|
GCTA estimates frequently find estimates 0.1-0.5, consistent with broadsense heritability estimates (with the exception of personality traits, for which theory & current GWAS results suggest non-additive genetics driven by [[frequency-dependent selection]]<ref name="Verweij2012"/><ref>[http://www.unm.edu/~gfmiller/newpapers_sept6/penke%202007%20targetarticle.pdf "The Evolutionary Genetics of Personality"], Penke et al 2007; [http://www.larspenke.eu/pdfs/Penke_&_Jokela_in_press_-_Evolutionary_Genetics_of_Personality_Revisited.pdf "The Evolutionary Genetics of Personality Revisited"], Penke & Jokela 2016</ref>). Traits univariate GCTA has been used on (excluding SNP heritability estimates computed using other algorithms such as LD score regression, and bivariate GCTAs which are listed in [[genetic correlation]]) include (point-estimate format: "<math>h^2_{SNP}</math>([[standard error]])"):
=== Human ===
==== Anthropometric ====
* [[Height]]: 0.544(0.101),<ref name="Yang2010"/> 0.498(0.04),<ref name="Wood2014"/> 0.56(0.023),<ref name="Yang2015"/> 0.448(0.029),<ref name="Yang2011"/> 0.42(0.052),<ref name="Lubke2012"/> 0.69(0.14),<ref name="Hemani2013">[https://genepi.qimr.edu.au/contents/p/staff/HemaniG_AJHG_865-875.pdf "Inference of the Genetic Architecture Underlying BMI and Height with the Use of 20,240 Sibling Pairs"], Hemani et al 2013</ref> 0.48(0.17)<ref name="Guggenheim2013"/> 0.37(0.14):<ref name="Trzaskowski2013"/> 0.32(0.06),<ref name="Conley2014"/> 0.35(0.12),<ref name="Plomin2013"/> 0.44(0.09),<ref name="Speed2012"/> 0.40(0.09)/0.33(0.09),<ref name="Domingue2016"/> 0.62(0.061),<ref name="Chen2015"/> 0.687(0.016),<ref name="Zaitlen2013"/> 0.56(0.23),<ref name="Toro2014"/> 0.51(0.01),<ref name="Pierson2014">[https://i.imgur.com/mX6LFF6.png Figure 4], [https://blog.23andme.com/wp-content/uploads/2014/10/ASHG_pierson_kleinman_eriksson_hinds_8-12.pdf "Like Mother, Like Daughter: Analysis of Parent-Child Phenotypic Correlations for Hundreds of Phenotypic Traits"], Pierson et al 2014<!-- Note: despite saying "We ran GCTA on a cohort of more than 30,000 unrelated individuals of European ancestry to estimate the narrow-sense heritability of more than 100 phenotype", only 17 of them have ever been published --></ref> 0.47(0.15)/0.69(0.08)<ref name="Trzaskowski2016">[http://ije.oxfordjournals.org/content/45/2/417.full "Application of linear mixed models to study genetic stability of height and body mass index across countries and time"], Trzaskowski et al 2016</ref>
* weight: 0.48(0.14),<ref name="Trzaskowski2013"/> 0.41(0.12),<ref name="Plomin2013"/> 0.25(0.09),<ref name="Domingue2016">[https://www.dropbox.com/s/wszkx5abzlptgd8/2016-domingue.pdf "Genome-Wide Estimates of Heritability for Social Demographic Outcomes"], Domingue et al 2016</ref> 0.26(0.061),<ref name="Chen2015"/> 0.394(0.174),<ref name="Zaidi2017">Zaidi et al 2017, [http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1006616 "Investigating the case of human nose shape and climate adaptation"]</ref> 0.224(0.091)<ref name="Zaidi2017"/>
* [[Body mass index]] (BMI): 0.42(0.17)<ref name="Hemani2013"/> 0.14(0.05),<ref name="Vattikuti2012">[http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1002637 "Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits"], Vattikuti et al 2012</ref> 0.50(0.05)<ref>[http://paa2013.princeton.edu/papers/130559 "Using Genome Wide Estimates of Heritability to Examine the Relevance of Gene-Environment Interplay"], Domingue & Boardman 2013</ref> 0.31(0.07),<ref name="Conley2014"/> 0.43(0.10),<ref name="Boardman2015"/> 0.21(0.061),<ref name="Chen2015"/> 0.424(0.018),<ref name="Zaitlen2013"/> 0.27(0.025),<ref name="Yang2015"/> 0.165(0.029),<ref name="Yang2011">[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4295936/ "Genome partitioning of genetic variation for complex traits using common SNPs"], Yang et al 2011</ref> 0.24(0.01),<ref name="Pierson2014"/> 0.26 (0.08)<ref name="Trzaskowski2016"/> 0.298(0.034)<ref name="Akiyama2017">Akiyama et al 2017, [https://www.dropbox.com/s/0jhl1lh3780ef6p/2017-akiyama.pdf?dl=0 "Genome-wide association study identifies 112 new loci for body mass index in the Japanese population"]</ref>
** in children: 0.37(0.15)<ref>[https://www.researchgate.net/profile/Maciej_Trzaskowski/publication/236080492_Finding_the_missing_heritability_in_pediatric_obesity_the_contribution_of_genome-wide_complex_trait_analysis/links/02e7e5162d6dd46f56000000.pdf "Finding the missing heritability in pediatric obesity: the contribution of genome-wide complex trait analysis"], Llewellyn et al 2013</ref>
* grip strength: 0.239(0.027)<ref name="Willems2017">Willems et al 2017, [https://www.nature.com/articles/ncomms16015 "Large-scale GWAS identifies multiple loci for hand grip strength providing biological insights into muscular fitness"]</ref>
* gestational (pregnancy) weight gain: maternal genome, 0.239(0.055);<ref name="Warrington2017"/> fetal genome, 0.121(0.053)<ref name="Warrington2017">Warrington et al 2017, [http://biorxiv.org/content/early/2017/03/14/116434 "Maternal and fetal genetic contribution to gestational weight gain"]</ref>
* birthweight: maternal genome, 0.13(0.06);<ref name="Warrington2017"/> fetal genome, 0.18(0.06)
* waist-to-hip ratio (WHR): 0.13(0.05)<ref name="Vattikuti2012"/> 0.188(0.037)<ref name="Zaitlen2013"/>
* waist circumference: 0.16(0.061)<ref name="Chen2015"/>
* Breast size: 0.31(0.16)/0.47(0.25)<ref name="Li2013">[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4159740/ "Large-scale genotyping identifies a new locus at 22q13.2 associated with female breast size"], Li et al 2013</ref>
* Health (self-rated): 0.177(0.089),<ref name="Boardman2015"/> 0.13(0.006)<ref>[http://biorxiv.org/content/early/2016/04/12/029504 "Molecular genetic contributions to self-rated health"], Harris et al 2016</ref>
* [[Hair color]]:
** Blond: 0.165(0.081)<ref name="Lin2015">[http://www.mdpi.com/2073-4425/6/3/559/pdf "Heritability and Genome-Wide Association Studies for Hair Color in a Dutch Twin Family Based Sample"], Lin et al 2015</ref>
** Brown: 0.095(0.079)<ref name="Lin2015"/>
** Red: 0.246(0.087)<ref name="Lin2015"/>
** Black: 0.00(0.083)<ref name="Lin2015"/>
** Light versus dark: 0.140(0.080)<ref name="Lin2015"/>
* [[unibrow]]: 0.28(0.02)<ref name="Pierson2014"/>
* [[Male pattern hair loss]] (balding): autosomal SNPs, 0.473(0.013), [[X chromosome]], 0.046(0.03), 0.519 total,<ref>[http://biorxiv.org/content/early/2016/08/30/072306 "Genetic Prediction of Male Pattern Baldness"], Hagenaars et al 2016</ref> 0.94<ref>Pirastu et al 2017, [https://www.nature.com/articles/s41467-017-01490-8 "GWAS for male-pattern baldness identifies 71 susceptibility loci explaining 38% of the risk"]</ref>
* melanin index: 0.191(0.263)<ref name="Zaidi2017"/>
* facial features:
** Nares width: 0.504(0.187),<ref name="Zaidi2017"/> 0.226(0.094)<ref name="Zaidi2017"/>
** Alar base width: 0.481(0.188),<ref name="Zaidi2017"/> 0.212(0.093)<ref name="Zaidi2017"/>
** Nasal height: 0.441(0.186),<ref name="Zaidi2017"/> 0.03(0.076)<ref name="Zaidi2017"/>
** Nasal ridge length: 0.524(0.188),<ref name="Zaidi2017"/> 0.059(0.078)<ref name="Zaidi2017"/>
** Nasal tip protrusion: 0.401(0.191),<ref name="Zaidi2017"/> 0.177(0.088)<ref name="Zaidi2017"/>
** External surface area: 0.449(0.187),<ref name="Zaidi2017"/> 0.121(0.086)<ref name="Zaidi2017"/>
** Nostril area: 0.657(0.187),<ref name="Zaidi2017"/> 0.059(0.088)<ref name="Zaidi2017"/>
** nasal root shape, mouth width: 0.669(0.138)<ref name="Cole2017">Cole et al 2017, [https://klein.ucsf.edu/sites/kleinlab.ucsf.edu/files/cole_2017.pdf "Human Facial Shape and Size Heritability and Genetic Correlations"]</ref>
** facial width: 0.521(0.138)<ref name="Cole2017"/>
** Allometry variation in shape due to size: 0.643(0.132)<ref name="Cole2017"/>
** Centroid Size (facial size): 0.277(0.134)<ref name="Cole2017"/>
** nasion to midendocanthion: 0.260(0.134)<ref name="Cole2017"/>
** nasal width: 0.623(0.131)<ref name="Cole2017"/>
** width of the nose, mandible height: 0.604(0.131)<ref name="Cole2017"/>
** overall facial height, lower facial height: 0.579(0.139)<ref name="Cole2017"/>
** outer canthal width: 0.421(0.141)<ref name="Cole2017"/>
** nasal bridge length: 0.456(0.142)<ref name="Cole2017"/>
** palpebral fissure length (average): 0.208(0.140)<ref name="Cole2017"/>
** upper facial depth (average): 0.419(0.136)<ref name="Cole2017"/>
** nose shape, height of the mouth: 0.211(0.138)<ref name="Cole2017"/>
** upper facial height: 0.443(0.140)<ref name="Cole2017"/>
** lower facial depth (average): 0.487(0.140)<ref name="Cole2017"/>
** philtrum length: 0.486(0.130)<ref