# Genetic variants for head size share genes and pathways with cancer

Maria J Knol, Raymond A Poot, Tavia E Evans, Claudia L Satizabal, Aniket Mishra, Muralidharan Sargurupremraj, Sandra van der Auwera, Marie-Gabrielle Duperron, Xueqiu Jian, Isabel C Hostettler, et al.

<figure><img src="image_1.png" /></figure>

To cite this version:

Maria J Knol, Raymond A Poot, Tavia E Evans, Claudia L Satizabal, Aniket Mishra, et al. Genetic variants for head size share genes and pathways with cancer. Cell Reports Medicine, 2024, 5 (5), pp.101529. 10.1016/j.xcrm.2024.101529. hal-04627076v2

HAL Id: hal-04627076

https://hal.science/hal-04627076v2

Submitted on 28 Jun 2024

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Distributed under a Creative Commons Attribution 4.0 International License
# Genetic variants for head size share genes and pathways with cancer

## Graphical abstract

<figure><img src="image_1.png" /></figure>

## Authors

Maria J. Knol, Raymond A. Poot, Tavia E. Evans, ..., Paul M. Thompson, Sudha Seshadri, Hieab H.H. Adams

## Correspondence

hieab.adams@radboudumc.nl

## In brief

Knol, Poot, et al. identify 67 loci for human head size in a genome-wide association study. Genes harboring the lead variants enrich for cancer genes and pathways, which was not seen for height variants. These findings suggest a potential link between a larger head and a higher cancer risk.

## Highlights

* Knol, Poot, et al. identify 67 genetic loci associated with human head size

* Genes harboring or near head size genetic variants enrich for macrocephaly genes

* Head size genetic variants preferentially locate to cancer genes and pathways

* Further research is needed on the potential link between head size and cancer risk

<figure><img src="image_2.png" /></figure>
# Genetic variants for head size share genes and pathways with cancer

## Graphical abstract

<figure><img src="image_3.png" /></figure>

## Authors

Maria J. Knol, Raymond A. Poot, Tavia E. Evans, ..., Paul M. Thompson, Sudha Seshadri, Hieab H.H. Adams

## Correspondence

hieab.adams@radboudumc.nl

## In brief

Knol, Poot, et al. identify 67 loci for human head size in a genome-wide association study. Genes harboring the lead variants enrich for cancer genes and pathways, which was not seen for height variants. These findings suggest a potential link between a larger head and a higher cancer risk.

## Highlights

* Knol, Poot, et al. identify 67 genetic loci associated with human head size

* Genes harboring or near head size genetic variants enrich for macrocephaly genes

* Head size genetic variants preferentially locate to cancer genes and pathways

* Further research is needed on the potential link between head size and cancer risk

<figure><img src="image_4.png" /></figure>
<figure><img src="image_3.png" /></figure>

Report

Genetic variants for head size share
genes and pathways with cancer

Maria J. Knol,<sup>1,115</sup> Raymond A. Poot,<sup>2,115</sup> Tavia E. Evans,<sup>3,4</sup> Claudia L. Satizabal,<sup>5,6,7</sup> Aniket Mishra,<sup>8</sup>

Muralidharan Sargurupremraj,<sup>5</sup> Sandra van der Auwera,<sup>3,10</sup> Marie-Gabrielle Duperron,<sup>8</sup> Xueqiu Jian,<sup>11</sup>

Isabel C. Hostettler,<sup>12,13,14</sup> Dianne H.K. van Dam-Nolen,<sup>4</sup> Sander Lamballais,<sup>3</sup> Mikolaj A. Pawlak,<sup>15,16</sup>

(Author list continued on next page)

<sup>1</sup>Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands

<sup>2</sup>Department of Cell Biology, Erasmus MC University Medical Center, Rotterdam, the Netherlands

<sup>3</sup>Department of Clinical Genetics, Erasmus MC University Medical Center, Rotterdam, the Netherlands

<sup>4</sup>Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands

<sup>5</sup>Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX, USA

<sup>6</sup>The Framingham Heart Study, Framingham, MA, USA

<sup>7</sup>Department of Neurology, Boston University School of Medicine, Boston, MA, USA

<sup>8</sup>University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, Bordeaux, France

<sup>9</sup>Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany

<sup>10</sup>German Centre of Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany

<sup>11</sup>Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA

<sup>12</sup>Stroke Research Centre, University College London, Institute of Neurology, London, UK

<sup>13</sup>Department of Neurosurgery, Klinikum rechts der Isar, University of Munich, Munich, Germany

<sup>14</sup>Neurosurgical Department, Cantonal Hospital St. Gallen, St. Gallen, Switzerland

<sup>15</sup>Department of Neurology, Poznań University of Medical Sciences, Poznań, Poland

<sup>16</sup>Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands

<sup>17</sup>Department of Epidemiology, School of Public Health, University of Alabama at Birmingham School of Medicine, Birmingham, AL, USA

<sup>18</sup>Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands

<sup>19</sup>Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, USA

<sup>20</sup>Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, USA

<sup>21</sup>Department of Biomedicine, University of Basel, Basel, Switzerland

<sup>22</sup>Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland

<sup>23</sup>Institute of Computational Life Sciences, Zurich University of Applied Sciences, Wädenswil, Switzerland

(Affiliations continued on next page)

SUMMARY

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.

INTRODUCTION

The size of the human head, measured by head circumference or
intracranial volume, correlates closely with brain size. Head size is

determined by growth in the first years of life and is largely
completed by 6 years of age, whereas the rest of the body typically
grows until early adulthood.¹ Head size is highly genetically deter-
mined, ranging from near 90% during childhood to 75% during

<figure><img src="image_4.png" /></figure>
<figure><img src="image_5.png" /></figure>

Report

Genetic variants for head size share
genes and pathways with cancer

Maria J. Knol,<sup>1,115</sup> Raymond A. Poot,<sup>2,115</sup> Tavia E. Evans,<sup>3,4</sup> Claudia L. Satizabal,<sup>5,6,7</sup> Aniket Mishra,<sup>8</sup>

Muralidharan Sargurupremraj,<sup>5</sup> Sandra van der Auwera,<sup>3,10</sup> Marie-Gabrielle Duperron,<sup>8</sup> Xueqiu Jian,<sup>11</sup>

Isabel C. Hostettler,<sup>12,13,14</sup> Dianne H.K. van Dam-Nolen,<sup>4</sup> Sander Lamballais,<sup>3</sup> Mikolaj A. Pawlak,<sup>15,16</sup>

(Author list continued on next page)

<sup>1</sup>Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands

<sup>2</sup>Department of Cell Biology, Erasmus MC University Medical Center, Rotterdam, the Netherlands

<sup>3</sup>Department of Clinical Genetics, Erasmus MC University Medical Center, Rotterdam, the Netherlands

<sup>4</sup>Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands

<sup>5</sup>Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX, USA

<sup>6</sup>The Framingham Heart Study, Framingham, MA, USA

<sup>7</sup>Department of Neurology, Boston University School of Medicine, Boston, MA, USA

<sup>8</sup>University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, Bordeaux, France

<sup>9</sup>Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany

<sup>10</sup>German Centre of Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany

<sup>11</sup>Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA

<sup>12</sup>Stroke Research Centre, University College London, Institute of Neurology, London, UK

<sup>13</sup>Department of Neurosurgery, Klinikum rechts der Isar, University of Munich, Munich, Germany

<sup>14</sup>Neurosurgical Department, Cantonal Hospital St. Gallen, St. Gallen, Switzerland

<sup>15</sup>Department of Neurology, Poznań University of Medical Sciences, Poznań, Poland

<sup>16</sup>Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands

<sup>17</sup>Department of Epidemiology, School of Public Health, University of Alabama at Birmingham School of Medicine, Birmingham, AL, USA

<sup>18</sup>Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands

<sup>19</sup>Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, USA

<sup>20</sup>Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, USA

<sup>21</sup>Department of Biomedicine, University of Basel, Basel, Switzerland

<sup>22</sup>Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland

<sup>23</sup>Institute of Computational Life Sciences, Zurich University of Applied Sciences, Wädenswil, Switzerland

(Affiliations continued on next page)

SUMMARY

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.

INTRODUCTION

The size of the human head, measured by head circumference or
intracranial volume, correlates closely with brain size. Head size is

determined by growth in the first years of life and is largely
completed by 6 years of age, whereas the rest of the body typically
grows until early adulthood.¹ Head size is highly genetically deter-
mined, ranging from near 90% during childhood to 75% during

<figure><img src="image_6.png" /></figure>
Cora E. Lewis,¹⁷ Amaia Carrion-Castillo,¹⁸ Theo G.M. van Erp,¹⁹,²⁰ Céline S. Reinbold,²¹,²²,²³ Jean Shin,<fnref n="24" />,<fnref n="25" />

Markus Scholz,<fnref n="26" />,<fnref n="27" /> Asta K. Håberg,<fnref n="28" />,<fnref n="29" /> Anders Kämpe,<fnref n="30" />,<fnref n="31" /> Gloria H.Y. Li,<fnref n="32" /> Reut Avinun,<fnref n="33" /> Joshua R. Atkins,<fnref n="34" />,<fnref n="35" />

Fang-Chi Hsu,<fnref n="36" /> Alyssa R. Amod,<fnref n="37" /> Max Lam,<fnref n="38" />,<fnref n="39" /> Ami Tsuchida,⁸,<fnref n="40" /> Mariël W.A. Teunissen,¹⁶,<fnref n="41" /> Nil Aygün,<fnref n="42" /> Yash Patel,<fnref n="43" />

Dan Liang,<fnref n="42" /> Alexa S. Beiser,⁶,⁷,<fnref n="44" /> Frauke Beyer,<fnref n="45" />,<fnref n="46" />,<fnref n="47" /> Joshua C. Bis,<fnref n="48" /> Daniel Bos,¹,⁴ R. Nick Bryan,<fnref n="49" /> Robin Bülow,<fnref n="50" />

Svenja Caspers,<fnref n="51" />,<fnref n="52" /> Gwenaëlle Catheline,<fnref n="53" />,<fnref n="54" /> Charlotte A.M. Cecil,¹,<fnref n="55" /> Shareefa Dalvie,<fnref n="37" /> Jean-François Dartigues,<fnref n="56" />

Charles DeCarli,<fnref n="57" /> Maria Enlund-Cerullo,<fnref n="58" />,<fnref n="59" /> Judith M. Ford,<fnref n="60" />,<fnref n="61" /> Barbara Franke,¹⁶,<fnref n="62" />,<fnref n="63" /> Barry I. Freedman,<fnref n="64" />

Nele Friedrich,<fnref n="65" /> Melissa J. Green,<fnref n="66" />,<fnref n="67" /> Simon Haworth,<fnref n="68" /> Catherine Helmer,<fnref n="69" /> Per Hoffmann,²¹,²²,²⁰ Georg Homuth,<fnref n="71" />

M. Kamran Ikram,¹,⁷² Clifford R. Jack, Jr.,⁷³ Neda Jahanshad,⁷⁴ Christiane Jockwitz,<fnref n="51" />,⁷⁵ Yoichiro Kamatani,⁷⁶

Annchen R. Knodt,<fnref n="33" /> Shuo Li,<fnref n="44" /> Keane Lim,⁷⁷ W.T. Longstreth,⁷⁸,⁷⁹ Fabio Macciardi,⁸⁰ The Cohorts for Heart and Aging

(Author list continued on next page)

(Affiliations continued on next page)

<footnote n="24">²⁴The Hospital for Sick Children, University of Toronto, Toronto, Canada</footnote>

<footnote n="25">²⁵Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Canada</footnote>

<footnote n="26">²⁶Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany</footnote>

<footnote n="27">²⁷LIFE Research Center for Civilization Disease, Leipzig, Germany</footnote>

<footnote n="28">²⁸Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway</footnote>

<footnote n="29">²⁹Department of Radiology and Nuclear Medicine, St. Olavs University Hospital, Trondheim, Norway</footnote>

<footnote n="30">³⁰Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden</footnote>

<footnote n="31">³¹Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden</footnote>

<footnote n="32">³²Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China</footnote>

<footnote n="33">³³Laboratory of NeuroGenetics, Department of Psychology & Neuroscience, Duke University, Durham, NC, USA</footnote>

<footnote n="34">³⁴School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia</footnote>

<footnote n="35">³⁵Centre for Brain and Mental Health Research, Hunter Medical Research Institute, Newcastle, NSW, Australia</footnote>

<footnote n="36">³⁶Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC, USA</footnote>

<footnote n="37">³⁷Department of Child and Adolescent Psychiatry, TU Dresden, Dresden, Germany</footnote>

<footnote n="38">³⁸North Region, Institute of Mental Health, Singapore, Singapore</footnote>

<footnote n="39">³⁹Population and Global Health, LKC Medicine, Nanyang Technological University, Singapore, Singapore</footnote>

<footnote n="40">⁴⁰Groupe d'imagerie neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, CNRS, CEA, Université de Bordeaux, Bordeaux, France</footnote>

<footnote n="41">⁴¹Department of Neurology, Maastricht University Medical Center+, Maastricht, the Netherlands</footnote>

<footnote n="42">⁴²Department of Genetics UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA</footnote>

<footnote n="43">⁴³Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada</footnote>

<footnote n="44">⁴⁴Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA</footnote>

<footnote n="45">⁴⁵Department of Neurology, Max Planck Institute for Cognitive and Brain Sciences, Leipzig, Germany</footnote>

<footnote n="46">⁴⁶Collaborative Research Center 1052 Obesity Mechanisms, Faculty of Medicine, University of Leipzig, Leipzig, Germany</footnote>

<footnote n="47">⁴⁷Day Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany</footnote>

<footnote n="48">⁴⁸Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA</footnote>

<footnote n="49">⁴⁹Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA</footnote>

<footnote n="50">⁵⁰Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany</footnote>

<footnote n="51">⁵¹Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany</footnote>

<footnote n="52">⁵²Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany</footnote>

<footnote n="53">⁵³University of Bordeaux, CNRS, INCIA, UMR 5287, team Neurolmagerie et Cognition Humaine, Bordeaux, France</footnote>

<footnote n="54">⁵⁴EPHE-PSL University, Bordeaux, France</footnote>

<footnote n="55">⁵⁵Department of Child and Adolescent Psychiatry, Erasmus MC University Medical Center, Rotterdam, the Netherlands</footnote>

<footnote n="56">⁵⁶University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team SEPIA, UMR 1219, Bordeaux, France</footnote>

<footnote n="57">⁵⁷Department of Neurology and Center for Neuroscience, University of California at Davis, Sacramento, CA, USA</footnote>

<footnote n="58">⁵⁸Children's Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland</footnote>

<footnote n="59">⁵⁹Folkhälsan Research Center, Helsinki, Finland</footnote>

<footnote n="60">⁶⁰San Francisco Veterans Administration Medical Center, San Francisco, CA, USA</footnote>

<footnote n="61">⁶¹University of California, San Francisco, San Francisco, CA, USA</footnote>

<footnote n="62">⁶²Department of Psychiatry, Radboud University Medical Center, Nijmegen, the Netherlands</footnote>

<footnote n="63">⁶³Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, the Netherlands</footnote>

<footnote n="64">⁶⁴Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA</footnote>

<footnote n="65">⁶⁵Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany</footnote>

<footnote n="66">⁶⁶School of Clinical Medicine, University of New South Wales, Sydney, NSW, Australia</footnote>

<footnote n="67">⁶⁷Neuroscience Research Australia, Sydney, NSW, Australia</footnote>

<footnote n="68">⁶⁸Bristol Dental School, University of Bristol, Bristol, UK</footnote>

<footnote n="69">⁶⁹University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team LEHA, UMR 1219, Bordeaux, France</footnote>

