Alexandra C Gillett1, Evangelos Vassos1, Cathryn M Lewis2,3. 1. Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom. 2. Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom, cathryn.lewis@kcl.ac.uk. 3. Department of Medical and Molecular Genetics, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom, cathryn.lewis@kcl.ac.uk.
Abstract
OBJECTIVE: Stratified medicine requires models of disease risk incorporating genetic and environmental factors. These may combine estimates from different studies, and the models must be easily updatable when new estimates become available. The logit scale is often used in genetic and environmental association studies; however, the liability scale is used for polygenic risk scores and measures of heritability, but combining parameters across studies requires a common scale for the estimates. METHODS: We present equations to approximate the relationship between univariate effect size estimates on the logit scale and the liability scale, allowing model parameters to be translated between scales. RESULTS: These equations are used to build a risk score on the liability scale, using effect size estimates originally estimated on the logit scale. Such a score can then be used in a joint effects model to estimate the risk of disease, and this is demonstrated for schizophrenia using a polygenic risk score and environmental risk factors. CONCLUSION: This straightforward method allows the conversion of model parameters between the logit and liability scales and may be a key tool to integrate risk estimates into a comprehensive risk model, particularly for joint models with environmental and genetic risk factors.
OBJECTIVE: Stratified medicine requires models of disease risk incorporating genetic and environmental factors. These may combine estimates from different studies, and the models must be easily updatable when new estimates become available. The logit scale is often used in genetic and environmental association studies; however, the liability scale is used for polygenic risk scores and measures of heritability, but combining parameters across studies requires a common scale for the estimates. METHODS: We present equations to approximate the relationship between univariate effect size estimates on the logit scale and the liability scale, allowing model parameters to be translated between scales. RESULTS: These equations are used to build a risk score on the liability scale, using effect size estimates originally estimated on the logit scale. Such a score can then be used in a joint effects model to estimate the risk of disease, and this is demonstrated for schizophrenia using a polygenic risk score and environmental risk factors. CONCLUSION: This straightforward method allows the conversion of model parameters between the logit and liability scales and may be a key tool to integrate risk estimates into a comprehensive risk model, particularly for joint models with environmental and genetic risk factors.
Authors: Evangelos Vassos; Pak Sham; Matthew Kempton; Antonella Trotta; Simona A Stilo; Charlotte Gayer-Anderson; Marta Di Forti; Cathryn M Lewis; Robin M Murray; Craig Morgan Journal: Psychol Med Date: 2019-09-19 Impact factor: 7.723
Authors: Henriette Thisted Horsdal; Esben Agerbo; John Joseph McGrath; Bjarni Jóhann Vilhjálmsson; Sussie Antonsen; Ane Marie Closter; Allan Timmermann; Jakob Grove; Pearl L H Mok; Roger T Webb; Clive Eric Sabel; Ole Hertel; Torben Sigsgaard; Christian Erikstrup; David Michael Hougaard; Thomas Werge; Merete Nordentoft; Anders Dupont Børglum; Ole Mors; Preben Bo Mortensen; Jørgen Brandt; Camilla Geels; Carsten Bøcker Pedersen Journal: JAMA Netw Open Date: 2019-11-01