Predicting physical activity by the personality styles of the five-factor model.

OBJECTIVE: Low neuroticism, high extraversion, and high conscientiousness are related to physical activity (PA). We tested whether the small size and heterogeneity of these relationships result because personality traits influence one another as well as because some narrow facets rather than the broad domains contain more specific variance relevant to PA. METHOD: Participants were men and women enrolled in the University of North Carolina Alumni Heart Study who completed the Revised NEO Personality Inventory (NEO-PI-R) and reported their past month's average activity on an 8-point scale. In Study 1, we examined prospective correlations between the five NEO-PI-R domains and PA. In Studies 2 and 3, we used multinomial logistic regression to examine associations between PA and trait pair combinations (personality styles) controlling for age, sex, educational achievement, relationship status, and depression. RESULTS: Study 1 revealed that lower neuroticism (N) and agreeableness (A) and higher conscientiousness (C) predicted more PA. Taken together, Studies 2 and 3 found that the combination of high Extraversion (E) and high openness (O) was related to higher PA and that combinations of low E and high A and low E and low C were related to lower PA. Study 3, which examined the activity facet of E (E4), found that E4 is an important driver of E-PA associations. CONCLUSIONS: Personality traits do not operate in isolation. They may influence how other traits are expressed and such nonadditive effects can impact PA. Assessment of personality styles could help to identify individuals at risk for PA avoidance and may be useful for developing personalized interventions. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Associations among NMR-measured inflammatory and metabolic biomarkers and accelerated aging in cardiac catheterization patients.

Research into aging has grown substantially with the creation of molecular biomarkers of biological age that can be used to determine age acceleration. Concurrently, nuclear magnetic resonance (NMR) assessment of biomarkers of inflammation and metabolism provides researchers with new ways to examine intermediate risk factors for chronic disease. We used data from a cardiac catheterization cohort to examine associations between biomarkers of cardiometabolic health and accelerated aging assessed using both gene expression (Transcriptomic Age) and DNA methylation (Hannum Age, GrimAge, Horvath Age, and Phenotypic Age). Linear regression models were used to associate accelerated aging with each outcome (cardiometabolic health biomarkers) while adjusting for chronological age, sex, race, and neighborhood socioeconomic status. Our study shows a robust association between GlycA and GrimAge (5.71, 95% CI = 4.36, 7.05, P = 7.94 × 10-16), Hannum Age (1.81, 95% CI = 0.65, 2.98, P = 2.30 × 10-3), and Phenotypic Age (2.88, 95% CI = 1.91, 3.87, P = 1.21 × 10-8). We also saw inverse associations between apolipoprotein A-1 and aging biomarkers. These associations provide insight into the relationship between aging and cardiometabolic health that may be informative for vulnerable populations.

Longitudinal Patterns of Multimorbidity in Gulf War Era Veterans With and Without Gulf War Illness.

Objectives: To examine whether severe Gulf War illness (SGWI) case status was associated with longitudinal multimorbidity patterns. Methods: Participants were users of the Veteran Health Administration Health Care System drawn from the Gulf War Era Cohort and Biorepository (n = 840). Longitudinal measures of multimorbidity were constructed using (1) electronic health records (Charlson Comorbidity Index; Elixhauser; and Veterans Affairs Frailty Index) from 10/1/1999 to 6/30/2023 and (2) self-reported medical conditions (Deficit Accumulation Index) since the war until the survey date. Accelerated failure time models examined SGWI case status as a predictor of time until threshold level of multimorbidity was reached, adjusted for age and sociodemographic and military characteristics. Results: Models, adjusted for covariates, revealed that (1) relative to the SWGI- group, the SGWI+ group was associated with an accelerated time for reaching each threshold and (2) the relationship between SGWI and each threshold was not moderated by age. Discussion: Findings suggest that veterans with SGWI experienced accelerated aging.

Genome-Wide Genetic Analysis of Dropout in a Controlled Exercise Intervention in Sedentary Adults With Overweight or Obesity and Cardiometabolic Disease.

