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3. Preface

Author

Mills, Melinda A.

Published
2021

5. Index

Author

Mills, Melinda A.

Published
2021

7. References

Author

Mills, Melinda A.

Published
2021

14. Notes

Author

Mills, Melinda A.

Published
2021

17. Contents

Author

Mills, Melinda A.

Published
2021

28. COVID-19 testing and reporting behaviours in England across different sociodemographic groups: a population-based study using testing data and data from community prevalence surveillance surveys

Author

Aguas, Ricardo, Amswych, Ma'ayan, Andersen-Waine, Billie, Bajaj, Sumali, Bimpong, Kweku, Bodley, Adam, Cantrell, Liberty, Chen, Siyu, Creswell, Richard, Dahal, Prabin, Dickinson, Sophie, Dittrich, Sabine, Evans, Tracy, Ferguson-Lewis, Angus, Franco, Caroline, Gao, Bo, Hounsell, Rachel, Kasim, Muhammad, Keene, Claire, Lambert, Ben, Mahmood, Umar, Mills, Melinda, Moldokmatova, Ainura, Molyneux, Sassy, Naidoo, Reshania, Ngwafor Anye, Randolph, Norman, Jared, Pan-Ngum, Wirichada, Pokharel, Sunil, Polner, Anastasiia, Rowe, Emily, Saralamba, Sompob, Shretta, Rima, Silal, Sheetal, Stepniewska, Kasia, L-H Tsui, Joseph, Voysey, Merryn, Wanat, Marta, White, Lisa J, Tsui, Joseph L-H, Kolade, Olumide, Nicholson, George, Lehmann, Brieuc, Hay, James A, Kraemer, Moritz U G, Donnelly, Christl A, Fowler, Tom, and Hopkins, Susan

Published
2024
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29. Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects

Author

Howe, Laurence J, Nivard, Michel G, Morris, Tim T, Hansen, Ailin F, Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A, Palviainen, Teemu, van der Zee, Matthijs D, Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M, Bielak, Lawrence F, Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A, Reynolds, Chandra A, Balbona, Jared V, Andreassen, Ole A, Ask, Helga, Baras, Aris, Bauer, Christopher R, Boomsma, Dorret I, Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C, Dokuru, Deepika R, Evans, Luke M, de Geus, Eco JC, Giddaluru, Sudheer, Gordon, Scott D, Harden, K Paige, Hill, W David, Hughes, Amanda, Kerr, Shona M, Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A, Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik KE, Mallard, Travis T, Martikainen, Pekka, Mills, Melinda C, Njølstad, Pål Rasmus, Overton, John D, Pedersen, Nancy L, Porteous, David J, Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C, Stoltenberg, Camilla, Tucker-Drob, Elliot M, Wright, Margaret J, Hewitt, John K, Keller, Matthew C, Stallings, Michael C, Lee, James J, Christensen, Kaare, Kardia, Sharon LR, Peyser, Patricia A, Smith, Jennifer A, Wilson, James F, Hopper, John L, Hägg, Sara, Spector, Tim D, Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G, Oskarsson, Sven, Justice, Anne E, Millwood, Iona Y, Hveem, Kristian, Naess, Øyvind, Willer, Cristen J, Åsvold, Bjørn Olav, Koellinger, Philipp D, Kaprio, Jaakko, Medland, Sarah E, Walters, Robin G, Benjamin, Daniel J, Turley, Patrick, Evans, David M, Davey Smith, George, Hayward, Caroline, Brumpton, Ben, Hemani, Gibran, and Davies, Neil M

Subjects
Human Genome, Genetics, Pediatric, 2.1 Biological and endogenous factors, Aetiology, Mental health, Generic health relevance, Genome-Wide Association Study, Humans, Mendelian Randomization Analysis, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide, Social Science Genetic Association Consortium, Within Family Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects.

Published
2022

30. Social network-based distancing strategies to flatten the COVID 19 curve in a post-lockdown world

Author

Block, Per, Hoffman, Marion, Raabe, Isabel J., Dowd, Jennifer Beam, Rahal, Charles, Kashyap, Ridhi, and Mills, Melinda C.

