Discovery Sample Research Articles

Identifying pragmatic solutions to reduce cigarette smoking prevalence in Indigenous North Americans: A sequential exploratory mixed-methods study protocol

Background American Indians and Alaska Natives (AI/AN) have the highest prevalence of cigarette smoking of any race or ethnicity in the United States. Efforts to address smoking prevalence in this population have not historically targeted maintenance of smoking cessation, or behaviors associated with pregnancy. Recent longitudinal cohort studies have identified maintenance of cessation and pregnancy as potential opportunities to address smoking in AI/AN people. Methods To promote success in achieving sustained smoking cessation in AI/AN people, we propose a community engaged sequential exploratory mixed-methods study focused on identifying pragmatic elements of cessation interventions. A discovery sample of 45 AI/AN people will be included in the qualitative study in one of two arms consisting of small groups or one-on-one interviews to develop elements of cessation interventions for evaluation in a discrete choice experiment survey. These one-on-one interviews will characterize the key drivers of smoking relapse and unique experiences of smoking during pregnancy. An additional, independent small group will consist of counselors who engage in smoking cessation counseling. A larger-scale survey will be administered to an AI/AN cohort from Olmsted County, Minnesota (n = 898). Elements of successful interventions will be used to inform a smoking cessation intervention pilot study. Community stakeholders have informed the methods outlined in this protocol, and there is a longitudinal engagement plan for the duration of study. Discussion We outline the methods to understand optimal strategies to promote sustained cigarette smoking cessation and cessation during pregnancy in AI/AN people. This study is critical to inform a pilot intervention aimed at reducing smoking prevalence in AI/AN people.

Plasma proteome and incident myocardial infarction: sex-specific differences.

Few population-based cohort studies, including both men and women, have explored circulating proteins associated with incident myocardial infarction (MI). This study investigated the relationships between circulating cardiometabolic-related proteins and MI risk using cohort-based and Mendelian randomization (MR) analyses and explored potential sex-specific differences. The discovery cohort included 11 751 Swedish adults (55-93 years). Data on 259 proteins assessed with Olink proximity extension assays, biochemical, and questionnaire-based information were used. Participants were followed up for incident MI and death over 8 years through linkage to Swedish registers. Replication analyses were conducted on the UK Biobank sample (n = 51 613). In MR analyses, index cis-genetic variants strongly related to the proteins were used as instrumental variables. Genetic association summary statistic data for MI were obtained from the CARDIoGRAMplusC4D consortium and FinnGen. Forty-five proteins were associated with incident MI in discovery and replication samples following adjustment for potential confounders and multiple testing. In the secondary analysis, 13 of the protein associations were sex-specific, with most associations identified among women. In MR analysis, genetically predicted higher levels of renin, follistatin, and retinoic acid receptor responder protein 2 were linked to an increased risk of MI. Tissue factor pathway inhibitor, tumor necrosis factor receptors 1 and 2, placenta growth factor had an inverse association with MI. This study identified both new and confirmed previously established associations between circulating proteins and incident MI and, for the first time, suggested sex-specific patterns in multiple protein-MI associations.

Newborn adiposity is associated with cord blood DNA methylation at IGF1R and KLF7.

This study aimed to identify whether cord blood DNA methylation at specific loci is associated with neonatal adiposity, a key risk factor for childhood obesity. An epigenome-wide association study was conducted using the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study as a discovery sample. Linear regression models adjusted for maternal and offspring covariates and cell counts were used to analyze associations between neonatal adiposity as measured by sum of three skinfold thicknesses and cord blood DNA methylation. Assays were performed with Illumina EPIC arrays (791,359 CpG sites after quality control). Replication was performed in an independent cohort, Genetics of Glucose regulation in Gestation and Growth (Gen3G). In 2740 HAPO samples, significant associations were identified at 89 CpG sites after accounting for multiple testing (Bonferroni-adjusted p < 0.05). Replication analyses conducted in 139 Gen3G participants confirmed associations for seven CpG sites. These included IGF1R, which encodes a transmembrane receptor involved in cell growth and survival that binds insulin-like growth factor I and insulin, and KLF7, which encodes a regulator of cell proliferation and inhibitor of adipogenesis; both are key regulators of growth during fetal life. These findings support epigenetic mechanisms in the developmental origins of neonatal adiposity and as potential biomarkers of metabolic disease risk.

