High LDL Particle and APOB Concentrations in Patients With Adrenal Cortical Adenomas: A Cross Sectional Study.

CONTEXT: Patients with nonfunctioning adenomas (NFA), adenomas with mild autonomous cortisol secretion (MACS) and Cushing syndrome (CS) demonstrate an increased cardiovascular risk. OBJECTIVE: To determine the extent of lipoprotein abnormalities in NFA, MACS, and CS. METHODS: We conducted a single-center cross-sectional study of patients with NFA (n = 167), MACS (n = 213), CS (n = 142) and referent subjects (n = 202) between January 2015 and July 2022. Triglyceride-rich lipoprotein particles (TRLP), low density lipoprotein particles (LDLP), high density lipoprotein particles (HDLP), their subclasses and sizes were measured using nuclear magnetic resonance spectroscopy. Multivariable logistic analyses were adjusted for age, sex, BMI, smoking, hypertension, diabetes and lipid lowering drug therapy. RESULTS: In age- and sex-adjusted analysis, all patients categories demonstrated increased very large TRLP, large TRLP and greater TRL size (odds ratio (OR) ranging from 1.22 to 2.08) and total LDLP (OR ranging from 1.22 to 1.75) and decreased LDL and HDL size compared to referent subjects. In fully adjusted analysis, LDLP concentrations remained elevated in all patient categories (odds ratios ranging from 1.31 to 1.84). Total cholesterol, LDL cholesterol, triglycerides and apolipoprotein B were also higher in all patient categories in age- and sex-adjusted analysis with apoB remaining elevated in all patient categories in fully adjusted analysis. Similar LDLP and apoB elevations were observed in all patient categories after excluding subjects on lipid lowering therapy. CONCLUSION: Patients with overt, mild, and even absent cortisol excess demonstrate lipoprotein profile abnormalities, in particular, high LDLP and apoB concentrations, which conceivably contribute to high cardiometabolic risk.

A harmonized public resource of deeply sequenced diverse human genomes.

Underrepresented populations are often excluded from genomic studies owing in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high-quality set of 4094 whole genomes from 80 populations in the HGDP and 1kGP with data from the Genome Aggregation Database (gnomAD) and identified over 153 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also show substantial added value from this data set compared with the prior versions of the component resources, typically combined via liftOver and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared with previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality-control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.

Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder.

Post-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.

A phenome-wide association and Mendelian randomisation study of alcohol use variants in a diverse cohort comprising over 3 million individuals.

BACKGROUND: Alcohol consumption is associated with numerous negative social and health outcomes. These associations may be direct consequences of drinking, or they may reflect common genetic factors that influence both alcohol consumption and other outcomes. METHODS: We performed exploratory phenome-wide association studies (PheWAS) of three of the best studied protective single nucleotide polymorphisms (SNPs) in genes encoding ethanol metabolising enzymes (ADH1B: rs1229984-T, rs2066702-A; ADH1C: rs698-T) using up to 1109 health outcomes across 28 phenotypic categories (e.g., substance-use, mental health, sleep, immune, cardiovascular, metabolic) from a diverse 23andMe cohort, including European (N ≤ 2,619,939), Latin American (N ≤ 446,646) and African American (N ≤ 146,776) populations to uncover new and perhaps unexpected associations. These SNPs have been consistently implicated by both candidate gene studies and genome-wide association studies of alcohol-related behaviours but have not been investigated in detail for other relevant phenotypes in a hypothesis-free approach in such a large cohort of multiple ancestries. To provide insight into potential causal effects of alcohol consumption on the outcomes significant in the PheWAS, we performed univariable two-sample and one-sample Mendelian randomisation (MR) analyses. FINDINGS: The minor allele rs1229984-T, which is protective against alcohol behaviours, showed the highest number of PheWAS associations across the three cohorts (N = 232, European; N = 29, Latin American; N = 7, African American). rs1229984-T influenced multiple domains of health. We replicated associations with alcohol-related behaviours, mental and sleep conditions, and cardio-metabolic health. We also found associations with understudied traits related to neurological (migraines, epilepsy), immune (allergies), musculoskeletal (fibromyalgia), and reproductive health (preeclampsia). MR analyses identified evidence of causal effects of alcohol consumption on liability for 35 of these outcomes in the European cohort. INTERPRETATION: Our work demonstrates that polymorphisms in genes encoding alcohol metabolising enzymes affect multiple domains of health beyond alcohol-related behaviours. Understanding the underlying mechanisms of these effects could have implications for treatments and preventative medicine. FUNDING: MVJ, NCK, SBB, SSR and AAP were supported by T32IR5226 and 28IR-0070. SSR was also supported by NIDA DP1DA054394. NCK and RBC were also supported by R25MH081482. ASH was supported by funds from NIAAA K01AA030083. JLMO was supported by VA 1IK2CX002095. JLMO and JJMM were also supported by NIDA R21DA050160. JJMM was also supported by the Kavli Postdoctoral Award for Academic Diversity. EGA was supported by K01MH121659 from the NIMH/NIH, the Caroline Wiess Law Fund for Research in Molecular Medicine and the ARCO Foundation Young Teacher-Investigator Fund at Baylor College of Medicine. MSA was supported by the Instituto de Salud Carlos III and co-funded by the European Union Found: Fondo Social Europeo Plus (FSE+) (P19/01224, PI22/00464 and CP22/00128).

