Leveraging population admixture to characterize the heritability of complex traits.

paper Cited Public

Authors: Zaitlen, Noah; Pasaniuc, Bogdan; Sankararaman, Sriram; Bhatia, Gaurav; Zhang, Jianqi; Gusev, Alexander; Young, Taylor; Tandon, Arti; Pollack, Samuela; Vilhjálmsson, Bjarni J; Assimes, Themistocles L; Berndt, Sonja I; Blot, William J; Chanock, Stephen; Franceschini, Nora; Goodman, Phyllis G; He, Jing; Hennis, Anselm J M; Hsing, Ann; Ingles, Sue A; Isaacs, William; Kittles, Rick A; Klein, Eric A; Lange, Leslie A; Nemesure, Barbara; Patterson, Nick; Reich, David; Rybicki, Benjamin A; Stanford, Janet L; Stevens, Victoria L; Strom, Sara S; Whitsel, Eric A; Witte, John S; Xu, Jianfeng; Haiman, Christopher; Wilson, James G; Kooperberg, Charles; Stram, Daniel; Reiner, Alex P; Tang, Hua; Price, Alkes L
Year: 2014
Journal: Nature genetics
PMID: 25383972
DOI: 10.1038/ng.3139
PMCID: PMC4244251

Figure 1

Relationships between genetic distance and phenotype for a trait with heritability = 80%. (a) The phenotypic covariance of pairs of individuals at different expected fractions of genome shared IBD is 0.8*%IBD. (b) Regression of genetic distance estimated from genetic variation against the product phenotypes normalized to have mean 0.0 and variance 1.0 has coefficient 0.79 (se = 0.014). (c) Regression of genetic distance estimated from local ancestry variation against normalized phenotypes has coefficient 0.033 (s.e. = 0.007) ≈2FSTCθ(1−θ)h2= 0.032, corresponding to h2 = 0.83 (s.e. = 0.18).

LLM interpretation

This is a scatter plot showing the relationship between chromosome length (Mb) on the x-axis and heritability from local ancestry per chromosome on the y-axis. Red data points, labeled by chromosome number, are plotted against a positive linear regression line. The data points show a general upward trend, though several chromosomes (e.g., 4, 16, 18) fall near zero regardless of length.

Figure 2

Estimated heritability of height for each chromosome in the CARe data set. The numbers adjacent to each point are the chromosomes. We plot the regression line of h2 per chromosome regressed on chromosome length. We find a strong correlation between chromosome length and height heritability (Pearson correlation = 0.513, weighted p-value = 0.0028).

LLM interpretation

This figure consists of three scatter plots (a, b, and c) with red linear regression lines. Each plot relates a measure of genetic distance or relationship on the x-axis to a phenotypic measure on the y-axis: (a) Genetic Distance (IBD) vs. Phenotypic Covariance, (b) Genetic Relationship (Genotypes) vs. Product of Normalized Phenotypes, and (c) Genetic Relationship (Local Ancestry) vs. Product of Normalized Phenotypes. Plots (a) and (b) show a strong positive linear correlation, while plot (c) shows a much weaker positive correlation.

#	Section	Preview
60	Online Methods — WHI Data Set	Affymetrix 6.0 genotyping and QC filtering of African-American samples from the Women's Health…
61	Online Methods — African American Prostate Cancer Data Set (AAPC)	IlluminaHuman1M-Duov3_B genotyping and QC filtering of African-American samples from the African…
62	Online Methods — Partitioning Heritability across the genome	To estimate the heritability for a particular genomic segment we compute the genetic relatedness…
63	Online Methods — Partitioning Heritability across the genome	We performed both weighted and standard linear regression to assess the relationship between the…

