Whole-exome sequencing in UK Biobank reveals rare genetic architecture for depression.

Nearly two hundred common-variant depression risk loci have been identified by genome-wide association studies (GWAS). However, the impact of rare coding variants on depression remains poorly understood. Here, we present whole-exome sequencing analyses of depression with seven different definitions based on survey, questionnaire, and electronic health records in 320,356 UK Biobank participants. We showed that the burden of rare damaging coding variants in loss-of-function intolerant genes is significantly associated with risk of depression with various definitions. We compared the rare and common genetic architecture across depression definitions by genetic correlation and showed different genetic relationships between definitions across common and rare variants. In addition, we demonstrated that the effects of rare damaging coding variant burden and polygenic risk score on depression risk are additive. The gene set burden analyses revealed overlapping rare genetic variant components with developmental disorder, autism, and schizophrenia. Our study provides insights into the contribution of rare coding variants, separately and in conjunction with common variants, on depression with various definitions and their genetic relationships with neurodevelopmental disorders.

PICALO: principal interaction component analysis for the identification of discrete technical, cell-type, and environmental factors that mediate eQTLs.

Expression quantitative trait loci (eQTL) offer insights into the regulatory mechanisms of trait-associated variants, but their effects often rely on contexts that are unknown or unmeasured. We introduce PICALO, a method for hidden variable inference of eQTL contexts. PICALO identifies and disentangles technical from biological context in heterogeneous blood and brain bulk eQTL datasets. These contexts are biologically informative and reproducible, outperforming cell counts or expression-based principal components. Furthermore, we show that RNA quality and cell type proportions interact with thousands of eQTLs. Knowledge of hidden eQTL contexts may aid in the inference of functional mechanisms underlying disease variants.

TWINGEN - protocol for an observational clinical biobank recall and biomarker study to identify individuals with high risk of Alzheimer's disease.

Introduction: A better understanding of the earliest stages of Alzheimer's disease (AD) could expedite the development or administration of treatments. Large population biobanks hold the promise to identify individuals at an elevated risk of AD and related dementias based on health registry information. Here, we establish the protocol for an observational clinical recall and biomarker study called TWINGEN with the aim to identify individuals at high risk of AD by assessing cognition, health and AD-related biomarkers. Suitable candidates were identified and invited to participate in the new study among Finnish biobank donors according to TWINGEN study criteria. Methods and analysis: A multi-center study (n=800) to obtain blood-based biomarkers, telephone-administered and web-based memory and cognitive parameters, questionnaire information on lifestyle, health and psychological factors, and accelerometer data for measures of physical activity, sedentary behavior and sleep. A sub-cohort are being asked to participate in an in-person neuropsychological assessment (n=200) and wear an Oura ring (n=50). All participants in the TWINGEN study have genome-wide genotyping data and up to 48 years of follow-up data from the population-based older Finnish Twin Cohort (FTC) study of the University of Helsinki. TWINGEN data will be transferred to Finnish Institute of Health and Welfare (THL) biobank and we aim to further to transfer it to the FinnGen study where it will be combined with health registry data for prediction of AD. Ethics and dissemination: This recall study consists of FTC/THL/FinnGen participants whose data were acquired in accordance with the Finnish Biobank Act. The recruitment protocols followed the biobank protocols approved by Finnish Medicines Agency. The TWINGEN study plan was approved by the Ethics Committee of Hospital District of Helsinki and Uusimaa (number 16831/2022). THL Biobank approved the research plan with the permission no: THLBB2022_83.

Rare variant associations with plasma protein levels in the UK Biobank.

Integrating human genomics and proteomics can help elucidate disease mechanisms, identify clinical biomarkers and discover drug targets1-4. Because previous proteogenomic studies have focused on common variation via genome-wide association studies, the contribution of rare variants to the plasma proteome remains largely unknown. Here we identify associations between rare protein-coding variants and 2,923 plasma protein abundances measured in 49,736 UK Biobank individuals. Our variant-level exome-wide association study identified 5,433 rare genotype-protein associations, of which 81% were undetected in a previous genome-wide association study of the same cohort5. We then looked at aggregate signals using gene-level collapsing analysis, which revealed 1,962 gene-protein associations. Of the 691 gene-level signals from protein-truncating variants, 99.4% were associated with decreased protein levels. STAB1 and STAB2, encoding scavenger receptors involved in plasma protein clearance, emerged as pleiotropic loci, with 77 and 41 protein associations, respectively. We demonstrate the utility of our publicly accessible resource through several applications. These include detailing an allelic series in NLRC4, identifying potential biomarkers for a fatty liver disease-associated variant in HSD17B13 and bolstering phenome-wide association studies by integrating protein quantitative trait loci with protein-truncating variants in collapsing analyses. Finally, we uncover distinct proteomic consequences of clonal haematopoiesis (CH), including an association between TET2-CH and increased FLT3 levels. Our results highlight a considerable role for rare variation in plasma protein abundance and the value of proteogenomics in therapeutic discovery.