When politics trumps truth: Political concordance versus veracity as a determinant of believing, sharing, and recalling the news.

Resistance to truth and susceptibility to falsehood threaten democracies around the globe. The present research assesses the magnitude, manifestations, and predictors of these phenomena, while addressing methodological concerns in past research. We conducted a preregistered study with a split-sample design (discovery sample N = 630, validation sample N = 1,100) of U.S. Census-matched online adults. Proponents and opponents of 2020 U.S. presidential candidate Donald Trump were presented with fake and real political headlines ahead of the election. The political concordance of the headlines determined participants' belief in and intention to share news more than the truth of the headlines. This "concordance-over-truth" bias persisted across education levels, analytic reasoning ability, and partisan groups, with some evidence of a stronger effect among Trump supporters. Resistance to true news was stronger than susceptibility to fake news. The most robust predictors of the bias were participants' belief in the relative objectivity of their political side, extreme views about Trump, and the extent of their one-sided media consumption. Interestingly, participants stronger in analytic reasoning, measured with the Cognitive Reflection Task, were more accurate in discerning real from fake headlines when accurate conclusions aligned with their ideology. Finally, participants remembered fake headlines more than real ones regardless of the political concordance of the news story. Discussion explores why the concordance-over-truth bias observed in our study is more pronounced than previous research suggests, and examines its causes, consequences, and potential remedies. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Reproducible Sex Differences in Personalized Functional Network Topography in Youth.

A key step towards understanding psychiatric disorders that disproportionately impact female mental health is delineating the emergence of sex-specific patterns of brain organization at the critical transition from childhood to adolescence. Prior work suggests that individual differences in the spatial organization of functional brain networks across the cortex are associated with psychopathology and differ systematically by sex. We aimed to evaluate the impact of sex on the spatial organization of person-specific functional brain networks. We leveraged person-specific atlases of functional brain networks defined using nonnegative matrix factorization in a sample of n = 6437 youths from the Adolescent Brain Cognitive Development Study. Across independent discovery and replication samples, we used generalized additive models to uncover associations between sex and the spatial layout ("topography") of personalized functional networks (PFNs). Next, we trained support vector machines to classify participants' sex from multivariate patterns of PFN topography. Finally, we leveraged transcriptomic data from the Allen Human Brain Atlas to evaluate spatial correlations between sex differences in PFN topography and gene expression. Sex differences in PFN topography were greatest in association networks including the fronto-parietal, ventral attention, and default mode networks. Machine learning models trained on participants' PFNs were able to classify participant sex with high accuracy. Brain regions with the greatest sex differences in PFN topography were enriched in expression of X-linked genes as well as genes expressed in astrocytes and excitatory neurons. Sex differences in PFN topography are robust, replicate across large-scale samples of youth, and are associated with expression patterns of X-linked genes. These results suggest a potential contributor to the female-biased risk in depressive and anxiety disorders that emerge at the transition from childhood to adolescence.

Lifetime depression and mania/hypomania risk predicted by neural markers in three independent young adult samples during working memory and emotional regulation.

Objective markers of pathophysiological processes underlying lifetime depression and mania/hypomania risk can provide biologically informed targets for novel interventions to help prevent the onset of affective disorders in individuals with subsyndromal symptoms. Greater activity within and functional connectivity (FC) between the central executive network (CEN), supporting emotional regulation (ER) subcomponent processes such as working memory (WM), the default mode network (DMN), supporting self-related information processing, and the salience network (SN), is thought to interfere with cognitive functioning and predispose to depressive disorders. Using an emotional n-back paradigm designed to examine WM and ER capacity, we examined in young adults: (1) relationships among activity and FC in these networks and lifetime depression and mania/hypomania risk; (2) the extent to which these relationships were specific to lifetime depression risk versus lifetime mania/hypomania risk; (3) whether findings in a first, Discovery sample n = 101, 63 female, age = 23.85 (2.9) could be replicated in a two independent Test samples of young adults: Test sample 1: n = 90, 60 female, age = 21.7 (2.0); Test sample 2: n = 96, 65 female, age = 21.6 (2.1). The Mood Spectrum Self-Report (MOODS-SR-L) assessed lifetime mania/hypomania risk and depression risk. We showed significant clusters of activity to each contrast in similar locations in the anatomic mask in each Test sample as in the Discovery sample, and, using extracted mean BOLD signal from these clusters as IVs, we showed similar patterns of IV-DV relationships in each Test sample as in the Discovery sample. Specifically, in the Discovery sample, greater DMN activity during WM was associated with greater lifetime depression risk. This finding was specific to depression and replicated in both independent samples (all ps<0.05 qFDR). Greater CEN activity during ER was associated with increased lifetime depression risk and lifetime mania/hypomania risk in all three samples (all ps< 0.05 qFDR). These replicated findings provide promising objective, neural markers to better identify, and guide and monitor early interventions for, depression and mania/hypomania risk in young adults.

