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PubMed2002

Attitudes to bioethical issues: a case study of a screening project.

Commonly expressed in theoretical discussions about ethical problems in the context of epidemiology and screening is the need for more data. A study was carried out involving 21 explorative interviews with participant and nonparticipant mothers in a neonatal research screening project in progress in Sweden, ABIS (All Babies in Southeast Sweden). The respondents were asked, by way of open-ended questions, to give their opinions about certain ethical issues: informed consent; reasons for joining/declining; surrogate decision; the collection, analysis and storage of written and "live" material (biobanks); intervention etc. The ethical implications mentioned in the literature mostly concern the risk of creating distress and anxiety (anxiety and possible stigmatisation in respect of positive or false-positive results, worry about material collected and stored, distress caused by blood sampling procedures, etc.). Our results do not support the idea that the risks are substantial. The respondents rather indicate an attitude of benevolence--they are positive both to the current research on children, to the material they contribute (both written material and "biomaterial"), to possible results and intervention plans. On the other hand the participants expressed concern about the storage of material and the right to be informed of any screening/project results. Further studies in this field are needed and would be of help in theoretical discussion, the work of ethical committees and the designing of, for example, screening and research projects.

Anxiety↗

PubMed2026

Sex differences in the genetic and causal relationships between depression, smoking, and alcohol use: the role of socioeconomic status.

Major depressive disorder (MDD), smoking, and drinking frequently co-occur, with evidence suggesting these relationships may differ by sex. However, the direction of causality and the extent of sex-specific associations remain unclear. We investigated sex-specific genetic relationships between MDD and substance use phenotypes using genome-wide association studies (GWAS) from the UK Biobank and publicly available sex-stratified GWAS for MDD and problematic alcohol use (PAU). Causal effects were assessed using bidirectional, sex-stratified Mendelian randomization (MR). We further applied multivariable MR (MVMR) to evaluate the influence of socioeconomic status (SES). Genetic correlation analyses indicated significant shared genetic architecture between MDD and all substance use traits in sex-combined GWAS. In sex-specific analyses, the correlation between cigarettes per day and MDD was significantly stronger in females, and drinks per week were correlated with MDD only in females. MR analyses showed that genetic liability to MDD increased the risk of smoking initiation and PAU in females, and was associated with reduced alcohol drinking frequency in males. In contrast, no tested substance use trait showed evidence of a causal effect on MDD in either sex. MVMR adjusting for SES attenuated the association between MDD and smoking initiation. The effect on PAU in females remained. In males, the negative association between MDD and drinking frequency became non-significant after SES adjustment. These findings reveal sex-specific genetic and causal relationships between smoking, drinking, and MDD, and highlight the role of SES as a potential confounder. Incorporating sex and socioeconomic context is critical when examining these associations.

Humans↗

PubMed2004

Determination of hereditary mutations in the BRCA1 gene using archived serum samples and capillary electrophoresis.

Analysis of DNA variation in biological samples most frequently utilizes the polymerase chain reaction (PCR) performed on extracted genomic DNA, followed by visualization of alleles using various methodologies. Few reports have demonstrated that amplification of DNA from plasma and serum samples is possible. We have performed DNA amplification on a large set of serum samples (n = 2955). Here, we report that known hereditary mutations in the BRCA gene can efficiently be analyzed in serum samples collected and stored over several decades. Fragments were PCR-amplified following a short initial denaturation of the serum sample in a standard microwave oven. Fragment analysis was subsequently performed using a DNA capillary-sequencing instrument. The PCR success rates were fragment- and size-dependent ranging from 83.2% to 97.9%. Of the 11,820 polymerase chain reactions performed, the overall PCR success rate was 91.3% (10,796/11,820), which is comparable to PCR performed on genomic DNA. The advantage of the method described herein is its ability to utilize archival material stored in serum biobanks for long periods of time.

Base Sequence↗

PubMed2006

Human dignity: a guide to policy making in the biotechnology era?

This article explores the ways in which human dignity is used in debates about controversial biotechnologies, including biobanks, human gene patents, stem cell research and human cloning. Increasingly, human dignity is used as a form of general condemnation and as blanket justification for regulatory restraint. However, this use of human dignity marks a significant departure from the traditional, human-rights informed view of human dignity that has dominated bioethics debates for decades. In addition, on its own, it stands as dubious justification for policies that are aimed at constraining controversial biotechnologies.

