Participation bias in the UK Biobank distorts genetic associations and downstream analyses

Latent profiles of modifiable dementia risk factors in later midlife: relationships with incident dementia, cognition, and neuroimaging outcomes

In 2020, the Lancet Commission identified 12 modifiable factors that increase population-level dementia risk. It is unclear if these risk factors co-occur among individuals in a clinically meaningful way. Using latent class analysis, we identified profiles of modifiable dementia risk factors in dementia-free adults aged 60-64 years from the UK Biobank. We then estimated associations between these profiles with incident dementia, cognition, and neuroimaging outcomes, and explored the differences across profiles in the effects of a polygenic risk score for Alzheimer's disease on outcomes. In 55,333 males and 63,063 females, three sex-specific latent profiles were identified: cardiometabolic risk, substance use-related risk, and low risk. The cardiometabolic risk profile in both males and females was associated with greater incidence of all-cause dementia (male: OR [95% CI] = 2.33 [2.03, 2.66]; female: OR [95% CI] = 1.44 [1.24, 1.68]), poorer cognitive performance, greater brain atrophy, and greater white matter hyperintensity volume compared to the low risk profile. The substance use-related risk profile in males was associated with poorer cognitive performance and greater white matter hyperintensities compared to the low risk profile, but no difference in all-cause dementia incidence was observed (OR [95% CI] = 1.00 [0.95, 1.06]). In females, the substance use-related risk profile demonstrated increased dementia incidence (OR [95% CI] = 1.58 [1.57, 1.58]) and greater brain atrophy but smaller white matter hyperintensity volume compared to the low risk profile. The polygenic risk score had larger effects among females, and differentially influenced outcomes across profiles; for instance, there were larger effects of the polygenic risk score on atrophy in the cardiometabolic profile vs. the low risk profile among males, and larger effects of the polygenic risk score on loss of white matter integrity in the cardiometabolic profile vs. the low risk profile among females. These results reveal three modifiable dementia risk profiles, their unique cognitive/neuroimaging outcomes, and their interactions with genetic risk for Alzheimer's disease. These differences highlight the need to consider population heterogeneity in risk prediction tools and in planning personalized prevention strategies.

Plasma proteomic evidence for increased β-amyloid pathology after SARS-CoV-2 infection

Previous studies have suggested that systemic viral infections may increase risks of dementia. Whether this holds true for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus infections is unknown. Determining this is important for anticipating the potential future incidence of dementia. To begin to do this, we measured plasma biomarkers linked to Alzheimer's disease pathology in the UK Biobank before and after serology-confirmed SARS-CoV-2 infections. SARS-CoV-2 infection was associated with biomarkers associated with β-amyloid pathology: reduced plasma Aβ42:Aβ40 ratio and, in more vulnerable participants, lower plasma Aβ42 and higher plasma pTau-181. The plasma biomarker changes were greater in participants who had been hospitalized with COVID-19 or had reported hypertension previously. We showed that the changes in biomarkers were linked to brain structural imaging patterns associated with Alzheimer's disease, lower cognitive test scores and poorer overall health evaluations. Our data from this post hoc case-control matched study thus provide observational biomarker evidence that SARS-CoV-2 infection can be associated with greater brain β-amyloid pathology in older adults. While these results do not establish causality, they suggest that SARS-CoV-2 (and possibly other systemic inflammatory diseases) may increase the risk of future Alzheimer's disease.

Are associations of adulthood overweight and obesity with all-cause mortality, cardiovascular disease, and obesity-related cancer modified by comparative body weight at age 10 years in the UK Biobank study?

OBJECTIVE

Adults living with overweight or obesity do not represent a single homogenous group in terms of mortality and disease risks. The aim of our study was to evaluate how the associations of adulthood overweight and obesity with mortality and incident disease are modified by (i.e., differ according to) self-reported childhood body weight categories.

METHODS

The sample comprised 191,181 men and 242,806 women aged 40-69 years (in 2006-2010) in the UK Biobank. The outcomes were all-cause mortality, incident cardiovascular disease (CVD), and incident obesity-related cancer. Cox proportional hazards regression models were used to estimate how the associations with the outcomes of adulthood weight status (normal weight, overweight, obesity) differed according to perceived body weight at age 10 years (about average, thinner, plumper). To triangulate results using an approach that better accounts for confounding, analyses were repeated using previously developed and validated polygenic risk scores (PRSs) for childhood body weight and adulthood BMI, categorised into three-tier variables using the same proportions as in the observational variables.

RESULTS

In both sexes, adulthood obesity was associated with higher hazards of all outcomes. However, the associations of obesity with all-cause mortality and incident CVD were stronger in adults who reported being thinner at 10 years. For example, obesity was associated with a 1.28 (1.21, 1.35) times higher hazard of all-cause mortality in men who reported being an average weight child, but among men who reported being a thinner child this estimate was 1.63 (1.53, 1.75). The ratio between these two estimates was 1.28 (1.17, 1.40). There was also some evidence that the associations of obesity with all-cause mortality and incident CVD were stronger in adults who reported being plumper at 10 years. In genetic analyses, however, there was no evidence that the association of obesity (according to the adult PRS) with mortality or incident CVD differed according to childhood body size (according to the child PRS). For incident obesity-related cancer, the evidence for effect modification was limited and inconsistent between the observational and genetic analyses.

CONCLUSIONS

Greater risks for all-cause mortality and incident CVD in adults with obesity who perceive themselves to have been a thinner or plumper than average child may be due to confounding and/or recall bias.

Shared polygenic susceptibility to treatment response in severe affective and psychotic disorders: Evidence from GWAS data sets

While schizophrenia (SCZ), bipolar disorder (BD) and major depressive disorder (MDD) genetically correlate, the pleiotropy underlying response/resistance to drugs used in these disorders has not been investigated. The aim of this study is to analyze the genetic relationship between treatment-resistant schizophrenia (TRS), response to lithium in BD (respLi) and response to antidepressants in MDD (respAD) using the conditional/conjunctional false discovery rate (cond/conjFDR) methodology, based on the hypothesis that shared mechanisms related to a common psychopathology factor underlie these phenotypes. A cross-trait polygenic enrichment for TRS conditioned on associations with respLi was observed. The conjFDR analysis identified rs11631065 (chr15:66654304) as a shared locus between them. One of the genes at this locus is MAP2K1, previously reported as associated with TRS after conditioning on body mass index genome-wide association study (GWAS). The set of genes at TRS-respLi conjFDR < 0.95 showed enrichment in response to psychotropic drugs in severe mental disorders from GWAS Catalog as well as in neurodevelopment and synaptic pathways. In conclusion, our study constitutes the first evidence of a transdiagnostic genetic signal associated with response to different pharmacological treatments in psychotic and affective disorders. It is necessary to confirm these results when larger GWAS of these phenotypes are available.

A scalable variational inference approach for increased mixed-model association power

The rapid growth of modern biobanks is creating new opportunities for large-scale genome-wide association studies (GWASs) and the analysis of complex traits. However, performing GWASs on millions of samples often leads to trade-offs between computational efficiency and statistical power, reducing the benefits of large-scale data collection efforts. We developed Quickdraws, a method that increases association power in quantitative and binary traits without sacrificing computational efficiency, leveraging a spike-and-slab prior on variant effects, stochastic variational inference and graphics processing unit acceleration. We applied Quickdraws to 79 quantitative and 50 binary traits in 405,088 UK Biobank samples, identifying 4.97% and 3.25% more associations than REGENIE and 22.71% and 7.07% more than FastGWA. Quickdraws had costs comparable to REGENIE, FastGWA and SAIGE on the UK Biobank Research Analysis Platform service, while being substantially faster than BOLT-LMM. These results highlight the promise of leveraging machine learning techniques for scalable GWASs without sacrificing power or robustness.

No association of posttraumatic stress disorder with epigenetic aging in women at mid-life: A longitudinal cohort study

Posttraumatic stress disorder (PTSD) is associated with mortality and increased risk of diseases of aging, but underlying mechanisms remain unclear. We examine associations of PTSD with one potential pathway, accelerated epigenetic aging. In a longitudinal cohort of trauma-exposed middle-aged women (n = 831, n observations = 1,516), we examined cross-sectional and longitudinal associations between PTSD, with and without comorbid depression, and epigenetic aging measured by six clocks at two time points approximately 13.5 years apart: Hannum, Horvath, PhenoAge, GrimAge, DunedinPoAM, and DunedinPACE. We further examined associations of 3 well-established predictors of aging and mortality also linked with PTSD, namely, body mass index (BMI), diet quality, and physical activity, with epigenetic aging. Cross-sectionally, across all six clocks, epigenetic aging in women with PTSD alone, depression alone, and co-occurring depression and PTSD did not differ from the reference group of women without PTSD or depression in analyses adjusted for age, self-reported race, cell proportions, and ancestry principal components. In longitudinal analyses, we similarly did not find any difference in change in epigenetic age over time by PTSD and depression status at baseline. Among the health factors, in cross-sectional analyses, higher BMI was significantly and consistently associated with greater epigenetic aging measured by the PhenoAge, GrimAge, DunedinPoAM, and DunedinPACE clocks, but not measured by the Hannum or Horvath clocks. Physical activity was not consistently associated with epigenetic aging measured by Hannum, Horvath, PhenoAge, or GrimAge. In analyses with the DunedinPoAm and DunedinPACE clocks, women who reported exercise equivalent to 1 or more hours/week walking had slower epigenetic aging than women with less exercise. Diet quality was not consistently associated with epigenetic aging measured by any of the clocks. Our data do not provide evidence that biological aging, as measured by any of the six epigenetic clocks, is a pathway linking PTSD with mortality and diseases of aging.