Citation	PMID	DOI	Status
Abecasis, GR, Nature, 2012, An integrated map of genetic variation from 1,092 human genomes	23128226	10.1038/nature11632	Cited
Akylbekova, EL, Circ Arrhythm Electrophysiol, 2009, Clinical correlates and heritability of QT interval duration in blacks: the Jackson Heart Study	19808499	10.1161/CIRCEP.109.858894	Cited
Alexander, DH et al., Genome Res, 2009, Fast model-based estimation of ancestry in unrelated individuals	19648217	10.1101/gr.094052.109	Cited
Bhatia, G et al., Genome Res, 2013, Estimating and interpreting FST: the impact of rare variants	23861382	10.1101/gr.154831.113	Cited
Bhatia, G, Am J Hum Genet, 2011, Genome-wide comparison of African-ancestry populations from CARe and other cohorts reveals signals of natural selection	21907010	10.1016/j.ajhg.2011.07.025	Cited
Chatterjee, N, Nat Genet, 2013, Projecting the performance of risk prediction based on polygenic analyses of genome-wide association studies	23455638	10.1038/ng.2579	Cited
Eichler, EE, Nat Rev Genet, 2010, Missing heritability and strategies for finding the underlying causes of complex disease	20479774	10.1038/nrg2809	Cited
Fox, ER, Am J Cardiol, 2008, Epidemiology, heritability, and genetic linkage of C-reactive protein in African Americans (from the Jackson Heart Study)	18805107	10.1016/j.amjcard.2008.05.049	Cited
Franceschini, N, Am J Hum Genet, 2013, Genome-wide association analysis of blood-pressure traits in African-ancestry individuals reveals common associated genes in African and non-African populations	23972371	10.1016/j.ajhg.2013.07.010	Cited
Freedman, BI, Diabetologia, 2005, Genome-wide scans for heritability of fasting serum insulin and glucose concentrations in hypertensive families	15747111	10.1007/s00125-005-1679-5	Cited
Freedman, ML, Proc Natl Acad Sci U S A, 2006, Admixture mapping identifies 8q24 as a prostate cancer risk locus in African-American men	16945910	10.1073/pnas.0605832103	Cited
Gibson, G, Nat Rev Genet, 2011, Rare and common variants: twenty arguments	22251874	10.1038/nrg3118	Cited
Golan, D et al., Narrowing the gap on heritability of common disease by direct estimation in case-control GWAS, 2013	—	—	—
Haiman, CA, PLoS Genet, 2011, Characterizing genetic risk at known prostate cancer susceptibility loci in African Americans	21637779	10.1371/journal.pgen.1001387	Cited
Hamblin, MT et al., Am J Hum Genet, 2000, Detection of the signature of natural selection in humans: evidence from the Duffy blood group locus	10762551	10.1086/302879	Cited
Hemani, G, Am J Hum Genet, 2013, Inference of the genetic architecture underlying BMI and height with the use of 20,240 sibling pairs	24183453	10.1016/j.ajhg.2013.10.005	Cited
Hernandez, RD, Science, 2011, Classic selective sweeps were rare in recent human evolution	21330547	10.1126/science.1198878	Cited
Hindorff, LA, Proc Natl Acad Sci U S A, 2009, Potential etiologic and functional implications of genome-wide association loci for human diseases and traits	19474294	10.1073/pnas.0903103106	Cited
Hjelmborg, JB, Cancer Epidemiol Biomarkers Prev, 2014, The Heritability of Prostate Cancer in the Nordic Twin Study of Cancer	24812039	10.1158/1055-9965.EPI-13-0568	Cited
Johnson, NA, PLoS Genet, 2011, Ancestral components of admixed genomes in a Mexican cohort	22194699	10.1371/journal.pgen.1002410	Cited
Kolonel, LN, Am J Epidemiol, 2000, A multiethnic cohort in Hawaii and Los Angeles: baseline characteristics	10695593	10.1093/oxfordjournals.aje.a010213	Cited
Lee, SH et al., Am J Hum Genet, 2011, Estimating Missing Heritability for Disease from Genome-wide Association Studies	21376301	10.1016/j.ajhg.2011.02.002	Cited
Lee, SH, Nat Genet, 2012, Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs	22344220	10.1038/ng.1108	Cited
Lee, SH, Nat Genet, 2013, Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs	23933821	10.1038/ng.2711	Cited
Lettre, G, PLoS Genet, 2011, Genome-wide association study of coronary heart disease and its risk factors in 8,090 African Americans: the NHLBI CARe Project	21347282	10.1371/journal.pgen.1001300	Cited
Lynch, M et al., Genetics and analysis of quantitative traits, 1998	—	—	—
Manolio, TA, Nature, 2009, Finding the missing heritability of complex diseases	19812666	10.1038/nature08494	Cited
