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.Peer reviewe

Genetic architecture of human plasma lipidome and its link to cardiovascular disease

Understanding genetic architecture of plasma lipidome could provide better insights into lipid metabolism and its link to cardiovascular diseases (CVDs). Here, we perform genome-wide association analyses of 141 lipid species (n = 2,181 individuals), followed by phenome-wide scans with 25 CVD related phenotypes (n = 511,700 individuals). We identify 35 lipid-species-associated loci (P Peer reviewe

Mendelian randomization highlights insomnia as a risk factor for pain diagnoses

Study Objective: Insomnia has been linked to acute and chronic pain conditions; however, it is unclear whether such relationships are causal. Recently, a large number of genetic variants have been discovered for both insomnia and pain through genome-wide association studies (GWASs) providing a unique opportunity to examine the evidence for causal relationships through the use of the Mendelian randomization paradigm. Methods: To elucidate the causality between insomnia and pain, we performed bidirectional Mendelian randomization analysis in FinnGen, where clinically diagnosed ICD-10 categories of pain had been evaluated. In addition, we used measures of self-reported insomnia symptoms. We used endpoints for pain in the FinnGen Release 5 (R5) (N = 218,379), and a non-overlapping sample for insomnia (UK Biobank (UKBB) and 23andMe, N = 1,331,010 or UKBB alone N = 453,379). We assessed the robustness of results through conventional Mendelian randomization sensitivity analyses. Results: Genetic liability to insomnia symptoms increased the odds of reporting pain (odds ratio (OR) [95% confidence interval (CI)] = 1.47 [1.38-1.58], p = 4.12 x 10(-28)). Manifested pain had a small effect on increased risk for insomnia (OR [95% CI] = 1.04 [1.01-1.07], p < 0.05). Results were consistent in sensitivity analyses. Conclusions: Our findings support a bidirectional causal relationship between insomnia and pain. These data support a further clinical investigation into the utility of insomnia treatment as a strategy for pain management and vice versa.Peer reviewe

Genetic variation in cervical preinvasive and invasive disease : a genome-wide association study

Background Most uterine cervical high-risk human papillomavirus (HPV) infections are transient, with only a small fraction developing into cervical cancer. Family aggregation studies and heritability estimates suggest a significant inherited genetic component. Candidate gene studies and previous genome-wide association studies (GWASs) report associations between the HLA region and cervical cancer. Adopting a genome-wide approach, we aimed to compare genetic variation in women with invasive cervical cancer and cervical intraepithelial neoplasia (CIN) grade 3 with that in healthy controls. Methods We did a GWAS in a cohort of unrelated European individuals using data from UK Biobank, a population-based cohort including 273 377 women aged 40-69 years at recruitment between March 13, 2006, and Oct 1, 2010. We used an additive univariate logistic regression model to analyse genetic variants associated with invasive cervical cancer or CIN3. We sought replication of candidate associations in FinnGen, a large independent dataset of 128 123 individuals. We also did a two-sample mendelian randomisation approach to explore the role of risk factors in the genetic risk of cervical cancer. Findings We included 4769 CIN3 and invasive cervical cancer case samples and 145 545 control samples in the GWAS. Of 9 600 464 assayed and imputed single-nucleotide polymorphisms (SNPs), six independent variants were associated with CIN3 and invasive cervical cancer. These included novel loci rs10175462 (PAX8; odds ratio [OR] 0.87, 95% CI 0.84-0.91; p=1.07 x 10(-9)) and rs27069 (CLPTM1L; 0.88, 0.84-0.92; p=2.51 x 10(-9)), and previously reported signals at rs9272050 (HLA-DQA1; 1.27, 1.21-1.32; p=2.51 x 10(-28)), rs6938453 (MICA; 0.79, 0.75-0 .83; p=1.97 x 10-(17)), rs55986091 (HLA-DQB1; 0.66, 0 .60-0.72; p=6.42 x 10-(22)), and rs9266183 (HLA-B; 0.73, 0.64-0.83; p=1.53 x 10(-6)). Three SNPs were replicated in the independent Finnish dataset of 1648 invasive cervical cancer cases: PAX8 (rs10175462; p=0.015), CLPTM1L (rs27069; p=2.54 x 10(-7)), and HLA-DQA1 (rs9272050; p=7.90 x 10(-8)). Mendelian randomisation further supported the complementary role of smoking (OR 2.46, 95% CI 1.64-3.69), older age at first pregnancy (0.80, 0.68-0.95), and number of sexual partners (1.95, 1.44-2.63) in the risk of developing cervical cancer. Interpretation Our results provide new evidence for the genetic susceptibility to cervical cancer, specifically the PAX8, CLPTM1L, and HLA genes, suggesting disruption in apoptotic and immune function pathways. Future studies integrating host and viral, genetic, and epigenetic variation, could further elucidate complex host-viral interactions. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

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

Publisher Copyright: © 2022, The Author(s).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-β, 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.Peer reviewe

Genome-wide association studies of metabolites in Finnish men identify disease-relevant loci