name="Cole2017"/>
** midfacial depth (average): 0.469(0.139)<ref name="Cole2017"/>
** upper and middle facial width: 0.308(0.139)<ref name="Cole2017"/>
** upper facial height, midfacial width: 0.477(0.140)<ref name="Cole2017"/>
** cheek protrusion: 0.074(0.137)<ref name="Cole2017"/>
** nasal height: 0.244(0.137)<ref name="Cole2017"/>
** midface protrusion, upper facial height: 0.431(0.125)<ref name="Cole2017"/>
** midfacial landmark network around the nose and mouth: 0.433(0.138)<ref name="Cole2017"/>
** morphological facial height: 0.159(0.137)<ref name="Cole2017"/>
** inner canthal width: 0.392(0.142)<ref name="Cole2017"/>
** nasal ala length (average): 0.311(0.140)<ref name="Cole2017"/>
** lower facial height: 0.239(0.139)<ref name="Cole2017"/>
** mouth width: 0.378(0.137)<ref name="Cole2017"/>
** subnasal width: 0.373(0.134)<ref name="Cole2017"/>
** cutaneous lower lip height: 0.177(0.134)<ref name="Cole2017"/>
** nasal protrusion: 0.242(0.139)<ref name="Cole2017"/>
** philtrum width: 0.337(0.126)<ref name="Cole2017"/>
** lower vermilion height: 0.324(0.139)<ref name="Cole2017"/>
** upper lip height: 0.314(0.131)<ref name="Cole2017"/>
** chin height, nasion protrusion: 0.291(0.140)<ref name="Cole2017"/>
** lower lip height: 0.283(0.134)<ref name="Cole2017"/>
** nasal width, maxillary prognathism: 0.169(0.131)<ref name="Cole2017"/>
* skin [[nevus]] (mole/lesion) density count: 0.58(0.025)<ref>Duffy et al 2017, [http://www.biorxiv.org/content/early/2017/08/07/173112 "Novel pleiotropic risk loci for melanoma and nevus density implicate multiple biological pathways"]</ref>
* age at [[menarche]]: 0.451(0.022)<ref name="Zaitlen2013"/>
* age at first birth: 0.15(0.04),<ref name="Tropf2015">[http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0126821 "Human Fertility, Molecular Genetics, and Natural Selection in Modern Societies"], Tropf et al 2015</ref> 0.19(0.039)<ref name="Tropf2016">[http://biorxiv.org/content/early/2016/05/02/049163 "Mega-analysis of 31,396 individuals from 6 countries uncovers strong gene-environment interaction for human fertility"], Tropf et al 2016</ref>
* age at [[menopause]]: 0.409(0.048)<ref name="Zaitlen2013"/>
* sex ratio of offspring: 0.026(0.017)<ref name="Zaitlen2013"/>
* number of offspring: 0.073(0.068)/0.102(0.028),<ref name="Zaitlen2013"/> 0.10(0.05),<ref name="Tropf2015"/> 0.22(0.026),<ref name="Tropf2016"/> 0.21(0.05),<ref name="Conley2016">[http://www.pnas.org/content/early/2016/05/25/1523592113.full "Assortative mating and differential fertility by phenotype and genotype across the 20th century"], Conley et al 2016 ([http://www.pnas.org/content/suppl/2016/05/25/1523592113.DCSupplemental/pnas.1523592113.sapp.pdf supplement])</ref> 0.20(0.10),<ref name="Conley2016"/> 0.19(0.09)<ref name="Conley2016"/>
* [[left handedness]]: 0.004(0.145)<ref name="Zaitlen2013"/>
* [[Eye color]]: 0.59(0.01)<ref name="Pierson2014"/>
* Eye dimensions (axial length & [[cornea]]l curvature): 0.46(0.16)/0.42(0.16)<ref name="Guggenheim2013">[http://iovs.arvojournals.org/article.aspx?articleid=2165969 "Coordinated Genetic Scaling of the Human Eye: Shared Determination of Axial Eye Length and Corneal Curvature"], Guggenheim et al 2013</ref>
* [[Coriander#Taste and smell|Cilantro tasting]]: 0.087<ref>[https://blog.23andme.com/wp-content/uploads/2012/11/ASHG2012poster-SW_cilantro-final.pdf "A Genetic Variant Near Olfactory Receptor Genes Associates With Cilantro Preference"], Wu et al 2012</ref>
* cry cutting onions: 0.12(0.02)<ref name="Pierson2014"/>
* sweet vs salty: 0.35(0.03)<ref name="Pierson2014"/>-
==== Social/behavioral ====
* [[Education]]: 0.224(0.042),<ref>[http://www.gwern.net/docs/iq/2013-rietveld.pdf "GWAS of 126,559 Individuals Identifies Genetic Variants Associated with Educational Attainment"], Rietveld et al 2013</ref> 0.21(0.06),<ref name="Davies2016"/> 0.158(0.061),<ref name="Benjamin2012"/> 0.21(0.05),<ref name="Marioni2014"/> 0.17(0.07),<ref name="Conley2014">[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4126504/ "Testing the key assumption of heritability estimates based on genome-wide genetic relatedness"], Conley et al 2014</ref> 0.33 (0.10),<ref name="Boardman2015"/> 0.23(0.09),<ref name="Domingue2016"/> 0.156(0.021)<ref name="Hill2017"/>
** rare/family variants: 0.281(0.03)<ref name="Hill2017"/>
** test scores: 0.31(0.12)<ref name="Krapohl2016"/>
** reading scores: 0.27(0.128)<ref name="Davis2014">Davis et al 2014, [http://www.nature.com/articles/ncomms5204 "The correlation between reading and mathematics ability at age twelve has a substantial genetic component"]</ref>
** mathematics scores: 0.52 (0.163)<ref name="Davis2014"/>
* [[Socioeconomic status]] (SES): 0.18(0.05),<ref name="Marioni2014"/> 0.18(0.12)/0.19(0.12),<ref name="Krapohl2016">[http://www.nature.com/mp/journal/v21/n3/pdf/mp20152a.pdf "Genetic link between family socioeconomic status and children's educational achievement estimated from genome-wide SNPs"], Krapohl & Plomin 2016</ref> 0.18(0.12)/0.19(0.12)<ref name="Trzaskowski2014b"/>
** social deprivation: 0.21(0.005)<ref name="Hill2016">[http://biorxiv.org/content/early/2016/03/09/043000 "Molecular genetic contributions to social deprivation and household income in UK Biobank (''n''=112,151)"], Hill et al 2016</ref>
** household income: 0.11(0.007)<ref name="Hill2016"/>
* Exercise:
** Moderate to Vigorous Activity: 0.17(0.09)<ref name="Richmond2014">[http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001618 "Assessing causality in the association between child adiposity and physical activity levels: A Mendelian randomization analysis"], Richmond et al 2014</ref>
** Sedentary Time: 0.25(0.09)<ref name="Richmond2014"/>
** Total Physical Activity: 0.21(0.10)<ref name="Richmond2014"/>
* ability to delay gratification/delay discounting (Monetary Choice Questionnaire): 0.122(0.017)<ref name="Sanchez_Roige2017">Sanchez-Roige et al 2017, [http://biorxiv.org/content/early/2017/06/07/146936 "Genetics of the Research Domain Criteria (RDoC): genome-wide association study of delay discounting"]</ref>
* Tiredness: 0.084(0.006)<ref>[http://biorxiv.org/content/early/2016/04/05/047290 "Genetic contributions to self-reported tiredness"], Deary et al 2016</ref>
* Insomnia: 0.08(0.02)<ref name="Pierson2014"/>
* [[Chronotype]]/morningness: 0.25(0.03),<ref name="Pierson2014"/> 0.194(?),<ref name="Lane2016"/> 0.377(?)<ref name="Lane2016">[http://biorxiv.org/content/early/2016/02/02/038620 "Genome-wide association analysis identifies novel loci for chronotype in 100,420 individuals from the UKBiobank"], Lane et al 2016 ([http://biorxiv.org/content/biorxiv/suppl/2016/02/02/038620.DC1/038620-1.pdf supplement])</ref>
* Adult antisocial behavior: 0.55(0.41)<ref>[http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0045086 "Unraveling the genetic etiology of adult antisocial behavior: A genome-wide association study"], Tielbeek et al 2012</ref>
* trust
** trust in people: 0.07(0.17)<ref name="Wootton2016">Wootton et al 2016, [https://www.cambridge.org/core/journals/twin-research-and-human-genetics/article/exploring-the-genetic-etiology-of-trust-in-adolescents-combined-twin-and-dna-analyses/5BF8A9F5E74796F1903A0E8878C70825/core-reader"Exploring the Genetic Etiology of Trust in Adolescents: Combined Twin and DNA Analyses"]</ref>
** trust in friends: 0.06(0.24)<ref name="Wootton2016"/>
* loneliness: 0.27(0.12)<ref>Gao et al 2016, [https://www.dropbox.com/s/3samba012ru70p9/2016-gao.pdf "Genome-Wide Association Study of Loneliness Demonstrates a Role for Common Variation"]</ref>
* family relationship satisfaction: 0.053(0.014)<ref name="Warrier2017">Warrier et al 2017, [https://www.biorxiv.org/content/early/2017/10/05/196071 "Genome-wide association study of social relationship satisfaction: significant loci and correlations with psychiatric conditions"]</ref>
* friendship satisfaction: 0.056(0.014)<ref name="Warrier2017"/>
* Non-substance related Behavioral Disinhibition: 0.28(0.102),<ref name="McGue2013"/> 0.19(0.16)<ref name="Vrieze2013"/>
* Stressful life events: 0.3(0.15)<ref>[http://hub.hku.hk/bitstream/10722/189366/1/Content.pdf?accept=1 "Estimating the heritability of reporting stressful life events captured by common genetic variants"], Power et al 2013</ref>
* [[carsickness]]: 0.2(0.01)<ref name="Pierson2014"/>
==== Psychological ====
