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Parent-offspring regression to estimate the heritability of an HIV-1 trait in a realistic setup


Bachmann, Nadine; Turk, Teja; Kadelka, Claus; Marzel, Alex; Shilaih, Mohaned; Böni, Jürg; Aubert, Vincent; Klimkait, Thomas; Leventhal, Gabriel E; Günthard, Huldrych F; Kouyos, Roger; Swiss HIV Cohort Study (2017). Parent-offspring regression to estimate the heritability of an HIV-1 trait in a realistic setup. Retrovirology, 14(1):33.

Abstract

Background: Parent-offspring (PO) regression is a central tool to determine the heritability of phenotypic traits; i.e., the relative extent to which those traits are controlled by genetic factors. The applicability of PO regression to viral traits is unclear because the direction of viral transmission—who is the donor (parent) and who is the recipient (offspring)—is typically unknown and viral phylogenies are sparsely sampled.
Methods: We assessed the applicability of PO regression in a realistic setting using Ornstein–Uhlenbeck simulated data on phylogenies built from 11,442 Swiss HIV Cohort Study (SHCS) partial pol sequences and set-point viral load (SPVL) data from 3293 patients.
Results: We found that the misidentification of donor and recipient plays a minor role in estimating heritability and showed that sparse sampling does not influence the mean heritability estimated by PO regression. A mixed-effect model approach yielded the same heritability as PO regression but could be extended to clusters of size greater than 2 and allowed for the correction of confounding effects. Finally, we used both methods to estimate SPVL heritability in the SHCS. We employed a wide range of transmission pair criteria to measure heritability and found a strong dependence of the heritability estimates to these criteria. For the most conservative genetic distance criteria, for which heritability estimates are conceptually expected to be closest to true heritability, we found estimates ranging from 32 to 46% across different bootstrap criteria. For less conservative distance criteria, we found estimates ranging down to 8%. All estimates did not change substantially after adjusting for host-demographic factors in the mixed-effect model (±2%).
Conclusions: For conservative transmission pair criteria, both PO regression and mixed-effect models are flexible and robust tools to estimate the contribution of viral genetic effects to viral traits under real-world settings. Overall, we find a strong effect of viral genetics on SPVL that is not confounded by host demographics.

Abstract

Background: Parent-offspring (PO) regression is a central tool to determine the heritability of phenotypic traits; i.e., the relative extent to which those traits are controlled by genetic factors. The applicability of PO regression to viral traits is unclear because the direction of viral transmission—who is the donor (parent) and who is the recipient (offspring)—is typically unknown and viral phylogenies are sparsely sampled.
Methods: We assessed the applicability of PO regression in a realistic setting using Ornstein–Uhlenbeck simulated data on phylogenies built from 11,442 Swiss HIV Cohort Study (SHCS) partial pol sequences and set-point viral load (SPVL) data from 3293 patients.
Results: We found that the misidentification of donor and recipient plays a minor role in estimating heritability and showed that sparse sampling does not influence the mean heritability estimated by PO regression. A mixed-effect model approach yielded the same heritability as PO regression but could be extended to clusters of size greater than 2 and allowed for the correction of confounding effects. Finally, we used both methods to estimate SPVL heritability in the SHCS. We employed a wide range of transmission pair criteria to measure heritability and found a strong dependence of the heritability estimates to these criteria. For the most conservative genetic distance criteria, for which heritability estimates are conceptually expected to be closest to true heritability, we found estimates ranging from 32 to 46% across different bootstrap criteria. For less conservative distance criteria, we found estimates ranging down to 8%. All estimates did not change substantially after adjusting for host-demographic factors in the mixed-effect model (±2%).
Conclusions: For conservative transmission pair criteria, both PO regression and mixed-effect models are flexible and robust tools to estimate the contribution of viral genetic effects to viral traits under real-world settings. Overall, we find a strong effect of viral genetics on SPVL that is not confounded by host demographics.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Institute of Medical Virology
04 Faculty of Medicine > University Hospital Zurich > Clinic for Infectious Diseases
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:23 May 2017
Deposited On:31 Oct 2017 14:18
Last Modified:19 Aug 2018 10:58
Publisher:BioMed Central
ISSN:1742-4690
OA Status:Gold
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1186/s12977-017-0356-3
PubMed ID:28535768
Project Information:
  • : FunderSNSF
  • : Grant ID324730_159868
  • : Project TitleHIV-1 Transmission in Switzerland: viral transmission traits, superinfection and drug resistance
  • : FunderFP7
  • : Grant ID265280
  • : Project TitleKULTURISK - Knowledge-based approach to develop a cULTUre of Risk prevention
  • : FunderFP7
  • : Grant ID213569
  • : Project TitleCESAR - CO2 Enhanced Separation and Recovery
  • : FunderFP7
  • : Grant ID212470
  • : Project TitleHYCYCLES - Materials and components for Hydrogen production by sulphur based thermochemical cycles
  • : FunderFP7
  • : Grant ID256830
  • : Project TitleHITECO - New solar collector concept for high temperature operation in CSP applications
  • : FunderFP7
  • : Grant ID223131
  • : Project TitleCHAIN - Collaborative HIV and Anti-HIV Drug Resistance Network

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