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Chikowore T, Läll K, Micklesfield LK, Lombard Z, Goedecke JH, Fatumo S, Norris SA, Magi R, Ramsay M, Franks PW, Pare G, Morris AP. Variability of polygenic prediction for body mass index in Africa. Genome Med 2024; 16:74. [PMID: 38816834 PMCID: PMC11140909 DOI: 10.1186/s13073-024-01348-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Accepted: 05/21/2024] [Indexed: 06/01/2024] Open
Abstract
BACKGROUND Polygenic prediction studies in continental Africans are scarce. Africa's genetic and environmental diversity pose a challenge that limits the generalizability of polygenic risk scores (PRS) for body mass index (BMI) within the continent. Studies to understand the factors that affect PRS variability within Africa are required. METHODS Using the first multi-ancestry genome-wide association study (GWAS) meta-analysis for BMI involving continental Africans, we derived a multi-ancestry PRS and compared its performance to a European ancestry-specific PRS in continental Africans (AWI-Gen study) and a European cohort (Estonian Biobank). We then evaluated the factors affecting the performance of the PRS in Africans which included fine-mapping resolution, allele frequencies, linkage disequilibrium patterns, and PRS-environment interactions. RESULTS Polygenic prediction of BMI in continental Africans is poor compared to that in European ancestry individuals. However, we show that the multi-ancestry PRS is more predictive than the European ancestry-specific PRS due to its improved fine-mapping resolution. We noted regional variation in polygenic prediction across Africa's East, South, and West regions, which was driven by a complex interplay of the PRS with environmental factors, such as physical activity, smoking, alcohol intake, and socioeconomic status. CONCLUSIONS Our findings highlight the role of gene-environment interactions in PRS prediction variability in Africa. PRS methods that correct for these interactions, coupled with the increased representation of Africans in GWAS, may improve PRS prediction in Africa.
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Affiliation(s)
- Tinashe Chikowore
- SAMRC/Wits Developmental Pathways for Health Research Unit, Department of Pediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
- Harvard Medical School, Boston, MA, USA.
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA.
| | - Kristi Läll
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Lisa K Micklesfield
- SAMRC/Wits Developmental Pathways for Health Research Unit, Department of Pediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Zane Lombard
- Division of Human Genetics, National Health Laboratory Service, and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Julia H Goedecke
- SAMRC/Wits Developmental Pathways for Health Research Unit, Department of Pediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Biomedical Research and Innovation Platform, South African Medical Research Council, Cape Town, South Africa
| | - Segun Fatumo
- NCD Genomics, MRC/UVRI LSHTM Uganda Research Unit, Entebbe, Uganda
- Precision Healthcare University Research Institute (PHURI), Queen Mary University of London, London, UK
| | - Shane A Norris
- SAMRC/Wits Developmental Pathways for Health Research Unit, Department of Pediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Human Development and Health, University of Southampton, Southampton, UK
| | - Reedik Magi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Michele Ramsay
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Paul W Franks
- Department of Clinical Sciences, Lund University, Helsingborg, Sweden
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Guillaume Pare
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, University of Manchester, Manchester, UK.
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Kurgan N, Kjærgaard Larsen J, Deshmukh AS. Harnessing the power of proteomics in precision diabetes medicine. Diabetologia 2024; 67:783-797. [PMID: 38345659 DOI: 10.1007/s00125-024-06097-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 12/20/2023] [Indexed: 03/21/2024]
Abstract
Precision diabetes medicine (PDM) aims to reduce errors in prevention programmes, diagnosis thresholds, prognosis prediction and treatment strategies. However, its advancement and implementation are difficult due to the heterogeneity of complex molecular processes and environmental exposures that influence an individual's disease trajectory. To address this challenge, it is imperative to develop robust screening methods for all areas of PDM. Innovative proteomic technologies, alongside genomics, have proven effective in precision cancer medicine and are showing promise in diabetes research for potential translation. This narrative review highlights how proteomics is well-positioned to help improve PDM. Specifically, a critical assessment of widely adopted affinity-based proteomic technologies in large-scale clinical studies and evidence of the benefits and feasibility of using MS-based plasma proteomics is presented. We also present a case for the use of proteomics to identify predictive protein panels for type 2 diabetes subtyping and the development of clinical prediction models for prevention, diagnosis, prognosis and treatment strategies. Lastly, we discuss the importance of plasma and tissue proteomics and its integration with genomics (proteogenomics) for identifying unique type 2 diabetes intra- and inter-subtype aetiology. We conclude with a call for action formed on advancing proteomics technologies, benchmarking their performance and standardisation across sites, with an emphasis on data sharing and the inclusion of diverse ancestries in large cohort studies. These efforts should foster collaboration with key stakeholders and align with ongoing academic programmes such as the Precision Medicine in Diabetes Initiative consortium.
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Affiliation(s)
- Nigel Kurgan
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Jeppe Kjærgaard Larsen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Atul S Deshmukh
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark.
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3
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Li Y, Yang AY, Marelli A, Li Y. MixEHR-SurG: A joint proportional hazard and guided topic model for inferring mortality-associated topics from electronic health records. J Biomed Inform 2024; 153:104638. [PMID: 38631461 DOI: 10.1016/j.jbi.2024.104638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 03/07/2024] [Accepted: 04/03/2024] [Indexed: 04/19/2024]
Abstract
Survival models can help medical practitioners to evaluate the prognostic importance of clinical variables to patient outcomes such as mortality or hospital readmission and subsequently design personalized treatment regimes. Electronic Health Records (EHRs) hold the promise for large-scale survival analysis based on systematically recorded clinical features for each patient. However, existing survival models either do not scale to high dimensional and multi-modal EHR data or are difficult to interpret. In this study, we present a supervised topic model called MixEHR-SurG to simultaneously integrate heterogeneous EHR data and model survival hazard. Our contributions are three-folds: (1) integrating EHR topic inference with Cox proportional hazards likelihood; (2) integrating patient-specific topic hyperparameters using the PheCode concepts such that each topic can be identified with exactly one PheCode-associated phenotype; (3) multi-modal survival topic inference. This leads to a highly interpretable survival topic model that can infer PheCode-specific phenotype topics associated with patient mortality. We evaluated MixEHR-SurG using a simulated dataset and two real-world EHR datasets: the Quebec Congenital Heart Disease (CHD) data consisting of 8211 subjects with 75,187 outpatient claim records of 1767 unique ICD codes; the MIMIC-III consisting of 1458 subjects with multi-modal EHR records. Compared to the baselines, MixEHR-SurG achieved a superior dynamic AUROC for mortality prediction, with a mean AUROC score of 0.89 in the simulation dataset and a mean AUROC of 0.645 on the CHD dataset. Qualitatively, MixEHR-SurG associates severe cardiac conditions with high mortality risk among the CHD patients after the first heart failure hospitalization and critical brain injuries with increased mortality among the MIMIC-III patients after their ICU discharge. Together, the integration of the Cox proportional hazards model and EHR topic inference in MixEHR-SurG not only leads to competitive mortality prediction but also meaningful phenotype topics for in-depth survival analysis. The software is available at GitHub: https://github.com/li-lab-mcgill/MixEHR-SurG.
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Affiliation(s)
- Yixuan Li
- Department of Mathematics and Statistics, McGill University, Montreal, Canada; Mila - Quebec AI institute, Montreal, Canada
| | - Archer Y Yang
- Department of Mathematics and Statistics, McGill University, Montreal, Canada; Mila - Quebec AI institute, Montreal, Canada; School of Computer Science, McGill University, Montreal, Canada.
| | - Ariane Marelli
- McGill Adult Unit for Congenital Heart Disease (MAUDE Unit), McGill University of Health Centre, Montreal, Canada.
| | - Yue Li
- Mila - Quebec AI institute, Montreal, Canada; School of Computer Science, McGill University, Montreal, Canada.
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4
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Hughes DA, Li-Gao R, Bull CJ, de Mutsert R, Rosendaal FR, Mook-Kanamori DO, Willems van Dijk K, Timpson NJ. The association between body mass index and metabolite response to a liquid mixed meal challenge: a Mendelian randomization study. Am J Clin Nutr 2024; 119:1354-1370. [PMID: 38494119 PMCID: PMC11130664 DOI: 10.1016/j.ajcnut.2024.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 01/30/2024] [Accepted: 03/12/2024] [Indexed: 03/19/2024] Open
Abstract
BACKGROUND Metabolite abundance is a dynamic trait that varies in response to environmental stimuli and phenotypic traits, such as food consumption and body mass index (BMI, kg/m2). OBJECTIVES In this study, we used the Netherlands Epidemiology of Obesity (NEO) study data to identify observational and causal associations between BMI and metabolite response to a liquid meal. METHODS A liquid meal challenge was performed, and Nightingale Health metabolite profiles were collected in 5744 NEO participants. Observational and one-sample Mendelian randomization (MR) analysis were conducted to estimate the effect of BMI on metabolites (n = 229) in the fasting, postprandial, and response (or change in abundance) states. RESULTS We observed 473 associations with BMI (175 fasting, 188 postprandial, and 110 response) in observational analyses. In MR analyses, we observed 20 metabolite traits (5 fasting, 12 postprandial, and 3 response) to be associated with BMI. MR associations included the glucogenic amino acid alanine, which was inversely associated with BMI in the response state (β: -0.081; SE: 0.023; P = 5.91 × 10-4), suggesting that as alanine increased in postprandial abundance, that increase was attenuated with increasing BMI. CONCLUSIONS Overall, this study showed that MR estimates were strongly correlated with observational effect estimates, suggesting that the broad associations seen between BMI and metabolite variation has a causal underpinning. Specific effects in previously unassessed postprandial and response states are detected, and these may likely mark novel life course risk exposures driven by regular nutrition.
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Affiliation(s)
- David A Hughes
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Caroline J Bull
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands; Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands; Division of Endocrinology, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
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Constantinides C, Baltramonaityte V, Caramaschi D, Han LKM, Lancaster TM, Zammit S, Freeman TP, Walton E. Assessing the association between global structural brain age and polygenic risk for schizophrenia in early adulthood: A recall-by-genotype study. Cortex 2024; 172:1-13. [PMID: 38154374 DOI: 10.1016/j.cortex.2023.11.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 09/22/2023] [Accepted: 11/23/2023] [Indexed: 12/30/2023]
Abstract
Neuroimaging studies consistently show advanced brain age in schizophrenia, suggesting that brain structure is often 'older' than expected at a given chronological age. Whether advanced brain age is linked to genetic liability for schizophrenia remains unclear. In this pre-registered secondary data analysis, we utilised a recall-by-genotype approach applied to a population-based subsample from the Avon Longitudinal Study of Parents and Children to assess brain age differences between young adults aged 21-24 years with relatively high (n = 96) and low (n = 93) polygenic risk for schizophrenia (SCZ-PRS). A global index of brain age (or brain-predicted age) was estimated using a publicly available machine learning model previously trained on a combination of region-wise gray-matter measures, including cortical thickness, surface area and subcortical volumes derived from T1-weighted magnetic resonance imaging (MRI) scans. We found no difference in mean brain-PAD (the difference between brain-predicted age and chronological age) between the high- and low-SCZ-PRS groups, controlling for the effects of sex and age at time of scanning (b = -.21; 95% CI -2.00, 1.58; p = .82; Cohen's d = -.034; partial R2 = .00029). These findings do not support an association between SCZ-PRS and brain-PAD based on global age-related structural brain patterns, suggesting that brain age may not be a vulnerability marker of common genetic risk for SCZ. Future studies with larger samples and multimodal brain age measures could further investigate global or localised effects of SCZ-PRS.
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Affiliation(s)
| | | | - Doretta Caramaschi
- Department of Psychology, Faculty of Health and Life Sciences, University of Exeter, UK
| | - Laura K M Han
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia; Orygen, Parkville, Australia
| | | | - Stanley Zammit
- Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK; Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tom P Freeman
- Addiction and Mental Health Group (AIM), Department of Psychology, University of Bath, UK
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Lancaster T, Creese B, Escott-Price V, Driver I, Menzies G, Khan Z, Corbett A, Ballard C, Williams J, Murphy K, Chandler H. Proof-of-concept recall-by-genotype study of extremely low and high Alzheimer's polygenic risk reveals autobiographical deficits and cingulate cortex correlates. Alzheimers Res Ther 2023; 15:213. [PMID: 38087383 PMCID: PMC10714651 DOI: 10.1186/s13195-023-01362-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 11/29/2023] [Indexed: 12/18/2023]
Abstract
BACKGROUND Genome-wide association studies demonstrate that Alzheimer's disease (AD) has a highly polygenic architecture, where thousands of independent genetic variants explain risk with high classification accuracy. This AD polygenic risk score (AD-PRS) has been previously linked to preclinical cognitive and neuroimaging features observed in asymptomatic individuals. However, shared variance between AD-PRS and neurocognitive features are small, suggesting limited preclinical utility. METHODS Here, we recruited sixteen clinically asymptomatic individuals (mean age 67; range 58-76) with either extremely low / high AD-PRS (defined as at least 2 standard deviations from the wider sample mean (N = 4504; N EFFECTIVE = 90)) with comparable age sex and education level. We assessed group differences in autobiographical memory and T1-weighted structural neuroimaging features. RESULTS We observed marked reductions in autobiographical recollection (Cohen's d = - 1.66; P FDR = 0.014) and midline structure (cingulate) thickness (Cohen's d = - 1.55, P FDR = 0.05), with no difference in hippocampal volume (P > 0.3). We further confirm the negative association between AD-PRS and cingulate thickness in a larger study with a comparable age (N = 31,966, β = - 0.002, P = 0.011), supporting the validity of our approach. CONCLUSIONS These observations conform with multiple streams of prior evidence suggesting alterations in cingulate structures may occur in individuals with higher AD genetic risk. We were able to use a genetically informed research design strategy that significantly improved the efficiency and power of the study. Thus, we further demonstrate that the recall-by-genotype of AD-PRS from wider samples is a promising approach for the detection, assessment, and intervention in specific individuals with increased AD genetic risk.
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Affiliation(s)
- Thomas Lancaster
- Department of Psychology, University of Bath, Bath, UK.
- School of Physics and Astronomy, Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK.
- Dementia Research Institute (UKDRI), Cardiff University, Cardiff, UK.
| | - Byron Creese
- Department of Clinical and Biomedical Science, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
- Department of Life Sciences, Brunel University London, Uxbridge, west London, UK
| | - Valentina Escott-Price
- Division of Neuroscience and Mental Health, School of Medicine, Cardiff University, Cardiff, UK
| | - Ian Driver
- School of Physics and Astronomy, Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK
| | - Georgina Menzies
- Dementia Research Institute (UKDRI), Cardiff University, Cardiff, UK
- School of Biosciences, Cardiff University, Cardiff, UK
| | - Zunera Khan
- Institute of Psychiatry, King's College London, Psychology & Neuroscience, London, UK
| | - Anne Corbett
- Deptartment of Health & Community Sciences, University of Exeter, Exeter, UK
| | - Clive Ballard
- Department of Clinical and Biomedical Science, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Julie Williams
- Dementia Research Institute (UKDRI), Cardiff University, Cardiff, UK
| | - Kevin Murphy
- School of Physics and Astronomy, Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK
| | - Hannah Chandler
- School of Physics and Astronomy, Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK
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7
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Biasiotto R, Kösters M, Tschigg K, Pramstaller PP, Brüggemann N, Borsche M, Klein C, Hicks AA, Mascalzoni D. Participant perspective on the recall-by-genotype research approach: a mixed-method embedded study with participants of the CHRIS study. Eur J Hum Genet 2023; 31:1218-1227. [PMID: 36599941 PMCID: PMC10620385 DOI: 10.1038/s41431-022-01277-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 10/27/2022] [Accepted: 12/15/2022] [Indexed: 01/06/2023] Open
Abstract
Recall-by-genotype (RbG) research recruits participants previously involved in genetic research based on their genotype. RbG enables the further study of a particular variant of interest, but in recalling participants, it risks disclosing potentially unwanted or distressing genetic information. Any RbG strategy must therefore be done in a manner that addresses the potential ethical and social issues. As part of an RbG pilot on the penetrance of Parkinson's disease variants, we conducted an empirical mixed-method study with 51 participants of the Cooperative Health Research in South Tyrol (CHRIS) study to understand participant views on RbG research approach. Participants were disclosed the disease under investigation but not the individual variant carrier status. Results showed that participants filtered the information received through personal experience and enacted mechanisms to address the concerns raised by invitation by resorting to personal resources and the support provided by experts. While the non-disclosure of the Parkin variant carrier status was deemed acceptable, disclosing the disease under study was important for participants. Participant preferences for disclosure of the disease under investigation and the carrier status varied according to how the knowledge of individual carrier status was perceived to impact the participant's life. This study provided insights into participant response to the RbG research approach, which are relevant for RbG policy development. A suitable communication strategy and granular options addressing preferences for invitation in the original informed consent are critical for an ethically informed RbG policy.
