Farmworker Acceptability of Backpack Hydration Systems.

OBJECTIVE: To improve water access while working and contribute to fewer heat-related illnesses (HRI), backpack hydration systems were provided to over 200 farmworkers to use during the 2022 growing season. Acceptability of the water intake intervention was assessed among farmworkers in eastern North Carolina, USA. METHODS: With a pre-established community-university partnership, the acceptability of the intervention was assessed using a cross-sectional survey. The backpack brand selected included a 3-liter water bladder and attached drinking hose. Data analysis included descriptive and correlation statistics. RESULTS: Among 47 male, migrant farmworkers, most (90%) reported the hydration backpack to be acceptable or completely acceptable to workplace fluid intake. Most (53%) reported using the backpack some of the time, compared to 28% who used it often. The participants reported an average of 4.8 (SD 2.2) liters of water intake from the backpack on a typical workday. Most reported the backpack improved the quantity and frequency of their water consumption. CONCLUSION: This study was an important first step in implementation of hydration backpack systems as an HRI-preventative intervention among farmworkers. Future interventional studies could assess the efficacy of the backpacks on health outcomes, including incidence of dehydration and symptoms of HRI.

Investigating light sensitivity in bipolar disorder (HELIOS-BD).

Many people with bipolar disorder have disrupted circadian rhythms. This means that the timing of sleep and wake activities becomes out-of-sync with the standard 24-hour cycle. Circadian rhythms are strongly influenced by light levels and previous research suggests that people with bipolar disorder might have a heightened sensitivity to light, causing more circadian rhythm disruption, increasing the potential for triggering a mood switch into mania or depression. Lithium has been in clinical use for over 70 years and is acknowledged to be the most effective long-term treatment for bipolar disorder. Lithium has many reported actions in the body but the precise mechanism of action in bipolar disorder remains an active area of research. Central to this project is recent evidence that lithium may work by stabilising circadian rhythms of mood, cognition and rest/activity. Our primary hypothesis is that people with bipolar disorder have some pathophysiological change at the level of the retina which makes them hypersensitive to the visual and non-visual effects of light, and therefore more susceptible to circadian rhythm dysfunction. We additionally hypothesise that the mood-stabilising medication lithium is effective in bipolar disorder because it reduces this hypersensitivity, making individuals less vulnerable to light-induced circadian disruption. We will recruit 180 participants into the HELIOS-BD study. Over an 18-month period, we will assess visual and non-visual responses to light, as well as retinal microstructure, in people with bipolar disorder compared to healthy controls. Further, we will assess whether individuals with bipolar disorder who are being treated with lithium have less pronounced light responses and attenuated retinal changes compared to individuals with bipolar disorder not being treated with lithium. This study represents a comprehensive investigation of visual and non-visual light responses in a large bipolar disorder population, with great translational potential for patient stratification and treatment innovation.

An epidemiological study of season of birth, mental health, and neuroimaging in the UK Biobank.

Environmental exposures during the perinatal period are known to have a long-term effect on adult physical and mental health. One such influential environmental exposure is the time of year of birth which affects the amount of daylight, nutrients, and viral load that an individual is exposed to within this key developmental period. Here, we investigate associations between season of birth (seasonality), four mental health traits (n = 137,588) and multi-modal neuroimaging measures (n = 33,212) within the UK Biobank. Summer births were associated with probable recurrent Major Depressive Disorder (ß = 0.026, pcorr = 0.028) and greater mean cortical thickness in temporal and occipital lobes (ß = 0.013 to 0.014, pcorr<0.05). Winter births were associated with greater white matter integrity globally, in the association fibers, thalamic radiations, and six individual tracts (ß = -0.013 to -0.022, pcorr<0.05). Results of sensitivity analyses adjusting for birth weight were similar, with an additional association between winter birth and white matter microstructure in the forceps minor and between summer births, greater cingulate thickness and amygdala volume. Further analyses revealed associations between probable depressive phenotypes and a range of neuroimaging measures but a paucity of interactions with seasonality. Our results suggest that seasonality of birth may affect later-life brain structure and play a role in lifetime recurrent Major Depressive Disorder. Due to the small effect sizes observed, and the lack of associations with other mental health traits, further research is required to validate birth season effects in the context of different latitudes, and by co-examining genetic and epigenetic measures to reveal informative biological pathways.

