Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-15T13:25:35.508Z Has data issue: false hasContentIssue false

Cognition, psychosis risk and metabolic measures in two adolescent birth cohorts

Published online by Cambridge University Press:  24 July 2018

Hugh Ramsay*
Affiliation:
Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, Oulu, Finland Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland St. Michael's House, Dublin, Ireland
Jennifer H Barnett
Affiliation:
Department of Psychiatry, University of Cambridge, Cambridge, UK Cambridge Cognition Ltd, Cambridge, UK
Graham K Murray
Affiliation:
Department of Psychiatry, University of Cambridge, Cambridge, UK
Jouko Miettunen
Affiliation:
Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, Oulu, Finland Faculty of Medicine, Center for Life Course Health Research, University of Oulu, Oulu, Finland
Pirjo Mäki
Affiliation:
Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, Oulu, Finland Department of Psychiatry, University Hospital of Oulu, Oulu, Finland Department of Psychiatry, Länsi-Pohja Healthcare District, Kauppakatu 25, 94100 Kemi, Finland Department of Psychiatry, The Middle Ostrobothnia Central Hospital, Kiuru, Finland Mental Health Services, Joint Municipal Authority of Wellbeing in Raahe District, Northern Ostrobothnia, Finland Mental Health Services, Basic Health Care District of Kallio, Helsinki, Finland Department of Psychiatry, Kainuu Central Hospital, Kainuu Social and Healthcare District, Kainuu, Finland
Marjo-Riitta Järvelin
Affiliation:
Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK Faculty of Medicine, Center for Life Course Health Research, University of Oulu, Oulu, Finland Biocenter Oulu, University of Oulu, Aapistie 5, 90220 Oulu, Finland Unit of Primary Health Care, Oulu University Hospital, OYS, Kajaanintie 50, 90220, Oulu, Finland Department of Life Sciences, College of Health and Life Sciences, Brunel University London, Kingston Lane, Uxbridge, Middlesex UB8 3PH, UK
George Davey Smith
Affiliation:
Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
Mika Ala-Korpela
Affiliation:
Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, The Alfred Hospital, Monash University, Melbourne, Victoria, Australia
Juha Veijola
Affiliation:
Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, Oulu, Finland Department of Psychiatry, University Hospital of Oulu, Oulu, Finland Medical Research Center Oulu, University Hospital of Oulu and University of Oulu, Oulu, Finland
*
Author for correspondence: Hugh Ramsay, E-mail: [email protected]

Abstract

Background

Psychoses, especially schizophrenia, are often preceded by cognitive deficits and psychosis risk states. Altered metabolic profiles have been found in schizophrenia. However, the associations between metabolic profiles and poorer cognitive performance and psychosis risk in the population remain to be determined.

Methods

Detailed molecular profiles were measured for up to 8976 individuals from two general population-based prospective birth cohorts: the Northern Finland Birth Cohort 1986 (NFBC 1986) and the Avon Longitudinal Study of Parents and Children (ALSPAC). A high-throughput nuclear magnetic resonance spectroscopy platform was used to quantify 70 metabolic measures at age 15–16 years in the NFBC 1986 and at ages 15 and 17 years in ALSPAC. Psychosis risk was assessed using the PROD-screen questionnaire at age 15–16 years in the NFBC 1986 or the psychotic-like symptoms assessment at age 17 years in ALSPAC. Cognitive measures included academic performance at age 16 years in both cohorts and general intelligence and executive function in ALSPAC. Logistic regression measured cross-sectional and longitudinal associations between metabolic measures and psychosis risk and cognitive performance, controlling for important covariates.

Results

Seven metabolic measures, primarily fatty acid (FA) measures, showed cross-sectional associations with general cognitive performance, four across both cohorts (low density lipoprotein diameter, monounsaturated FA ratio, omega-3 ratio and docosahexaenoic acid ratio), even after controlling for important mental and physical health covariates. Psychosis risk showed minimal metabolic associations.