Bioethical Issues↗

PubMed2026

Genetic architecture of postpartum psychosis: from common to rare genetic variation.

Postpartum psychosis is a severe psychiatric condition marked by the abrupt onset of psychosis, mania, or psychotic depression following childbirth. Despite evidence for a strong genetic basis, the roles of common and rare genetic variation remain poorly understood. Leveraging data from Swedish national registers and genomic data from the All of Us Research Program, we estimated family-based heritability at 55% and whole-genome sequencing-based heritability at 46%. Rare coding variant analysis identified HMGCR as a gene in which rare damaging variants confer risk for postpartum psychosis (FDR < 0.05). Analyses of 240,009 participants from the All of Us Research Program and 58,990 participants from the Mount Sinai BioMe Biobank identified significant associations linking deleterious rare variants in HMGCR to vascular dementia and mental disorder, not otherwise specified, supporting the gene's broader psychiatric relevance. Additionally, among the top 200 genes ranked by association statistics, 17% of bipolar disorder, 21% of schizophrenia, and 16-25% of multiple autoimmune disorders exhibit a possible association with postpartum psychosis. These findings reveal unique genetic contributions and shared pathways, providing a foundation for understanding pathophysiology and advancing therapeutic strategies.

Humans↗

PubMed2026

Leveraging the genetics of psychiatric disorders to prioritize potential drug targets and compounds.

Genetics can inform biologically relevant drug development and repurposing, which may improve patient care. Here, we leverage the genetics of psychiatric disorders to prioritize potential drug targets and compounds. We used the genome-wide association studies of four psychiatric disorders [attention deficit hyperactivity disorder (ADHD), bipolar disorder, depression, and schizophrenia] and genes encoding drug targets. We conducted drug enrichment analyses incorporating the novel and biologically specific GSA-MiXeR tool. We conducted multiple molecular trait analyses using large-scale transcriptomic and proteomic datasets sampled from brain and blood tissue. This included the novel use of the UK Biobank proteomic data for a proteome-wide association study of psychiatric disorders. With the accumulated evidence, we prioritize potential drug targets and compounds for each disorder. We reveal candidate drug targets associated with a single or multiple disorders that implicate glutamate signaling. Drug prioritization indicated genetic support for psychotropic medications, including several top-ranked antipsychotics for schizophrenia. We also observed genetic support for commonly used psychotropics for psychiatric treatment (e.g., clozapine, duloxetine, and lithium). Revealed opportunities for drug repurposing included cholinergic drugs for ADHD, estrogen modulators for depression, and matrix metalloproteinases for ADHD and depression. Our findings indicate the genetic liability to schizophrenia is associated with reduced brain and blood expression of CYP2D6, a gene encoding a metabolizer of drugs and neurotransmitters, suggesting a genetic risk for poor drug response and altered neurotransmission. Our extensive analyses highlight the utility of genetics for informing drug development and repurposing for psychiatric disorders, providing novel opportunities for improving patient outcomes. Depicted is the series of analyses conducted to generate a list of prioritized drug targets and compounds. First pairings of genome-wide association study (GWAS) traits with drugs are generated using enrichment analyses. Next, a series of molecular trait analyses is conducted to generate and rank a list of potential drug targets for each GWAS trait. Finally, enrichment and molecular trait results are combined to generate a ranked list of prioritized drugs for each GWAS trait based on supporting genetic evidence. ADHD = Attention deficit hyperactivity disorder, BIP = Bipolar disorder, DEP = Depression, SCZ = Schizophrenia, DBP = Diastolic blood pressure, T2D = Type 2 diabetes, RNA = ribonucleic acid, XWAS = both transcriptome and proteome-wide association studies, MR = Mendelian randomization, coloc = colocalization.

Humans↗

PubMed2019

CYP2D6 genotype and adverse events to risperidone in children and adolescents.