BACKGROUND: Despite the benefits of exercise, many individuals are unable or unwilling to adopt an exercise intervention. PURPOSE: The purpose of this analysis was to identify putative genetic variants associated with dropout from exercise training interventions among individuals in the STRRIDE trials. METHODS: We used a genome-wide association study approach to identify genetic variants in 603 participants initiating a supervised exercise intervention. Exercise intervention dropout occurred when a subject withdrew from further participation in the study or was otherwise lost to follow-up. RESULTS: Exercise intervention dropout was associated with a cluster of single-nucleotide polymorphisms with the top candidate being rs722069 (T/C, risk allele = C) (unadjusted p = 2.2 × 10-7, odds ratio = 2.23) contained within a linkage disequilibrium block on chromosome 16. In Genotype-Tissue Expression, rs722069 is an expression quantitative trait locus of the EARS2, COG7, and DCTN5 genes in skeletal muscle tissue. In subsets of the STRRIDE genetic cohort with available muscle gene expression (n = 37) and metabolic data (n = 82), at baseline the C allele was associated with lesser muscle expression of EARS2 (p < .002) and COG7 (p = .074) as well as lesser muscle concentrations of C2- and C3-acylcarnitines (p = .026). CONCLUSIONS: Our observations imply that exercise intervention dropout is genetically moderated through alterations in gene expression and metabolic pathways in skeletal muscle. Individual genetic traits may allow the development of a biomarker-based approach for identifying individuals who may benefit from more intensive counseling and other interventions to optimize exercise intervention adoption. CLINICAL TRIAL INFORMATION: STRRIDE I = NCT00200993; STRRIDE AT/RT = NCT00275145; STRRIDE-PD = NCT00962962.

Regular participation in exercise can provide a myriad of health benefits. Although individuals recognize these benefits, many are unable or unwilling to adopt an exercise intervention once initiated. The purpose of this analysis was to identify genetic variants associated with dropout from an exercise training intervention. We found exercise intervention dropout to be genetically moderated through changes in gene expression and metabolic pathways in muscle. Thus, individual genetic traits may allow for the development of a biomarker-based targeted approach for identifying individuals who may benefit from more intensive counseling and interventions to optimize the adoption of an exercise intervention program.

The Million Veteran Program 1990-1991 Gulf War Era Survey: An Evaluation of Veteran Response, Characteristics, and Representativeness of the Gulf War Era Veteran Population.

To address gaps in understanding the pathophysiology of Gulf War Illness (GWI), the VA Million Veteran Program (MVP) developed and implemented a survey to MVP enrollees who served in the U.S. military during the 1990-1991 Persian Gulf War (GW). Eligible Veterans were invited via mail to complete a survey assessing health conditions as well as GW-specific deployment characteristics and exposures. We evaluated the representativeness of this GW-era cohort relative to the broader population by comparing demographic, military, and health characteristics between respondents and non-respondents, as well as with all GW-era Veterans who have used Veterans Health Administration (VHA) services and the full population of U.S. GW-deployed Veterans. A total of 109,976 MVP GW-era Veterans were invited to participate and 45,270 (41%) returned a completed survey. Respondents were 84% male, 72% White, 8% Hispanic, with a mean age of 61.6 years (SD = 8.5). Respondents were more likely to be older, White, married, better educated, slightly healthier, and have higher socioeconomic status than non-respondents, but reported similar medical conditions and comparable health status. Although generally similar to all GW-era Veterans using VHA services and the full population of U.S. GW Veterans, respondents included higher proportions of women and military officers, and were slightly older. In conclusion, sample characteristics of the MVP GW-era cohort can be considered generally representative of the broader GW-era Veteran population. The sample represents the largest research cohort of GW-era Veterans established to date and provides a uniquely valuable resource for conducting in-depth studies to evaluate health conditions affecting 1990-1991 GW-era Veterans.

Military exposures and Gulf War illness in veterans with and without posttraumatic stress disorder.

