Research Internship: characterising genomic and phenotypic structures in sub-groups of individuals with autism spectrum disorder

Internship
Population Genetics of Human Communication

The Max Planck Institute (MPI) for Psycholinguistics, Nijmegen, the Netherlands, is offering a 5-to-10-month MSc internship position in the Population Genetics of Human Communication research group (PGHC). The host research group, led by Dr. Beate St Pourcain, is embedded within the Language & Genetics Department at the MPI. Research within the group focuses on (i) studying the genetic basis of social communication, language and interaction in population-based and clinical cohorts and (ii) developing statistical modelling approaches. The internship duration is flexible but lies between 5 to 10 months.

Job description

In this biostatistics research internship, you will disentangle differences in clinical phenotype presentations of Autism Spectrum Disorder (ASD) by studying the genetic and/or phenotypic factor structures in autistic individuals. ASD is a phenotypically and genetically highly heterogeneous neurodevelopmental condition with a substantial genetic component (twin heritability ~80%) (1). Core diagnostic features include difficulties in social communication and interaction and restricted, repetitive behaviour, as well as sensory abnormalities (1). Previous studies investigated heterogeneity in autism at the phenotypic level (2). Within our group, we study this heterogeneity at the genomic level (3), investigating aggregate variation across millions of markers as captured by genotyping chips. While phenotypic and genomic structures are often similar (4), this is not always the case (5). In this project, expanding previous work (3), you will apply different structural equation modelling approaches to identify phenotypic and genomic structures. You will study autistic individuals from a large US cohort and apply state-of-the-art statistical genetic analysis methods, such as GREML and/or GRM-SEM (6,7) (familiarity with these methods is not a requirement) and compare structures across different subgroups of individuals with autism. You will also learn how to work within a Linux environment and gain experience with coding in R and bash.

 

Requirements

  • MSc student enrolled on a Master's programme such as Cognitive Neuroscience, Medical Biology, Biomedical Sciences, Computing Science, Statistics or similar
  • Bachelor-level knowledge of Statistics and/or Genetics
  • Bachelor-level programming expertise (e.g. R or Linux) is an advantage
  • Good knowledge of English

 

What we offer you

  • Experience with structural equation modelling techniques
  • Experience with modelling "big genomic data" with genomic tools
  • A nice team

 

Application procedure

  • The internship will last at least five months; the starting date is negotiable. Note that the MPI cannot remunerate any work during this internship. Applications will be reviewed until the position has been filled.
  • To apply, please submit your motivation letter (max. 1 page) and a CV and contact details via this link on our application portal. For further information, please get in touch with Dr Beate St Pourcain (beate.stpourcain [at] mpi.nl (beate[dot]stpourcain[at]mpi[dot]nl))

 

References

1. Lord C, Brugha TS, Charman T, Cusack J, Dumas G, Frazier T, et al. Autism spectrum disorder. Nat Rev Dis Primers. 2020 Jan 16;6(1):1–23.

2. Warrier V, Zhang X, Reed P, Havdahl A, Moore TM, Cliquet F, et al. Genetic correlates of phenotypic heterogeneity in autism. Nat Genet. 2022 Sep;54(9):1293–304.

3. de Hoyos L, Barendse MT, Schlag F, Donkelaar MM van, Verhoef E, Shapland CY, et al. Structural models of genome-wide covariance identify multiple common dimensions in autism. medRxiv. 2022 Oct;

4. Cheverud JM. A Comparison of Genetic and Phenotypic Correlations. Evolution. 1988;42(5):958–68.

5. Williams CM, Peyre H, Wolfram T, Lee YH, Ge T, Smoller JW, et al. Characterizing the phenotypic and genetic structure of psychopathology in UK Biobank. medRxiv. 2023 Sep;

6.  St Pourcain B, Eaves LJ, Ring SM, Fisher SE, Medland S, Evans DM, et al. Developmental Changes Within the Genetic Architecture of Social Communication Behavior: A Multivariate Study of Genetic Variance in Unrelated Individuals. Biological Psychiatry. 2018 Apr 1;83(7):598–606.

7.  Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: A Tool for Genome-wide Complex Trait Analysis. The American Journal of Human Genetics. 2011 Jan 7;88(1):76–82.

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