The Finnish population is enriched for genetic variants which are rare in other populations. Here, the authors find new genetic loci associated with 1391 circulating metabolites in 6136 Finnish men, demonstrating that metabolite genetic associations can help elucidate disease mechanisms. Few studies have explored the impact of rare variants (minor allele frequency < 1%) on highly heritable plasma metabolites identified in metabolomic screens. The Finnish population provides an ideal opportunity for such explorations, given the multiple bottlenecks and expansions that have shaped its history, and the enrichment for many otherwise rare alleles that has resulted. Here, we report genetic associations for 1391 plasma metabolites in 6136 men from the late-settlement region of Finland. We identify 303 novel association signals, more than one third at variants rare or enriched in Finns. Many of these signals identify genes not previously implicated in metabolite genome-wide association studies and suggest mechanisms for diseases and disease-related traits.Peer reviewe

Integration of questionnaire-based risk factors improves polygenic risk scores for human coronary heart disease and type 2 diabetes

Max Tamlander et al. combine polygenic risk scores and clinical assessments to improve prediction of coronary artery disease and type 2 diabetes in European cohorts. Taken together, their results provide a useful method for preliminary cardiometabolic risk assessment in patients. Large-scale biobank initiatives and commercial repositories store genomic data collected from millions of individuals, and tools to leverage the rapidly growing pool of health and genomic data in disease prevention are needed. Here, we describe the derivation and validation of genomics-enhanced risk tools for two common cardiometabolic diseases, coronary heart disease and type 2 diabetes. Data used for our analyses include the FinnGen study (N = 309,154) and the UK Biobank project (N = 343,672). The risk tools integrate contemporary genome-wide polygenic risk scores with simple questionnaire-based risk factors, including demographic, lifestyle, medication, and comorbidity data, enabling risk calculation across resources where genome data is available. Compared to routinely used clinical risk scores for coronary heart disease and type 2 diabetes prevention, the risk tools show at least equivalent risk discrimination, improved risk reclassification (overall net reclassification improvements ranging from 3.7 [95% CI 2.8-4.6] up to 6.2 [4.6-7.8]), and capacity to be improved even further with standard lipid and blood pressure measurements. Without the need for blood tests or evaluation by a health professional, the risk tools provide a powerful yet simple method for preliminary cardiometabolic risk assessment for individuals with genome data available.Peer reviewe

Genome-wide association study meta-analysis of suicide death and suicidal behavior

Suicide is a worldwide health crisis. We aimed to identify genetic risk variants associated with suicide death and suicidal behavior. Meta-analysis for suicide death was performed using 3765 cases from Utah and matching 6572 controls of European ancestry. Meta-analysis for suicidal behavior using data across five cohorts (n = 8315 cases and 256,478 psychiatric or populational controls of European ancestry) was also performed. One locus in neuroligin 1 (NLGN1) passing the genome-wide significance threshold for suicide death was identified (top SNP rs73182688, with p = 5.48 x 10(-8) before and p = 4.55 x 10(-8) after mtCOJO analysis conditioning on MDD to remove genetic effects on suicide mediated by MDD). Conditioning on suicidal attempts did not significantly change the association strength (p = 6.02 x 10(-8)), suggesting suicide death specificity. NLGN1 encodes a member of a family of neuronal cell surface proteins. Members of this family act as splice site-specific ligands for beta-neurexins and may be involved in synaptogenesis. The NRXN-NLGN pathway was previously implicated in suicide, autism, and schizophrenia. We additionally identified ROBO2 and ZNF28 associations with suicidal behavior in the meta-analysis across five cohorts in gene-based association analysis using MAGMA. Lastly, we replicated two loci including variants near SOX5 and LOC101928519 associated with suicidal attempts identified in the ISGC and MVP meta-analysis using the independent FinnGen samples. Suicide death and suicidal behavior showed positive genetic correlations with depression, schizophrenia, pain, and suicidal attempt, and negative genetic correlation with educational attainment. These correlations remained significant after conditioning on depression, suggesting pleiotropic effects among these traits. Bidirectional generalized summary-data-based Mendelian randomization analysis suggests that genetic risk for the suicidal attempt and suicide death are both bi-directionally causal for MDD.Peer reviewe

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 genes(1). 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. A meta-analysis combining whole-exome sequencing data from UK Biobank participants and imputed genotypes from FinnGen participants enables identification of genetic associations with human disease in the rare and low-frequency allelic spectrumPeer reviewe

Genetic analyses identify widespread sex-differential participation bias

Genetic analyses identify widespread sex-differential participation bias in population-based studies and show how this bias can lead to incorrect inferences. These findings highlight new challenges for association studies as sample sizes continue to grow. Genetic association results are often interpreted with the assumption that study participation does not affect downstream analyses. Understanding the genetic basis of participation bias is challenging since it requires the genotypes of unseen individuals. Here we demonstrate that it is possible to estimate comparative biases by performing a genome-wide association study contrasting one subgroup versus another. For example, we showed that sex exhibits artifactual autosomal heritability in the presence of sex-differential participation bias. By performing a genome-wide association study of sex in approximately 3.3 million males and females, we identified over 158 autosomal loci spuriously associated with sex and highlighted complex traits underpinning differences in study participation between the sexes. For example, the body mass index-increasing allele at FTO was observed at higher frequency in males compared to females (odds ratio = 1.02, P = 4.4 x 10(-)(36)). Finally, we demonstrated how these biases can potentially lead to incorrect inferences in downstream analyses and propose a conceptual framework for addressing such biases. Our findings highlight a new challenge that genetic studies may face as sample sizes continue to grow.Peer reviewe