Alexessander Couto Alves

Dr Alexessander Couto Alves


Lecturer in Bioinformatics and Statistical Genomics
PhD, MSc, MEng
14AX02, by appointment

麻豆视频

Areas of specialism

Genome wide association studies (GWAS); Expression quantitative trait loci studies (eQTL, and GxE-eQTL); Gene expression association studies; Statistical modeling of continuous and discrete outcomes; Regression and applied graphical models to health data; Variable selection and model averaging; Applied machine learning to health and biological data

University roles and responsibilities

  • Head of Bioinformatics Core Facility

    Affiliations and memberships

    Academic networks

      News

      In the media

      Lead author
      News Medical
      Lead author
      Genome web
      Lead author
      Medindia
      Lead author
      Weather Herald
      Lead author
      Daily Mail

      Research

      Research interests

      Research collaborations

      Indicators of esteem

      • Personal research awards and fellowships

        2018 Research Fellow, School of Public Health, Imperial College London

        2015 Research Fellow, Dept of Twin Research and Genetic Epidemiology, King鈥檚 College London

        2007 PhD Fellowship of the Portuguese National Science and Technology Foundation

      • Editorial board member:

        • , MDPI
        • , MDPI
      • Keynote and plenary addresses at conferences

        2014 Systems biology and functional analysis of disease genes. European academy of allergy and clinical immunology congress.

        • Conference organisation

          2007 Co-chair Workshop on Computational Methods in Bioinformatics and Systems Biology. As part of the Portuguese Conference on Artificial

          2005 Co-chair Workshop on Computational Methods in Bioinformatics. As part of the Portuguese Conference on Artificial Intelligence.

        • Reviewer for:

          • Journal of the Royal Statistical Society
          • International Journal of Epidemiology
          • International Journal of Allergy and Clinical Immunology
          • Nature Scientific Reports
          • Nature Communications Biology
          • Genome Medicine
          • Annals of Human Genetics

        Supervision

        Completed postgraduate research projects I have supervised

        Postgraduate research supervision

        Teaching

        Publications

        Highlights

        Couto Alves, A., De Silva, N. M. G.,  Karhunen, V. , Sovio, U., Das, S., et al. . Science Advances (2019).

        Glastonbury, C., Couto Alves, A., et al.  . Am J Hum Genet. (2019)

        Couto Alves, A.; Glastonbury, CA; Moustafa, JSES; Small, KS Fasting and time of day independently modulate circadian rhythm relevant gene expression in adipose and skin tissue. BMC genomics (2018)

        Demenais, F., Margaritte-Jeannin, P., Barnes, K. C., Cookson, W. O., Altm眉ller, J., Ang, W., Barr, R. G., Beaty, T. H., Becker, A. B., Beilby, J., et al. Multiancestry association study identifies new asthma risk loci that colocalize with immune-cell enhancer marks. Nature genetics 50, 1 (2018), 42.

        Liu, D. J., Peloso, G. M., Yu, H., Butterworth, A. S., Wang, X., Mahajan, A., Saleheen, D., Emdin, C., Alam, D., Couto Alves, A., et al. Exome-wide association study of plasma lipids in> 300,000 individuals. Nature genetics 49, 12 (2017), 1758.

        Ried, J. S., Chu, A. Y., Bragg-Gresham, J. L., Van Dongen, J.,Huffman, J. E., Ahluwalia, T. S., Cadby, G., Eklund, N., Eriksson, J., Esko, T., et al. A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape. Nature communications 7 (2016), 13357.

        Paternoster, L., Standl, M., Waage, J., Baurecht, H., Hotze, M., Strachan, D. P., Curtin, J. A., B酶nnelykke, K., Tian, C., Takahashi, A., et al. Multi-ethnic genome-wide association study of 21,000 cases and 95,000 controls identifies new risk loci for atopic dermatitis. Nature genetics 47, 12 (2015), 1449

        Kato, N., Loh, M., Takeuchi, F., Verweij, N., Wang, X., Zhang, W., Kelly, T. N., Saleheen, D., Lehne, B., Leach, I. M., et al. Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for dna methylation. Nature genetics 47, 11 (2015), 1282鈥1293

        Loth, D. W., Artigas, M. S., Gharib, S. A., Wain, L. V., Franceschini, N., Koch, B., Pottinger, T. D., Smith, A. V., Duan, Q., Oldmeadow, C., et al. Genome-wide association analysis identifies six new loci associated with forced vital capacity. Nature genetics 46, 7 (2014), 669鈥677.