Factors Associated With Enrollment to a Decentralized Study

OBJECTIVE

To assess whether the mode and formatting of invitations affect enrollment in a large, decentralized study.

PATIENTS AND METHODS

Between July 1, 2022, and October 30, 2022, we prospectively compared various approaches to enroll patients in the Tapestry DNA Sequencing Research Study, a decentralized exome-sequencing study. In phase 1, patients were randomized to receive invitations via the electronic health record (EHR) patient portal or email (cohort 1, 69,852 patients). Phase 2 randomized in a 2×2 factorial design to receive (by portal or email) standard or enhanced (ie, more visually appealing) invitations (cohort 2, 26,198 patients). Factors that predicted enrollment rates were analyzed.

RESULTS

The enrollment rate was greater in cohort 2 (1,785 of 24,550, 7.27%) than 1 (1,758 or 69,765, 2.52%) and remained significant after multivariable adjustment (odds ratio, 1.31; 95% CI, 1.19-1.45). Enrollment rates were greater in women than men, patients 50 to 70 years of age than younger patients, White or non-Hispanic or Latino patients than those in other racial categories, urban than rural residents, and patients who had more health care encounters or more recent health care before this study (P<.02). The enrollment rate was also greater when invitations were delivered via EHR than email (odds ratio, 1.56; 95% CI, 1.44-1.68; P<.001).

CONCLUSION

Invitations via EHR rather than email facilitate enrollment to large, decentralized studies. Enhanced display of invitation material did not increase enrollment. Lower enrollment rates in men, younger individuals, non-White and Hispanic individuals, and rural residents highlight a continued need to focus enrollment strategies on these subgroups.

Life's essential 8 and cardiovascular diseases progression among adults in the United Kingdom

BACKGROUND

Recently, the American Heart Association introduced Life's Essential 8 (LE8) as a new cardiovascular health (CVH) metric, and studies have reported associations between LE8 and CVH outcomes. However, there is limited understanding of LE8's impact on the risk of transitions between different stages of CVH. The current study investigated whether adhering to LE8 during a healthy stage could mitigate the progression from hypertension (HT) to cardiovascular diseases (CVDs), and consequent death.

METHODS

The study included 107,682 participants in the UK Biobank who were initially free of HT and CVDs. CVH were evaluated using LE8 metrics (diet, physical activity, nicotine exposure, sleep duration, body mass index, non-high-density lipoprotein cholesterol, blood glucose, and blood pressure). Multistate models were used to analyse the impacts of LE8 on the progression of CVDs.

RESULTS

During a median follow-up of 12.2 years, 5727 participants developed HT, 7243 developed CVDs, and 1183 died afterwards. LE8 was negatively associated with the dynamic disease progression. A per-10 points increase of CVH scores was significantly associated with the reduced risk [Hazard ratios (95 % confidence intervals)] at 0.71 (0.69, 0.72), 0.83 (0.81, 0.85), 0.79 (0.77, 0.82), and 0.91 (0.86, 0.96) in the transition from healthy to HT, CVDs, death, and from CVDs to death, respectively. Mediation analyses indicated that HT significantly mediated LE8-reduced risks of CVDs and mortality.

CONCLUSIONS

This study offered evidence that LE8 may influence the stages of CVD progression. The findings underscore the significance of adhering to LE8 in health management and CVDs management.

Comparing Ancestry Standardization Approaches for a Transancestry Colorectal Cancer Polygenic Risk Score

Colorectal cancer (CRC) is a complex disease with monogenic, polygenic and environmental risk factors. Polygenic risk scores (PRSs) aim to identify high polygenic risk individuals. Due to differences in genetic background, PRS distributions vary by ancestry, necessitating standardization. We compared four post-hoc methods using the All of Us Research Program Whole Genome Sequence data for a transancestry CRC PRS. We contrasted results from linear models trained on A. the entire data or an ancestrally diverse subset AND B. covariates including principal components of ancestry or admixture. Standardization with the training subset also adjusted the variance. All methods performed similarly within ancestry, OR (95% C.I.) per s.d. change in PRS: African 1.5 (1.02, 2.08), Admixed American 2.2 (1.27, 3.85), European 1.6 (1.43, 1.89), and Middle Eastern 1.1 (0.71, 1.63). Using admixture and an ancestrally diverse training set provided distributions closest to standard Normal. Training a model on ancestrally diverse participants, adjusting both the mean and variance using admixture as covariates, created standard Normal z-scores, which can be used to identify patients at high polygenic risk. These scores can be incorporated into comprehensive risk calculation including other known risk factors, allowing for more precise risk estimates.

Exploring the association between familial hemiplegic migraine genes (CACNA1A, ATP1A2 and SCN1A) with migraine and epilepsy: A UK Biobank exome-wide association study

BACKGROUND

Familial hemiplegic migraine (FHM) types 1-3 are associated with protein-altering genetic variants in CACNA1A, ATP1A2 and SCN1A, respectively. These genes have also been linked to epilepsy. Previous studies primarily focused on phenotypes, examining genetic variants in individuals with characteristic FHM symptoms. This study aimed to investigate the association of FHM genetic variation with migraine and epilepsy, utilizing a genotype-first approach.

METHODS

Whole-exome sequence data from 454,706 individuals from the UK Biobank were examined for self-reported and inpatient-diagnosed migraine and epilepsy. Carriers were compared with non-carriers in a burden analysis using logistic regression while accounting for age, biological sex and UK Biobank assessment center. A machine learning-based approach was employed to predict whether variants resulted in gain-of-function (GoF), loss-of-function (LoF) or neutral effects.

RESULTS

Heterozygous carriers of GoF CACNA1A variants, LoF ATP1A2 variants or neutral SCN1A variants were at increased risk of migraine. Homozygous carriers of neutral SCN1A variants were also associated with migraine but these carriers showed a reduced disease risk of epilepsy.

CONCLUSIONS

Heterozygous genotypes in all three FHM genes were associated with migraine but not epilepsy in this genotype-focused study. Homozygous SCN1A genotypes also showed increased disease risk of migraine, yet these carriers were protected against epilepsy.

Assessment and ascertainment in psychiatric molecular genetics: challenges and opportunities for cross-disorder research

Psychiatric disorders are highly comorbid, heritable, and genetically correlated [1-4]. The primary objective of cross-disorder psychiatric genetics research is to identify and characterize both the shared genetic factors that contribute to convergent disease etiologies and the unique genetic factors that distinguish between disorders [4, 5]. This information can illuminate the biological mechanisms underlying comorbid presentations of psychopathology, improve nosology and prediction of illness risk and trajectories, and aid the development of more effective and targeted interventions. In this review we discuss how estimates of comorbidity and identification of shared genetic loci between disorders can be influenced by how disorders are measured (phenotypic assessment) and the inclusion or exclusion criteria in individual genetic studies (sample ascertainment). Specifically, the depth of measurement, source of diagnosis, and time frame of disease trajectory have major implications for the clinical validity of the assessed phenotypes. Further, biases introduced in the ascertainment of both cases and controls can inflate or reduce estimates of genetic correlations. The impact of these design choices may have important implications for large meta-analyses of cohorts from diverse populations that use different forms of assessment and inclusion criteria, and subsequent cross-disorder analyses thereof. We review how assessment and ascertainment affect genetic findings in both univariate and multivariate analyses and conclude with recommendations for addressing them in future research.

Polygenic prediction of occupational status GWAS elucidates genetic and environmental interplay in intergenerational transmission, careers and health in UK Biobank

Socioeconomic status (SES) impacts health and life-course outcomes. This genome-wide association study (GWAS) of sociologically informed occupational status measures (ISEI, SIOPS, CAMSIS) using the UK Biobank (N = 273,157) identified 106 independent single-nucleotide polymorphisms of which 8 are novel to the study of SES. Genetic correlations with educational attainment (rg = 0.96-0.97) and income (rg = 0.81-0.91) point to a common genetic factor for SES. We observed a 54-57% reduction in within-family predictions compared with population-based predictions, attributed to indirect parental effects (22-27% attenuation) and assortative mating (21-27%) following our calculations. Using polygenic scores from population predictions of 5-10% (incremental R2 = 0.023-0.097 across different approaches and occupational status measures), we showed that (1) cognitive and non-cognitive traits, including scholastic and occupational motivation and aspiration, link polygenic scores to occupational status and (2) 62% of the intergenerational transmission of occupational status cannot be ascribed to genetic inheritance of common variants but other factors such as family environments. Finally, links between genetics, occupation, career trajectory and health are interrelated with parental occupational status.