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Affiliation(s)
- Roberta Biasiotto
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy.
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy.
| | - Maria Kösters
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy
| | - Katharina Tschigg
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy
- Department of Cellular, Computational, and Integrative Biology, University of Trento, Trento, Italy
| | - Peter P Pramstaller
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy
| | - Norbert Brüggemann
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Max Borsche
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Christine Klein
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
| | - Andrew A Hicks
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy
| | - Deborah Mascalzoni
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy
- Centre for Research Ethics and Bioethics, Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
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Julkunen V, Schwarz C, Kalapudas J, Hallikainen M, Piironen AK, Mannermaa A, Kujala H, Laitinen T, Kosma VM, Paajanen TI, Kälviäinen R, Hiltunen M, Herukka SK, Kärkkäinen S, Kokkola T, Urjansson M, Perola M, Palotie A, Vuoksimaa E, Runz H. A FinnGen pilot clinical recall study for Alzheimer's disease. Sci Rep 2023; 13:12641. [PMID: 37537264 PMCID: PMC10400697 DOI: 10.1038/s41598-023-39835-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 07/31/2023] [Indexed: 08/05/2023] Open
Abstract
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.
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Affiliation(s)
- Valtteri Julkunen
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland.
- Department of Neurology, Neurocenter, Kuopio University Hospital, Kuopio, Finland.
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
| | - Claudia Schwarz
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Juho Kalapudas
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland
| | - Merja Hallikainen
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland
| | | | | | | | | | | | - Teemu I Paajanen
- Work Ability and Working Careers, Finnish Institute of Occupational Health, Helsinki, Finland
| | - Reetta Kälviäinen
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland
| | - Mikko Hiltunen
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland
| | - Sanna-Kaisa Herukka
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland
| | - Sari Kärkkäinen
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland
| | - Tarja Kokkola
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland
| | - Mia Urjansson
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Markus Perola
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Department of Neurology and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- The Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
| | - Heiko Runz
- Translational Sciences, Biogen, Cambridge, MA, USA.
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Nádasdi Á, Gál V, Masszi T, Somogyi A, Firneisz G. PNPLA3 rs738409 risk genotype decouples TyG index from HOMA2-IR and intrahepatic lipid content. Cardiovasc Diabetol 2023; 22:64. [PMID: 36944955 PMCID: PMC10031960 DOI: 10.1186/s12933-023-01792-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 03/06/2023] [Indexed: 03/23/2023] Open
Abstract
BACKGROUND Recent reports suggested a different predictive value for TyG index compared to HOMA-IR in coronary artery calcification (CAC) and other atherosclerotic outcomes, despite that both indices are proposed as surrogate markers of insulin resistance. We hypothesized a key role for liver pathology as an explanation and therefore assessed the relationship among the two indices and the intrahepatic lipid content stratified by PNPLA3 rs738409 genotypes as a known non-alcoholic fatty liver disease (NAFLD) genetic risk. METHODS Thirty-nine women from a prior GDM-genetic study were recalled with PNPLA3 rs738409 CC and GG genotypes for metabolic phenotyping and to assess hepatic triglyceride content (HTGC). 75 g OGTT was performed, fasting lipid, glucose, insulin levels and calculated insulin resistance indices (TyG and HOMA2-IR) were used. HTGC was measured by MR based methods. Mann-Whitney-U, χ2 and for the correlation analysis Spearman rank order tests were applied. RESULTS The PNPLA3 rs738409 genotype had a significant effect on the direct correlation between the HOMA2-IR and TyG index: the correlation (R = 0.52, p = 0.0054) found in the CC group was completely abolished in those with the GG (NAFLD) risk genotype. In addition, the HOMA2-IR correlated with HTGC in the entire study population (R = 0.69, p < 0.0001) and also separately in both genotypes (CC R = 0.62, p = 0.0006, GG: R = 0.74, p = 0.0058). In contrast, the correlation between TyG index and HTGC was only significant in rs738409 CC genotype group (R = 0.42, p = 0.0284) but not in GG group. A similar pattern was observed in the correlation between TG and HTGC (CC: R = 0.41, p = 0.0335), when the components of the TyG index were separately assessed. CONCLUSIONS PNPLA3 rs738409 risk genotype completely decoupled the direct correlation between two surrogate markers of insulin resistance: TyG and HOMA2-IR confirming our hypothesis. The liver lipid content increased in parallel with the HOMA2-IR independent of genotype, in contrast to the TyG index where the risk genotype abolished the correlation. This phenomenon seems to be related to the nature of hepatic fat accumulation and to the different concepts establishing the two insulin resistance markers.
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Affiliation(s)
- Ákos Nádasdi
- Translational Medicine Institute, Faculty of Medicine, Semmelweis University, Budapest, Hungary
- Department of Internal Medicine and Haematology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Viktor Gál
- Brain Imaging Centre, Research Centre for Natural Sciences, Eötvös Loránd Research Network, Budapest, Hungary
- Medical Imaging Centre, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Tamás Masszi
- Department of Internal Medicine and Haematology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Anikó Somogyi
- Department of Internal Medicine and Haematology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Gábor Firneisz
- Translational Medicine Institute, Faculty of Medicine, Semmelweis University, Budapest, Hungary.
- Department of Internal Medicine and Haematology, Faculty of Medicine, Semmelweis University, Budapest, Hungary.
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10
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Braun A, Kraft J, Ripke S. Study protocol of the Berlin Research Initiative for Diagnostics, Genetics and Environmental Factors in Schizophrenia (BRIDGE-S). BMC Psychiatry 2023; 23:31. [PMID: 36635663 PMCID: PMC9835268 DOI: 10.1186/s12888-022-04447-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 12/05/2022] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND Large-scale collaborative efforts in the field of psychiatric genetics have made substantial progress in unraveling the biological architecture of schizophrenia (SCZ). Although both genetic and environmental factors are known to play a role in schizophrenia etiology our mechanistic understanding of how they shape risk, resilience and disease trajectories remains limited. METHODS Here, we present the study protocol of the Berlin Research Initiative for Diagnostics, Genetic and Environmental Factors of Schizophrenia (BRIDGE-S), which aims to collect a densely phenotyped genetic cohort of 1,000 schizophrenia cases and 1,000 controls. The study's main objectives are to build a resource for i) promoting genetic discoveries and ii) genotype-phenotype associations to infer specific disease subtypes, and iii) exploring gene-environment interactions using polyrisk models. All subjects provide a biological sample for genotyping and complete a core questionnaire capturing a variety of environmental exposures, demographic, psychological and health data. Approximately 50% of individuals in the sample will further undergo a comprehensive clinical and neurocognitive assessment. DISCUSSION With BRIDGE-S we created a valuable database to study genomic and environmental contributions to schizophrenia risk, onset, and outcomes. Results of the BRIDGE-S study could yield insights into the etiological mechanisms of schizophrenia that could ultimately inform risk prediction, and early intervention and treatment strategies.
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Affiliation(s)
- Alice Braun
- grid.6363.00000 0001 2218 4662Department of Psychiatry and Psychotherapy, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Julia Kraft
- grid.6363.00000 0001 2218 4662Department of Psychiatry and Psychotherapy, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Stephan Ripke
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany. .,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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11
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Wilczewski CM, Obasohan J, Paschall JE, Zhang S, Singh S, Maxwell GL, Similuk M, Wolfsberg TG, Turner C, Biesecker LG, Katz AE. Genotype first: Clinical genomics research through a reverse phenotyping approach. Am J Hum Genet 2023; 110:3-12. [PMID: 36608682 PMCID: PMC9892776 DOI: 10.1016/j.ajhg.2022.12.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Although genomic research has predominantly relied on phenotypic ascertainment of individuals affected with heritable disease, the falling costs of sequencing allow consideration of genomic ascertainment and reverse phenotyping (the ascertainment of individuals with specific genomic variants and subsequent evaluation of physical characteristics). In this research modality, the scientific question is inverted: investigators gather individuals with a genomic variant and test the hypothesis that there is an associated phenotype via targeted phenotypic evaluations. Genomic ascertainment research is thus a model of predictive genomic medicine and genomic screening. Here, we provide our experience implementing this research method. We describe the infrastructure we developed to perform reverse phenotyping studies, including aggregating a super-cohort of sequenced individuals who consented to recontact for genomic ascertainment research. We assessed 13 studies completed at the National Institutes of Health (NIH) that piloted our reverse phenotyping approach. The studies can be broadly categorized as (1) facilitating novel genotype-disease associations, (2) expanding the phenotypic spectra, or (3) demonstrating ex vivo functional mechanisms of disease. We highlight three examples of reverse phenotyping studies in detail and describe how using a targeted reverse phenotyping approach (as opposed to phenotypic ascertainment or clinical informatics approaches) was crucial to the conclusions reached. Finally, we propose a framework and address challenges to building collaborative genomic ascertainment research programs at other institutions. Our goal is for more researchers to take advantage of this approach, which will expand our understanding of the predictive capability of genomic medicine and increase the opportunity to mitigate genomic disease.
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Affiliation(s)
- Caralynn M. Wilczewski
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20814, USA
| | - Justice Obasohan
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20814, USA
| | - Justin E. Paschall
- Bioinformatics and Scientific Programming Core, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20814, USA
| | - Suiyuan Zhang
- Bioinformatics and Scientific Programming Core, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20814, USA
| | - Sumeeta Singh
- Bioinformatics and Scientific Programming Core, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20814, USA
| | - George L. Maxwell
- Women’s Health Integrated Research Center, Inova Health System, Falls Church, VA 22042, USA
| | - Morgan Similuk
- National Institute for Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20814, USA
| | - Tyra G. Wolfsberg
- Bioinformatics and Scientific Programming Core, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20814, USA
| | - Clesson Turner
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20814, USA
| | - Leslie G. Biesecker
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20814, USA,Corresponding author
| | - Alexander E. Katz
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20814, USA
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12
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Enhancing Molecular Testing for Effective Delivery of Actionable Gene Diagnostics. BIOENGINEERING (BASEL, SWITZERLAND) 2022; 9:bioengineering9120745. [PMID: 36550951 PMCID: PMC9774983 DOI: 10.3390/bioengineering9120745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 11/07/2022] [Accepted: 11/29/2022] [Indexed: 12/02/2022]
Abstract
There is a deep need to navigate within our genomic data to find, understand and pave the way for disease-specific treatments, as the clinical diagnostic journey provides only limited guidance. The human genome is enclosed in every nucleated cell, and yet at the single-cell resolution many unanswered questions remain, as most of the sequencing techniques use a bulk approach. Therefore, heterogeneity, mosaicism and many complex structural variants remain partially uncovered. As a conceptual approach, nanopore-based sequencing holds the promise of being a single-molecule-based, long-read and high-resolution technique, with the ability of uncovering the nucleic acid sequence and methylation almost in real time. A key limiting factor of current clinical genetics is the deciphering of key disease-causing genomic sequences. As the technological revolution is expanding regarding genetic data, the interpretation of genotype-phenotype correlations should be made with fine caution, as more and more evidence points toward the presence of more than one pathogenic variant acting together as a result of intergenic interplay in the background of a certain phenotype observed in a patient. This is in conjunction with the observation that many inheritable disorders manifest in a phenotypic spectrum, even in an intra-familial way. In the present review, we summarized the relevant data on nanopore sequencing regarding clinical genomics as well as highlighted the importance and content of pre-test and post-test genetic counselling, yielding a complex approach to phenotype-driven molecular diagnosis. This should significantly lower the time-to-right diagnosis as well lower the time required to complete a currently incomplete genotype-phenotype axis, which will boost the chance of establishing a new actionable diagnosis followed by therapeutical approach.
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13
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Nurm M, Reigo A, Nõukas M, Leitsalu L, Nikopensius T, Palover M, Annilo T, Alver M, Saar A, Marandi T, Ainla T, Metspalu A, Esko T, Tõnisson N. Do Biobank Recall Studies Matter? Long-Term Follow-Up of Research Participants With Familial Hypercholesterolemia. Front Genet 2022; 13:936131. [PMID: 35928446 PMCID: PMC9343846 DOI: 10.3389/fgene.2022.936131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 06/23/2022] [Indexed: 12/04/2022] Open
Abstract
Recall-by-genotype (RbG) studies conducted with population-based biobank data remain urgently needed, and follow-up RbG studies, which add substance to this research approach, remain solitary. In such studies, potentially disease-related genotypes are identified and individuals with those genotypes are recalled for consultation to gather more detailed clinical phenotypic information and explain to them the meaning of their genetic findings. Familial hypercholesterolemia (FH) is among the most common autosomal-dominant single-gene disorders, with a global prevalence of 1 in 500 (Nordestgaard et al., Eur. Heart J., 2013, 34 (45), 3478–3490). Untreated FH leads to lifelong elevated LDL cholesterol levels, which can cause ischemic heart disease, with potentially fatal consequences at a relatively early age. In most cases, the pathogenesis of FH is based on a defect in one of three LDL receptor-related genes–APOB, LDLR, and PCSK9. We present our first long-term follow-up RbG study of FH, conducted within the Estonian Biobank (34 recalled participants from a pilot RbG study and 291 controls harboring the same APOB, LDLR, and PCSK9 variants that were included in the pilot study). The participants’ electronic health record data (FH-related diagnoses, lipid-lowering treatment prescriptions) and pharmacogenomic risk of developing statin-induced myopathy were assessed. A survey was administered to recalled participants to discern the impact of the knowledge of their genetic findings on their lives 4–6 years later. Significant differences in FH diagnoses and lipid-lowering treatment prescriptions were found between the recalled participants and controls (34 and 291 participants respectively). Our study highlights the need for more consistent lipid-lowering treatment adherence checkups and encourage more follow-up RbG studies to be performed.
