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A Eyre-Walker

A Ganna

A Kong

A Okbay

A Terracciano

AA Vinkhuyzen

AF McRae

AK MacLeod

Andrew M. McIntosh

AR Jensen

AR Power

B Bulik-Sullivan

B Rammstedt

BB Lahey

BH Smith

C Amador

C Spearman

C Xia

CA Rietveld

Carmen Amador

Caroline Hayward

Charley Xia

Chris S. Haley

D Conley

D J Smith

D Posthuma

D Wechsler

David J. Porteous

E Krapohl

ED Gamsiz

FR Day

G Davies

GC Banks

GD Batty

HM Chipuer

Ian J. Deary

IJ Deary

J Bashi

J O’Connell

J Yang

James M. Sherlock

JC Raven

JP Beauchamp

Kevin L. Gunderson

KJ Verweij

L Penke

Lars Penke

M Jokela

M Lezak

M Luciano

Michael R Johnson

Michelle Luciano

N Barban

N Zaitlen

Nicholas Mancuso

O Delaneau

OJ Bienvenu

P Visscher

Pau Navarro

PK Joshi

PS Dyrenforth

R Durbin

R Nagy

R Plomin

RA Yeo

RC Arslan

RE Marioni

Reka Nagy

RM Kirkpatrick

RO Roberts

Ruben C. Arslan

S Dongen Van

SB Eysenck

SM Berg van Den

SM Kerr

T Vukasović

TJ Polderman

W D Hill

W. David Hill

WD Hill

YB Simons

Z Zhu

English

NEUROSURGERY ENTHUSIASTIC WOMEN SOCIETY

Genomic analysis of family data reveals additional genetic effects on intelligence and personality

Pedigree-based analyses of intelligence have reported that genetic differences account for 50-80% of the phenotypic variation. For personality traits these effects are smaller, with 34-48% of the variance being explained by genetic differences. However, molecular genetic studies using unrelated individuals typically report a heritability estimate of around 30% for intelligence and between 0 and 15% for personality variables. Pedigree-based estimates and molecular genetic estimates may differ because current genotyping platforms are poor at tagging causal variants, variants with low minor allele frequency, copy number variants, and structural variants. Using ~20,000 individuals in the Generation Scotland family cohort genotyped for ~700,000 single-nucleotide polymorphisms (SNPs), we exploit the high levels of linkage disequilibrium (LD) found in members of the same family to quantify the total effect of genetic variants that are not tagged in GWAS of unrelated individuals. In our models, genetic variants in low LD with genotyped SNPs explain over half of the genetic variance in intelligence, education, and neuroticism. By capturing these additional genetic effects our models closely approximate the heritability estimates from twin studies for intelligence and education, but not for neuroticism and extraversion. We then replicated our finding using imputed molecular genetic data from unrelated individuals to show that ~50% of differences in intelligence, and ~40% of the differences in education, can be explained by genetic effects when a larger number of rare SNPs are included. From an evolutionary genetic perspective, a substantial contribution of rare genetic variants to individual differences in intelligence, and education is consistent with mutation-selection balance

Hill, W. David

Arslan, Ruben C.

Xia, Charley

Luciano, Michelle

Amador, Carmen

Navarro, Pau

Hayward, Caroline

Nagy, Reka

Porteous, David J.

McIntosh, Andrew M.

Deary, Ian J.

Haley, Chris S.

Penke, Lars

GRO.publications (Univ. Göttingen)

Pedigree-based analyses of intelligence have reported that genetic differences account for 50–80% of the phenotypic variation. For personality traits these effects are smaller, with 34–48% of the variance being explained by genetic differences. However, molecular genetic studies using unrelated individuals typically report a heritability estimate of around 30% for intelligence and between 0 and 15% for personality variables. Pedigree-based estimates and molecular genetic estimates may differ because current genotyping platforms are poor at tagging causal variants, variants with low minor allele frequency, copy number variants, and structural variants. Using ~20,000 individuals in the Generation Scotland family cohort genotyped for ~700,000 single-nucleotide polymorphisms (SNPs), we exploit the high levels of linkage disequilibrium (LD) found in members of the same family to quantify the total effect of genetic variants that are not tagged in GWAS of unrelated individuals. In our models, genetic variants in low LD with genotyped SNPs explain over half of the genetic variance in intelligence, education, and neuroticism. By capturing these additional genetic effects our models closely approximate the heritability estimates from twin studies for intelligence and education, but not for neuroticism and extraversion. We then replicated our finding using imputed molecular genetic data from unrelated individuals to show that ~50% of differences in intelligence, and ~40% of the differences in education, can be explained by genetic effects when a larger number of rare SNPs are included. From an evolutionary genetic perspective, a substantial contribution of rare genetic variants to individual differences in intelligence, and education is consistent with mutation-selection balance

Genomic analysis of family data reveals additional genetic effects on intelligence and personality

Abstract

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NEUROSURGERY ENTHUSIASTIC WOMEN SOCIETY

GRO.publications (Univ. Göttingen)

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Edinburgh Research Explorer

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