Gulf War illness (GWI) is a chronic multisymptom disorder of unknown etiology that is believed to be caused by neurotoxicant exposure experienced during deployment to the Gulf War. Posttraumatic stress disorder (PTSD) covaries with GWI and is believed to play a role in GWI symptoms. The present study examined the association between self-reported military exposures and GWI, stratified by PTSD status, in veterans from the Gulf War Era Cohort and Biorepository who were deployed to the Persian Gulf during the war. Participants self-reported current GWI and PTSD symptoms as well as military exposures (e.g., pyridostigmine [PB] pills, pesticides/insecticides, combat, chemical attacks, and oil well fires) experienced during the Gulf War. Deployed veterans' (N = 921) GWI status was ascertained using the Centers for Disease Control and Prevention definition. Individuals who met the GWI criteria were stratified by PTSD status, yielding three groups: GWI-, GWI+/PTSD-, and GWI+/PTSD+. Multivariable logistic regression, adjusted for covariates, was used to examine associations between GWI/PTSD groups and military exposures. Apart from insect bait use, the GWI+/PTSD+ group had higher odds of reporting military exposures than the GWI+/PTSD- group, adjusted odds ratio (aOR) = 2.15, 95% CI [1.30, 3.56]-aOR = 6.91, 95% CI [3.39, 14.08]. Except for PB pills, the GWI+/PTSD- group had a higher likelihood of reporting military exposures than the GWI- group, aOR = 2.03, 95% CI [1.26, 3.26]-aOR = 4.01, 95% CI [1.57, 10.25]. These findings are consistent with roles for both PTSD and military exposures in the etiology of GWI.

Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations.

Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expand PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS are 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1681-3651 cases and 8696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They are significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values < 0.05). Further inclusion of non-European ancestry populations, especially Black/African American and Latinx/Hispanic, is needed to improve the risk prediction and enhance equity in applying PRS in clinical practice.

GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors.

OBJECTIVE: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and cross-validated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS meta-analysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. METHODS: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. RESULTS: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values <5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors. CONCLUSIONS: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.

Association of Atherosclerotic Cardiovascular Disease, Hypertension, Diabetes, and Hyperlipidemia With Gulf War Illness Among Gulf War Veterans.

BACKGROUND: Approximately 30% of the 700 000 Gulf War veterans report a chronic symptom-based illness of varying severity referred to as Gulf War illness (GWI). Toxic deployment-related exposures have been implicated in the cause of GWI, some of which contribute to metabolic dysregulation and lipid abnormalities. As this cohort ages, the relationship between GWI and atherosclerotic cardiovascular disease (ASCVD) is a growing concern. We evaluated associations between GWI and ASCVD, diabetes, hyperlipidemia, and hypertension in veterans of the Gulf War (1990-1991). METHODS AND RESULTS: Analysis of survey data collected in 2014 to 2016 from a national sample of deployed Gulf War veterans (n=942) and Veterans Health Administration electronic health record data (n=669). Multivariable logistic regression models tested for associations of GWI with self-reported ASCVD, diabetes, hyperlipidemia, and hypertension, controlling for confounding factors. Separate models tested for GWI associations with ASCVD and risk factors documented in the electronic health record. GWI was associated with self-reported hypertension (adjusted odds ratio [aOR], 1.67 [95% CI, 1.18-2.36]), hyperlipidemia (aOR, 1.46 [95% CI, 1.03-2.05]), and ASCVD (aOR, 2.65 [95% CI, 1.56-4.51]). In the subset of veterans with electronic health record data, GWI was associated with documented diabetes (aOR, 2.34 [95% CI, 1.43-3.82]) and hypertension (aOR, 2.84 [95% CI, 1.92-4.20]). Hyperlipidemia and hypertension served as partial mediators of the association between GWI and self-reported ASCVD. CONCLUSIONS: Gulf War veterans with GWI had higher odds of hyperlipidemia, hypertension, diabetes, and ASCVD compared with Gulf War veterans without GWI. Further examination of the mechanisms underlying this association, including a possible shared exposure-related mechanism, is necessary.