<footnote n="70">⁷⁰Institute of Human Genetics, University of Bonn Medical School, Bonn, Germany</footnote>

<footnote n="71">⁷¹Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany</footnote>
Cora E. Lewis,¹⁷ Amaia Carrion-Castillo,¹⁸ Theo G.M. van Erp,¹⁹,²⁰ Céline S. Reinbold,²¹,²²,²³ Jean Shin,<fnref n="24" />,<fnref n="25" />

Markus Scholz,<fnref n="26" />,<fnref n="27" /> Asta K. Håberg,<fnref n="28" />,<fnref n="29" /> Anders Kämpe,<fnref n="30" />,<fnref n="31" /> Gloria H.Y. Li,<fnref n="32" /> Reut Avinun,<fnref n="33" /> Joshua R. Atkins,<fnref n="34" />,<fnref n="35" />

Fang-Chi Hsu,<fnref n="36" /> Alyssa R. Amod,<fnref n="37" /> Max Lam,<fnref n="38" />,<fnref n="39" /> Ami Tsuchida,⁸,<fnref n="40" /> Mariël W.A. Teunissen,¹⁶,<fnref n="41" /> Nil Aygün,<fnref n="42" /> Yash Patel,<fnref n="43" />

Dan Liang,<fnref n="42" /> Alexa S. Beiser,⁶,⁷,<fnref n="44" /> Frauke Beyer,<fnref n="45" />,<fnref n="46" />,<fnref n="47" /> Joshua C. Bis,<fnref n="48" /> Daniel Bos,¹,⁴ R. Nick Bryan,<fnref n="49" /> Robin Bülow,<fnref n="50" />

Svenja Caspers,<fnref n="51" />,<fnref n="52" /> Gwenaëlle Catheline,<fnref n="53" />,<fnref n="54" /> Charlotte A.M. Cecil,¹,<fnref n="55" /> Shareefa Dalvie,<fnref n="37" /> Jean-François Dartigues,<fnref n="56" />

Charles DeCarli,<fnref n="57" /> Maria Enlund-Cerullo,<fnref n="58" />,<fnref n="59" /> Judith M. Ford,<fnref n="60" />,<fnref n="61" /> Barbara Franke,¹⁶,<fnref n="62" />,<fnref n="63" /> Barry I. Freedman,<fnref n="64" />

Nele Friedrich,<fnref n="65" /> Melissa J. Green,<fnref n="66" />,<fnref n="67" /> Simon Haworth,<fnref n="68" /> Catherine Helmer,<fnref n="69" /> Per Hoffmann,²¹,²²,²⁰ Georg Homuth,<fnref n="71" />

M. Kamran Ikram,¹,⁷² Clifford R. Jack, Jr.,⁷³ Neda Jahanshad,⁷⁴ Christiane Jockwitz,<fnref n="51" />,⁷⁵ Yoichiro Kamatani,⁷⁶

Annchen R. Knodt,<fnref n="33" /> Shuo Li,<fnref n="44" /> Keane Lim,⁷⁷ W.T. Longstreth,⁷⁸,⁷⁹ Fabio Macciardi,⁸⁰ The Cohorts for Heart and Aging

(Author list continued on next page)

(Affiliations continued on next page)

<footnote n="24">²⁴The Hospital for Sick Children, University of Toronto, Toronto, Canada</footnote>

<footnote n="25">²⁵Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Canada</footnote>

<footnote n="26">²⁶Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany</footnote>

<footnote n="27">²⁷LIFE Research Center for Civilization Disease, Leipzig, Germany</footnote>

<footnote n="28">²⁸Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway</footnote>

<footnote n="29">²⁹Department of Radiology and Nuclear Medicine, St. Olavs University Hospital, Trondheim, Norway</footnote>

<footnote n="30">³⁰Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden</footnote>

<footnote n="31">³¹Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden</footnote>

<footnote n="32">³²Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China</footnote>

<footnote n="33">³³Laboratory of NeuroGenetics, Department of Psychology & Neuroscience, Duke University, Durham, NC, USA</footnote>

<footnote n="34">³⁴School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia</footnote>

<footnote n="35">³⁵Centre for Brain and Mental Health Research, Hunter Medical Research Institute, Newcastle, NSW, Australia</footnote>

<footnote n="36">³⁶Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC, USA</footnote>

<footnote n="37">³⁷Department of Child and Adolescent Psychiatry, TU Dresden, Dresden, Germany</footnote>

<footnote n="38">³⁸North Region, Institute of Mental Health, Singapore, Singapore</footnote>

<footnote n="39">³⁹Population and Global Health, LKC Medicine, Nanyang Technological University, Singapore, Singapore</footnote>

<footnote n="40">⁴⁰Groupe d'imagerie neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, CNRS, CEA, Université de Bordeaux, Bordeaux, France</footnote>

<footnote n="41">⁴¹Department of Neurology, Maastricht University Medical Center+, Maastricht, the Netherlands</footnote>

<footnote n="42">⁴²Department of Genetics UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA</footnote>

<footnote n="43">⁴³Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada</footnote>

<footnote n="44">⁴⁴Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA</footnote>

<footnote n="45">⁴⁵Department of Neurology, Max Planck Institute for Cognitive and Brain Sciences, Leipzig, Germany</footnote>

<footnote n="46">⁴⁶Collaborative Research Center 1052 Obesity Mechanisms, Faculty of Medicine, University of Leipzig, Leipzig, Germany</footnote>

<footnote n="47">⁴⁷Day Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany</footnote>

<footnote n="48">⁴⁸Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA</footnote>

<footnote n="49">⁴⁹Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA</footnote>

<footnote n="50">⁵⁰Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany</footnote>

<footnote n="51">⁵¹Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany</footnote>

<footnote n="52">⁵²Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany</footnote>

<footnote n="53">⁵³University of Bordeaux, CNRS, INCIA, UMR 5287, team Neurolmagerie et Cognition Humaine, Bordeaux, France</footnote>

<footnote n="54">⁵⁴EPHE-PSL University, Bordeaux, France</footnote>

<footnote n="55">⁵⁵Department of Child and Adolescent Psychiatry, Erasmus MC University Medical Center, Rotterdam, the Netherlands</footnote>

<footnote n="56">⁵⁶University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team SEPIA, UMR 1219, Bordeaux, France</footnote>

<footnote n="57">⁵⁷Department of Neurology and Center for Neuroscience, University of California at Davis, Sacramento, CA, USA</footnote>

<footnote n="58">⁵⁸Children's Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland</footnote>

<footnote n="59">⁵⁹Folkhälsan Research Center, Helsinki, Finland</footnote>

<footnote n="60">⁶⁰San Francisco Veterans Administration Medical Center, San Francisco, CA, USA</footnote>

<footnote n="61">⁶¹University of California, San Francisco, San Francisco, CA, USA</footnote>

<footnote n="62">⁶²Department of Psychiatry, Radboud University Medical Center, Nijmegen, the Netherlands</footnote>

<footnote n="63">⁶³Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, the Netherlands</footnote>

<footnote n="64">⁶⁴Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA</footnote>

<footnote n="65">⁶⁵Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany</footnote>

<footnote n="66">⁶⁶School of Clinical Medicine, University of New South Wales, Sydney, NSW, Australia</footnote>

<footnote n="67">⁶⁷Neuroscience Research Australia, Sydney, NSW, Australia</footnote>

<footnote n="68">⁶⁸Bristol Dental School, University of Bristol, Bristol, UK</footnote>

<footnote n="69">⁶⁹University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team LEHA, UMR 1219, Bordeaux, France</footnote>

<footnote n="70">⁷⁰Institute of Human Genetics, University of Bonn Medical School, Bonn, Germany</footnote>

<footnote n="71">⁷¹Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany</footnote>
<figure><img src="image_5.png" /></figure>

Research in Genomic Epidemiology (CHARGE) Consortium, The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium, Outi Mäkitie,<sup>30,31,58,59</sup> Bernard Mazoyer,<sup>40,81</sup> Sarah E. Medland,<sup>82,83,84</sup> Susumu Miyamoto,<sup>85</sup> Susanne Moebus,<sup>86</sup> Thomas H. Mosley,<sup>87,88</sup> Ryan Muetzel,<sup>1,55</sup> Thomas W. Mühleisen,<sup>21,51,89</sup> Manabu Nagata,<sup>85</sup> Soichiro Nakahara,<sup>19,90</sup> Nicholette D. Palmer,<sup>91</sup> Zdenka Pausova,<sup>24,25</sup> Adrian Preda,<sup>92</sup> Yann Quidé,<sup>66,67</sup> William R. Reay,<sup>34,35</sup> Gennady V. Roshchupkin,<sup>1,4</sup> Reinhold Schmidt,<sup>93</sup> Pamela J. Schreiner,<sup>94</sup> Kazuya Setoh,<sup>76</sup> Chin Yang Shapland,<sup>18,95,96</sup> Stephen Sidney,<sup>97</sup> Beate St Pourcain,<sup>18,63,95</sup> Jason L. Stein,<sup>42</sup> Yasuharu Tabara,<sup>76</sup> Alexander Teumer,<sup>9,98</sup> Anne Uhlmann,<sup>37</sup> Aad van der Lugt,<sup>4</sup> Meike W. Vernooij,<sup>1,4</sup> David J. Werring,<sup>12</sup>

(Author list continued on next page)

(Affiliations continued on next page)

<footnote n="72"><sup>72</sup>Department of Neurology, Erasmus MC University Medical Center, Rotterdam, the Netherlands</footnote>

<footnote n="73"><sup>73</sup>Department of Radiology, Mayo Clinic, Rochester, MN, USA</footnote>

<footnote n="74"><sup>74</sup>Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck USC School of Medicine, Los Angeles, CA, USA</footnote>

<footnote n="75"><sup>75</sup>Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Medical Faculty, Aachen, Germany</footnote>

<footnote n="76"><sup>76</sup>Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan</footnote>

<footnote n="77"><sup>77</sup>Research Division, Institute of Mental Health, Singapore, Singapore</footnote>

<footnote n="78"><sup>78</sup>Department of Neurology, University of Washington, Seattle, WA, USA</footnote>

<footnote n="79"><sup>79</sup>Department of Epidemiology, University of Washington, Seattle, WA, USA</footnote>

<footnote n="80"><sup>80</sup>Laboratory of Molecular Psychiatry, Department of Psychiatry and Human Behavior, School of Medicine, University of California, Irvine, Irvine, CA, USA</footnote>

<footnote n="81"><sup>81</sup>Centre Hospitalo-Universitaire de Bordeaux, Bordeaux, France</footnote>

<footnote n="82"><sup>82</sup>Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia</footnote>

<footnote n="83"><sup>83</sup>School of Psychology, University of Queensland, Brisbane, QLD, Australia</footnote>

<footnote n="84"><sup>84</sup>Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia</footnote>

<footnote n="85"><sup>85</sup>Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, Japan</footnote>

<footnote n="86"><sup>86</sup>Institute for Urban Public Health, University of Duisburg-Essen, Essen, Germany</footnote>

<footnote n="87"><sup>87</sup>Department of Medicine, Division of Geriatrics, University of Mississippi Medical Center, Jackson, MS, USA</footnote>

<footnote n="88"><sup>88</sup>Memory Impairment and Neurodegenerative Dementia (MIND) Center, Jackson, MS, USA</footnote>

<footnote n="89"><sup>89</sup>C. and O. Vogt Institute for Brain Research, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany</footnote>

<footnote n="90"><sup>90</sup>Unit 2, Candidate Discovery Science Labs, Drug Discovery Research, Astellas Pharma Inc, 21 Miyukigaoka, Tsukuba, Ibaraki 305-8585, Japan</footnote>

<footnote n="91"><sup>91</sup>Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA</footnote>

<footnote n="92"><sup>92</sup>Department of Psychiatry, University of California, Irvine, Irvine, CA, USA</footnote>

<footnote n="93"><sup>93</sup>Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria</footnote>

<footnote n="94"><sup>94</sup>University of Minnesota School of Public Health, Minneapolis, MN, USA</footnote>

<footnote n="95"><sup>95</sup>MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK</footnote>

<footnote n="96"><sup>96</sup>Population Health Sciences, University of Bristol, Bristol, UK</footnote>

<footnote n="97"><sup>97</sup>Kaiser Permanente Division of Research, Oakland, CA, USA</footnote>

<footnote n="98"><sup>98</sup>Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany</footnote>

<footnote n="99"><sup>99</sup>Department of Human Genetics, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands</footnote>

<footnote n="100"><sup>100</sup>Department of Clinical Genetics MUMC+, GROW School of Oncology and Developmental Biology, and MHeNs School of Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands</footnote>

<footnote n="101"><sup>101</sup>Bordeaux Population Health, University of Bordeaux, INSERM U1219, Bordeaux, France</footnote>

<footnote n="102"><sup>102</sup>West Region, Institute of Mental Health, Singapore, Singapore</footnote>

<footnote n="103"><sup>103</sup>Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore</footnote>

<footnote n="104"><sup>104</sup>Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore</footnote>

<footnote n="105"><sup>105</sup>SAMRC Unit on Risk and Resilience, University of Cape Town, Cape Town, South Africa</footnote>

<footnote n="106"><sup>106</sup>Centre for Genomic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China</footnote>

<footnote n="107"><sup>107</sup>Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China</footnote>

<footnote n="108"><sup>108</sup>Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, QC, Canada</footnote>

<footnote n="109"><sup>109</sup>Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada</footnote>

<footnote n="110"><sup>110</sup>Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) (Georgia State, Georgia Tech, Emory), Atlanta, GA, USA</footnote>

<footnote n="111"><sup>111</sup>Laboratory of Epidemiology, Demography, and Biometry, Intramural Research Program, National Institute of Aging, The National Institutes of Health, Bethesda, MD, USA</footnote>

<footnote n="112"><sup>112</sup>Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA</footnote>

<footnote n="113"><sup>113</sup>Department of Neurology, Bordeaux University Hospital, Bordeaux, France</footnote>

<footnote n="114"><sup>114</sup>Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile</footnote>

<footnote n="115"><sup>115</sup>These authors contributed equally</footnote>
Research in Genomic Epidemiology (CHARGE) Consortium, The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium, Outi Mäkitie,<sup>30,31,58,59</sup> Bernard Mazoyer,<sup>40,81</sup> Sarah E. Medland,<sup>82,83,84</sup>

Susumu Miyamoto,<sup>85</sup> Susanne Moebus,<sup>86</sup> Thomas H. Mosley,<sup>87,88</sup> Ryan Muetzel,<sup>1,55</sup> Thomas W. Mühleisen,<sup>21,51,89</sup>

Manabu Nagata,<sup>85</sup> Soichiro Nakahara,<sup>19,90</sup> Nicholette D. Palmer,<sup>91</sup> Zdenka Pausova,<sup>24,25</sup> Adrian Preda,<sup>92</sup> Yann Quidé,<sup>66,67</sup>

William R. Reay,<sup>34,35</sup> Gennady V. Roshchupkin,<sup>1,4</sup> Reinhold Schmidt,<sup>93</sup> Pamela J. Schreiner,<sup>94</sup> Kazuya Setoh,<sup>76</sup>

Chin Yang Shapland,<sup>18,95,96</sup> Stephen Sidney,<sup>97</sup> Beate St Pourcain,<sup>18,63,95</sup> Jason L. Stein,<sup>42</sup> Yasuharu Tabara,<sup>76</sup>

Alexander Teumer,<sup>9,98</sup> Anne Uhlmann,<sup>37</sup> Aad van der Lugt,<sup>4</sup> Meike W. Vernooij,<sup>1,4</sup> David J. Werring,<sup>12</sup>

(Author list continued on next page)

<sup>72</sup>Department of Neurology, Erasmus MC University Medical Center, Rotterdam, the Netherlands