        B酶nnelykke, K., Matheson, M. C., Pers, T. H., Granell, R., Strachan, D. P., Couto Alves, A., Linneberg, A., Curtin, J. A., Warrington, N. M., Standl, M., et al. Meta-analysis of genomewide association studies identifies ten loci influencing allergic sensitization. Nature genetics 45, 8 (2013), 902鈥906.

        Paternoster, L., Standl, M., Chen, C.-M., Ramasamy, A., B酶nnelykke, K., Duijts, L., Ferreira, M. A., Couto Alves, A., Thyssen, J. P., Albrecht, E., et al. Meta-analysis of genome-wide association studies identifies three new risk loci for atopic dermatitis. Nature genetics 44, 2 (2012), 187鈥192.

        Cibele A. Crispim, Catarina M. Azeredo, Ana E. M. Rinaldi, Alexessander Couto Alves, Debra Jean Skene, Claudia R. C. Moreno (2025), In: European Journal of Nutrition64(3)134 Springer

        Purpose Global dietary patterns are increasingly driven by ultra-processed foods鈥揷heap, highly palatable, and ready-to-eat options. Exploring time-related eating patterns and its association with ultra-processed foods could help in intervention efforts, but knowledge on this topic is still limited. This study assessed the association of time-related eating patterns with unprocessed/minimally processed and ultra-processed food consumption across different life stages. Methods Two 24-hour food recalls from a nationally representative sample in Brazil (Brazilian Household Budget Survey, POF, 2017鈥2018; n鈥=鈥46,164) were used to estimate tertiles of first and last intake times, eating midpoint, caloric midpoint time, and night fasting (independent variables). All consumed foods were classified according to the Nova classification system, and the outcomes of interest were consumption of unprocessed/minimally processed and ultra-processed foods. Multiple linear regression models were performed for all individuals and stratified for each age group: adolescents (10鈥19 years, n鈥=鈥8,469), adults (20鈥59 years, n鈥=鈥29,332), and older individuals (鈮モ60 years, n鈥=鈥8,322). Results The later tertile of first food intake time, last food intake time, caloric midpoint, and eating midpoint were positively associated with consumption of ultra-processed foods (尾鈥=鈥3.69, 95%CI鈥=鈥3.04, 4.34; 尾鈥=鈥1.89, 95%CI鈥=鈥1.32, 2.47; 尾鈥=鈥5.20, 95%CI鈥=鈥4.60, 5.81; 尾鈥=鈥3.10, 95%CI鈥=鈥2.49, 3.71, respectively) and negatively associated with consumption of unprocessed or minimally processed foods (尾=-2.79, 95%CI=-3.37; -2.22; 尾=-1.65, 95%CI=-2.24, -1.05; 尾=-3.94, 95%CI=-4.44, -3.44; 尾=- 2.35, 95%CI=-2.93, -1.78, respectively) compared to the first 鈥渆arlier鈥 tertile (reference). An inverse association was found for night fasting (尾=-1.74, 95%CI=-2.28, -1.22 and 尾鈥=鈥1.52, 95%CI鈥=鈥0.98, 2.06 for ultra-processed and unprocessed/minimally processed foods, respectively). These associations were consistent across all age groups. Conclusion Chrononutrition patterns characterized by late intake timing and shortened overnight fasting were associated with higher consumption of ultra-processed foods and lower intake of unprocessed/minimally processed foods across all age groups.