* Overall brain size: 0.845(0.457)/0.00(0.476)/0.00(0.483)/0.574(0.468),<ref>[https://ncrad.iu.edu/docs/Publications/149_Bryant_2013.pdf "Mapping the Genetic Variation of Regional Brain Volumes as Explained by All Common SNPs from the ADNI Study"], Bryant et al 2013</ref> 0.54(0.23)/0.44(0.23)/0.53(0.23)/0.22(0.24)/0.16(0.23)/0.31(0.23)/0.54(0.23)/0.45(0.23)/0.52(0.23)<ref name="Toro2014">[http://www.fondation-fondamental.org/upload/editeur/files/ToroMolPsy2014.pdf "Genomic architecture of human neuroanatomical diversity"], Toro et al 2014 ([https://neuroanatomy.github.io/pdfs/2014Toro-Bourgeron;GenomicArchitecture;Supplement.pdf supplement])</ref>
* Volume of neuroanatomical structures: 100 brain volumes & latent factors thereof, median 0.348<ref>Zhao et al 2018, [https://www.dropbox.com/s/csfqhc5zx1kgl6s/2018-zhao.pdf?dl=0 "Heritability of Regional Brain Volumes in Large-Scale Neuroimaging and Genetic Studies"]</ref>
*** [[Accumbens Area]]: 0.001(0.279)<ref name="Ge2015">[http://biorxiv.org/content/early/2015/12/01/033407 "Heritability of Neuroanatomical Shape"], Ge et al 2015</ref>
*** [[Amygdala]]: 0.096(0.279)<ref name="Ge2015"/>
*** [[Caudate nucleus|Caudate]]: 0.620(0.279)<ref name="Ge2015"/>
*** [[Cerebellum]]: 0.002(0.279)<ref name="Ge2015"/>
*** [[Corpus Callosum]]: 0.521(0.279)<ref name="Ge2015"/>
*** [[Hippocampus]]: 0.001(0.279)<ref name="Ge2015"/>
*** [[Lateral Ventricle]]: 0.266(0.279)<ref name="Ge2015"/>
*** 3rd Ventricle: 0.534(0.279)<ref name="Ge2015"/>
*** 4th Ventricle: 0.392(0.279)<ref name="Ge2015"/>
*** [[Pallidum]]: 0.259(0.279)<ref name="Ge2015"/>
*** [[Putamen]]: 0.310(0.279)<ref name="Ge2015"/>
*** [[Thalamus]]: 0.227(0.279)<ref name="Ge2015"/>
** Global:
*** Intracranial volume: 0.880(0.238)<ref name="Lee2016">[https://www.dropbox.com/s/bfflgmrfd7473hn/2016-lee.pdf "Partitioning heritability analysis reveals a shared genetic basis of brain anatomy and schizophrenia"], Lee et al 2016</ref>
*** Overall mean cortical thickness: 0.796(0.244)<ref name="Lee2016"/>
** Frontal:
*** Left precentral gyrus thickness: 0.718(0.249)<ref name="Lee2016"/>
*** Left rostral anterior cingulate cortex thickness: 0.737(0.243)<ref name="Lee2016"/>
*** Left superior frontal gyrus thickness: 0.597(0.246)<ref name="Lee2016"/>
*** Right lateral orbital frontal cortex thickness: 0.483(0.240)<ref name="Lee2016"/>
*** Right pars opercularis surface area: 0.545(0.252)<ref name="Lee2016"/>
*** Right paracentral lobule thickness: 0.494(0.252)<ref name="Lee2016"/>
*** Right precentral gyrus thickness: 0.731(0.244)<ref name="Lee2016"/>
** Occipital:
*** Left cuneus cortex thickness: 0.550(0.244)<ref name="Lee2016"/>
*** Left lateral occipital cortex thickness: 0.498(0.248)<ref name="Lee2016"/>
*** Right cuneus cortex thickness: 0.723(0.251)<ref name="Lee2016"/>
** Parietal:
*** Left inferior parietal cortex thickness: 0.566(0.248)<ref name="Lee2016"/>
*** Left postcentral gyrus thickness: 0.501(0.249)<ref name="Lee2016"/>
*** Left posterior-cingulate cortex thickness: 0.601(0.246)<ref name="Lee2016"/>
*** Left precuneus cortex surface area: 0.555(0.262)<ref name="Lee2016"/>
*** Left precuneus cortex thickness: 0.896(0.245)<ref name="Lee2016"/>
*** Left superior parietal gyrus surface area: 0.558(0.251)<ref name="Lee2016"/>
*** Left superior parietal gyrus thickness: 0.903(0.241)<ref name="Lee2016"/>
*** Right postcentral gyrus thickness: 0.760(0.246)<ref name="Lee2016"/>
*** Right precuneus cortex surface area: 0.547(0.246)<ref name="Lee2016"/>
*** Right precuneus cortex thickness: 0.965(0.243)<ref name="Lee2016"/>
*** Right superior parietal gyrus thickness: 0.941(0.239)<ref name="Lee2016"/>
*** Right supramarginal gyrus thickness: 0.769(0.240)<ref name="Lee2016"/>
** Temporal:
*** Left banks superior temporal sulcus thickness: 0.680(0.242)<ref name="Lee2016"/>
*** Left entorhinal cortex thickness: 0.587(0.249)<ref name="Lee2016"/>
*** Left fusiform gyrus surface area: 0.566(0.259)<ref name="Lee2016"/>
*** Left insula cortex surface area: 0.561(0.251)<ref name="Lee2016"/>
*** Left superior temporal gyrus surface area: 0.658(0.244)<ref name="Lee2016"/>
*** Left transverse temporal cortex thickness: 0.555(0.245)<ref name="Lee2016"/>
*** Right entorhinal cortex surface area: 0.651(0.251)<ref name="Lee2016"/>
*** Right insula cortex surface area: 0.878(0.252)<ref name="Lee2016"/>
*** Right middle temporal gyrus surface area: 0.610(0.244)<ref name="Lee2016"/>
*** Right temporal pole surface area: 0.524(0.249)<ref name="Lee2016"/>
*** Right transverse temporal cortex thickness: 0.536(0.254)<ref name="Lee2016"/>
** Shape of neuroanatomical structures:
*** Accumbens Area: 0.230(0.134)<ref name="Ge2015"/>
*** Amygdala: 0.036(0.138)<ref name="Ge2015"/>
*** Caudate: 0.497(0.187)<ref name="Ge2015"/>
*** Cerebellum: 0.456(0.190)<ref name="Ge2015"/>
*** Corpus Callosum: 0.243(0.132)<ref name="Ge2015"/>
*** Hippocampus: 0.339(0.168)<ref name="Ge2015"/>
*** Lateral Ventricle: 0.207(0.152)<ref name="Ge2015"/>
*** 3rd Ventricle: 0.454(0.156)<ref name="Ge2015"/>
*** 4th Ventricle: 0.014(0.206)<ref name="Ge2015"/>
*** Pallidum: 0.074(0.116)<ref name="Ge2015"/>
*** Putamen: 0.365(0.146)<ref name="Ge2015"/>
*** Thalamus Proper: 0.132(0.143)<ref name="Ge2015"/>
* [[Intelligence]]: 0.40(0.11)/0.51(0.11),<ref>[http://www.nature.com/mp/journal/v16/n10/full/mp201185a.html "Genome-wide association studies establish that human intelligence is highly heritable and polygenic"], Davies et al 2011</ref> 0.47(?),<ref>[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3498585/ "Most Reported Genetic Associations with General Intelligence Are Probably False Positives"], Chabris et al 2012</ref> 0.24(0.20),<ref name="Deary2012">[https://www.researchgate.net/profile/David_Dave_Liewald/publication/221760226_Genetic_contributions_to_stability_and_change_in_intelligence_from_childhood_to_old_age/links/02e7e52ca9a723a8fa000000.pdf "Genetic contributions to stability and change in intelligence from childhood to old age"], Deary et al 2012</ref> 0.29(0.12)/0.26(0.11)/0.20(0.11)/0.35(0.12),<ref name="Plomin2013">[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3652710/ "Common DNA Markers Can Account for More Than Half of the Genetic Influence on Cognitive Abilities"], Plomin et al 2013</ref> 0.47(0.18)/0.26(0.17)/0.23(0.13)/0.15(0.14)<ref>[http://www.sciencedirect.com/science/article/pii/S0160289613001049 "Intelligence indexes generalist genes for cognitive abilities"], Trzaskowski et al 2013</ref><ref>[https://link.springer.com/article/10.1007/s10519-013-9594-x/fulltext.html "DNA Evidence for Strong Genome-Wide Pleiotropy of Cognitive and Learning Abilities"], Trzaskowski et al 2013b<!-- no specific estimate given; may be redundant with one of Trzaskowski's many other papers --></ref> 0.29(0.05),<ref name="Marioni2014">[http://www.sciencedirect.com/science/article/pii/S0160289614000178 "Molecular genetic contributions to socioeconomic status and intelligence"], Marioni et al 2014</ref> 0.35(0.11),<ref>[http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0112390 "Results of a 'GWAS Plus': General Cognitive Ability Is Substantially Heritable and Massively Polygenic"], Kirkpatrick et al 2014</ref> 0.60(0.26),<ref>[https://www.researchgate.net/profile/Maciej_Trzaskowski/publication/235379639_DNA_evidence_for_strong_genetic_stability_and_increasing_heritability_of_intelligence_from_age_7_to_12/links/004635162d9aa8ba50000000.pdf "DNA evidence for strong genetic stability and increasing heritability of intelligence from age 7 to 12"], Trzaskowski et al 2014a</ref> 0.32(0.14)/0.28(0.17),<ref name="Trzaskowski2014b">[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3907681/ "Genetic influence on family socioeconomic status and children's intelligence"], Trzaskowski et al 2014b</ref> 0.40(0.21)/0.46(0.06),<ref>[https://www.researchgate.net/profile/Beben_Benyamin/publication/235379638_Childhood_intelligence_is_heritable_highly_polygenic_and_associated_with_FNBP1L/links/5458a9090cf2bccc491183f0.pdf "Childhood intelligence is heritable, highly polygenic and associated with _FNBP1L_"], Benyamin et al 2014</ref> 0.56(0.25)/0.52(0.25),<ref name="Toro2014"/> 0.29%(0.05)/0.28(0.07),<ref>[http://www.nature.com/mp/journal/v20/n2/full/mp2014188a.html "Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (''n''=53949)"], Davies et al 2015</ref> 0.174(0.017),<ref>[http://www.nature.com/mp/journal/vaop/ncurrent/full/mp2015108a.html "A genome-wide analysis of putative functional and exonic variation associated with extremely high intelligence"], Spain et al 2015</ref> 0.00(?)/0.00(?),<ref name="Levine2015"/> 0.31(0.018),<ref name="Davies2016">[http://www.nature.com/mp/journal/vaop/ncurrent/full/mp201645a.html "Genome-wide association study of cognitive functions and educational attainment in UK Biobank (''n''=112151)"], Davies et al 2016</ref> 0.360(0.108),<ref name="Robinson2015">[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4294962/ "The genetic architecture of pediatric cognitive abilities in the Philadelphia Neurodevelopmental Cohort"], Robinson et al 2015</ref> 0.23(0.02)<ref name="Hill2017"/>