A FinnGen pilot clinical recall study for Alzheimer's disease.

Successful development of novel therapies requires that clinical trials are conducted in patient cohorts with the highest benefit-to-risk ratio. Population-based biobanks with comprehensive health and genetic data from large numbers of individuals hold promise to facilitate identification of trial participants, particularly when interventions need to start while symptoms are still mild, such as for Alzheimer's disease (AD). This study describes a process for clinical recall studies from FinnGen. We demonstrate the feasibility to systematically ascertain customized clinical data from FinnGen participants with ICD10 diagnosis of AD or mild cognitive disorder (MCD) in a single-center cross-sectional study testing blood-based biomarkers and cognitive functioning in-person, computer-based and remote. As a result, 19% (27/140) of a pre-specified FinnGen subcohort were successfully recalled and completed the study. Hospital records largely validated registry entries. For 8/12 MCD patients, other reasons than AD were identified as underlying diagnosis. Cognitive measures correlated across platforms, with highest consistencies for dementia screening (r = 0.818) and semantic fluency (r = 0.764), respectively, for in-person versus telephone-administered tests. Glial fibrillary acidic protein (GFAP) (p < 0.002) and phosphorylated-tau 181 (pTau-181) (p < 0.020) most reliably differentiated AD from MCD participants. We conclude that informative, customized clinical recall studies from FinnGen are feasible.

Genome-wide study of longitudinal brain imaging measures of multiple sclerosis progression across six clinical trials.

While the genetics of MS risk susceptibility are well-described, and recent progress has been made on the genetics of disease severity, the genetics of disease progression remain elusive. We therefore investigated the genetic determinants of MS progression on longitudinal brain MRI: change in brain volume (BV) and change in T2 lesion volume (T2LV), reflecting progressive tissue loss and increasing disease burden, respectively. We performed genome-wide association studies of change in BV (N = 3401) and change in T2LV (N = 3513) across six randomized clinical trials from Biogen and Roche/Genentech: ADVANCE, ASCEND, DECIDE, OPERA I & II, and ORATORIO. Analyses were adjusted for randomized treatment arm, age, sex, and ancestry. Results were pooled in a meta-analysis, and were evaluated for enrichment of MS risk variants. Variant colocalization and cell-specific expression analyses were performed using published cohorts. The strongest peaks were in PTPRD (rs77321193-C/A, p = 3.9 × 10-7) for BV change, and NEDD4L (rs11398377-GC/G, p = 9.3 × 10-8) for T2LV change. Evidence of colocalization was observed for NEDD4L, and both genes showed increased expression in neuronal and/or glial populations. No association between MS risk variants and MRI outcomes was observed. In this unique, precompetitive industry partnership, we report putative regions of interest in the neurodevelopmental gene PTPRD, and the ubiquitin ligase gene NEDD4L. These findings are distinct from known MS risk genetics, indicating an added role for genetic progression analyses and informing drug discovery.

Genome-Wide Association Study Identifies 4 Novel Risk Loci for Small Intestinal Neuroendocrine Tumors Including a Missense Mutation in LGR5.

BACKGROUND & AIMS: Small intestinal neuroendocrine tumor (SI-NET) is a rare disease, but its incidence has increased over the past 4 decades. Understanding the genetic risk factors underlying SI-NETs can help in disease prevention and may provide clinically beneficial markers for diagnosis. Here the results of the largest genome-wide association study of SI-NETs performed to date with 405 cases and 614,666 controls are reported. METHODS: Samples from 307 patients with SI-NETs and 287,137 controls in the FinnGen study were used for the identification of SI-NET risk-associated genetic variants. The results were also meta-analyzed with summary statistics from the UK Biobank (n = 98 patients with SI-NET and n = 327,529 controls). RESULTS: We identified 6 genome-wide significant (P < 5 × 10-8) loci associated with SI-NET risk, of which 4 (near SEMA6A, LGR5, CDKAL1, and FERMT2) are novel and 2 (near LTA4H-ELK and in KIF16B) have been reported previously. Interestingly, the top hit (rs200138614; P = 1.80 × 10-19) was a missense variant (p.Cys712Phe) in the LGR5 gene, a bona-fide marker of adult intestinal stem cells and a potentiator of canonical WNT signaling. The association was validated in an independent Finnish collection of 70 patients with SI-NETs, as well as in the UK Biobank exome sequence data (n = 92 cases and n = 392,814 controls). Overexpression of LGR5 p.Cys712Phe in intestinal organoids abolished the ability of R-Spondin1 to support organoid growth, indicating that the mutation perturbed R-Spondin-LGR5 signaling. CONCLUSIONS: Our study is the largest genome-wide association study to date on SI-NETs and reported 4 new associated genome-wide association study loci, including a novel missense mutation (rs200138614, p.Cys712Phe) in LGR5, a canonical marker of adult intestinal stem cells.