Modeling the longitudinal changes of ancestry diversity in the Million Veteran Program.

BACKGROUND: The Million Veteran Program (MVP) participants represent 100 years of US history, including significant social and demographic changes over time. Our study assessed two aspects of the MVP: (i) longitudinal changes in population diversity and (ii) how these changes can be accounted for in genome-wide association studies (GWAS). To investigate these aspects, we divided MVP participants into five birth cohorts (N-range = 123,888 [born from 1943 to 1947] to 136,699 [born from 1948 to 1953]). RESULTS: Ancestry groups were defined by (i) HARE (harmonized ancestry and race/ethnicity) and (ii) a random-forest clustering approach using the 1000 Genomes Project and the Human Genome Diversity Project (1kGP + HGDP) reference panels (77 world populations representing six continental groups). In these groups, we performed GWASs of height, a trait potentially affected by population stratification. Birth cohorts demonstrate important trends in ancestry diversity over time. More recent HARE-assigned Europeans, Africans, and Hispanics had lower European ancestry proportions than older birth cohorts (0.010 < Cohen's d < 0.259, p < 7.80 × 10-4). Conversely, HARE-assigned East Asians showed an increase in European ancestry proportion over time. In GWAS of height using HARE assignments, genomic inflation due to population stratification was prevalent across all birth cohorts (linkage disequilibrium score regression intercept = 1.08 ± 0.042). The 1kGP + HGDP-based ancestry assignment significantly reduced the population stratification (mean intercept reduction = 0.045 ± 0.007, p < 0.05) confounding in the GWAS statistics. CONCLUSIONS: This study provides a characterization of ancestry diversity of the MVP cohort over time and compares two strategies to infer genetically defined ancestry groups by assessing differences in controlling population stratification in genome-wide association studies.

Declining autozygosity over time: An exploration in over 1 million individuals from three diverse cohorts.

Previous studies have hypothesized that autozygosity is decreasing over generational time. However, these studies were limited to relatively small samples (n < 11,000) lacking in diversity, which may limit the generalizability of their findings. We present data that partially support this hypothesis from three large cohorts of diverse ancestries, two from the US (All of Us, n = 82,474; the Million Veteran Program, n = 622,497) and one from the UK (UK Biobank, n = 380,899). Our results from a mixed-effect meta-analysis demonstrate an overall trend of decreasing autozygosity over generational time (meta-analyzed slope = -0.029, SE = 0.009, p = 6.03e-4). On the basis of our estimates, we would predict FROH to decline 0.29% for every 20-year increase in birth year. We determined that a model including an ancestry-by-country interaction term fit the data best, indicating that ancestry differences in this trend differ by country. We found further evidence to suggest a difference between the US and UK cohorts by meta-analyzing within country, observing a significant negative estimate in the US cohorts (meta-analyzed slope = -0.058, SE = 0.015, p = 1.50e-4) but a non-significant estimate in the UK (meta-analyzed slope = -0.001, SE = 0.008, p = 0.945). The association between autozygosity and birth year was substantially attenuated when accounting for educational attainment and income (meta-analyzed slope = -0.011, SE = 0.008, p = 0.167), suggesting they may partially account for decreasing autozygosity over time. Overall, we demonstrate decreasing autozygosity over time in a large, modern sample and speculate that this trend can be attributed to increases in urbanization and panmixia and differences in sociodemographic processes lead to country-specific differences in the rate of decline.

Genome-wide association study identifies four pan-ancestry loci for suicidal ideation in the Million Veteran Program.

