Periodic Reporting for period 4 - MHINT (Genetic, behavioural and cognitive mechanisms underpinning the association between mother and offspring mental health problems: mental (M) health (H) intergenerational transmission (INT) -(MHINT))
Okres sprawozdawczy: 2021-09-01 do 2023-02-28
Despite decades of research, and the introduction of parenting interventions, children of mentally ill mothers remain substantially more likely to have mental health problems themselves. I propose to shed new light on why mental health problems in a mother are passed on to her child, and help break this reinforcing cycle of mental health risk across generations. In order to harness the potential of modifying parenting for the prevention of child mental health risk, I will study parenting using more detailed, ecologically valid and genetically sensitive designs than have been done before.
Objectives: 1: To investigate the respective role of genetic and environmental (chiefly parenting) mechanisms in explaining associations between mother and child mental health. HOW: using a consortium of international cohorts with intergenerational genetic and phenotypic data (n>10,000) and, for the first time, modelling genetic risk which is and is not transmitted from mother to child to test alternative hypotheses. 2: To identify behavioural manifestation of maternal mental health, in observed mother-infant interaction, in an ecologically valid way. HOW: recording 300 mother- child dyads at home, using novel wearable cameras, in the next generation of a key cohort (ALSPAC-G2). 3: To identify cognitive underpinnings of maternal behaviour. HOW: including cognitive tasks (with eye tracking) as new measures in ALSPAC-G2, applying computational models to cognitive and (uniquely) real life data (measured in 2). 4: To establish whether modification of maternal parenting (highlighted in 1-3), changes child mental health. HOW: systematic review of parenting intervention trials and new synthesis methods to extract which intervention components reduce child mental health problems.
My study will provide critical new evidence regarding the nature of parenting interventions that have potential to improve child mental health and break intergenerational transmission of mental health problems
Objectives: 1: To investigate the respective role of genetic and environmental (chiefly parenting) mechanisms in explaining associations between mother and child mental health. HOW: using a consortium of international cohorts with intergenerational genetic and phenotypic data (n>10,000) and, for the first time, modelling genetic risk which is and is not transmitted from mother to child to test alternative hypotheses. 2: To identify behavioural manifestation of maternal mental health, in observed mother-infant interaction, in an ecologically valid way. HOW: recording 300 mother- child dyads at home, using novel wearable cameras, in the next generation of a key cohort (ALSPAC-G2). 3: To identify cognitive underpinnings of maternal behaviour. HOW: including cognitive tasks (with eye tracking) as new measures in ALSPAC-G2, applying computational models to cognitive and (uniquely) real life data (measured in 2). 4: To establish whether modification of maternal parenting (highlighted in 1-3), changes child mental health. HOW: systematic review of parenting intervention trials and new synthesis methods to extract which intervention components reduce child mental health problems.
My study will provide critical new evidence regarding the nature of parenting interventions that have potential to improve child mental health and break intergenerational transmission of mental health problems
Work Package 1
We have developed latent parenting factors across 3 domains and age ranges using ALPAC which predict later outcomes, we have published one of these papers in the European Child and Adolescent Psychiatry and biorxiv https://www.biorxiv.org/content/10.1101/509513v1.abstract. Four further papers are in the submission process, including our analyses demonstrating that specific parenting behaviours mediate the association between maternal and offspring depression at age 24.We have completed the parsing of genetic data across the entire genome in ALSPAC, this is being written up as a data note for ALSPAC and the completed datasets released back into the resource. We are working closely with MobA, Generation Scotland, Millennium Cohort, we have set up a consortium following a further workshop, for further collaborations. We have published one initial paper looking at the associations between genetic risk factors and later offspring depression. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2736940. We have pulled together international cohorts with genetic data to conduct a meta analyses on untransmitted genetic effects for >30,000 families. We have published 4 papers looking at genetic links to mental health. We have also demonstrated evocative effects using genetic similarity scores.
Work Package 2
Following 2 very successfully internationally attended workshop we confirmed new mental health measures in the second generation of ALSPAC including impulsivity, social support and further depression. We also established a video collection protocol as demonstrated in this video https://www.youtube.com/watch?v=eXuCSXKXteY&feature=youtu.be> 100 families have already provided video data. We have a completed the development of an in-depth coding system in observer XT and development of a comprehensive manual for micro-coding, including 4 subjects, 27 behavioural categories, 34 modifier categories and have already coded in depth 25 families.