Inflammation and prediction of death in type 2 diabetes. Evidence of an intertwined link with tryptophan metabolism.

To study whether inflammation is associated with and helps predict mortality risk in patients with type 2 diabetes. To explore the intertwined link between inflammation and tryptophan metabolism on death risk. Two prospective cohorts: the aggregate Gargano Mortality Study (1,731 individuals; 872 all-cause deaths) as discovery sample, the Foggia Mortality Study (490 individuals; 256 deaths) as validation sample. Twenty-seven inflammatory markers were measured. Causal mediation analysis and in vitro studies were carried out to explore the link between inflammatory markers and the kynurenine-to-tryptophan ratio (KTR) in shaping mortality risk. Using multivariable stepwise Cox regression analysis, IL-4, IL-6, IL-8, IL-13, RANTES and IP-10, were independently associated with death. An inflammation score (I-score) comprising these six molecules is strongly associated with death in both the discovery and the validation cohorts HR (95%CI) = 2.13 (1.91-2.37) and 2.20 (1.79-2.72), respectively. The I-score improved discrimination and reclassification measures (all P<0.01) of two mortality prediction models based on clinical variables. The causal mediation analysis showed that 28% of the KTR effect on mortality was mediated by IP-10. Studies in cultured endothelial cells showed that 5-Methoxy-tryptophan, an anti-inflammatory metabolite derived from tryptophan, reduces the expression of IP-10, thus providing a functional basis for the observed causal mediation. Adding the I-score to clinical prediction models may help identify individuals who are at greater risk of death. Deeply addressing the intertwined relationship between low-grade inflammation and imbalanced tryptophan metabolism in shaping mortality risk may help discover new therapies targeting patients characterized by these abnormalities.

Impact of NPSR1 gene variation on the neural correlates of phasic and sustained fear in spider phobia-an imaging genetics and independent replication approach.

The functional neuropeptide S receptor 1 (NPSR1) gene A/T variant (rs324981) is associated with fear processing. We investigated the impact of NPSR1 genotype on fear processing and on symptom reduction following treatment in individuals with spider phobia. A replication approach was applied [discovery sample: Münster (MS) nMS = 104; replication sample Würzburg (WZ) nWZ = 81]. Participants were genotyped for NPSR1 rs324981 [T-allele carriers (risk) versus AA homozygotes (no-risk)]. A sustained and phasic fear paradigm was applied during functional magnetic resonance imaging. A one-session virtual reality exposure treatment was conducted. Change of symptom severity from pre to post treatment and within session fear reduction were assessed. T-allele carriers in the discovery sample displayed lower anterior cingulate cortex (ACC) activation compared to AA homozygotes independent of condition. For sustained fear, this effect was replicated within a small cluster and medium effect size. No association with symptom reduction was found. Within-session fear reduction was negatively associated with ACC activation in T-allele carriers in the discovery sample. NPSR1 rs324981 genotype might be associated with fear processing in the ACC in spider phobia. Interpretation as potential risk-increasing function of the NPSR1 rs324981 T-allele via impaired top-down control of limbic structures remains speculative. Potential association with symptom reduction warrants further research.

Maternal smoking DNA methylation risk score associated with health outcomes in offspring of European and South Asian ancestry