BACKGROUND: There are few and conflicting data on the role of cytochrome P450 2D6 (CYP2D6) polymorphisms in relation to risperidone adverse events (AEs) in children. This study assessed the association between CYP2D6 metabolizer status and risk for risperidone AEs in children. METHODS: Children ≤18 years with at least 4 weeks of risperidone exposure were identified using BioVU, a de-identified DNA biobank linked to electronic health record data. The primary outcome of this study was AEs. After DNA sequencing, individuals were classified as CYP2D6 poor, intermediate, normal, or ultrarapid CYP2D6 metabolizers. RESULTS: For analysis, the 257 individuals were grouped as poor/intermediate metabolizers (n = 33, 13%) and normal/ultrarapid metabolizers (n = 224, 87%). AEs were more common in poor/intermediate vs. normal/ultrarapid metabolizers (15/33, 46% vs. 61/224, 27%, P = 0.04). In multivariate analysis adjusting for age, sex, race, and initial dose, poor/intermediate metabolizers had increased AE risk (adjusted odds ratio 2.4, 95% confidence interval 1.1-5.1, P = 0.03). CONCLUSION: Children with CYP2D6 poor or intermediate metabolizer phenotypes are at greater risk for risperidone AEs. Pre-prescription genotyping could identify this high-risk subset for an alternate therapy, risperidone dose reduction, and/or increased monitoring for AEs.

Adolescent↗

PubMed2026

Targeting super elongation complex-driven RNA polymerase II elongation reduces plaque vulnerability.

Atherosclerotic plaque rupture is a major cause of myocardial infarction and stroke, yet the mechanisms governing plaque stability remain incompletely understood. Endothelial activation can trigger endothelial-to-mesenchymal transition, a program linked to endothelial dysfunction and lesion vulnerability. Here we investigated whether transcriptional pause release and RNA polymerase II elongation constitute an early regulatory layer that promotes endothelial-to-mesenchymal transition and atherosclerosis. Analysis of human plaque single-cell transcriptomics indicated increased expression of super elongation complex components in endothelial cells with a transition signature. In primary human endothelial cell models, pharmacological inhibition of the super elongation complex attenuated the induction of mesenchymal markers. AFF4, pCDK9, and pSMAD2/3 showed physical interaction during endothelial transition. Genome-wide profiling of RNA polymerase II occupancy revealed reduced promoter-proximal pausing during early transition, accompanied by a rapid increase in nascent transcriptional elongation rates. Super elongation complex inhibition restored pausing and suppressed fast-responding transition-associated target genes. In a human cardiac organoid model, inhibition of the super elongation complex prevented EndMT-induced fibrillar collagen deposition and prevented the loss of beating rate. In a hyperlipidemic Pcsk9 gain-of-function mouse model, super elongation complex inhibition administered both prophylactically and therapeutically after established atherosclerosis reduced plaque burden and reduced features of plaque vulnerability. Finally, analysis of 1048 human plaque segments from the Athero-Express biobank showed significant associations between the elongation axis and multiple vulnerability-related plaque traits. Together, these findings identify rapid transcriptional elongation as a mechanistic driver of endothelial plasticity and features of plaque vulnerability and support targeting the elongation machinery as a potential strategy to reduce features of plaque vulnerability in atherosclerotic disease.

Humans↗

PubMed2026

Identifying potential therapeutic targets for high myopia via a case-control study and Mendelian randomisation analyses of the human blood metabolome.

BACKGROUND: High myopia increases the risk of pathological ocular changes that may lead to irreversible vision loss. Therefore, the identification of potential biomarkers and therapeutic targets for high myopia is essential for early intervention and prevention. METHODS: Summary statistics for 122 blood metabolites were obtained from three genome-wide association studies (GWASs), whereas data on high myopia were derived from a large GWAS conducted with 50,372 participants from the UK Biobank. Mendelian randomisation (MR) analyses were conducted to assess the causal relationships between blood metabolites and high myopia. A real-world case-control study was conducted to validate the causal associations identified in the MR analyses. RESULTS: The systematic MR analysis identified 5 blood metabolites as both biomarkers and potential drug targets for high myopia, including glutamine (odds ratio [OR]: 0.98, 95% confidence interval [CI]: 0.97-1.00), tyrosine (OR: 0.98; 95% CI: 0.97-0.99), degree of unsaturation (OR: 0.98, 95% CI: 0.98-0.99), docosahexaenoic acid (DHA) (OR: 0.99; 95% CI: 0.98-1.00) and isobutyrylcarnitine (OR: 1.09, 95% CI: 1.05-1.13). The case-control study indicated that the levels of glutamine (OR = 0.76, 95% CI: 0.58-0.98) and tyrosine (OR = 0.72, 95% CI: 0.55-0.94) were significantly associated with a decreased risk of high myopia. CONCLUSIONS: Systematic MR analysis suggested that glutamine, tyrosine, the degree of unsaturation, DHA, and isobutyrylcarnitine may represent promising drug targets for high myopia prevention. Further investigations are needed to validate the therapeutic efficacy and elucidate the underlying mechanisms involved.