Maples, BK et al., Am J Hum Genet, 2013, RFMix: a discriminative modeling approach for rapid and robust local-ancestry inference	23910464	10.1016/j.ajhg.2013.06.020	Cited
Morrison, AC, Nat Genet, 2013, Whole-genome sequence-based analysis of high-density lipoprotein cholesterol	23770607	10.1038/ng.2671	Cited
Nalls, MA, Am J Hum Genet, 2008, Admixture mapping of white cell count: genetic locus responsible for lower white blood cell count in the Health ABC and Jackson Heart studies	18179887	10.1016/j.ajhg.2007.09.003	Cited
Olama, AA, Nat Genet, 2014, A meta-analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer	25217961	10.1038/ng.3094	Cited
Pasaniuc, B, Bioinformatics, 2013, Analysis of Latino populations from GALA and MEC studies reveals genomic loci with biased local ancestry estimation	23572411	10.1093/bioinformatics/btt166	Cited
Pasaniuc, B, PLoS Genet, 2011, Enhanced statistical tests for GWAS in admixed populations: assessment using African Americans from CARe and a Breast Cancer Consortium	21541012	10.1371/journal.pgen.1001371	Cited
Patterson, N et al., PLoS Genet, 2006, Population structure and eigenanalysis	17194218	10.1371/journal.pgen.0020190	Cited
Pennisi, E, Science, 2010, Genomics. 1000 Genomes Project gives new map of genetic diversity	21030618	10.1126/science.330.6004.574	Cited
Price, AL, Am J Hum Genet, 2007, A genomewide admixture map for Latino populations	17503322	10.1086/518313	Cited
Price, AL, PLoS Genet, 2009, Sensitive detection of chromosomal segments of distinct ancestry in admixed populations	19543370	10.1371/journal.pgen.1000519	Cited
Reich, D, PLoS Genet, 2009, Reduced neutrophil count in people of African descent is due to a regulatory variant in the Duffy antigen receptor for chemokines gene	19180233	10.1371/journal.pgen.1000360	Cited
Reiner, AP, PLoS Genet, 2011, Genome-wide association study of white blood cell count in 16,388 African Americans: the continental origins and genetic epidemiology network (COGENT)	21738479	10.1371/journal.pgen.1002108	Cited
Sham, PC et al., Am J Hum Genet, 2001, Equivalence between Haseman-Elston and variance-components linkage analyses for sib pairs	11353401	10.1086/320593	Cited
Simons, YB et al., Nat Genet, 2014, The deleterious mutation load is insensitive to recent population history	24509481	10.1038/ng.2896	Cited
Speed, D et al., Am J Hum Genet, 2012, Improved heritability estimation from genome-wide SNPs	23217325	10.1016/j.ajhg.2012.10.010	Cited
Vattikuti, S et al., PLoS Genet, 2012, Heritability and Genetic Correlations Explained by Common SNPs for Metabolic Syndrome Traits	22479213	10.1371/journal.pgen.1002637	Cited
Visscher, PM et al., Am J Hum Genet, 2012, Five Years of GWAS Discovery	22243964	10.1016/j.ajhg.2011.11.029	Cited
Visscher, PM et al., Nat Rev Genet, 2008, Heritability in the genomics era--concepts and misconceptions	18319743	10.1038/nrg2322	Cited
Visscher, PM, Am J Hum Genet, 2007, Genome partitioning of genetic variation for height from 11,214 sibling pairs	17924350	10.1086/522934	Cited
Wilson, JG, Ethn Dis, 2005, Study design for genetic analysis in the Jackson Heart Study	16317983	—	Cited
Wray, NR, Nat Rev Genet, 2013, Pitfalls of predicting complex traits from SNPs	23774735	10.1038/nrg3457	Cited
Yang, J et al., Am J Hum Genet, 2011, GCTA: a tool for genome-wide complex trait analysis	21167468	10.1016/j.ajhg.2010.11.011	Cited
Yang, J et al., Nat Genet, 2014, Advantages and pitfalls in the application of mixed-model association methods	24473328	10.1038/ng.2876	Cited
Yang, J, Nat Genet, 2010, Common SNPs explain a large proportion of the heritability for human height	20562875	10.1038/ng.608	Cited
Yang, J, Nat Genet, 2011, Genome partitioning of genetic variation for complex traits using common SNPs	21552263	10.1038/ng.823	Cited
Zaitlen, N et al., Hum Genet, 2012, Heritability in the genome-wide association era	22821350	10.1007/s00439-012-1199-6	Cited
Zaitlen, N, PLoS Genet, 2013, Using extended genealogy to estimate components of heritability for 23 quantitative and dichotomous traits	23737753	10.1371/journal.pgen.1003520	Cited
Zuk, O et al., Proc Natl Acad Sci U S A, 2012, The mystery of missing heritability: Genetic interactions create phantom heritability	22223662	10.1073/pnas.1119675109	Cited