Background:Maternal smoking has been linked to adverse health outcomes in newborns but the extent to which it impacts newborn health has not been quantified through an aggregated cord blood DNA methylation (DNAm) score. Here, we examine the feasibility of using cord blood DNAm scores leveraging large external studies as discovery samples to capture the epigenetic signature of maternal smoking and its influence on newborns in White European and South Asian populations.Methods:We first examined the association between individual CpGs and cigarette smoking during pregnancy, and smoking exposure in two White European birth cohorts (n=744). Leveraging established CpGs for maternal smoking, we constructed a cord blood epigenetic score of maternal smoking that was validated in one of the European-origin cohorts (n=347). This score was then tested for association with smoking status, secondary smoking exposure during pregnancy, and health outcomes in offspring measured after birth in an independent White European (n=397) and a South Asian birth cohort (n=504).Results:Several previously reported genes for maternal smoking were supported, with the strongest and most consistent association signal from the GFI1 gene (6 CpGs with p&lt;5 × 10-5). The epigenetic maternal smoking score was strongly associated with smoking status during pregnancy (OR = 1.09 [1.07, 1.10], p=5.5 × 10-33) and more hours of self-reported smoking exposure per week (1.93 [1.27, 2.58], p=7.8 × 10-9) in White Europeans. However, it was not associated with self-reported exposure (p&gt;0.05) among South Asians, likely due to a lack of smoking in this group. The same score was consistently associated with a smaller birth size (–0.37±0.12 cm, p=0.0023) in the South Asian cohort and a lower birth weight (–0.043±0.013 kg, p=0.0011) in the combined cohorts.Conclusions:This cord blood epigenetic score can help identify babies exposed to maternal smoking and assess its long-term impact on growth. Notably, these results indicate a consistent association between the DNAm signature of maternal smoking and a small body size and low birth weight in newborns, in both White European mothers who exhibited some amount of smoking and in South Asian mothers who themselves were not active smokers.Funding:This study was funded by the Canadian Institutes of Health Research Metabolomics Team Grant: MWG-146332.

Maternal smoking DNA methylation risk score associated with health outcomes in offspring of European and South Asian ancestry.

Maternal smoking has been linked to adverse health outcomes in newborns but the extent to which it impacts newborn health has not been quantified through an aggregated cord blood DNA methylation (DNAm) score. Here, we examine the feasibility of using cord blood DNAm scores leveraging large external studies as discovery samples to capture the epigenetic signature of maternal smoking and its influence on newborns in White European and South Asian populations. We first examined the association between individual CpGs and cigarette smoking during pregnancy, and smoking exposure in two White European birth cohorts (n=744). Leveraging established CpGs for maternal smoking, we constructed a cord blood epigenetic score of maternal smoking that was validated in one of the European-origin cohorts (n=347). This score was then tested for association with smoking status, secondary smoking exposure during pregnancy, and health outcomes in offspring measured after birth in an independent White European (n=397) and a South Asian birth cohort (n=504). Several previously reported genes for maternal smoking were supported, with the strongest and most consistent association signal from the GFI1 gene (6 CpGs with p<5 × 10-5). The epigenetic maternal smoking score was strongly associated with smoking status during pregnancy (OR = 1.09 [1.07, 1.10], p=5.5 × 10-33) and more hours of self-reported smoking exposure per week (1.93 [1.27, 2.58], p=7.8 × 10-9) in White Europeans. However, it was not associated with self-reported exposure (p>0.05) among South Asians, likely due to a lack of smoking in this group. The same score was consistently associated with a smaller birth size (-0.37±0.12 cm, p=0.0023) in the South Asian cohort and a lower birth weight (-0.043±0.013 kg, p=0.0011) in the combined cohorts. This cord blood epigenetic score can help identify babies exposed to maternal smoking and assess its long-term impact on growth. Notably, these results indicate a consistent association between the DNAm signature of maternal smoking and a small body size and low birth weight in newborns, in both White European mothers who exhibited some amount of smoking and in South Asian mothers who themselves were not active smokers. This study was funded by the Canadian Institutes of Health Research Metabolomics Team Grant: MWG-146332.

Causality between migraine and cardiovascular disease: a bidirectional Mendelian randomization study

BackgroundWhile growing evidence suggests a relationship between migraine and cardiovascular disease, the genetic evidence for a causal relationship between migraine and cardiovascular disease is still scarce. Investigating the causal association between migraine and cardiovascular disease is vital.MethodsWe carried out a bidirectional Mendelian randomization (MR) study including discovery samples and replication samples using publicly available genome-wide association study (GWAS) summary datasets and stringent screening instrumental variables. Four different MR techniques—Inverse variance weighted (IVW), MR ‒Egger, weighted median, and weighted mode—as well as various sensitivity analyses—Cochran’s Q, IVW radial, leave-one-out (LOO), and MR-PRESSO—were utilized to investigate the causal relationship between cardiovascular disease and migraine.ResultsThe protective causal effects of genetically predicted migraine on coronary artery disease (OR, 0.881; 95% CI 0.790–0.982; p = 0.023) and ischemic stroke (OR, 0.912; 95% CI 0.854–0.974; p = 0.006) were detected in forward MR analysis but not in any other cardiovascular disease. Consistently, we also discovered protective causal effects of coronary atherosclerosis (OR, 0.865; 95% CI 0.797–0.940; p = 0.001) and myocardial infarction (OR, 0.798; 95% CI 0.668–0.952; p = 0.012) on migraine in reverse MR analysis.ConclusionWe found a potential protective effect of migraine on coronary artery disease and ischemic stroke and a potential protective effect of coronary atherosclerosis and myocardial infarction on migraine. We emphasised epidemiological and genetic differences and the need for long-term safety monitoring of migraine medications and future research to improve cardiovascular outcomes in migraine patients.