Exploring the causes of COPD misdiagnosis in primary care: A mixed methods study.

BACKGROUND: Within primary care there exists a cohort of patients misdiagnosed with Chronic Obstructive Pulmonary Disease (COPD). Misdiagnosis can have a detrimental impact on healthcare finances and patient health and so understanding the factors leading to misdiagnosis is crucial in order to reduce misdiagnosis in the future. The objective of this study is to understand and explore the perceived causes of COPD misdiagnosis in primary care. METHODS: A sequential mixed methods study, quantifying prevalence and features of patients misdiagnosed with COPD in primary care followed by a qualitative analysis to explore perceived causes of misdiagnosis. Quantitative data was collected for 206 patients identified as misdiagnosed with COPD within the INTEGR COPD study (NCT03482700). Qualitative data collected from 21 healthcare professionals involved in providing COPD care and 8 misdiagnosed patients who were recruited using a maximum variation purposive sampling. RESULTS: Misinterpretation of spirometry results was the prevailing factor leading to patients initially being misdiagnosed with COPD, affecting 59% of misdiagnosed patients in this cohort. Of the 99 patients who were investigated for their underlying diagnosis; 41% had normal spirometry and 40% had asthma. Further investigation through qualitative methodology uncovered reluctance to challenge historical misdiagnoses and challenges in differential diagnosis as the underlying explanations for COPD misdiagnosis in this cohort. CONCLUSIONS: Patients historically diagnosed with COPD without spirometric evidence are at risk of remaining labelled and treated for COPD despite non-obstructive respiratory physiology, leading to a persistent cohort of patients misdiagnosed with COPD in primary care. The lack of spirometry services during and after the COVID19 pandemic in primary care risks adding to the cohort of misdiagnosed patients. Support from respiratory specialists can potentially help to reduce the prevalence of COPD misdiagnosis in primary care. TRIAL REGISTRATION: NCT03482700.

Impact of CFTR Modulation on Pseudomonas aeruginosa Infection in People With Cystic Fibrosis.

BACKGROUND: Pseudomonas aeruginosa is a multidrug-resistant pathogen causing recalcitrant pulmonary infections in people with cystic fibrosis (pwCF). Cystic fibrosis transmembrane conductance regulator (CFTR) modulators have been developed that partially correct the defective chloride channel driving disease. Despite the many clinical benefits, studies in adults have demonstrated that while P. aeruginosa sputum load decreases, chronic infection persists. Here, we investigate how P. aeruginosa in pwCF may change in the altered lung environment after CFTR modulation. METHODS: P. aeruginosa strains (n = 105) were isolated from the sputum of 11 chronically colonized pwCF at baseline and up to 21 months posttreatment with elexacaftor-tezacaftor-ivacaftor or tezacaftor-ivacaftor. Phenotypic characterization and comparative genomics were performed. RESULTS: Clonal lineages of P. aeruginosa persisted after therapy, with no evidence of displacement by alternative strains. We identified commonly mutated genes among patient isolates that may be positively selected for in the CFTR-modulated lung. However, classic chronic P. aeruginosa phenotypes such as mucoid morphology were sustained, and isolates remained just as resistant to clinically relevant antibiotics. CONCLUSIONS: Despite the clinical benefits of CFTR modulators, clonal lineages of P. aeruginosa persist that may prove just as difficult to manage in the future, especially in pwCF with advanced lung disease.

Sensitivity to light in bipolar disorder: implications for research and clinical practice.

Circadian dysfunction is a core feature of bipolar disorder and may be due, at least in part, to abnormalities of non-visual photoreception. We critically review the evidence for light hypersensitivity in bipolar disorder and discuss how this may shape future research and clinical innovation, with a focus on a possible novel mechanism of action for lithium.