The impact of self-report inaccuracy in the UK Biobank and its interplay with selective participation

Although the use of short self-report measures is common practice in biobank initiatives, such a phenotyping strategy is inherently prone to reporting errors. To explore challenges related to self-report errors, we first derived a reporting error score in the UK Biobank (UKBB; n = 73,127), capturing inconsistent self-reporting in time-invariant phenotypes across multiple measurement occasions. We then performed genome-wide scans on the reporting error score, applied downstream analyses (linkage disequilibrium score regression and Mendelian randomization) and compared its properties to the UKBB participation propensity. Finally, we improved phenotype resolution for 24 measures and inspected the changes in genomic findings. We found that reporting error was present across all 33 assessed self-report measures, with repeatability levels as low as 47% (childhood body size). Reporting error was not independent from UKBB participation, evidenced by the negative genetic correlation between the two outcomes (rg = -0.77), their shared causes (for example, education) and the loss in self-report accuracy following participation bias correction. Across all analyses, the impact of reporting error ranged from reduced power (for example, for gene discovery) to biased estimates (for example, if present in the exposure variable) and attenuation of genome-wide quantities (for example, 21% relative attenuation in SNP heritability for childhood height). Our findings highlight that both self-report accuracy and selective participation are competing biases and sources of poor reproducibility for biobank-scale research.

Evaluating the impact of shift work on the risk of cardiometabolic disease: A Mendelian randomization study

BACKGROUND AND AIMS

Evidence is increasingly suggesting that shift work is a risk factor for cardiometabolic disease. However, the causal relationship between shift work and cardiometabolic disease is not yet fully understood. In this study, we employed two-sample Mendelian randomization (MR) to investigate the causal relationship between shift work and the risk of cardiometabolic outcomes.

METHODS AND RESULTS

Genome-wide association study (GWAS) statistics for shift work were obtained from the UK Biobank. Mendelian randomization analyses were conducted to explore the causal effects of shift work on cardiometabolic outcomes, using single-nucleotide polymorphisms (SNPs) as instrumental variables. The results suggested a causal effect between shift work and body mass index, body fat percentage, triglycerides, high-density lipoprotein, type 2 diabetes, hypertension, and cardiorespiratory fitness. After correcting for multiple tests, only body mass index and high-density lipoprotein showed significant associations. No causal effects were found between shift work and overweight, obesity, total cholesterol, low-density lipoprotein, fasting glucose, 2-h glucose, fasting insulin, coronary artery disease, myocardial infarction, heart failure, atrial fibrillation, or ischemic stroke.

CONCLUSION

This MR study provides genetic evidence for a suggestive causal link between shift work and certain cardiometabolic outcomes. Our research may have the significance of providing insight into public hygiene to improve the understanding of shift work and cardiometabolic disease risk. Further experimental studies are needed to confirm our findings.

The duration of lithium use and biological ageing: telomere length, frailty, metabolomic age and all-cause mortality

Lithium is an established first-line treatment for bipolar disorder. Beyond its therapeutic effect as a mood stabiliser, lithium exhibits potential anti-ageing effects. This study aimed to examine the relationship between the duration of lithium use, biological ageing and mortality. The UK Biobank is an observational study of middle-aged and older adults. We tested associations between the duration of lithium use (number of prescriptions, total duration of use and duration of the first prescription period) and telomere length, frailty, metabolomic age (MileAge) delta, pulse rate and all-cause mortality. Five hundred ninety-one individuals (mean age = 57.49 years; 55% females) had been prescribed lithium. There was no evidence that the number of prescriptions (β =  - 0.022, 95% CI - 0.081 to 0.037, p = 0.47), the total duration of use (β =  - 0.005, 95% CI - 0.023 to 0.013, p = 0.57) or the duration of the first prescription period (β =  - 0.018, 95% CI - 0.051 to 0.015, p = 0.29) correlated with telomere length. There was also no evidence that the duration of lithium use correlated with frailty or MileAge delta. However, a higher prescription count and a longer duration of use was associated with a lower pulse rate. The duration of lithium use did not predict all-cause mortality. We observed no evidence of associations between the duration of lithium use and biological ageing markers, including telomere length. Our findings suggest that the potential anti-ageing effects of lithium do not differ by the duration of use.

Polygenic Risk Score Informed Clinical Model for Improving Abdominal Aortic Aneurysm Screening

BACKGROUND

Abdominal aortic aneurysm (AAA) is a complex disease with environmental and genetic risk factors. Polygenic risk scores (PRSs) based on disease-specific risk-associated single nucleotide variants (SNVs) have demonstrated effectiveness in stratifying individual-level disease risk for cardiovascular diseases. This prospective cohort study assessed associations of PRS of AAA (PRSAAA) with risk of incident AAA, analyzed the effectiveness of a combined clinical-genetic risk model, and explored the clinical utility of the model in identifying high-risk individuals for AAA screening.

METHODS

PRSAAA was calculated using 911,440 SNVs and PRS of coronary artery disease was calculated using 2,324,683 SNVs derived from mixed ancestry genome-wide association studies. The UK Biobank was used as the study cohort. All individuals with complete genetic data available and no diagnosis of AAA at the time of recruitment were included in the analysis and followed prospectively to assess for incident AAA. A PRS-informed clinical model, Prob-AAA, was developed using clinically significant variables and PRSAAA.

RESULTS

Four hundred eighty-one thousand one hundred 5 individuals were included in the analysis with 2,668 incident AAA cases. Incident AAA increased from 0.30 to 0.93% between the lowest and highest decile of PRSAAA; similarly, severe AAA, requiring surgery and/or presenting with rupture, increased from 23 to 39% of incident AAA cases across deciles. PRSAAA was a predictor of incident AAA diagnosis (hazard ratio 2.06 [1.70-2.48]) independent of other clinical risk factors including male sex, older age, and smoking history. Prob-AAA was an independent predictor of incident AAA (hazard ratio 1.92 [1.69-2.20]), and identified 9.6% of cases of incident AAA compared to only 4.2% by PRSAAA. Current screening guidelines captured 5.7% of the overall cohort, with an incident AAA rate of approximately 3.2%. Among males not included by current guidelines, Prob-AAA identified an additional cohort, approximately 2% of the overall cohort, with a similar rate of incident AAA.

CONCLUSIONS

Prob-AAA, a PRS-informed clinical model for AAA, improved upon the predictive power of current, clinical risk factor-informed, screening guidelines for AAA.

Pervasive biases in proxy genome-wide association studies based on parental history of Alzheimer's disease

Almost every recent Alzheimer's disease (AD) genome-wide association study (GWAS) has performed meta-analysis to combine studies with clinical diagnosis of AD with studies that use proxy phenotypes based on parental disease history. Here, we report major limitations in current GWAS-by-proxy (GWAX) practices due to uncorrected survival bias and nonrandom participation in parental illness surveys, which cause substantial discrepancies between AD GWAS and GWAX results. We demonstrate that the current AD GWAX provide highly misleading genetic correlations between AD risk and higher education, which subsequently affects a variety of genetic epidemiological applications involving AD and cognition. Our study sheds light on potential issues in the design and analysis of middle-aged biobank cohorts and underscores the need for caution when interpreting genetic association results based on proxy-reported parental disease history.

Sex-Specific Association Between Genetic Risk of Psychiatric Disorders and Cardiovascular Diseases

BACKGROUND

Though epidemiological studies show increased cardiovascular disease (CVD) risks among individuals with psychiatric disorders, findings on sex differences in comorbidity have been inconsistent.

METHODS

This genetic epidemiology study examined the sex-specific association between the genetic risk of 3 psychiatric disorders (major depression [MD], schizophrenia, and bipolar disorder), estimated using polygenic scores (PGSs), and risks of 3 CVDs (atrial fibrillation [AF], coronary artery disease [CAD], and heart failure [HF]) in 345 169 European-ancestry individuals (UK Biobank), with analyses replicated in an independent BioVU cohort (n=49 057). Mediation analysis was conducted to determine whether traditional CVD risk factors could explain any observed sex difference.

RESULTS

In the UK Biobank, a 1-SD increase in PGSMD was significantly associated with the incident risks of all 3 CVDs in females after multiple testing corrections (hazard ratio [HR]AF-female=1.04 [95% CI, 1.02-1.06]; P=1.5×10-4; HRCAD-female=1.07 [95% CI, 1.04-1.11]; P=2.6×10-6; and HRHF-female=1.09 [95% CI, 1.06-1.13]; P=9.7×10-10), but not in males. These female-specific associations remained even in the absence of any psychiatric disorder diagnosis or psychiatric medication use. Although mediation analysis demonstrated that the association between PGSMD and CVDs in females was partly mediated by baseline body mass index, hypercholesterolemia, hypertension, and smoking, these risk factors did not explain the higher risk compared with males. The association between PGSMD and CAD was consistent between females who were premenopausal and postmenopausal at baseline, while the association with AF and HF was only observed in the baseline postmenopausal cohort. No significant association with CVD risks was observed for the PGS of schizophrenia or bipolar disorder. The female-specific positive association of PGSMD with CAD risk was replicated in BioVU.

CONCLUSIONS

Genetic predisposition to MD confers a greater risk of CVDs in females versus males, even in the absence of any depression diagnosis. This study warrants further investigation into whether genetic predisposition to depression could be useful for improving cardiovascular risk prediction, especially in women.

Investigating the influence of oral contraceptive pill use on multiple sclerosis risk using UK Biobank data

OBJECTIVE

To investigate the association between oral contraceptive (OC) pill use and the risk of developing multiple sclerosis (MS), attempting to address the limitations present in previous studies that produced conflicting results.