Conclusions

FA ratios may be important in marking risk for cognitive deficits in adolescence. Further research is needed to clarify whether these biomarkers could be causal and thereby possible targets for intervention.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abu-Hilal, MM, Al-Baili, MA, Sartawi, A, Abdel-Fattah, F and Al-Qarayout, AI (2011) Psychometric properties of the Wechsler Abbreviated Scale of Intelligence (WASI) with an Arab sample of school students. Individual Differences Research 9, 219230.Google Scholar
Ala-Korpela, M (2007 a) Critical evaluation of 1H NMR metabonomics of serum as a methodology for disease risk assessment and diagnostics. Clinical Chemistry and Laboratory Medicine 46, 2742.Google Scholar
Ala-Korpela, M (2007 b) Potential role of body fluid 1H NMR metabolomics as a prognostic and diagnostic tool. Expert Review of Molecular Diagnostics 7, 761773.Google Scholar
Auro, K, Joensuu, A, Fischer, K, Kettunen, J, Salo, P, Mattsson, H, Niironen, M, Kaprio, J, Eriksson, JG, Lehtimäki, T, Raitakari, O, Jula, A, Tiitinen, A, Jauhiainen, M, Soininen, P, Kangas, AJ, Kähönen, M, Havulinna, AS, Ala-Korpela, M, Salomaa, V, Metspalu, A and Perola, M (2014) A metabolic view on menopause and ageing. Nature Communications 5, 4708.Google Scholar
Blakemore, SJ and Choudhury, S (2006) Development of the adolescent brain: implications for executive function and social cognition. Journal of Child Psychology and Psychiatry and Allied Disciplines 47, 296312.Google Scholar
Bos, DJ, Oranje, B, Veerhoek, ES, Van Diepen, RM, Weusten, JMH, Demmelmair, H, Koletzko, B, de Sain-van der Velden, MGM, Eilander, A, Hoeksma, M and Durston, S (2015) Reduced symptoms of inattention after dietary Omega-3 fatty acid supplementation in boys with and without attention deficit/hyperactivity disorder. Neuropsychopharmacology 40, 22982306.Google Scholar
Boyd, A, Golding, J, Macleod, J, Lawlor, DA, Fraser, A, Henderson, J, Molloy, L, Ness, A, Ring, S and Smith, GD (2013) Cohort profile: the “Children of the 90s” – The index offspring of the Avon longitudinal study of parents and children. International Journal of Epidemiology 42, 111127.Google Scholar
Bradford Hill, A (1965) The environment and disease: association or causation? Proceedings of the Royal Society of Medicine 58, 295300.Google Scholar
Carrión, RE, McLaughlin, D, Goldberg, TE, Auther, AM, Olsen, RH, Olvet, DM, Correll, CU and Cornblatt, BA (2013) Prediction of functional outcome in individuals at clinical high risk for psychosis. JAMA Psychiatry 70, 11331142.Google Scholar
Coe, DP, Peterson, T, Blair, C, Schutten, MC and Peddie, H (2013) Physical fitness, academic achievement, and socioeconomic status in school-aged youth. Journal of School Health 83, 500507.Google Scholar
Duckworth, AL and Seligman, MEP (2005) Self-discipline outdoes IQ in predicting academic performance of adolescents. Psychological Science 16, 939944.Google Scholar
Fett, AKJ, Viechtbauer, W, de Dominguez, MG, Penn, DL, van Os, J and Krabbendam, L (2011) The relationship between neurocognition and social cognition with functional outcomes in schizophrenia: a meta-analysis. Neuroscience and Biobehavioral Reviews 35, 573588.Google Scholar
Fischer, K, Kettunen, J, Würtz, P, Haller, T, Havulinna, AS, Kangas, AJ, Soininen, P, Esko, T, Tammesoo, ML, Mägi, R, Smit, S, Palotie, A, Ripatti, S, Salomaa, V, Ala-Korpela, M, Perola, M and Metspalu, A (2014) Biomarker profiling by nuclear magnetic resonance spectroscopy for the prediction of All-cause mortality: an observational study of 17 345 persons. Public Library of Science (PLoS) Medicine 11, e1001606.Google Scholar