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Affiliation(s)
- Miriam Nurm
- Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Technology, University of Tartu, Tartu, Estonia
| | - Anu Reigo
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Margit Nõukas
- Institute of Genomics, University of Tartu, Tartu, Estonia
- Department of Biotechnology, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Liis Leitsalu
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Marili Palover
- Institute of Genomics, University of Tartu, Tartu, Estonia
- Department of Biotechnology, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Tarmo Annilo
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Maris Alver
- Institute of Genomics, University of Tartu, Tartu, Estonia
- Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland
| | - Aet Saar
- Department of Cardiology, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
- Cardiology Centre, North Estonia Medical Centre, Tallinn, Estonia
| | - Toomas Marandi
- Department of Cardiology, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
- Cardiology Centre, North Estonia Medical Centre, Tallinn, Estonia
| | - Tiia Ainla
- Department of Cardiology, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
- Cardiology Centre, North Estonia Medical Centre, Tallinn, Estonia
| | - Andres Metspalu
- Institute of Genomics, University of Tartu, Tartu, Estonia
- Department of Biotechnology, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Tõnu Esko
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Neeme Tõnisson
- Institute of Genomics, University of Tartu, Tartu, Estonia
- Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
- *Correspondence: Neeme Tõnisson,
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14
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Tschigg K, Consoli L, Biasiotto R, Mascalzoni D. Ethical, legal and social/societal implications (ELSI) of recall-by-genotype (RbG) and genotype-driven-research (GDR) approaches: a scoping review. Eur J Hum Genet 2022; 30:1000-1010. [PMID: 35705790 PMCID: PMC9437022 DOI: 10.1038/s41431-022-01120-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 03/17/2022] [Accepted: 05/05/2022] [Indexed: 11/29/2022] Open
Abstract
Recall by Genotype (RbG), Genotype-driven-recall (GDR), and Genotype-based-recall (GBR) strategies are increasingly used to conduct genomic or biobanking sub-studies that single out participants as eligible because of their specific individual genotypic information. However, existing regulatory and governance frameworks do not apply to all aspects of genotype-driven research approaches. The recall strategies disclose or withhold personal genotypic information with uncertain clinical utility. Accordingly, this scoping review aims to identify peculiar, explicit and implicit ethical, legal, and societal/social implications (ELSI) of RbG study designs. We conducted a systematic literature search of three electronic databases from November 2020 to February 2021. We investigated qualitative and quantitative research methods used to report ELSI aspects in RbG research. Congruent with other research findings, we identified a lack of qualitative research investigating the particular ELSI challenges with RbG. We included and analysed the content of twenty-five publications. We found a consensus on RbG posing significant ethical issues, dilemmas, barriers, concerns and societal challenges. However, we found that the approaches to disclosure and study-specific recall and communication strategies employed consent models and Return of Research Results (RoRR) policies varied considerably. Furthermore, we identified a high heterogeneity in perspectives of participants and experts about ELSI of study-specific RbG policies. Therefore, further fine-mapping through qualitative and empirical research is needed to draw conclusions and re-fine ELSI frameworks.
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Affiliation(s)
- Katharina Tschigg
- Department of Cellular, Computational, and Integrative Biology, University of Trento, Trento, Italy. .,Institute for Biomedicine & Affiliated Institute of the University of Lübeck, Eurac Research, Bolzano, Italy, Bozen, Italy.
| | - Luca Consoli
- Institute for Science in Society, Radboud University, Nijmegen, Netherlands
| | - Roberta Biasiotto
- Institute for Biomedicine & Affiliated Institute of the University of Lübeck, Eurac Research, Bolzano, Italy, Bozen, Italy.,Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Deborah Mascalzoni
- Institute for Biomedicine & Affiliated Institute of the University of Lübeck, Eurac Research, Bolzano, Italy, Bozen, Italy.,Department of Public Health and Caring Sciences, Center for Research Ethics and Bioethics, Uppsala University, Uppsala, Sweden
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15
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Fang S, Wade KH, Hughes DA, Fitzgibbon S, Yip V, Timpson NJ, Corbin LJ. A multivariant recall-by-genotype study of the metabolomic signature of BMI. Obesity (Silver Spring) 2022; 30:1298-1310. [PMID: 35598895 PMCID: PMC9324973 DOI: 10.1002/oby.23441] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 03/14/2022] [Accepted: 03/15/2022] [Indexed: 12/12/2022]
Abstract
OBJECTIVE This study estimated the effect of BMI on circulating metabolites in young adults using a recall-by-genotype study design. METHODS A recall-by-genotype study was implemented in the Avon Longitudinal Study of Parents and Children. Samples from 756 participants were selected for untargeted metabolomics analysis based on low versus high genetic liability for higher BMI defined by a genetic risk score (GRS). Regression analyses were performed to investigate associations between BMI GRS group and relative abundance of 973 metabolites. RESULTS After correction for multiple testing, 29 metabolites were associated with BMI GRS group. Bilirubin was among the most strongly associated metabolites, with reduced levels measured in individuals in the high-BMI GRS group (β = -0.32, 95% CI: -0.46 to -0.18, Benjamini-Hochberg adjusted p = 0.005). This study observed associations between BMI GRS group and the levels of several potentially diet-related metabolites, including hippurate, which had lower mean abundance in individuals in the high-BMI GRS group (β = -0.29, 95% CI: -0.44 to -0.15, Benjamini-Hochberg adjusted p = 0.008). CONCLUSIONS Together with existing literature, these results suggest that a genetic predisposition to higher BMI captures differences in metabolism leading to adiposity gain. In the absence of prospective data, separating these effects from the downstream consequences of weight gain is challenging.
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Affiliation(s)
- Si Fang
- MRC Integrative Epidemiology Unit at the University of BristolBristolUK
- Population Health ScienceBristol Medical SchoolUniversity of BristolBristolUK
| | - Kaitlin H. Wade
- MRC Integrative Epidemiology Unit at the University of BristolBristolUK
- Population Health ScienceBristol Medical SchoolUniversity of BristolBristolUK
| | - David A. Hughes
- MRC Integrative Epidemiology Unit at the University of BristolBristolUK
- Population Health ScienceBristol Medical SchoolUniversity of BristolBristolUK
| | - Sophie Fitzgibbon
- Bristol Bioresource LaboratoriesPopulation Health ScienceBristol Medical SchoolUniversity of BristolBristolUK
| | - Vikki Yip
- Bristol Bioresource LaboratoriesPopulation Health ScienceBristol Medical SchoolUniversity of BristolBristolUK
| | - Nicholas J. Timpson
- MRC Integrative Epidemiology Unit at the University of BristolBristolUK
- Population Health ScienceBristol Medical SchoolUniversity of BristolBristolUK
| | - Laura J. Corbin
- MRC Integrative Epidemiology Unit at the University of BristolBristolUK
- Population Health ScienceBristol Medical SchoolUniversity of BristolBristolUK
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16
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Stacey D, Chen L, Stanczyk PJ, Howson JMM, Mason AM, Burgess S, MacDonald S, Langdown J, McKinney H, Downes K, Farahi N, Peters JE, Basu S, Pankow JS, Tang W, Pankratz N, Sabater-Lleal M, de Vries PS, Smith NL, Gelinas AD, Schneider DJ, Janjic N, Samani NJ, Ye S, Summers C, Chilvers ER, Danesh J, Paul DS. Elucidating mechanisms of genetic cross-disease associations at the PROCR vascular disease locus. Nat Commun 2022; 13:1222. [PMID: 35264566 PMCID: PMC8907312 DOI: 10.1038/s41467-022-28729-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 02/08/2022] [Indexed: 02/05/2023] Open
Abstract
Many individual genetic risk loci have been associated with multiple common human diseases. However, the molecular basis of this pleiotropy often remains unclear. We present an integrative approach to reveal the molecular mechanism underlying the PROCR locus, associated with lower coronary artery disease (CAD) risk but higher venous thromboembolism (VTE) risk. We identify PROCR-p.Ser219Gly as the likely causal variant at the locus and protein C as a causal factor. Using genetic analyses, human recall-by-genotype and in vitro experimentation, we demonstrate that PROCR-219Gly increases plasma levels of (activated) protein C through endothelial protein C receptor (EPCR) ectodomain shedding in endothelial cells, attenuating leukocyte-endothelial cell adhesion and vascular inflammation. We also associate PROCR-219Gly with an increased pro-thrombotic state via coagulation factor VII, a ligand of EPCR. Our study, which links PROCR-219Gly to CAD through anti-inflammatory mechanisms and to VTE through pro-thrombotic mechanisms, provides a framework to reveal the mechanisms underlying similar cross-phenotype associations.
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Affiliation(s)
- David Stacey
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Lingyan Chen
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Paulina J Stanczyk
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Joanna M M Howson
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Department of Genetics, Novo Nordisk Research Centre Oxford, Innovation Building, Old Road Campus, Roosevelt Drive, Oxford, UK
| | - Amy M Mason
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Stephen Burgess
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Stephen MacDonald
- Specialist Haemostasis Unit, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Jonathan Langdown
- Specialist Haemostasis Unit, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Harriett McKinney
- Department of Haematology, University of Cambridge, Cambridge, UK
- National Health Service Blood and Transplant, Cambridge, UK
| | - Kate Downes
- Department of Haematology, University of Cambridge, Cambridge, UK
- National Health Service Blood and Transplant, Cambridge, UK
- National Institute for Health Research BioResource, University of Cambridge, Cambridge, UK
| | - Neda Farahi
- Department of Medicine, University of Cambridge, Cambridge, UK
| | - James E Peters
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Centre for Inflammatory Disease, Department of Immunology and Inflammation, Imperial College London, London, UK
- Health Data Research UK London, London, UK
| | - Saonli Basu
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Weihong Tang
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, School of Medicine, University of Minnesota, Minneapolis, MN, USA
| | - Maria Sabater-Lleal
- Genomics of Complex Diseases Group, Sant Pau Biomedical Research Institute, IIB-Sant Pau, Barcelona, Spain
- Cardiovascular Medicine Unit, Department of Medicine, Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences; School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Nicholas L Smith
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
- Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | | | | | | | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Shu Ye
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | | | - Edwin R Chilvers
- National Heart and Lung Institute, Imperial College London, London, UK
| | - John Danesh
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK
| | - Dirk S Paul
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK.
- Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK.
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17
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Associations of circulating C-reactive proteins, APOE ε4, and brain markers for Alzheimer's disease in healthy samples across the lifespan. Brain Behav Immun 2022; 100:243-253. [PMID: 34920091 DOI: 10.1016/j.bbi.2021.12.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 11/12/2021] [Accepted: 12/11/2021] [Indexed: 12/14/2022] Open
Abstract
The apolipoprotein E gene ε4 allele (APOE ε4) and higher circulating level of C-reactive protein (CRP) have been extensively investigated as risk factors for Alzheimer's disease (AD). Paradoxically, APOE ε4 has been associated with lower levels of blood CRP in middle-aged and older populations. However, few studies have investigated this intriguing relation and its impact on neurological markers for AD in younger ages, nor across the whole lifespan. Here, we examine associations of blood CRP levels, APOE ε4, and biomarkers for AD in a cognitively healthy lifespan cohort (N up to 749; 20-81 years of age) and replicate the findings in UK Biobank (N = 304 322; 37-72 years of age), the developmental ABCD study (N = 10 283; 9-11 years of age), and a middle-aged sample (N = 339; 40-65 years of age). Hippocampal volume, brain amyloid-β (Aβ) plaque levels, cerebrospinal fluid (CSF) levels of Aβ and tau species, and neurofilament protein light protein (NFL) were used as AD biomarkers in subsamples. In addition, we examined the genetic contribution to the variation of CRP levels over different CRP ranges using polygenic scores for CRP (PGS-CRP). Our results show APOE ε4 consistently associates with low blood CRP levels across all age groups (p < 0.05). Strikingly, both ε4 and PGS-CRP associated mainly with blood CRP levels within the low range (<5mg/L). We then show both APOE ε4 and high CRP levels associate with smaller hippocampus volumes across the lifespan (p < 0.025). APOE ε4 was associated with high Aβ plaque levels in the brain (FDR-corrected p = 8.69x10-4), low levels of CSF Aβ42 (FDR-corrected p = 6.9x10-2), and lower ratios of Aβ42 to Aβ40 (FDR-corrected p = 5.08x10-5). Blood CRP levels were weakly correlated with higher ratio of CSF Aβ42 to Aβ40 (p = 0.03, FDR-corrected p = 0.4). APOE ε4 did not correlate with blood concentrations of another 9 inflammatory cytokines, and none of these cytokines correlated with AD biomarkers. CONCLUSION: The inverse correlation between APOEε 4 and blood CRP levels existed before any pathological AD biomarker was observed, and only in the low CRP level range. Thus, we suggest to investigate whether APOEε 4 can confer risk by being associated with a lower inflammatory response to daily exposures, possibly leading to greater accumulation of low-grade inflammatory stress throughout life. A lifespan perspective is needed to understand this relationship concerning risk of developing AD.
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Nickerson AP, Corbin LJ, Timpson NJ, Phillips K, Pickering AE, Dunham JP. Evaluating the association of TRPA1 gene polymorphisms with pain sensitivity: a protocol for an adaptive recall by genotype study. BMC Med Genomics 2022; 15:9. [PMID: 35022050 PMCID: PMC8753821 DOI: 10.1186/s12920-022-01156-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 01/01/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Pain is a complex polygenic trait whose common genetic underpinnings are relatively ill-defined due in part to challenges in measuring pain as a phenotype. Pain sensitivity can be quantified, but this is difficult to perform at the scale required for genome wide association studies (GWAS). Existing GWAS of pain have identified surprisingly few loci involved in nociceptor function which contrasts strongly with rare monogenic pain states. This suggests a lack of resolution with current techniques. We propose an adaptive methodology within a recall-by-genotype (RbG) framework using detailed phenotyping to screen minor alleles in a candidate 'nociceptor' gene in an attempt to estimate their genetic contribution to pain. METHODS/DESIGN Participants of the Avon Longitudinal Study of Parents and Children will be recalled on the basis of genotype at five common non-synonomous SNPs in the 'nociceptor' gene transient receptor potential ankylin 1 (TRPA1). Those homozygous for the common alleles at each of the five SNPs will represent a control group. Individuals homozygous for the minor alleles will then be recruited in a series of three sequential test groups. The outcome of a pre-planned early assessment (interim) of the current test group will determine whether to continue recruitment or switch to the next test group. Pain sensitivity will be assessed using quantitative sensory testing (QST) before and after topical application of 10% cinnamaldehyde (a TRPA1 agonist). DISCUSSION The design of this adaptive RbG study offers efficiency in the assessment of associations between genetic variation at TRPA1 and detailed pain phenotypes. The possibility to change the test group in response to preliminary data increases the likelihood to observe smaller effect sizes relative to a conventional multi-armed design, as well as reducing futile testing of participants where an effect is unlikely to be observed. This specific adaptive RbG design aims to uncover the influence of common TRPA1 variants on pain sensation but can be applied to any hypothesis-led genotype study where costly and time intensive investigation is required and / or where there is large uncertainty around the expected effect size. TRIAL REGISTRATION ISRCTN, ISRCTN16294731. Retrospectively registered 25th November 2021.
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Affiliation(s)
- Aidan P Nickerson
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, BS8 1TD, UK
- Anaesthesia, Pain and Critical Care Sciences, University of Bristol, Bristol, UK
- Eli Lilly and Company, 8 Arlington Square West, Bracknell, RG12 1WA, UK
| | - Laura J Corbin
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - Keith Phillips
- Eli Lilly and Company, 8 Arlington Square West, Bracknell, RG12 1WA, UK
| | - Anthony E Pickering
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, BS8 1TD, UK
- Anaesthesia, Pain and Critical Care Sciences, University of Bristol, Bristol, UK
| | - James P Dunham
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, BS8 1TD, UK.
- Anaesthesia, Pain and Critical Care Sciences, University of Bristol, Bristol, UK.
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Custovic A, Siddiqui S, Saglani S. Considering biomarkers in asthma disease severity. J Allergy Clin Immunol 2021; 149:480-487. [PMID: 34942235 DOI: 10.1016/j.jaci.2021.11.021] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 11/25/2021] [Accepted: 11/30/2021] [Indexed: 10/19/2022]
Abstract
Amongst patients with asthma, reliance on the type/dose of prescribed medication and symptom control does not adequately capture those at risk of adverse outcomes, and we need biomarkers for risk and treatment stratification which are consistently accurate, readily quantifiable and reproducible. The majority of patients with severe asthma, regardless of age, have predominant type-2 (T2) inflammation mediated disease, making airway/blood eosinophils, FeNO, periostin and/or allergic sensitization potentially important biomarkers for severe disease. In both adult and pediatric asthma, there is scope to improve prediction of severe attacks by using a composite T2 biomarkers of blood eosinophils and FeNO. Technological advances in component-resolved diagnostics (CRD) microarray technologies coupled with the development of interpretation software offer a possibility to use CRD as biomarkers of asthma severity amongst sensitized asthmatics. Genetic predisposition and polygenic risk scores of relevant traits (e.g., lung function, host immune responses, biomarkers of exposure from the indoor and outdoor environment, infection and microbial dysbiosis) may also contribute to prediction algorithms. We challenge the idea that asthma can be accurately defined in an individual patient by a discrete and static "endotype" (e.g., T2-high asthma). As we traverse the new era of molecular endotyping in asthma, we need to understand how relevant mechanisms impact patient outcomes, and in parallel develop new tools and approaches to stratify therapies and define individual patient trajectories.