DESIGN

A population-based cohort study using data from the UK Biobank.

PATIENTS

The study included 181,058 women of white ethnicity born in England between 1937 and 1970, among which 1,131 had an MS diagnosis.

INTERVENTION

Oral contraceptive use, considering the self-reported age of initiation and discontinuation. The exposures of interest include the following: ever-use, current use, duration of current use in years, and age and year at initiation.

MAIN OUTCOME MEASURES

Multiple sclerosis diagnosis (International Classification of Disease, 10th revision: G35) was used as an outcome of interest, and the associations with the exposures of interest were investigated using marginal structural models with a time-to-event approach. To adjust for confounding, we included in the models several variables, including MS polygenic risk score, education level, parity, smoking, fertility problems, obesity, and mononucleosis. We further aimed to evaluate the influence of parity using a mediation analysis.

RESULTS

The association of both ever and current OC use did not result in a statistically significant MS hazard increase (ever vs. never-users, hazard ratio [HR] = 1.30 [95% confidence interval {CI}: 0.93,1.82]; current vs. never-users, HR = 1.35 [95% CI: 0.81, 2.25]). However, we highlighted parity as an effect modifier for this association. In nulliparous women, ever and current use resulted in a significant twofold and threefold MS hazard increase (HR = 2.08 [95% CI: 1.04, 4.17] and HR = 3.15 [95% CI: 1.43, 6.9]). These associations were supported by significant MS hazard increases for a higher duration of current use and for an earlier age at initiation. We further highlighted genetic MS susceptibility as another effect modifier, as a stronger OC-MS hazard association was found in women with a low MS polygenic risk score.

CONCLUSION

Our findings highlighted how the association between OC use and MS varies on the basis of individual characteristics such as parity and genetic MS susceptibility. Importantly, current use in nulliparous women was found to be associated with a threefold increase in MS hazard. We acknowledge the need for cautious causal interpretation and further research to validate these findings across diverse populations and OC types.

Telomere length and cognitive changes in 7,877 older UK adults of European ancestry

Background

Telomere length (TL) has been linked to cognitive function, decline and dementia. This study aimed to explore whether both measured TL and genetic disposition for TL predict dimensions of cognitive performance in a longitudinal sample of older UK adults.

Methods

We analysed data from PROTECT study participants aged ≥50 years without a dementia diagnosis, who had completed longitudinal cognitive testing. We calculated polygenic scores for telomere length (PGS-TL) for 7,877 participants and measured relative telomere length (RTL) in a subgroup of 846 participants using DNA extracted from saliva samples collected within 6 months either side of their baseline cognitive testing. Latent growth models were used to examine whether RTL and PGS-TL predict both baseline and longitudinal changes in cognitive performance (4 time-points, annually).

Results

In the whole sample, we did not observe significant associations between either measure of telomere length and initial or longitudinal changes in cognitive performance. Stratifying by median age, in older adults (≥ ∼62 years), longer baseline RTL showed a nominal association with poorer baseline verbal reasoning performance (n = 423, M intercept = 47.58, B = -1.05, p = .011) and PGS-TL was associated with performance over time (n = 3,939; slope factor, M slope = 3.23, B = -0.45, p = .001; slope 2 factor, M slope 2 = 0.21, B = 0.13, p = .002).

Conclusion

Our findings suggest either the absence of a significant relationship between telomere length (RTL and PGS-TL) and cognitive performance (baseline and change over time), or possibly a weak age-dependent and domain-specific relationship, in older adults of European ancestry. More research is needed in representative and ancestrally diverse samples over a longer assessment period. Alternative biological ageing indicators may still provide utility in the early detection of individuals at risk for cognitive decline (e.g., pace-of ageing epigenetic clocks).

Alcohol Use Disorder-Associated DNA Methylation in the Nucleus Accumbens and Dorsolateral Prefrontal Cortex

Background

Alcohol use disorder (AUD) has a profound public health impact. However, understanding of the molecular mechanisms that underlie the development and progression of AUD remains limited. Here, we investigated AUD-associated DNA methylation changes within and across 2 addiction-relevant brain regions, the nucleus accumbens and dorsolateral prefrontal cortex.

Methods

Illumina HumanMethylation EPIC array data from 119 decedents (61 cases, 58 controls) were analyzed using robust linear regression with adjustment for technical and biological variables. Associations were characterized using integrative analyses of public annotation data and published genetic and epigenetic studies. We also tested for brain region-shared and brain region-specific associations using mixed-effects modeling and assessed implications of these results using public gene expression data from human brain.

Results

At a false discovery rate of ≤.05, we identified 105 unique AUD-associated CpGs (annotated to 120 genes) within and across brain regions. AUD-associated CpGs were enriched in histone marks that tag active promoters, and our strongest signals were specific to a single brain region. Some concordance was found between our results and those of earlier published alcohol use or dependence methylation studies. Of the 120 genes, 23 overlapped with previous genetic associations for substance use behaviors, some of which also overlapped with previous addiction-related methylation studies.

Conclusions

Our findings identify AUD-associated methylation signals and provide evidence of overlap with previous genetic and methylation studies. These signals may constitute predisposing genetic differences or robust methylation changes associated with AUD, although more work is needed to further disentangle the mechanisms that underlie these associations and their implications for AUD.

The genetically predicted causal associations between circulating 3-hydroxybutyrate levels and malignant neoplasms: A pan-cancer Mendelian randomization study

OBJECTIVE

The ketogenic diet or exogenous supplementation with 3-hydroxybutyrate (3HB) is progressively gaining recognition as a valuable therapeutic or health intervention strategy. However, the effects of 3HB on cancers have been inconsistent in previous studies. This study aimed to comprehensively investigate the causal effects of circulating 3HB levels on 120 cancer phenotypes, and explore the 3HB mediation effect between liver fat accumulation and cancers.

METHODS

Univariate Mendelian randomization (UVMR) was used in this study to investigate the causal impact of circulating 3HB levels on cancers. We conducted meta-analyses for 3HB-cancer associations sourced from different exposure data. In multivariate MR(MVMR), the body mass index, alcohol frequency and diabetes were included as covariates to investigate the independent effect of 3HB on cancer risk. Additionally, utilizing mediation MR analysis, we checked the potential mediating role of 3HB in the association between liver fat and cancer.

RESULTS

Integrating findings from UVMR and MVMR, we observed that elevated circulating 3HB levels were associated with reduced risk of developing diffuse large B-cell lymphoma(DLBCL) (OR[95%CI] = 0.28[0.14-0.57] p = 3.92e-04), biliary malignancies (OR[95%CI] = 0.30[0.15-0.60], p = 7.67e-04), hepatocellular carcinoma(HCC) (OR[95%CI] = 0.25[0.09-0.71], p = 9.33e-03), primary lymphoid and hematopoietic malignancies (OR[95%CI] = 0.76[0.58-0.99], p = 0.045). Further UVMR analysis revealed that an increase in the percent liver fat was associated with reduced 3HB levels (Beta[95%CI] = -0.073[-0.122∼-0.024], p = 0.0034) and enhanced susceptibility to HCC (OR[95%CI] = 13.9[9.76-19.79], p = 3.14e-48), biliary malignancies (OR[95%CI] = 4.04[3.22-5.07], p = 1.64e-33), nasopharyngeal cancer (OR[95%CI] = 3.26[1.10-9.67], p = 0.03), and primary lymphoid and hematopoietic malignancies (OR[95%CI] = 1.27[1.13-1.44], p = 1.04e-4). Furthermore, 3HB fully mediated the effect of liver fat on susceptibility to DLBCL (OR[95%CI] = 1.076[1.01-1.15], p = 0.034).

CONCLUSIONS

Circulating 3HB is associated with a reduced susceptibility to developing DLBCL, HCC, biliary malignancies, and primary lymphoid and hematopoietic malignancies. The impaired ketogenesis induced by metabolic-dysfunction associated fatty liver disease (MAFLD) contributes to risk of DLBCL.

A meta-analysis and polygenic score study identifies novel genetic markers for waist-hip ratio in African populations

OBJECTIVE

Understanding the genetic underpinnings of anthropometric traits in diverse populations is crucial for gaining insights into their biological mechanisms and potential implications for health.

METHODS

We conducted a genome-wide association study, meta-analysis, and gene set analysis of waist-hip ratio (WHR), WHR adjusted for BMI (WHRadjBMI), waist circumference, BMI, and height using the African Collaborative Center for Microbiome and Genomics Research (ACCME) cohort (n = ~11,000) for discovery and polygenic score target analyses and the Africa America Diabetes Mellitus (AADM) study (n = ~5200) for replication and polygenic score validation. We generated and compared polygenic scores from European, African, Afro-Caribbean, and multiethnic ancestry populations.