** extremely high intelligence: 0.33(0.02)<ref name="Zabaneh2017">Zabaneh et al 2017, [https://www.nature.com/mp/journal/vaop/ncurrent/full/mp2017121a.html "A genome-wide association study for extremely high intelligence"]</ref>
*** extremely high intelligence variants in the major histocompatibility complex (MHC)/[[Human leukocyte antigen|HLA]] immune system gene complex: 0.0028(0.0018)<ref>Zabaneh et al 2017, [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5259706/ "Fine mapping genetic associations between the HLA region and extremely high intelligence"]</ref>
** rare/family variants: 0.31(0.03)<ref name="Hill2017"/>
** [[reaction time]]: 0.11(0.06)<ref name="Davies2016"/>
** memory: 0.05(0.06),<ref name="Davies2016"/> 0.00(?)/0.00(?)<ref name="Levine2015"/>
** [[working memory]]: 0.17(?)/0.07(?),<ref name="Levine2015"/> 0.108(0.096)<ref name="Robinson2015"/>
** Facial Memory: 0.064(0.093)<ref name="Robinson2015"/>
** Spatial Memory: 0.028(0.090)<ref name="Robinson2015"/>
** Verbal Memory: 0.244(0.097)<ref name="Robinson2015"/>
** Digit Symbol Test: 0.214(0.021)<ref name="Hill2017"/>
*** rare/family variants: 0.147 (0.028)<ref name="Hill2017"/>
** Logical memory: 0.119 (0.02)<ref name="Hill2017"/>
*** rare/family variants:0.203 (0.028)<ref name="Hill2017"/>
** Abstraction and Mental Flexibility: 0.064(0.096)<ref name="Robinson2015"/>
** Attention: 0.148(0.097)<ref name="Robinson2015"/>
** Language Reasoning: 0.302(0.098)<ref name="Robinson2015"/>
** vocabulary: 0.256(0.02)<ref name="Hill2017"/>
*** rare/family variants: 0.301(0.028)<ref name="Hill2017"/>
** TOWRE word reading fluency: 0.74 (0.04)/0.68 (0.04)<ref name="Harlaar2014">[http://onlinelibrary.wiley.com/doi/10.1111/cdev.12207/full "Word Reading Fluency: Role of Genome-Wide Single-Nucleotide Polymorphisms in Developmental Stability and Correlations With Print Exposure"], Harlaar et al 2014</ref>
** Verbal fluency: 0.189(0.021)<ref name="Hill2017"/>
*** rare/family variants: 0.271(0.029)<ref name="Hill2017"/>
** Wide Range Achievement Test (Reading): 0.433(0.098)<ref name="Robinson2015"/>
** ART written/printed material exposure: 0.39(0.02)<ref name="Harlaar2014"/>
** Nonverbal Reasoning: 0.406(0.096)<ref name="Robinson2015"/>
** Spatial Reasoning: 0.357(0.101)<ref name="Robinson2015"/>
** Age Differentiation: 0.039(0.098)<ref name="Robinson2015"/>
** Emotion Differentiation: 0.000(0.092)<ref name="Robinson2015"/>
** Emotion Identification: 0.357(0.093)<ref name="Robinson2015"/>
** Trailing Making test/visual-numeric reasoning<ref name="Hagenaars2016"/>
* Trail Making test: 0.079(0.024)/0.224(0.026)/0.176(0.025)<ref name="Hagenaars2016">Hagenaars et al 2017, [http://biorxiv.org/content/early/2017/01/25/103119 "Genetic contributions to trail making test performance in UK Biobank"]</ref>
* Number sense: 0.00(0.29)<ref>[http://www.lauragermine.org/articles/intelligence2014.pdf "Why do we differ in number sense? Evidence from a genetically sensitive investigation"], Tosto et al 2013</ref>
* Economic preferences
** risk aversion: 0.137(0.152)<ref name="Benjamin2012">[http://www.nyu.edu/projects/dawes/The%20genetic%20architecture%20of%20economic%20and%20political%20preferences.pdf "The genetic architecture of economic and political preferences"], Benjamin 2012</ref>
** patience: 0.085(0.148) <ref name="Benjamin2012"/>
** trust: 0.242(0.146)<ref name="Benjamin2012"/>
** fair-mindedness: 0.00(0.15)<ref name="Benjamin2012"/>
* Political preferences
** immigration/crime: 0.203(0.147)<ref name="Benjamin2012"/>
** economic policy: 0.344(0.150)<ref name="Benjamin2012"/>
** environmentalism: 0.00(0.148)<ref name="Benjamin2012"/>
** feminism/equality: 0.00(0.147)<ref name="Benjamin2012"/>
** foreign policy: 0.354(0.149)<ref name="Benjamin2012"/>
* Happiness (self-rated): 0.05–0.10(0.05–0.10)<ref>[http://eprints.lse.ac.uk/51004/1/__lse.ac.uk_storage_LIBRARY_Secondary_libfile_shared_repository_Content_De%20Neve,%20JE_Molecular%20genetics_De%20Neve_Molecular%20genetics_2014.pdf "Molecular genetics and subjective well-being"], Rietveld et al 2013</ref>
* positive affect: 0.08(0.02)<ref name="Weiss2016"/>
* life satisfaction: 0.13(0.02)<ref name="Weiss2016"/>
* brain region activity response to faces<ref>[http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1004523 "Global Genetic Variations Predict Brain Response to Faces"], Dickie et al 2014</ref><!-- too many, over too many conditions, to bother listing -->
* [[Big Five personality traits]]
** [[Neuroticism]] (autosomal): 0.06(0.03),<ref name="Vinkhuyzen2012">[http://www.nature.com/tp/journal/v2/n4/full/tp201227a.html "Common SNPs explain some of the variation in the personality dimensions of neuroticism and extraversion"], Vinkhuyzen et al 2012</ref> 0.147(0.07)/0.157(0.16),<ref>[http://www.cs.princeton.edu/~bee/pubs/DeMoor-JAMA-2015.pdf "Meta-analysis of genome-wide association studies for neuroticism, and the polygenic association with major depressive disorder"], De Moor et al 2015</ref> 0.15(0.08),<ref name="Power2015">[http://www.philosonic.com/michaelpluess_construction/Files/PowerPluess_2015_Heritability%20estimates%20of%20the%20Big%20Five%20personality%20traits%20based%20on%20common%20genetic%20variants.pdf "Heritability estimates of the Big Five personality traits based on common genetic variants"], Power & Pluess 2015</ref> 0.156(0.0074),<ref>[http://www.gwern.net/docs/genetics/2016-smith.pdf "Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci"], Smith et al 2016</ref> 0.15(0.02),<ref name="Pierson2014"/> 0.15(0.02),<ref name="Weiss2016">Weiss et al 2016, [https://www.cambridge.org/core/journals/twin-research-and-human-genetics/article/personality-polygenes-positive-affect-and-life-satisfaction/4DB2BE673BF122FB9A0AF2147EED80C0/core-reader "Personality Polygenes, Positive Affect, and Life Satisfaction"]</ref> 0.108 (0.02),<ref name="Hill2017"/> 0.146(0.007)<ref name="Hill2017b">Hill et al 2017, [http://biorxiv.org/content/early/2017/06/06/146787 "Genetic contribution to two factors of neuroticism is associated with affluence, better health, and longer life"]</ref>, 0.1437(0.0042)<ref name="Luciano2018">Luciano et al 2018, [https://www.biorxiv.org/content/early/2018/08/27/401166 "The influence of X chromosome variants on trait neuroticism"]</ref>
*** X-chromosome only: 0.0034(0.00007)<ref name="Luciano2018"/>
*** rare/family variants: 0.192 (0.025)<ref name="Hill2017"/>
*** Neuroticism worry-vulnerability facet: 0.097(0.007)<ref name="Hill2017b"/>
*** Neuroticism anxiety-tension facet: 0.078(0.007)<ref name="Hill2017b"/>
** [[Extraversion]]: 0.12(0.03)<ref name="Vinkhuyzen2012"/> 0.00(0.15)/0.05(0.072),<ref>[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4751159/ "Meta-analysis of Genome-Wide Association Studies for Extraversion: Findings from the Genetics of Personality Consortium"], van den Berg et al 2015</ref> 0.08(0.08),<ref name="Power2015"/> 0.130 (0.017)<ref name="Hill2017"/>
** [[Openness]]: 0.21(0.08)<ref name="Power2015"/>
** [[Conscientiousness]]: 0.01 (0.08),<ref name="Power2015"/> 0.16(0.02)<ref name="Pierson2014"/>
** [[Agreeableness]]: 0.001(0.08)<ref name="Power2015"/>
* Social Anxiety score: European-Americans: 0.12(0.033);<ref name="Stein2017"/> African-Americans: 0.12(0.134);<ref name="Stein2017"/> Hispanic: 0.21(0.102)<ref name="Stein2017">[https://www.dropbox.com/s/h1pojwuayp8t6y9/2017-stein.pdf "Genetic risk variants for social anxiety"], Stein et al 2017</ref>
* [[Biological basis of personality#Cloninger model of personality|Cloninger's personality dimensions]]:
** Harm Avoidance: 0.066(0.037)<ref name="Verweij2012">[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3518920/ "Maintenance of genetic variation in human personality: Testing evolutionary models by estimating heritability due to common causal variants and investigating the effect of distant inbreeding"], Verweij et al 2012</ref>
** Novelty Seeking: 0.099(0.036)<ref name="Verweij2012"/>
** Reward Dependence: 0.042(0.036)<ref name="Verweij2012"/>
** Persistence: 0.081(0.037)<ref name="Verweij2012"/>
* optimism: 0.10(0.02)<ref name="Pierson2014"/>
* Psychology [[endophenotype]]s:<ref name="Iacono2014">[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4231488/ "Knowns and unknowns for psychophysiological endophenotypes: Integration and response to commentaries"], Iacono et al 2014</ref>