<sup>73</sup>Department of Radiology, Mayo Clinic, Rochester, MN, USA

<sup>74</sup>Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck USC School of Medicine, Los Angeles, CA, USA

<sup>75</sup>Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Medical Faculty, Aachen, Germany

<sup>76</sup>Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan

<sup>77</sup>Research Division, Institute of Mental Health, Singapore, Singapore

<sup>78</sup>Department of Neurology, University of Washington, Seattle, WA, USA

<sup>79</sup>Department of Epidemiology, University of Washington, Seattle, WA, USA

<sup>80</sup>Laboratory of Molecular Psychiatry, Department of Psychiatry and Human Behavior, School of Medicine, University of California, Irvine, Irvine, CA, USA

<sup>81</sup>Centre Hospitalo-Universitaire de Bordeaux, Bordeaux, France

<sup>82</sup>Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia

<sup>83</sup>School of Psychology, University of Queensland, Brisbane, QLD, Australia

<sup>84</sup>Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia

<sup>85</sup>Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, Japan

<sup>86</sup>Institute for Urban Public Health, University of Duisburg-Essen, Essen, Germany

<sup>87</sup>Department of Medicine, Division of Geriatrics, University of Mississippi Medical Center, Jackson, MS, USA

<sup>88</sup>Memory Impairment and Neurodegenerative Dementia (MIND) Center, Jackson, MS, USA

<sup>89</sup>C. and O. Vogt Institute for Brain Research, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany

<sup>90</sup>Unit 2, Candidate Discovery Science Labs, Drug Discovery Research, Astellas Pharma Inc, 21 Miyukigaoka, Tsukuba, Ibaraki 305-8585, Japan

<sup>91</sup>Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA

<sup>92</sup>Department of Psychiatry, University of California, Irvine, Irvine, CA, USA

<sup>93</sup>Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria

<sup>94</sup>University of Minnesota School of Public Health, Minneapolis, MN, USA

<sup>95</sup>MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK

<sup>96</sup>Population Health Sciences, University of Bristol, Bristol, UK

<sup>97</sup>Kaiser Permanente Division of Research, Oakland, CA, USA

<sup>98</sup>Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany

<sup>99</sup>Department of Human Genetics, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands

<sup>100</sup>Department of Clinical Genetics MUMC+, GROW School of Oncology and Developmental Biology, and MHeNs School of Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands

<sup>101</sup>Bordeaux Population Health, University of Bordeaux, INSERM U1219, Bordeaux, France

<sup>102</sup>West Region, Institute of Mental Health, Singapore, Singapore

<sup>103</sup>Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

<sup>104</sup>Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore

<sup>105</sup>SAMRC Unit on Risk and Resilience, University of Cape Town, Cape Town, South Africa

<sup>106</sup>Centre for Genomic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China

<sup>107</sup>Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China

<sup>108</sup>Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, QC, Canada

<sup>109</sup>Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada

<sup>110</sup>Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) (Georgia State, Georgia Tech, Emory), Atlanta, GA, USA

<sup>111</sup>Laboratory of Epidemiology, Demography, and Biometry, Intramural Research Program, National Institute of Aging, The National Institutes of Health, Bethesda, MD, USA

<sup>112</sup>Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA

<sup>113</sup>Department of Neurology, Bordeaux University Hospital, Bordeaux, France

<sup>114</sup>Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile

<sup>115</sup>These authors contributed equally

(Affiliations continued on next page)
B. Gwen Windham,<sup>87,88</sup> A. Veronica Witte,<sup>45,46,47</sup> Katharina Wittfeld,<sup>9,10</sup> Qiong Yang,<sup>44</sup> Kazumichi Yoshida,<sup>85</sup>

Han G. Brunner,<sup>99,100</sup> Quentin Le Grand,<sup>101</sup> Kang Sim,<sup>102,103,104</sup> Dan J. Stein,<sup>37,105</sup> Donald W. Bowden,<sup>91</sup>

Murray J. Cairns,<sup>34,35</sup> Ahmad R. Hariri,<sup>33</sup> Ching-Lung Cheung,<sup>32,106,107</sup> Sture Andersson,<sup>58</sup> Arno Villringer,<sup>45,47</sup>

Tomas Paus,<sup>108,109</sup> Sven Cichon,<sup>21,22,51</sup> Vince D. Calhoun,<sup>110</sup> Fabrice Crivello,<sup>40</sup> Lenore J. Launer,<sup>111</sup> Tonya White,<sup>4,55</sup>

Peter J. Koudstaal,<sup>72</sup> Henry Houlden,<sup>12</sup> Myriam Fornage,<sup>11,112</sup> Fumihiko Matsuda,<sup>76</sup> Hans J. Grabe,<sup>9</sup> M. Arfan Ikram,<sup>1</sup>

Stéphanie Debette,<sup>101,113</sup> Paul M. Thompson,<sup>74,116</sup> Sudha Seshadri,<sup>5,6,7,116</sup> and Hieab H.H. Adams<sup>16,114,116,117,*</sup>

adulthood.² Rare genetic syndromes have revealed individual genes strongly affecting head size.³ Nevertheless, genetic determinants of its variation within the general population are still poorly characterized, with no coherent and well-supported picture of associated biological pathways.

A previous genome-wide association study (GWAS) on 47,000 individuals identified 18 genetic loci for intracranial volume,⁴ while another GWAS on head size in 46,000 children and adults identified 17 loci for head size including low-frequency variants in *TP53*.⁵ Here, we increased the sample size to a total GWAS discovery sample size of 80,890 individuals, and validated the results in an independent sample of 25,088 individuals. Our GWAS analyses show strong enrichment for genes and multiple pathways involved in cancer, macrocephaly genes, and show preferential expression of genes near variants in intermediate progenitor cells.

## RESULTS

We performed a meta-analysis of GWASs for head size, as proxied by intracranial volume from brain imaging, or head circumference (Tables S1–S3 and S4; STAR Methods). Compared with previous efforts,<sup>5,6</sup> we nearly doubled the sample size (N = 80,890), in majority from European ancestry (N = 75,309). We identified 90 independent genetic variants in 67 loci associated with human head size in the European sample (Figure 1A; Tables S6–S8; Data S1, S2, and S3), of which 50 loci were novel. Although the results showed some bias (linkage disequilibrium [LD] score regression intercept 1.056; Table S5), the identified variants remained genome-wide significant after correction for this amount of bias. Most variants (N = 48) showed consistent directions of association among the European, African (N = 1,356), and Asian (N = 4,225) ancestry samples (Figure 1B; Table S6), suggesting population-specific genetic effects on head size in these loci. Since we had limited non-European samples, we also tested the combined effect of the lead variants, which showed positive associations in African and East Asian ancestry samples (β<sub>African</sub> = 0.34, confidence interval [CI] 0.08–0.60; β<sub>East Asian</sub> = 0.40, CI 0.24–0.57). In the European validation sample (N = 25,088), 20 of the 89 lead variants were associated with head size at a Bonferroni significance level (p < 5.6 × 10<sup>-4</sup>) and 54 at a nominal significance level, while all lead variants showed the same direction of effect. In the UK Biobank validation sample (N = 23,046), the 89 available lead variants together explained 2.3% of the phenotypic head size variance. A meta-analysis combining the European discovery and validation sample (N = 101,241) identified 102 genomic loci with 126 lead vari-

ants (Table S8), of which 60 loci overlapped with the 67 genomic loci identified by the discovery meta-analysis.

## Head-specific growth vs. general growth

We investigated whether variants affecting head size are specific for growth of the human head or are driven, at least in part, by an effect on human body height. Accordingly, we performed a height-adjusted head size GWAS (N = 50,424). The genetic correlation between head size and height (ρ<sub>genetic</sub> = 0.26, *p* = 2.1 × 10<sup>-30</sup>) disappeared in this model (ρ<sub>genetic</sub> = -0.02, *p* = 0.58) (Figure 1C), confirming the removal of height-associated effects. Importantly, there was no significant reduction for any of the lead variants' effect sizes with head size (Table S6). We further explored the effect of these variants on the size of other body parts using area measures obtained from bone density scans (N = 3,313). As expected, a polygenic score of the lead variants was associated with the skull area, even after adjusting for height (*p* = 2.1 × 10<sup>-12</sup>). One lead genetic variant (rs12277225) was significantly associated with the L1-L4 spine area (*p* = 1.3 × 10<sup>-5</sup>), but the other lead variants did not affect bone area measures of arm, leg, and spine (Table S9). Altogether, this indicates that the effect of the identified variants on head size is predominantly head-specific.

## Regional brain volumetric effects

Head size may reflect growth of specific brain regions. Indeed, 15 lead genetic variants or variants in LD (r² > 0.6) from 12 genetic loci were previously reported to affect volumes of subregions of the brain (Figure 2A; Table S10). We screened all loci previously associated with these regional brain volumes, and found 16 of those 132 loci significantly related with head size after multiple testing correction (Table S11). To determine if the current findings can be localized to specific brain regions, we investigated the 90 independent head size variants in relation to more fine-grained measures of brain morphometry—corrected for head size—in 22,145 individuals (Figure 2B; Table S12). Thirty-nine variants were associated with one or multiple cortical, subcortical, and global brain regions of which 17 variants were preferentially associated with one or two specific cortical or subcortical regions. For example, rs111939932, an intronic variant in *PCBP2*, is associated with nucleus accumbens volume and is an expression quantitative trait locus (eQTL) for several genes, including *ATP5G2* in the nucleus accumbens and basal ganglia. Further analysis revealed its localized effects on this structure's shape (Figure 2C; Table S13). In the largest GWAS on nucleus accumbens volume,⁷ this variant was nominally significant (*p* = 0.02), showing the improved power of our

<footnote n="116"><sup>116</sup>These authors contributed equally</footnote>

<footnote n="117"><sup>117</sup>Lead contact</footnote>

<footnote>*Correspondence: hieab.adams@radboudumc.nl</footnote>

<footnote>https://doi.org/10.1016/j.xcrm.2024.101529</footnote>
B. Gwen Windham,<sup>87,88</sup> A. Veronica Witte,<sup>45,46,47</sup> Katharina Wittfeld,<sup>9,10</sup> Qiong Yang,<sup>44</sup> Kazumichi Yoshida,<sup>85</sup>

Han G. Brunner,<sup>99,100</sup> Quentin Le Grand,<sup>101</sup> Kang Sim,<sup>102,103,104</sup> Dan J. Stein,<sup>37,105</sup> Donald W. Bowden,<sup>91</sup>

Murray J. Cairns,<sup>34,35</sup> Ahmad R. Hariri,<sup>33</sup> Ching-Lung Cheung,<sup>32,106,107</sup> Sture Andersson,<sup>58</sup> Arno Villringer,<sup>45,47</sup>

Tomas Paus,<sup>108,109</sup> Sven Cichon,<sup>21,22,51</sup> Vince D. Calhoun,<sup>110</sup> Fabrice Crivello,<sup>40</sup> Lenore J. Launer,<sup>111</sup> Tonya White,<sup>4,55</sup>

Peter J. Koudstaal,<sup>72</sup> Henry Houlden,<sup>12</sup> Myriam Fornage,<sup>11,112</sup> Fumihiko Matsuda,<sup>76</sup> Hans J. Grabe,<sup>9</sup> M. Arfan Ikram,<sup>1</sup>

Stéphanie Debette,<sup>101,113</sup> Paul M. Thompson,<sup>74,116</sup> Sudha Seshadri,<sup>5,6,7,116</sup> and Hieab H.H. Adams<sup>16,114,116,117,*</sup>

adulthood.² Rare genetic syndromes have revealed individual genes strongly affecting head size.³ Nevertheless, genetic determinants of its variation within the general population are still poorly characterized, with no coherent and well-supported picture of associated biological pathways.

A previous genome-wide association study (GWAS) on 47,000 individuals identified 18 genetic loci for intracranial volume,⁴ while another GWAS on head size in 46,000 children and adults identified 17 loci for head size including low-frequency variants in *TP53*.⁵ Here, we increased the sample size to a total GWAS discovery sample size of 80,890 individuals, and validated the results in an independent sample of 25,088 individuals. Our GWAS analyses show strong enrichment for genes and multiple pathways involved in cancer, macrocephaly genes, and show preferential expression of genes near variants in intermediate progenitor cells.

## RESULTS

We performed a meta-analysis of GWASs for head size, as proxied by intracranial volume from brain imaging, or head circumference (Tables S1–S3 and S4; STAR Methods). Compared with previous efforts,<sup>5,6</sup> we nearly doubled the sample size (N = 80,890), in majority from European ancestry (N = 75,309). We identified 90 independent genetic variants in 67 loci associated with human head size in the European sample (Figure 1A; Tables S6–S8; Data S1, S2, and S3), of which 50 loci were novel. Although the results showed some bias (linkage disequilibrium [LD] score regression intercept 1.056; Table S5), the identified variants remained genome-wide significant after correction for this amount of bias. Most variants (N = 48) showed consistent directions of association among the European, African (N = 1,356), and Asian (N = 4,225) ancestry samples (Figure 1B; Table S6), suggesting population-specific genetic effects on head size in these loci. Since we had limited non-European samples, we also tested the combined effect of the lead variants, which showed positive associations in African and East Asian ancestry samples (β<sub>African</sub> = 0.34, confidence interval [CI] 0.08–0.60; β<sub>East Asian</sub> = 0.40, CI 0.24–0.57). In the European validation sample (N = 25,088), 20 of the 89 lead variants were associated with head size at a Bonferroni significance level (p < 5.6 × 10<sup>-4</sup>) and 54 at a nominal significance level, while all lead variants showed the same direction of effect. In the UK Biobank validation sample (N = 23,046), the 89 available lead variants together explained 2.3% of the phenotypic head size variance. A meta-analysis combining the European discovery and validation sample (N = 101,241) identified 102 genomic loci with 126 lead vari-

ants (Table S8), of which 60 loci overlapped with the 67 genomic loci identified by the discovery meta-analysis.

## Head-specific growth vs. general growth

We investigated whether variants affecting head size are specific for growth of the human head or are driven, at least in part, by an effect on human body height. Accordingly, we performed a height-adjusted head size GWAS (N = 50,424). The genetic correlation between head size and height (ρ<sub>genetic</sub> = 0.26, *p* = 2.1 × 10<sup>-30</sup>) disappeared in this model (ρ<sub>genetic</sub> = -0.02, *p* = 0.58) (Figure 1C), confirming the removal of height-associated effects. Importantly, there was no significant reduction for any of the lead variants' effect sizes with head size (Table S6). We further explored the effect of these variants on the size of other body parts using area measures obtained from bone density scans (N = 3,313). As expected, a polygenic score of the lead variants was associated with the skull area, even after adjusting for height (*p* = 2.1 × 10<sup>-12</sup>). One lead genetic variant (rs12277225) was significantly associated with the L1-L4 spine area (*p* = 1.3 × 10<sup>-5</sup>), but the other lead variants did not affect bone area measures of arm, leg, and spine (Table S9). Altogether, this indicates that the effect of the identified variants on head size is predominantly head-specific.