RESULTS

The top loci associated with each trait in the meta-analysis were in CD36 (rs3211826 [p = 5.90 × 10-12] for WHR and rs73709003 [p = 1.75 × 10-13] for WHRadjBMI), IFI27L1 (rs59775050 [p = 2.66 × 10-08] for waist circumference), INPP4B (rs2636629 [p = 1.44 × 10-09] for BMI), and HMGA1 (rs6937622 [p = 1.40 × 10-15] for height) gene regions. A novel variant rs7797157, near GNAT3, was also significantly associated with WHR (p = 2.50 × 10-10) and WHRadjBMI (p = 2.66 × 10-11). The ancestry-specific parameters for the best predictive polygenic scores were European ancestry (R2 = 0.68%; p = 1.63 × 10-16) and multiethnic ancestry (R2 = 0.06%; p = 1.29 × 10-02) for WHR; European ancestry (R2 = 1.36%; p = 2.94 × 10-31) and multiethnic ancestry (R2 = 1.12%; p = 3.52 × 10-25) for BMI; and European ancestry (R2 = 3.16%; p = 2.95 × 10-73), African ancestry (R2 = 4.16%; p = 1.75 × 10-96), and African and Afro-Caribbean ancestry (R2 = 2.67%; p = 4.35 × 10-62) for height.

CONCLUSIONS

The discovery of a novel locus for WHR and genetic signals for each trait and the assessment of polygenic score performance underscore the importance of conducting well-powered studies in diverse populations.

Reducing Information and Selection Bias in EHR-Linked Biobanks via Genetics-Informed Multiple Imputation and Sample Weighting

Electronic health records (EHRs) are valuable for public health and clinical research but are prone to many sources of bias, including missing data and non-probability selection. Missing data in EHRs is complex due to potential non-recording, fragmentation, or clinically informative absences. This study explores whether polygenic risk score (PRS)-informed multiple imputation for missing traits, combined with sample weighting, can mitigate missing data and selection biases in estimating disease-exposure associations. Simulations were conducted for missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR) conditions under different sampling mechanisms. PRS-informed multiple imputation showed generally lower bias, particularly when combined with sample weighting. For example, in biased samples of 10,000 with exposure and outcome MAR data, PRS-informed imputation had lower percent bias (3.8%) and better coverage rate (0.883) compared to PRS-uninformed (4.5%; 0.877) and complete case analyses (10.3%; 0.784) in covariate-adjusted, weighted, multiple imputation scenarios. In a case study using Michigan Genomics Initiative (n=50,026) data, PRS-informed imputation aligned more closely with a sample-weighted All of Us-derived benchmark than analyses ignoring missing data and selection bias. Researchers should consider leveraging genetic data and sample weighting to address biases from missing data and non-probability sampling in biobanks.

Associations between polygenic scores for cognitive and non-cognitive factors of educational attainment and measures of behavior, psychopathology, and neuroimaging in the adolescent brain cognitive development study

BACKGROUND

Educational attainment (EduA) is correlated with life outcomes, and EduA itself is influenced by both cognitive and non-cognitive factors. A recent study performed a 'genome-wide association study (GWAS) by subtraction,' subtracting genetic effects for cognitive performance from an educational attainment GWAS to create orthogonal 'cognitive' and 'non-cognitive' factors. These cognitive and non-cognitive factors showed associations with behavioral health outcomes in adults; however, whether these correlations are present during childhood is unclear.

METHODS

Using data from up to 5517 youth (ages 9-11) of European ancestry from the ongoing Adolescent Brain Cognitive DevelopmentSM Study, we examined associations between polygenic scores (PGS) for cognitive and non-cognitive factors and cognition, risk tolerance, decision-making & personality, substance initiation, psychopathology, and brain structure (e.g. volume, fractional anisotropy [FA]). Within-sibling analyses estimated whether observed genetic associations may be consistent with direct genetic effects.

RESULTS

Both PGSs were associated with greater cognition and lower impulsivity, drive, and severity of psychotic-like experiences. The cognitive PGS was also associated with greater risk tolerance, increased odds of choosing delayed reward, and decreased likelihood of ADHD and bipolar disorder; the non-cognitive PGS was associated with lack of perseverance and reward responsiveness. Cognitive PGS were more strongly associated with larger regional cortical volumes; non-cognitive PGS were more strongly associated with higher FA. All associations were characterized by small effects.

CONCLUSIONS

While the small sizes of these associations suggest that they are not effective for prediction within individuals, cognitive and non-cognitive PGS show unique associations with phenotypes in childhood at the population level.

Clinical Phenotypes Associated With Cerebral Small Vessel Disease: A Study of 45,013 UK Biobank Participants

BACKGROUND AND OBJECTIVES

Cerebral small vessel disease (cSVD) is the most common pathology underlying vascular cognitive impairment. Although other clinical features of cSVD are increasingly recognized, it is likely that certain symptoms are being overlooked. A comprehensive description of cSVD associations with clinical phenotypes at scale is lacking. The objective of this study was to conduct a large-scale, hypothesis-free study of associations between cSVD and clinical phenotypes in UK Biobank (UKB).

METHODS

We included participants from the UKB imaging study who had available information on total volume of white matter hyperintensities (WMHs), the most common cSVD neuroimaging feature. We included various UKB variables describing clinical phenotypes, defined as observable signs and symptoms of individuals with concurrent neuroimaging evidence of cSVD. We conducted a phenome scan using the open-source PHESANT software package. Total volume of WMHs was introduced as the independent variable and clinical phenotypes as the dependent variables in the regression model. The association of each phenotype with total volume of WMHs was tested using one of several regression analyses (all age at recruitment and sex-adjusted). All associations were corrected for multiple comparisons using the false discovery rate (FDR) correction method.

RESULTS

We included 45,013 participants in the analysis (mean age = 54.97 years, SD = 7.55). We confirm previously reported associations with depression (odds ratio [OR] = 1.07 [95% CI 1.05-1.10]), apathy (OR = 1.11 [95% CI 1.08-1.14]), falls (OR = 1.11 [95% CI 1.09-1.13]), respiratory problems (OR = 1.14 [95% CI 1.04-1.25]), and sleep disturbance (OR = 1.07 [95% CI 1.04-1.09], all FDR-adjusted p < 0.001). We further identified associations with all-cause dental issues (OR = 0.94 [95% CI 0.96-0.92]), hearing problems (OR = 1.06 [95% CI 1.03-1.08]), and eye problems (OR = 0.93 [95% CI 0.91-0.95], all FDR-adjusted p < 0.001).

DISCUSSION

Our findings suggest that presence of cSVD associates with concurrent clinical phenotypes across several body systems. We have corroborated established associations of cSVD and present novel ones. While our results do not provide causality or direction of association because of the cross-sectional nature of our study, they support the need for a more holistic view of cSVD in research, practice, and policy.

Sex-specific Genetic Determinants of Right Ventricular Structure and Function

RATIONALE

While sex differences in right heart phenotypes have been observed, the molecular drivers remain unknown.

OBJECTIVES

To provide biological insights into sex differences in the structure and function of the right ventricle (RV) using common genetic variation.

METHODS

RV phenotypes were obtained from cardiac magnetic resonance imaging in 18,156 women and 16,171 men from the UK Biobank. Observational analyses and sex-stratified genome-wide association studies were performed. Candidate female-specific loci were evaluated against invasively measured cardiac performance in 479 female patients with idiopathic or heritable pulmonary arterial hypertension (PAH), recruited to the UK NIHR BioResource Rare Diseases study.

MEASUREMENTS AND MAIN RESULTS

Sex was associated with differences in RV volumes and ejection fraction in models adjusting for left heart counterparts, blood pressure, lung function and sex hormone levels. Six genome-wide significant loci (13%) revealed heterogeneity of allelic effects between women and men, and significant sex-by-genotype interaction. These included two sex-specific candidate loci present in women only: a locus for RV ejection fraction in BMPR1A and a locus for RV end-systolic volume near DMRT2. Epigenetic data in RV tissue indicate that variation at the BMPR1A locus likely alters transcriptional regulation. In female patients with PAH, a variant located in the promoter of BMPR1A was significantly associated with cardiac index (effect size 0.16 l/min/m2), despite similar RV afterload.

CONCLUSIONS

BMPR1A has emerged as a biologically plausible candidate gene for female-specific genetic determination of RV function, showing associations with cardiac performance under chronically increased afterload in female patients with PAH.

The methodological and ethical concerns of genetic studies of same-sex sexual behavior

Same-sex sexual behavior has long interested genetics researchers in part because, while there is evidence of heritability, the trait as typically defined is associated with fewer offspring. Investigations of this phenomenon began in the 1990s with linkage studies and continue today with the advent of genome-wide association studies. As this body of research grows, so does critical scientific and ethical review of it. Here, we provide a targeted overview of existing genetics studies on same-sex sexual behavior, highlight the ethical and scientific considerations of this nascent field, and provide recommendations developed by the authors to enhance social and ethical responsibility.

Increasing Representativeness in the All of Us Cohort Using Inverse Probability Weighting

Large-scale population biobanks rely on volunteer participants, which may introduce biases that compromise the external validity of epidemiological studies. We characterized the volunteer participant bias for the All of Us Research Program cohort and developed a set of inverse probability (IP) weights that can be used to mitigate this bias. The All of Us cohort is older, more female, more educated, more likely to be covered by health insurance, less White, less likely to drink or smoke, and less healthy compared to the US population. IP weights developed via comparison of a nationally representative database eliminated the observed biases for all demographic and lifestyle characteristics and reduced the observed disease prevalence differences. IP weights also impact genetic associations with type 2 diabetes across diverse ancestry cohorts. We provide our IP weights as a community resource to increase the representativeness and external validity of the All of Us cohort.