** Total power: ~0.08(?)<ref name="Iacono2014"/>
** Theta power: ~0.04(?)<ref name="Iacono2014"/>
** Delta power: ~0.15(?)<ref name="Iacono2014"/>
** Beta power: ~0.19(?)<ref name="Iacono2014"/>
** CZ alpha power: ~0.21(?)<ref name="Iacono2014"/>
** O1O2 alpha power: ~0.45(?)<ref name="Iacono2014"/>
** Alpha frequency: ~0.49(?)<ref name="Iacono2014"/>
** SCL: ~0.23(?)<ref name="Iacono2014"/>
** SCR amplitude: ~0.25(?)<ref name="Iacono2014"/>
** SCR frequency: ~0.33(?)<ref name="Iacono2014"/>
** EDA factor: ~0.35(?)<ref name="Iacono2014"/>
** P3 amplitude: ~0.29(?)<ref name="Iacono2014"/>
** Antisaccade: ~0.47(?)<ref name="Iacono2014"/>
** Overall startle: ~0.49(?)<ref name="Iacono2014"/>
==== Psychiatric ====
* Antisocial Process Screening Devise (APSD; Psychopathic Symptoms); composite:0.00(0.12)/0.15(0.16)<ref name="Trzaskowski2013c"/>
** Callous-Unemotional: 0.02(0.12)/0.00(0.16),<ref name="Trzaskowski2013c"/> 0.07(0.12)<ref>[https://drrulab.files.wordpress.com/2016/01/genetics-of-callous-unemotional-behavior-in-children.pdf "Genetics of Callous-Unemotional Behavior in Children"], Viding et al 2013</ref>
** Impulsivity: 0.00(0.12)/0.24(0.16)<ref name="Trzaskowski2013c"/>
** Narcissism total: 0.00(0.12)/0.50(0.16)<ref name="Trzaskowski2013c"/>
* psychopathology in children: 0.38(0.16)<ref>[https://www.dropbox.com/s/oyp1a6thqsq09y9/2016-neumann.pdf "Single Nucleotide Polymorphism Heritability of a General Psychopathology Factor in Children"], Neumann et al 2016</ref>
* childhood trauma (sexual abuse, physical abuse, emotional abuse, emotional neglect, and physical neglect): 5-___domain continuous: 0.00(0.07),<ref name="Peyrot2017">Peyrot et al 2017, [https://www.dropbox.com/s/1srt9j8as2621h1/2017-peyrot.pdf?dl=0 "Does childhood trauma moderate polygenic risk for depression? A meta-analysis of 5,765 subjects from the Psychiatric Genomics Consortium"]</ref> 2-___domain dichotomous: 0.09(0.08)<ref name="Peyrot2017"/>
* anxiety: 0.16(0.11)<ref name="Trzaskowski2013">[http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0058676 "First genome-wide association study on anxiety-related behaviours in childhood"], Trzaskowski et al 2013</ref>
* epilepsy: 0.26(0.05)/0.27(0.06)<ref>[http://brain.oxfordjournals.org/content/137/10/2680.full "Describing the genetic architecture of epilepsy through heritability analysis"], Speed et al 2014</ref>
* [[Major depressive disorder|Depression]]: 0.21(0.021),<ref name="Lee2013"/> 0.32(0.09)/0.32(0.086),<ref name="Lubke2012">[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3404250/ "Estimating the genetic variance of major depressive disorder due to all single nucleotide polymorphisms"], Lubke et al 2012</ref> 0.19(0.10),<ref name="Boardman2015">[https://www.researchgate.net/profile/Benjamin_Domingue/publication/264795159_What_can_genes_tell_us_about_the_relationship_between_education_and_health/links/554766090cf2f5349a86df6c.pdf "What can genes tell us about the relationship between education and health?"], Boardman et al 2015</ref> 0.15(0.02),<ref name="Pierson2014"/> 0.20(0.04),<ref name="Hall2017">Hall et al 2017, [http://biorxiv.org/content/early/2017/04/24/130229?rss=1 "Genome-Wide Meta-Analyses Of Stratified Depression In Generation Scotland And UK Biobank"]</ref> 0.14(0.03),<ref name="Peyrot2017"/> 0.31(0.13)<ref name="Milaneschi2015">Milaneschi et al 2015, [https://www.researchgate.net/profile/Abdel_Abdellaoui/publication/279515037_Polygenic_dissection_of_major_depression_clinical_heterogeneity/links/5594284108ae793d13797c34.pdf "Polygenic dissection of major depression clinical heterogeneity"]</ref>
** Age at onset: 0.17(0.10),<ref name="Ferentinos2015">[http://www.tara.tcd.ie/handle/2262/73542 "Familiality and SNP heritability of age at onset and episodicity in major depressive disorder"], Ferentinos et al 2015</ref>
** Episodicity: 0.09(0.14)<ref name="Ferentinos2015"/>
*** Moods and Feelings Questionnaire (MFQ; Depressive Symptoms): 0.00(0.1)/0.00(0.12)<ref name="Trzaskowski2013c"/>
** recurrent major depressive disorder: 0.20(0.03)<ref name="Hall2017"/>
** by sex:
*** male: 0.18(0.06)<ref name="Hall2017"/>
*** female: 0.22(0.06)<ref name="Hall2017"/>
** MDD decreased-appetite subtype: 0.38(0.17)<ref name="Milaneschi2015"/>
** MDD increased-appetite subtype: 0.43(0.20)<ref name="Milaneschi2015"/>
* patient response to antidepressive treatment: all response: 0.42(0.18), SSRI response: 0.428(0.23)<ref>Tansey et al 2013, [https://www.dropbox.com/s/er4748rth65uioh/2013-tansey.pdf "Contribution of Common Genetic Variants to Antidepressant Response"]</ref>
* [[Schizophrenia]]: 0.23 (0.008),<ref name="Lee2013"/> 0.23(0.01),<ref>[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3327879/ "Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs"], Lee et al 2012</ref> 0.32(0.03),<ref>[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3827979/ "Genome-wide association analysis identifies 13 new risk loci for schizophrenia"], Ripke et al 2013</ref> 0.39(0.12),<ref>[https://genetics.emory.edu/documents/Warren%20Publications/Goes%202015.pdf "Genome-Wide Association Study of Schizophrenia in Ashkenazi Jews"], Goes et al 2015</ref> 0.24(0.09)/0.28(0.03)/0.27(0.02),<ref>[http://www.sciencedirect.com/science/article/pii/S000292971300325X "Additive Genetic Variation in Schizophrenia Risk Is Shared by Populations of African and European Descent"], Candia et al 2013</ref> 0.274(0.007),<ref name="Loh2015">[http://biorxiv.org/content/biorxiv/early/2015/06/05/016527.full.pdf "Contrasting genetic architectures of schizophrenia and other complex diseases using fast variance-components analysis"], Loh et al 2015; see also [http://biorxiv.org/content/early/2015/06/05/016527 "Contrasting regional architectures of schizophrenia and other complex diseases using fast variance components analysis"], Loh et al 2015</ref> 0.20(0.025)<ref name="Gusev2014"/>
* [[Bipolar disorder]]:<ref>[http://biorxiv.org/content/early/2016/03/22/044412 "Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder"], Hou et al 2016</ref> 0.25(0.012),<ref name="Lee2013"/> 0.37(0.04)<ref name="Lee2011"/> 0.59(0.06),<ref name="Speed2012">[http://www.sciencedirect.com/science/article/pii/S0002929712005332 "Improved heritability estimation from genome-wide SNPs"], Speed et al 2012</ref> 0.26(0.032),<ref name="Gusev2014"/> 0.26(0.032)<ref name="Gusev2013">[http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1003993 "Quantifying missing heritability at known GWAS loci"], Gusev et al 2013</ref>
* [[postpartum depression]]: 0.22(0.12)<ref name="Byrne2014">Byrne et al 2014, [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4341990/ "Applying polygenic risk scores to postpartum depression"]</ref>
* [[Borderline Personality]]: 0.23(0.09)<ref name="Lubke2014">[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3872258/ "Genome-wide analyses of borderline personality features"], Lubke et al 2014</ref>
* [[Tourette syndrome]]: 0.58(0.09)<ref name="Davis2013">[http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1003864 "Partitioning the heritability of Tourette syndrome and obsessive compulsive disorder reveals differences in genetic architecture"], Davis 2013</ref>
* [[Obsessive compulsive disorder]]: 0.37(0.07)<ref name="Davis2013"/>
* Empathy Quotient: 0.11(0.014)<ref name="Warrier2016">[http://biorxiv.org/content/early/2016/04/29/050682 "Genome-wide analyses of empathy and systemizing: heritability and correlates with sex, education, and psychiatric risk"], Warrier et al 2016</ref>
* Systemizing Quotient-Revised: 0.12(0.012)<ref name="Warrier2016"/>
* Social and Communication Disorders Checklist (SCDC): 0.24(0.07)<ref>[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4986048/ "Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population"], Robinson et al 2015</ref>
* [[Autism spectrum disorders]]: 0.17(0.025),<ref name="Lee2013"/> 0.396(0.082)/0.498(0.118),<ref name="Klei2012">[http://molecularautism.biomedcentral.com/articles/10.1186/2040-2392-3-9 "Common genetic variants, acting additively, are a major source of risk for autism"], Klei et al 2012</ref> 0.655(0.139),<ref name="Klei2012"/> 0.494(0.096),<ref>[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4137411/ "Most genetic risk for autism resides with common variation"], Gaugler et al 2014</ref> 0.24(0.07)<ref>[http://pubman.mpdl.mpg.de/pubman/item/escidoc:2196732:6/component/escidoc:2240876/art_10.1186_2040-2392-5-18.pdf "Variability in the common genetic architecture of social-communication spectrum phenotypes during childhood and adolescence"], St Pourcain et al 2014</ref>