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Affiliation(s)
- Adnan Custovic
- National Heart and Lung Institute, Imperial College London, UK.
| | - Salman Siddiqui
- Department of Respiratory Sciences, University of Leicester and NIHR Respiratory Biomedical Research Unit, Glenfield Hospital, Leicester UK
| | - Sejal Saglani
- National Heart and Lung Institute, Imperial College London, UK
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20
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Bartsch U, Corbin LJ, Hellmich C, Taylor M, Easey KE, Durant C, Marston HM, Timpson NJ, Jones MW. Schizophrenia-associated variation at ZNF804A correlates with altered experience-dependent dynamics of sleep slow waves and spindles in healthy young adults. Sleep 2021; 44:zsab191. [PMID: 34329479 PMCID: PMC8664578 DOI: 10.1093/sleep/zsab191] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 07/06/2021] [Indexed: 12/12/2022] Open
Abstract
The rs1344706 polymorphism in ZNF804A is robustly associated with schizophrenia and schizophrenia is, in turn, associated with abnormal non-rapid eye movement (NREM) sleep neurophysiology. To examine whether rs1344706 is associated with intermediate neurophysiological traits in the absence of disease, we assessed the relationship between genotype, sleep neurophysiology, and sleep-dependent memory consolidation in healthy participants. We recruited healthy adult males with no history of psychiatric disorder from the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort. Participants were homozygous for either the schizophrenia-associated 'A' allele (N = 22) or the alternative 'C' allele (N = 18) at rs1344706. Actigraphy, polysomnography (PSG) and a motor sequence task (MST) were used to characterize daily activity patterns, sleep neurophysiology and sleep-dependent memory consolidation. Average MST learning and sleep-dependent performance improvements were similar across genotype groups, albeit more variable in the AA group. During sleep after learning, CC participants showed increased slow-wave (SW) and spindle amplitudes, plus augmented coupling of SW activity across recording electrodes. SW and spindles in those with the AA genotype were insensitive to learning, whilst SW coherence decreased following MST training. Accordingly, NREM neurophysiology robustly predicted the degree of overnight motor memory consolidation in CC carriers, but not in AA carriers. We describe evidence that rs1344706 polymorphism in ZNF804A is associated with changes in the coordinated neural network activity that supports offline information processing during sleep in a healthy population. These findings highlight the utility of sleep neurophysiology in mapping the impacts of schizophrenia-associated common genetic variants on neural circuit oscillations and function.
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Affiliation(s)
- Ullrich Bartsch
- School of Physiology, Pharmacology & Neuroscience, University of Bristol, Bristol, UK
- Translational Neuroscience, Eli Lilly & Co Ltd UK, Erl Wood Manor, Windlesham, UK
- UK DRI Health Care & Technology at Imperial College London and the University of Surrey, Surrey Sleep Research Centre, University of Surrey, Clinical Research Building, Egerton Road, Guildford, Surrey, UK
| | - Laura J Corbin
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Charlotte Hellmich
- School of Physiology, Pharmacology & Neuroscience, University of Bristol, Bristol, UK
| | - Michelle Taylor
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, UK
| | - Kayleigh E Easey
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, UK
- UK Centre for Tobacco and Alcohol Studies, School of Psychological Science, University of Bristol, Bristol, UK
| | - Claire Durant
- Clinical Research and Imaging Centre (CRIC), University of Bristol, Bristol, UK
| | - Hugh M Marston
- Translational Neuroscience, Eli Lilly & Co Ltd UK, Erl Wood Manor, Windlesham, UK
- Böhringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Matthew W Jones
- School of Physiology, Pharmacology & Neuroscience, University of Bristol, Bristol, UK
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Mascalzoni D, Biasiotto R, Borsche M, Brüggemann N, De Grandi A, Goegele M, Frygner-Holm S, Klein C, Kösters M, Staunton C, Pramstaller PP, Krawczak M, Hicks AA. Balancing scientific interests and the rights of participants in designing a recall by genotype study. Eur J Hum Genet 2021; 29:1146-1157. [PMID: 33981014 PMCID: PMC8298596 DOI: 10.1038/s41431-021-00860-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 12/15/2020] [Accepted: 03/02/2021] [Indexed: 01/14/2023] Open
Abstract
Recall by genotype (RbG) studies aim to better understand the phenotypes that correspond to genetic variants of interest, by recruiting carriers of such variants for further phenotyping. RbG approaches pose major ethical and legal challenges related to the disclosure of possibly unwanted genetic information. The Cooperative Health Research in South Tyrol (CHRIS) study is a longitudinal cohort study based in South Tyrol, Italy. Demand has grown for CHRIS study participants to be enrolled in RbG studies, thus making the design of a suitable ethical framework a pressing need. We here report upon the design of a pilot RbG study conducted with CHRIS study participants. By reviewing the literature and by consulting relevant stakeholders (CHRIS participants, clinical geneticists, ethics board, GPs), we identified key ethical issues in RbG approaches (e.g. complexity of the context, communication of genetic results, measures to further protect participants). The design of the pilot was based on a feasibility assessment, the selection of a suitable test case within the ProtectMove Research Unit on reduced penetrance of hereditary movement disorders, and the development of appropriate recruitment and communication strategies. An empirical study was embedded in the pilot study with the aim of understanding participants' views on RbG. Our experience with the pilot study in CHRIS allowed us to contribute to the development of best practices and policies for RbG studies by drawing recommendations: addressing the possibility of RbG in the original consent, implementing tailored communication strategies, engaging stakeholders, designing embedded empirical studies, and sharing research experiences and methodology.
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Affiliation(s)
- Deborah Mascalzoni
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy.
- Department of Public Health and Caring Sciences, Center for Research Ethics and Bioethics, Uppsala University, Uppsala, Sweden.
| | - Roberta Biasiotto
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy
| | - Max Borsche
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Department of Neurology, University Medical Center Schleswig-Holstein, Lübeck, Germany
| | - Norbert Brüggemann
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Department of Neurology, University Medical Center Schleswig-Holstein, Lübeck, Germany
| | - Alessandro De Grandi
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy
| | - Martin Goegele
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy
| | | | - Christine Klein
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
| | - Maria Kösters
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy
| | - Ciara Staunton
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy
- School of Law, Middlesex University, London, UK
| | - Peter P Pramstaller
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy
| | - Michael Krawczak
- Institute of Medical Informatics and Statistics, Kiel University, Kiel, Germany
| | - Andrew A Hicks
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy
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Jallow MW, Campino S, Saidykhan A, Prentice AM, Cerami C. Common Variants in the TMPRSS6 Gene Alter Hepcidin but not Plasma Iron in Response to Oral Iron in Healthy Gambian Adults: A Recall-by-Genotype Study. Curr Dev Nutr 2021; 5:nzab014. [PMID: 33817543 PMCID: PMC7994066 DOI: 10.1093/cdn/nzab014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 02/02/2021] [Accepted: 02/17/2021] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND The role of genetic determinants in mediating iron status in Africans is not fully understood. Genome-wide association studies in non-African populations have revealed genetic variants in the transmembrane protease serine 6 gene (TMPRSS6) that are associated with the risk of anemia. OBJECTIVES To investigate the effects of risk alleles for low iron status, namely TMPRSS6 rs2235321, rs855791, and rs4820268, on responses to oral iron in healthy Gambian adults. METHODS Using a recall-by-genotype design, participants were selected from a pregenotype cohort of 3000 individuals in the Keneba Biobank (Medical Research Council Unit The Gambia at the London School of Hygiene & Tropical Medicine). Participants were invited to participate in the study based on 9 genotype combinations obtained from 3 TMPRSS6 single nucleotide polymorphisms (SNPs): rs2235321, rs855791, and rs4820268. The participants fasted overnight and then ingested a single oral dose of ferrous sulfate (130 mg elemental iron). Blood samples were collected prior to iron ingestion and at 2 and 5 h after the oral iron dose. The effects of genotype on hepcidin and plasma iron parameters were assessed. RESULTS A total of 251 individuals were enrolled. Homozygous carriers of the major TMPRSS6 alleles at each of the SNPs had higher plasma hepcidin at baseline (rs2235321: GG compared with AA = 9.50 compared with 6.60 ng/ml, P = 0.035; rs855791: GG compared with AG = 9.50 compared with 4.96 ng/mL, P = 0.015; rs4820268: AA compared with GG = 9.50 compared with 3.27 ng/mL, P = 0.002) and at subsequent timepoints. In most subjects, hepcidin concentrations increased following iron ingestion (overall group mean = 4.98 ± 0.98 ng/mL at 5 h, P < 0.001), but double heterozygotes at rs2235321 and rs855791 showed no increase (0.36 ± 0.40 ng/mL at 5 h, P = 0.667). CONCLUSIONS This study revealed that common TMPRSS6 variants influence hepcidin concentrations, but not iron status indicators either at baseline or following a large oral dose of iron. These results suggest that genetic variations in the TMPRSS6 gene are unlikely to be important contributors to variations in iron status in Africans.This study was registered at clinicaltrials.gov (# NCT03341338).
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Affiliation(s)
- Momodou W Jallow
- MRC Unit The Gambia at London School of Hygiene & Tropical Medicine, Fajara, Banjul, The Gambia
- Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Susana Campino
- Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Alasana Saidykhan
- MRC Unit The Gambia at London School of Hygiene & Tropical Medicine, Fajara, Banjul, The Gambia
| | - Andrew M Prentice
- MRC Unit The Gambia at London School of Hygiene & Tropical Medicine, Fajara, Banjul, The Gambia
| | - Carla Cerami
- MRC Unit The Gambia at London School of Hygiene & Tropical Medicine, Fajara, Banjul, The Gambia
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Momozawa Y, Mizukami K. Unique roles of rare variants in the genetics of complex diseases in humans. J Hum Genet 2021; 66:11-23. [PMID: 32948841 PMCID: PMC7728599 DOI: 10.1038/s10038-020-00845-2] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 09/06/2020] [Indexed: 12/19/2022]
Abstract
Genome-wide association studies have identified >10,000 genetic variants associated with various phenotypes and diseases. Although the majority are common variants, rare variants with >0.1% of minor allele frequency have been investigated by imputation and using disease-specific custom SNP arrays. Rare variants sequencing analysis mainly revealed have played unique roles in the genetics of complex diseases in humans due to their distinctive features, in contrast to common variants. Unique roles are hypothesis-free evidence for gene causality, a precise target of functional analysis for understanding disease mechanisms, a new favorable target for drug development, and a genetic marker with high disease risk for personalized medicine. As whole-genome sequencing continues to identify more rare variants, the roles associated with rare variants will also increase. However, a better estimation of the functional impact of rare variants across whole genome is needed to enhance their contribution to improvements in human health.
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Affiliation(s)
- Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan.
- Laboratory for Molecular Science for Drug Discovery, Graduate School of Medical Life Science, Yokohama City University, Kanagawa, Japan.
| | - Keijiro Mizukami
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
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24
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Swietlik EM, Prapa M, Martin JM, Pandya D, Auckland K, Morrell NW, Gräf S. 'There and Back Again'-Forward Genetics and Reverse Phenotyping in Pulmonary Arterial Hypertension. Genes (Basel) 2020; 11:E1408. [PMID: 33256119 PMCID: PMC7760524 DOI: 10.3390/genes11121408] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 11/17/2020] [Accepted: 11/23/2020] [Indexed: 02/07/2023] Open
Abstract
Although the invention of right heart catheterisation in the 1950s enabled accurate clinical diagnosis of pulmonary arterial hypertension (PAH), it was not until 2000 when the landmark discovery of the causative role of bone morphogenetic protein receptor type II (BMPR2) mutations shed new light on the pathogenesis of PAH. Since then several genes have been discovered, which now account for around 25% of cases with the clinical diagnosis of idiopathic PAH. Despite the ongoing efforts, in the majority of patients the cause of the disease remains elusive, a phenomenon often referred to as "missing heritability". In this review, we discuss research approaches to uncover the genetic architecture of PAH starting with forward phenotyping, which in a research setting should focus on stable intermediate phenotypes, forward and reverse genetics, and finally reverse phenotyping. We then discuss potential sources of "missing heritability" and how functional genomics and multi-omics methods are employed to tackle this problem.
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Affiliation(s)
- Emilia M. Swietlik
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; (E.M.S.); (M.P.); (J.M.M.); (D.P.); (K.A.); (N.W.M.)
- Royal Papworth Hospital NHS Foundation Trust, Cambridge CB2 0AY, UK
- Addenbrooke’s Hospital NHS Foundation Trust, Cambridge CB2 0QQ, UK
| | - Matina Prapa
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; (E.M.S.); (M.P.); (J.M.M.); (D.P.); (K.A.); (N.W.M.)
- Addenbrooke’s Hospital NHS Foundation Trust, Cambridge CB2 0QQ, UK
| | - Jennifer M. Martin
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; (E.M.S.); (M.P.); (J.M.M.); (D.P.); (K.A.); (N.W.M.)
| | - Divya Pandya
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; (E.M.S.); (M.P.); (J.M.M.); (D.P.); (K.A.); (N.W.M.)
| | - Kathryn Auckland
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; (E.M.S.); (M.P.); (J.M.M.); (D.P.); (K.A.); (N.W.M.)
| | - Nicholas W. Morrell
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; (E.M.S.); (M.P.); (J.M.M.); (D.P.); (K.A.); (N.W.M.)
- Royal Papworth Hospital NHS Foundation Trust, Cambridge CB2 0AY, UK
- Addenbrooke’s Hospital NHS Foundation Trust, Cambridge CB2 0QQ, UK
- NIHR BioResource for Translational Research, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Stefan Gräf
- Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; (E.M.S.); (M.P.); (J.M.M.); (D.P.); (K.A.); (N.W.M.)
- NIHR BioResource for Translational Research, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
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Strategic vision for improving human health at The Forefront of Genomics. Nature 2020; 586:683-692. [PMID: 33116284 DOI: 10.1038/s41586-020-2817-4] [Citation(s) in RCA: 162] [Impact Index Per Article: 40.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 09/04/2020] [Indexed: 12/20/2022]
Abstract
Starting with the launch of the Human Genome Project three decades ago, and continuing after its completion in 2003, genomics has progressively come to have a central and catalytic role in basic and translational research. In addition, studies increasingly demonstrate how genomic information can be effectively used in clinical care. In the future, the anticipated advances in technology development, biological insights, and clinical applications (among others) will lead to more widespread integration of genomics into almost all areas of biomedical research, the adoption of genomics into mainstream medical and public-health practices, and an increasing relevance of genomics for everyday life. On behalf of the research community, the National Human Genome Research Institute recently completed a multi-year process of strategic engagement to identify future research priorities and opportunities in human genomics, with an emphasis on health applications. Here we describe the highest-priority elements envisioned for the cutting-edge of human genomics going forward-that is, at 'The Forefront of Genomics'.