## Regional brain volumetric effects

Head size may reflect growth of specific brain regions. Indeed, 15 lead genetic variants or variants in LD (r² > 0.6) from 12 genetic loci were previously reported to affect volumes of subregions of the brain (Figure 2A; Table S10). We screened all loci previously associated with these regional brain volumes, and found 16 of those 132 loci significantly related with head size after multiple testing correction (Table S11). To determine if the current findings can be localized to specific brain regions, we investigated the 90 independent head size variants in relation to more fine-grained measures of brain morphometry—corrected for head size—in 22,145 individuals (Figure 2B; Table S12). Thirty-nine variants were associated with one or multiple cortical, subcortical, and global brain regions of which 17 variants were preferentially associated with one or two specific cortical or subcortical regions. For example, rs111939932, an intronic variant in *PCBP2*, is associated with nucleus accumbens volume and is an expression quantitative trait locus (eQTL) for several genes, including *ATP5G2* in the nucleus accumbens and basal ganglia. Further analysis revealed its localized effects on this structure's shape (Figure 2C; Table S13). In the largest GWAS on nucleus accumbens volume,⁷ this variant was nominally significant (*p* = 0.02), showing the improved power of our

<footnote n="116"><sup>116</sup>These authors contributed equally</footnote>

<footnote n="117"><sup>117</sup>Lead contact</footnote>

<footnote>*Correspondence: hieab.adams@radboudumc.nl</footnote>

<footnote>https://doi.org/10.1016/j.xcrm.2024.101529</footnote>
<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /><figcaption>**Figure 1. Genome-wide association studies on human head size**</figcaption></figure>

(A) Circos Manhattan plot of the European ancestry head size GWAS, with gray lines corresponding to genome-wide significant ($p < 5 \times 10^{-8}$) or sub-significant ($p < 1 \times 10^{-6}$) $p$ value thresholds. Known variants are in blue, novel ones in red. For each lead variant, the nearest gene is presented, with the color corresponding to its position to the lead variant: exonic (red), 3'-UTR (green), intronic (blue), intergenic including up- and downstream, exonic and intronic non-coding RNA (gray). Nearest genes for more than one locus are denoted with an asterisk (*).

(B) Circos heatmap showing the betas of lead variants in African, Asian, and European ancestry meta-analyses, as well as the transancestral meta-analysis. Differences between the height-unadjusted (model 1) and -adjusted (model 2) meta-analysis are also shown.

(C) Bar plot of the genetic correlation coefficient ($ρ_{genetic}$) of the height-unadjusted and -adjusted head size GWAS with the height GWAS, with their accompanying 95% confidence intervals.

current study to identify novel brain morphometry loci. For the other 51 variants there was no apparent association with particular brain regions. Overall, these results suggest that most head size variants affect generalized brain or cranial growth, while a minority influence regional brain growth.

## Genetic correlation with neuropsychiatric traits

Genetic correlation analyses with neuropsychiatric traits have been conducted previously.⁵,⁶ We replicated positive genetic correlations with cognitive functioning and Parkinson's disease, also when only including new samples (Figure S1; Table S14). The replicated correlation with Parkinson's disease provides independent evidence for the proposed brain overgrowth hypothesis in this disorder.⁸ Novel genetic correlations were found with multiple psychiatric traits; negative correlations with attention-deficit hyperactivity disorder ($ρ_{genetic} = -0.18, p = 4.5 \times 10^{-7}$), insomnia ($ρ_{genetic} = -0.19, p = 1.8 \times 10^{-5}$), major depressive disorder ($ρ_{genetic} = -0.11, p = 2.6 \times 10^{-4}$), and neuroticism ($ρ_{genetic} = -0.11, p = 5.4 \times 10^{-4}$) (Figure S1; Table S14). Since psychiatric disorders themselves are genetically correlated, incorporating head size and other brain anatomy traits could aid in disentangling underlying genetic factors.

## Pathway analysis

To obtain novel insights into the biological mechanisms underlying head size variation, we performed a gene set enrichment analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG)⁹ gene sets and found 14 to be significantly enriched (Figure 3A; Table S15). Nine of those gene sets represent different cancer types that substantially overlap between each other and share underlying biological pathways (Figure 3B). The remaining gene sets represent the p53, Wnt, and ErbB signaling pathways, all involved in tumorigenesis including in the abovementioned cancer types.¹⁰ Remarkably, lead variants in our GWAS were predominantly intragenic for the seven genes in the p53 pathway, eight genes in the Wnt pathway, and six genes in the ErbB-EGFR pathway (Figure 3C), suggesting that modulation of these pathways plays an important role in head size variation.

The p53 signaling pathway showed the strongest enrichment ($ρ_{adjusted} = 7.6 \times 10^{-4}$) (Figure 3A; Table S15). Tumor suppressor protein p53, encoded by TP53, is activated by different stress signals to regulate the cell cycle and apoptosis. Our lead signal in this locus was TP53 3'-UTR variant rs78378222 with predicted deleterious effects (CADD = 15.93), which was identified previously.⁵ Three other genes in this pathway (ATR, CDK6, and
<figure><img src="image_7.png" /></figure>

A

<figure><img src="image_8.png" /></figure>

B

<figure><img src="image_9.png" /></figure>

C

<figure><img src="image_10.png" /><figcaption>**Figure 1. Genome-wide association studies on human head size**</figcaption></figure>

(A) Circos Manhattan plot of the European ancestry head size GWAS, with gray lines corresponding to genome-wide significant ($p < 5 \times 10^{-8}$) or sub-significant ($p < 1 \times 10^{-6}$) $p$ value thresholds. Known variants are in blue, novel ones in red. For each lead variant, the nearest gene is presented, with the color corresponding to its position to the lead variant: exonic (red), 3'-UTR (green), intronic (blue), intergenic including up- and downstream, exonic and intronic non-coding RNA (gray). Nearest genes for more than one locus are denoted with an asterisk (*).

(B) Circos heatmap showing the betas of lead variants in African, Asian, and European ancestry meta-analyses, as well as the transancestral meta-analysis. Differences between the height-unadjusted (model 1) and -adjusted (model 2) meta-analysis are also shown.

(C) Bar plot of the genetic correlation coefficient ($ρ_{genetic}$) of the height-unadjusted and -adjusted head size GWAS with the height GWAS, with their accompanying 95% confidence intervals.

current study to identify novel brain morphometry loci. For the other 51 variants there was no apparent association with particular brain regions. Overall, these results suggest that most head size variants affect generalized brain or cranial growth, while a minority influence regional brain growth.

## Genetic correlation with neuropsychiatric traits

Genetic correlation analyses with neuropsychiatric traits have been conducted previously.⁵,⁶ We replicated positive genetic correlations with cognitive functioning and Parkinson's disease, also when only including new samples (Figure S1; Table S14). The replicated correlation with Parkinson's disease provides independent evidence for the proposed brain overgrowth hypothesis in this disorder.⁸ Novel genetic correlations were found with multiple psychiatric traits; negative correlations with attention-deficit hyperactivity disorder ($ρ_{genetic} = -0.18, p = 4.5 \times 10^{-7}$), insomnia ($ρ_{genetic} = -0.19, p = 1.8 \times 10^{-5}$), major depressive disorder ($ρ_{genetic} = -0.11, p = 2.6 \times 10^{-4}$), and neuroticism ($ρ_{genetic} = -0.11, p = 5.4 \times 10^{-4}$) (Figure S1; Table S14). Since psychiatric disorders themselves are genetically correlated, incorporating head size and other brain anatomy traits could aid in disentangling underlying genetic factors.

## Pathway analysis

To obtain novel insights into the biological mechanisms underlying head size variation, we performed a gene set enrichment analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG)⁹ gene sets and found 14 to be significantly enriched (Figure 3A; Table S15). Nine of those gene sets represent different cancer types that substantially overlap between each other and share underlying biological pathways (Figure 3B). The remaining gene sets represent the p53, Wnt, and ErbB signaling pathways, all involved in tumorigenesis including in the abovementioned cancer types.¹⁰ Remarkably, lead variants in our GWAS were predominantly intragenic for the seven genes in the p53 pathway, eight genes in the Wnt pathway, and six genes in the ErbB-EGFR pathway (Figure 3C), suggesting that modulation of these pathways plays an important role in head size variation.

The p53 signaling pathway showed the strongest enrichment ($ρ_{adjusted} = 7.6 \times 10^{-4}$) (Figure 3A; Table S15). Tumor suppressor protein p53, encoded by TP53, is activated by different stress signals to regulate the cell cycle and apoptosis. Our lead signal in this locus was TP53 3'-UTR variant rs78378222 with predicted deleterious effects (CADD = 15.93), which was identified previously.⁵ Three other genes in this pathway (ATR, CDK6, and
<figure><img src="image_8.png" /><figcaption>**Figure 2.** Genetic loci for head size and effects on regional brain volumes</figcaption></figure>

(A) Heatmap showing head size loci that overlap with previously identified loci for global brain volumes (red), subcortical volumes (blue), and cortical region of interest volumes (green).

(B) UpSet plot of associations between head size lead variants and brain volumes. Intersection size corresponds to the frequency of the combination depicted below the bar. Set size corresponds to the frequency of associations with one of the brain volume categories (i.e., global, subcortical, or cortical).

(C) Plot showing the subcortical shape analysis of rs111939932 using log Jacobian determinants. Colors correspond to t values, with positive associations depicted in blue, and negative ones in red. Letters point to different subcortical structures: a, putamen; b, pallidum; c, caudate; d, amygdala; e, hippocampus; f, thalamus; g, accumbens.

PTEN) also contained 3'-UTR or exonic variants in LD ($r^2$ > 0.6) with lead variants. Identified genes act in cell-cycle arrest and cellular senescence (CDK6, CDK2, and CCND2), apoptosis (IGF1), or inhibition of the insulin growth factor (IGF)-1/mammalian target of rapamycin (mTOR) pathway (PTEN), suggesting comprehensive involvement of the p53 signaling pathway in head growth. This finding is in line with evidence that p53 signaling regulates both normal and malignant neural stem cell populations.<sup>11-13</sup>

The Wnt signaling pathway has links to carcinogenesis and the developing and adult central nervous system,<sup>14,15</sup> as well as to bone development including cranial growth.<sup>16</sup> Of the eight overlapping genes, three contained exonic or 3'-UTR variants in LD ($r^2$ > 0.6) with identified lead variants (APC, TP53, and TCF7L1). Wnt signaling pathway gene FRZB, not annotated in KEGG, also contained exonic and 3'-UTR variants. In total, 1,948 genetic variants in LD with the identified lead variants ($r^2$ > 0.6), including 35 exonic variants, are eQTLs for WNT3 in 27 different tissues including the cerebellar hemispheres. In addition, various exonic, 3'-UTR and 5'-UTR variants in LD with the lead variants are eQTLs for TCF7L1 in brain tissues. These observations suggest that variants in this pathway affect brain and cranial growth in the human population.

The ErbB pathway ($p_{adjusted} = 0.014$, Figure 3A), also known as the EGFR signaling pathway, has six overlapping genes near head

size variants, which are involved in calcium signaling (PLCG1), MAPK signaling (NCK1 and MAPK1), and PI3K-AKT signaling (ERBB3, AKT3, and CDKN1B). In addition, five genetic variants are eQTLs for EGFR in the cerebellum. Interestingly, both AKT3 and CDKN1B are linked to clinical head size syndromes and cancer risk<sup>17-20</sup> and contain, respectively, 3'-UTR variants and an exonic variant that reach genome-wide significance. ErbB signaling is involved in neurodevelopment,<sup>21-23</sup> making it a plausible pathway involved in head size variation.

Since the above signaling pathways also have universal roles in cell growth, we determined their enrichment in the height GWAS. We found that only the Wnt signaling pathway was significantly enriched in the height GWAS ($p_{adjusted} = 0.038$), suggesting that the p53 and ErbB signaling pathways are more specifically involved in head growth rather than generalized body growth.

## Functional prioritization using gene expression

Using a transcriptome-wide association study (TWAS), we identified 156 head size-associated variants functioning as eQTLs, regulating the expression of 112 genes (eGenes) in relevant tissue types (Table S16). Genomic overlap with additional gene-regulatory and epigenetic features provides evidence for 67 eQTLs regulating the expression of 58 eGenes (RegulomeDB probability score >0.5), including AKT3 in brain tissue and
<figure><img src="image_11.png" /><figcaption>**Figure 2.** Genetic loci for head size and effects on regional brain volumes</figcaption></figure>

(A) Heatmap showing head size loci that overlap with previously identified loci for global brain volumes (red), subcortical volumes (blue), and cortical region of interest volumes (green).

(B) UpSet plot of associations between head size lead variants and brain volumes. Intersection size corresponds to the frequency of the combination depicted below the bar. Set size corresponds to the frequency of associations with one of the brain volume categories (i.e., global, subcortical, or cortical).

(C) Plot showing the subcortical shape analysis of rs111939932 using log Jacobian determinants. Colors correspond to t values, with positive associations depicted in blue, and negative ones in red. Letters point to different subcortical structures: a, putamen; b, pallidum; c, caudate; d, amygdala; e, hippocampus; f, thalamus; g, accumbens.

PTEN) also contained 3'-UTR or exonic variants in LD ($r^2$ > 0.6) with lead variants. Identified genes act in cell-cycle arrest and cellular senescence (CDK6, CDK2, and CCND2), apoptosis (IGF1), or inhibition of the insulin growth factor (IGF)-1/mammalian target of rapamycin (mTOR) pathway (PTEN), suggesting comprehensive involvement of the p53 signaling pathway in head growth. This finding is in line with evidence that p53 signaling regulates both normal and malignant neural stem cell populations.<sup>11-13</sup>

The Wnt signaling pathway has links to carcinogenesis and the developing and adult central nervous system,<sup>14,15</sup> as well as to bone development including cranial growth.<sup>16</sup> Of the eight overlapping genes, three contained exonic or 3'-UTR variants in LD ($r^2$ > 0.6) with identified lead variants (APC, TP53, and TCF7L1). Wnt signaling pathway gene FRZB, not annotated in KEGG, also contained exonic and 3'-UTR variants. In total, 1,948 genetic variants in LD with the identified lead variants ($r^2$ > 0.6), including 35 exonic variants, are eQTLs for WNT3 in 27 different tissues including the cerebellar hemispheres. In addition, various exonic, 3'-UTR and 5'-UTR variants in LD with the lead variants are eQTLs for TCF7L1 in brain tissues. These observations suggest that variants in this pathway affect brain and cranial growth in the human population.

The ErbB pathway ($p_{adjusted} = 0.014$, Figure 3A), also known as the EGFR signaling pathway, has six overlapping genes near head

<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

size variants, which are involved in calcium signaling (PLCG1), MAPK signaling (NCK1 and MAPK1), and PI3K-AKT signaling (ERBB3, AKT3, and CDKN1B). In addition, five genetic variants are eQTLs for EGFR in the cerebellum. Interestingly, both AKT3 and CDKN1B are linked to clinical head size syndromes and cancer risk<sup>17-20</sup> and contain, respectively, 3'-UTR variants and an exonic variant that reach genome-wide significance. ErbB signaling is involved in neurodevelopment,<sup>21-23</sup> making it a plausible pathway involved in head size variation.

Since the above signaling pathways also have universal roles in cell growth, we determined their enrichment in the height GWAS. We found that only the Wnt signaling pathway was significantly enriched in the height GWAS ($p_{adjusted} = 0.038$), suggesting that the p53 and ErbB signaling pathways are more specifically involved in head growth rather than generalized body growth.

## Functional prioritization using gene expression

Using a transcriptome-wide association study (TWAS), we identified 156 head size-associated variants functioning as eQTLs, regulating the expression of 112 genes (eGenes) in relevant tissue types (Table S16). Genomic overlap with additional gene-regulatory and epigenetic features provides evidence for 67 eQTLs regulating the expression of 58 eGenes (RegulomeDB probability score >0.5), including AKT3 in brain tissue and
<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /><figcaption>**Figure 3. Gene sets enriched in human head size loci**</figcaption></figure>

(A) Bar plots presenting enriched KEGG gene sets. -log₁₀ of adjusted *p* value and proportion of nearby genes overlapping with the gene set are presented. Cancer gene sets are depicted in pink, cell growth and death gene sets in yellow-green, and signal transduction gene sets in turquoise.