Enhanced chronic inflammation and increased branched chain amino acids in adrenal disorders: a cross-sectional study.

CONTEXT: Patients with adrenal hormone excess demonstrate increased cardiovascular risk and mortality. OBJECTIVE: We aimed to determine the impact of adrenal disorders on the inflammation marker GlycA, total branched-chain amino acids (BCAA), ketone bodies and the gut microbiome-derived metabolites trimethylamine N-oxide (TMAO) and betaine. METHODS: We conducted a single-center cross-sectional study of patients with nonfunctioning adenomas (NFA), mild autonomous cortisol secretion (MACS), primary aldosteronism (PA), Cushing syndrome (CS), pheochromocytoma/paragangliomas (PPGL), other benign or malignant adrenal masses, and adrenocortical carcinoma (ACC) between January 2015 and July 2022 (n=802). Referent subjects included participants of the PREVEND (Prevention of Renal and Vascular End-stage Disease) study (n=5241). GlycA, BCAA, ketone bodies, TMAO, and betaine were measured using nuclear magnetic resonance spectroscopy. Multivariable logistic analyses were adjusted for age, sex, BMI, smoking, hypertension, diabetes mellitus and statin therapy. RESULTS: In age-and sex-adjusted comparison to referent subjects, increased GlycA was noted in all patient categories, increased BCAA in NFA, MACS, CS, PA and ACC, increased TMAO in patients with other malignant adrenal masses, increased betaine in NFA and MACS, and increased ketone bodies in NFA, CS and ACC. Essentially similar findings were observed in fully adjusted analysis and after exclusion of subjects with diabetes and cardiovascular disease. CONCLUSION: Patients with functioning and non-functioning adrenal masses demonstrated increased GlycA and BCAA, biomarkers associated with adverse cardiometabolic disorders and mortality. Patients with NFA demonstrated an adverse metabolic profile similar to patients with MACS and CS.

Admix-kit: an integrated toolkit and pipeline for genetic analyses of admixed populations.

SUMMARY: Admixed populations, with their unique and diverse genetic backgrounds, are often underrepresented in genetic studies. This oversight not only limits our understanding but also exacerbates existing health disparities. One major barrier has been the lack of efficient tools tailored for the special challenges of genetic studies of admixed populations. Here, we present admix-kit, an integrated toolkit and pipeline for genetic analyses of admixed populations. Admix-kit implements a suite of methods to facilitate genotype and phenotype simulation, association testing, genetic architecture inference, and polygenic scoring in admixed populations. AVAILABILITY AND IMPLEMENTATION: Admix-kit package is open-source and available at https://github.com/KangchengHou/admix-kit. Additionally, users can use the pipeline designed for admixed genotype simulation available at https://github.com/UW-GAC/admix-kit_workflow.

Comorbidity clusters in patients with rheumatoid arthritis identify a patient phenotype with a favourable prognosis.