In this knowledge base

Title	Year	PMID
Multi-trait genome-wide association study of opioid addiction: OPRM1 and beyond.	2022	36207451

External

Title	Authors	Journal	Year	Link
Interpreting SNP heritability in admixed populations.	Huang J et al.	—	2025	→
Leveraging haplotype information in heritability estimation and polygenic prediction.	Meisner J et al.	—	2025	→
Heritability within groups is uninformative about differences among groups: Cases from behavioral, evolutionary, and statistical genetics.	Schraiber JG et al.	—	2024	→
Interpreting population- and family-based genome-wide association studies in the presence of confounding.	Veller C et al.	—	2024	→
Rare variant contribution to the heritability of coronary artery disease.	Rocheleau G et al.	—	2024	→
Estimating heritability explained by local ancestry and evaluating stratification bias in admixture mapping from summary statistics.	Chan TF et al.	—	2023	→
Impact of cross-ancestry genetic architecture on GWASs in admixed populations.	Mester R et al.	—	2023	→
Overview of Admixture Mapping.	Shriner D	—	2023	→
Strategies for the Genomic Analysis of Admixed Populations.	Tan T et al.	—	2023	→
Genome-wide trans-ethnic meta-analysis identifies novel susceptibility loci for childhood acute lymphoblastic leukemia.	Jeon S et al.	—	2022	→
Human genetic admixture through the lens of population genomics.	Gopalan S et al.	—	2022	→
Multi-trait genome-wide association study of opioid addiction: OPRM1 and beyond.	Gaddis N et al.	—	2022	→
Eating behaviour in contrasting adiposity phenotypes: Monogenic obesity and congenital generalized lipodystrophy.	Santos JL et al.	—	2021	→
Estimating heritability and its enrichment in tissue-specific gene sets in admixed populations.	Luo Y et al.	—	2021	→
Genetic Ancestry Contributes to Somatic Mutations in Lung Cancers from Admixed Latin American Populations.	Carrot-Zhang J et al.	—	2021	→
Estimating narrow-sense heritability using family data from admixed populations.	Athanasiadis G et al.	—	2020	→
Genome-defined African ancestry is associated with distinct mutations and worse survival in patients with diffuse large B-cell lymphoma.	Lee MJ et al.	—	2020	→
Heritability of the Fibromyalgia Phenotype Varies by Age.	Dutta D et al.	—	2020	→
Meta-Analysis of 26 638 Individuals Identifies Two Genetic Loci Associated With Left Ventricular Ejection Fraction.	Choquet H et al.	—	2020	→
Mixed-model admixture mapping identifies smoking-dependent loci of lung function in African Americans.	Ziyatdinov A et al.	—	2020	→
Benefits and limitations of genome-wide association studies.	Tam V et al.	—	2019	→
Genome-wide Association Studies in Ancestrally Diverse Populations: Opportunities, Methods, Pitfalls, and Recommendations.	Peterson RE et al.	—	2019	→
GWEHS: A Genome-Wide Effect Sizes and Heritability Screener.	López-Cortegano E et al.	—	2019	→
Local ancestry at APOE modifies Alzheimer's disease risk in Caribbean Hispanics.	Blue EE et al.	—	2019	→