Humans↗

PubMed2026

Urate-lowering effects of losartan: a meta-analysis of randomised controlled trials and target trial emulation.

Common in hypertensive patients, hyperuricaemia is often exacerbated by guideline-recommended antihypertensive therapies such as thiazide diuretics. Losartan is known as an angiotensin II receptor type 1 antagonist with a uricosuric effect, but the magnitude of its efficacy in lowering urate has not been quantified versus a placebo-reference. We sought to quantify the urate-lowering effect of losartan versus placebo using two complementary approaches. We first conducted a meta-analysis of randomised controlled trials (RCTs) to quantify the effect of losartan on serum urate levels versus placebo. We then applied a target trial emulation framework in the UK Biobank as a secondary source of data and a replication experiment. The meta-analysis of six prospective randomised controlled trials (RCTs), including 1119 losartan-treated patients and 1093 controls, demonstrated that losartan reduced serum urate levels by approximately 0.29 mg/dL relative to placebo (95% CI: -0.46 to -0.12, p = 0.0009). In the target trial emulation, 23 losartan-treated individuals showed a reduction in serum urate of approximately 0.35 mg/dL (95% CI: -0.66 to -0.03, p = 0.03) when compared with 92 matched controls, and after accounting for 12 potential confounders including established urate-lowering therapies. Our results provide evidence for a modest yet consistent urate-lowering potential of losartan. This modest biochemical effect (~0.3 mg/dL) may be an attractive option to mitigate the diuretic-induced urate elevation. Thus, losartan can be considered as a favourable antihypertensive choice for patients managed with diuretics or those who are at risk of hyperuricaemia/gout.

Losartan↗

PubMed2024

Whole-genome sequencing in 333,100 individuals reveals rare non-coding single variant and aggregate associations with height.

The role of rare non-coding variation in complex human phenotypes is still largely unknown. To elucidate the impact of rare variants in regulatory elements, we performed a whole-genome sequencing association analysis for height using 333,100 individuals from three datasets: UK Biobank (N = 200,003), TOPMed (N = 87,652) and All of Us (N = 45,445). We performed rare ( < 0.1% minor-allele-frequency) single-variant and aggregate testing of non-coding variants in regulatory regions based on proximal-regulatory, intergenic-regulatory and deep-intronic annotation. We observed 29 independent variants associated with height at P < after conditioning on previously reported variants, with effect sizes ranging from -7cm to +4.7 cm. We also identified and replicated non-coding aggregate-based associations proximal to HMGA1 containing variants associated with a 5 cm taller height and of highly-conserved variants in MIR497HG on chromosome 17. We have developed an approach for identifying non-coding rare variants in regulatory regions with large effects from whole-genome sequencing data associated with complex traits.

Humans↗

PubMed2025

Identification of plasma proteomic markers underlying polygenic risk of type 2 diabetes and related comorbidities.

Genomics can provide insight into the etiology of type 2 diabetes and its comorbidities, but assigning functionality to non-coding variants remains challenging. Polygenic scores, which aggregate variant effects, can uncover mechanisms when paired with molecular data. Here, we test polygenic scores for type 2 diabetes and cardiometabolic comorbidities for associations with 2,922 circulating proteins in the UK Biobank. The genome-wide type 2 diabetes polygenic score associates with 617 proteins, of which 75% also associate with another cardiometabolic score. Partitioned type 2 diabetes scores, which capture distinct disease biology, associate with 342 proteins (20% unique). In this work, we identify key pathways (e.g., complement cascade), potential therapeutic targets (e.g., FAM3D in type 2 diabetes), and biomarkers of diabetic comorbidities (e.g., EFEMP1 and IGFBP2) through causal inference, pathway enrichment, and Cox regression of clinical trial outcomes. Our results are available via an interactive portal ( https://public.cgr.astrazeneca.com/t2d-pgs/v1/ ).