OBJECTIVES: We aimed to cluster patients with rheumatoid arthritis (RA) based on comorbidities and then examine the association between these clusters and RA disease activity and mortality. METHODS: In this population-based study, residents of an eight-county region with prevalent RA on 1 January 2015 were identified. Patients were followed for vital status until death, last contact or 31 December 2021. Diagnostic codes for 5 years before the prevalence date were used to define 55 comorbidities. Latent class analysis was used to cluster patients based on comorbidity patterns. Standardised mortality ratios were used to assess mortality. RESULTS: A total of 1643 patients with prevalent RA (72% female; 94% white; median age 64 years, median RA duration 7 years) were studied. Four clusters were identified. Cluster 1 (n=686) included patients with few comorbidities, and cluster 4 (n=134) included older patients with 10 or more comorbidities. Cluster 2 (n=200) included patients with five or more comorbidities and high prevalences of depression and obesity, while cluster 3 (n=623) included the remainder. RA disease activity and survival differed across the clusters, with cluster 1 demonstrating more remission and mortality comparable to the general population. CONCLUSIONS: More than 40% of patients with prevalent RA did not experience worse mortality than their peers without RA. The cluster with the worst prognosis (<10% of patients with prevalent RA) was older, had more comorbidities and had less disease-modifying antirheumatic drug and biological use compared with the other clusters. Comorbidity patterns may hold the key to moving beyond a one-size-fits-all perspective of RA prognosis.

Genome-wide study investigating effector genes and polygenic prediction for kidney function in persons with ancestry from Africa and the Americas.

Chronic kidney disease is a leading cause of death and disability globally and impacts individuals of African ancestry (AFR) or with ancestry in the Americas (AMS) who are under-represented in genome-wide association studies (GWASs) of kidney function. To address this bias, we conducted a large meta-analysis of GWASs of estimated glomerular filtration rate (eGFR) in 145,732 AFR and AMS individuals. We identified 41 loci at genome-wide significance (p < 5 × 10-8), of which two have not been previously reported in any ancestry group. We integrated fine-mapped loci with epigenomic and transcriptomic resources to highlight potential effector genes relevant to kidney physiology and disease, and reveal key regulatory elements and pathways involved in renal function and development. We demonstrate the varying but increased predictive power offered by a multi-ancestry polygenic score for eGFR and highlight the importance of population diversity in GWASs and multi-omics resources to enhance opportunities for clinical translation for all.

A harmonized public resource of deeply sequenced diverse human genomes.

Underrepresented populations are often excluded from genomic studies due in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high quality set of 4,094 whole genomes from HGDP and 1kGP with data from the Genome Aggregation Database (gnomAD) and identified over 153 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also demonstrate substantial added value from this dataset compared to the prior versions of the component resources, typically combined via liftover and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared to previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.

Calorie restriction reduces biomarkers of cellular senescence in humans.

Calorie restriction (CR) with adequate nutrient intake is a potential geroprotective intervention. To advance this concept in humans, we tested the hypothesis that moderate CR in healthy young-to-middle-aged individuals would reduce circulating biomarkers of cellular senescence, a fundamental mechanism of aging and aging-related conditions. Using plasma specimens from the Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy (CALERIE™) phase 2 study, we found that CR significantly reduced the concentrations of several senescence biomarkers at 12 and 24 months compared to an ad libitum diet. Using machine learning, changes in biomarker concentrations emerged as important predictors of the change in HOMA-IR and insulin sensitivity index at 12 and 24 months, and the change in resting metabolic rate residual at 12 months. Finally, using adipose tissue RNA-sequencing data from a subset of participants, we observed a significant reduction in a senescence-focused gene set in response to CR at both 12 and 24 months compared to baseline. Our results advance the understanding of the effects of CR in humans and further support a link between cellular senescence and metabolic health.

Diabetes Study of Children of Diverse Ethnicity and Race: Study design.

AIMS: Determining diabetes type in children has become increasingly difficult due to an overlap in typical characteristics between type 1 diabetes (T1D) and type 2 diabetes (T2D). The Diabetes Study in Children of Diverse Ethnicity and Race (DISCOVER) programme is a National Institutes of Health (NIH)-supported multicenter, prospective, observational study that enrols children and adolescents with non-secondary diabetes. The primary aim of the study was to develop improved models to differentiate between T1D and T2D in diverse youth. MATERIALS AND METHODS: The proposed models will evaluate the utility of three existing T1D genetic risk scores in combination with data on islet autoantibodies and other parameters typically available at the time of diabetes onset. Low non-fasting serum C-peptide (<0.6 nmol/L) between 3 and 10 years after diabetes diagnosis will be considered a biomarker for T1D as it reflects the loss of insulin secretion ability. Participating centres are enrolling youth (<19 years old) either with established diabetes (duration 3-10 years) for a cross-sectional evaluation or with recent onset diabetes (duration 3 weeks-15 months) for the longitudinal observation with annual visits for 3 years. Cross-sectional data will be used to develop models. Longitudinal data will be used to externally validate the best-fitting model. RESULTS: The results are expected to improve the ability to classify diabetes type in a large and growing subset of children who have an unclear form of diabetes at diagnosis. CONCLUSIONS: Accurate and timely classification of diabetes type will help establish the correct clinical management early in the course of the disease.