(B) Network graph showing enriched KEGG gene sets and their included genes near genetic lead variants. Gene sets are shown in squares with arrows to overlapping genes. Colors correspond to gene set categories: only cancer gene sets (pink), only cell growth and death gene sets (yellow-green), only signal transduction gene sets (turquoise), cancer gene sets and cell growth and death gene sets (dark blue), cell growth and death and signal transduction gene sets (green), or all three gene set categories (orange). Sphere size corresponds to the number of gene sets linked to that gene.

(C) Schematic overview of enriched signaling pathways with proteins encoded by genes near (<10 kb) identified genetic loci. Proteins encoded by these genes are colored (green, ErbB pathway; red, p53 pathway; blue, Wnt pathway), other proteins are depicted in gray. Circles next to protein names provide the locus number of the encoding gene. Locations of lead variants and variants in LD (r² > 0.6) are shown in squares next to the proteins: exonic (e; red), 3'-UTR (3'; green), 5'-UTR (5'; light green), intronic (i; blue), intergenic including up- and downstream, exonic and intronic non-coding RNA (g; gray). For Frizzled, not only FZD2 but also FRZB is taken into consideration.

TCF7L1 in the cerebellum—part of the ErbB and Wnt pathway, respectively. In addition, 22 eGenes were suggested to be regulated by 22 splicing QTLs (sQTLs), including AKT3. The omnibus test revealed a shared effect for 80 eGenes across the tested gene expression panels (Table S17), including WNT3, AKT3, and EGFR.

## Enrichment of Mendelian head size genes and cancer genes

Target genes of GWAS variants are often close to the lead variant.²⁴ Accordingly, we determined the enrichment of different categories of genes located nearby head size variants, stratified by their distance (Table S18).
<figure><img src="image_14.png" /><figcaption>**Figure 3. Gene sets enriched in human head size loci**</figcaption></figure>

(A) Bar plots presenting enriched KEGG gene sets. -log₁₀ of adjusted *p* value and proportion of nearby genes overlapping with the gene set are presented. Cancer gene sets are depicted in pink, cell growth and death gene sets in yellow-green, and signal transduction gene sets in turquoise.

(B) Network graph showing enriched KEGG gene sets and their included genes near genetic lead variants. Gene sets are shown in squares with arrows to overlapping genes. Colors correspond to gene set categories: only cancer gene sets (pink), only cell growth and death gene sets (yellow-green), only signal transduction gene sets (turquoise), cancer gene sets and cell growth and death gene sets (dark blue), cell growth and death and signal transduction gene sets (green), or all three gene set categories (orange). Sphere size corresponds to the number of gene sets linked to that gene.

(C) Schematic overview of enriched signaling pathways with proteins encoded by genes near (<10 kb) identified genetic loci. Proteins encoded by these genes are colored (green, ErbB pathway; red, p53 pathway; blue, Wnt pathway), other proteins are depicted in gray. Circles next to protein names provide the locus number of the encoding gene. Locations of lead variants and variants in LD (r² > 0.6) are shown in squares next to the proteins: exonic (e; red), 3'-UTR (3'; green), 5'-UTR (5; light green), intronic (i; blue), intergenic including up- and downstream, exonic and intronic non-coding RNA (g; gray). For Frizzled, not only FZD2 but also FRZB is taken into consideration.

TCF7L1 in the cerebellum—part of the ErbB and Wnt pathway, respectively. In addition, 22 eGenes were suggested to be regulated by 22 splicing QTLs (sQTLs), including AKT3. The omnibus test revealed a shared effect for 80 eGenes across the tested gene expression panels (Table S17), including WNT3, AKT3, and EGFR.

## Enrichment of Mendelian head size genes and cancer genes

Target genes of GWAS variants are often close to the lead variant.²⁴ Accordingly, we determined the enrichment of different categories of genes located nearby head size variants, stratified by their distance (Table S18).
First, we investigated genes mutated in OMIM syndromes associated with abnormal head size, i.e., macrocephaly or microcephaly (Tables S19 and S20). We found increasing enrichment for macrocephaly genes with decreasing distance to the lead variants, culminating in a 37-fold enrichment of macrocephaly genes in genes containing an intragenic lead variant (Figure 4A). In contrast, microcephaly genes were not enriched with shorter distance from lead variants. The striking enrichment of macrocephaly genes did not change in the height-adjusted head size GWAS (Table S21). Furthermore, there was only a modest enrichment for macrocephaly genes in the height GWAS, even for the top 67 loci (i.e., the same number of loci as our GWAS; Table S21). Macrocephaly syndrome genes with intragenic lead variants include *AKT3*, *PTCH1*, *PTEN*, *CCND2*, and *NFIX* (Table S19). We conclude that common genetic variants near genes associated with macrocephaly syndromes, but not microcephaly syndromes, contribute to variation in head size in the general population. Our GWAS of head size may therefore identify novel macrocephaly genes. Accordingly, a patient with intellectual disability²⁵ presented with macrocephaly and a mutation in *TICRR*, a gene for which a lead variant and variants in LD were eQTLs in 12 different tissues. *TICRR* acts in initiation of DNA replication and interacts with *CDK2*,²⁶ a gene nearby another lead variant. *TICRR* is therefore an interesting candidate macrocephaly syndrome gene.

We determined whether cancer genes are enriched close to lead variants (Figure 4A). Indeed, there was a 9-fold enrichment for high-fidelity cancer genes (first-tier COSMIC²⁷) among genes with an intragenic lead variant, which persisted after height adjustment (Table S21). There was only a modest enrichment of cancer genes close to height GWAS variants, providing additional evidence that cancer-related genes are specifically relevant for head size variation.

At a variant-level, no genetic correlation was found with GWAS meta-analyses of various cancer types²⁸⁻³¹ (Table S22).

## Autosomal dominance score

We did not observe a significant enrichment for microcephaly genes (Figure 4A). This may be due to differences between the micro- and macrocephaly gene sets. Macrocephaly typically results from mutations with an autosomal dominant inheritance pattern (64.6%, Table S19), whereas microcephaly predominantly involves mutations with an autosomal recessive inheritance pattern (72.3%, Table S20). We observed a profound increase for genes with a predicted dominant inheritance pattern closer to our lead variants (Figure 4B). However, neither dominant nor recessive microcephaly genes were enriched (Table S21) and the predominant recessive inheritance patterns of microcephaly genes could not explain their lack of enrichment. An alternative explanation is that microcephaly syndromes are more clinically heterogeneous and the underlying mechanisms are less specific to brain and cranial growth.

## Gain of function and loss of function

The overlap among macrocephaly genes, microcephaly genes, and cancer genes is shown in Figure 4C. Macrocephaly-associated genes were more enriched for high-fidelity cancer genes than microcephaly-associated genes (enrichment ratio 12.9 vs.

3.2, Table S21). We therefore investigated whether the same mutation type, i.e., gain of function or loss of function, causes both macrocephaly syndromes as a germline mutation but also associate with cancer as somatic mutations. We found that this was the case for the vast majority of macrocephaly-associated genes with a defined role in cancer (37 of 41 genes, Table S19), i.e., the same type of mutation associated with both macrocephaly and cancer. Moreover, germline mutations in 14 of these 37 genes, including our GWAS genes *PTEN*, *PTCH1*, and *SUFU*, are associated with a syndrome or condition with a suggested cancer predisposition (Table S19). Our GWAS data and these observations may therefore suggest that subtle up-regulation of oncogenes and oncogenic pathways or down-regulation of tumor suppressor genes and pathways increases head size in the general population.

## Brain cell expression

As neural progenitors are the actively dividing cells in the developing brain, their expressed genes may explain the observed genetic variants for head size.³² Indeed, genes at or near the head size loci were enriched in differentially expressed neural progenitor cell genes (Figure 4D; Table S23). Subsequently, we looked at a single-cell RNA-sequencing (scRNA-seq) dataset from cell types in the human cortex.³³,³⁴ Intriguingly, we find that genes close to head size variants are strongly enriched for genes preferentially expressed in intermediate progenitor cells (IPCs) (Figure 4E; Tables S24 and S25; Figure S2). Increased proliferation of IPCs in a primate-specific area of the brain, the outer region subventricular zone, is believed to be responsible for the evolutionary expansion of the human brain.³⁵,³⁶ This suggests that genetic variation regulating the proliferation or neuronal differentiation of IPCs plays an important role in determining human head size. Indeed, Wnt pathway genes, p53 pathway genes, and *PTCH1*, *SUFU*, and *NFIX*, which we find near genetic variants determining head size, are examples of regulators of IPCs.³⁷⁻⁴³ To understand which type of variants influence head size, we performed a partitioned heritability analysis that classifies variants into categories based on functional elements. We found an enrichment for variants in the regulatory elements of both neural progenitors and their neuronal progenies (enrichment<sub>progenitors</sub> = 12.7, *p* = 8.3 × 10<sup>-4</sup>; enrichment<sub>neurons</sub> = 16.1, *p* = 3.7 × 10<sup>-4</sup>).

Finally, we assessed whether a similar pattern was seen for the Catalog of Somatic Mutations in Cancer (COSMIC) first-tier cancer genes. Indeed, our differential gene expression analysis dataset indeed showed an enrichment of cancer genes in the genes specific for neural progenitors (enrichment = 2.9, *p* = 1.7 × 10<sup>-6</sup>, Table S23). However, no significant enrichment was found for IPCs using the scRNA-seq data.

## DISCUSSION

Here we performed the largest head size GWAS to date and found that associated genetic variants significantly locate to cancer genes and cancer-associated pathways. Genes near head size variants were enriched for high-fidelity cancer genes even after adjustment for height, suggesting a specific association of head growth with cancer, rather than general growth. Germline mutations in multiple macrocephaly syndrome genes
First, we investigated genes mutated in OMIM syndromes associated with abnormal head size, i.e., macrocephaly or microcephaly (Tables S19 and S20). We found increasing enrichment for macrocephaly genes with decreasing distance to the lead variants, culminating in a 37-fold enrichment of macrocephaly genes in genes containing an intragenic lead variant (Figure 4A). In contrast, microcephaly genes were not enriched with shorter distance from lead variants. The striking enrichment of macrocephaly genes did not change in the height-adjusted head size GWAS (Table S21). Furthermore, there was only a modest enrichment for macrocephaly genes in the height GWAS, even for the top 67 loci (i.e., the same number of loci as our GWAS; Table S21). Macrocephaly syndrome genes with intragenic lead variants include *AKT3*, *PTCH1*, *PTEN*, *CCND2*, and *NFIX* (Table S19). We conclude that common genetic variants near genes associated with macrocephaly syndromes, but not microcephaly syndromes, contribute to variation in head size in the general population. Our GWAS of head size may therefore identify novel macrocephaly genes. Accordingly, a patient with intellectual disability²⁵ presented with macrocephaly and a mutation in *TICRR*, a gene for which a lead variant and variants in LD were eQTLs in 12 different tissues. *TICRR* acts in initiation of DNA replication and interacts with *CDK2*,²⁶ a gene nearby another lead variant. *TICRR* is therefore an interesting candidate macrocephaly syndrome gene.

We determined whether cancer genes are enriched close to lead variants (Figure 4A). Indeed, there was a 9-fold enrichment for high-fidelity cancer genes (first-tier COSMIC²⁷) among genes with an intragenic lead variant, which persisted after height adjustment (Table S21). There was only a modest enrichment of cancer genes close to height GWAS variants, providing additional evidence that cancer-related genes are specifically relevant for head size variation.

At a variant-level, no genetic correlation was found with GWAS meta-analyses of various cancer types²⁸⁻³¹ (Table S22).

## Autosomal dominance score

We did not observe a significant enrichment for microcephaly genes (Figure 4A). This may be due to differences between the micro- and macrocephaly gene sets. Macrocephaly typically results from mutations with an autosomal dominant inheritance pattern (64.6%, Table S19), whereas microcephaly predominantly involves mutations with an autosomal recessive inheritance pattern (72.3%, Table S20). We observed a profound increase for genes with a predicted dominant inheritance pattern closer to our lead variants (Figure 4B). However, neither dominant nor recessive microcephaly genes were enriched (Table S21) and the predominant recessive inheritance patterns of microcephaly genes could not explain their lack of enrichment. An alternative explanation is that microcephaly syndromes are more clinically heterogeneous and the underlying mechanisms are less specific to brain and cranial growth.

## Gain of function and loss of function

The overlap among macrocephaly genes, microcephaly genes, and cancer genes is shown in Figure 4C. Macrocephaly-associated genes were more enriched for high-fidelity cancer genes than microcephaly-associated genes (enrichment ratio 12.9 vs.

3.2, Table S21). We therefore investigated whether the same mutation type, i.e., gain of function or loss of function, causes both macrocephaly syndromes as a germline mutation but also associate with cancer as somatic mutations. We found that this was the case for the vast majority of macrocephaly-associated genes with a defined role in cancer (37 of 41 genes, Table S19), i.e., the same type of mutation associated with both macrocephaly and cancer. Moreover, germline mutations in 14 of these 37 genes, including our GWAS genes *PTEN*, *PTCH1*, and *SUFU*, are associated with a syndrome or condition with a suggested cancer predisposition (Table S19). Our GWAS data and these observations may therefore suggest that subtle up-regulation of oncogenes and oncogenic pathways or down-regulation of tumor suppressor genes and pathways increases head size in the general population.

## Brain cell expression

As neural progenitors are the actively dividing cells in the developing brain, their expressed genes may explain the observed genetic variants for head size.³² Indeed, genes at or near the head size loci were enriched in differentially expressed neural progenitor cell genes (Figure 4D; Table S23). Subsequently, we looked at a single-cell RNA-sequencing (scRNA-seq) dataset from cell types in the human cortex.³³,³⁴ Intriguingly, we find that genes close to head size variants are strongly enriched for genes preferentially expressed in intermediate progenitor cells (IPCs) (Figure 4E; Tables S24 and S25; Figure S2). Increased proliferation of IPCs in a primate-specific area of the brain, the outer region subventricular zone, is believed to be responsible for the evolutionary expansion of the human brain.³⁵,³⁶ This suggests that genetic variation regulating the proliferation or neuronal differentiation of IPCs plays an important role in determining human head size. Indeed, Wnt pathway genes, p53 pathway genes, and *PTCH1*, *SUFU*, and *NFIX*, which we find near genetic variants determining head size, are examples of regulators of IPCs.³⁷⁻⁴³ To understand which type of variants influence head size, we performed a partitioned heritability analysis that classifies variants into categories based on functional elements. We found an enrichment for variants in the regulatory elements of both neural progenitors and their neuronal progenies (enrichment<sub>progenitors</sub> = 12.7, *p* = 8.3 × 10<sup>-4</sup>; enrichment<sub>neurons</sub> = 16.1, *p* = 3.7 × 10<sup>-4</sup>).

Finally, we assessed whether a similar pattern was seen for the Catalog of Somatic Mutations in Cancer (COSMIC) first-tier cancer genes. Indeed, our differential gene expression analysis dataset indeed showed an enrichment of cancer genes in the genes specific for neural progenitors (enrichment = 2.9, *p* = 1.7 × 10<sup>-6</sup>, Table S23). However, no significant enrichment was found for IPCs using the scRNA-seq data.

