acid oxidation and hormone processing, as well as a modestly increased risk of obesity. Clinical and genetic characterization of two patients with severe early-onset obesity revealed the co-occurrence of these variants, which were associated with metabolic disturbances such as insulin resistance. PURPOSE OF THE REVIEW: This narrative review examined the functional and clinical significance of UCP3 and PCSK1 variants in severe obesity, presenting two case reports to illustrate their potential impact. Our findings support a potential model in which rare variants in distinct metabolic genes may interact synergistically to exacerbate disease severity. Further studies are needed to elucidate their combined functional effects and contributions to obesity pathogenesis.

Genetic risk prediction for non-European populations is hindered by limited Genome-Wide Association Study (GWAS) sample sizes and small tuning datasets. We propose JointPRS, a data-adaptive framework that leverages genetic correlations across multiple populations using GWAS summary statistics. It achieves accurate predictions without individual-level tuning data and remains effective in the presence of a small tuning set thanks to its data-adaptive approach. Through extensive simulations and real data applications to 22 quantitative and four binary traits in five continental populations evaluated using the UK Biobank (UKBB) and All of Us (AoU), JointPRS consistently outperforms six state-of-the-art methods across three data scenarios: no tuning data, same-cohort tuning and testing, and cross-cohort tuning and testing. Notably, in the Admixed American population, JointPRS improves lipid trait prediction in AoU by 6.46%-172.00% compared to the other existing methods.

Type 2 diabetes (T2D) and obesity-related traits are highly comorbid with coronavirus disease 2019 (COVID-19), but their causal relationships with disease severity remain unclear. While recent Mendelian randomization (MR) studies suggest a causal link between obesity-related traits and COVID-19 severity, findings regarding T2D are inconsistent, particularly when adjusting for body mass index (BMI). This study aims to clarify these relationships.

We applied various MR methods to assess the causal effects of BMI-adjusted T2D (T2DadjBMI) and obesity-related traits (BMI, waist circumference, and waist-hip ratio) on COVID-19 severity. Genetic instruments were obtained from large-scale genome-wide association studies (GWAS), including 898K participants for T2D and 2M for COVID-19 severity. To address potential bias from sample overlap, we conducted large-scale simulations comparing MR results from overlapping and independent samples.

Our MR analysis identified a significant causal relationship between T2DadjBMI and increased COVID-19 severity (OR = 1.057, 95% CI = 1.012-1.105). Obesity-related traits were also causally associated with COVID-19 severity. Simulations confirmed that MR results remained robust to sample overlap, demonstrating consistency between overlapping and independent datasets.

These findings highlight the causal role of T2D and obesity-related traits in COVID-19 severity, emphasizing the need for targeted prevention and management strategies for high-risk populations. The robustness of our MR analysis, even in the presence of sample overlap, strengthens the reliability of these causal inferences.

Polygenic risk score has become increasingly popular for predicting the value of complex traits. In many settings, polygenic risk score is used as a covariate in regression analysis to study the association between different phenotypes. However, measurement error in polygenic risk score causes attenuation bias in the estimation of regression coefficients. In this paper, we employ a Bayesian approach to accounting for the measurement error of polygenic risk score and correcting the attenuation bias in linear and logistic regression. Through simulation, we show that our approach is able to obtain approximately unbiased estimation of coefficients and credible intervals with correct coverage probability. We also empirically compare our Bayesian measurement error model with the conventional regression model by analyzing real traits in the UK Biobank. The results demonstrate the effectiveness of our approach as it significantly reduces the error in coefficient estimates.

While weight-inclusive approaches are becoming more widely accepted and used in nutrition and dietetics, educators and professionals often lack adequate training. The purpose of this paper is to provide faculty and preceptors with strategies to incorporate weight-inclusive approaches into nutrition and dietetics curricula. We present a framework for demonstrating how students can meet knowledge and competency requirements embedded in courses in nationally accredited nutrition and dietetics programs using a variety of weight-inclusive concepts and learning activities. Providing weight-inclusive approaches is essential for equipping nutrition professionals to offer patient-centered care that minimizes weight stigma and disordered eating.

There are obvious individual differences in the growth and development of Cynoglossus semilaevis, mainly due to female bias. We selected 500 female Cynoglossus semilaevis of different sizes for GWAS and transcriptome analysis to screen for differential genes. qPCR was performed to detect the expression of the genes in various tissues, and RNAi experiments were performed in testicular cells to knock down the grid1 and grid2 genes and transcriptome sequencing was performed to check the changes of the downstream genes. Grid gene was screened for the common genes by GWAS sequencing and transcriptome sequencing. In the QPCR results, the expression of the grid gene family was negatively correlated with fish size, and was slightly higher in males than in females; in the transcriptome results, the expression of shcbp1, sass6, cdca7, and gh was up-regulated, and the expression of igf1 was down-regulated. It is speculated that igf1 has an antagonistic effect on gh, which is deregulated when the grid gene family is knocked down. The grid gene family may affect the growth of individual Cynoglossus semilaevis through the gh-igf1 axis, which provides a basis for the study of the differences in the growth size of Cynoglossus semilaevis.

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.