Comprehensive assessment of sleep duration, insomnia, and brain structure within the UK Biobank cohort.

STUDY OBJECTIVES: To assess for associations between sleeping more than or less than recommended by the National Sleep Foundation (NSF), and self-reported insomnia, with brain structure. METHODS: Data from the UK Biobank cohort were analyzed (N between 9K and 32K, dependent on availability, aged 44 to 82 years). Sleep measures included self-reported adherence to NSF guidelines on sleep duration (sleeping between 7 and 9 hours per night), and self-reported difficulty falling or staying asleep (insomnia). Brain structural measures included global and regional cortical or subcortical morphometry (thickness, surface area, volume), global and tract-related white matter microstructure, brain age gap (difference between chronological age and age estimated from brain scan), and total volume of white matter lesions. RESULTS: Longer-than-recommended sleep duration was associated with lower overall grey and white matter volumes, lower global and regional cortical thickness and volume measures, higher brain age gap, higher volume of white matter lesions, higher mean diffusivity globally and in thalamic and association fibers, and lower volume of the hippocampus. Shorter-than-recommended sleep duration was related to higher global and cerebellar white matter volumes, lower global and regional cortical surface areas, and lower fractional anisotropy in projection fibers. Self-reported insomnia was associated with higher global gray and white matter volumes, and with higher volumes of the amygdala, hippocampus, and putamen. CONCLUSIONS: Sleeping longer than recommended by the NSF is associated with a wide range of differences in brain structure, potentially indicative of poorer brain health. Sleeping less than recommended is distinctly associated with lower cortical surface areas. Future studies should assess the potential mechanisms of these differences and investigate long sleep duration as a putative marker of brain health.

Genomic analyses of Burkholderia respiratory isolates indicates two evolutionarily distinct B. anthina clades.

Introduction: The Burkholderia cepacia complex (BCC) encompasses a group of at least 22 genetically distinct gram-negatives bacterial species ubiquitous in nature. Recognised as a group of genetically and phenotypically flexible species, the BCC inhabits diverse ecological niches causing both plant and human diseases. Comparative genomic analysis provides an in depth understanding into the population biology, phylogenetic relationship, and genomic architecture of species. Methods: Here, we genomically characterise Burkholderia anthina isolated from patients with chronic lung infections, an understudied pathogen within the Burkholderia cepacia complex. Results: We demonstrate that B. anthina is polyphyletic and constitutes two distinct evolutionary lineages. Core- and pan-genome analyses demonstrated substantial metabolic diversity, with B. anthina Clade I enriched in genes associated with microbial metabolism in diverse environments, including degradation of aromatic compounds and metabolism of xenobiotics, while B. anthina Clade II demonstrated an enhanced capability for siderophore biosynthesis. Discussion: Based on our phylogenetic and comparative genomic analyses, we suggest stratifying B. anthina to recognise a distinct species harbouring increased potential for iron metabolism via siderophore synthesis, for which we propose the name Burkholderia anthinoferum (sp. nov.).

Severe and common mental disorders and risk of emergency hospital admissions for ambulatory care sensitive conditions among the UK Biobank cohort.

BACKGROUND: People with mental disorders have worse physical health compared with the general population, which could be attributable to receiving poorer quality healthcare. AIMS: To examine the relationship between severe and common mental disorders and risk of emergency hospital admissions for ambulatory care sensitive conditions (ACSCs), and factors associated with increased risk. METHOD: Baseline data for England (N = 445 814) were taken from UK Biobank, which recruited participants aged 37-73 years during 2006-2010, and linked to hospital admission records up to 31 December 2019. Participants were grouped into those with a history of either schizophrenia, bipolar disorder, depression or anxiety, or no mental disorder. Survival analysis was used to assess the risk of hospital admission for ACSCs among those with mental disorders compared with those without, adjusting for factors in different domains (sociodemographic, socioeconomic, health and biomarkers, health-related behaviours, social isolation and psychological). RESULTS: People with schizophrenia had the highest (unadjusted) risk of hospital admission for ACSCs compared with those with no mental disorder (hazard ratio 4.40, 95% CI 4.04-4.80). People with bipolar disorder (hazard ratio 2.48, 95% CI 2.28-2.69) and depression or anxiety (hazard ratio 1.76, 95% CI 1.73-1.80) also had higher risk. Associations were more conservative when including all admissions, as opposed to first admissions only. The observed associations persisted after adjusting for a range of factors. CONCLUSIONS: People with severe mental disorders have the highest risk of preventable hospital admissions. Ensuring people with mental disorders receive adequate ambulatory care is essential to reduce the large health inequalities they experience.