Humans↗

PubMed2026

Determinants of functional burden pleiotropy and gene dosage responses across human traits.

Pleiotropic and monotonic effects of gene dosage are central to understanding comorbidities in developmental pediatric and psychiatric disorders, yet the underlying biological processes are not well characterized. Here we develop a functional burden analysis to investigate the association of all protein-coding copy-number variants, genome-wide, with 43 complex traits in approximately 500,000 UK Biobank participants. We test variant associations disrupting 172 tissue or cell-type gene sets, finding associations for all traits, which we replicate in the All of Us cohort. Functional burden pleiotropy, defined as the number of traits significantly associated with a gene set, correlates with genetic constraint and is higher for brain than non-brain functions, even after normalizing for genetic constraint. Levels of pleiotropy, measured by burden correlation, are similar in deletions and loss-of-function single-nucleotide variants, and higher than in common variants and duplications. Most gene dosage responses are non-monotonic, with deletions and duplications showing same-direction effects, and monotonic responses decrease with genetic constraint. We observe associations between functional gene sets and traits for either deletions or duplications, but rarely both, with negatively correlated effect sizes. Together, these results link genetic constraint and brain-specific mechanisms to the whole-body multimorbidity of neurodevelopmental and psychiatric conditions.

Humans↗

PubMed2026

Validation and refinement of a biomarker panel for frailty assessment and prediction of muscle weakness in older adults.

Frailty is a complex geriatric syndrome characterized by age-related declines in physiological function and cognitive reserve. To promote early prevention and intervention, minimally invasive and objective biomarkers that can detect frailty progression are required. We aimed to identify biomarkers associated with frailty progression and to elucidate their relevance to the Japanese version of the Cardiovascular Health Study (J-CHS) criteria, consist of five components (unintentional weight loss, self-reported exhaustion, muscle weakness, slow walking speed, and low physical activity). A total of 168 individuals (61 robust, 25 pre-frail, and 82 frail) enrolled in the NCGG (National Center for Geriatrics and Gerontology) Biobank were analyzed. Clinical information, blood-test data, aging-related factors, and gene-expression data were integrated for the analysis. First, linear regression identified one clinical factor, five aging-related factors, and 251 gene-expression factors associated with frailty. Subsequent logistic regression analyses examining each J-CHS components highlighted six candidate biomarkers. Cross-validation further suggested that three of these biomarkers-SMI, apelin, and GDF15-may represent potential biomarkers. Finally, retrospective and prospective analyses further demonstrated that those biomarkers were predictive of future muscle weakness, yielding a concordance index of 0.70. In conclusion, we validated and refined a biomarker panel consisting of SMI, apelin, and GDF15 that is associated with frailty, particularly muscle weakness (a major J-CHS component). These biomarkers may be useful for frailty assessment. Longitudinal analyses further suggested that they may be associated with the future development of muscle weakness in initially robust older adults, although validation in larger prospective cohorts is warranted.

Journal Article↗

PubMed2026

Correlations between causal effect sizes of proximal SNPs vary with functional annotations and implicate stabilizing selection.

Causal disease effect sizes of proximal single-nucleotide polymorphisms (SNPs) are widely assumed to be independent but could be correlated. Here we introduce a new method, linkage disequilibrium SNP-pair effect correlation regression (LDSPEC), to estimate the correlation of causal disease effect sizes of derived alleles between proximal SNPs; LDSPEC produced robust estimates in simulations. Analyzing 70 UK Biobank diseases and traits (average N = 305,646), we detected significantly non-zero SNP-pair effect correlations (for example, -0.37 ± 0.09 for low-frequency positive linkage disequilibrium 0-100-bp SNP pairs) that decayed with distance and varied with allele frequency and linkage disequilibrium between SNPs. SNP pairs with shared functions had stronger effect correlations that spanned longer genomic distances. Consequently, SNP heritability estimates were smaller than estimates of the sum of causal effect size variances across SNPs, particularly for certain functional annotations. We recapitulated our findings via forward simulations involving stabilizing selection, implicating the action of linkage masking, whereby haplotypes containing linked SNPs with opposite effects on disease have reduced effects on fitness and escape negative selection.