Rare genetic variants impact muscle strength.

Muscle strength is highly heritable and predictive for multiple adverse health outcomes including mortality. Here, we present a rare protein-coding variant association study in 340,319 individuals for hand grip strength, a proxy measure of muscle strength. We show that the exome-wide burden of rare protein-truncating and damaging missense variants is associated with a reduction in hand grip strength. We identify six significant hand grip strength genes, KDM5B, OBSCN, GIGYF1, TTN, RB1CC1, and EIF3J. In the example of the titin (TTN) locus we demonstrate a convergence of rare with common variant association signals and uncover genetic relationships between reduced hand grip strength and disease. Finally, we identify shared mechanisms between brain and muscle function and uncover additive effects between rare and common genetic variation on muscle strength.

The impact of rare protein coding genetic variation on adult cognitive function.

Compelling evidence suggests that human cognitive function is strongly influenced by genetics. Here, we conduct a large-scale exome study to examine whether rare protein-coding variants impact cognitive function in the adult population (n = 485,930). We identify eight genes (ADGRB2, KDM5B, GIGYF1, ANKRD12, SLC8A1, RC3H2, CACNA1A and BCAS3) that are associated with adult cognitive function through rare coding variants with large effects. Rare genetic architecture for cognitive function partially overlaps with that of neurodevelopmental disorders. In the case of KDM5B we show how the genetic dosage of one of these genes may determine the variability of cognitive, behavioral and molecular traits in mice and humans. We further provide evidence that rare and common variants overlap in association signals and contribute additively to cognitive function. Our study introduces the relevance of rare coding variants for cognitive function and unveils high-impact monogenic contributions to how cognitive function is distributed in the normal adult population.

Brain expression quantitative trait locus and network analyses reveal downstream effects and putative drivers for brain-related diseases.

Identification of therapeutic targets from genome-wide association studies (GWAS) requires insights into downstream functional consequences. We harmonized 8,613 RNA-sequencing samples from 14 brain datasets to create the MetaBrain resource and performed cis- and trans-expression quantitative trait locus (eQTL) meta-analyses in multiple brain region- and ancestry-specific datasets (n ≤ 2,759). Many of the 16,169 cortex cis-eQTLs were tissue-dependent when compared with blood cis-eQTLs. We inferred brain cell types for 3,549 cis-eQTLs by interaction analysis. We prioritized 186 cis-eQTLs for 31 brain-related traits using Mendelian randomization and co-localization including 40 cis-eQTLs with an inferred cell type, such as a neuron-specific cis-eQTL (CYP24A1) for multiple sclerosis. We further describe 737 trans-eQTLs for 526 unique variants and 108 unique genes. We used brain-specific gene-co-regulation networks to link GWAS loci and prioritize additional genes for five central nervous system diseases. This study represents a valuable resource for post-GWAS research on central nervous system diseases.

Collective genomic segments with differential pleiotropic patterns between cognitive dimensions and psychopathology.

Cognitive deficits are known to be related to most forms of psychopathology. Here, we perform local genetic correlation analysis as a means of identifying independent segments of the genome that show biologically interpretable pleiotropic associations between cognitive dimensions and psychopathology. We identify collective segments of the genome, which we call "meta-loci", showing differential pleiotropic patterns for psychopathology relative to either cognitive task performance (CTP) or performance on a non-cognitive factor (NCF) derived from educational attainment. We observe that neurodevelopmental gene sets expressed during the prenatal-early childhood period predominate in CTP-relevant meta-loci, while post-natal gene sets are more involved in NCF-relevant meta-loci. Further, we demonstrate that neurodevelopmental gene sets are dissociable across CTP meta-loci with respect to their spatial distribution across the brain. Additionally, we find that GABA-ergic, cholinergic, and glutamatergic genes drive pleiotropic relationships within dissociable meta-loci.

Genetic map of regional sulcal morphology in the human brain from UK biobank data.