** Childhood Asperger Syndrome Test (CAST; Autistic-Like Symptoms); composite: 0.09(0.12)/0.00(0.16)<ref name="Trzaskowski2013c"/>
*** Communication: 0.00(0.12)/0.00(0.15)<ref name="Trzaskowski2013c"/>
*** Nonsocial: 0.00(0.12)/0.00(0.16)<ref name="Trzaskowski2013c"/>
*** Social: 0.06(0.12)/0.00(0.16)<ref name="Trzaskowski2013c"/>
** male/female differences in autism etiology<ref>Mitra et al 2016, [http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1006425 "Pleiotropic Mechanisms Indicated for Sex Differences in Autism"]</ref>
** autism symptoms (SCDC):
*** age 8: 0.24(0.07)<ref name="Stergiakouli2017"/>
*** age 11: 0.16(0.07)<ref name="Stergiakouli2017"/>
*** age 14: 0.08(0.07)<ref name="Stergiakouli2017"/>
*** age 17: 0.45(0.09)<ref name="Stergiakouli2017"/>
* [[Attention-deficit/hyperactivity disorder|ADHD]]: 0.28(0.023),<ref name="Lee2013">[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3800159/ "Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs"], Lee et al 2013</ref> 0.40(0.14),<ref name="Pappa2015"/> 0.42(0.13),<ref>[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4321789/ "Polygenic transmission and complex neuro developmental network for attention deficit hyperactivity disorder: genome-wide association study of both common and rare variants"], Yang et al 2013</ref> 0.5902(0.279)<ref name="Bidwell2017">Bidwell et al 2017, [https://www.dropbox.com/s/3b14bdryixht79n/2017-bidwell.pdf "Genetic influences on ADHD symptom dimensions: Examination of a priori candidates, gene-based tests, genome-wide variation, and SNP heritability"]</ref>
** hyperactivity-impulsivity: 0.5383(0.262)<ref name="Bidwell2017"/>
** inattention: 0.4365(0.301)<ref name="Bidwell2017"/>
* ADHD symptoms (SDQ-ADHD):
** age 12: 0.19(0.07)<ref name="Stergiakouli2017">Stergiakouli et al 2017, [https://molecularautism.biomedcentral.com/articles/10.1186/s13229-017-0131-2 "Shared genetic influences between dimensional ASD and ADHD symptoms during child and adolescent development"]</ref>
** age 13: 0.18(0.07)<ref name="Stergiakouli2017"/>
* DSM-IV–based ADHD scale from the Conners' Parent Rating Scale–Revised (CPRS-R); Conners composite: 0.00(0.12)<ref name="Trzaskowski2013c">[http://www.sciencedirect.com/science/article/pii/S0890856713005182 "No genetic influence for childhood behavior problems from DNA analysis"], Trzaskowski et al 2013</ref>
** Hyperactivity-impulsivity: 0.06(0.12)<ref name="Trzaskowski2013c"/>
** Inattention: 0.00(0.12)<ref name="Trzaskowski2013c"/>
* Child behavioral problems (ADHD, externalizing problems, total problems): 0.40(0.14)/0.37(0.14)/0.45(0.14)/0.20(0.14)/0.12(0.10)/0.12(0.10)/0.18(0.10)/0.16(0.11)/0.71(0.22)/0.44(0.22)/0.11(0.16)<ref name="Pappa2015">[https://www.researchgate.net/profile/Irene_Pappa/publication/278969768_Single_Nucleotide_Polymorphism_Heritability_of_Behavior_Problems_in_Childhood_Genome-Wide_Complex_Trait_Analysis/links/55ed557508ae3e121847fffd.pdf "Single nucleotide polymorphism heritability of behavior problems in childhood: genome-wide complex trait analysis"], Pappa et al 2015</ref>
* childhood aggression: 0.10(0.06)/0.54(0.19)/0.46(0.35)/0.08(0.06)<ref>[http://pubman.mpdl.mpg.de/pubman/item/escidoc:2176524/component/escidoc:2332385/Pappa_etal_AMJMedGenB_2015.pdf "A genome-wide approach to children's aggressive behavior: The EAGLE consortium"], Pappa et al 2015b</ref>
* Preschool internalizing problems: 0.26(0.07)/0.18(0.30)/0.13(0.33)<ref>[http://www.tweelingenregister.org/nederlands/verslaggeving/NTR-publicaties_2014/Benke_JAACAP_2014.pdf "A genome-wide association meta-analysis of preschool internalizing problems"], Benke et al 2014</ref>
* Strengths and Difficulties Questionnaire (SDQ; Behavior Problems); composite: 0.00(0.1)/0.00(0.12)/0.11(0.15)<ref name="Trzaskowski2013c"/>
** Anxiety: 0.02(0.12)/0.00(0.12)/0.11(0.15)<ref name="Trzaskowski2013c"/>
** Conduct: 0.00(0.12)/0.00(0.12)/0.26(0.15)<ref name="Trzaskowski2013c"/>
** Hyperactivity: 0.00(0.12)/0.00(0.12)/0.05(0.15)<ref name="Trzaskowski2013c"/>
** Peer problems: 0.00(0.1)/0.16(0.12)/0.00(0.15),<ref name="Trzaskowski2013c"/> 0.04(0.05)/0.06(0.05)/0.11(0.06)/0.02(0.05)<ref>[https://link.springer.com/article/10.1007/s00439-014-1514-5/fulltext.html "Heritability and genome-wide analyses of problematic peer relationships during childhood and adolescence"], St Pourcain et al 2015 <!-- backup link for supplemental: https://www.dropbox.com/s/l4pakhesfoofali/2015-pourcain-supplementary.docx --></ref>
* Psychotism:
** Paranoia 0.14(0.13)<ref name="Sieradzka2015">[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4561057/ "Heritability of Individual Psychotic Experiences Captured by Common Genetic Variants in a Community Sample of Adolescents"], Sieradzka 2015</ref>
** Hallucinations: 0.00(0.12)<ref name="Sieradzka2015"/>
** Cognitive Disorganization: 0.19(0.13)<ref name="Sieradzka2015"/>
** Grandiosity: 0.17(0.13)<ref name="Sieradzka2015"/>
** Anhedonia: 0.20(0.12)<ref name="Sieradzka2015"/>
** Negative Symptoms: 0.00(0.12)<ref name="Sieradzka2015"/>
* [[Parkinson's Disease]]: 0.22(0.02),<ref>[http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1002141 "Web-based genome-wide association study identifies two novel loci and a substantial genetic component for Parkinson's disease"], Do et al 2011</ref> 0.27(0.05),<ref name="Keller2012">[http://hmg.oxfordjournals.org/content/21/22/4996.full "Using genome-wide complex trait analysis to quantify 'missing heritability' in Parkinson's disease"], Keller et al 2012</ref> 0.28(0.05)<ref name="Guerreiro2016"/>
** Early onset: 0.15(0.14)<ref name="Keller2012"/>
** Late onset: 0.31(0.07)<ref name="Keller2012"/>
* [[dementia with Lewy bodies]]: 0.31(0.03)<ref name="Guerreiro2016">Guerreiro et al 2016, [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4759606/ "Genome-wide analysis of genetic correlation in dementia with Lewy bodies, Parkinson's and Alzheimer's diseases"]</ref>
* [[Alzheimer's disease]]: 0.60(0.05)<ref name="Guerreiro2016"/>
* PTSD: 0.12(0.05)<ref name="Duncan2017">Duncan et al 2017, [http://www.nature.com/mp/journal/vaop/ncurrent/full/mp201777a.html "Largest GWAS of PTSD (''N''=20070) yields genetic overlap with schizophrenia and sex differences in heritability"]</ref>
** female PTSD: 0.21(0.09)<ref name="Duncan2017"/>
** male PTSD: 0.08(0.10)<ref name="Duncan2017"/>
==== Drug use ====
* [[Caffeine]] use: 0.07(?)<ref>[http://www.nature.com/mp/journal/v20/n5/extref/mp2014107x1.pdf "Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption"], The Coffee and Caffeine Genetics Consortium et al 2014</ref>
* [[Marijuana]] ever: 0.06(0.102),<ref>Verweij et al 2013, [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3548058/ "The genetic aetiology of cannabis use initiation: a meta-analysis of genome-wide association studies and a SNP-based heritability estimation"]</ref> 0.25(0.088)<ref>[https://link.springer.com/article/10.1007/s10519-015-9723-9 "Heritability, SNP- and Gene-Based Analyses of Cannabis Use Initiation and Age at Onset"], Minca et al 2015</ref>
** marijuana use disorder: 0.09(0.03)<ref>Demontis et al 2017, [https://www.biorxiv.org/content/early/2017/12/21/237321 "Genome-wide association study implicates CHRNA2 in cannabis use disorder"] ([https://www.biorxiv.org/content/biorxiv/suppl/2017/12/21/237321.DC1/237321-1.pdf supplement table 6])</ref>
* [[Smoking]] ever: 0.19(0.087)<ref name="Lubke2012"/>
* Smoking, current: 0.24(0.096),<ref name="Lubke2012"/> 0.19(0.102),<ref name="McGue2013"/> 0.18(0.16),<ref name="Vrieze2013">[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3579160/ "Three mutually informative ways to understand the genetic relationships among behavioral disinhibition, alcohol use, drug use, nicotine use/dependence, and their co-occurrence: Twin biometry, GCTA, and genome-wide scoring"], Vrieze et al 2013</ref> 0.19(0.04)<ref name="Pierson2014"/>
* alcohol