Fusar-Poli, P, Borgwardt, S, Bechdolf, A, Addington, J, Riecher-Rössler, A, Schultze-Lutter, F, Keshavan, MS, Wood, S, Ruhrmann, S, Seidman, LJ, Valmaggia, L, Cannon, T, Velthorst, E, de Haan, L, Cornblatt, B, Bonoldi, I, Birchwood, M, Mcglashan, TH, Carpenter, WT, McGorry, PD, Klosterkötter, J, McGuire, P and Yung, AR (2013) The psychosis at risk state: a comprehensive state-of-the-art review. JAMA Psychiatry 70, 107120.Google Scholar
Golding, J, Pembrey, M and Jones, R (2001) ALSPAC--the Avon Longitudinal Study of Parents and Children. I. Study methodology. Paediatric and Perinatal Epidemiology 15, 7487.Google Scholar
He, Y, Yu, Z, Giegling, I, Xie, L, Hartmann, AM, Prehn, C, Adamski, J, Kahn, R, Li, Y, Illig, T, Wang-Sattler, R and Rujescu, D (2012) Schizophrenia shows a unique metabolomics signature in plasma. Translational Psychiatry 2, e149.Google Scholar
Heinimaa, M, Salokangas, RK, Ristkari, T, Plathin, M, Huttunen, J, Ilonen, T, Suomela, T, Korkeila, J and McGlashan, TH (2003) PROD-screen – a screen for prodromal symptoms of psychosis. International Journal of Methods in Psychiatric Research 12, 92104.Google Scholar
Holmes, E, Tsang, TM, Huang, JTJ, Leweke, FM, Koethe, D, Gerth, CW, Nolden, BM, Gross, S, Schreiber, D, Nicholson, JK and Bahn, S (2006) Metabolic profiling of CSF: evidence that early intervention may impact on disease progression and outcome in schizophrenia. PLoS Medicine 3, 14201428.Google Scholar
Holshausen, K, Bowie, CR, Mausbach, BT, Patterson, TL and Harvey, PD (2014) Neurocognition, functional capacity, and functional outcomes: the cost of inexperience. Schizophrenia Research 152, 430434.Google Scholar
Hurtig, TM, Taanila, A, Veijola, J, Ebeling, H, Mäki, P, Miettunen, J, Kaakinen, M, Joukamaa, M, Therman, S, Heinimaa, M, Järvelin, MR and Moilanen, I (2011) Associations between psychotic-like symptoms and inattention/hyperactivity symptoms. Social Psychiatry and Psychiatric Epidemiology 46, 1727.Google Scholar
Inouye, M, Kettunen, J, Soininen, P, Silander, K, Ripatti, S, Kumpula, LS, Hämäläinen, E, Jousilahti, P, Kangas, AJ, Männistö, S, Savolainen, MJ, Jula, A, Leiviskä, J, Palotie, A, Salomaa, V, Perola, M, Ala-Korpela, M and Peltonen, L (2010) Metabonomic, transcriptomic, and genomic variation of a population cohort. Molecular Systems Biology 6, 441.Google Scholar
Ishikawa, M, Maekawa, K, Saito, K, Senoo, Y, Urata, M, Murayama, M, Tajima, Y, Kumagai, Y and Saito, Y (2014) Plasma and serum lipidomics of healthy white adults shows characteristic profiles by subjects’ gender and age. PLoS ONE 9, 112.Google Scholar
Järvelin, MR, Hartikainen-Sorri, AL and Rantakallio, P (1993) Labour induction policy in hospitals of different levels of specialisation. British journal of Obstetrics and Gynaecology 100, 310315.Google Scholar
Kelleher, I, Connor, D, Clarke, MC, Devlin, N, Harley, M and Cannon, M (2012) Prevalence of psychotic symptoms in childhood and adolescence: a systematic review and meta-analysis of population-based studies. Psychological Medicine 42, 18571863.Google Scholar
Kettunen, J, Demirkan, A, Würtz, P, Draisma, HHM, Haller, T, Rawal, R, Vaarhorst, A, Kangas, AJ, Lyytikäinen, LP, Pirinen, M, Pool, R, Sarin, AP, Soininen, P, Tukiainen, T, Wang, Q, Tiainen, M, Tynkkynen, T, Amin, N, Zeller, T, Beekman, M, Deelen, J, Van Dijk, KW, Esko, T, Hottenga, JJ, Van Leeuwen, EM, Lehtimäki, T, Mihailov, E, Rose, RJ, De Craen, AJM, Gieger, C, Kähönen, M, Perola, M, Blankenberg, S, Savolainen, MJ, Verhoeven, A, Viikari, J, Willemsen, G, Boomsma, DI, Van Duijn, CM, Eriksson, J, Jula, A, Järvelin, MR, Kaprio, J, Metspalu, A, Raitakari, O, Salomaa, V, Eline Slagboom, P, Waldenberger, M, Ripatti, S and Ala-Korpela, M (2016) Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA. Nature Communications 7, 19.Google Scholar