Suicidal ideation (SI) often precedes and predicts suicide attempt and death, is the most common suicidal phenotype and is over-represented in veterans. The genetic architecture of SI in the absence of suicide attempt (SA) is unknown, yet believed to have distinct and overlapping risk with other suicidal behaviors. We performed the first GWAS of SI without SA in the Million Veteran Program (MVP), identifying 99,814 SI cases from electronic health records without a history of SA or suicide death (SD) and 512,567 controls without SI, SA or SD. GWAS was performed separately in the four largest ancestry groups, controlling for sex, age and genetic substructure. Ancestry-specific results were combined via meta-analysis to identify pan-ancestry loci. Four genome-wide significant (GWS) loci were identified in the pan-ancestry meta-analysis with loci on chromosomes 6 and 9 associated with suicide attempt in an independent sample. Pan-ancestry gene-based analysis identified GWS associations with DRD2, DCC, FBXL19, BCL7C, CTF1, ANNK1, and EXD3. Gene-set analysis implicated synaptic and startle response pathways (q's<0.05). European ancestry (EA) analysis identified GWS loci on chromosomes 6 and 9, as well as GWS gene associations in EXD3, DRD2, and DCC. No other ancestry-specific GWS results were identified, underscoring the need to increase representation of diverse individuals. The genetic correlation of SI and SA within MVP was high (rG = 0.87; p = 1.09e-50), as well as with post-traumatic stress disorder (PTSD; rG = 0.78; p = 1.98e-95) and major depressive disorder (MDD; rG = 0.78; p = 8.33e-83). Conditional analysis on PTSD and MDD attenuated most pan-ancestry and EA GWS signals for SI without SA to nominal significance, with the exception of EXD3 which remained GWS. Our novel findings support a polygenic and complex architecture for SI without SA which is largely shared with SA and overlaps with psychiatric conditions frequently comorbid with suicidal behaviors.

Combining Asian-European Genome-Wide Association Studies of Colorectal Cancer Improves Risk Prediction Across Race and Ethnicity.

Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expanded PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS were 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1,681-3,651 cases and 8,696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They were significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values<0.05). Further inclusion of non-European ancestry populations, especially Black/African American and Latinx/Hispanic, is needed to improve the risk prediction and enhance equity in applying PRS in clinical practice.

Validation of a Genetic-Enhanced Risk Prediction Model for Colorectal Cancer in a Large Community-Based Cohort.

BACKGROUND: Polygenic risk scores (PRS) which summarize individuals' genetic risk profile may enhance targeted colorectal cancer screening. A critical step towards clinical implementation is rigorous external validations in large community-based cohorts. This study externally validated a PRS-enhanced colorectal cancer risk model comprising 140 known colorectal cancer loci to provide a comprehensive assessment on prediction performance. METHODS: The model was developed using 20,338 individuals and externally validated in a community-based cohort (n = 85,221). We validated predicted 5-year absolute colorectal cancer risk, including calibration using expected-to-observed case ratios (E/O) and calibration plots, and discriminatory accuracy using time-dependent AUC. The PRS-related improvement in AUC, sensitivity and specificity were assessed in individuals of age 45 to 74 years (screening-eligible age group) and 40 to 49 years with no endoscopy history (younger-age group). RESULTS: In European-ancestral individuals, the predicted 5-year risk calibrated well [E/O = 1.01; 95% confidence interval (CI), 0.91-1.13] and had high discriminatory accuracy (AUC = 0.73; 95% CI, 0.71-0.76). Adding the PRS to a model with age, sex, family and endoscopy history improved the 5-year AUC by 0.06 (P < 0.001) and 0.14 (P = 0.05) in the screening-eligible age and younger-age groups, respectively. Using a risk-threshold of 5-year SEER colorectal cancer incidence rate at age 50 years, adding the PRS had a similar sensitivity but improved the specificity by 11% (P < 0.001) in the screening-eligible age group. In the younger-age group it improved the sensitivity by 27% (P = 0.04) with similar specificity. CONCLUSIONS: The proposed PRS-enhanced model provides a well-calibrated 5-year colorectal cancer risk prediction and improves discriminatory accuracy in the external cohort. IMPACT: The proposed model has potential utility in risk-stratified colorectal cancer prevention.

Genetic and epigenetic signatures associated with plasma oxytocin levels in children and adolescents with autism spectrum disorder.