Genetic associations with macroscopic brain structure can provide insights into brain function and disease. However, specific associations with measures of local brain folding are largely under-explored. Here, we conducted large-scale genome- and exome-wide associations of regional cortical sulcal measures derived from magnetic resonance imaging scans of 40,169 individuals in UK Biobank. We discovered 388 regional brain folding associations across 77 genetic loci, with genes in associated loci enriched for expression in the cerebral cortex, neuronal development processes, and differential regulation during early brain development. We integrated brain eQTLs to refine genes for various loci, implicated several genes involved in neurodevelopmental disorders, and highlighted global genetic correlations with neuropsychiatric phenotypes. We provide an interactive 3D visualisation of our summary associations, emphasising added resolution of regional analyses. Our results offer new insights into the genetic architecture of brain folding and provide a resource for future studies of sulcal morphology in health and disease.

Recontacting biobank participants to collect lifestyle, behavioural and cognitive information via online questionnaires: lessons from a pilot study within FinnGen.

OBJECTIVES: To recontact biobank participants and collect cognitive, behavioural and lifestyle information via a secure online platform. DESIGN: Biobank-based recontacting pilot study. SETTING: Three Finnish biobanks (Helsinki, Auria, Tampere) recruiting participants from February 2021 to July 2021. PARTICIPANTS: All eligible invitees were enrolled in FinnGen by their biobanks (Helsinki, Auria, Tampere), had available genetic data and were >18 years old. Individuals with severe neuropsychiatric disease or cognitive or physical disabilities were excluded. Lastly, 5995 participants were selected based on their polygenic score for cognitive abilities and invited to the study. Among invitees, 1115 had successfully participated and completed the study questionnaire(s). OUTCOME MEASURES: The primary outcome was the participation rate among study invitees. Secondary outcomes included questionnaire completion rate, quality of data collected and comparison of participation rate boosting strategies. RESULTS: The overall participation rate was 18.6% among all invitees and 23.1% among individuals aged 18-69. A second reminder letter yielded an additional 9.7% participation rate in those who did not respond to the first invitation. Recontacting participants via an online healthcare portal yielded lower participation than recontacting via physical letter. The completion rate of the questionnaire and cognitive tests was high (92% and 85%, respectively), and measurements were overall reliable among participants. For example, the correlation (r) between self-reported body mass index and that collected by the biobanks was 0.92. CONCLUSION: In summary, this pilot suggests that recontacting FinnGen participants with the goal to collect a wide range of cognitive, behavioural and lifestyle information without additional engagement results in a low participation rate, but with reliable data. We suggest that such information be collected at enrolment, if possible, rather than via post hoc recontacting.

Genetic associations of protein-coding variants in human disease.

Genome-wide association studies (GWAS) have identified thousands of genetic variants linked to the risk of human disease. However, GWAS have so far remained largely underpowered in relation to identifying associations in the rare and low-frequency allelic spectrum and have lacked the resolution to trace causal mechanisms to underlying genes1. Here we combined whole-exome sequencing in 392,814 UK Biobank participants with imputed genotypes from 260,405 FinnGen participants (653,219 total individuals) to conduct association meta-analyses for 744 disease endpoints across the protein-coding allelic frequency spectrum, bridging the gap between common and rare variant studies. We identified 975 associations, with more than one-third being previously unreported. We demonstrate population-level relevance for mutations previously ascribed to causing single-gene disorders, map GWAS associations to likely causal genes, explain disease mechanisms, and systematically relate disease associations to levels of 117 biomarkers and clinical-stage drug targets. Combining sequencing and genotyping in two population biobanks enabled us to benefit from increased power to detect and explain disease associations, validate findings through replication and propose medical actionability for rare genetic variants. Our study provides a compendium of protein-coding variant associations for future insights into disease biology and drug discovery.

Systematic single-variant and gene-based association testing of thousands of phenotypes in 394,841 UK Biobank exomes.

Genome-wide association studies have successfully discovered thousands of common variants associated with human diseases and traits, but the landscape of rare variations in human disease has not been explored at scale. Exome-sequencing studies of population biobanks provide an opportunity to systematically evaluate the impact of rare coding variations across a wide range of phenotypes to discover genes and allelic series relevant to human health and disease. Here, we present results from systematic association analyses of 4,529 phenotypes using single-variant and gene tests of 394,841 individuals in the UK Biobank with exome-sequence data. We find that the discovery of genetic associations is tightly linked to frequency and is correlated with metrics of deleteriousness and natural selection. We highlight biological findings elucidated by these data and release the dataset as a public resource alongside the Genebass browser for rapidly exploring rare-variant association results.

The burden of rare protein-truncating genetic variants on human lifespan.