Koivukangas, J, Tammelin, T, Kaakinen, M, Mäki, P, Moilanen, I, Taanila, A and Veijola, J (2010) Physical activity and fitness in adolescents at risk for psychosis within the Northern Finland 1986 Birth Cohort. Schizophrenia Research 116, 152158.Google Scholar
Koponen, H, Maki, P, Halonen, H, Miettunen, J, Laitinen, J, Tammelin, T, Moilanen, I, Taanila, A, Ruokonen, A, Korkeila, J and Veijola, J (2008) Insulin resistance and lipid levels in adolescents with familial risk for psychosis. Acta Psychiatrica Scandinavica 117, 337341.Google Scholar
Kujala, UM, Makinen, VP, Heinonen, I, Soininen, P, Kangas, AJ, Leskinen, TH, Rahkila, P, Wurtz, P, Kovanen, V, Cheng, S, Sipila, S, Hirvensalo, M, Telama, R, Tammelin, T, Savolainen, MJ, Pouta, A, O'Reilly, PF, Mantyselka, P, Viikari, J, Kahonen, M, Lehtimaki, T, Elliott, P, Vanhala, MJ, Raitakari, OT, Jarvelin, MR, Kaprio, J, Kainulainen, H and Ala-Korpela, M (2013) Long-term leisure-time physical activity and serum metabolome. Circulation 127, 340348.Google Scholar
Mahendran, Y, Cederberg, H, Vangipurapu, J, Kangas, AJ, Soininen, P, Kuusisto, J, Uusitupa, M, Ala-Korpela, M and Laakso, M (2013) Glycerol and fatty acids in serum predict the development of hyperglycemia and type 2 diabetes in Finnish men. Diabetes Care 36, 37323738.Google Scholar
Mäki, P, Koskela, S, Murray, GK, Nordström, T, Miettunen, J, Jääskeläinen, E and Veijola, JM (2014) Difficulty in making contact with others and social withdrawal as early signs of psychosis in adolescents-the Northern Finland Birth Cohort 1986. European Psychiatry 29, 345351.Google Scholar
Mapstone, M, Cheema, AK, Fiandaca, MS, Zhong, X, Mhyre, TR, MacArthur, LH, Hall, WJ, Fisher, SG, Peterson, DR, Haley, JM, Nazar, MD, Rich, SA, Berlau, DJ, Peltz, CB, Tan, MT, Kawas, CH and Federoff, HJ (2014) Plasma phospholipids identify antecedent memory impairment in older adults. Nature Medicine 20, 415418.Google Scholar
McIntyre, RS, Cha, DS, Soczynska, JK, Woldeyohannes, HO, Gallaugher, LA, Kudlow, P, Alsuwaidan, M and Baskaran, A (2013) Cognitive deficits and functional outcomes in major depressive disorder: determinants, substrates, and treatment interventions. Depression and Anxiety 30, 515527.Google Scholar
Metcalf, SA, Jones, PB, Nordstrom, T, Timonen, M, Mäki, P, Miettunen, J, Jääskeläinen, E, Järvelin, M-R, Stochl, J, Murray, GK, Veijola, J and Khandaker, GM (2017) Serum C-reactive protein in adolescence and risk of schizophrenia in adulthood: a prospective birth cohort study. Brain, Behavior, and Immunity 59, 253259.Google Scholar
Miettunen, J, Törmänen, S, Murray, GK, Jones, PB, Mäki, P, Ebeling, H, Moilanen, I, Taanila, A, Heinimaa, M, Joukamaa, M and Veijola, J (2008) Association of cannabis use with prodromal symptoms of psychosis in adolescence. The British Journal of Psychiatry: the Journal of Mental Science 192, 470471.Google Scholar
Miller, KM, Price, CC, Okun, MS, Montijo, H and Bowers, D (2009) Is the N-back task a valid neuropsychological measure for assessing working memory? Archives of Clinical Neuropsychology 24, 711717.Google Scholar
Murray, RM and Lewis, SW (1988) Is schizophrenia a neurodevelopmental disorder? British Medical Journal (Clinical research ed.) 296, 63.Google Scholar