Pilot study of a ketogenic diet in bipolar disorder.

BACKGROUND: Recent evidence from case reports suggests that a ketogenic diet may be effective for bipolar disorder. However, no clinical trials have been conducted to date. AIMS: To assess the recruitment and feasibility of a ketogenic diet intervention in bipolar disorder. METHOD: Euthymic individuals with bipolar disorder were recruited to a 6-8 week trial of a modified ketogenic diet, and a range of clinical, economic and functional outcome measures were assessed. Study registration number: ISRCTN61613198. RESULTS: Of 27 recruited participants, 26 commenced and 20 completed the modified ketogenic diet for 6-8 weeks. The outcomes data-set was 95% complete for daily ketone measures, 95% complete for daily glucose measures and 95% complete for daily ecological momentary assessment of symptoms during the intervention period. Mean daily blood ketone readings were 1.3 mmol/L (s.d. = 0.77, median = 1.1) during the intervention period, and 91% of all readings indicated ketosis, suggesting a high degree of adherence to the diet. Over 91% of daily blood glucose readings were within normal range, with 9% indicating mild hypoglycaemia. Eleven minor adverse events were recorded, including fatigue, constipation, drowsiness and hunger. One serious adverse event was reported (euglycemic ketoacidosis in a participant taking SGLT2-inhibitor medication). CONCLUSIONS: The recruitment and retention of euthymic individuals with bipolar disorder to a 6-8 week ketogenic diet intervention was feasible, with high completion rates for outcome measures. The majority of participants reached and maintained ketosis, and adverse events were generally mild and modifiable. A future randomised controlled trial is now warranted.

Physics-informed neural networks for predicting gas flow dynamics and unknown parameters in diesel engines.

This paper presents a physics-informed neural network (PINN) approach for monitoring the health of diesel engines. The aim is to evaluate the engine dynamics, identify unknown parameters in a "mean value" model, and anticipate maintenance requirements. The PINN model is applied to diesel engines with a variable-geometry turbocharger and exhaust gas recirculation, using measurement data of selected state variables. The results demonstrate the ability of the PINN model to predict simultaneously both unknown parameters and dynamics accurately with both clean and noisy data, and the importance of the self-adaptive weight in the loss function for faster convergence. The input data for these simulations are derived from actual engine running conditions, while the outputs are simulated data, making this a practical case study of PINN's ability to predict real-world dynamical systems. The mean value model of the diesel engine incorporates empirical formulae to represent certain states, but these formulae may not be generalizable to other engines. To address this, the study considers the use of deep neural networks (DNNs) in addition to the PINN model. The DNNs are trained using laboratory test data and are used to model the engine-specific empirical formulae in the mean value model, allowing for a more flexible and adaptive representation of the engine's states. In other words, the mean value model uses both the PINN model and the DNNs to represent the engine's states, with the PINN providing a physics-based understanding of the engine's overall dynamics and the DNNs offering a more engine-specific and adaptive representation of the empirical formulae. By combining these two approaches, the study aims to offer a comprehensive and versatile approach to monitoring the health and performance of diesel engines.

Bipolar disorder: Diagnosis, treatment and future directions.

Bipolar disorder is a relatively common mental illness, characterised by recurrent episodes of mania (or hypomania) and major depression, and associated with a significant burden of morbidity and premature mortality. Physicians across all specialities are likely to encounter individuals with the condition within their clinical practice. This short review provides an up-to-date overview of the clinical features, epidemiology, pathophysiology, evidence-based management, prognosis and future directions for treatment and research in bipolar disorder. Aspects of cross-specialty relevance are highlighted, including the physical health burden associated with the condition, and the side effects and safety considerations of medication regimes used in bipolar disorder.