Polymorphism, Single Nucleotide↗

PubMed2026

Prediction of human missense variant effects from functional evidence.

Prediction of missense variant effects remains a critical bottleneck in both research and diagnostic genetics. Current predictors typically rely on clinical outcomes or population patterns rather than direct measures of functional impact, leading to limited generalizability and data circularity. Here we present FuncVEP, a family of variant effect predictors trained on diverse functional data to predict the functional impact of missense variants. FuncVEP generalizes across datasets and outperforms 48 existing predictors across a wide range of benchmarks, improving accuracy from 78.8% to 84.6% on functional benchmarks and from 90.1% to 92.4% on clinical benchmarks. From a discovery perspective, we identified 210 new gene-phenotype associations involving 494 genes linked to inborn errors of immunity in the UK Biobank and the Mount Sinai Million Health Discoveries Program. FuncVEP substantially improved the discovery rate relative to state-of-the-art predictors. Overall, FuncVEP provides a robust, scalable solution for variant interpretation, advancing both diagnostic precision and gene discovery.

Humans↗

PubMed2024

Multi-ancestry polygenic mechanisms of type 2 diabetes.

Type 2 diabetes (T2D) is a multifactorial disease with substantial genetic risk, for which the underlying biological mechanisms are not fully understood. In this study, we identified multi-ancestry T2D genetic clusters by analyzing genetic data from diverse populations in 37 published T2D genome-wide association studies representing more than 1.4 million individuals. We implemented soft clustering with 650 T2D-associated genetic variants and 110 T2D-related traits, capturing known and novel T2D clusters with distinct cardiometabolic trait associations across two independent biobanks representing diverse genetic ancestral populations (African, n = 21,906; Admixed American, n = 14,410; East Asian, n =2,422; European, n = 90,093; and South Asian, n = 1,262). The 12 genetic clusters were enriched for specific single-cell regulatory regions. Several of the polygenic scores derived from the clusters differed in distribution among ancestry groups, including a significantly higher proportion of lipodystrophy-related polygenic risk in East Asian ancestry. T2D risk was equivalent at a body mass index (BMI) of 30 kg m-2 in the European subpopulation and 24.2 (22.9-25.5) kg m-2 in the East Asian subpopulation; after adjusting for cluster-specific genetic risk, the equivalent BMI threshold increased to 28.5 (27.1-30.0) kg m-2 in the East Asian group. Thus, these multi-ancestry T2D genetic clusters encompass a broader range of biological mechanisms and provide preliminary insights to explain ancestry-associated differences in T2D risk profiles.

Humans↗

PubMed2025

Polygenic prediction of body mass index and obesity through the life course and across ancestries.

Polygenic scores (PGSs) for body mass index (BMI) may guide early prevention and targeted treatment of obesity. Using genetic data from up to 5.1 million people (4.6% African ancestry, 14.4% American ancestry, 8.4% East Asian ancestry, 71.1% European ancestry and 1.5% South Asian ancestry) from the GIANT consortium and 23andMe, Inc., we developed ancestry-specific and multi-ancestry PGSs. The multi-ancestry score explained 17.6% of BMI variation among UK Biobank participants of European ancestry. For other populations, this ranged from 16% in East Asian-Americans to 2.2% in rural Ugandans. In the ALSPAC study, children with higher PGSs showed accelerated BMI gain from age 2.5 years to adolescence, with earlier adiposity rebound. Adding the PGS to predictors available at birth nearly doubled explained variance for BMI from age 5 onward (for example, from 11% to 21% at age 8). Up to age 5, adding the PGS to early-life BMI improved prediction of BMI at age 18 (for example, from 22% to 35% at age 5). Higher PGSs were associated with greater adult weight gain. In intensive lifestyle intervention trials, individuals with higher PGSs lost modestly more weight in the first year (0.55 kg per s.d.) but were more likely to regain it. Overall, these data show that PGSs have the potential to improve obesity prediction, particularly when implemented early in life.

Adolescent↗