** alcohol consumption: 0.14(0.071),<ref name="McGue2013">[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3886341/ "A genome-wide association study of behavioral disinhibition"], McGue et al 2013</ref> 0.16(0.16)<ref name="Vrieze2013"/> 0.19 (0.11),<ref name="Webb2017">[http://journal.frontiersin.org/article/10.3389/fgene.2017.00030/abstract "Molecular genetic influences on normative and problematic alcohol use in a population-based sample of college students"], Webb et al 2017</ref> 0.13(0.01)<ref name="Clarke2017">Clarke et al 2017, [http://biorxiv.org/content/early/2017/03/14/116707 "Genome-wide association study of alcohol consumption and genetic overlap with other health-related traits in UK Biobank (N=112,117)"]</ref>
*** male: 0.16(0.01)<ref name="Clarke2017"/>
*** female: 0.13(0.01)<ref name="Clarke2017"/>
** alcohol dependence: 0.08(0.107),<ref name="McGue2013"/> 0.12(0.16),<ref name="Vrieze2013"/> 0.235(0.03)<ref name="Zaitlen2013"/> 0.02(0.10)<ref name="Webb2017"/>
*** alcohol abuse (Alcohol Use Disorders Identification Test/AUDIT): 0.1205(0.0191)<ref name="Sanchez-Roige2017">Sanchez-Roige et al 2017, [http://biorxiv.org/content/early/2017/06/15/147397 "Genome-wide association study of Alcohol Use Disorder Identification Test (AUDIT) scores in 20,328 research participants of European ancestry"]</ref>
** alcohol dependence diagnosis: 0.30(0.136)<ref name="Palmer2015b">Palmer et al 2015, [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4644467/ "Shared Additive Genetic Influences on DSM-IV Criteria for Alcohol Dependence in Subjects of European Ancestry"]</ref>
*** alcohol tolerance: 0.242(0.129)<ref name="Palmer2015b"/>
*** alcohol withdrawal: 0.281(0.174)<ref name="Palmer2015b"/>
*** using alcohol longer than intended: 0.324(0.158)<ref name="Palmer2015b"/>
*** Unsuccessful attempts to cut down alcohol consumption: 0.197(0.146)<ref name="Palmer2015b"/>
*** Great time spent using/recovering from alcohol: 0.072(0.104)<ref name="Palmer2015b"/>
*** Social/Occupation activities foregone due to alcohol: 0.199(0.091)<ref name="Palmer2015b"/>
*** Continued use of alcohol despite problems: 0.237(0.109)<ref name="Palmer2015b"/>
** maximum drinks: 0.01(0.12)<ref name="Webb2017"/>
* Illicit Drugs: 0.37(0.102),<ref name="McGue2013"/> 0.22(0.16),<ref name="Vrieze2013"/>
* DSM-IV drug dependence diagnoses (DD): 0.36(0.13)<ref name="Palmer2015">[http://www.downstate.edu/hbnl/documents/2015-Palmer-Examiningtheroleofcommongeneticvariantsonalcoholtobaccocannabisandillicitdrugdep.pdf "Examining the role of common genetic variants on alcohol, tobacco, cannabis and illicit drug dependence: Genetics of vulnerability to drug dependence"], Palmer et al 2015</ref>
** factor score based on problem use (PU; i.e. 1+ [[DSM-IV]] symptoms): 0.25(0.13)<ref name="Palmer2015"/>
** drug dependence vulnerability (DV; a ratio of DSM-IV symptoms to the number of substances used): 0.33(0.13)<ref name="Palmer2015"/>
==== Disease ====
* allergic diseases: 0.075(0.007)<ref name="Zhu2017"/>
* [[Allergic rhinitis]]: 0.074(0.015)<ref name="Loh2015"/>
* [[Amyotrophic lateral sclerosis]]: 0.085(0.005)<ref>[http://www.research.ed.ac.uk/portal/files/26903768/MinE_GWAS_manuscript_NG.pdf "Genome-wide association analyses identify new risk variants and the genetic architecture of amyotrophic lateral sclerosis"], van Rheenen et al 2016</ref>
* [[Asthma]]: 0.264(0.067),<ref name="Zaitlen2013"/> 0.152(0.018),<ref name="Loh2015"/> 0.072(0.007),<ref name="Zhu2017">Zhu et al 2017, [http://biorxiv.org/content/early/2017/05/26/133322 "Shared Genetic Architecture Of Asthma With Allergic Diseases: A Genome-wide Cross Trait Analysis Of 112,000 Individuals From UK Biobank"]</ref> 0.38(0.015)<ref name="Ek2017">Ek et al 2017, ["Genome-wide association analysis identifies 26 novel loci for asthma, hay fever and eczema"]</ref>
** Airway hyperresponsiveness (AHR): 0.45(0.29)<ref name="McGeachie2016">McGeachie et al 2016, [http://onlinelibrary.wiley.com/doi/10.1002/iid3.133/full "Whole genome prediction and heritability of childhood asthma phenotypes"]</ref>
** Serum total IgE (IGE): 0.53(0.27)<ref name="McGeachie2016"/>
** Eosinophil count (EOS): 0.29(0.32)<ref name="McGeachie2016"/>
** Pre-bronchodilator FEV1: 0.81(0.22)<ref name="McGeachie2016"/>
** Post-bronchodilator FEV: 0.83(0.22)<ref name="McGeachie2016"/>
** Bronchodilator response (BDR): 0.67(0.24)<ref name="McGeachie2016"/>
** Steroid responsiveness endophenotype (SRE): 0.00(0.42)<ref name="McGeachie2016"/>
** Normal lung growth only: 0.47(0.27)<ref name="McGeachie2016"/>
** Normal lung growth with early decline: 0.55(0.23)<ref name="McGeachie2016"/>
** Reduced lung growth only: 0.49(0.26)<ref name="McGeachie2016"/>
** Reduced lung growth with early decline: 0.17(0.27)<ref name="McGeachie2016"/>
** Early decline with normal or reduced lung growth: 0.22(0.28)<ref name="McGeachie2016"/>
** Reduced lung growth with or without early decline: 0.95(0.19)<ref name="McGeachie2016"/>
* [[hay fever]]: 0.53(0.05)<ref name="Pierson2014"/>
** hay fever/eczema: 0.30(0.020)<ref name="Ek2017"/>
* [[Multiple sclerosis]]: 0.19(0.009),<ref name="Gusev2013"/> 0.3(0.02),<ref>[http://www.nature.com/articles/srep00770 "Estimating the proportion of variation in susceptibility to multiple sclerosis captured by common SNPs"], Watson et al 2012</ref> 0.19(0.009)<ref name="Gusev2014"/>
* autoimmune Systemic RA+SLE+SSc+AS (rheumatoid arthritis, systemic lupus erythematosus, systemic sclerosis, ankylosing spondylitis): 0.2(0.048)<ref name="Zaitlen2013"/>
* T-cell mediated autoimmune disease: 0.192(0.033)<ref name="Zaitlen2013"/>
* [[Crohn's disease]]: 0.18 0.024),<ref name="Gusev2013"/> 0.61(0.08),<ref name="Lee2011">[http://www.sciencedirect.com/science/article/pii/S0002929711000206 "Estimating missing heritability for disease from genome-wide association studies"], Lee et al 2011</ref> 0.54(0.06),<ref name="Speed2012"/> 0.18(0.024),<ref name="Gusev2014"/> 0.46(0.020)<ref name="Chen2014">Chen et al 2014, [http://hmg.oxfordjournals.org/content/23/17/4710.full "Estimation and partitioning of (co)heritability of inflammatory bowel disease from GWAS and immunochip data"]</ref>
* [[Ulcerative colitis]]: 0.17(0.017),<ref name="Gusev2013"/> 0.17(0.017)<ref name="Gusev2014"/>
* [[psoriasis]]: 0.349(0.06)<ref>Yin et al 2014, [https://bmcgenomics.biomedcentral.com/articles/10.1186/1471-2164-15-87 "Common variants explain a large fraction of the variability in the liability to psoriasis in a Han Chinese population"]</ref>
* [[celiac disease]]: 0.33(0.042)<ref name="Stahl2012"/>
* [[Macular degeneration]]: 0.242(0.029),<ref name="Loh2015"/> 0.36(0.016)<ref name="Chen2014"/>
* [[Arthritis]]: 0.11(0.031),<ref name="Gusev2013"/> 0.57(0.06),<ref name="Speed2012"/> 0.098(0.014),<ref name="Loh2015"/> 0.11(0.031),<ref name="Gusev2014"/> 0.126(0.026)/0.261(0.061),<ref name="Zaitlen2013"/> 0.32(0.037)<ref name="Stahl2012">Stahl et al 2012, [http://coruscant.itmat.upenn.edu/pubs/stahlea_natgenet_polygene.pdf "Bayesian inference analyses of the polygenic architecture of rheumatoid arthritis"]</ref>
* [[Osteoporosis]]: 0.195(0.024)<ref name="Loh2015"/>
* [[Ankylosing spondylitis]]: 0.18(0.028)<ref name="Gusev2014">[http://www.sciencedirect.com/science/article/pii/S0002929714004261 "Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases"], Gusev et al 2014a; see also [http://biorxiv.org/content/early/2014/04/20/004309 "Regulatory variants explain much more heritability than coding variants across 11 common diseases"], Gusev et al 2014b</ref>
* [[breast cancer]] (BC): 0.117(0.051),<ref name="Zaitlen2013"/> 0.57(0.11)/0.32(0.17)<ref name="Li2013"/>
* [[prostate cancer]] (PC): 0.204(0.056),<ref name="Zaitlen2013"/> 0.30(0.06)<ref>[http://biorxiv.org/content/early/2015/07/31/023440.1 "The contribution of rare variation to prostate cancer heritability"], Mancuso et al 2015</ref>
* [[Hematoma]] volume: 0.60(0.70)<ref name="Devan2013"/>
* Intracerebral hemorrhage mortality: 0.40(0.70)<ref name="Devan2013"/>
* [[Intracerebral hemorrhage]] risk: 0.44(0.21)<ref name="Devan2013">[http://stroke.ahajournals.org/content/44/6/1578.full.pdf "Heritability Estimates Identify a Substantial Genetic Contribution to Risk and Outcome of Intracerebral Hemorrhage"], Devan et al 2013</ref>
* [[Dyslipidemia]]: 0.263(0.014)<ref name="Loh2015"/>
* [[HIV]] viral load: 0.084(0.04)<ref>[http://biorxiv.org/content/biorxiv/early/2015/10/14/029017.full.pdf "Estimating the respective contributions of human and viral genetic variation to HIV control"], Bartha et al 2015</ref>
* [[esophageal adenocarcinoma]]: 0.0(0.21)<ref name="Ek2013">Ek et al 2013, [http://jnci.oxfordjournals.org/content/105/22/1711.full "Germline genetic contributions to risk for esophageal adenocarcinoma, Barretts Esophagus, and gastroesophageal reflux"]</ref>
* [[Barrett's esophagus]]: 0.35(0.06)<ref name="Ek2013"/>
* [[Gastroesophageal reflux disease]]: 0.25(0.05)<ref name="Ek2013"/>
* [[developmental dysplasia of the hip]]: 0.55(0.06)<ref>Hatzikotoulas et al 2017, [https://www.dropbox.com/s/r3dq3uq61saztjn/2017-hatzikotoulas.pdf "National clinical audit data decodes the genetic architecture of developmental dysplasia of the hip"]</ref>
==== Heart-related ====
* [[Hypertension]]: 0.42(0.06),<ref name="Speed2012"/> 0.255(0.014),<ref name="Loh2015"/> 0.37(0.053),<ref name="Gusev2014"/> 0.60(0.089)<ref name="Gusev2013"/>
** in pregnancy: 0.083(0.043)<ref name="Zaitlen2013"/>
* fasting [[triglyceride]]s (TG): 0.16(0.05),<ref name="Vattikuti2012"/> 0.31(0.061)<ref name="Chen2015"/>