Polygenic risk of major depressive disorder as a risk factor for venous thromboembolism.

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are associated with an increased risk of cardiovascular diseases, including venous thromboembolism (VTE). The reasons for this are complex and include obesity, smoking, and use of hormones and psychotropic medications. Genetic studies have increasingly provided evidence of the shared genetic risk of psychiatric and cardiometabolic illnesses. This study aimed to determine whether a genetic predisposition to MDD, BD, or SCZ is associated with an increased risk of VTE. Genetic correlations using the largest genome-wide genetic meta-analyses summary statistics for MDD, BD, and SCZ (Psychiatric Genetics Consortium) and a recent genome-wide genetic meta-analysis of VTE (INVENT Consortium) demonstrated a positive association between VTE and MDD but not BD or SCZ. The same summary statistics were used to construct polygenic risk scores for MDD, BD, and SCZ in UK Biobank participants of self-reported White British ancestry. These were assessed for impact on self-reported VTE risk (10 786 cases, 285 124 controls), using logistic regression, in sex-specific and sex-combined analyses. We identified significant positive associations between polygenic risk for MDD and the risk of VTE in men, women, and sex-combined analyses, independent of the known risk factors. Secondary analyses demonstrated that this association was not driven by those with lifetime experience of mental illness. Meta-analyses of individual data from 6 additional independent cohorts replicated the sex-combined association. This report provides evidence for shared biological mechanisms leading to MDD and VTE and suggests that, in the absence of genetic data, a family history of MDD might be considered when assessing the risk of VTE.

Genetic architecture of DCC and influence on psychological, psychiatric and cardiometabolic traits in multiple ancestry groups in UK Biobank.

BACKGROUND: People with severe mental illness have a higher risk of cardiometabolic disease than the general population. Traditionally attributed to sociodemographic, behavioural factors and medication effects, recent genetic studies have provided evidence of shared biological mechanisms underlying mental illness and cardiometabolic disease. We aimed to determine whether signals in the DCC locus, implicated in psychiatric and cardiometabolic traits, were shared or distinct. METHODS: In UK Biobank, we systematically assessed genetic variation in the DCC locus for association with metabolic, cardiovascular and psychiatric-related traits in unrelated "white British" participants (N = 402,837). Logistic or linear regression were applied assuming an additive genetic model and adjusting for age, sex, genotyping chip and population structure. Bonferroni correction for the number of independent variants was applied. Conditional analyses (including lead variants as covariates) and trans-ancestry analyses were used to investigate linkage disequilibrium between signals. RESULTS: Significant associations were observed between DCC variants and smoking, anhedonia, body mass index (BMI), neuroticism and mood instability. Conditional analyses and linkage disequilibrium structure suggested signals for smoking and BMI were distinct from each other and the mood traits, whilst individual mood traits were inter-related in a complex manner. LIMITATIONS: Restricting analyses in non-"white British" individuals to the phenotypes significant in the "white British" sample is not ideal, but the smaller samples sizes restricted the phenotypes possible to analyse. CONCLUSIONS: Genetic variation in the DCC locus had distinct effects on BMI, smoking and mood traits, and therefore is unlikely to contribute to shared mechanisms underpinning mental and cardiometabolic traits.

Sociodemographic, mental health, and physical health factors associated with participation within re-contactable mental health cohorts: an investigation of the GLAD Study.

