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Multiple-testing corrections in case-control studies using identity-by-descent segments.

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Summary
This summary is machine-generated.

This study introduces a novel Identity-by-descent (IBD) mapping statistic to improve Alzheimer's disease (AD) risk locus discovery. The method controls false discoveries and identifies six potential AD risk loci, advancing genetic research in complex diseases.

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Alzheimer’s diseasebinary traitshaplotypesidentity by descentmean-reverting processesmultiple testing

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Area of Science:

  • Genetics
  • Genomic analysis
  • Statistical genetics

Background:

  • Identity-by-descent (IBD) mapping complements genome-wide association studies (GWAS) for detecting complex genetic architectures.
  • Uncorrected multiple testing in case-control IBD studies can lead to false positive findings.

Purpose of the Study:

  • To develop a robust IBD mapping statistic and hypothesis test to control the family-wise error rate (FWER).
  • To identify novel Alzheimer's disease (AD) risk loci using genome-wide data.
  • To integrate IBD mapping with selection scans to mitigate confounding factors like population structure.

Main Methods:

  • Proposed a novel IBD mapping statistic based on the difference between case-case and control-control IBD rates.
  • Utilized a computationally efficient stochastic process approach to derive genome-wide significance levels controlling FWER.
  • Developed automated workflows for haplotype phasing, local ancestry calling, and IBD mapping scans.
  • Paired IBD mapping with selection scans to account for confounding effects.

Main Results:

  • Whole genome simulations confirmed conservative control of the FWER.
  • Identified six genome-wide significant signals for AD risk in diverse populations.
  • Detected variants within these loci previously associated with AD, dementia, and memory decline.
  • Found three genes at two loci nominated as therapeutic targets.

Conclusions:

  • The developed IBD mapping method offers a scalable and reproducible approach for genetic discovery.
  • This method effectively utilizes large consortia resources to uncover disease-associated loci.
  • The identified loci and genes provide new avenues for understanding AD pathogenesis and developing therapies.