A novel classification framework for genome-wide association study of whole brain MRI images using deep learning

Genome-wide association studies (GWASs) have been widely applied in the neuroimaging field to discover genetic variants associated with brain-related traits. So far, almost all GWASs conducted in neuroimaging genetics are performed on univariate quantitative features summarized from brain images. On the other hand, powerful deep learning technologies have dramatically improved our ability to classify images. In this study, we proposed and implemented a novel machine learning strategy for systematically identifying genetic variants that lead to detectable nuances on Magnetic Resonance Images (MRI). For a specific single nucleotide polymorphism (SNP), if MRI images labeled by genotypes of this SNP can be reliably distinguished using machine learning, we then hypothesized that this SNP is likely to be associated with brain anatomy or function which is manifested in MRI brain images. We applied this strategy to a catalog of MRI image and genotype data collected by the Alzheimer's Disease Neuroimaging Initiative (ADNI) consortium. From the results, we identified novel variants that show strong association to brain phenotypes.

Mendelian randomization studies of periodontitis: Understanding benefits and natural limitations in an applied context

Mendelian randomization (MR) is a flexible analytical tool that has been widely applied to strengthen causal inference in observational epidemiology and is now gaining attention in many areas including periodontal research. The interpretation of results drawn from MR is based on a series of assumptions, which can be unrealistic or difficult to meet faithfully in some settings. However, we argue that with care, this does not necessarily prevent valuable deployment of the approach. We argue that clarity of presentation as well as careful assessment of specific analytical conditions is a fundamental part of all MR analyses. To that end, awareness of its limitations should also guide the design of MR investigations and the presentation of results rather than rule out its use altogether. Notably, considerations similar to those known to be important in conventional epidemiological settings apply to MR. While MR studies are valuable in their contrast to other study limitations, the application of this technique must be carefully cross-examined. Specific considerations include possible confounders, recruitment strategy and phenotypic measurement and differential analysis properties across studies. In the case of periodontal research, current MR applications are limited by the available evidence base for genetic contributions to periodontitis; however, this sets a specific scene for the strategic use of MR and shines light on a need for greater research emphasis on the genetics of the condition and intermediaries. This article provides a perspective on the uses and inherent limitations of MR studies and the importance of adhering to basic epidemiological principles when designing them.

Improving prediction models of amyotrophic lateral sclerosis (ALS) using polygenic, pre-existing conditions, and survey-based risk scores in the UK Biobank

BACKGROUND AND OBJECTIVES

Amyotrophic lateral sclerosis (ALS) causes profound impairments in neurological function, and a cure for this devastating disease remains elusive. This study aimed to identify pre-disposing genetic, phenotypic, and exposure-related factors for amyotrophic lateral sclerosis using multi-modal data and assess their joint predictive potential.

METHODS

Utilizing data from the UK (United Kingdom) Biobank, we analyzed an unrelated set of 292 ALS cases and 408,831 controls of European descent. Two polygenic risk scores (PRS) are constructed: "GWAS Hits PRS" and "PRS-CS," reflecting oligogenic and polygenic ALS risk profiles, respectively. Time-restricted phenome-wide association studies (PheWAS) were performed to identify pre-existing conditions increasing ALS risk, integrated into phenotypic risk scores (PheRS). A poly-exposure score ("PXS") captures the influence of environmental exposures measured through survey questionnaires. We evaluate the performance of these scores for predicting ALS incidence and stratifying risk, adjusting for baseline demographic covariates.

RESULTS

Both PRSs modestly predicted ALS diagnosis but with increased predictive power when combined (covariate-adjusted receiver operating characteristic [AAUC] = 0.584 [0.525, 0.639]). PheRS incorporated diagnoses 1 year before ALS onset (PheRS1) modestly discriminated cases from controls (AAUC = 0.515 [0.472, 0.564]). The "PXS" did not significantly predict ALS. However, a model incorporating PRSs and PheRS1 improved the prediction of ALS (AAUC = 0.604 [0.547, 0.667]), outperforming a model combining all risk scores. This combined risk score identified the top 10% of risk score distribution with a fourfold higher ALS risk (95% CI [2.04, 7.73]) versus those in the 40%-60% range.

DISCUSSION

By leveraging UK Biobank data, our study uncovers pre-disposing ALS factors, highlighting the improved effectiveness of multi-factorial prediction models to identify individuals at highest risk for ALS.

Population-Based Risk of Psychiatric Disorders Associated With Recurrent Copy Number Variants

Importance

Recurrent copy number variants (rCNVs) have been associated with increased risk of psychiatric disorders in case-control studies, but their population-level impact is unknown.

Objective

To provide unbiased population-based estimates of prevalence and risk associated with psychiatric disorders for rCNVs and to compare risks across outcomes, rCNV dosage type (deletions or duplications), and locus features.

Design, Setting, and Participants

This genetic association study is an analysis of data from the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH) case-cohort sample of individuals born in Denmark in 1981-2008 and followed up until 2015, including (1) all individuals (n = 92 531) with a hospital discharge diagnosis of attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder, major depressive disorder (MDD), or schizophrenia spectrum disorder (SSD) and (2) a subcohort (n = 50 625) randomly drawn from the source population. Data were analyzed from January 2021 to August 2023.

Exposures

Carrier status of deletions and duplications at 27 autosomal rCNV loci was determined from neonatal blood samples genotyped on single-nucleotide variant microarrays.

Main Outcomes and Measures

Population-based rCNV prevalence was estimated with a survey model using finite population correction to account for oversampling of cases. Hazard ratio (HR) estimates and 95% CIs for psychiatric disorders were derived using weighted Cox proportional hazard models. Risks were compared across outcomes, dosage type, and locus features using generalized estimating equation models.

Results

A total of 3547 rCNVs were identified in 64 735 individuals assigned male at birth (53.8%) and 55 512 individuals assigned female at birth (46.2%) whose age at the end of follow-up ranged from 7.0 to 34.7 years (mean, 21.8 years). Most observed increases in rCNV-associated risk for ADHD, ASD, or SSD were moderate, and risk estimates were highly correlated across these disorders. Notable exceptions included high ASD-associated risk observed for Prader-Willi/Angelman syndrome duplications (HR, 20.8; 95% CI, 7.9-55). No rCNV was associated with increased MDD risk. Also, rCNV-associated risk was positively correlated with locus size and gene constraint but not with dosage type. Comparison with published case-control and community-based studies revealed a higher prevalence of deletions and lower associated increase in risk for several rCNVs in iPSYCH2015.

Conclusions and Relevance

This study found that several rCNVs were more prevalent and conferred less risk of psychiatric disorders than estimated previously. Most case-control studies overestimate rCNV-associated risk of psychiatric disorders, likely because of selection bias. In an era where genetics is increasingly being clinically applied, these results highlight the importance of population-based risk estimates for genetics-based predictions.

Cross-ancestry genetic investigation of schizophrenia, cannabis use disorder, and tobacco smoking

Individuals with schizophrenia frequently experience co-occurring substance use, including tobacco smoking and heavy cannabis use, and substance use disorders. There is interest in understanding the extent to which these relationships are causal, and to what extent shared genetic factors play a role. We explored the relationships between schizophrenia (Scz; European ancestry N = 161,405; African ancestry N = 15,846), cannabis use disorder (CanUD; European ancestry N = 886,025; African ancestry N = 120,208), and ever-regular tobacco smoking (Smk; European ancestry N = 805,431; African ancestry N = 24,278) using the largest available genome-wide studies of these phenotypes in individuals of African and European ancestries. All three phenotypes were positively genetically correlated (rgs = 0.17-0.62). Genetic instrumental variable analyses suggested the presence of shared heritable factors, but evidence for bidirectional causal relationships was also found between all three phenotypes even after correcting for these shared genetic factors. We identified 327 pleiotropic loci with 439 lead SNPs in the European ancestry data, 150 of which were novel (i.e., not genome-wide significant in the original studies). Of these pleiotropic loci, 202 had lead variants which showed convergent effects (i.e., same direction of effect) on Scz, CanUD, and Smk. Genetic variants convergent across all three phenotypes showed strong genetic correlations with risk-taking, executive function, and several mental health conditions. Our results suggest that both shared genetic factors and causal mechanisms may play a role in the relationship between CanUD, Smk, and Scz, but longitudinal, prospective studies are needed to confirm a causal relationship.

Screening embryos for polygenic disease risk: a review of epidemiological, clinical, and ethical considerations

BACKGROUND

The genetic composition of embryos generated by in vitro fertilization (IVF) can be examined with preimplantation genetic testing (PGT). Until recently, PGT was limited to detecting single-gene, high-risk pathogenic variants, large structural variants, and aneuploidy. Recent advances have made genome-wide genotyping of IVF embryos feasible and affordable, raising the possibility of screening embryos for their risk of polygenic diseases such as breast cancer, hypertension, diabetes, or schizophrenia. Despite a heated debate around this new technology, called polygenic embryo screening (PES; also PGT-P), it is already available to IVF patients in some countries. Several articles have studied epidemiological, clinical, and ethical perspectives on PES; however, a comprehensive, principled review of this emerging field is missing.