BACKGROUND: The Genetic Links to Anxiety and Depression (GLAD) Study is a large cohort of individuals with lifetime anxiety and/or depression, designed to facilitate re-contact of participants for mental health research. At the start of the pandemic, participants from three cohorts, including the GLAD Study, were invited to join the COVID-19 Psychiatry and Neurological Genetics (COPING) study to monitor mental and neurological health. However, previous research suggests that participation in longitudinal studies follows a systematic, rather than random, process, which can ultimately bias results. Therefore, this study assessed participation biases following the re-contact of GLAD Study participants. METHODS: In April 2020, all current GLAD Study participants (N = 36,770) were invited to the COPING study. Using logistic regression, we investigated whether sociodemographic, mental, and physical health characteristics were associated with participation in the COPING baseline survey (aim one). Subsequently, we used a zero-inflated negative binomial regression to examine whether these factors were also related to participation in the COPING follow-up surveys (aim two). RESULTS: For aim one, older age, female gender identity, non-binary or self-defined gender identities, having one or more physical health disorders, and providing a saliva kit for the GLAD Study were associated with an increased odds of completing the COPING baseline survey. In contrast, lower educational attainment, Asian or Asian British ethnic identity, Black or Black British ethnic identity, higher alcohol consumption at the GLAD sign-up survey, and current or ex-smoking were associated with a reduced odds. For aim two, older age, female gender, and saliva kit provision were associated with greater COPING follow-up survey completion. Lower educational attainment, higher alcohol consumption at the GLAD Study sign-up, ex-smoking, and self-reported attention deficit hyperactivity disorder had negative relationships. CONCLUSIONS: Participation biases surrounding sociodemographic and physical health characteristics were particularly evident when re-contacting the GLAD Study volunteers. Factors associated with participation may vary depending on study design. Researchers should examine the barriers and mechanisms underlying participation bias in order to combat these issues and address recruitment biases in future studies.

Subjective and objective sleep and circadian parameters as predictors of depression-related outcomes: A machine learning approach in UK Biobank.

BACKGROUND: Sleep and circadian disruption are associated with depression onset and severity, but it is unclear which features (e.g., sleep duration, chronotype) are important and whether they can identify individuals showing poorer outcomes. METHODS: Within a subset of the UK Biobank with actigraphy and mental health data (n = 64,353), penalised regression identified the most useful of 51 sleep/rest-activity predictors of depression-related outcomes; including case-control (Major Depression (MD) vs. controls; postnatal depression vs. controls) and within-case comparisons (severe vs. moderate MD; early vs. later onset, atypical vs. typical symptoms; comorbid anxiety; suicidality). Best models (of lasso, ridge, and elastic net) were selected based on Area Under the Curve (AUC). RESULTS: For MD vs. controls (n(MD) = 24,229; n(control) = 40,124), lasso AUC was 0.68, 95 % confidence interval (CI) 0.67-0.69. Discrimination was reasonable for atypical vs. typical symptoms (n(atypical) = 958; n(typical) = 18,722; ridge: AUC 0.74, 95 % CI 0.71-0.77) but poor for remaining models (AUCs 0.59-0.67). Key predictors across most models included: difficulty getting up, insomnia symptoms, snoring, actigraphy-measured daytime inactivity and lower morning activity (~8 am). In a distinct subset (n = 310,718), the number of these factors shown was associated with all depression outcomes. LIMITATIONS: Analyses were cross-sectional and in middle-/older aged adults: comparison with longitudinal investigations and younger cohorts is necessary. DISCUSSION: Sleep and circadian measures alone provided poor to moderate discrimination of depression outcomes, but several characteristics were identified that may be clinically useful. Future work should assess these features alongside broader sociodemographic, lifestyle and genetic features.

Severe Mental Illness and Type 2 Diabetes Outcomes and Complications: A Nationwide Cohort Study.