Oxytocin (OT), the brain's most abundant neuropeptide, plays an important role in social salience and motivation. Clinical trials of the efficacy of OT in autism spectrum disorder (ASD) have reported mixed results due in part to ASD's complex etiology. We investigated whether genetic and epigenetic variation contribute to variable endogenous OT levels that modulate sensitivity to OT therapy. To carry out this analysis, we integrated genome-wide profiles of DNA-methylation, transcriptional activity, and genetic variation with plasma OT levels in 290 participants with ASD enrolled in a randomized controlled trial of OT. Our analysis identified genetic variants with novel association with plasma OT, several of which reside in known ASD risk genes. We also show subtle but statistically significant association of plasma OT levels with peripheral transcriptional activity and DNA-methylation profiles across several annotated gene sets. These findings broaden our understanding of the effects of the peripheral oxytocin system and provide novel genetic candidates for future studies to decode the complex etiology of ASD and its interaction with OT signaling and OT-based interventions. LAY SUMMARY: Oxytocin (OT) is an abundant chemical produced by neurons that plays an important role in social interaction and motivation. We investigated whether genetic and epigenetic factors contribute to variable OT levels in the blood. To this, we integrated genetic, gene expression, and non-DNA regulated (epigenetic) signatures with blood OT levels in 290 participants with autism enrolled in an OT clinical trial. We identified genetic association with plasma OT, several of which reside in known autism risk genes. We also show statistically significant association of plasma OT levels with gene expression and epigenetic across several gene pathways. These findings broaden our understanding of the factors that influence OT levels in the blood for future studies to decode the complex presentation of autism and its interaction with OT and OT-based treatment.

Effect of behavioral weight-loss program on biomarkers of cardiometabolic disease risk: Heart Health Study randomized trial.

OBJECTIVE: This study aimed to determine whether novel biomarkers of cardiometabolic health improve in response to a 12-month behavioral weight-loss intervention and to compare benefits of diet alone with diet plus physical activity for these biomarkers. METHODS: Participants (N = 374) were randomized to either diet alone (DIET), diet plus 150 min/wk of prescribed moderate-intensity physical activity (DIET + PA150), or diet plus 250 min/wk of prescribed moderate-intensity physical activity (DIET + PA250). Biomarker concentrations were determined using nuclear magnetic resonance spectroscopy. Mixed models assessed for a time effect, group effect, or group by time interaction. RESULTS: All groups significantly improved body weight (time: p < 0.0001), Lipoprotein Insulin Resistance Index score (time: p < 0.0001), Diabetes Risk Index score (time: p < 0.0001), branched-chain amino acid concentration (time: p < 0.0001), and GlycA concentration (time: p < 0.0001), with no group effect or group by time interactions. CONCLUSIONS: All intervention groups prompted a notable beneficial change among biomarkers of insulin resistance and cardiometabolic health. However, the addition of at least moderate-intensity physical activity to a diet-only intervention did not provide any additional benefit. These findings highlight that an average weight loss of approximately 10% profoundly impacts biomarkers of insulin resistance and cardiometabolic disease in adults with overweight or obesity.

Identification of Novel, Replicable Genetic Risk Loci for Suicidal Thoughts and Behaviors Among US Military Veterans.

