Biomedical subjects

Laurie J Hannigan

Publications and source records attributed to Laurie J Hannigan.

3 recordsLinked to original sources

PubMed2026

Family genetic designs in MoBa provide insights into health and functioning.

Genome-wide association studies using large, population-based samples of unrelated individuals have discovered thousands of genetic associations with health and disease1. These studies can help explain genetic and environmental risks. However, increasing evidence suggests that population-based estimates, while precise, can also reflect confounding that affects their use and interpretation. This confounding can be overcome using data from genotyped family members, such as nuclear mother-father-child trios2,3. However, samples of genotyped families are rare4-11. Here we illustrate some of the advantages of familial data using the Norwegian Mother, Father and Child Cohort Study (MoBa), a population-based cohort of parents and offspring with extensive genotype data (n ≈ 230,000) (ref. 3), along with broad and longitudinal phenotyping of health and functioning. We provide an overview of MoBa and describe the quality control of genotype data tailored to this extensively related sample. We then use trio data to illustrate how family-based genomic designs can identify distinct direct and indirect sources of genetic influence and structural confounding. As examples, we analyse children's height, educational achievement, depressive symptoms and sleep duration. These demonstrations highlight MoBa as a broadly valuable resource for advancing understanding of health and functioning across the lifecourse and generations.

Journal Article↗

PubMed2026

The reporting and handling of missing data in genetic epidemiological studies of mental health in childhood and adolescence: A systematic review.

BACKGROUND: Genetic epidemiological analyses of child and adolescent mental health often use data from prospective longitudinal cohorts. Missingness due to selective attrition is therefore an important potential source of bias in such analyses. Informatively reporting on missingness and taking appropriate steps to handle it in analyses can mitigate this potential bias. Here, we aim to systematically assess how researchers report and address missingness in genetic epidemiological studies of child and adolescent mental health-related outcomes using cohort data. METHODS: We systematically searched the Ovid Medline database for studies published between August 2012 and August 2025, reporting polygenic score, genome-wide association, or Mendelian randomization analyses, of data on children or adolescents participating in cohort studies. We extracted information from eligible studies based on criteria adapted from the strengthening and reporting of observational studies in epidemiology (STROBE) guidelines. RESULTS: A total of 133 eligible studies were included, of which 125 (93.98%) reported the number of complete cases in all waves, while 84 (63.16%) detailed the amount of missingness on all key variables. Most studies used complete case analysis, while 39 studies explicitly reported applying other methods to handle missingness, with multiple imputation (n = 20, 15.04%) being the most common, followed by full information maximum likelihood 10 (8.1%). Only 18 studies (13.53%) reported an assumed missing mechanism along with the method used to address missingness. Full reporting of both the extent and handling of missingness at the item level was rare, occurring in only 5 (3.76%) and 15 (11.28%) studies, respectively, among the 123 studies that used multi-item instruments. CONCLUSION: Best practice recommendations for reporting on missing data handling emphasize the importance of detailing the proportion of missingness, types of mechanisms underpinning missingness, and details of approaches used. Based on this review, these recommendations for proper reporting of missing data are rarely followed in full.

children and adolescents↗

PubMed2025

Genome-wide association study of adolescent-onset depression.

Adolescent depression is a heritable psychiatric condition with rising global prevalence and severe long-term outcomes, yet its biological underpinnings remain poorly understood. We conducted the first genome-wide association study of adolescent-onset depression, comprising 102,428 cases (diagnosis or clinical symptom thresholds) and 286,911 controls, including diverse ancestries. Cross-ancestry meta-analysis identified 52 independent variants across 17 loci; European-only analysis found 61 variants at 29 loci, with a SNP-based heritability of 9.8%. Comparative analyses revealed two genes unique to adolescent-onset versus lifetime depression, enriched in neuronal subtypes, and two genes as potential drug repurposing targets. Polygenic scores were associated with adolescent-onset depression across ancestries, persistent depression trajectories, more severe outcomes, as well as reduced cortical volume, surface area and white matter integrity. Genetic correlation and Mendelian randomisation analyses support shared genetic liability and causal links with early puberty and modifiable health and behavioural risk factors. These findings uncover novel genetic loci and refine biological pathways underlying adolescent-onset depression, revealing age-specific mechanisms and early intervention opportunities.

Journal Article↗