Orešič, M, Tang, J, Seppänen-Laakso, T, Mattila, I, Saarni, SI, Suoma, E, Lönnqvist, J, Sysi-Aho, M, Hyötyläinen, T, Perälä, J and Suvisaari, J (2011) Metabolome in schizophrenia and other psychotic disorders: a general population-based study. Genome Medicine 3, 19.Google Scholar
Paus, T, Keshavan, M and Giedd, JN (2008) Why do many psychiatric disorders emerge during adolescence? Nature Reviews Neuroscience 9, 947957.Google Scholar
Rapoport, JL, Addington, AM, Frangou, S and Psych, MRC (2005) The neurodevelopmental model of schizophrenia: update 2005. Molecular Psychiatry 10, 434449.Google Scholar
Reichenberg, A, Caspi, A, Harrington, H, Houts, R, Keefe, RSE, Murray, RM, Poulton, R and Moffitt, TE (2010) Static and dynamic cognitive deficits in childhood preceding adult schizophrenia: a 30-year study. American Journal of Psychiatry 167, 160169.Google Scholar
Rohde, TE and Thompson, LA (2007) Predicting academic achievement with cognitive ability. Intelligence 35, 8392.Google Scholar
Saklofske, DH, Caravan, G and Schwartz, C (2000) Concurrent validity of the Wechsler Abbreviated Scale of Intelligence (WASI) with a sample of Canadian children. Canadian Journal of School Psychology 16, 8794.Google Scholar
Scoriels, L, Salek, RM, Goodby, E, Grainger, D, Dean, AM, West, JA, Griffin, JL, Suckling, J, Nathan, PJ, Lennox, BR, Murray, GK, Bullmore, ET and Jones, PB (2015) Behavioural and molecular endophenotypes in psychotic disorders reveal heritable abnormalities in glutamatergic neurotransmission. Translational Psychiatry 5, e540.Google Scholar
Serbin, LA, Zelkowitz, P, Doyle, AB, Gold, D and Wheaton, B (1990) The socialization of sex-differentiated skills and academic performance: a mediational model. Sex Roles 23, 613628.Google Scholar
Soininen, P, Kangas, AJ, Würtz, P, Suna, T and Ala-Korpela, M (2015) Quantitative serum nuclear magnetic resonance metabolomics in cardiovascular epidemiology and genetics. Circulation: Cardiovascular Genetics 8, 192206.Google Scholar
Soininen, P, Kangas, AJ, Würtz, P, Tukiainen, T, Tynkkynen, T, Laatikainen, R, Järvelin, M-R, Kähönen, M, Lehtimäki, T, Viikari, J, Raitakari, OT, Savolainen, MJ and Ala-Korpela, M (2009) High-throughput serum NMR metabonomics for cost-effective holistic studies on systemic metabolism. The Analyst 134, 17811785.Google Scholar
Song, L, Singh, J and Singer, M (1994) The youth self-report inventory: a study of its measurements fidelity. Psychological Assessment 6, 236245.Google Scholar
Taanila, AM, Hurtig, TM, Miettunen, J, Ebeling, HE and Moilonen, IK (2009) Association between ADHD symptoms and adolescents’ psychosocial well-being: a study of the northern Finland birth cohort 1986. International Journal of Circumpolar Health 68, 133144.Google Scholar
Therman, S, Heinimaa, M, Miettunen, J, Joukamaa, M, Moilanen, I, Mäki, P and Veijola, J (2011) Symptoms associated with psychosis risk in an adolescent birth cohort: improving questionnaire utility with a multidimensional approach. Early Intervention in Psychiatry 5, 343348.Google Scholar
Trushina, E, Dutta, T, Persson, XMT, Mielke, MM and Petersen, RC (2013) Identification of altered metabolic pathways in plasma and CSF in mild cognitive impairment and Alzheimer's disease using metabolomics. PLoS ONE 8, e63644.Google Scholar
Tukiainen, T, Tynkkynen, T, Mäkinen, V-P, Jylänki, P, Kangas, A, Hokkanen, J, Vehtari, A, Gröhn, O, Hallikainen, M, Soininen, H, Kivipelto, M, Groop, P-H, Kaski, K, Laatikainen, R, Soininen, P, Pirttilä, and Ala-Korpela, M (2008) A multi-metabolite analysis of serum by 1 H NMR spectroscopy: early systemic signs of Alzheimer's disease. Biochemical and Biophysical Research Communications 375, 356361.Google Scholar