OBJECTIVE AND RATIONALE

This review has four main goals. First, given the interdisciplinary nature of PES studies, we aim to provide a self-contained educational background about PES to reproductive specialists interested in the subject. Second, we provide a comprehensive and critical review of arguments for and against the introduction of PES, crystallizing and prioritizing the key issues. We also cover the attitudes of IVF patients, clinicians, and the public towards PES. Third, we distinguish between possible future groups of PES patients, highlighting the benefits and harms pertaining to each group. Finally, our review, which is supported by ESHRE, is intended to aid healthcare professionals and policymakers in decision-making regarding whether to introduce PES in the clinic, and if so, how, and to whom.

SEARCH METHODS

We searched for PubMed-indexed articles published between 1/1/2003 and 1/3/2024 using the terms 'polygenic embryo screening', 'polygenic preimplantation', and 'PGT-P'. We limited the review to primary research papers in English whose main focus was PES for medical conditions. We also included papers that did not appear in the search but were deemed relevant.

OUTCOMES

The main theoretical benefit of PES is a reduction in lifetime polygenic disease risk for children born after screening. The magnitude of the risk reduction has been predicted based on statistical modelling, simulations, and sibling pair analyses. Results based on all methods suggest that under the best-case scenario, large relative risk reductions are possible for one or more diseases. However, as these models abstract several practical limitations, the realized benefits may be smaller, particularly due to a limited number of embryos and unclear future accuracy of the risk estimates. PES may negatively impact patients and their future children, as well as society. The main personal harms are an unindicated IVF treatment, a possible reduction in IVF success rates, and patient confusion, incomplete counselling, and choice overload. The main possible societal harms include discarded embryos, an increasing demand for 'designer babies', overemphasis of the genetic determinants of disease, unequal access, and lower utility in people of non-European ancestries. Benefits and harms will vary across the main potential patient groups, comprising patients already requiring IVF, fertile people with a history of a severe polygenic disease, and fertile healthy people. In the United States, the attitudes of IVF patients and the public towards PES seem positive, while healthcare professionals are cautious, sceptical about clinical utility, and concerned about patient counselling.

WIDER IMPLICATIONS

The theoretical potential of PES to reduce risk across multiple polygenic diseases requires further research into its benefits and harms. Given the large number of practical limitations and possible harms, particularly unnecessary IVF treatments and discarded viable embryos, PES should be offered only within a research context before further clarity is achieved regarding its balance of benefits and harms. The gap in attitudes between healthcare professionals and the public needs to be narrowed by expanding public and patient education and providing resources for informative and unbiased genetic counselling.

SLC39A8.p.(Ala391Thr) is associated with poorer cognitive ability: a cross-sectional study of schizophrenia and the general UK population

The missense SNP NC_000004.12:g.102267552C>T (SLC39A8.p.(Ala391Thr), rs13107325) in SLC39A8, which encodes a zinc transporter, has been linked to schizophrenia and is the likely causal variant for one of the genome-wide association loci associated with the disorder. We tested whether the schizophrenia-risk allele at p.(Ala391Thr) was associated with schizophrenia-related phenotypes, including positive, negative, and disorganised symptoms, cognitive ability, educational attainment, and age of psychosis onset, within three schizophrenia cohorts (combined N=1,232) and, with equivalent phenotypes, in a sample of population controls (UK Biobank, N=355,069). We used regression analyses controlling for age, sex, and population stratification. Within the schizophrenia cohorts, after correction for multiple testing, p.(Ala391Thr) was not significantly associated with any schizophrenia-related phenotypes. In the unaffected participants from the UK Biobank, the schizophrenia-risk allele at p.(Ala391Thr) was associated with significantly poorer cognitive ability and fluid intelligence, a lower probability of obtaining GCSEs or a degree-level qualification, and fewer years in education. There was no association between p.(Ala391Thr) and self-reported psychotic experiences in this cohort. The schizophrenia-risk allele was associated with poorer cognitive ability, but not psychotic experiences, in a volunteer sample drawn from of the general population. To determine whether p.(Ala391Thr) is associated with cognitive phenotypes in people with schizophrenia, and to understand the role of p.(Ala391Thr) in the aetiology of cognitive impairment in schizophrenia, larger independent samples are required.

Does tea intake increase the risk of anemia? Evidence from a large prospective cohort and Mendelian randomization study

Tea consumption is avoided by some due to concerns about its potential to cause anemia. To clarify this impact, we assessed the association between tea intake and anemia in a Chinese prospective cohort study and by Mendelian randomization (MR). We analyzed associations of tea intake with anemia using data from the baseline (N = 30 085) and three subsequent follow-ups (the first: N = 17 898; the second: N = 10 435; the third: N = 5311) in the Guangzhou Biobank Cohort Study (GBCS). We also assessed the causal effect of tea intake on anemia, hemoglobin (Hgb) and hematocrit (Hct) using two-sample MR with summary statistics from relevant genome-wide association studies and the UK Biobank (N = 447 485). At the baseline, compared with never-drinkers, regular tea drinkers had higher levels of Hgb and Hct and a lower risk of anemia after adjustment for confounders (all P < 0.05; all P for trend ≤0.006). Prospectively, compared with never-drinkers, regular tea drinkers had higher Hgb (g L-1) (β = 0.69; 95% CI, 0.28 to 1.10; P for trend <0.001) and Hct (%) (β = 0.30; 95% CI, 0.19 to 0.41; P for trend <0.001), but no significant difference in anemia risk (OR = 0.91; 95% CI, 0.82 to 1.02; P for trend = 0.071). MR analyses showed no association between tea intake and anemia, Hgb and Hct. Through triangulation of evidence using a Chinese cohort and genetics, tea consumption appears unlikely to impact anemia risk.

Cognitive processing speed and accuracy are intrinsically different in genetic architecture and brain phenotypes

Since the birth of cognitive science, researchers have used reaction time and accuracy to measure cognitive ability. Although recognition of these two measures is often based on empirical observations, the underlying consensus is that most cognitive behaviors may be along two fundamental dimensions: cognitive processing speed (CPS) and cognitive processing accuracy (CPA). In this study, we used genomic-wide association studies (GWAS) data from 14 cognitive traits to show the presence of those two factors and revealed the specific neurobiological basis underlying them. We identified that CPS and CPA had distinct brain phenotypes (e.g. white matter microstructure), neurobiological bases (e.g. postsynaptic membrane), and developmental periods (i.e. late infancy). Moreover, those two factors showed differential associations with other health-related traits such as screen exposure and sleep status, and a significant causal relationship with psychiatric disorders such as major depressive disorder and schizophrenia. Utilizing an independent cohort from the Adolescent Brain Cognitive Development (ABCD) study, we also uncovered the distinct contributions of those two factors on the cognitive development of young adolescents. These findings reveal two fundamental factors underlying various cognitive abilities, elucidate the distinct brain structural fingerprint and genetic architecture of CPS and CPA, and hint at the complex interrelationship between cognitive ability, lifestyle, and mental health.

Causal association among glaucoma, cerebral cortical structures, and Alzheimer's disease: insights from genetic correlation and Mendelian randomization

Glaucoma and Alzheimer's disease are critical degenerative neuropathies with global impact. Previous studies have indicated that glaucomatous damage could extend beyond ocular structures, leading to brain alterations potentially associated with Alzheimer's disease risk. This study aimed to explore the causal associations among glaucoma, brain alterations, and Alzheimer's disease. We conducted a comprehensive investigation into the genetic correlation and causality between glaucoma, glaucoma endophenotypes, cerebral cortical surficial area and thickness, and Alzheimer's disease (including late-onset Alzheimer's disease, cognitive performance, and reaction time) using linkage disequilibrium score regression and Mendelian randomization. This study showed suggestive genetic correlations between glaucoma, cortical structures, and Alzheimer's disease. The genetically predicted all-caused glaucoma was nominally associated with a decreased risk of Alzheimer's disease (OR = 0.96, 95% CI: 0.93-0.99, P = 0.013). We found evidence for suggestive causality between glaucoma (endophenotypes) and 20 cortical regions and between 29 cortical regions and Alzheimer's disease (endophenotypes). Four cortical regions were causally associated with cognitive performance or reaction time at a significant threshold (P < 6.2E-04). Thirteen shared cortical regions between glaucoma (endophenotypes) and Alzheimer's disease (endophenotypes) were identified. Our findings complex causal relationships among glaucoma, cerebral cortical structures, and Alzheimer's disease. More studies are required to clarify the mediation effect of cortical alterations in the relationship between glaucoma and Alzheimer's disease.

Investigating the impact of poverty on mental illness in the UK Biobank using Mendelian randomization

It is unclear whether poverty and mental illness are causally related. Using UK Biobank and Psychiatric Genomic Consortium data, we examined evidence of causal links between poverty and nine mental illnesses (attention deficit and hyperactivity disorder (ADHD), anorexia nervosa, anxiety disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, obsessive-compulsive disorder, post-traumatic stress disorder and schizophrenia). We applied genomic structural equation modelling to derive a poverty common factor from household income, occupational income and social deprivation. Then, using Mendelian randomization, we found evidence that schizophrenia and ADHD causally contribute to poverty, while poverty contributes to major depressive disorder and schizophrenia but decreases the risk of anorexia nervosa. Poverty may also contribute to ADHD, albeit with uncertainty due to unbalanced pleiotropy. The effects of poverty were reduced by approximately 30% when we adjusted for cognitive ability. Further investigations of the bidirectional relationships between poverty and mental illness are warranted, as they may inform efforts to improve mental health for all.