Importance: Suicide is a leading cause of death; however, the molecular genetic basis of suicidal thoughts and behaviors (SITB) remains unknown. Objective: To identify novel, replicable genomic risk loci for SITB. Design, Setting, and Participants: This genome-wide association study included 633 778 US military veterans with and without SITB, as identified through electronic health records. GWAS was performed separately by ancestry, controlling for sex, age, and genetic substructure. Cross-ancestry risk loci were identified through meta-analysis. Study enrollment began in 2011 and is ongoing. Data were analyzed from November 2021 to August 2022. Main Outcome and Measures: SITB. Results: A total of 633 778 US military veterans were included in the analysis (57 152 [9%] female; 121 118 [19.1%] African ancestry, 8285 [1.3%] Asian ancestry, 452 767 [71.4%] European ancestry, and 51 608 [8.1%] Hispanic ancestry), including 121 211 individuals with SITB (19.1%). Meta-analysis identified more than 200 GWS (P < 5 × 10-8) cross-ancestry risk single-nucleotide variants for SITB concentrated in 7 regions on chromosomes 2, 6, 9, 11, 14, 16, and 18. Top single-nucleotide variants were largely intronic in nature; 5 were independently replicated in ISGC, including rs6557168 in ESR1, rs12808482 in DRD2, rs77641763 in EXD3, rs10671545 in DCC, and rs36006172 in TRAF3. Associations for FBXL19 and AC018880.2 were not replicated. Gene-based analyses implicated 24 additional GWS cross-ancestry risk genes, including FURIN, TSNARE1, and the NCAM1-TTC12-ANKK1-DRD2 gene cluster. Cross-ancestry enrichment analyses revealed significant enrichment for expression in brain and pituitary tissue, synapse and ubiquitination processes, amphetamine addiction, parathyroid hormone synthesis, axon guidance, and dopaminergic pathways. Seven other unique European ancestry-specific GWS loci were identified, 2 of which (POM121L2 and METTL15/LINC02758) were replicated. Two additional GWS ancestry-specific loci were identified within the African ancestry (PET112/GATB) and Hispanic ancestry (intergenic locus on chromosome 4) subsets, both of which were replicated. No GWS loci were identified within the Asian ancestry subset; however, significant enrichment was observed for axon guidance, cyclic adenosine monophosphate signaling, focal adhesion, glutamatergic synapse, and oxytocin signaling pathways across all ancestries. Within the European ancestry subset, genetic correlations (r > 0.75) were observed between the SITB phenotype and a suicide attempt-only phenotype, depression, and posttraumatic stress disorder. Additionally, polygenic risk score analyses revealed that the Million Veteran Program polygenic risk score had nominally significant main effects in 2 independent samples of veterans of European and African ancestry. Conclusions and Relevance: The findings of this analysis may advance understanding of the molecular genetic basis of SITB and provide evidence for ESR1, DRD2, TRAF3, and DCC as cross-ancestry candidate risk genes. More work is needed to replicate these findings and to determine if and how these genes might impact clinical care.

A Cluster Randomized Trial of a Family Health History Platform to Identify and Manage Patients at Increased Risk for Colorectal Cancer.

BACKGROUND: Obtaining comprehensive family health history (FHH) to inform colorectal cancer (CRC) risk management in primary care settings is challenging. OBJECTIVE: To examine the effectiveness of a patient-facing FHH platform to identify and manage patients at increased CRC risk. DESIGN: Two-site, two-arm, cluster-randomized, implementation-effectiveness trial with primary care providers (PCPs) randomized to immediate intervention versus wait-list control. PARTICIPANTS: PCPs treating patients at least one half-day per week; patients aged 40-64 with no medical conditions that increased CRC risk. INTERVENTIONS: Immediate-arm patients entered their FHH into a web-based platform that provided risk assessment and guideline-driven decision support; wait-list control patients did so 12 months later. MAIN MEASURES: McNemar's test examined differences between the platform and electronic medical record (EMR) in rates of increased risk documentation. General estimating equations using logistic regression models compared arms in risk-concordant provider actions and patient screening test completion. Referral for genetic consultation was analyzed descriptively. KEY RESULTS: Seventeen PCPs were randomized to each arm. Patients (n = 252 immediate, n = 253 control) averaged 51.4 (SD = 7.2) years, with 83% assigned male at birth, 58% White persons, and 33% Black persons. The percentage of patients identified as increased risk for CRC was greater with the platform (9.9%) versus EMR (5.2%), difference = 4.8% (95% CI: 2.6%, 6.9%), p < .0001. There was no difference in PCP risk-concordant action [odds ratio (OR) = 0.7, 95% CI (0.4, 1.2; p = 0.16)]. Among 177 patients with a risk-concordant screening test ordered, there was no difference in test completion, OR = 0.8 [0.5,1.3]; p = 0.36. Of 50 patients identified by the platform as increased risk, 78.6% immediate and 68.2% control patients received a recommendation for genetic consultation, of which only one in each arm had a referral placed. CONCLUSIONS: FHH tools could accurately assess and document the clinical needs of patients at increased risk for CRC. Barriers to acting on those recommendations warrant further exploration. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov NCT02247336 https://clinicaltrials.gov/ct2/show/NCT02247336.