Wang, Q, Kangas, AJ, Soininen, P, Tiainen, M, Tynkkynen, T, Puukka, K, Ruokonen, A, Viikari, J, Kähönen, M, Lehtimäki, T, Salomaa, V, Perola, M, Smith, GD, Raitakari, OT, Järvelin, MR, Würtz, P, Kettunen, J and Ala-Korpela, M (2015) Sex hormone-binding globulin associations with circulating lipids and metabolites and the risk for type 2 diabetes: observational and causal effect estimates. International Journal of Epidemiology 44, 623637.Google Scholar
Würtz, P, Cook, S, Wang, Q, Tiainen, M and Tynkkynen, T (2016) Metabolic profiling of alcohol consumption in 9778 young adults. International Journal of Epidemiology 45, 14931506.Google Scholar
Würtz, P, Havulinna, AS, Soininen, P, Tynkkynen, T, Prieto-Merino, D, Tillin, T, Ghorbani, A, Artati, A, Wang, Q, Tiainen, M, Kangas, AJ, Kettunen, J, Kaikkonen, J, Mikkilä, V, Jula, A, Kähönen, M, Lehtimäki, T, Lawlor, DA, Gaunt, TR, Hughes, AD, Sattar, N, Illig, T, Adamski, J, Wang, TJ, Perola, M, Ripatti, S, Vasan, RS, Raitakari, OT, Gerszten, RE, Casas, JP, Chaturvedi, N, Ala-Korpela, M and Salomaa, V (2015) Metabolite profiling and cardiovascular event risk: a prospective study of 3 population-based cohorts. Lippincott Williams and Wilkins Circulation 131, 774785.Google Scholar
Würtz, P, Mäkinen, VP, Soininen, P, Kangas, AJ, Tukiainen, T, Kettunen, J, Savolainen, MJ, Tammelin, T, Viikari, JS, Rönnemaa, T, Kähönen, M, Lehtimäki, T, Ripatti, S, Raitakari, OT, Järvelin, MR and Ala-Korpela, M (2012) Metabolic signatures of insulin resistance in 7098 young adults. Diabetes 61, 13721380.Google Scholar
Würtz, P, Wang, Q, Kangas, AJ, Richmond, RC, Skarp, J, Tiainen, M, Tynkkynen, T, Soininen, P, Havulinna, AS, Kaakinen, M, Viikari, JS, Savolainen, MJ, Kähönen, M, Lehtimäki, T, Männistö, S, Blankenberg, S, Zeller, T, Laitinen, J, Pouta, A, Mäntyselkä, P, Vanhala, M, Elliott, P, Pietiläinen, KH, Ripatti, S, Salomaa, V, Raitakari, OT, Järvelin, MR, Smith, GD and Ala-Korpela, M (2014) Metabolic signatures of adiposity in young adults: Mendelian randomization analysis and effects of weight change. PLoS Medicine 11, e1001765.Google Scholar
Yang, J, Chen, T, Sun, L, Zhao, Z, Qi, X, Zhou, K, Cao, Y, Wang, X, Qiu, Y, Su, M, Zhao, A, Wang, P, Yang, P, Wu, J, Feng, G, He, L, Jia, W and Wan, C (2013) Potential metabolite markers of schizophrenia. Molecular Psychiatry 18, 6778.Google Scholar
Zammit, S, Odd, D, Horwood, J, Thompson, A, Thomas, K, Menezes, P, Gunnell, D, Hollis, C, Wolke, D, Lewis, G and Harrison, G (2009) Investigating whether adverse prenatal and perinatal events are associated with non-clinical psychotic symptoms at age 12 years in the ALSPAC birth cohort. Psychological Medicine 39, 14571467.Google Scholar
Supplementary material: Image

Ramsay et al. supplementary material

Ramsay et al. supplementary material 1

Download Ramsay et al. supplementary material(Image)
Image 2 MB
Supplementary material: Image

Ramsay et al. supplementary material

Ramsay et al. supplementary material 2

Download Ramsay et al. supplementary material(Image)
Image 2 MB
Supplementary material: Image

Ramsay et al. supplementary material

Ramsay et al. supplementary material 3

Download Ramsay et al. supplementary material(Image)
Image 2 MB
Supplementary material: Image

Ramsay et al. supplementary material

Ramsay et al. supplementary material 4

Download Ramsay et al. supplementary material(Image)
Image 2 MB