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26
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Jallow MW, Cerami C, Clark TG, Prentice AM, Campino S. Differences in the frequency of genetic variants associated with iron imbalance among global populations. PLoS One 2020; 15:e0235141. [PMID: 32609760 PMCID: PMC7329092 DOI: 10.1371/journal.pone.0235141] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Accepted: 06/09/2020] [Indexed: 02/08/2023] Open
Abstract
Iron deficiency anaemia is a major health problem affecting approximately 1.2 billion people worldwide. Young children, women of reproductive age and pregnant women living in sub-Saharan Africa are the most vulnerable. It is estimated that iron deficiency accounts for half of anaemia cases. Apart from nutritional deficiency, infection, inflammation and genetic factors are the major drivers of anaemia. However, the role of genetic risk factors has not been thoroughly investigated. This is particularly relevant in African populations, as they carry high genetic diversity and have a high prevalence of anaemia. Multiple genetic variations in iron regulatory genes have been linked to impaired iron status. Here we conducted a literature review to identify genetic variants associated with iron imbalance among global populations. We compare their allele frequencies and risk scores and we investigated population-specific selection among populations of varying geographic origin using data from the Keneba Biobank representing individuals in rural Gambia and the 1000 Genomes Project. We identified a significant lack of data on the genetic determinants of iron status in sub-Saharan Africa. Most of the studies on genetic determinants of iron status have been conducted in Europeans. Also, we identified population differences in allele frequencies in candidate putative genetic risk factors. Given the disproportionately high genetic diversity in African populations coupled with their high prevalence of iron deficiency, there is need to investigate the genetic influences of low iron status in Sub-Saharan Africa. The resulting insights may inform the future implementation of iron intervention strategies.
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Affiliation(s)
- Momodou W. Jallow
- Nutrition Theme, MRC Unit The Gambia at London School of Hygiene & Tropical Medicine, Banjul, The Gambia
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
- * E-mail: (SC); (MWJ)
| | - Carla Cerami
- Nutrition Theme, MRC Unit The Gambia at London School of Hygiene & Tropical Medicine, Banjul, The Gambia
| | - Taane G. Clark
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Andrew M. Prentice
- Nutrition Theme, MRC Unit The Gambia at London School of Hygiene & Tropical Medicine, Banjul, The Gambia
| | - Susana Campino
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
- * E-mail: (SC); (MWJ)
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Bovijn J, Krebs K, Chen CY, Boxall R, Censin JC, Ferreira T, Pulit SL, Glastonbury CA, Laber S, Millwood IY, Lin K, Li L, Chen Z, Milani L, Smith GD, Walters RG, Mägi R, Neale BM, Lindgren CM, Holmes MV. Evaluating the cardiovascular safety of sclerostin inhibition using evidence from meta-analysis of clinical trials and human genetics. Sci Transl Med 2020; 12:eaay6570. [PMID: 32581134 PMCID: PMC7116615 DOI: 10.1126/scitranslmed.aay6570] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 11/26/2019] [Accepted: 05/26/2020] [Indexed: 12/23/2022]
Abstract
Inhibition of sclerostin is a therapeutic approach to lowering fracture risk in patients with osteoporosis. However, data from phase 3 randomized controlled trials (RCTs) of romosozumab, a first-in-class monoclonal antibody that inhibits sclerostin, suggest an imbalance of serious cardiovascular events, and regulatory agencies have issued marketing authorizations with warnings of cardiovascular disease. Here, we meta-analyze published and unpublished cardiovascular outcome trial data of romosozumab and investigate whether genetic variants that mimic therapeutic inhibition of sclerostin are associated with higher risk of cardiovascular disease. Meta-analysis of up to three RCTs indicated a probable higher risk of cardiovascular events with romosozumab. Scaled to the equivalent dose of romosozumab (210 milligrams per month; 0.09 grams per square centimeter of higher bone mineral density), the SOST genetic variants were associated with lower risk of fracture and osteoporosis (commensurate with the therapeutic effect of romosozumab) and with a higher risk of myocardial infarction and/or coronary revascularization and major adverse cardiovascular events. The same variants were also associated with increased risk of type 2 diabetes mellitus and higher systolic blood pressure and central adiposity. Together, our findings indicate that inhibition of sclerostin may elevate cardiovascular risk, warranting a rigorous evaluation of the cardiovascular safety of romosozumab and other sclerostin inhibitors.
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Affiliation(s)
- Jonas Bovijn
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7FZ, UK.
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Kristi Krebs
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
| | - Chia-Yen Chen
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ruth Boxall
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Jenny C Censin
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7FZ, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Teresa Ferreira
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7FZ, UK
| | - Sara L Pulit
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7FZ, UK
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- Department of Genetics, University Medical Center Utrecht, 3584 CX Utrecht, Netherlands
| | - Craig A Glastonbury
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7FZ, UK
| | - Samantha Laber
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7FZ, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Kuang Lin
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, Peking University Health Science Centre, Peking University, Beijing 100191, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Lili Milani
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Reedik Mägi
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Cecilia M Lindgren
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7FZ, UK.
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
- National Institute for Health Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford OX3 9DU, UK
| | - Michael V Holmes
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7FZ, UK.
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- National Institute for Health Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford OX3 9DU, UK
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28
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Corbin LJ, Hughes DA, Chetwynd AJ, Taylor AE, Southam AD, Jankevics A, Weber RJM, Groom A, Dunn WB, Timpson NJ. Metabolic characterisation of disturbances in the APOC3/triglyceride-rich lipoprotein pathway through sample-based recall by genotype. Metabolomics 2020; 16:69. [PMID: 32494907 PMCID: PMC7270992 DOI: 10.1007/s11306-020-01689-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Accepted: 05/15/2020] [Indexed: 12/11/2022]
Abstract
INTRODUCTION High plasma triacylglyceride levels are known to be associated with increased risk of atherosclerotic cardiovascular disease. Apolipoprotein C-III (apoC-III) is a key regulator of plasma triacylglyceride levels and is associated with hypertriglyceridemia via a number of pathways. There is consistent evidence for an association of cardiovascular events with blood apoC-III level, with support from human genetic studies of APOC3 variants. As such, apoC-III has been recognised as a potential therapeutic target for patients with severe hypertriglyceridaemia with one of the most promising apoC-III-targeting drugs, volanesorsen, having recently progressed through Phase III trials. OBJECTIVES To exploit a rare loss of function variant in APOC3 (rs138326449) to characterise the potential long-term treatment effects of apoC-III targeting interventions on the metabolome. METHODS In a recall-by-genotype study, 115 plasma samples were analysed by UHPLC-MS to acquire non-targeted metabolomics data. The study included samples from 57 adolescents and 33 adults. Overall, 12 985 metabolic features were tested for an association with APOC3 genotype. RESULTS 161 uniquely annotated metabolites were found to be associated with rs138326449(APOC3). The highest proportion of associated metabolites belonged to the acyl-acyl glycerophospholipid and triacylglyceride metabolite classes. In addition to the anticipated (on-target) reduction of metabolites in the triacylglyceride and related classes, carriers of the rare variant exhibited previously unreported increases in levels of a number of metabolites from the acyl-alkyl glycerophospholipid class. CONCLUSION Overall, our results suggest that therapies targeting apoC-III may potentially achieve a broad shift in lipid profile that favours better metabolic health.
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Affiliation(s)
- Laura J Corbin
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - David A Hughes
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - Andrew J Chetwynd
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Amy E Taylor
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, BS8 2BN, UK
| | - Andrew D Southam
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Andris Jankevics
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Ralf J M Weber
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Alix Groom
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - Warwick B Dunn
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- Institute of Metabolism and Systems Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit at University of Bristol, Bristol, BS8 2BN, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK.
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29
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McGregor TL, Hunt KA, Yee E, Mason D, Nioi P, Ticau S, Pelosi M, Loken PR, Finer S, Lawlor DA, Fauman EB, Huang QQ, Griffiths CJ, MacArthur DG, Trembath RC, Oglesbee D, Lieske JC, Erbe DV, Wright J, van Heel DA. Characterising a healthy adult with a rare HAO1 knockout to support a therapeutic strategy for primary hyperoxaluria. eLife 2020; 9:e54363. [PMID: 32207686 PMCID: PMC7108859 DOI: 10.7554/elife.54363] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Accepted: 03/23/2020] [Indexed: 11/13/2022] Open
Abstract
By sequencing autozygous human populations, we identified a healthy adult woman with lifelong complete knockout of HAO1 (expected ~1 in 30 million outbred people). HAO1 (glycolate oxidase) silencing is the mechanism of lumasiran, an investigational RNA interference therapeutic for primary hyperoxaluria type 1. Her plasma glycolate levels were 12 times, and urinary glycolate 6 times, the upper limit of normal observed in healthy reference individuals (n = 67). Plasma metabolomics and lipidomics (1871 biochemicals) revealed 18 markedly elevated biochemicals (>5 sd outliers versus n = 25 controls) suggesting additional HAO1 effects. Comparison with lumasiran preclinical and clinical trial data suggested she has <2% residual glycolate oxidase activity. Cell line p.Leu333SerfsTer4 expression showed markedly reduced HAO1 protein levels and cellular protein mis-localisation. In this woman, lifelong HAO1 knockout is safe and without clinical phenotype, de-risking a therapeutic approach and informing therapeutic mechanisms. Unlocking evidence from the diversity of human genetic variation can facilitate drug development.
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Affiliation(s)
| | - Karen A Hunt
- Blizard Institute and Institute for Population Health Sciences, Barts and The London School of Medicine and Dentistry, Queen Mary University of LondonLondonUnited Kingdom
| | - Elaine Yee
- Alnylam PharmaceuticalsCambridgeUnited States
| | - Dan Mason
- Bradford Institute for Health Research, Bradford Teaching Hospitals National Health Service (NHS) Foundation TrustBradfordUnited Kingdom
| | - Paul Nioi
- Alnylam PharmaceuticalsCambridgeUnited States
| | | | | | - Perry R Loken
- Mayo Clinic, Division of Nephrology and HypertensionRochesterUnited States
| | - Sarah Finer
- Blizard Institute and Institute for Population Health Sciences, Barts and The London School of Medicine and Dentistry, Queen Mary University of LondonLondonUnited Kingdom
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield GroveBristolUnited Kingdom
- Population Health Science, Bristol Medical School, Bristol UniversityBristolUnited Kingdom
- Bristol NIHR Biomedical Research CentreBristolUnited Kingdom
| | - Eric B Fauman
- Internal Medicine Research Unit, Pfizer Worldwide Research, Development and MedicalCambridgeUnited States
| | | | - Christopher J Griffiths
- Blizard Institute and Institute for Population Health Sciences, Barts and The London School of Medicine and Dentistry, Queen Mary University of LondonLondonUnited Kingdom
| | - Daniel G MacArthur
- Analytic and Translational Genetics Unit, Massachusetts General HospitalBostonUnited States
- Program in Medical and Population Genetics, Broad Institute of MIT and HarvardCambridgeUnited States
| | - Richard C Trembath
- School of Basic and Medical Biosciences, Faculty of Life Sciences and Medicine, King’s College LondonLondonUnited Kingdom
| | - Devin Oglesbee
- Mayo Clinic, Division of Nephrology and HypertensionRochesterUnited States
| | - John C Lieske
- Mayo Clinic, Division of Nephrology and HypertensionRochesterUnited States
| | | | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals National Health Service (NHS) Foundation TrustBradfordUnited Kingdom
| | - David A van Heel
- Blizard Institute and Institute for Population Health Sciences, Barts and The London School of Medicine and Dentistry, Queen Mary University of LondonLondonUnited Kingdom
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30
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Finer S, Martin HC, Khan A, Hunt KA, MacLaughlin B, Ahmed Z, Ashcroft R, Durham C, MacArthur DG, McCarthy MI, Robson J, Trivedi B, Griffiths C, Wright J, Trembath RC, van Heel DA. Cohort Profile: East London Genes & Health (ELGH), a community-based population genomics and health study in British Bangladeshi and British Pakistani people. Int J Epidemiol 2020; 49:20-21i. [PMID: 31504546 PMCID: PMC7124496 DOI: 10.1093/ije/dyz174] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/05/2019] [Indexed: 11/12/2022] Open
Affiliation(s)
- Sarah Finer
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Hilary C Martin
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Ahsan Khan
- London Borough of Waltham Forest, Waltham Forest Town Hall, Walthamstow, UK
| | - Karen A Hunt
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Beverley MacLaughlin
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Zaheer Ahmed
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | | | | | - Daniel G MacArthur
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - John Robson
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Bhavi Trivedi
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Chris Griffiths
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals National Health Service (NHS) Foundation Trust, Bradford, UK
| | - Richard C Trembath
- School of Basic and Medical Biosciences, Faculty of Life Sciences and Medicine, King’s College London, London, UK
| | - David A van Heel
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
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31
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Zeggini E, Gloyn AL, Barton AC, Wain LV. Translational genomics and precision medicine: Moving from the lab to the clinic. Science 2019; 365:1409-1413. [PMID: 31604268 DOI: 10.1126/science.aax4588] [Citation(s) in RCA: 94] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Translational genomics aims to improve human health by building on discoveries made through genetics research and applying them in the clinical setting. This progress has been made possible by technological advances in genomics and analytics and by the digital revolution. Such advances should enable the development of prognostic markers, tailored interventions, and the design of prophylactic preventive approaches. We are at the cusp of predicting disease risk for some disorders by means of polygenic risk scores integrated with classical epidemiological risk factors. This should lead to better risk stratification and clinical decision-making. A deeper understanding of the link between genome-wide sequence and association with well-characterized phenotypes will empower the development of biomarkers to aid diagnosis, inform disease progression trajectories, and allow better targeting of treatments to those patients most likely to respond.
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Affiliation(s)
- Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
| | - Anna L Gloyn
- Oxford Centre for Diabetes Endocrinology and Metabolism, Oxford University, Oxford, UK.,Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.,Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Anne C Barton
- Versus Arthritis Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK.,NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester, UK
| | - Louise V Wain
- Department of Health Sciences, University of Leicester, Leicester, UK.,National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
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32
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Abstract
PURPOSE OF REVIEW Genome-wide association studies have delineated the genetic architecture of type 2 diabetes. While functional studies to identify target transcripts are ongoing, new genetic knowledge can be translated directly to health applications. The review covers several translation directions but focuses on genomic polygenic scores for screening and prevention. RECENT FINDINGS Over 400 genomic variants associated with T2D and its related quantitative traits are now known. Genetic scores comprising dozens to millions of associated variants can predict incident T2D. However, measurement of body mass index is more efficient than genetic scores to detect T2D risk groups, and knowledge of T2D genetic risk alone seems insufficient to improve health. Genetically determined metabolic sub-phenotypes can be identified by clustering variants associated with physiological axes like insulin resistance. Genetic sub-phenotyping may be a way forward to identify specific individual phenotypes for prevention and treatment. Genomic polygenic scores for T2D can predict incident diabetes but may not be useful to improve health overall. Genetic detection of T2D sub-phenotypes could be useful to personalize screening and care.
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Affiliation(s)
- James B Meigs
- Harvard Medical School, Boston, USA.
- Division of General Internal Medicine, Massachusetts General Hospital, 100 Cambridge St 16th Floor, Boston, MA, 02114, USA.
- MGH Division of Clinical Research Clinical Effectiveness Research Unit, Boston, USA.
- Broad Institute, Cambridge, USA.