Biomarkers of Cellular Senescence Predict the Onset of Mobility Disability and Are Reduced by Physical Activity in Older Adults.

Studies in mice and cross-sectional studies in humans support the premise that cellular senescence is a contributing mechanism to age-associated deficits in physical function. We tested the hypotheses that circulating proteins secreted by senescent cells are (i) associated with the incidence of major mobility disability (MMD), the development of persistent mobility disability (PMMD), and decrements in physical functioning in older adults, and (ii) influenced by physical activity (PA). Using samples and data obtained longitudinally from the Lifestyle Interventions in Elders Study clinical trial, we measured a panel of 27 proteins secreted by senescent cells. Among 1 377 women and men randomized to either a structured PA intervention or a healthy aging (HA) intervention, we observed significant associations between several senescence biomarkers, most distinctly vascular endothelial growth factor A (VEGFA), tumor necrosis factor receptor 1 (TNFR1), and matrix metallopeptidase 7 (MMP7), and the onset of both MMD and PMMD. Moreover, VEGFA, GDF15, osteopontin, and other senescence biomarkers were associated with reductions in short physical performance battery scores. The change in senescence biomarkers did not differ between PA and HA participants. In the whole cohort, higher levels of PA were associated with significantly greater reductions in 10 senescence-related proteins at 12 and/or 24 months. These data reinforce cellular senescence as a contributing mechanism of age-associated functional decline and the potential for PA to attenuate this hallmark of aging. Clinical Trials Registration Number: NCT01072500.

Kidney function in patients with adrenal adenomas: A single-center retrospective cohort study.

OBJECTIVE: Patients with nonfunctioning adrenal adenomas (NFA) and mild autonomous cortisol secretion (MACS) demonstrate an increased risk of chronic kidney disease (CKD), however factors associated with CKD are unknown. We aimed to identify the factors associated with CKD and assess the impact of adrenalectomy on kidney function in patients with NFA or MACS. DESIGN: Single-center cohort study of patients with NFA and MACS, 1999-2020. METHODS: MACS was diagnosed based on post-dexamethasone cortisol (DST) ≥ 1.8 mcg/dL. Age, sex, dysglycemia, hypertension, therapy with statin, angiotensin converting enzyme inhibitor, or angiotensin II receptor blocker were included in the multivariable analysis. Outcomes included estimated glomerular filtration rate (eGFR) at the time of diagnosis with MACS or NFA and post-adrenalectomy delta eGFR. RESULTS: Of 972 patients, 429 (44%) had MACS and 543 (56%) had NFA. At the time of diagnosis, patients with MACS had lower eGFR (median 79.6 vs 83.8 ml/min/1.73m2, p < 0.001) than patients with NFA. In a multivariable analysis, factors associated with lower eGFR were older age, hypertension, and higher DST. In 204 patients (MACS: 155, 76% and NFA: 49, 24%) treated with adrenalectomy, post adrenalectomy eGFR improved in both groups starting at 18 months up to 3.5 years of follow up. Factors associated with increased eGFR were younger age, lower pre-adrenalectomy eGFR and longer follow-up period. CONCLUSION: DST cortisol is an independent risk factor for lower eGFR in patients with adrenal adenomas. Both patients with MACS and NFA demonstrate an increase in eGFR post-adrenalectomy, especially younger patients with lower eGFR pre-adrenalectomy.

Latin American Trans-ancestry INitiative for OCD genomics (LATINO): Study protocol.