Mitochondrial related variants associated with cardiovascular traits

Introduction

Cardiovascular disease (CVD) is responsible for over 30% of mortality worldwide. CVD arises from the complex influence of molecular, clinical, social, and environmental factors. Despite the growing number of autosomal genetic variants contributing to CVD, the cause of most CVDs is still unclear. Mitochondria are crucial in the pathophysiology, development and progression of CVDs; the impact of mitochondrial DNA (mtDNA) variants and mitochondrial haplogroups in the context of CVD has recently been highlighted.

Aims

We investigated the role of genetic variants in both mtDNA and nuclear-encoded mitochondrial genes (NEMG) in CVD, including coronary artery disease (CAD), hypertension, and serum lipids in the UK Biobank, with sub-group analysis for diabetes.

Methods

We investigated 371,542 variants in 2,527 NEMG, along with 192 variants in 32 mitochondrial genes in 381,994 participants of the UK Biobank, stratifying by presence of diabetes.

Results

Mitochondrial variants showed associations with CVD, hypertension, and serum lipids. Mitochondrial haplogroup J was associated with CAD and serum lipids, whereas mitochondrial haplogroups T and U were associated with CVD. Among NEMG, variants within Nitric Oxide Synthase 3 (NOS3) showed associations with CVD, CAD, hypertension, as well as diastolic and systolic blood pressure. We also identified Translocase Of Outer Mitochondrial Membrane 40 (TOMM40) variants associated with CAD; Solute carrier family 22 member 2 (SLC22A2) variants associated with CAD and CVD; and HLA-DQA1 variants associated with hypertension. Variants within these three genes were also associated with serum lipids.

Conclusion

Our study demonstrates the relevance of mitochondrial related variants in the context of CVD. We have linked mitochondrial haplogroup U to CVD, confirmed association of mitochondrial haplogroups J and T with CVD and proposed new markers of hypertension and serum lipids in the context of diabetes. We have also evidenced connections between the etiological pathways underlying CVDs, blood pressure and serum lipids, placing NOS3, SLC22A2, TOMM40 and HLA-DQA1 genes as common nexuses.

[Causal relationship between sleep phenotype and idiopathic normal pressure hydrocephalus: a two-sample bidirectional Mendelian randomization study]

OBJECTIVE

To explore the causal relationship between sleep phenotype and idiopathic normal pressure hydrocephalus (iNPH) using two-sample bidirectional Mendelian randomization.

METHODS

The exposure data including 8 sleep phenotypes used in this study were obtained from GWAS catalog, FinnGenR10 and MRCIEU GWAS. The outcome data for idiopathic normal-pressure hydrocephalus were obtained from FinnGen R10. We used the inverse-variance weighted (IVW) method to perform the principal analyses. Cochrane Q-statistics test was used to assess the heterogeneity and MR Egger‑intercept test performed to evaluate the pleiotropy for sensitivity analyses.

RESULTS

IVW result showed that frequent daytime nap was associated with higher odds of iNPH (OR=3.3393, 95 CI% : 1.0646-10.4742, P=0.0270). Cochrane Q-statistics test and MR Egger‑intercept test showed that the MR analysis had no pleiotropy or heterogeneity (P > 0.05). The external validation reproduced this result (OR=2.5660, 95 CI% : 1.1680-5.6373, P=0.0189; OR=4.0424, 95 CI% : 1.5709-10.4024, P=0.0038). Reverse Mendelian randomization suggested that iNPH did not have significant impact on sleep phenotype.

CONCLUSION

The frequency of daytime naps is causally associated with iNPH, and reducing the frequency of weekly daytime naps can reduce the risk of iNPH in the elderly population.

Exploring the genetic causal relationship between physical activity and migraine in European population based on Mendelian randomization analysis

Background

Previous studies have shown a connection between physical activity and migraines, but they don't prove a cause-and-effect relationship due to potential biases in observational methods.

Methods

Utilizing accelerometer-measured physical activity data from a cohort of 377,234 participants in the UK Biobank and information from 599,356 European migraine patients (including 48,975 cases and 550,381 controls) obtained from 24 cohorts, we performed a bidirectional Mendelian randomization analysis to investigate the genetic bidirectional causal relationship between accelerometer-measured physical activity and migraines.

Results

Research findings indicated a slight negative genetic correlation between "average acceleration" physical activity (rg  = -0.091, p = 0.011), overall physical activity (rg  = -0.081, p = 0.017), and migraine. Nevertheless, no shared genetic components were observed between migraine and "fraction of accelerations > 425 mg" of physical activity (rg  = -0.124, p = 0.076). The study results also demonstrated a lack of genetic bidirectional causality between accelerometer-measured physical activity and migraine ("average acceleration", OR = 1.002, 95% CI 0.975-1.031, p = 0.855, "fraction of accelerations > 425 mg", OR = 1.127, 95% CI 0.802-1.583, p = 0.488, overall physical activity, OR = 0.961, 95% CI 0.713-1.296, p = 0.799), and vice versa. Additionally, this lack of causal association persists even after adjusting for obesity (OR = 1.005, p = 0.578), education (OR = 1.019, p = 0.143), and depression (OR = 1.005, p = 0.847), either separately or simultaneously.

Conclusion

The Mendelian randomization results based on genetic data do not provide support for a causal association between physical activity and migraine.

Fast and scalable ensemble learning method for versatile polygenic risk prediction

Polygenic risk scores (PRS) enhance population risk stratification and advance personalized medicine, but existing methods face several limitations, encompassing issues related to computational burden, predictive accuracy, and adaptability to a wide range of genetic architectures. To address these issues, we propose Aggregated L0Learn using Summary-level data (ALL-Sum), a fast and scalable ensemble learning method for computing PRS using summary statistics from genome-wide association studies (GWAS). ALL-Sum leverages a L0L2 penalized regression and ensemble learning across tuning parameters to flexibly model traits with diverse genetic architectures. In extensive large-scale simulations across a wide range of polygenicity and GWAS sample sizes, ALL-Sum consistently outperformed popular alternative methods in terms of prediction accuracy, runtime, and memory usage by 10%, 20-fold, and threefold, respectively, and demonstrated robustness to diverse genetic architectures. We validated the performance of ALL-Sum in real data analysis of 11 complex traits using GWAS summary statistics from nine data sources, including the Global Lipids Genetics Consortium, Breast Cancer Association Consortium, and FinnGen Biobank, with validation in the UK Biobank. Our results show that on average, ALL-Sum obtained PRS with 25% higher accuracy on average, with 15 times faster computation and half the memory than the current state-of-the-art methods, and had robust performance across a wide range of traits and diseases. Furthermore, our method demonstrates stable prediction when using linkage disequilibrium computed from different data sources. ALL-Sum is available as a user-friendly R software package with publicly available reference data for streamlined analysis.

Single-nucleus multiomics reveals the disrupted regulatory programs in three brain regions of sporadic early-onset Alzheimer's disease

Sporadic early-onset Alzheimer's disease (sEOAD) represents a significant but less-studied subtype of Alzheimer's disease (AD). Here, we generated a single-nucleus multiome atlas derived from the postmortem prefrontal cortex, entorhinal cortex, and hippocampus of nine individuals with or without sEOAD. Comprehensive analyses were conducted to delineate cell type-specific transcriptomic changes and linked candidate cis-regulatory elements (cCREs) across brain regions. We prioritized seven conservative transcription factors in glial cells in multiple brain regions, including RFX4 in astrocytes and IKZF1 in microglia, which are implicated in regulating sEOAD-associated genes. Moreover, we identified the top 25 altered intercellular signaling between glial cells and neurons, highlighting their regulatory potential on gene expression in receiver cells. We reported 38 cCREs linked to sEOAD-associated genes overlapped with late-onset AD risk loci, and sEOAD cCREs enriched in neuropsychiatric disorder risk loci. This atlas helps dissect transcriptional and chromatin dynamics in sEOAD, providing a key resource for AD research.

Large-scale whole-exome sequencing analyses identified protein-coding variants associated with immune-mediated diseases in 350,770 adults

The genetic contribution of protein-coding variants to immune-mediated diseases (IMDs) remains underexplored. Through whole exome sequencing of 40 IMDs in 350,770 UK Biobank participants, we identified 162 unique genes in 35 IMDs, among which 124 were novel genes. Several genes, including FLG which is associated with atopic dermatitis and asthma, showed converging evidence from both rare and common variants. 91 genes exerted significant effects on longitudinal outcomes (interquartile range of Hazard Ratio: 1.12-5.89). Mendelian randomization identified five causal genes, of which four were approved drug targets (CDSN, DDR1, LTA, and IL18BP). Proteomic analysis indicated that mutations associated with specific IMDs might also affect protein expression in other IMDs. For example, DXO (celiac disease-related gene) and PSMB9 (alopecia areata-related gene) could modulate CDSN (autoimmune hypothyroidism-, psoriasis-, asthma-, and Graves' disease-related gene) expression. Identified genes predominantly impact immune and biochemical processes, and can be clustered into pathways of immune-related, urate metabolism, and antigen processing. Our findings identified protein-coding variants which are the key to IMDs pathogenesis and provided new insights into tailored innovative therapies.