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33
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John C, Reeve NF, Free RC, Williams AT, Ntalla I, Farmaki AE, Bethea J, Barton LM, Shrine N, Batini C, Packer R, Terry S, Hargadon B, Wang Q, Melbourne CA, Adams EL, Bee CE, Harrington K, Miola J, Brunskill NJ, Brightling CE, Barwell J, Wallace SE, Hsu R, Shepherd DJ, Hollox EJ, Wain LV, Tobin MD. Cohort Profile: Extended Cohort for E-health, Environment and DNA (EXCEED). Int J Epidemiol 2019; 48:678-679j. [PMID: 31062032 PMCID: PMC6659362 DOI: 10.1093/ije/dyz073] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/26/2019] [Indexed: 12/22/2022] Open
Affiliation(s)
- Catherine John
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Nicola F Reeve
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Robert C Free
- NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
- Department of Respiratory Sciences, University of Leicester, Leicester, UK
| | | | - Ioanna Ntalla
- Department of Health Sciences, University of Leicester, Leicester, UK
- Department of Clinical Pharmacology, William Harvey Research Institute, Barts & The London Medical School, Queen Mary University of London, Charterhouse Square, London, UK
| | - Aliki-Eleni Farmaki
- Department of Health Sciences, University of Leicester, Leicester, UK
- Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, University College London, London, UK
| | - Jane Bethea
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Linda M Barton
- Department of Haematology, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Nick Shrine
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Chiara Batini
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Richard Packer
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Sarah Terry
- NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Beverley Hargadon
- NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Qingning Wang
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Carl A Melbourne
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Emma L Adams
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Catherine E Bee
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Kyla Harrington
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - José Miola
- Leicester Law School, University of Leicester, Leicester, UK
| | - Nigel J Brunskill
- Department of Cardiovascular Sciences University of Leicester, Leicester, UK
| | - Christopher E Brightling
- NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
- Department of Respiratory Sciences, University of Leicester, Leicester, UK
| | - Julian Barwell
- Department of Genetics and Genome Biology, University of Leicester, Leicester, UK
| | - Susan E Wallace
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Ron Hsu
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - David J Shepherd
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Edward J Hollox
- Department of Genetics and Genome Biology, University of Leicester, Leicester, UK
| | - Louise V Wain
- Department of Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Martin D Tobin
- Department of Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
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34
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Jallow MW, Campino S, Prentice AM, Cerami C. A recall-by-genotype study on polymorphisms in the TMPRSS6 gene and oral iron absorption: a study protocol. F1000Res 2019. [DOI: 10.12688/f1000research.19080.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Background: Oral iron supplementation is commonly used to treat and prevent anaemia. The transmembrane protease serine 6 gene (TMPRSS6), which encodes matriptase 2, is a negative regulator of hepcidin, the key controller of iron homeostasis. Genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) in the TMPRSS6 gene that are associated with an increased risk of iron-deficiency anaemia. We will investigate the in vivo effects of three previously reported TMPRSS6 variants (rs855791, rs4820268 and rs2235321) on oral iron absorption in non-anaemic volunteers in The Gambia. Methods: A recall-by-genotype study design will be employed. Pre-genotyped participants will be recruited from the West African BioResouce (WABR), which currently contains over 3000 genotyped individuals. Male and female volunteers will be selected based on polymorphisms (rs855791, rs4820268 and rs2235321) in the TMPRSS6 gene in the Gambian population. The effects of a single variant allele at one SNP and the additive effect of two or three variant alleles from either two or all three SNPs will be investigated. Study participants will be given a single oral dose of 400mg ferrous sulfate, and blood samples will be collected at baseline, two hours and five hours post supplementation. Differences in iron absorption between genotype groups will be assessed by measuring the increase in serum iron concentration at five hours post iron ingestion. Discussion: This study will increase understanding of the role of genetic variations in TMPRSS6 on oral iron absorption in subjects of West African origin. This will test for the biological basis for the association of each of the three TMPRSS6 variants with iron absorption. This may help in guiding future iron intervention strategies, particularly in populations with a high frequency of these SNPs and a high frequency of anaemia. Study registration: ClinicalTrials.gov NCT03341338 14/11/17.
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35
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Lancaster TM, Dimitriadis SL, Tansey KE, Perry G, Ihssen N, Jones DK, Singh KD, Holmans P, Pocklington A, Davey Smith G, Zammit S, Hall J, O’Donovan MC, Owen MJ, Linden DE. Structural and Functional Neuroimaging of Polygenic Risk for Schizophrenia: A Recall-by-Genotype-Based Approach. Schizophr Bull 2019; 45:405-414. [PMID: 29608775 PMCID: PMC6403064 DOI: 10.1093/schbul/sby037] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Risk profile scores (RPS) derived from genome-wide association studies (GWAS) explain a considerable amount of susceptibility for schizophrenia (SCZ). However, little is known about how common genetic risk factors for SCZ influence the structure and function of the human brain, largely due to the constraints of imaging sample sizes. In the current study, we use a novel recall-by-genotype (RbG) methodological approach, where we sample young adults from a population cohort (Avon Longitudinal Study of Parents and Children: N genotyped = 8365) based on their SCZ-RPS. We compared 197 healthy individuals at extremes of low (N = 99) or high (N = 98) SCZ-RPS with behavioral tests, and structural and functional magnetic resonance imaging (fMRI). We first provide methodological details that will inform the design of future RbG studies for common SCZ genetic risk. We further provide an between group analysis of the RbG individuals (low vs high SCZ-RPS) who underwent structural neuroimaging data (T1-weighted scans) and fMRI data during a reversal learning task. While we found little evidence for morphometric differences between the low and high SCZ-RPS groups, we observed an impact of SCZ-RPS on blood oxygen level-dependent (BOLD) signal during reward processing in the ventral striatum (PFWE-VS-CORRECTED = .037), a previously investigated broader reward-related network (PFWE-ROIS-CORRECTED = .008), and across the whole brain (PFWE-WHOLE-BRAIN-CORRECTED = .013). We also describe the study strategy and discuss specific challenges of RbG for SCZ risk (such as SCZ-RPS related homoscedasticity). This study will help to elucidate the behavioral and imaging phenotypes that are associated with SCZ genetic risk.
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Affiliation(s)
- Thomas M Lancaster
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, UK
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, UK
| | - Stavros L Dimitriadis
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, UK
| | - Katherine E Tansey
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, UK
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
| | - Gavin Perry
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | | | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Krish D Singh
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Peter Holmans
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, UK
| | - Andrew Pocklington
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Stan Zammit
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, UK
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jeremy Hall
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, UK
| | - Michael C O’Donovan
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, UK
| | - Michael J Owen
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, UK
| | - David E Linden
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, UK
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, UK
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Lewis KL, Facio FM, Berrios CD. Using the diffusion of innovations model to guide participant engagement in the genomics era. J Genet Couns 2019; 28:419-427. [PMID: 30653790 DOI: 10.1002/jgc4.1090] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Revised: 12/06/2018] [Accepted: 12/09/2018] [Indexed: 12/12/2022]
Abstract
Exome and genome sequencing (EGS) are increasingly the genetic testing modalities of choice among researchers owing to their ready availability, low cost, and large data output. Recruitment of larger, more diverse cohorts into long-term studies with extensive data collection is fundamental to the success of EGS research and to the widespread benefit of genomic medicine to various populations. Effective engagement will be critical to meeting this demand. The Diffusion of Innovation (DOI) model provides a framework for how new technologies are adopted in communities, including antecedents of an individual's decision to adopt the technology, how the technology's attributes influence its acceptability, the predictors of sustained use of that technology, and its diffusion through society. We apply the DOI model to frame participant engagement in EGS research and to guide the proposal of potential strategies that aim to overcome forecasted challenges. Finally, we suggest a variety of ways genetic counselors can apply their skills and training to the development and implementation of these strategies.
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Affiliation(s)
- Katie L Lewis
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, Bethesda, Maryland
| | - Flavia M Facio
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, Bethesda, Maryland
| | - Courtney D Berrios
- Center for Pediatric Genomic Medicine, Children's Mercy Kansas City, Kansas City, Missouri
- School of Medicine, University of Missouri Kansas City, Kansas City, Missouri
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Traylor M, Tozer DJ, Croall ID, Lisiecka-Ford DM, Olorunda AO, Boncoraglio G, Dichgans M, Lemmens R, Rosand J, Rost NS, Rothwell PM, Sudlow CLM, Thijs V, Rutten-Jacobs L, Markus HS. Genetic variation in PLEKHG1 is associated with white matter hyperintensities (n = 11,226). Neurology 2019; 92:e749-e757. [PMID: 30659137 PMCID: PMC6396967 DOI: 10.1212/wnl.0000000000006952] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Accepted: 10/15/2018] [Indexed: 12/11/2022] Open
Abstract
OBJECTIVE To identify novel genetic associations with white matter hyperintensities (WMH). METHODS We performed a genome-wide association meta-analysis of WMH volumes in 11,226 individuals, including 8,429 population-based individuals from UK Biobank and 2,797 stroke patients. Replication of novel loci was performed in an independent dataset of 1,202 individuals. In all studies, WMH were quantified using validated automated or semi-automated methods. Imputation was to either the Haplotype Reference Consortium or 1,000 Genomes Phase 3 panels. RESULTS We identified a locus at genome-wide significance in an intron of PLEKHG1 (rs275350, β [SE] = 0.071 [0.013]; p = 1.6 × 10-8), a Rho guanine nucleotide exchange factor that is involved in reorientation of cells in the vascular endothelium. This association was validated in an independent sample (overall p value, 2.4 × 10-9). The same single nucleotide polymorphism was associated with all ischemic stroke (odds ratio [OR] [95% confidence interval (CI)] 1.07 [1.03-1.12], p = 0.00051), most strongly with the small vessel subtype (OR [95% CI] 1.09 [1.00-1.19], p = 0.044). Previous associations at 17q25 and 2p16 reached genome-wide significance in this analysis (rs3744020; β [SE] = 0.106 [0.016]; p = 1.2 × 10-11 and rs7596872; β [SE] = 0.143 [0.021]; p = 3.4 × 10-12). All identified associations with WMH to date explained 1.16% of the trait variance in UK Biobank, equivalent to 6.4% of the narrow-sense heritability. CONCLUSIONS Genetic variation in PLEKHG1 is associated with WMH and ischemic stroke, most strongly with the small vessel subtype, suggesting it acts by promoting small vessel arteriopathy.
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Affiliation(s)
- Matthew Traylor
- From the Department of Clinical Neurosciences, Stroke Research Group (M.T., D.J.T., I.D.C., D.M.L.F., A.O.O., L.R.-J., H.S.M.), University of Cambridge, UK; Department of Cerebrovascular Diseases (G.B.), Fondazione IRCCS Istituto Neurologico "Carlo Besta," Milan, Italy; Institute for Stroke and Dementia Research (M.D.), Klinikum der Universität München, Ludwig-Maximilians-Universität München, Munich; German Center for Neurodegenerative Diseases (DZNE) and Munich Cluster for Systems Neurology (SyNergy) (M.D.), Germany; Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND) (R.L.), KU Leuven-University of Leuven; Department of Neurology (R.L.), University Hospitals Leuven; Laboratory of Neurobiology (R.L.), VIB Center for Brain and Disease Research, Leuven, Belgium; Center for Human Genetic Research (J.R.) and Division of Neurocritical Care and Emergency Neurology (J.R.) and J. Philip Kistler Stroke Research Center (J.R., N.S.R.), Department of Neurology, Massachusetts General Hospital, Boston; Nuffield Department of Clinical Neurosciences (Clinical Neurology), Stroke Prevention Research Unit (P.M.R.), University of Oxford; Centre for Clinical Brain Sciences and Institute for Genetics and Molecular Medicine (C.L.M.S.), University of Edinburgh, UK; Stroke Division, Florey Institute of Neuroscience and Mental Health (V.T.), University of Melbourne; and Department of Neurology (V.T.), Austin Health, Heidelberg, Victoria, Australia.