Subjects
Physics - Physics and Society, Quantitative Biology - Populations and Evolution, Statistics - Other Statistics
Abstract

Social distancing and isolation have been introduced widely to counter the COVID-19 pandemic. However, more moderate contact reduction policies become desirable owing to adverse social, psychological, and economic consequences of a complete or near-complete lockdown. Adopting a social network approach, we evaluate the effectiveness of three targeted distancing strategies designed to 'keep the curve flat' and aid compliance in a post-lockdown world. These are limiting interaction to a few repeated contacts, seeking similarity across contacts, and strengthening communities via triadic strategies. We simulate stochastic infection curves that incorporate core elements from infection models, ideal-type social network models, and statistical relational event models. We demonstrate that strategic reduction of contact can strongly increase the efficiency of social distancing measures, introducing the possibility of allowing some social contact while keeping risks low. This approach provides nuanced insights to policy makers for effective social distancing that can mitigate negative consequences of social isolation.

Published
2020

31. Genome-wide analysis identifies genetic effects on reproductive success and ongoing natural selection at the FADS locus

Author

Mathieson, Iain, Day, Felix R., Barban, Nicola, Tropf, Felix C., Brazel, David M., Vaez, Ahmad, van Zuydam, Natalie, Bitarello, Bárbara D., Gardner, Eugene J., Akimova, Evelina T., Azad, Ajuna, Bergmann, Sven, Bielak, Lawrence F., Boomsma, Dorret I., Bosak, Kristina, Brumat, Marco, Buring, Julie E., Cesarini, David, Chasman, Daniel I., Chavarro, Jorge E., Cocca, Massimiliano, Concas, Maria Pina, Davey Smith, George, Davies, Gail, Deary, Ian J., Esko, Tõnu, Faul, Jessica D., Franco, Oscar, Ganna, Andrea, Gaskins, Audrey J., Gelemanovic, Andrea, de Geus, Eco J. C., Gieger, Christian, Girotto, Giorgia, Gopinath, Bamini, Grabe, Hans Jörgen, Gunderson, Erica P., Hayward, Caroline, He, Chunyan, van Heemst, Diana, Hill, W. David, Hoffmann, Eva R., Homuth, Georg, Hottenga, Jouke Jan, Huang, Hongyang, Hyppӧnen, Elina, Ikram, M. Arfan, Jansen, Rick, Johannesson, Magnus, Kamali, Zoha, Kardia, Sharon L. R., Kavousi, Maryam, Kifley, Annette, Kiiskinen, Tuomo, Kraft, Peter, Kühnel, Brigitte, Langenberg, Claudia, Liew, Gerald, Lind, Penelope A., Luan, Jian’an, Mägi, Reedik, Magnusson, Patrik K. E., Mahajan, Anubha, Martin, Nicholas G., Mbarek, Hamdi, McCarthy, Mark I., McMahon, George, Medland, Sarah E., Meitinger, Thomas, Metspalu, Andres, Mihailov, Evelin, Milani, Lili, Missmer, Stacey A., Mitchell, Paul, Møllegaard, Stine, Mook-Kanamori, Dennis O., Morgan, Anna, van der Most, Peter J., de Mutsert, Renée, Nauck, Matthias, Nolte, Ilja M., Noordam, Raymond, Penninx, Brenda W. J. H., Peters, Annette, Peyser, Patricia A., Polašek, Ozren, Power, Chris, Pribisalic, Ajka, Redmond, Paul, Rich-Edwards, Janet W., Ridker, Paul M., Rietveld, Cornelius A., Ring, Susan M., Rose, Lynda M., Rueedi, Rico, Shukla, Vallari, Smith, Jennifer A., Stankovic, Stasa, Stefánsson, Kári, Stöckl, Doris, Strauch, Konstantin, Swertz, Morris A., Teumer, Alexander, Thorleifsson, Gudmar, Thorsteinsdottir, Unnur, Thurik, A. Roy, Timpson, Nicholas J., Turman, Constance, Uitterlinden, André G., Waldenberger, Melanie, Wareham, Nicholas J., Weir, David R., Willemsen, Gonneke, Zhao, Jing Hau, Zhao, Wei, Zhao, Yajie, Snieder, Harold, den Hoed, Marcel, Ong, Ken K., Mills, Melinda C., and Perry, John R. B.