        Chen Li, Svetlana Stoma, Luca A. Lotta, Sophie Warner, Eva Albrecht, Alessandra Allione, Pascal P. Arp, Linda Broer, Jessica L. Bruxton, Alexessander Da Silva Couto Alves, Joris Deelen, Iryna O. Fedko, Scott D. Gordon, Tao Jiang, Robert Karlsson, Nicola Kerrison, Taylor K. Loe, Massimo Mangino, Yuri Milaneschi, Benjamin Miraglio, Natalia Pervjakova, Alessia Russo, Ida Surakka, Ashley van der Spek, Josine E. Verhoeven, Najaf Amin, Marian Beekman, Alexandra I. Blakemore, Frederico Canzian, Stephen E. Hamby, Jouke-Jan Hottenga, Peter D. Jones, Pekka Jousilahti, Reedik Magi, Sarah E. Medland, Grant W. Montgomery, Dale R. Nyholt, Markus Perola, Kirsi H. Pietilainen, Veikko Salomaa, Elina Sillanpaa, H. Eka Suchiman, Diana van Heemst, Gonneke Willemsen, Antonio Agudo, Heiner Boeing, Dorret I. Boomsma, Maria-Dolores Chirlaque, Guy Fagherazzi, Pietro Ferrari, Paul Franks, Christian Gieger, Johan Gunnar Eriksson, Marc Gunter, Sara Hagg, Iiris Hovatta, Liher Imaz, Jaakko Kaprio, Rudolf Kaaks, Timothy Key (2020), In: American Journal of Human Genetics106(3)pp. 389-404 Elsevier

        Leukocyte telomere length (LTL) is a heritable biomarker of genomic aging. In this study, we perform a genome-wide meta-analysis of LTL by pooling densely genotyped and imputed association results across large-scale European-descent studies including up to 78,592 individuals. We identify 49 genomic regions at a false dicovery rate (FDR) < 0.05 threshold and prioritize genes at 31, with five highlighting nucleotide metabolism as an important regulator of LTL. We report six genome-wide significant loci in or near SENP7, MOB1B, CARMIL1, PRRC2A, TERF2, and RFWD3, and our results support recently identified PARP1, POT1, ATM, and MPHOSPH6 loci. Phenome-wide analyses in >350,000 UK Biobank participants suggest that genetically shorter telomere length increases the risk of hypothyroidism and decreases the risk of thyroid cancer, lymphoma, and a range of proliferative conditions. Our results replicate previously reported associations with increased risk of coronary artery disease and lower risk for multiple cancer types. Our findings substantially expand current knowledge on genes that regulate LTL and their impact on human health and disease.

        Tom A. Bond, Rebecca C. Richmond, Ville Karhunen, Gabriel Cuellar-Partida, Maria Carolina Borges, Verena Zuber, Alexessander Couto Alves, Dan Mason, Tiffany C. Yang, Marc J. Gunter, Abbas Dehghan, Ioanna Tzoulaki, Sylvain Sebert, David M. Evans, Alex M. Lewin, Paul F. O'Reilly, Deborah A. Lawlor, Marjo-Riitta Jarvelin, Alexessander Couto Alves (2022), In: BMC medicine20(1)34pp. 34-34 Springer Nature

        Background Greater maternal adiposity before or during pregnancy is associated with greater offspring adiposity throughout childhood, but the extent to which this is due to causal intrauterine or periconceptional mechanisms remains unclear. Here, we use Mendelian randomisation (MR) with polygenic risk scores (PRS) to investigate whether associations between maternal pre-/early pregnancy body mass index (BMI) and offspring adiposity from birth to adolescence are causal. Methods We undertook confounder adjusted multivariable (MV) regression and MR using mother-offspring pairs from two UK cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC) and Born in Bradford (BiB). In ALSPAC and BiB, the outcomes were birthweight (BW; N = 9339) and BMI at age 1 and 4 years (N = 8659 to 7575). In ALSPAC only we investigated BMI at 10 and 15 years (N = 4476 to 4112) and dual-energy X-ray absorptiometry (DXA) determined fat mass index (FMI) from age 10-18 years (N = 2659 to 3855). We compared MR results from several PRS, calculated from maternal non-transmitted alleles at between 29 and 80,939 single nucleotide polymorphisms (SNPs). Results MV and MR consistently showed a positive association between maternal BMI and BW, supporting a moderate causal effect. For adiposity at most older ages, although MV estimates indicated a strong positive association, MR estimates did not support a causal effect. For the PRS with few SNPs, MR estimates were statistically consistent with the null, but had wide confidence intervals so were often also statistically consistent with the MV estimates. In contrast, the largest PRS yielded MR estimates with narrower confidence intervals, providing strong evidence that the true causal effect on adolescent adiposity is smaller than the MV estimates (P-difference = 0.001 for 15-year BMI). This suggests that the MV estimates are affected by residual confounding, therefore do not provide an accurate indication of the causal effect size. Conclusions Our results suggest that higher maternal pre-/early-pregnancy BMI is not a key driver of higher adiposity in the next generation. Thus, they support interventions that target the whole population for reducing overweight and obesity, rather than a specific focus on women of reproductive age.