## DISCUSSION

Here we performed the largest head size GWAS to date and found that associated genetic variants significantly locate to cancer genes and cancer-associated pathways. Genes near head size variants were enriched for high-fidelity cancer genes even after adjustment for height, suggesting a specific association of head growth with cancer, rather than general growth. Germline mutations in multiple macrocephaly syndrome genes
<figure><img src="image_11.png" /><figcaption>Figure 4. Gene enrichments stratified by distance from head size lead variants</figcaption></figure>

(A) Enrichment of OMIM macro- and microcephaly genes and COSMIC tier 1 genes near identified genetic loci. Depicted are enrichments of genes within 1 Mb (orange), 100 kb (purple), or 10 kb (pink) of identified genetic loci, genes with intragenic genetic variants (light green) and genes with intragenic genetic lead variants (yellow) in comparison with genes in the reference genome (dark green). \*p < 0.05; \*\*p < 0.0125 (0.05/4); \*\*\*p < 0.0025 (0.05/4/5).

(B) Violin plots showing DOMINO autosomal dominance scores of different gene sets. \*p < 0.05; \*\*p < 0.01; \*\*\*p < 0.001.

(C) Venn diagram showing genes within 10 kb of genetic loci that overlap with OMIM microcephaly genes (yellow) or macrocephaly genes (green) or COSMIC cancer tier 1 genes (red). Genes with intragenic lead variants are depicted in black, others in gray.

(D) Bar plot showing enrichments of gene sets for genes differentially expressed in neurons and progenitors. \*p < 0.05; \*\*p < 0.025 (0.05/2); \*\*\*p < 0.003 (0.05/2/8).

(E) Bar plots showing enrichments of gene sets for the various cell types in the human cortical brain using single-cell RNA-sequencing data. \*p < 0.05; \*\*FDR < 0.05; \*\*\*p < 0.0007 (0.05/9/8).
<figure><img src="image_15.png" /><figcaption>Figure 4. Gene enrichments stratified by distance from head size lead variants</figcaption></figure>

(A) Enrichment of OMIM macro- and microcephaly genes and COSMIC tier 1 genes near identified genetic loci. Depicted are enrichments of genes within 1 Mb (orange), 100 kb (purple), or 10 kb (pink) of identified genetic loci, genes with intragenic genetic variants (light green) and genes with intragenic genetic lead variants (yellow) in comparison with genes in the reference genome (dark green). \*p < 0.05; \*\*p < 0.0125 (0.05/4); \*\*\*p < 0.0025 (0.05/4/5).

(B) Violin plots showing DOMINO autosomal dominance scores of different gene sets. \*p < 0.05; \*\*p < 0.01; \*\*\*p < 0.001.

(C) Venn diagram showing genes within 10 kb of genetic loci that overlap with OMIM microcephaly genes (yellow) or macrocephaly genes (green) or COSMIC cancer tier 1 genes (red). Genes with intragenic lead variants are depicted in black, others in gray.

(D) Bar plot showing enrichments of gene sets for genes differentially expressed in neurons and progenitors. \*p < 0.05; \*\*p < 0.025 (0.05/2); \*\*\*p < 0.003 (0.05/2/8).

(E) Bar plots showing enrichments of gene sets for the various cell types in the human cortical brain using single-cell RNA-sequencing data. \*p < 0.05; \*\*FDR < 0.05; \*\*\*p < 0.0007 (0.05/9/8).
are known to be an increased cancer risk, including *PTEN* (Cowden syndrome) and *PTCH1* (Gorlin syndrome) (Table S19). Our GWAS was performed in the general population, which prompts the question of whether the link between head size and cancer extends beyond rare genetic syndromes.

Previous meta-analyses of prospective observational studies found associations between adult height and increased risk for various forms of cancer.⁴⁴ Similarly, head circumference at birth has previously been positively associated with brain cancer during childhood,⁴⁵ and with different types of cancer later in life including stomach cancer and breast cancer,⁴⁶ with stronger associations than for respectively birth weight or birth length. The correlation between head size at birth and breast cancer later in life was further supported by a pooled analysis of 32 studies,⁴⁷ but not by another prospective cohort study.⁴⁸ Our study provides further evidence for this link between head size and cancer.

The abovementioned observational studies together with our genetic results suggest that early growth rather than later adolescent growth may be associated with neoplasia, since craniial growth is completed around the sixth year of age, whereas height is primarily determined by peri-pubertal growth. Head size at birth and its growth during early infancy in relation to cancer risk therefore deserves further studies to identify potential underlying pathophysiological mechanisms and its potential clinical implications.⁴⁵,⁴⁹,⁵⁰

## Limitations of the study

Although this study suggests an association between head growth and cancer, further studies are needed to investigate whether head size is causally related to cancer development. In our study, we were not able to account for environmental factors such as socio-economic status and diet, especially during childhood, which would be important to adjust for in future studies. In addition, the clinical implications of the findings of our study need to be investigated, for example if patients with clinical macrocephaly syndromes need to be screened for cancer more extensively.

## CONSORTIA

The members of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium are Philippe Amouyel, Konstantinos Arfanakis, Benjamin S. Aribisala, Mark E. Bastin, Ganesh Chauhan, Christopher Chen, Ching-Yu Cheng, Philip L. de Jager, Ian J. Deary, Debra A. Fleischman, Rebecca F. Gottesman, Vilmundur Gudnason, Saima Hilal, Edith Hofer, Deborah Janowitz, J. Wouter Jukema, David C.M. Liewald, Lorna M. Lopez, Oscar Lopez, Michelle Luciano, Oliver Martinez, Wiro J. Niessen, Paul Nyquist, Jerome I. Rotter, Tatjana Rundek, Ralph L. Sacco, Helena Schmidt, Henning Tiemeier, Stella Trompet, Jeroen van der Grond, Henry Völzke, Joanna M. Wardlaw, Lisa Yanek, and Jingyun Yang.

The members of the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium are Ingrid Agartz, Saud Alhusaini, Laura Almasy, David Ames, Katrin Amunts, Ole A. Andreassen, Nicola Armstrong, Manon Bernard, John Blangero, Laura M.E. Blanken, Marco P. Boks, Dorret I. Boomsma, Adam M. Brickman, Henry Brodaty, Randy L. Buckner, Jan K.

Buitelaar, Dara M. Cannon, Vaughan J. Carr, Stanley V. Catts, M. Mallar Chakravarty, Qiang Chen, Christopher R.K. Ching, Aiden Corvin, Benedicto Crespo-Facorro, Joanne E. Curran, Gareth E. Davies, Eco J.C. de Geus, Greig I. de Zubicaray, Anouk den Braber, Sylvane Desrivières, Allissa Dillman, Srdjan Djurovic, Wayne C. Drevets, Ravi Duggirala, Stefan Ehrlich, Susanne Erk, Thomas Espeseth, Iryna O. Fedko, Guillén Fernández, Simon E. Fisher, Tatiana M. Foroud, Tian Ge, Sudheer Giddaluru, David C. Glahn, Aaron L. Goldman, Robert C. Green, Corina U. Greven, Oliver Grimm, Narelle K. Hansell, Catharina A. Hartman, Ryota Hashimoto, Andreas Heinz, Frans Henskens, Derrek P. Hibar, Beng-Choon Ho, Pieter J. Hoekstra, Avram J. Holmes, Martine Hoogman, Jouke-Jan Hottenga, Hilleke E. Hulshoff Pol, Assen Jablensky, Mark Jenkinson, Tianye Jia, Karl-Heinz Jöckel, Erik G. Jönsson, Sungeun Kim, Marieke Klein, Peter Kochunov, John B. Kwok, Stephen M. Lawrie, Stephanie Le Hellard, Hervé Lemaitre, Carmel Loughland, Andre F. Marquand, Nicholas G. Martin, Jean-Luc Martinot, Mar Matarin, Daniel H. Mathalon, Karen A. Mather, Venkata S. Mattay, Colm McDonald, Francis J. McMahon, Katie L. McMahon, Rebekah E. McWhirter, Patrizia Mecocci, Ingrid Melle, Andreas Meyer-Lindenberg, Patricia T. Michie, Yuri Milaneschi, Derek W. Morris, Bryan Mowry, Kwang-sik Nho, Thomas E. Nichols, Markus N. Nöthen, Rene L. Olvera, Jaap Oosterlaan, Roel A. Ophoff, Massimo Pandolfo, Christos Pantelis, Irene Pappa, Brenda Penninx, G. Bruce Pike, Paul E. Rasser, Miguel E. Rentería, Simone Reppermund, Marcella Rietschel, Shannon L. Risacher, Nina Romanczuk-Seiferth, Emma Jane Rose, Perminder S. Sachdev, Philipp G. Sämann, Andrew J. Saykin, Ulrich Schall, Peter R. Schofield, Sara Schramm, Gunter Schumann, Rodney Scott, Li Shen, Sanjay M. Sisodiya, Hilkka Soininen, Emma Sprooten, Velandai Srikanth, Vidar M. Steen, Lachlan T. Strike, Anbupalam Thalamuthu, Arthur W. Toga, Paul Tooney, Diana Tordesillas-Gutiérrez, Jessica A. Turner, Maria del C. Valdés Hernández, Dennis van der Meer, Nic J.A. Van der Wee, Neeltje E.M. Van Haren, Dennis van 't Ent, Dick J. Veltman, Henrik Walter, Daniel R. Weinberger, Michael W. Weiner, Wei Wen, Lars T. Westlye, Eric Westman, Anderson M. Winkler, Girma Woldehawariat, Margaret J. Wright, and Jingqin Wu.

## STAR★METHODS

Detailed methods are provided in the online version of this paper and include the following:

* KEY RESOURCES TABLE

* RESOURCE AVAILABILITY

* Lead contact

* Materials availability

* Data and code availability

* EXPERIMENTAL MODEL AND SUBJECT DETAILS

* Study population

* Genotyping

* Phenotyping

* METHOD DETAILS

* Genome-wide association studies

* Functional annotations

* Effects on anthropomorphic measures and regional brain volumes

* Genetic correlations

* Enrichment analyses

* Experimental datasets of brain cells
are known to be an increased cancer risk, including *PTEN* (Cowden syndrome) and *PTCH1* (Gorlin syndrome) (Table S19). Our GWAS was performed in the general population, which prompts the question of whether the link between head size and cancer extends beyond rare genetic syndromes.

Previous meta-analyses of prospective observational studies found associations between adult height and increased risk for various forms of cancer.⁴⁴ Similarly, head circumference at birth has previously been positively associated with brain cancer during childhood,⁴⁵ and with different types of cancer later in life including stomach cancer and breast cancer,⁴⁶ with stronger associations than for respectively birth weight or birth length. The correlation between head size at birth and breast cancer later in life was further supported by a pooled analysis of 32 studies,⁴⁷ but not by another prospective cohort study.⁴⁸ Our study provides further evidence for this link between head size and cancer.

The abovementioned observational studies together with our genetic results suggest that early growth rather than later adolescent growth may be associated with neoplasia, since craniial growth is completed around the sixth year of age, whereas height is primarily determined by peri-pubertal growth. Head size at birth and its growth during early infancy in relation to cancer risk therefore deserves further studies to identify potential underlying pathophysiological mechanisms and its potential clinical implications.⁴⁵,⁴⁹,⁵⁰

## Limitations of the study

Although this study suggests an association between head growth and cancer, further studies are needed to investigate whether head size is causally related to cancer development. In our study, we were not able to account for environmental factors such as socio-economic status and diet, especially during childhood, which would be important to adjust for in future studies. In addition, the clinical implications of the findings of our study need to be investigated, for example if patients with clinical macrocephaly syndromes need to be screened for cancer more extensively.

## CONSORTIA

The members of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium are Philippe Amouyel, Konstantinos Arfanakis, Benjamin S. Aribisala, Mark E. Bastin, Ganesh Chauhan, Christopher Chen, Ching-Yu Cheng, Philip L. de Jager, Ian J. Deary, Debra A. Fleischman, Rebecca F. Gottesman, Vilmundur Gudnason, Saima Hilal, Edith Hofer, Deborah Janowitz, J. Wouter Jukema, David C.M. Liewald, Lorna M. Lopez, Oscar Lopez, Michelle Luciano, Oliver Martinez, Wiro J. Niessen, Paul Nyquist, Jerome I. Rotter, Tatjana Rundek, Ralph L. Sacco, Helena Schmidt, Henning Tiemeier, Stella Trompet, Jeroen van der Grond, Henry Völzke, Joanna M. Wardlaw, Lisa Yanek, and Jingyun Yang.

The members of the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium are Ingrid Agartz, Saud Alhusaini, Laura Almasy, David Ames, Katrin Amunts, Ole A. Andreassen, Nicola Armstrong, Manon Bernard, John Blangero, Laura M.E. Blanken, Marco P. Boks, Dorret I. Boomsma, Adam M. Brickman, Henry Brodaty, Randy L. Buckner, Jan K.

Buitelaar, Dara M. Cannon, Vaughan J. Carr, Stanley V. Catts, M. Mallar Chakravarty, Qiang Chen, Christopher R.K. Ching, Aiden Corvin, Benedicto Crespo-Facorro, Joanne E. Curran, Gareth E. Davies, Eco J.C. de Geus, Greig I. de Zubicaray, Anouk den Braber, Sylvane Desrivières, Allissa Dillman, Srdjan Djurovic, Wayne C. Drevets, Ravi Duggirala, Stefan Ehrlich, Susanne Erk, Thomas Espeseth, Iryna O. Fedko, Guillén Fernández, Simon E. Fisher, Tatiana M. Foroud, Tian Ge, Sudheer Giddaluru, David C. Glahn, Aaron L. Goldman, Robert C. Green, Corina U. Greven, Oliver Grimm, Narelle K. Hansell, Catharina A. Hartman, Ryota Hashimoto, Andreas Heinz, Frans Henskens, Derrek P. Hibar, Beng-Choon Ho, Pieter J. Hoekstra, Avram J. Holmes, Martine Hoogman, Jouke-Jan Hottenga, Hilleke E. Hulshoff Pol, Assen Jablensky, Mark Jenkinson, Tianye Jia, Karl-Heinz Jöckel, Erik G. Jönsson, Sungeun Kim, Marieke Klein, Peter Kochunov, John B. Kwok, Stephen M. Lawrie, Stephanie Le Hellard, Hervé Lemaitre, Carmel Loughland, Andre F. Marquand, Nicholas G. Martin, Jean-Luc Martinot, Mar Matarin, Daniel H. Mathalon, Karen A. Mather, Venkata S. Mattay, Colm McDonald, Francis J. McMahon, Katie L. McMahon, Rebekah E. McWhirter, Patrizia Mecocci, Ingrid Melle, Andreas Meyer-Lindenberg, Patricia T. Michie, Yuri Milaneschi, Derek W. Morris, Bryan Mowry, Kwang-sik Nho, Thomas E. Nichols, Markus N. Nöthen, Rene L. Olvera, Jaap Oosterlaan, Roel A. Ophoff, Massimo Pandolfo, Christos Pantelis, Irene Pappa, Brenda Penninx, G. Bruce Pike, Paul E. Rasser, Miguel E. Rentería, Simone Reppermund, Marcella Rietschel, Shannon L. Risacher, Nina Romanczuk-Seiferth, Emma Jane Rose, Perminder S. Sachdev, Philipp G. Sämann, Andrew J. Saykin, Ulrich Schall, Peter R. Schofield, Sara Schramm, Gunter Schumann, Rodney Scott, Li Shen, Sanjay M. Sisodiya, Hilkka Soininen, Emma Sprooten, Velandai Srikanth, Vidar M. Steen, Lachlan T. Strike, Anbupalam Thalamuthu, Arthur W. Toga, Paul Tooney, Diana Tordesillas-Gutiérrez, Jessica A. Turner, Maria del C. Valdés Hernández, Dennis van der Meer, Nic J.A. Van der Wee, Neeltje E.M. Van Haren, Dennis van 't Ent, Dick J. Veltman, Henrik Walter, Daniel R. Weinberger, Michael W. Weiner, Wei Wen, Lars T. Westlye, Eric Westman, Anderson M. Winkler, Girma Woldehawariat, Margaret J. Wright, and Jingqin Wu.