Obsessive-compulsive disorder (OCD) is a debilitating psychiatric disorder. Worldwide, its prevalence is ~2% and its etiology is mostly unknown. Identifying biological factors contributing to OCD will elucidate underlying mechanisms and might contribute to improved treatment outcomes. Genomic studies of OCD are beginning to reveal long-sought risk loci, but >95% of the cases currently in analysis are of homogenous European ancestry. If not addressed, this Eurocentric bias will result in OCD genomic findings being more accurate for individuals of European ancestry than other ancestries, thereby contributing to health disparities in potential future applications of genomics. In this study protocol paper, we describe the Latin American Trans-ancestry INitiative for OCD genomics (LATINO, https://www.latinostudy.org). LATINO is a new network of investigators from across Latin America, the United States, and Canada who have begun to collect DNA and clinical data from 5000 richly phenotyped OCD cases of Latin American ancestry in a culturally sensitive and ethical manner. In this project, we will utilize trans-ancestry genomic analyses to accelerate the identification of OCD risk loci, fine-map putative causal variants, and improve the performance of polygenic risk scores in diverse populations. We will also capitalize on rich clinical data to examine the genetics of treatment response, biologically plausible OCD subtypes, and symptom dimensions. Additionally, LATINO will help elucidate the diversity of the clinical presentations of OCD across cultures through various trainings developed and offered in collaboration with Latin American investigators. We believe this study will advance the important goal of global mental health discovery and equity.

Polygenic prediction across populations is influenced by ancestry, genetic architecture, and methodology.

Polygenic risk scores (PRSs) developed from multi-ancestry genome-wide association studies (GWASs), PRSmulti, hold promise for improving PRS accuracy and generalizability across populations. To establish best practices for leveraging the increasing diversity of genomic studies, we investigated how various factors affect the performance of PRSmulti compared with PRSs constructed from single-ancestry GWASs (PRSsingle). Through extensive simulations and empirical analyses, we showed that PRSmulti overall outperformed PRSsingle in understudied populations, except when the understudied population represented a small proportion of the multi-ancestry GWAS. Furthermore, integrating PRSs based on local ancestry-informed GWASs and large-scale, European-based PRSs improved predictive performance in understudied African populations, especially for less polygenic traits with large-effect ancestry-enriched variants. Our work highlights the importance of diversifying genomic studies to achieve equitable PRS performance across ancestral populations and provides guidance for developing PRSs from multiple studies.

Admix-kit: An Integrated Toolkit and Pipeline for Genetic Analyses of Admixed Populations.

Admixed populations, with their unique and diverse genetic backgrounds, are often underrepresented in genetic studies. This oversight not only limits our understanding but also exacerbates existing health disparities. One major barrier has been the lack of efficient tools tailored for the special challenges of genetic study of admixed populations. Here, we present admix-kit, an integrated toolkit and pipeline for genetic analyses of admixed populations. Admix-kit implements a suite of methods to facilitate genotype and phenotype simulation, association testing, genetic architecture inference, and polygenic scoring in admixed populations.

Risk of dementia and psychiatric or sleep disorders after diagnosis of adrenal adenomas: a population-based cohort study.

OBJECTIVE: Adrenal adenomas are commonly encountered in clinical practice. To date, population-based data on their impact on cognition, mental health, and sleep are lacking. We aimed to study possible associations between adrenal adenomas and dementia, psychiatric or sleep disorders. DESIGN: Population-based cohort study, Olmsted County, MN, 1995-2017. METHODS: Patients with adrenal adenoma and absent overt hormone excess were age- and sex-matched 1:1 to a referent person without adrenal adenoma. Outcomes were baseline and incident diagnoses of dementia, psychiatric or sleep disorders, assessed using ICD codes. RESULTS: Of 1004 patients with adrenal adenomas, 582 (58%) were women, and median age at diagnosis was 63 years. At baseline, and after adjusting for age, sex, education, BMI, and tobacco use, patients with adenoma had higher odds of depression (adjusted odds ratio, aOR: 1.3, 95% CI, 1.1-1.6), anxiety (aOR: 1.4, 95% CI, 1.1-1.8), and substance abuse (aOR: 2.4, 95% CI, 1.7-3.4) compared to referents. During a median follow-up of 6.8 years, and after adjusting for age, sex, socioeconomic status, BMI, tobacco, and substance abuse, patients demonstrated a higher risk of psychiatric and sleep disorders [adjusted hazard ratio (95% CI)]: depression [1.7 (1.3-2.2)], anxiety [1.4, CI (1.1-1.7)], insomnia [1.4 (1.0-1.9)], sleep-related breathing disorders [1.5 (1.1-1.9)], hypersomnias [2.1 (1.0-4.2)], parasomnias [2.1 (1.0-4.2)], and sleep-related movement disorders [1.5 (1.0-2.1)], but not dementia. CONCLUSIONS: Patients with adenomas demonstrate a higher incidence of psychiatric and sleep disorders, possibly due to the underlying subtle increase in cortisol secretion.