Polygenic prediction of major depressive disorder and related traits in African ancestries UK Biobank participants.

Genome-Wide Association Studies (GWAS) over-represent European ancestries, neglecting all other ancestry groups and low-income nations. Consequently, polygenic risk scores (PRS) more accurately predict complex traits in Europeans than African Ancestries groups. Very few studies have looked at the transferability of European-derived PRS for behavioural and mental health phenotypes to Africans. We assessed the comparative accuracy of depression PRS trained on European and African Ancestries GWAS studies to predict major depressive disorder (MDD) and related traits in African ancestry participants from the UK Biobank. UK Biobank participants were selected based on Principal component analysis clustering with an African genetic similarity reference population, MDD was assessed with the Composite International Diagnostic Interview (CIDI). PRS were computed using PRSice2 software using either European or African Ancestries GWAS summary statistics. PRS trained on European ancestry samples (246,363 cases) predicted case control status in Africans of the UK Biobank with similar accuracies (R2 = 2%, β = 0.32, empirical p-value = 0.002) to PRS trained on far much smaller samples of African Ancestries participants from 23andMe, Inc. (5045 cases, R² = 1.8%, β = 0.28, empirical p-value = 0.008). This suggests that prediction of MDD status from Africans to Africans had greater efficiency relative to discovery sample size than prediction of MDD from Europeans to Africans. Prediction of MDD status in African UK Biobank participants using GWAS findings of likely causal risk factors from European ancestries was non-significant. GWAS of MDD in European ancestries are inefficient for improving polygenic prediction in African samples; urgent MDD studies in Africa are needed.

Plasma proteins associated with plant-based diets: Results from the Atherosclerosis Risk in Communities (ARIC) study and Framingham Heart Study (FHS)

Background & AimsPlant-based diets are associated with a lower risk of chronic diseases. Large-scale proteomics can identify objective biomarkers of plant-based diets, and can improve our understanding of the pathways that link plant-based diets to health outcomes. This study investigated the plasma proteome of four different plant-based diets [overall plant-based diet (PDI), provegetarian diet, healthful plant-based diet (hPDI), and unhealthful plant-based diet (uPDI)] in the Atherosclerosis Risk in Communities (ARIC) Study and replicated the findings in the Framingham Heart Study (FHS) Offspring cohort. MethodsARIC Study participants at visit 3 (1993-1995) with completed food frequency questionnaire (FFQ) data and proteomics data were divided into internal discovery (n=7,690) and replication (n=2,543) data sets. Multivariable linear regression was used to examine associations between plant-based diet indices (PDIs) and 4,955 individual proteins in the discovery sample. Then, proteins that were internally replicated in the ARIC Study were tested for external replication in FHS (n=1,358). Pathway overrepresentation analysis was conducted for diet-related proteins. C-statistics were used to predict if the proteins improved prediction of plant-based diet indices beyond participant characteristics. ResultsIn ARIC discovery, a total of 837 diet-protein associations (PDI=233; provegetarian=182; hPDI=406; uPDI=16) were observed at false discovery rate (FDR) <0.05. Of these, 453 diet-protein associations (PDI=132; provegetarian=104; hPDI=208; uPDI=13) were internally replicated. In FHS, 167/453 diet-protein associations were available for external replication, of which 8 proteins (PDI=1; provegetarian=0; hPDI=8; uPDI=0) replicated. Complement and coagulation cascades, cell adhesion molecules, and retinol metabolism were over-represented. C-C motif chemokine 25 for PDI and 8 proteins for hPDI modestly but significantly improved the prediction of these indices individually and collectively (P value for difference in C-statistics<0.05 for all tests) ConclusionsUsing large-scale proteomics, we identified potential candidate biomarkers of plant-based diets, and pathways that may partially explain the associations between plant-based diets and chronic conditions.