Genetic predisposition has been shown to contribute substantially to the age at which we die. Genome-wide association studies (GWASs) have linked more than 20 loci to phenotypes related to human lifespan1. However, little is known about how lifespan is impacted by gene loss of function. Through whole-exome sequencing of 352,338 UK Biobank participants of European ancestry, we assessed the relevance of protein-truncating variant (PTV) gene burden on individual and parental survival. We identified four exome-wide significant (P < 4.2 × 10-7) human lifespan genes, BRCA1, BRCA2, ATM and TET2. Gene and gene-set, PTV-burden, phenome-wide association studies support known roles of these genes in cancer to impact lifespan at the population level. The TET2 PTV burden was associated with a lifespan through somatic mutation events presumably due to clonal hematopoiesis. The overlap between PTV burden and common variant-based lifespan GWASs was modest, underscoring the value of exome sequencing in well-powered biobank cohorts to complement GWASs for identifying genes underlying complex traits.

Immune system-wide Mendelian randomization and triangulation analyses support autoimmunity as a modifiable component in dementia-causing diseases.

Immune system and blood-brain barrier dysfunction are implicated in the development of Alzheimer's and other dementia-causing diseases, but their causal role remains unknown. We performed Mendelian randomization for 1,827 immune system- and blood-brain barrier-related biomarkers and identified 127 potential causal risk factors for dementia-causing diseases. Pathway analyses linked these biomarkers to amyloid-ß, tau and α-synuclein pathways and to autoimmunity-related processes. A phenome-wide analysis using Mendelian randomization-based polygenic risk score in the FinnGen study (n = 339,233) for the biomarkers indicated shared genetic background for dementias and autoimmune diseases. This association was further supported by human leukocyte antigen analyses. In inverse-probability-weighted analyses that simulate randomized controlled drug trials in observational data, anti-inflammatory methotrexate treatment reduced the incidence of Alzheimer's disease in high-risk individuals (hazard ratio compared with no treatment, 0.64, 95% confidence interval 0.49-0.88, P = 0.005). These converging results from different lines of human research suggest that autoimmunity is a modifiable component in dementia-causing diseases.

Pairwise effects between lipid GWAS genes modulate lipid plasma levels and cellular uptake.

Complex traits are characterized by multiple genes and variants acting simultaneously on a phenotype. However, studying the contribution of individual pairs of genes to complex traits has been challenging since human genetics necessitates very large population sizes, while findings from model systems do not always translate to humans. Here, we combine genetics with combinatorial RNAi (coRNAi) to systematically test for pairwise additive effects (AEs) and genetic interactions (GIs) between 30 lipid genome-wide association studies (GWAS) genes. Gene-based burden tests from 240,970 exomes show that in carriers with truncating mutations in both, APOB and either PCSK9 or LPL ("human double knock-outs") plasma lipid levels change additively. Genetics and coRNAi identify overlapping AEs for 12 additional gene pairs. Overlapping GIs are observed for TOMM40/APOE with SORT1 and NCAN. Our study identifies distinct gene pairs that modulate plasma and cellular lipid levels primarily via AEs and nominates putative drug target pairs for improved lipid-lowering combination therapies.

Pan-ancestry exome-wide association analyses of COVID-19 outcomes in 586,157 individuals.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a respiratory illness that can result in hospitalization or death. We used exome sequence data to investigate associations between rare genetic variants and seven COVID-19 outcomes in 586,157 individuals, including 20,952 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome wide or when specifically focusing on (1) 13 interferon pathway genes in which rare deleterious variants have been reported in individuals with severe COVID-19, (2) 281 genes located in susceptibility loci identified by the COVID-19 Host Genetics Initiative, or (3) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, and results are publicly available through the Regeneron Genetics Center COVID-19 Results Browser.

Advancing human genetics research and drug discovery through exome sequencing of the UK Biobank.

The UK Biobank Exome Sequencing Consortium (UKB-ESC) is a private-public partnership between the UK Biobank (UKB) and eight biopharmaceutical companies that will complete the sequencing of exomes for all ~500,000 UKB participants. Here, we describe the early results from ~200,000 UKB participants and the features of this project that enabled its success. The biopharmaceutical industry has increasingly used human genetics to improve success in drug discovery. Recognizing the need for large-scale human genetics data, as well as the unique value of the data access and contribution terms of the UKB, the UKB-ESC was formed. As a result, exome data from 200,643 UKB enrollees are now available. These data include ~10 million exonic variants-a rich resource of rare coding variation that is particularly valuable for drug discovery. The UKB-ESC precompetitive collaboration has further strengthened academic and industry ties and has provided teams with an opportunity to interact with and learn from the wider research community.