On Using Local Ancestry to Characterize the Genetic Architecture of Human Traits: Genetic Regulation of Gene Expression in Multiethnic or Admixed Populations.	Zhong Y et al.	—	2019	→
A novel linkage-disequilibrium corrected genomic relationship matrix for SNP-heritability estimation and genomic prediction.	Mathew B et al.	—	2018	→
Comparing Ethnicity-Specific Reference Intervals for Clinical Laboratory Tests from EHR Data.	Rappoport N et al.	—	2018	→
Fuzzy set-based generalized multifactor dimensionality reduction analysis of gene-gene interactions.	Jung HY et al.	—	2018	→
Proteomic-genomic adjustments and their confluence for elucidation of pathways and networks during liver fibrosis.	Husain H et al.	—	2018	→
An Unexpectedly Complex Architecture for Skin Pigmentation in Africans.	Martin AR et al.	—	2017	→
Evidence of epigenetic admixture in the Colombian population.	Rawlik K et al.	—	2017	→
Genetic Analysis of Venous Thromboembolism in UK Biobank Identifies the ZFPM2 Locus and Implicates Obesity as a Causal Risk Factor.	Klarin D et al.	—	2017	→
Genetic parameters and genome-wide associations of twinning rate in a local breed, the Maremmana cattle.	Moioli B et al.	—	2017	→
Investigating the case of human nose shape and climate adaptation.	Zaidi AA et al.	—	2017	→
Phenome-wide heritability analysis of the UK Biobank.	Ge T et al.	—	2017	→
The genetic underpinnings of body fat distribution.	Pulit SL et al.	—	2017	→
A Continuous Correlated Beta Process Model for Genetic Ancestry in Admixed Populations.	Gompert Z	—	2016	→
Contrasting the Genetic Architecture of 30 Complex Traits from Summary Association Data.	Shi H et al.	—	2016	→
Developing and evaluating polygenic risk prediction models for stratified disease prevention.	Chatterjee N et al.	—	2016	→
Genomic prediction contributing to a promising global strategy to turbocharge gene banks.	Yu X et al.	—	2016	→
Modelling local gene networks increases power to detect trans-acting genetic effects on gene expression.	Rakitsch B et al.	—	2016	→
Multidimensional heritability analysis of neuroanatomical shape.	Ge T et al.	—	2016	→
The Genetics of Stress-Related Disorders: PTSD, Depression, and Anxiety Disorders.	Smoller JW	—	2016	→
A General Model of the Relationship between the Apportionment of Human Genetic Diversity and the Apportionment of Human Phenotypic Diversity.	Edge MD et al.	—	2015	→
An Examination of the Relationship between Lipid Levels and Associated Genetic Markers across Racial/Ethnic Populations in the Multi-Ethnic Study of Atherosclerosis.	Johnson L et al.	—	2015	→
A review of study designs and statistical methods for genomic epidemiology studies using next generation sequencing.	Wang Q et al.	—	2015	→
Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index.	Yang J et al.	—	2015	→
Haplotypes of common SNPs can explain missing heritability of complex diseases	Bhatia G et al.	—	2015	—
Leveraging local ancestry to detect gene-gene interactions in genome-wide data.	Aschard H et al.	—	2015	→
Phenotypic variance explained by local ancestry in admixed African Americans.	Shriner D et al.	—	2015	→