The impact of consanguinity on the design of iPSC banks

The effect of consanguinity on identifying universal induced pluripotent stem cell (iPSC) donors, i.e., homozygous for the major human leukocyte antigen (HLA) loci, is unknown. The discovery sample size was calculated in a consanguineous population using a method (1qF) based on the inbreeding coefficient. The result was orders of magnitude smaller compared to the standard method.

Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Estimating substance use disparities across intersectional social positions using machine learning: An application of group-lasso interaction network.

An aim of quantitative intersectional research is to model the joint impact of multiple social positions on health risk behaviors. Although moderated multiple regression is frequently used to pursue intersectional research hypotheses, such parametric approaches may produce unreliable effect estimates due to data sparsity and high dimensionality. Machine learning provides viable alternatives, offering greater flexibility in evaluating many candidate interactions amid sparse data conditions, yet remains rarely employed. This study introduces group-lasso interaction network (glinternet), a novel machine learning approach involving hierarchical regularization, to assess intersectional differences in substance use prevalence. Utilizing variable selection and parameter stabilization functionality for main and interaction effects, glinternet was employed to examine two-way interactions between three primary social positions (gender, sexual orientation, and race) predicting heavy episodic drinking, cannabis use, and cigarette use prevalence. Analyses were conducted using the All of Us Research Program (N = 283,403), a national sample with high representation from populations historically underrepresented in biomedical research. Results were replicated using holdout cross-validation and compared against logistic regression estimates. Glinternet prevalence estimates were more stable across discovery and replication samples relative to logistic regression, particularly among sparsely represented groups. Prevalence estimates for cigarette and cannabis use were elevated among sexual minority and White cisgender women compared to heterosexual and non-White women, respectively. Glinternet may improve upon traditional moderated multiple regression methods for pursuing intersectional hypotheses by improving model parsimony and parameter stability, providing novel means for quantifying health disparities among intersectional social positions. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Associations between polygenic risk scores for cardiometabolic phenotypes and adolescent depression and body dissatisfaction.

Adolescents with elevated body mass index (BMI) are at an increased risk for depression and body dissatisfaction. Type 2 diabetes (T2D) is an established risk factor for depression. However, shared genetic risk between cardiometabolic conditions and mental health outcomes remains understudied in youth. The current study examined associations between polygenic risk scores (PRS) for BMI and T2D, and symptoms of depression and body dissatisfaction, in a sample of 827 community adolescents (Mage = 13.63, SDage = 1.01; 76% girls). BMI, depressive symptoms, and body dissatisfaction were assessed using validated self-report questionnaires. BMI-PRS was associated with phenotypic BMI (β = 0.24, p < 0.001) and body dissatisfaction (β = 0.17, p < 0.001), but not with depressive symptoms. The association between BMI-PRS and body dissatisfaction was significantly mediated by BMI (indirect effect = 0.10, CI [0.07-0.13]). T2D-PRS was not associated with depression or body dissatisfaction. The results suggest phenotypic BMI may largely explain the association between genetic risk for elevated BMI and body dissatisfaction in adolescents. Further research on age-specific genetic effects is needed, as summary statistics from adult discovery samples may have limited utility in youth. The association between genetic risk for elevated BMI and body dissatisfaction in adolescents may be largely explained by phenotypic BMI, indicating a potential pathway through which genetic predisposition influences body image perception. Furthermore, age-specific genetic research is needed to understand the unique influences on health outcomes during adolescence. By identifying BMI as a potential mediator in the association between genetic risk for elevated BMI and body dissatisfaction, the current findings offer insights that could inform interventions targeting body image concerns and mental health in this population.

The causal relationship between autoimmune diseases and age-related macular degeneration: A two-sample mendelian randomization study.