Published
2023
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42. Evidence for Genetic Overlap Between Schizophrenia and Age at First Birth in Women

Author

Mehta, Divya, Tropf, Felix C, Gratten, Jacob, Bakshi, Andrew, Zhu, Zhihong, Bacanu, Silviu-Alin, Hemani, Gibran, Magnusson, Patrik KE, Barban, Nicola, Esko, Tõnu, Metspalu, Andres, Snieder, Harold, Mowry, Bryan J, Kendler, Kenneth S, Yang, Jian, Visscher, Peter M, McGrath, John J, Mills, Melinda C, Wray, Naomi R, Lee, S Hong, Andreassen, Ole A, Bramon, Elvira, Bruggeman, Richard, Buxbaum, Joseph D, Cairns, Murray J, Cantor, Rita M, Cloninger, C Robert, Cohen, David, Crespo-Facorro, Benedicto, Darvasi, Ariel, DeLisi, Lynn E, Dinan, Timothy, Djurovic, Srdjan, Donohoe, Gary, Drapeau, Elodie, Escott-Price, Valentina, Freimer, Nelson B, Georgieva, Lyudmila, de Haan, Lieuwe, Henskens, Frans A, Joa, Inge, Julià, Antonio, Khrunin, Andrey, Lerer, Bernard, Limborska, Svetlana, Loughland, Carmel M, Macek, Milan, Marsal, Sara, McCarley, Robert W, McIntosh, Andrew M, McQuillin, Andrew, Melegh, Bela, Michie, Patricia T, Morris, Derek W, Murphy, Kieran C, Myin-Germeys, Inez, Olincy, Ann, Van Os, Jim, Pantelis, Christos, Posthuma, Danielle, Quested, Digby, Schall, Ulrich, Scott, Rodney J, Seidman, Larry J, Toncheva, Draga, Tooney, Paul A, Waddington, John, Weinberger, Daniel R, Weiser, Mark, and Wu, Jing Qin

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Epidemiology, Health Sciences, Human Genome, Prevention, Brain Disorders, Serious Mental Illness, Mental Health, Schizophrenia, Clinical Research, Mental health, Adult, Alleles, Birth Order, Cohort Studies, Denmark, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Maternal Age, Phenotype, Pregnancy, Risk, Schizophrenia Working Group of the Psychiatric Genomics Consortium, LifeLines Cohort Study, and TwinsUK, Other Medical and Health Sciences, Psychology, Cognitive Sciences, Clinical sciences, Clinical and health psychology
Abstract

ImportanceA recently published study of national data by McGrath et al in 2014 showed increased risk of schizophrenia (SCZ) in offspring associated with both early and delayed parental age, consistent with a U-shaped relationship. However, it remains unclear if the risk to the child is due to psychosocial factors associated with parental age or if those at higher risk for SCZ tend to have children at an earlier or later age.ObjectiveTo determine if there is a genetic association between SCZ and age at first birth (AFB) using genetically informative but independently ascertained data sets.Design, setting, and participantsThis investigation used multiple independent genome-wide association study data sets. The SCZ sample comprised 18 957 SCZ cases and 22 673 controls in a genome-wide association study from the second phase of the Psychiatric Genomics Consortium, and the AFB sample comprised 12 247 genotyped women measured for AFB from the following 4 community cohorts: Estonia (Estonian Genome Center Biobank, University of Tartu), the Netherlands (LifeLines Cohort Study), Sweden (Swedish Twin Registry), and the United Kingdom (TwinsUK). Schizophrenia genetic risk for each woman in the AFB community sample was estimated using genetic effects inferred from the SCZ genome-wide association study.Main outcomes and measuresWe tested if SCZ genetic risk was a significant predictor of response variables based on published polynomial functions that described the relationship between maternal age and SCZ risk in offspring in Denmark. We substituted AFB for maternal age in these functions, one of which was corrected for the age of the father, and found that the fit was superior for the model without adjustment for the father's age.ResultsWe observed a U-shaped relationship between SCZ risk and AFB in the community cohorts, consistent with the previously reported relationship between SCZ risk in offspring and maternal age when not adjusted for the age of the father. We confirmed that SCZ risk profile scores significantly predicted the response variables (coefficient of determination R2 = 1.1E-03, P = 4.1E-04), reflecting the published relationship between maternal age and SCZ risk in offspring by McGrath et al in 2014.Conclusions and relevanceThis study provides evidence for a significant overlap between genetic factors associated with risk of SCZ and genetic factors associated with AFB. It has been reported that SCZ risk associated with increased maternal age is explained by the age of the father and that de novo mutations that occur more frequently in the germline of older men are the underlying causal mechanism. This explanation may need to be revised if, as suggested herein and if replicated in future studies, there is also increased genetic risk of SCZ in older mothers.

Published
2016

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