We have carefully devised a maternally adapted bandit computerised task in python and already collected proof of principle data on 30 subjects and applied existing modelling. This was presented by the ERC funded PhD student at a poster session on results of the pilot of cognitive task at “Theory and Practice of Bayesian Hypothesis Testing: A JASP Workshop” (22/08/2019) Poster session on results of the pilot of cognitive task at “Ninth Annual JAGS and WinBUGS Workshop Bayesian Modelling for Cognitive Science” (27/08/2019) We have also utilised the second generation mental health data and initial paper reporting the prevalence of antenatal depression in the ALSPAC-G2 young women compared to those in the 1990s, it received global media attention including a live interview by the PI on BBC breakfast , and citation in policy documents https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2687389. We have pulled together international cohorts with genetic data to conduct a meta analyses on untransmitted genetic effects for >30,000 families.
We have also linked perinatal mental health data to preconception psychological variables and have an invited paper to Frontiers of Psychology to report these data which is now published, we conducted training in observed measures in South Africa , Sri Lanka and Brazil , local teams are planning to conduct pilot studies (locally funded) using similar methods and funded by 2 Wellcome Trust fellowships linked to the program. Our coding system is being adopted by these teams and the Little in Norway study in Oslo. The team have grown in capacity with 5 postdocs and 4 PhD students developing novel methods. We have worked with an industry partner https://www.kinneirdufort.com/ to co-produce a new user friendly wearable head camera to improve data collection. We have also developed automated techniques to process facial expressions .
Work Package 3
We have completed a review protocol which is published , we have selected over 100 studies and are in the data extraction process.
We have developed latent parenting factors across 3 domains and age ranges using ALPAC which predict later outcomes, we have published one of these papers in the European Child and Adolescent Psychiatry and biorxiv https://www.biorxiv.org/content/10.1101/509513v1.abstract. Four further papers are in the submission process, including our analyses demonstrating that specific parenting behaviours mediate the association between maternal and offspring depression at age 24.We have completed the parsing of genetic data across the entire genome in ALSPAC, this is being written up as a data note for ALSPAC and the completed datasets released back into the resource. We are working closely with MobA, Generation Scotland, Millennium Cohort, we have set up a consortium following a further workshop, for further collaborations. We have published one initial paper looking at the associations between genetic risk factors and later offspring depression. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2736940. We have pulled together international cohorts with genetic data to conduct a meta analyses on untransmitted genetic effects for >30,000 families. We have published 4 papers looking at genetic links to mental health. We have also demonstrated evocative effects using genetic similarity scores.
Work Package 2
Following 2 very successfully internationally attended workshop we confirmed new mental health measures in the second generation of ALSPAC including impulsivity, social support and further depression. We also established a video collection protocol as demonstrated in this video https://www.youtube.com/watch?v=eXuCSXKXteY&feature=youtu.be> 100 families have already provided video data. We have a completed the development of an in-depth coding system in observer XT and development of a comprehensive manual for micro-coding, including 4 subjects, 27 behavioural categories, 34 modifier categories and have already coded in depth 25 families.
We have carefully devised a maternally adapted bandit computerised task in python and already collected proof of principle data on 30 subjects and applied existing modelling. This was presented by the ERC funded PhD student at a poster session on results of the pilot of cognitive task at “Theory and Practice of Bayesian Hypothesis Testing: A JASP Workshop” (22/08/2019) Poster session on results of the pilot of cognitive task at “Ninth Annual JAGS and WinBUGS Workshop Bayesian Modelling for Cognitive Science” (27/08/2019) We have also utilised the second generation mental health data and initial paper reporting the prevalence of antenatal depression in the ALSPAC-G2 young women compared to those in the 1990s, it received global media attention including a live interview by the PI on BBC breakfast , and citation in policy documents https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2687389. We have pulled together international cohorts with genetic data to conduct a meta analyses on untransmitted genetic effects for >30,000 families.
We have also linked perinatal mental health data to preconception psychological variables and have an invited paper to Frontiers of Psychology to report these data which is now published, we conducted training in observed measures in South Africa , Sri Lanka and Brazil , local teams are planning to conduct pilot studies (locally funded) using similar methods and funded by 2 Wellcome Trust fellowships linked to the program. Our coding system is being adopted by these teams and the Little in Norway study in Oslo. The team have grown in capacity with 5 postdocs and 4 PhD students developing novel methods. We have worked with an industry partner https://www.kinneirdufort.com/ to co-produce a new user friendly wearable head camera to improve data collection. We have also developed automated techniques to process facial expressions .
Work Package 3
We have completed a review protocol which is published , we have selected over 100 studies and are in the data extraction process.
We have already identified components of parenting that mediate associations between parental and offspring depression , established a novel and detailed mirco-coding observer system and protocol to collect home videos this will make real progress in understanding parenting. We have developed a new bespoke wearble camera with our industry partner and novel coding methods.
We have established methods to explore the role of genetic associations and established collaborations we expect to make an important step change in our understanding of how maternal depression influences offspring.
We have established methods to explore the role of genetic associations and established collaborations we expect to make an important step change in our understanding of how maternal depression influences offspring.