The aim of this study is to investigate the potential causal relationship between autoimmune diseases, including systemic lupus erythematosus, rheumatoid arthritis, inflammatory bowel disease, multiple sclerosis, and Type 1 diabetes, and age-related macular degeneration (AMD). By utilizing the two-sample Mendelian Randomization (MR) approach, we endeavor to address this complex medical issue. Genome-wide association study (GWAS) data for autoimmune diseases and AMD were obtained from the IEU Open GWAS database and the FinnGen consortium. A series of stringent SNP filtering steps was applied to ensure the reliability of the genetic instruments. MR analyses were conducted using the TwoSampleMR and MR-PRESSO packages in R. The inverse-variance weighted (IVW) method served as the primary analysis, complemented by multiple supplementary analyses and sensitivity tests. Within the discovery sample, only a statistically significant inverse causal relationship between multiple sclerosis (MS) and AMD was observed (OR = 0.92, 95% CI: 0.88-0.97, P = 0.003). This finding was confirmed in the replication sample (OR = 0.85, 95% CI: 0.80-0.89, P = 3.32×10-12). No statistically significant associations were detected between systemic lupus erythematosus, rheumatoid arthritis, inflammatory bowel disease, and Type 1 diabetes and AMD. Strong evidence is provided by this study to support the existence of an inverse causal relationship between multiple sclerosis and age-related macular degeneration. However, no causal evidence was found linking other autoimmune diseases with AMD. These findings not only offer novel insights into the potential etiological mechanisms underlying AMD but also suggest possible directions for future clinical interventions.

Assessing Causal Relationships Between Periodontitis and Non-alcoholic Fatty Liver Disease: A Two-Sample Bidirectional Mendelian Randomisation Study.

To investigate the causality between periodontitis and non-alcoholic fatty liver disease (NAFLD) using a two-sample bidirectional Mendelian randomisation (MR) analysis. Genetic variations in periodontitis and NAFLD were acquired from genome-wide association studies (GWAS) using the Gene-Lifestyle Interaction in Dental Endpoints, a large-scale meta-analysis, and FinnGen consortia. Data from the first two databases were used to explore the causal relationship between periodontitis and NAFLD ("discovery stage"), and the data from FinnGen was used to validate our results ("validation stage"). We initially performed MR analysis using 5 single nucleotide polymorphisms (SNPs) in the discovery samples and 18 in the replicate samples as genetic instruments for periodontitis to investigate the causative impact of periodontitis on NAFLD. We then conducted a reverse MR analysis using 6 SNPs in the discovery samples and 4 in the replicate samples as genetic instruments for NAFLD to assess the causative impact of NAFLD on periodontitis. We further implemented heterogeneity and sensitivity analyses to assess the reliability of the MR results. Periodontitis was not causally related to NAFLD (odds ratio [OR] = 1.036, 95% CI: 0.914-1.175, p = 0.578 in the discovery stage; OR = 1.070, 95% CI: 0.935-1.224, p = 0.327 in the validation stage), and NAFLD was not causally linked with periodontitis (OR = 1.059, 95% CI: 0.916-1.225, p = 0.439 in the discovery stage; OR = 0.993, 95% CI: 0.896-1.102, p = 0.901 in the validation stage). No heterogeneity was observed among the selected SNPs. Sensitivity analyses demonstrated the absence of pleiotropy and the reliability of our MR results. The present MR analysis showed no genetic evidence for a cause-and-effect relationship between periodontitis and NAFLD. Periodontitis may not directly influence the development of NAFLD and vice versa.

MYLK*FLNB and DOCK1*LAMA2 gene-gene interactions associated with rheumatoid arthritis in the focal adhesion pathway.

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease caused by a combination of genetic and environmental factors. Rare variants with low predicted effects in genes participating in the same biological function might be involved in developing complex diseases such as RA. From whole-exome sequencing (WES) data, we identified genes containing rare non-neutral variants with complete penetrance and no phenocopy in at least one of nine French multiplex families. Further enrichment analysis highlighted focal adhesion as the most significant pathway. We then tested if interactions between the genes participating in this function would increase or decrease the risk of developing RA disease. The model-based multifactor dimensionality reduction (MB-MDR) approach was used to detect epistasis in a discovery sample (19 RA cases and 11 healthy individuals from 9 families and 98 unrelated CEU controls from the International Genome Sample Resource). We identified 9 significant interactions involving 11 genes (MYLK, FLNB, DOCK1, LAMA2, RELN, PIP5K1C, TNC, PRKCA, VEGFB, ITGB5, and FLT1). One interaction (MYLK*FLNB) increasing RA risk and one interaction decreasing RA risk (DOCK1*LAMA2) were confirmed in a replication sample (200 unrelated RA cases and 91 GBR unrelated controls). Functional and genomic data in RA samples or relevant cell types argue the key role of these genes in RA.