The association of accelerated epigenetic age with all-cause mortality in cardiac catheterization patients as mediated by vascular and cardiometabolic outcomes.

BACKGROUND: Epigenetic age is a DNA methylation-based biomarker of aging that is accurate across the lifespan and a range of cell types. The difference between epigenetic age and chronological age, termed age acceleration (AA), is a strong predictor of lifespan and healthspan. The predictive capabilities of AA for all-cause mortality have been evaluated in the general population; however, its utility is less well evaluated in those with chronic conditions. Additionally, the pathophysiologic pathways whereby AA predicts mortality are unclear. We hypothesized that AA predicts mortality in individuals with underlying cardiovascular disease; and the association between AA and mortality is mediated, in part, by vascular and cardiometabolic measures. METHODS: We evaluated 562 participants in an urban, three-county area of central North Carolina from the CATHGEN cohort, all of whom received a cardiac catheterization procedure. We analyzed three AA biomarkers, Horvath epigenetic age acceleration (HAA), phenotypic age acceleration (PhenoAA), and Grim age acceleration (GrimAA), by Cox regression models, to assess whether AAs were associated with all-cause mortality. We also evaluated if these associations were mediated by vascular and cardiometabolic outcomes, including left ventricular ejection fraction (LVEF), blood cholesterol concentrations, angiopoietin-2 (ANG2) protein concentration, peripheral artery disease, coronary artery disease, diabetes, and hypertension. The total effect, direct effect, indirect effect, and percentage mediated were estimated using pathway mediation tests with a regression adjustment approach. RESULTS: PhenoAA (HR = 1.05, P < 0.0001), GrimAA (HR = 1.10, P < 0.0001) and HAA (HR = 1.03, P = 0.01) were all associated with all-cause mortality. The association of mortality and PhenoAA was partially mediated by ANG2, a marker of vascular function (19.8%, P = 0.016), and by diabetes (8.2%, P = 0.043). The GrimAA-mortality association was mediated by ANG2 (12.3%, P = 0.014), and showed weaker evidence for mediation by LVEF (5.3%, P = 0.065). CONCLUSIONS: Epigenetic age acceleration remains strongly predictive of mortality even in individuals already burdened with cardiovascular disease. Mortality associations were mediated by ANG2, which regulates endothelial permeability and angiogenic functions, suggesting that specific vascular pathophysiology may link accelerated epigenetic aging with increased mortality risks.

Establishment of multi-stage intravenous self-administration paradigms in mice.

Genetically tractable animal models provide needed strategies to resolve the biological basis of drug addiction. Intravenous self-administration (IVSA) is the gold standard for modeling psychostimulant and opioid addiction in animals, but technical limitations have precluded the widespread use of IVSA in mice. Here, we describe IVSA paradigms for mice that capture the multi-stage nature of the disorder and permit predictive modeling. In these paradigms, C57BL/6J mice with long-standing indwelling jugular catheters engaged in cocaine- or remifentanil-associated lever responding that was fixed ratio-dependent, dose-dependent, extinguished by withholding the drug, and reinstated by the presentation of drug-paired cues. The application of multivariate analysis suggested that drug taking in both paradigms was a function of two latent variables we termed incentive motivation and discriminative control. Machine learning revealed that vulnerability to drug seeking and relapse were predicted by a mouse's a priori response to novelty, sensitivity to drug-induced locomotion, and drug-taking behavior. The application of these behavioral and statistical-analysis approaches to genetically-engineered mice will facilitate the identification of neural circuits driving addiction susceptibility and relapse and focused therapeutic development.