## STAR★METHODS

Detailed methods are provided in the online version of this paper and include the following:

* KEY RESOURCES TABLE

* RESOURCE AVAILABILITY

* Lead contact

* Materials availability

* Data and code availability

* EXPERIMENTAL MODEL AND SUBJECT DETAILS

* Study population

* Genotyping

* Phenotyping

* METHOD DETAILS

* Genome-wide association studies

* Functional annotations

* Effects on anthropomorphic measures and regional brain volumes

* Genetic correlations

* Enrichment analyses

* Experimental datasets of brain cells
● QUANTIFICATION AND STATISTICAL ANALYSIS

SUPPLEMENTAL INFORMATION

Supplemental information can be found online at https://doi.org/10.1016/j.xcrm.2024.101529.

ACKNOWLEDGMENTS

Acknowledgments are provided for the studies that contributed new samples
in addition to samples in previous efforts.⁵,⁶

The TWAS analysis in this study is supported by the following funding
resource: P30AG066546 (South Texas Alzheimer's Disease Research Center).

The 1000BRAINS study was funded by the Institute of Neuroscience and Medicine, Research Center Juelich, Germany. We thank the Heinz Nixdorf Foundation (Germany) for the generous support of the Heinz Nixdorf Recall Study on which 1000BRAINS is based. We also thank the scientists and the study staff of the Heinz Nixdorf Recall Study and 1000BRAINS. Funding was also granted by the Initiative and Networking Fund of the Helmholtz Association (S. Caspers) and the European Union's Horizon 2020 Research and Innovation Programme under grant agreements 785907 (Human Brain Project SGA2; K. Amunts, S. Caspers, and S. Cichon) and 945539 (Human Brain Project SGA3; K. Amunts, S. Caspers, and S. Cichon).

The Three-City (3C) Study (Bordeaux and Dijon) is conducted under a part-
nership agreement between the Institut National de la Santé et de la Re-
cherche Médicale (INSERM), the Institut de Santé Publique et Développement
of the Victor Segalen Bordeaux 2 University, and Sanofi-Aventis. The Fonda-
tion pour la Recherche Médicale funded the preparation and initiation of the
study. The 3C Study is also supported by the Caisse Nationale Maladie des
Travailleurs Salariés, Direction Générale de la Santé, Mutuelle Générale de
l'Education Nationale, Institut de la Longévité, Regional Governments of Aqui-
taine and Bourgogne, Fondation de France, Ministry of Research-INSERM
Program "Cohortes et collections de données biologiques," French National
Research Agency COGINUT (ANR-06-PNRA-005), the Fondation Plan Alz-
heimer (FCS 2009-2012), and the Caisse Nationale pour la Solidarité et
l'Autonomie (CNSA). This project has received funding from the European
Union's Horizon 2020 Research and Innovation Programme under grant
agreement nos. 643417 and 640643, the French National Research Agency
(ANR) - France 2030: ANR-18-RHUS-0002 and ANR-23-IAHU-0001, and the
University of Bordeaux Initiative of Excellence (IdEX). Part of the computations
were performed at the Bordeaux Bioinformatics Center (CBiB), the University
of Bordeaux, and the CREDIM (Centre de Ressource et Développement en In-
formatique Médicale) at University of Bordeaux, on a server infrastructure sup-
ported by the Fondation Claude Pompidou. The project is supported through
the following funding organizations under the aegis of JPDN (www.jpnd.eu;
BRIDGET project): Australia, National Health and Medical Research Council;
Austria, Federal Ministry of Science, Research and Economy; Canada, Cana-
dian Institutes of Health Research; France, French National Research Agency;
Germany, Federal Ministry of Education and Research; Netherlands, The
Netherlands Organisation for Health Research and Development; and United
Kingdom, Medical Research Council.

The Atherosclerosis Risk in Communities (ARIC) study has been funded in whole or in part with federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services (contract numbers HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I, and HHSN268201700005I), R01HL087641 and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. The authors thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by grant number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. This project was supported in part by National Institute of Neurological Disorders and Stroke grant NS087541.

Data and samples were collected by the Australian Schizophrenia Research
Bank (ASRB), supported by the Australian NHMRC, the Pratt Foundation,

Ramsay Health Care, and the Viertel Charitable Foundation. The ASRB was
also supported by the Schizophrenia Research Institute (Australia), utilizing
infrastructure funding from NSW Health and the Macquarie Group Foundation.
DNA analysis was supported by the Neurobehavioral Genetics Unit, using
funding from NSW Health. M.J.C. was supported by an NHMRC Senior
Research Fellowship (1121474), and M.J.C. and M.J.G. were supported by
NHMRC project grants 1147644 and 1051672.

The authors are deeply indebted to Gael Jobard, Marc Joliot, Emmanuel Mellet, Laurent Petit, and Laure Zago for their contribution to the design, acquisition, and analyses of the BIL&GIN. A.C.-C. was funded by a grant to C.F. from the Netherlands Organization for Scientific Research (NWO) (054-15-101) and B.M. and F.C. by a grant from the French National Research Agency (ANR) (grant no. 15-HBPR-0001-03) as part of the FLAG-ERA consortium project "MULTI-LATERAL," a partner project to the European Union's Flagship Human Brain Project.

The Coronary Artery Risk Development in Young Adults Study (CARDIA) is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with the University of Alabama at Birmingham (75N92023D00002 and 75N92023D00005), Northwestern University (75N92023D00004), University of Minnesota (75N92023D00006), and Kaiser Foundation Research Institute (75N92023D00003). CARDIA was also partially supported by the Intramural Research Program of the National Institute on Aging (NIA) and an intra-agency agreement between NIA and NHLBI (AG0005). This manuscript has been reviewed by CARDIA for scientific content.

The CROMIS-2 ICH study is funded by the Stroke Association and British Heart Foundation. Funding for genotyping was provided by the UCLH/UCL National Institute for Health Research (NIHR) Biomedical Research Centre.

The Diabetes Heart Study (DHS) was supported in part by the National Institutes of Health through R01 HL67348, R01 HL092301, R01 NS058700, R01 NS075107, and R01 AG058921 and the General Clinical Research Center at Wake Forest School of Medicine (M01 RR07122 and F32 HL085989). The authors thank the investigators, staff, and participants of the DHS for their valuable contributions.

The Duke Neurogenetics Study (DNS) was supported by Duke University as well as National Institutes of Health grants R01DA033369 and R01DA031579. R.A., A.R.K., and A.R.H. received further support from National Institutes of Health grant R01AG049789.

We are grateful to all the participants of the Epidemiological Prevention
Study Zoetermeer (EPOZ). We would like to thank Dr. Ir. Natalie Terzikhan
for imputing the genetic data.

The Erasmus Stroke Study (ESS) was supported by Stroke Research Foun-
dation and Erasmus MC MRACE grants.

This work was supported by the National Center for Research Resources at the National Institutes of Health (grant numbers NIH 1 U24 RR021992 [Function Biomedical Informatics Research Network] and NIH 1 U24 RR025736-01 [Biomedical Informatics Research Network Coordinating Center]), the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health through grant UL1 TR000153, and the National Institutes of Health through 5R01MH094524 and P20GM103472. J.M.F. was funded by the Veterans Administration (1I1K6CX002519).

This work was supported by the NHLBI's Framingham Heart Study (contracts N01-HC-25195, HHSN268201500001I, and 75N92019D00031) and its contract with Affymetrix, Inc., for genotyping services (contract no. N02-HL-6-4278). A portion of this research utilized the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. This study was also supported by grants from the National Institute of Aging (R01s AG033040, AG033193, AG054076, AG049607, AG008122, AG016495, U01-AG049505, AG052409, AG058589, and RF1AG059421) and the National Institute of Neurological Disorders and Stroke (R01-NS017950). We would like to thank the dedication of the Framingham Study participants as well as the Framingham Study team, especially investigators and staff from the Neurology group, for their contributions to data collection. C.D. is supported by the Alzheimer's Disease Center (P30 AG 010129) and by National Institute on Aging grants R01AG054076 and P30 AG072972. The views expressed in this manuscript are those of the authors and do not necessarily
● QUANTIFICATION AND STATISTICAL ANALYSIS

SUPPLEMENTAL INFORMATION

Supplemental information can be found online at https://doi.org/10.1016/j.xcrm.2024.101529.

ACKNOWLEDGMENTS

Acknowledgments are provided for the studies that contributed new samples
in addition to samples in previous efforts.⁵,⁶

The TWAS analysis in this study is supported by the following funding
resource: P30AG066546 (South Texas Alzheimer's Disease Research Center).

The 1000BRAINS study was funded by the Institute of Neuroscience and Medicine, Research Center Juelich, Germany. We thank the Heinz Nixdorf Foundation (Germany) for the generous support of the Heinz Nixdorf Recall Study on which 1000BRAINS is based. We also thank the scientists and the study staff of the Heinz Nixdorf Recall Study and 1000BRAINS. Funding was also granted by the Initiative and Networking Fund of the Helmholtz Association (S. Caspers) and the European Union's Horizon 2020 Research and Innovation Programme under grant agreements 785907 (Human Brain Project SGA2; K. Amunts, S. Caspers, and S. Cichon) and 945539 (Human Brain Project SGA3; K. Amunts, S. Caspers, and S. Cichon).

The Three-City (3C) Study (Bordeaux and Dijon) is conducted under a part-
nership agreement between the Institut National de la Santé et de la Re-
cherche Médicale (INSERM), the Institut de Santé Publique et Développement
of the Victor Segalen Bordeaux 2 University, and Sanofi-Aventis. The Fonda-
tion pour la Recherche Médicale funded the preparation and initiation of the
study. The 3C Study is also supported by the Caisse Nationale Maladie des
Travailleurs Salariés, Direction Générale de la Santé, Mutuelle Générale de
l'Education Nationale, Institut de la Longévité, Regional Governments of Aqui-
taine and Bourgogne, Fondation de France, Ministry of Research-INSERM
Program "Cohortes et collections de données biologiques," French National
Research Agency COGINUT (ANR-06-PNRA-005), the Fondation Plan Alz-
heimer (FCS 2009-2012), and the Caisse Nationale pour la Solidarité et
l'Autonomie (CNSA). This project has received funding from the European
Union's Horizon 2020 Research and Innovation Programme under grant
agreement nos. 643417 and 640643, the French National Research Agency
(ANR) - France 2030: ANR-18-RHUS-0002 and ANR-23-IAHU-0001, and the
University of Bordeaux Initiative of Excellence (IdEX). Part of the computations
were performed at the Bordeaux Bioinformatics Center (CBiB), the University
of Bordeaux, and the CREDIM (Centre de Ressource et Développement en In-
formatique Médicale) at University of Bordeaux, on a server infrastructure sup-
ported by the Fondation Claude Pompidou. The project is supported through
the following funding organizations under the aegis of JPDN (www.jpnd.eu;
BRIDGET project): Australia, National Health and Medical Research Council;
Austria, Federal Ministry of Science, Research and Economy; Canada, Cana-
dian Institutes of Health Research; France, French National Research Agency;
Germany, Federal Ministry of Education and Research; Netherlands, The
Netherlands Organisation for Health Research and Development; and United
Kingdom, Medical Research Council.

The Atherosclerosis Risk in Communities (ARIC) study has been funded in whole or in part with federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services (contract numbers HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I, and HHSN268201700005I), R01HL087641 and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. The authors thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by grant number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. This project was supported in part by National Institute of Neurological Disorders and Stroke grant NS087541.

Data and samples were collected by the Australian Schizophrenia Research
Bank (ASRB), supported by the Australian NHMRC, the Pratt Foundation,

Ramsay Health Care, and the Viertel Charitable Foundation. The ASRB was
also supported by the Schizophrenia Research Institute (Australia), utilizing
infrastructure funding from NSW Health and the Macquarie Group Foundation.
DNA analysis was supported by the Neurobehavioral Genetics Unit, using
funding from NSW Health. M.J.C. was supported by an NHMRC Senior
Research Fellowship (1121474), and M.J.C. and M.J.G. were supported by
NHMRC project grants 1147644 and 1051672.

The authors are deeply indebted to Gael Jobard, Marc Joliot, Emmanuel Mellet, Laurent Petit, and Laure Zago for their contribution to the design, acquisition, and analyses of the BIL&GIN. A.C.-C. was funded by a grant to C.F. from the Netherlands Organization for Scientific Research (NWO) (054-15-101) and B.M. and F.C. by a grant from the French National Research Agency (ANR) (grant no. 15-HBPR-0001-03) as part of the FLAG-ERA consortium project "MULTI-LATERAL," a partner project to the European Union's Flagship Human Brain Project.

The Coronary Artery Risk Development in Young Adults Study (CARDIA) is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with the University of Alabama at Birmingham (75N92023D00002 and 75N92023D00005), Northwestern University (75N92023D00004), University of Minnesota (75N92023D00006), and Kaiser Foundation Research Institute (75N92023D00003). CARDIA was also partially supported by the Intramural Research Program of the National Institute on Aging (NIA) and an intra-agency agreement between NIA and NHLBI (AG0005). This manuscript has been reviewed by CARDIA for scientific content.

The CROMIS-2 ICH study is funded by the Stroke Association and British Heart Foundation. Funding for genotyping was provided by the UCLH/UCL National Institute for Health Research (NIHR) Biomedical Research Centre.

The Diabetes Heart Study (DHS) was supported in part by the National Institutes of Health through R01 HL67348, R01 HL092301, R01 NS058700, R01 NS075107, and R01 AG058921 and the General Clinical Research Center at Wake Forest School of Medicine (M01 RR07122 and F32 HL085989). The authors thank the investigators, staff, and participants of the DHS for their valuable contributions.

The Duke Neurogenetics Study (DNS) was supported by Duke University as well as National Institutes of Health grants R01DA033369 and R01DA031579. R.A., A.R.K., and A.R.H. received further support from National Institutes of Health grant R01AG049789.

We are grateful to all the participants of the Epidemiological Prevention
Study Zoetermeer (EPOZ). We would like to thank Dr. Ir. Natalie Terzikhan
for imputing the genetic data.

The Erasmus Stroke Study (ESS) was supported by Stroke Research Foun-
dation and Erasmus MC MRACE grants.

This work was supported by the National Center for Research Resources at the National Institutes of Health (grant numbers NIH 1 U24 RR021992 [Function Biomedical Informatics Research Network] and NIH 1 U24 RR025736-01 [Biomedical Informatics Research Network Coordinating Center]), the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health through grant UL1 TR000153, and the National Institutes of Health through 5R01MH094524 and P20GM103472. J.M.F. was funded by the Veterans Administration (1I1K6CX002519).

This work was supported by the NHLBI's Framingham Heart Study (contracts N01-HC-25195, HHSN268201500001I, and 75N92019D00031) and its contract with Affymetrix, Inc., for genotyping services (contract no. N02-HL-6-4278). A portion of this research utilized the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. This study was also supported by grants from the National Institute of Aging (R01s AG033040, AG033193, AG054076, AG049607, AG008122, AG016495, U01-AG049505, AG052409, AG058589, and RF1AG059421) and the National Institute of Neurological Disorders and Stroke (R01-NS017950). We would like to thank the dedication of the Framingham Study participants as well as the Framingham Study team, especially investigators and staff from the Neurology group, for their contributions to data collection. C.D. is supported by the Alzheimer's Disease Center (P30 AG 010129) and by National Institute on Aging grants R01AG054076 and P30 AG072972. The views expressed in this manuscript are those of the authors and do not necessarily
represent the views of the NHLBI, the National Institutes of Health, or the US Department of Health and Human Services.