OBJECTIVE: To compare cardiovascular and mortality outcomes in people with severe mental illness (SMI) versus no mental illness in a national cohort study of people with type 2 diabetes. RESEARCH DESIGN AND METHODS: We included adults diagnosed with type 2 diabetes between 2004 and 2018 from the national Scottish diabetes register, ascertaining history of mental illness from linked psychiatric and general hospital admission records. We identified major cardiovascular disease (CVD) events, all-cause mortality, and CVD-specific mortality through record linkage. Using Cox regression, we estimated hazard ratios (HRs) for associations between SMI and outcomes, adjusting for baseline sociodemographic and clinical characteristics, including history of CVD, comorbidity, hypertension, high cholesterol, HbA1c, BMI, alcohol use disorder, and smoking. RESULTS: Among 259,875 people with type 2 diabetes, 1.0%, 0.5%, and 3.0% had schizophrenia, bipolar disorder, and major depression, respectively. After adjusting for sociodemographic characteristics, the risk of major CVD events was higher in people with schizophrenia (HR 1.22, 95% CI 1.06-1.41), bipolar disorder (HR 1.58, 95% CI 1.33-1.87), and major depression (HR 1.59, 95% CI 1.49-1.70) compared with people without a history of mental illness. SMI was also associated with an approximately twofold increased risk of CVD-specific and all-cause mortality. All associations attenuated following further adjustment for clinical characteristics. CONCLUSIONS: Among people with diabetes, people with a history of SMI have poorer cardiovascular and mortality outcomes compared with those without mental illness. While the underlying mechanisms are further investigated, effective prevention and management of cardiovascular risk factors is needed in this high-risk group.

Cognitive Function in People With Familial Risk of Depression.

Importance: Cognitive impairment in depression is poorly understood. Family history of depression is a potentially useful risk marker for cognitive impairment, facilitating early identification and targeted intervention in those at highest risk, even if they do not themselves have depression. Several research cohorts have emerged recently that enable findings to be compared according to varying depths of family history phenotyping, in some cases also with genetic data, across the life span. Objective: To investigate associations between familial risk of depression and cognitive performance in 4 independent cohorts with varied depth of assessment, using both family history and genetic risk measures. Design, Setting, and Participants: This study used data from the Three Generations at High and Low Risk of Depression Followed Longitudinally (TGS) family study (data collected from 1982 to 2015) and 3 large population cohorts, including the Adolescent Brain Cognitive Development (ABCD) study (data collected from 2016 to 2021), National Longitudinal Study of Adolescent to Adult Health (Add Health; data collected from 1994 to 2018), and UK Biobank (data collected from 2006 to 2022). Children and adults with or without familial risk of depression were included. Cross-sectional analyses were conducted from March to June 2022. Exposures: Family history (across 1 or 2 prior generations) and polygenic risk of depression. Main Outcomes and Measures: Neurocognitive tests at follow-up. Regression models were adjusted for confounders and corrected for multiple comparisons. Results: A total of 57 308 participants were studied, including 87 from TGS (42 [48%] female; mean [SD] age, 19.7 [6.6] years), 10 258 from ABCD (4899 [48%] female; mean [SD] age, 12.0 [0.7] years), 1064 from Add Health (584 [49%] female; mean [SD] age, 37.8 [1.9] years), and 45 899 from UK Biobank (23 605 [51%] female; mean [SD] age, 64.0 [7.7] years). In the younger cohorts (TGS, ABCD, and Add Health), family history of depression was primarily associated with lower performance in the memory domain, and there were indications that this may be partly associated with educational and socioeconomic factors. In the older UK Biobank cohort, there were associations with processing speed, attention, and executive function, with little evidence of education or socioeconomic influences. These associations were evident even in participants who had never been depressed themselves. Effect sizes between familial risk of depression and neurocognitive test performance were largest in TGS; the largest standardized mean differences in primary analyses were -0.55 (95% CI, -1.49 to 0.38) in TGS, -0.09 (95% CI, -0.15 to -0.03) in ABCD, -0.16 (95% CI, -0.31 to -0.01) in Add Health, and -0.10 (95% CI, -0.13 to -0.06) in UK Biobank. Results were generally similar in the polygenic risk score analyses. In UK Biobank, several tasks showed statistically significant associations in the polygenic risk score analysis that were not evident in the family history models. Conclusions and Relevance: In this study, whether assessed by family history or genetic data, depression in prior generations was associated with lower cognitive performance in offspring. There are opportunities to generate hypotheses about how this arises through genetic and environmental determinants, moderators of brain development and brain aging, and potentially modifiable social and lifestyle factors across the life span.