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Predicting Consanguinity Rates from Exome Sequencing Data in the Lebanese Population.

Eileen Marie Hanna1, Cybel Mehawej2, Joelle Assy1

  • 1Department of Computer Science and Mathematics, Lebanese American University, Byblos, Lebanon.

The Journal of Molecular Diagnostics : JMD
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Consanguineous marriages increase genetic disorder risk. This study developed a model using exome sequencing data to predict consanguinity status in Lebanese individuals, achieving 94% accuracy.

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Area of Science:

  • Genetics
  • Population Health

Background:

  • Consanguinity, common in Lebanon (35.5%), elevates the risk of autosomal recessive genetic disorders.
  • Predicting consanguinity is crucial for genetic counseling and risk assessment in high-prevalence populations.

Purpose of the Study:

  • To develop a predictive model for consanguinity status using total runs of homozygosity (ROH) size from exome sequencing data.
  • To establish population-specific thresholds for assessing consanguinity in Lebanese individuals.

Main Methods:

  • Analysis of exome sequencing data from 784 Lebanese individuals to detect runs of homozygosity (ROH) using AutoMap.
  • Development of logistic regression models to predict consanguinity status based on total ROH size, with accuracy assessed on 521 individuals.

Main Results:

  • A logistic regression model excluding outliers achieved 94% accuracy in predicting consanguinity status.
  • Specific ROH thresholds were defined: nonconsanguineous (<40.28 Mb), uncertain (40.28–79.17 Mb), probable consanguinity (79.18–118.06 Mb), and consanguineous (>118.06 Mb).

Conclusions:

  • The study presents a valuable tool for clinical genetics in populations with high consanguinity rates.
  • The findings highlight the importance of population-specific ROH thresholds for accurate consanguinity assessment and genetic risk evaluation.