| | - Daniel J Tozer
- From the Department of Clinical Neurosciences, Stroke Research Group (M.T., D.J.T., I.D.C., D.M.L.F., A.O.O., L.R.-J., H.S.M.), University of Cambridge, UK; Department of Cerebrovascular Diseases (G.B.), Fondazione IRCCS Istituto Neurologico "Carlo Besta," Milan, Italy; Institute for Stroke and Dementia Research (M.D.), Klinikum der Universität München, Ludwig-Maximilians-Universität München, Munich; German Center for Neurodegenerative Diseases (DZNE) and Munich Cluster for Systems Neurology (SyNergy) (M.D.), Germany; Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND) (R.L.), KU Leuven-University of Leuven; Department of Neurology (R.L.), University Hospitals Leuven; Laboratory of Neurobiology (R.L.), VIB Center for Brain and Disease Research, Leuven, Belgium; Center for Human Genetic Research (J.R.) and Division of Neurocritical Care and Emergency Neurology (J.R.) and J. Philip Kistler Stroke Research Center (J.R., N.S.R.), Department of Neurology, Massachusetts General Hospital, Boston; Nuffield Department of Clinical Neurosciences (Clinical Neurology), Stroke Prevention Research Unit (P.M.R.), University of Oxford; Centre for Clinical Brain Sciences and Institute for Genetics and Molecular Medicine (C.L.M.S.), University of Edinburgh, UK; Stroke Division, Florey Institute of Neuroscience and Mental Health (V.T.), University of Melbourne; and Department of Neurology (V.T.), Austin Health, Heidelberg, Victoria, Australia
| | - Iain D Croall
- From the Department of Clinical Neurosciences, Stroke Research Group (M.T., D.J.T., I.D.C., D.M.L.F., A.O.O., L.R.-J., H.S.M.), University of Cambridge, UK; Department of Cerebrovascular Diseases (G.B.), Fondazione IRCCS Istituto Neurologico "Carlo Besta," Milan, Italy; Institute for Stroke and Dementia Research (M.D.), Klinikum der Universität München, Ludwig-Maximilians-Universität München, Munich; German Center for Neurodegenerative Diseases (DZNE) and Munich Cluster for Systems Neurology (SyNergy) (M.D.), Germany; Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND) (R.L.), KU Leuven-University of Leuven; Department of Neurology (R.L.), University Hospitals Leuven; Laboratory of Neurobiology (R.L.), VIB Center for Brain and Disease Research, Leuven, Belgium; Center for Human Genetic Research (J.R.) and Division of Neurocritical Care and Emergency Neurology (J.R.) and J. Philip Kistler Stroke Research Center (J.R., N.S.R.), Department of Neurology, Massachusetts General Hospital, Boston; Nuffield Department of Clinical Neurosciences (Clinical Neurology), Stroke Prevention Research Unit (P.M.R.), University of Oxford; Centre for Clinical Brain Sciences and Institute for Genetics and Molecular Medicine (C.L.M.S.), University of Edinburgh, UK; Stroke Division, Florey Institute of Neuroscience and Mental Health (V.T.), University of Melbourne; and Department of Neurology (V.T.), Austin Health, Heidelberg, Victoria, Australia
| | - Danuta M Lisiecka-Ford
- From the Department of Clinical Neurosciences, Stroke Research Group (M.T., D.J.T., I.D.C., D.M.L.F., A.O.O., L.R.-J., H.S.M.), University of Cambridge, UK; Department of Cerebrovascular Diseases (G.B.), Fondazione IRCCS Istituto Neurologico "Carlo Besta," Milan, Italy; Institute for Stroke and Dementia Research (M.D.), Klinikum der Universität München, Ludwig-Maximilians-Universität München, Munich; German Center for Neurodegenerative Diseases (DZNE) and Munich Cluster for Systems Neurology (SyNergy) (M.D.), Germany; Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND) (R.L.), KU Leuven-University of Leuven; Department of Neurology (R.L.), University Hospitals Leuven; Laboratory of Neurobiology (R.L.), VIB Center for Brain and Disease Research, Leuven, Belgium; Center for Human Genetic Research (J.R.) and Division of Neurocritical Care and Emergency Neurology (J.R.) and J. Philip Kistler Stroke Research Center (J.R., N.S.R.), Department of Neurology, Massachusetts General Hospital, Boston; Nuffield Department of Clinical Neurosciences (Clinical Neurology), Stroke Prevention Research Unit (P.M.R.), University of Oxford; Centre for Clinical Brain Sciences and Institute for Genetics and Molecular Medicine (C.L.M.S.), University of Edinburgh, UK; Stroke Division, Florey Institute of Neuroscience and Mental Health (V.T.), University of Melbourne; and Department of Neurology (V.T.), Austin Health, Heidelberg, Victoria, Australia
| | - Abiodun Olubunmi Olorunda
- From the Department of Clinical Neurosciences, Stroke Research Group (M.T., D.J.T., I.D.C., D.M.L.F., A.O.O., L.R.-J., H.S.M.), University of Cambridge, UK; Department of Cerebrovascular Diseases (G.B.), Fondazione IRCCS Istituto Neurologico "Carlo Besta," Milan, Italy; Institute for Stroke and Dementia Research (M.D.), Klinikum der Universität München, Ludwig-Maximilians-Universität München, Munich; German Center for Neurodegenerative Diseases (DZNE) and Munich Cluster for Systems Neurology (SyNergy) (M.D.), Germany; Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND) (R.L.), KU Leuven-University of Leuven; Department of Neurology (R.L.), University Hospitals Leuven; Laboratory of Neurobiology (R.L.), VIB Center for Brain and Disease Research, Leuven, Belgium; Center for Human Genetic Research (J.R.) and Division of Neurocritical Care and Emergency Neurology (J.R.) and J. Philip Kistler Stroke Research Center (J.R., N.S.R.), Department of Neurology, Massachusetts General Hospital, Boston; Nuffield Department of Clinical Neurosciences (Clinical Neurology), Stroke Prevention Research Unit (P.M.R.), University of Oxford; Centre for Clinical Brain Sciences and Institute for Genetics and Molecular Medicine (C.L.M.S.), University of Edinburgh, UK; Stroke Division, Florey Institute of Neuroscience and Mental Health (V.T.), University of Melbourne; and Department of Neurology (V.T.), Austin Health, Heidelberg, Victoria, Australia
| | - Giorgio Boncoraglio
- From the Department of Clinical Neurosciences, Stroke Research Group (M.T., D.J.T., I.D.C., D.M.L.F., A.O.O., L.R.-J., H.S.M.), University of Cambridge, UK; Department of Cerebrovascular Diseases (G.B.), Fondazione IRCCS Istituto Neurologico "Carlo Besta," Milan, Italy; Institute for Stroke and Dementia Research (M.D.), Klinikum der Universität München, Ludwig-Maximilians-Universität München, Munich; German Center for Neurodegenerative Diseases (DZNE) and Munich Cluster for Systems Neurology (SyNergy) (M.D.), Germany; Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND) (R.L.), KU Leuven-University of Leuven; Department of Neurology (R.L.), University Hospitals Leuven; Laboratory of Neurobiology (R.L.), VIB Center for Brain and Disease Research, Leuven, Belgium; Center for Human Genetic Research (J.R.) and Division of Neurocritical Care and Emergency Neurology (J.R.) and J. Philip Kistler Stroke Research Center (J.R., N.S.R.), Department of Neurology, Massachusetts General Hospital, Boston; Nuffield Department of Clinical Neurosciences (Clinical Neurology), Stroke Prevention Research Unit (P.M.R.), University of Oxford; Centre for Clinical Brain Sciences and Institute for Genetics and Molecular Medicine (C.L.M.S.), University of Edinburgh, UK; Stroke Division, Florey Institute of Neuroscience and Mental Health (V.T.), University of Melbourne; and Department of Neurology (V.T.), Austin Health, Heidelberg, Victoria, Australia
| | - Martin Dichgans
- From the Department of Clinical Neurosciences, Stroke Research Group (M.T., D.J.T., I.D.C., D.M.L.F., A.O.O., L.R.-J., H.S.M.), University of Cambridge, UK; Department of Cerebrovascular Diseases (G.B.), Fondazione IRCCS Istituto Neurologico "Carlo Besta," Milan, Italy; Institute for Stroke and Dementia Research (M.D.), Klinikum der Universität München, Ludwig-Maximilians-Universität München, Munich; German Center for Neurodegenerative Diseases (DZNE) and Munich Cluster for Systems Neurology (SyNergy) (M.D.), Germany; Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND) (R.L.), KU Leuven-University of Leuven; Department of Neurology (R.L.), University Hospitals Leuven; Laboratory of Neurobiology (R.L.), VIB Center for Brain and Disease Research, Leuven, Belgium; Center for Human Genetic Research (J.R.) and Division of Neurocritical Care and Emergency Neurology (J.R.) and J. Philip Kistler Stroke Research Center (J.R., N.S.R.), Department of Neurology, Massachusetts General Hospital, Boston; Nuffield Department of Clinical Neurosciences (Clinical Neurology), Stroke Prevention Research Unit (P.M.R.), University of Oxford; Centre for Clinical Brain Sciences and Institute for Genetics and Molecular Medicine (C.L.M.S.), University of Edinburgh, UK; Stroke Division, Florey Institute of Neuroscience and Mental Health (V.T.), University of Melbourne; and Department of Neurology (V.T.), Austin Health, Heidelberg, Victoria, Australia
| | - Robin Lemmens
- From the Department of Clinical Neurosciences, Stroke Research Group (M.T., D.J.T., I.D.C., D.M.L.F., A.O.O., L.R.-J., H.S.M.), University of Cambridge, UK; Department of Cerebrovascular Diseases (G.B.), Fondazione IRCCS Istituto Neurologico "Carlo Besta," Milan, Italy; Institute for Stroke and Dementia Research (M.D.), Klinikum der Universität München, Ludwig-Maximilians-Universität München, Munich; German Center for Neurodegenerative Diseases (DZNE) and Munich Cluster for Systems Neurology (SyNergy) (M.D.), Germany; Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND) (R.L.), KU Leuven-University of Leuven; Department of Neurology (R.L.), University Hospitals Leuven; Laboratory of Neurobiology (R.L.), VIB Center for Brain and Disease Research, Leuven, Belgium; Center for Human Genetic Research (J.R.) and Division of Neurocritical Care and Emergency Neurology (J.R.) and J. Philip Kistler Stroke Research Center (J.R., N.S.R.), Department of Neurology, Massachusetts General Hospital, Boston; Nuffield Department of Clinical Neurosciences (Clinical Neurology), Stroke Prevention Research Unit (P.M.R.), University of Oxford; Centre for Clinical Brain Sciences and Institute for Genetics and Molecular Medicine (C.L.M.S.), University of Edinburgh, UK; Stroke Division, Florey Institute of Neuroscience and Mental Health (V.T.), University of Melbourne; and Department of Neurology (V.T.), Austin Health, Heidelberg, Victoria, Australia
| | - Jonathan Rosand
- From the Department of Clinical Neurosciences, Stroke Research Group (M.T., D.J.T., I.D.C., D.M.L.F., A.O.O., L.R.-J., H.S.M.), University of Cambridge, UK; Department of Cerebrovascular Diseases (G.B.), Fondazione IRCCS Istituto Neurologico "Carlo Besta," Milan, Italy; Institute for Stroke and Dementia Research (M.D.), Klinikum der Universität München, Ludwig-Maximilians-Universität München, Munich; German Center for Neurodegenerative Diseases (DZNE) and Munich Cluster for Systems Neurology (SyNergy) (M.D.), Germany; Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND) (R.L.), KU Leuven-University of Leuven; Department of Neurology (R.L.), University Hospitals Leuven; Laboratory of Neurobiology (R.L.), VIB Center for Brain and Disease Research, Leuven, Belgium; Center for Human Genetic Research (J.R.) and Division of Neurocritical Care and Emergency Neurology (J.R.) and J. Philip Kistler Stroke Research Center (J.R., N.S.R.), Department of Neurology, Massachusetts General Hospital, Boston; Nuffield Department of Clinical Neurosciences (Clinical Neurology), Stroke Prevention Research Unit (P.M.R.), University of Oxford; Centre for Clinical Brain Sciences and Institute for Genetics and Molecular Medicine (C.L.M.S.), University of Edinburgh, UK; Stroke Division, Florey Institute of Neuroscience and Mental Health (V.T.), University of Melbourne; and Department of Neurology (V.T.), Austin Health, Heidelberg, Victoria, Australia
| | - Natalia S Rost
- From the Department of Clinical Neurosciences, Stroke Research Group (M.T., D.J.T., I.D.C., D.M.L.F., A.O.O., L.R.-J., H.S.M.), University of Cambridge, UK; Department of Cerebrovascular Diseases (G.B.), Fondazione IRCCS Istituto Neurologico "Carlo Besta," Milan, Italy; Institute for Stroke and Dementia Research (M.D.), Klinikum der Universität München, Ludwig-Maximilians-Universität München, Munich; German Center for Neurodegenerative Diseases (DZNE) and Munich Cluster for Systems Neurology (SyNergy) (M.D.), Germany; Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND) (R.L.), KU Leuven-University of Leuven; Department of Neurology (R.L.), University Hospitals Leuven; Laboratory of Neurobiology (R.L.), VIB Center for Brain and Disease Research, Leuven, Belgium; Center for Human Genetic Research (J.R.) and Division of Neurocritical Care and Emergency Neurology (J.R.) and J. Philip Kistler Stroke Research Center (J.R., N.S.R.), Department of Neurology, Massachusetts General Hospital, Boston; Nuffield Department of Clinical Neurosciences (Clinical Neurology), Stroke Prevention Research Unit (P.M.R.), University of Oxford; Centre for Clinical Brain Sciences and Institute for Genetics and Molecular Medicine (C.L.M.S.), University of Edinburgh, UK; Stroke Division, Florey Institute of Neuroscience and Mental Health (V.T.), University of Melbourne; and Department of Neurology (V.T.), Austin Health, Heidelberg, Victoria, Australia
| | - Peter M Rothwell
- From the Department of Clinical Neurosciences, Stroke Research Group (M.T., D.J.T., I.D.C., D.M.L.F., A.O.O., L.R.-J., H.S.M.), University of Cambridge, UK; Department of Cerebrovascular Diseases (G.B.), Fondazione IRCCS Istituto Neurologico "Carlo Besta," Milan, Italy; Institute for Stroke and Dementia Research (M.D.), Klinikum der Universität München, Ludwig-Maximilians-Universität München, Munich; German Center for Neurodegenerative Diseases (DZNE) and Munich Cluster for Systems Neurology (SyNergy) (M.D.), Germany; Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND) (R.L.), KU Leuven-University of Leuven; Department of Neurology (R.L.), University Hospitals Leuven; Laboratory of Neurobiology (R.L.), VIB Center for Brain and Disease Research, Leuven, Belgium; Center for Human Genetic Research (J.R.) and Division of Neurocritical Care and Emergency Neurology (J.R.) and J. Philip Kistler Stroke Research Center (J.R., N.S.R.), Department of Neurology, Massachusetts General Hospital, Boston; Nuffield Department of Clinical Neurosciences (Clinical Neurology), Stroke Prevention Research Unit (P.M.R.), University of Oxford; Centre for Clinical Brain Sciences and Institute for Genetics and Molecular Medicine (C.L.M.S.), University of Edinburgh, UK; Stroke Division, Florey Institute of Neuroscience and Mental Health (V.T.), University of Melbourne; and Department of Neurology (V.T.), Austin Health, Heidelberg, Victoria, Australia
| | - Cathie L M Sudlow
- From the Department of Clinical Neurosciences, Stroke Research Group (M.T., D.J.T., I.D.C., D.M.L.F., A.O.O., L.R.-J., H.S.M.), University of Cambridge, UK; Department of Cerebrovascular Diseases (G.B.), Fondazione IRCCS Istituto Neurologico "Carlo Besta," Milan, Italy; Institute for Stroke and Dementia Research (M.D.), Klinikum der Universität München, Ludwig-Maximilians-Universität München, Munich; German Center for Neurodegenerative Diseases (DZNE) and Munich Cluster for Systems Neurology (SyNergy) (M.D.), Germany; Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND) (R.L.), KU Leuven-University of Leuven; Department of Neurology (R.L.), University Hospitals Leuven; Laboratory of Neurobiology (R.L.), VIB Center for Brain and Disease Research, Leuven, Belgium; Center for Human Genetic Research (J.R.) and Division of Neurocritical Care and Emergency Neurology (J.R.) and J. Philip Kistler Stroke Research Center (J.R., N.S.R.), Department of Neurology, Massachusetts General Hospital, Boston; Nuffield Department of Clinical Neurosciences (Clinical Neurology), Stroke Prevention Research Unit (P.M.R.), University of Oxford; Centre for Clinical Brain Sciences and Institute for Genetics and Molecular Medicine (C.L.M.S.), University of Edinburgh, UK; Stroke Division, Florey Institute of Neuroscience and Mental Health (V.T.), University of Melbourne; and Department of Neurology (V.T.), Austin Health, Heidelberg, Victoria, Australia
| | - Vincent Thijs
- From the Department of Clinical Neurosciences, Stroke Research Group (M.T., D.J.T., I.D.C., D.M.L.F., A.O.O., L.R.-J., H.S.M.), University of Cambridge, UK; Department of Cerebrovascular Diseases (G.B.), Fondazione IRCCS Istituto Neurologico "Carlo Besta," Milan, Italy; Institute for Stroke and Dementia Research (M.D.), Klinikum der Universität München, Ludwig-Maximilians-Universität München, Munich; German Center for Neurodegenerative Diseases (DZNE) and Munich Cluster for Systems Neurology (SyNergy) (M.D.), Germany; Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND) (R.L.), KU Leuven-University of Leuven; Department of Neurology (R.L.), University Hospitals Leuven; Laboratory of Neurobiology (R.L.), VIB Center for Brain and Disease Research, Leuven, Belgium; Center for Human Genetic Research (J.R.) and Division of Neurocritical Care and Emergency Neurology (J.R.) and J. Philip Kistler Stroke Research Center (J.R., N.S.R.), Department of Neurology, Massachusetts General Hospital, Boston; Nuffield Department of Clinical Neurosciences (Clinical Neurology), Stroke Prevention Research Unit (P.M.R.), University of Oxford; Centre for Clinical Brain Sciences and Institute for Genetics and Molecular Medicine (C.L.M.S.), University of Edinburgh, UK; Stroke Division, Florey Institute of Neuroscience and Mental Health (V.T.), University of Melbourne; and Department of Neurology (V.T.), Austin Health, Heidelberg, Victoria, Australia
| | - Loes Rutten-Jacobs
- From the Department of Clinical Neurosciences, Stroke Research Group (M.T., D.J.T., I.D.C., D.M.L.F., A.O.O., L.R.-J., H.S.M.), University of Cambridge, UK; Department of Cerebrovascular Diseases (G.B.), Fondazione IRCCS Istituto Neurologico "Carlo Besta," Milan, Italy; Institute for Stroke and Dementia Research (M.D.), Klinikum der Universität München, Ludwig-Maximilians-Universität München, Munich; German Center for Neurodegenerative Diseases (DZNE) and Munich Cluster for Systems Neurology (SyNergy) (M.D.), Germany; Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND) (R.L.), KU Leuven-University of Leuven; Department of Neurology (R.L.), University Hospitals Leuven; Laboratory of Neurobiology (R.L.), VIB Center for Brain and Disease Research, Leuven, Belgium; Center for Human Genetic Research (J.R.) and Division of Neurocritical Care and Emergency Neurology (J.R.) and J. Philip Kistler Stroke Research Center (J.R., N.S.R.), Department of Neurology, Massachusetts General Hospital, Boston; Nuffield Department of Clinical Neurosciences (Clinical Neurology), Stroke Prevention Research Unit (P.M.R.), University of Oxford; Centre for Clinical Brain Sciences and Institute for Genetics and Molecular Medicine (C.L.M.S.), University of Edinburgh, UK; Stroke Division, Florey Institute of Neuroscience and Mental Health (V.T.), University of Melbourne; and Department of Neurology (V.T.), Austin Health, Heidelberg, Victoria, Australia
| | - Hugh S Markus
- From the Department of Clinical Neurosciences, Stroke Research Group (M.T., D.J.T., I.D.C., D.M.L.F., A.O.O., L.R.-J., H.S.M.), University of Cambridge, UK; Department of Cerebrovascular Diseases (G.B.), Fondazione IRCCS Istituto Neurologico "Carlo Besta," Milan, Italy; Institute for Stroke and Dementia Research (M.D.), Klinikum der Universität München, Ludwig-Maximilians-Universität München, Munich; German Center for Neurodegenerative Diseases (DZNE) and Munich Cluster for Systems Neurology (SyNergy) (M.D.), Germany; Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND) (R.L.), KU Leuven-University of Leuven; Department of Neurology (R.L.), University Hospitals Leuven; Laboratory of Neurobiology (R.L.), VIB Center for Brain and Disease Research, Leuven, Belgium; Center for Human Genetic Research (J.R.) and Division of Neurocritical Care and Emergency Neurology (J.R.) and J. Philip Kistler Stroke Research Center (J.R., N.S.R.), Department of Neurology, Massachusetts General Hospital, Boston; Nuffield Department of Clinical Neurosciences (Clinical Neurology), Stroke Prevention Research Unit (P.M.R.), University of Oxford; Centre for Clinical Brain Sciences and Institute for Genetics and Molecular Medicine (C.L.M.S.), University of Edinburgh, UK; Stroke Division, Florey Institute of Neuroscience and Mental Health (V.T.), University of Melbourne; and Department of Neurology (V.T.), Austin Health, Heidelberg, Victoria, Australia
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38
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Chiesa ST, Rapala A, Charakida M, Wade KH, Timpson NJ, Deanfield JE. The ‘ALSPAC in London’ dataset: adiposity, cardiometabolic risk profiles, and the emerging arterial phenotype in young adulthood. Wellcome Open Res 2018. [DOI: 10.12688/wellcomeopenres.14942.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Rising rates of adiposity in the young pose one of the greatest threats to future population burden of cardiovascular disease. Understanding the contribution of genetic and early-life influences to adiposity profiles in young adulthood – when the first signs of subclinical cardiovascular disease commonly appear – are vital if effective lifetime prevention strategies are to be developed. This data note documents the extensive range of genotypic and phenotypic data available from a London-based sub-study of the long-running Avon Longitudinal Study of Parents and Children (ALSPAC)—the ‘ALSPAC in London’ Study—in which extensive adipose and cardiovascular phenotyping was carried out in participants recruited based on a genetic predisposition to obesity.