Biomarkers of cellular senescence and risk of death in humans.

A robust and heterogenous secretory phenotype is a core feature of most senescent cells. In addition to mediators of age-related pathology, components of the senescence associated secretory phenotype (SASP) have been studied as biomarkers of senescent cell burden and, in turn, biological age. Therefore, we hypothesized that circulating concentrations of candidate senescence biomarkers, including chemokines, cytokines, matrix remodeling proteins, and growth factors, could predict mortality in older adults. We assessed associations between plasma levels of 28 SASP proteins and risk of mortality over a median follow-up of 6.3 years in 1923 patients 65 years of age or older with zero or one chronic condition at baseline. Overall, the five senescence biomarkers most strongly associated with an increased risk of death were GDF15, RAGE, VEGFA, PARC, and MMP2, after adjusting for age, sex, race, and the presence of one chronic condition. The combination of biomarkers and clinical and demographic covariates exhibited a significantly higher c-statistic for risk of death (0.79, 95% confidence interval (CI): 0.76-0.82) than the covariates alone (0.70, CI: 0.67-0.74) (p < 0.001). Collectively, these findings lend further support to biomarkers of cellular senescence as informative predictors of clinically important health outcomes in older adults, including death.

Discovery of 95 PTSD loci provides insight into genetic architecture and neurobiology of trauma and stress-related disorders.

Posttraumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 novel). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (e.g., GRIA1, GRM8, CACNA1E ), developmental, axon guidance, and transcription factors (e.g., FOXP2, EFNA5, DCC ), synaptic structure and function genes (e.g., PCLO, NCAM1, PDE4B ), and endocrine or immune regulators (e.g., ESR1, TRAF3, TANK ). Additional top genes influence stress, immune, fear, and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.

High prevalence of frailty in patients with adrenal adenomas and adrenocortical hormone excess: a cross-sectional multi-centre study with prospective enrolment.

OBJECTIVE: Frailty, characterized by multi-system decline, increases vulnerability to adverse health outcomes and can be measured using Frailty Index (FI). We aimed to assess the prevalence of frailty in patients with adrenal disorders (based on hormonal sub-type) and examine association between FI and performance-based measures of physical function. DESIGN: Multi-centre, cross-sectional study (March 2019-August 2022). METHODS: Adult patients with adrenal disorders (non-functioning adrenal adenomas [NFA], mild autonomous cortisol secretion [MACS], Cushing syndrome [CS], primary aldosteronism [PA]) and referent subjects without adrenal disorders completed a questionnaire encompassing 47 health variables (comorbidities, symptoms, daily living activities). FI was calculated as the average score of all variables and frailty defined as FI ≥ 0.25. Physical function was assessed with hand grip, timed up-and-go test, chair rising test, 6-minute walk test, and gait speed. RESULTS: Compared to referent subjects (n = 89), patients with adrenal disorders (n = 520) showed increased age, sex, and body mass index-adjusted prevalence of frailty (CS [odds ratio-OR 19.2, 95% confidence interval-CI 6.7-70], MACS [OR 12.5, 95% CI 4.8-42.9], PA [OR 8.4, 95% CI 2.9-30.4], NFA [OR 4.5, 95% CI 1.7-15.9]). Prevalence of frailty was similar to referent subjects when post-dexamethasone cortisol was <28 nmol/L and was higher when post-dexamethasone cortisol was 28-50 nmol/L (OR 4.6, 95% CI 1.7-16.5). FI correlated with all measures of physical function (P < .001). CONCLUSIONS: Whilst frailty prevalence was highest in patients with adrenocortical hormone excess, even patients with NFA demonstrated an increased prevalence compared to the referent population. Future longitudinal studies are needed to evaluate the impact of various management strategies on frailty.