        Alexessander Da Silva Couto Alves, N. Maneka G. De Silva, Ville Karhunen, Ulla Sovio, Shikta Das, H. Rob Taal, Nicole M. Warrington, Alexandra M. Lewin, Marika Kaakinen, Diana L. Cousminer, Elisabeth Thiering, Nicholas J. Timpson, Tom A. Bond, Estelle Lowry, Christopher D. Brown, Xavier Estivill, Virpi Lindi, Jonathan P. Bradfield, Frank Geller, Doug Speed, Lachlan J. M. Coin, Marie Loh, Sheila J. Barton, Lawrence J. Beilin, Hans Bisgaard, Klaus Bonnelykke, Rohia Alili, Ida J. Hatoum, Katharina Schramm, Rufus Cartwright, Marie-Aline Charles, Vincenzo Salerno, Karine Clement, Annique A.J Claringbould, BIOS Consortium, Cornelia M. van Duijin, Elena Moltchanova, Johan G. Eriksson, Cathy Elks, Bjarke Feenstra, Claudia Flexeder, Stephen Franks, Timothy M. Frayling, Rachel M. Freathy, Paul Elliot, Elisabeth Widen, Hakon Hakonarson, Andrew T. Hattersley, Alina Rodriguez, Marco Banterle, Joachim Heinrich, Barbara Heude, John W. Holloway, Albert Hofman, Elina Hypponen, Hazel Inskip, Lee M. Kaplan, Asa K. Hedman, Esa Laara, Holger Prokisch, Harald Grallert, Timo A. Lakka, Debbie A. Lawlor, Mads Melbye, Tarunveer S. Ahluwalia, Marcella Marinelli, Iona Y. Millwood, Lyle J. Palmer, Craig E. Pennell, John R. Perry, Susan M. Ring, Markku J. Savolainen, Fernando Rivadeneira, Marie Standl, Jordi Sunyer, Carla M.T Tiesler, Andre G. Uitterlinden, William Schierding, Justin M. O'Sullivan, Inga Prokopenko, Karl-Heinz Herzig, George Davey Smith, Paul O'Reilly, Janine F. Felix, Jessica L. Buxton, Alexandra L. F Blakemore, Ken K. Ong, Vincent W.V Jaddoe, Struan F.A Grant, Sylvain Sebert, Mark L. McCarthy, Marjo-Riitta Jarvelin (2019), In: Science Advances5(9) American Association for the Advancement of Science

        Early childhood growth patterns are associated with adult health, yet the genetic factors and the developmental stages involved are not fully understood. Here, we combine genome-wide association studies with modeling of longitudinal growth traits to study the genetics of infant and child growth, followed by functional, pathway, genetic correlation, risk score, and colocalization analyses to determine how developmental timings, molecular pathways, and genetic determinants of these traits overlap with those of adult health. We found a robust overlap between the genetics of child and adult body mass index (BMI), with variants associated with adult BMI acting as early as 4 to 6 years old. However, we demonstrated a completely distinct genetic makeup for peak BMI during infancy, influenced by variation at the LEPR/LEPROT locus. These findings suggest that different genetic factors control infant and child BMI. In light of the obesity epidemic, these findings are important to inform the timing and targets of prevention strategies.

        Additional publications