* Total cholesterol: 0.15(0.061)<ref name="Chen2015">[http://www.sciencedirect.com/science/article/pii/S0002929715004061 "Dominant Genetic Variation and Missing Heritability for Human Complex Traits: Insights from Twin versus Genome-wide Common SNP Models"], Chen et al 2015</ref>
* fasting [[high-density lipoprotein]] (HDL): 0.12(0.05)<ref name="Vattikuti2012"/><ref name="Morrison2013">[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4030301/ "Whole-genome sequence–based analysis of high-density lipoprotein cholesterol"], Morrison et al 2013</ref> 0.24(0.061),<ref name="Chen2015"/> 0.45(0.017)<ref name="Zaitlen2013"/>
* low density lipoprotein cholesterol (LDL): 0.16(0.061),<ref name="Chen2015"/> 0.199(0.063)<ref name="Zaitlen2013">[http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1003520 "Using Extended Genealogy to Estimate Components of Heritability for 23 Quantitative and Dichotomous Traits"], Zaitlen et al 2013</ref>
* [[systolic blood pressure]] (SBP): 0.24(0.05)<ref name="Vattikuti2012"/>
* [[Cardiovascular disease]]: 0.092(0.015)<ref name="Loh2015"/>
* [[Coronary artery disease]]: 0.30(0.058),<ref name="Gusev2013"/> 0.39(0.06),<ref name="Speed2012"/> 0.31(0.057),<ref name="Gusev2014"/> 0.146(0.017),<ref name="Zaitlen2013"/> 0.41(0.067)<ref name="Stahl2012"/>
* [[Ischemic stroke]]:
** all: 0.379(0.052)<ref name="Bevan2012">Bevan et al 2012, [https://s3.amazonaws.com/academia.edu.documents/46072372/Genetic_Heritability_of_Ischemic_Stroke_20160530-6664-1umiyy2.pdf "Genetic heritability of ischemic stroke and the contribution of previously reported candidate gene and genome-wide associations"]</ref>
** large-vessel disease: 0.403(0.076)<ref name="Bevan2012"/>
** small-vessel disease: 0.161(0.077)<ref name="Bevan2012"/>
** Cardioembolic stroke: 0.326(0.074)<ref name="Bevan2012"/>
==== Diabetes-related ====
* [[Diabetes Type I]]: 0.13(0.030),<ref name="Gusev2013"/> 0.28 (0.04),<ref name="Lee2011"/> 0.73(0.06),<ref name="Speed2012"/> 0.13 (0.030)<ref name="Gusev2014"/>
* [[Diabetes type II]]: 0.35(0.06),<ref name="Speed2012"/> 0.297(0.022),<ref name="Loh2015"/> 0.37(0.065),<ref name="Gusev2014"/> 0.254(0.041),<ref name="Zaitlen2013"/> 0.36(0.066),<ref name="Gusev2013"/> 0.286(?),<ref>[http://biorxiv.org/content/early/2016/02/25/041335 "Type 2 Diabetes Risk Prediction Incorporating Family History Revealing a Substantial Fraction of Missing Heritability"], Gim et al 2016</ref> 0.51(0.065)<ref name="Stahl2012"/>
* [[Fasting glucose]]: 0.198(0.075),<ref name="Zheng2013">[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3810463/ "Genome-Wide Contribution of Genotype by Environment Interaction to Variation of Diabetes-Related Traits"], Zheng et al 2013 <!-- while focused on GxE, they necessarily estimate the main effects as well, check the supplements --></ref> 0.22(0.059),<ref name="Lubke2012"/> 0.10(0.05),<ref name="Vattikuti2012"/> 0.17(0.061)<ref name="Chen2015"/>
* [[HbA1c]]: 0.20(0.061)<ref name="Chen2015"/>
* fasting [[insulin]] (INS): 0.202(0.075),<ref name="Zheng2013"/> 0.09(0.05)<ref name="Vattikuti2012"/>
==== Biological ====
* X chromosome heritability in 20 UK Biobank traits: males, 0.0062(0.0034); females, 0.0030 (0.00020)<ref>Sidorenko et al 2018, [https://www.biorxiv.org/content/early/2018/10/03/433870 "The effect of X-linked dosage compensation on complex trait variation"]</ref>
* [[QT interval]] (QTi): 0.209(0.050)<ref name="Yang2011"/>
* [[von Willebrand factor]] (vWF): 0.252(0.051)<ref name="Yang2011"/>
* [[Hemoglobin]]: 0.21(0.061)<ref name="Chen2015"/>
* [[Cystatin]]: 0.27(0.061)<ref name="Chen2015"/>
* [[Creatinine]]: 0.18(0.061)<ref name="Chen2015"/>
* estimated [[Renal function|glomerular filtration rate]] (eGFR): 0.32(0.061)<ref name="Chen2015"/>
* [[Vitamin D]] blood levels: 0.23(0.147)<ref>[http://jn.nutrition.org/content/145/4/799.full.pdf "Genetic and Environmental Factors Are Associated with Serum 25-Hydroxyvitamin D Concentrations in Older African Americans"], Hansen et al 2015</ref>
* [[Epigenetic clock|Epigenetic age acceleration]]: 0.41(?)<ref name="Levine2015">[http://www.impactaging.com/papers/v7/n12/full/100864.html "Epigenetic age of the pre-frontal cortex is associated with neuritic plaques, amyloid load, and Alzheimer's disease related cognitive functioning "], Levine et al 2015</ref>
* [[Amyloid|Amyloid plaque]]: 0.03(?)<ref name="Levine2015"/>
* [[Senile plaques|Neuritic plaque]]: 0.05(?)<ref name="Levine2015"/>
* Diffuse plaque: 0.38(?)<ref name="Levine2015"/>
* [[Neurofibrillary tangle]]s (NFT): 0.00(?)<ref name="Levine2015"/>
* [[thyroid hormone]] levels:
** [[Thyroid-stimulating hormone|TSH]]: 0.24(0.255) <ref name="Taylor2015">[http://www.uk10k.org/assets/25743335.pdf "Whole-genome sequence-based analysis of thyroid function"], Taylor et al 2015</ref>
** [[FT4]]: 0.20(0.306)<ref name="Taylor2015"/>
* [[HOMA-IR]]: 0.209(0.075)<ref name="Zheng2013"/>
* [[HOMA-B]]: 0.187(0.077)<ref name="Zheng2013"/>
* [[Apolipoprotein A1]]: 0.17(0.061)<ref name="Chen2015"/>
* [[Apolipoprotein B]]: 0.14(0.071)<ref name="Chen2015"/>
* [[C-reactive protein]]: 0.37(0.061)<ref name="Chen2015"/>
* [[Immunoglobulin A]]: 0.24(0.061)<ref name="Chen2015"/>
* [[monocyte]] white blood cell count: 0.343(0.032)<ref name="Zaitlen2013"/>
* [[Genetic recombination|recombination]] rate: 0.099(0.023)<ref name="Zaitlen2013"/>
* [[telomere]] length: 0.31(0.14)<ref>[http://www.tandfonline.com./doi/abs/10.1080/19485565.2015.1120645 "Estimating Telomere Length Heritability in an Unrelated Sample of Adults: Is Heritability of Telomere Length Modified by Life Course Socioeconomic Status?"], Faul et al 2016</ref>
===== Neanderthal admixture =====
[[Neanderthal]] admixture as a risk factor for:<ref>{{br-separated entries |[http://news.harvard.edu/gazette/story/2014/01/neanderthals-dna-legacy-linked-to-modern-ailments/ "Neanderthals’ DNA legacy linked to modern ailments: Humans inherited variants affecting disease risk, infertility, skin and hair characteristics"], Stephanie Dutchen, 2014-01-29 |[https://www.dropbox.com/s/urpbjiinbp57q9p/2016-simonti.pdf "The phenotypic legacy of admixture between modern humans and Neandertals"], Corinne N. Simonti et al, 2016-02-11}}</ref>{{Unreliable source? |reason=Reports GCTA estimates on a weird scale without SEs. |date=September 2016}}
* [[Mood disorder]]s
* [[Major depressive disorder|Depression]]
* [[Actinic keratosis]]
* [[Seborrheic keratosis]]
* [[Obesity]]
* [[Overweight]]
* [[Acute upper respiratory infections]]
* [[Coronary atherosclerosis]]
* [[Hypercoagulability|Hypercoagulation]]
* [[Tobacco use]]<ref>{{br-separated entries |[http://mbe.oxfordjournals.org/content/33/10/2648 Divergent ah receptor ligand selectivity during hominin evolution], Troy D. Hubbard et al, 2016-08-02 |[https://www.theguardian.com/science/2016/aug/02/smoke-signals-dna-adaptation-helped-early-humans-deal-with-toxic-fumes Smoke signals: DNA adaptation helped early humans deal with toxic fumes], Naomi Stewart, 2016-08-02}}</ref>
* [[Type 2 diabetes]]
* [[Crohn's disease]]
* [[Lupus]]
* [[Biliary cirrhosis]]
* [[Infertility]]
=== Animal/plant ===
* [[Boar taint]]: 0.118(0.064)<ref>[http://bmcgenomics.biomedcentral.com/articles/10.1186/1471-2164-15-424 "Analysis of the genetics of boar taint reveals both single SNPs and regional effects"], Rowe et al 2014</ref>
* [[Merino sheep]] body size: ?<ref>[https://asas.org/docs/default-source/wcgalp-posters/599_paper_9386_manuscript_602_0.pdf "Genome-Wide Association Study on Body Weight Reveals Major Loci on OAR6 in Australian Merino Sheep"], Al-Mamun et al 2014</ref><!-- no total reported -->
* [[Anopheles arabiensis|Mosquito]] behavior:
** host preference (cattle vs human): 0.94(3.47)<ref name="Main2016">[http://biorxiv.org/content/early/2016/04/05/044701 "The genetic basis of host preference and indoor resting behavior in the major African malaria vector, ''Anopheles arabiensis''"], Main et al 2016</ref>
** resting behavior (indoors vs outdoors): 0.05(2.34)<ref name="Main2016"/>
* [[Cassava]] resistance to [[Cassava mosaic disease]]: 0.51<ref>[http://biorxiv.org/content/biorxiv/early/2015/11/11/031179.full.pdf "Genome-wide association and prediction reveals the genetic architecture of cassava mosaic disease resistance and prospects for rapid genetic improvement"], Wolfe et al 2015</ref>
<!-- todo: summarize tempest in a teapot == Unbiasedness == http://infoproc.blogspot.com/2016/01/gcta-missing-heritability-and-all-that.html http://infoproc.blogspot.com/2016/02/missing-heritability-and-gcta-update-on.html http://biorxiv.org/content/biorxiv/early/2016/09/09/074310.full.pdf
robust to heteroscedastic errors: Domingue et al 2016
see also Conley -->
== See also ==
| 