Recent advances in drug development allowed for the identification of THRβ-selective thyromimetic TG68 as a very promising lipid lowering and anti-amyloid agent. In the current study, we first investigated the neuroprotective effects of TG68 on in vitro human models of neuroinflammation and β-amyloid neurotoxicity in order to expand our knowledge of the therapeutic potential of this novel thyromimetic. Subsequently, we examined metabolic and inflammatory profiles, along with cognitive changes, using a high-fat diet (HFD) mouse model of obesity. Our data demonstrated that TG68 was able to prevent either LPS/TNFα-induced inflammatory response or β-amyloid-induced cytotoxicity in human microglial (HMC3) cells. Next, we demonstrated that in HFD-fed mice, treatment with TG68 (10 mg/kg/day; 2 weeks) significantly reduced anxiety-like behavior in stretch-attend posture (SAP) tests while producing a 12% BW loss and a significant decrease in blood glucose and lipid levels. Notably, these data highlight a close relationship between improved serum metabolic parameters and a reduction of anxious behavior. Moreover, TG68 administration was observed to efficiently counteract HFD-altered central and peripheral expressions in mice with selected biomarkers of metabolic dysfunction, inflammation, and neurotoxicity, revealing promising neuroprotective effects. In conclusion, our work provides preliminary evidence that TG68 may represent a novel therapeutic opportunity for the treatment of interlinked diseases such as obesity and neurodegenerative diseases.

Over the past 30 years, obesity prevalence has markedly increased globally, including among children. Although genome-wide association studies (GWASs) have identified over 1,000 genetic loci associated with obesity-related traits in adults, the genetic architecture of childhood obesity is less well characterized. Moreover, most childhood obesity GWASs have been restricted to severely obese children, in relatively small sample sizes, and in primarily European-ancestry populations. To identify genetic loci associated with early-childhood body mass index (BMI), we performed GWAS of BMI Z scores in eight ancestrally diverse cohorts: ZOE 2.0 cohort, the Santiago Longitudinal Study (SLS), the Vanderbilt University BioVU biobank, the Geisinger MyCode Health Initiative biobank, Study of Latino (SOL) Youth, Pelotas (Brazil) Birth Cohort, Cameron County Hispanic Cohort (CCHC), and Viva La Familia cohort. We subsequently performed inverse-variance-weighted fixed-effect meta-analysis of these results with previously published GWAS summary statistics of BMI Z scores of children in the Early Growth Genetics (EGG) Consortium and the Norwegian Mother and Child Cohort (MoBa), constituting a final total of 84,804 individuals. We identified 39 genome-wide significant loci associated with childhood BMI, including three putatively novel loci (EFNA5 and DTWD2, RP11-2N5.1 on chromosome 5, and LSM14A on chromosome 19). We also observed a dynamic nature of genetic loci-BMI associations across the life course, with distinct effects across childhood and adulthood, highlighting possible critical periods for early-childhood interventions. These findings strengthen calls for larger population-based studies of children across age strata and across diverse populations.

In the domain of swine production, body weight (BW) and average daily gain (ADG) are recognized as the primary performance indicators. Nevertheless, the genetic architecture of ADG and BW in Dongliao black (DLB) pigs remains to be fully elucidated. In this study, we performed a genome-wide association analysis of BW, ADG, and body mass index (BMI) in 358 DLB pigs of different days of age. The genome-wide association study (GWAS) showed the following: (1) The most significant single nucleotide polymorphism (SNP) detected for BW was on Sus scrofa chromosome (SSC) 11:100,808 (p-value = 1.16 × 10-6) that was also the most significant SNP for ADG. (2) The most significant SNP associated with BMI was SSC17:51,463,521 (p-value = 5.16 × 10-8). (3) SNPs SSC10:6,523,844 and SSC17:23,852,682 were identified in both BW and ADG. A meta-analysis was conducted on BW at different days and demonstrated SSC5:39,028,335 (p-value = 8.37 × 10-6) which was not identified in the results of each single trait. The regions of two SNPs (SSC11:100,808, SSC4:10,703,277) exhibited considerable influence on both BW and ADG and the related regions were selected for linkage disequilibrium (LD) analyses that exhibited a notable linkage. In addition, several genes were identified that are associated with obesity and play roles in lipid metabolism, including MACROD2, PHLPP2, CYP2E1, and STT3B.

Despite well-documented associations between Body mass index (BMI) and Osteoarthritis (OA), the specific biological pathways and mediators involved remain poorly understood. This study aims to explore mediators through which BMI influences OA risk, particularly knee osteoarthritis (KOA), using Mendelian Randomization (MR) and mediation analysis.

We used a two-step MR approach with data from the IEU OpenGWAS and FinnGen version 7 databases. BMI (N = 322,154) was the primary exposure, with knee disorders (KD), total bone mineral density (TBMD), metabolic disorders (MD), and anxiety disorders (AD) as potential mediators. Outcomes included KOA (N = 22,347), hip OA (HOA) (N = 11,989), and all OA (AllOA) (N = 50,508). Univariate MR evaluated causal relationships, followed by multivariate MR to quantify mediation effects. Multiple sensitivity analyses were conducted to validate robustness, while horizontal pleiotropy and heterogeneity were assessed using MR-Egger intercept and Cochran's Q statistic.

BMI significantly increased the risk of KOA (odds ratio [OR]: 2.00, 95% confidence interval [CI]: 1.56-2.56), HOA (OR: 2.05, 95% CI: 1.40-2.98), and AllOA (OR: 1.66, 95% CI: 1.41-1.95). KD and TBMD significantly mediated the effect on KOA, with mediation proportions of 20.89% and 3.59%, respectively. MD and AD showed no significant effects. Sensitivity analyses supported the robustness of these findings. Horizontal pleiotropy and heterogeneity tests indicated minimal evidence of bias, supporting the reliability of our results.

BMI increases OA risk, with KD and TBMD partially mediating the effect, particularly for KOA. The direct impact of BMI remains predominant, emphasizing the importance of weight reduction, joint protection, and physical activity as preventive measures.