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Updated: Mar 31, 2026

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
Published on: May 6, 2022
Practical Experience of the Application of a Weighted Burden Test to Whole Exome Sequence Data for Obesity and
1UCL Genetics Institute, UCL, Darwin Building, Gower Street, London, WC1E 6BT, UK.
Abstract:
For biological and statistical reasons it makes sense to combine information from variants at the level of the gene. One may wish to give more weight to variants which are rare and those that are more likely to affect function. A combined weighting scheme, implemented in the SCOREASSOC program, was applied to whole exome sequence data for 1392 subjects with schizophrenia and 982 with obesity from the UK10K project. Results conformed fairly well with null hypothesis expectations and no individual gene was strongly implicated. However, a number of the higher ranked genes appear plausible candidates as being involved in one or other phenotype and may warrant further investigation. These include MC4R, NLGN2, CRP, DONSON, GTF3A, IL36B, ADCYAP1R1, ARSA, DLG1, SIK2, SLAIN1, UBE2Q2, ZNF507, CRHR1, MUSK, NSF, SNORD115, GDF3 and HIBADH. Some individual variants in these genes have different frequencies between cohorts and could be genotyped in additional subjects. For other genes, there is a general excess of variants at many different sites so attempts at replication would be more difficult. Overall, the weighted burden test provides a convenient method for using sequence data to highlight genes of interest.
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