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Wade KH, Chiesa ST, Hughes AD, Chaturvedi N, Charakida M, Rapala A, Muthurangu V, Khan T, Finer N, Sattar N, Howe LD, Fraser A, Lawlor DA, Davey Smith G, Deanfield JE, Timpson NJ. Assessing the causal role of body mass index on cardiovascular health in young adults: Mendelian randomization and recall-by-genotype analyses. Circulation 2018; 138:2187-2201. [PMID: 30524135 PMCID: PMC6250296 DOI: 10.1161/circulationaha.117.033278] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Accepted: 06/12/2018] [Indexed: 01/19/2023]
Abstract
Background Body mass index (BMI) has been suggested to be causally related to cardiovascular health in mid-to-late life, but this has not been explored systematically at younger ages - nor with detailed cardiovascular phenotyping. Recall-by-Genotype (RbG) is an approach that enables the collection of precise phenotypic measures in smaller studies, whilst maintaining statistical power and ability for causal inference. Methods In this study, we used a combination of conventional multivariable regression analysis, Mendelian randomization (MR) and sub-sample RbG methodologies to estimate the causal effect of BMI on gross-level and detailed cardiovascular health in healthy participants from the Avon Longitudinal Study of Parents and Children at age 17 (N=1420-3108 for different outcomes) and an independent sample from the same cohort (for RbG) study at age 21 (N=386-418). Results In both MR and RbG analyses, results suggested that higher BMI causes higher blood pressure (BP) and left ventricular mass index (LVMI) in young adults (e.g., difference in LVMI per kg/m2 using MR: 1.07g/m2.7; 95% CI: 0.62, 1.52; P=3.87x10-06 and per 3.58kg/m2 using RbG: 1.65g/m2.7 95% CI: 0.83, 2.47; P=0.0001). Additionally, RbG results suggested a causal role of higher BMI on higher stroke volume (SV: difference per 3.58kg/m2: 1.49ml/m2.04; 95% CI: 0.62, 2.35; P=0.001) and cardiac output (CO: difference per 3.58kg/m2: 0.11l/min/m1.83; 95% CI: 0.03, 0.19; P=0.01) but no strong evidence for a causal role on systemic vascular resistance or total arterial compliance. Neither analysis supported a causal role of higher BMI on heart rate. Conclusions Complementary MR and RbG causal methodologies, together with a range of sensitivity analyses, suggest that higher BMI is likely to cause worse cardiovascular health, specifically higher BP and LVMI, even in youth. Higher BMI also resulted in increased CO in the RbG study, which appeared to be solely driven by SV, as neither MR nor RbG analyses suggested a causal effect of BMI on heart rate. These consistent results support efforts to reduce BMI from a young age to prevent later adverse cardiovascular health and illustrate the potential for phenotypic resolution with maintained analytical power using RbG.
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Affiliation(s)
- Kaitlin H. Wade
- Medical Research Council Integrative Epidemiology Unit (K.H.W., L.D.H., A.F., D.A.L., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School, Faculty of Health Sciences, University of Bristol, UK (K.H.W., L.D.H., D.A.L., G.D.S., N.J.T.)
| | - Scott T. Chiesa
- Vascular Physiology Unit, Institute of Cardiovascular Science, University College London, UK (S.T.C, M.C., A.R., V.M., T.K., N.F., J.E.D.)
| | - Alun D. Hughes
- Cardiometabolic Phenotyping Group, Institute of Cardiovascular Science, University College London, UK (A.D.H., A.R., N.C.)
| | - Nish Chaturvedi
- Cardiometabolic Phenotyping Group, Institute of Cardiovascular Science, University College London, UK (A.D.H., A.R., N.C.)
| | - Marietta Charakida
- Vascular Physiology Unit, Institute of Cardiovascular Science, University College London, UK (S.T.C, M.C., A.R., V.M., T.K., N.F., J.E.D.)
| | - Alicja Rapala
- Vascular Physiology Unit, Institute of Cardiovascular Science, University College London, UK (S.T.C, M.C., A.R., V.M., T.K., N.F., J.E.D.)
- Cardiometabolic Phenotyping Group, Institute of Cardiovascular Science, University College London, UK (A.D.H., A.R., N.C.)
| | - Vivek Muthurangu
- Vascular Physiology Unit, Institute of Cardiovascular Science, University College London, UK (S.T.C, M.C., A.R., V.M., T.K., N.F., J.E.D.)
| | - Tauseef Khan
- Vascular Physiology Unit, Institute of Cardiovascular Science, University College London, UK (S.T.C, M.C., A.R., V.M., T.K., N.F., J.E.D.)
| | - Nicholas Finer
- Vascular Physiology Unit, Institute of Cardiovascular Science, University College London, UK (S.T.C, M.C., A.R., V.M., T.K., N.F., J.E.D.)
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, British Heart Foundation (BHF) Glasgow Cardiovascular Research Centre, University of Glasgow, UK (N.S.)
| | - Laura D. Howe
- Medical Research Council Integrative Epidemiology Unit (K.H.W., L.D.H., A.F., D.A.L., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School, Faculty of Health Sciences, University of Bristol, UK (K.H.W., L.D.H., D.A.L., G.D.S., N.J.T.)
| | - Abigail Fraser
- Medical Research Council Integrative Epidemiology Unit (K.H.W., L.D.H., A.F., D.A.L., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School, Faculty of Health Sciences, University of Bristol, UK (K.H.W., L.D.H., D.A.L., G.D.S., N.J.T.)
| | - Debbie A. Lawlor
- Medical Research Council Integrative Epidemiology Unit (K.H.W., L.D.H., A.F., D.A.L., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School, Faculty of Health Sciences, University of Bristol, UK (K.H.W., L.D.H., D.A.L., G.D.S., N.J.T.)
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit (K.H.W., L.D.H., A.F., D.A.L., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School, Faculty of Health Sciences, University of Bristol, UK (K.H.W., L.D.H., D.A.L., G.D.S., N.J.T.)
| | - John E. Deanfield
- Vascular Physiology Unit, Institute of Cardiovascular Science, University College London, UK (S.T.C, M.C., A.R., V.M., T.K., N.F., J.E.D.)
| | - Nicholas J. Timpson
- Medical Research Council Integrative Epidemiology Unit (K.H.W., L.D.H., A.F., D.A.L., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School, Faculty of Health Sciences, University of Bristol, UK (K.H.W., L.D.H., D.A.L., G.D.S., N.J.T.)
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Alver M, Palover M, Saar A, Läll K, Zekavat SM, Tõnisson N, Leitsalu L, Reigo A, Nikopensius T, Ainla T, Kals M, Mägi R, Gabriel SB, Eha J, Lander ES, Irs A, Philippakis A, Marandi T, Natarajan P, Metspalu A, Kathiresan S, Esko T. Recall by genotype and cascade screening for familial hypercholesterolemia in a population-based biobank from Estonia. Genet Med 2018; 21:1173-1180. [PMID: 30270359 PMCID: PMC6443485 DOI: 10.1038/s41436-018-0311-2] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Accepted: 09/06/2018] [Indexed: 01/13/2023] Open
Abstract
Purpose Large-scale, population-based biobanks integrating health records and genomic profiles may provide a platform to identify individuals with disease-predisposing genetic variants. Here, we recall probands carrying familial hypercholesterolemia (FH)-associated variants, perform cascade screening of family members, and describe health outcomes affected by such a strategy. Methods The Estonian Biobank of Estonian Genome Center, University of Tartu, comprises 52,274 individuals. Among 4776 participants with exome or genome sequences, we identified 27 individuals who carried FH-associated variants in the LDLR, APOB, or PCSK9 genes. Cascade screening of 64 family members identified an additional 20 carriers of FH-associated variants. Results Via genetic counseling and clinical management of carriers, we were able to reclassify 51% of the study participants from having previously established nonspecific hypercholesterolemia to having FH and identify 32% who were completely unaware of harboring a high-risk disease-associated genetic variant. Imaging-based risk stratification targeted 86% of the variant carriers for statin treatment recommendations. Conclusion Genotype-guided recall of probands and subsequent cascade screening for familial hypercholesterolemia is feasible within a population-based biobank and may facilitate more appropriate clinical management.
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Affiliation(s)
- Maris Alver
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia.,Department of Biotechnology, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Marili Palover
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia.,Department of Biotechnology, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Aet Saar
- Department of Cardiology, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia.,Cardiology Centre, North Estonia Medical Centre, Tallinn, Estonia
| | - Kristi Läll
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia.,Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
| | - Seyedeh Maryam Zekavat
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Yale School of Medicine, New Haven, CT, USA
| | - Neeme Tõnisson
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia.,Department of Clinical Genetics in Tallinn, United Laboratories, Tartu University Hospital, Tartu, Estonia
| | - Liis Leitsalu
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Anu Reigo
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Tiit Nikopensius
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Tiia Ainla
- Department of Cardiology, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia.,Cardiology Centre, North Estonia Medical Centre, Tallinn, Estonia
| | - Mart Kals
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia.,Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
| | - Reedik Mägi
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Jaan Eha
- Department of Cardiology, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia.,Heart Clinic, Tartu University Hospital, Tartu, Estonia
| | - Eric S Lander
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Alar Irs
- Heart Clinic, Tartu University Hospital, Tartu, Estonia
| | | | - Toomas Marandi
- Department of Cardiology, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia.,Cardiology Centre, North Estonia Medical Centre, Tallinn, Estonia
| | - Pradeep Natarajan
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Andres Metspalu
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia.,Department of Biotechnology, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Sekar Kathiresan
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Tõnu Esko
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia. .,Broad Institute of Harvard and MIT, Cambridge, MA, USA.
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Franks PW, Timpson NJ. Genotype-Based Recall Studies in Complex Cardiometabolic Traits. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2018; 11:e001947. [PMID: 30354344 PMCID: PMC6813040 DOI: 10.1161/circgen.118.001947] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
In genotype-based recall (GBR) studies, people (or their biological samples) who carry genotypes of special interest for a given hypothesis test are recalled from a larger cohort (or biobank) for more detailed investigations. There are several GBR study designs that offer a range of powerful options to elucidate (1) genotype-phenotype associations (by increasing the efficiency of genetic association studies, thereby allowing bespoke phenotyping in relatively small cohorts), (2) the effects of environmental exposures (within the Mendelian randomization framework), and (3) gene-treatment interactions (within the setting of GBR interventional trials). In this review, we overview the literature on GBR studies as applied to cardiometabolic health outcomes. We also review the GBR approaches used to date and outline new methods and study designs that might enhance the utility of GBR-focused studies. Specifically, we highlight how GBR methods have the potential to augment randomized controlled trials, providing an alternative application for the now increasingly accepted Mendelian randomization methods usually applied to large-scale population-based data sets. Further to this, we consider how functional and basic science approaches alongside GBR designs offer intellectually intriguing and potentially powerful ways to explore the implications of alterations to specific (and potentially druggable) biological pathways.
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Affiliation(s)
- Paul W Franks
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Skåne University Hospital, SE-21741, Malmö, Sweden
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, Avon Longitudinal Study of Parents and Children, Population Health Science, Bristol Medical School, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
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Inshaw JRJ, Cutler AJ, Burren OS, Stefana MI, Todd JA. Approaches and advances in the genetic causes of autoimmune disease and their implications. Nat Immunol 2018; 19:674-684. [PMID: 29925982 DOI: 10.1038/s41590-018-0129-8] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2017] [Accepted: 04/04/2018] [Indexed: 12/18/2022]
Abstract
Genome-wide association studies are transformative in revealing the polygenetic basis of common diseases, with autoimmune diseases leading the charge. Although the field is just over 10 years old, advances in understanding the underlying mechanistic pathways of these conditions, which result from a dense multifactorial blend of genetic, developmental and environmental factors, have already been informative, including insights into therapeutic possibilities. Nevertheless, the challenge of identifying the actual causal genes and pathways and their biological effects on altering disease risk remains for many identified susceptibility regions. It is this fundamental knowledge that will underpin the revolution in patient stratification, the discovery of therapeutic targets and clinical trial design in the next 20 years. Here we outline recent advances in analytical and phenotyping approaches and the emergence of large cohorts with standardized gene-expression data and other phenotypic data that are fueling a bounty of discovery and improved understanding of human physiology.
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Affiliation(s)
- Jamie R J Inshaw
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Antony J Cutler
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Oliver S Burren
- Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - M Irina Stefana
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - John A Todd
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK.
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Abstract
Recent large-scale genomic studies have confirmed that schizophrenia is a polygenic syndrome and have implicated a number of biological pathways in its aetiology. Both common variants individually of small effect and rarer but more penetrant genetic variants have been shown to play a role in the pathogenesis of the disorder. No simple Mendelian forms of the condition have been identified, but progress has been made in stratifying risk on the basis of the polygenic burden of common variants individually of small effect, and the contribution of rarer variants of larger effect such as Copy Number Variants (CNVs). Pathway analysis of risk-associated variants has begun to identify specific biological processes implicated in risk for the disorder, including elements of the glutamatergic NMDA receptor complex and post synaptic density, voltage-gated calcium channels, targets of the Fragile X Mental Retardation Protein (FMRP targets) and immune pathways. Genetic studies have also been used to drive genomic imaging approaches to the investigation of brain markers associated with risk for the disorder. Genomic imaging approaches have been applied both to investigate the effect of polygenic risk and to study the impact of individual higher-penetrance variants such as CNVs. Both genomic and genomic imaging approaches offer potential for the stratification of patients and at-risk groups and the development of better biomarkers of risk and treatment response; however, further research is needed to integrate this work and realise the full potential of these approaches.
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