This week’s Said&Dunn post is by guest blogger, Megan Skelton. Megan is a PhD student at King’s College London in the Social, Genetic Developmental & Psychiatry Centre. She is interested in investigating how genetic, clinical and demographic factors predict response to psychological therapies for adult depression and anxiety disorders, within the NHS “Increasing Access to Psychological Therapy” program.
This post is adapted from the original post by Megan Skelton from The Mental Elf, National Elf Service Blog.
Depression is a common and debilitating mental health condition. Although the average age of onset is early- to mid-twenties, there is quite a wide range, and some research suggests that early onset depression is associated with specific characteristics. For example, early onset depression may have a higher likelihood of showing a more chronic course (continuously experiencing symptoms), greater symptom severity, and may also be influenced by different risk factors. The focus of this paper was to explore the extent to which genetic influences might be useful in understanding differences in risk for early and later onset of depression in adolescence.
A polygenic score captures the degree of known genetic variants an individual has that have been associated with a particular disorder. Individuals with depression will usually have a higher polygenic score for depression than those without it. However, a previous study indicated that earlier onset depression has a stronger association with a polygenic score for schizophrenia than later onset depression does. The authors of the current paper therefore wished to investigate whether polygenic scores influence depression trajectories. They also investigated polygenic scores for Attention Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder that has high comorbidity and a genetic correlation with depression.
Individuals from the Avon Longitudinal Study of Parents and Children (ALSPAC) completed depression symptom questionnaires up to six times between the ages of 10.5 years and 18.5 years. A statistical analysis was performed to find groups or ‘classes’ of symptom trajectories. Next, associations were explored between these groups and the polygenic scores for depression, ADHD and schizophrenia, as well as diagnoses of neurodevelopmental difficulties (ADHD, social communication problems, pragmatic language difficulties).
There were three classes of trajectories, the number in the brackets indicates the proportion of individuals who fell into the class:
1. Persistently low (73.7%) – low risk of depression
2. Early-adolescence-onset (9.0%) – first elevated risk of clinically significant depression at age 12 years
3. Later-adolescence-onset (17.3%) – first elevated risk of clinically significant depression at age 16.5 years.
Early-adolescent onset depression was strongly associated with polygenic scores for schizophrenia and ADHD, and less strongly with polygenic scores for depression. This trajectory class was significantly associated with diagnoses of childhood ADHD, social communication and pragmatic language difficulties, and individuals displayed higher rates of these difficulties compared to those in the other classes.
In contrast, later-adolescent onset depression was strongly associated with polygenic scores for depression only, not with genetic scores for schizophrenia or ADHD. There were significant associations between this trajectory and pragmatic language difficulties, but not ADHD or social communication diagnoses.
Overall, these results suggest that individuals with neurodevelopmental difficulties may be at an increased risk of depression due to genetic overlap, or the difficulties they face in their environment as a result of their difficulties e.g. peer rejection.
Depression which begins later in adolescence is most strongly associated with genetic risk of depression, whereas earlier adolescent onset is associated with a broader range of genetic risks – schizophrenia, ADHD and depression.
Strengths and limitations
This paper presents an interesting combination of using polygenic scores in the context of longitudinal developmental data. It would be useful to also explore the degree of social adversity experienced by these groups and take this into account in the analyses, given evidence that individuals with depression first diagnosed before the age of 11 years have far higher levels of social adversity and risk compared to later onset. One other aspect to note is that as the data were collected over several years there is a risk of non-random drop-out in participants, especially of those with more severe mental health problems.
Implications for practice
Polygenic scores could be combined with neurodevelopmental assessments to determine the likelihood and trajectory of depression. These subtypes of depression, based on trajectory, may respond to treatment differently.