The Generation R Study was supported by ZonMw (TOP project 91211021 [T.W.]), the Sophia Foundation (grant S18-20 [R.L.M.]), and the European Union's Horizon 2020 Research and Innovation Programme (no. 733206 LifeCycle Project [S. Lamballais], no. 848158 EarlyCause Project [C.A.M.C.], and Marie Skłodowska-Curie grant agreement no. 707404 [C.A.M.C.]). The Generation R Study is conducted by the Erasmus Medical Center in close collaboration with the School of Law and Faculty of Social Sciences of the Erasmus University Rotterdam; the Municipal Health Service Rotterdam Area, Rotterdam; the Rotterdam Homecare Foundation, Rotterdam; and the Stichting Trombosedienst & Artsenlaboratorium Rijnmond (STAR-MDC), Rotterdam. We gratefully acknowledge the contribution of children and parents, general practitioners, hospitals, midwives, and pharmacies in Rotterdam. The general design of the Generation R Study is made possible by financial support from the Erasmus Medical Center, Rotterdam; the Erasmus University Rotterdam; the Netherlands Organization for Health Research and Development (ZonMw); the Netherlands Organisation for Scientific Research (NWO); the Ministry of Health, Welfare and Sport; and the Ministry of Youth and Families.

The Trøndelag Health Study (HUNT) is a collaboration between HUNT Research Center (Faculty of Medicine and Health Sciences, NTNU - Norwegian University of Science and Technology), Nord-Trøndelag County Council, Central Norway Health Authority, and the Norwegian Institute of Public Health. HUNT MRI was funded by the liaison committee between the Central Norway Regional Health Authority and the Norwegian University of Science and Technology as well as the Norwegian National Advisory Unit for functional magnetic resonance imaging (MRI).

The Institute of Mental Health (IMH) study was supported by research grants from the National Healthcare Group, Singapore (SIG/05004 and SIG/05028), and the Singapore Bioimaging Consortium (RP C-009/2006) research grants awarded to K. Sim.

The Internet-based Students Health Research Enterprise (i-Share) study is conducted by the Universities of Bordeaux and Versailles Saint-Quentin-en-Yvelines (France). The i-Share study has received funding from the French National Agency (Agence Nationale de la Recherche [ANR]) via the "Investissements d'Avenir" program (grant number ANR-10-COH0-05) and from the University of Bordeaux Initiative of Excellence (IdEX). This project has also received funding from the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation Programme under grant agreement no. 640643. The 3C Study is conducted under a partnership agreement among the Institut National de la Santé et de la Recherche Médicale (INSERM), the University of Bordeaux, and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. S. Debette has received investigator-initiated research funding from the French National Research Agency (ANR) and from the Fondation Leducq. This work was supported by the National Foundation for Alzheimer's Disease and Related Disorders, the Institut Pasteur de Lille, the LabEx DISTALZ, and the Centre National de Génotypage. This project is an EU Joint Program - Neurodegenerative Disease Research (JPND) project. The project is supported through the following funding organizations under the aegis of JPND (www.jpnd.eu): Australia, National Health and Medical Research Council; Austria, Federal Ministry of Science, Research and Economy; Canada, Canadian Institutes of Health Research; France, French National Research Agency; Germany, Federal Ministry of Education and Research; Netherlands, The Netherlands Organisation for Health Research and Development; and United Kingdom, Medical Research Council. In addition, S. Debette is supported by a grant overseen by the French National Research Agency (ANR) as part of the Investment for the Future Program ANR-18-RHUS-0002. Part of the computations were performed at the Bordeaux Bioinformatics Center (CBiB), University of Bordeaux, and at the CREDIM at University of Bordeaux, on a server infrastructure supported by the Fondation Claude Pompidou.

LIFE-Adult is supported by LIFE - Leipzig Research Center for Civilization Diseases, an organizational unit affiliated to the Medical Faculty of the University of Leipzig. LIFE is funded by means of the European Union, European Regional Development Fund (ERDF) and by funds of the Free State of Saxony within the framework of the excellence initiative (project numbers 713-241202,

713-241202, 14505/2470, and 14575/2470). We thank all participants and Kerstin Wirkner, Ulrike Scharrer, Katrin Arelin, and everyone involved in MRI data acquisition and analysis.

The Nagahama Prospective Genome Cohort for Comprehensive Human Bioscience is grateful to the Nagahama City Office and the nonprofit organization Zeroji Club for their help in conducting the study. This project is supported by operational funds of Kyoto University and the Top Global University Project of the Ministry of Education, Culture, Sports, Science and Technology (MEXT) in Japan. We also receive Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science and research grants from the Japan Agency for Medical Research and Development for the Practical Research Project for Rare/Intractable Diseases and the Comprehensive Research on Aging and Health Science for Dementia R&D. M.-G.D. received a grant from the Fondation Bettencourt Schueler.

As part of the Poznan MS study, M.A.P. reported receiving grants from the Polish National Science Centre: 2011/01/D/NZ4/05801.

The Rotterdam Study (RS) is funded by Erasmus Medical Center and Erasmus University, Rotterdam; the Netherlands Organization for Health Research and Development (ZonMw); the Research Institute for Diseases in the Elderly (RIDE); the Ministry of Education, Culture and Science; the Ministry for Health, Welfare and Sports; the European Commission (DG XII); and the Municipality of Rotterdam. The authors are grateful to the study participants, the staff from the Rotterdam Study, and the participating general practitioners and pharmacists. The generation and management of GWAS genotype data for the Rotterdam Study (RS I, RS II, and RS III) were executed by the Human Genotyping Facility of the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands. The GWAS datasets are supported by the Netherlands Organisation of Scientific Research NWO Investments (no. 175.010.2005.011, 911-03-012); the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC; the Research Institute for Diseases in the Elderly (014-93-015; RIDE2); the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO); and Netherlands Consortium for Healthy Aging (NCHA) project no. 050-060-810. We thank Pascal Arp, Mila Jhamai, Marijn Verkerk, Lizbeth Herrera, Marjolein Peters, and Carolina Medina-Gomez for their help in creating the GWAS database and Karol Estrada, Yurii Aulchenko, and Carolina Medina-Gomez for the creation and analysis of imputed data. H.H.H.A. is supported by ZonMw grant number 916.19.151.

Study of Health in Pomerania - TREND (SHIP-TREND) is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grant nos. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs, and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. MRI scans and genome-wide SNP typing in SHIP-TREND have been supported by a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. The University of Greifswald is a member of the Caché Campus program of the InterSystems GmbH.

The Canadian Institutes of Health Research and the Heart and Stroke Foundation of Canada fund the Saguenay Youth Study (SYS). Computations were performed on the GPC supercomputer at the SciNet HPC Consortium. SciNet is funded by the Canada Foundation for Innovation under the auspices of Compute Canada, the Government of Ontario, Ontario Research Fund - Research Excellence, and the University of Toronto.

This research has been conducted using the UK Biobank Resource under application number 23509.

Vitamin D Intervention in Infants (VIDI) is supported by the Finnish Medical Foundation, the Academy of Finland, the Sigrid Jusélius Foundation, the Swedish Research Council, the Novo Nordisk Foundation, Finska Läkaresällskapet, and the Folkhälsan Research Foundation. We want to thank Dr. Helena Hauta-alus, Dr. Elisa Holmlund-Suila, Dr. Saara Valkama, and Dr. Jenni Rosendahl for their contribution in acquiring the data.

## AUTHOR CONTRIBUTIONS

Performed statistical analysis: M.J.K., R.A.P., T.E.E., C.L.S., A.M., S.v.d.A., M.-G.D., X.J., I.C.H., S. Lamballais, M.A.P., C.E.L., A.C.-C., T.G.M.v.E., C.S.R., J.S., M. Scholz, A.K., G.H.Y.L., R.A., J.R.A., F.-C.H., A.R.A., M.L., A.
<figure><img src="image_16.png" /></figure>

represent the views of the NHLBI, the National Institutes of Health, or the US Department of Health and Human Services.

The Generation R Study was supported by ZonMw (TOP project 91211021 [T.W.]), the Sophia Foundation (grant S18-20 [R.L.M.]), and the European Union's Horizon 2020 Research and Innovation Programme (no. 733206 LifeCycle Project [S. Lamballais], no. 848158 EarlyCause Project [C.A.M.C.], and Marie Skłodowska-Curie grant agreement no. 707404 [C.A.M.C.]). The Generation R Study is conducted by the Erasmus Medical Center in close collaboration with the School of Law and Faculty of Social Sciences of the Erasmus University Rotterdam; the Municipal Health Service Rotterdam Area, Rotterdam; the Rotterdam Homecare Foundation, Rotterdam; and the Stichting Trombosedienst & Artsenlaboratorium Rijnmond (STAR-MDC), Rotterdam. We gratefully acknowledge the contribution of children and parents, general practitioners, hospitals, midwives, and pharmacies in Rotterdam. The general design of the Generation R Study is made possible by financial support from the Erasmus Medical Center, Rotterdam; the Erasmus University Rotterdam; the Netherlands Organization for Health Research and Development (ZonMw); the Netherlands Organisation for Scientific Research (NWO); the Ministry of Health, Welfare and Sport; and the Ministry of Youth and Families.

The Trøndelag Health Study (HUNT) is a collaboration between HUNT Research Center (Faculty of Medicine and Health Sciences, NTNU - Norwegian University of Science and Technology), Nord-Trøndelag County Council, Central Norway Health Authority, and the Norwegian Institute of Public Health. HUNT MRI was funded by the liaison committee between the Central Norway Regional Health Authority and the Norwegian University of Science and Technology as well as the Norwegian National Advisory Unit for functional magnetic resonance imaging (MRI).

The Institute of Mental Health (IMH) study was supported by research grants from the National Healthcare Group, Singapore (SIG/05004 and SIG/05028), and the Singapore Bioimaging Consortium (RP C-009/2006) research grants awarded to K. Sim.

The Internet-based Students Health Research Enterprise (i-Share) study is conducted by the Universities of Bordeaux and Versailles Saint-Quentin-en-Yvelines (France). The i-Share study has received funding from the French National Agency (Agence Nationale de la Recherche [ANR]) via the "Investissements d'Avenir" program (grant number ANR-10-COH0-05) and from the University of Bordeaux Initiative of Excellence (IdEX). This project has also received funding from the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation Programme under grant agreement no. 640643. The 3C Study is conducted under a partnership agreement among the Institut National de la Santé et de la Recherche Médicale (INSERM), the University of Bordeaux, and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. S. Debette has received investigator-initiated research funding from the French National Research Agency (ANR) and from the Fondation Leducq. This work was supported by the National Foundation for Alzheimer's Disease and Related Disorders, the Institut Pasteur de Lille, the LabEx DISTALZ, and the Centre National de Génotypage. This project is an EU Joint Program - Neurodegenerative Disease Research (JPND) project. The project is supported through the following funding organizations under the aegis of JPND (www.jpnd.eu): Australia, National Health and Medical Research Council; Austria, Federal Ministry of Science, Research and Economy; Canada, Canadian Institutes of Health Research; France, French National Research Agency; Germany, Federal Ministry of Education and Research; Netherlands, The Netherlands Organisation for Health Research and Development; and United Kingdom, Medical Research Council. In addition, S. Debette is supported by a grant overseen by the French National Research Agency (ANR) as part of the Investment for the Future Program ANR-18-RHUS-0002. Part of the computations were performed at the Bordeaux Bioinformatics Center (CBiB), University of Bordeaux, and at the CREDIM at University of Bordeaux, on a server infrastructure supported by the Fondation Claude Pompidou.

LIFE-Adult is supported by LIFE - Leipzig Research Center for Civilization Diseases, an organizational unit affiliated to the Medical Faculty of the University of Leipzig. LIFE is funded by means of the European Union, European Regional Development Fund (ERDF) and by funds of the Free State of Saxony within the framework of the excellence initiative (project numbers 713-241202,

713-241202, 14505/2470, and 14575/2470). We thank all participants and Kerstin Wirkner, Ulrike Scharrer, Katrin Arelin, and everyone involved in MRI data acquisition and analysis.

The Nagahama Prospective Genome Cohort for Comprehensive Human Bioscience is grateful to the Nagahama City Office and the nonprofit organization Zeroji Club for their help in conducting the study. This project is supported by operational funds of Kyoto University and the Top Global University Project of the Ministry of Education, Culture, Sports, Science and Technology (MEXT) in Japan. We also receive Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science and research grants from the Japan Agency for Medical Research and Development for the Practical Research Project for Rare/Intractable Diseases and the Comprehensive Research on Aging and Health Science for Dementia R&D. M.-G.D. received a grant from the Fondation Bettencourt Schueler.

As part of the Poznan MS study, M.A.P. reported receiving grants from the Polish National Science Centre: 2011/01/D/NZ4/05801.

The Rotterdam Study (RS) is funded by Erasmus Medical Center and Erasmus University, Rotterdam; the Netherlands Organization for Health Research and Development (ZonMw); the Research Institute for Diseases in the Elderly (RIDE); the Ministry of Education, Culture and Science; the Ministry for Health, Welfare and Sports; the European Commission (DG XII); and the Municipality of Rotterdam. The authors are grateful to the study participants, the staff from the Rotterdam Study, and the participating general practitioners and pharmacists. The generation and management of GWAS genotype data for the Rotterdam Study (RS I, RS II, and RS III) were executed by the Human Genotyping Facility of the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands. The GWAS datasets are supported by the Netherlands Organisation of Scientific Research NWO Investments (no. 175.010.2005.011, 911-03-012); the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC; the Research Institute for Diseases in the Elderly (014-93-015; RIDE2); the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO); and Netherlands Consortium for Healthy Aging (NCHA) project no. 050-060-810. We thank Pascal Arp, Mila Jhamai, Marijn Verkerk, Lizbeth Herrera, Marjolein Peters, and Carolina Medina-Gomez for their help in creating the GWAS database and Karol Estrada, Yurii Aulchenko, and Carolina Medina-Gomez for the creation and analysis of imputed data. H.H.H.A. is supported by ZonMw grant number 916.19.151.

Study of Health in Pomerania - TREND (SHIP-TREND) is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grant nos. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs, and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. MRI scans and genome-wide SNP typing in SHIP-TREND have been supported by a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. The University of Greifswald is a member of the Caché Campus program of the InterSystems GmbH.

The Canadian Institutes of Health Research and the Heart and Stroke Foundation of Canada fund the Saguenay Youth Study (SYS). Computations were performed on the GPC supercomputer at the SciNet HPC Consortium. SciNet is funded by the Canada Foundation for Innovation under the auspices of Compute Canada, the Government of Ontario, Ontario Research Fund - Research Excellence, and the University of Toronto.

This research has been conducted using the UK Biobank Resource under application number 23509.

Vitamin D Intervention in Infants (VIDI) is supported by the Finnish Medical Foundation, the Academy of Finland, the Sigrid Jusélius Foundation, the Swedish Research Council, the Novo Nordisk Foundation, Finska Läkaresällskapet, and the Folkhälsan Research Foundation. We want to thank Dr. Helena Hauta-alus, Dr. Elisa Holmlund-Suila, Dr. Saara Valkama, and Dr. Jenni Rosendahl for their contribution in acquiring the data.

## AUTHOR CONTRIBUTIONS

Performed statistical analysis: M.J.K., R.A.P., T.E.E., C.L.S., A.M., S.v.d.A., M.-G.D., X.J., I.C.H., S. Lamballais, M.A.P., C.E.L., A.C.-C., T.G.M.v.E., C.S.R., J.S., M. Scholz, A.K., G.H.Y.L., R.A., J.R.A., F.-C.H., A.R.A., M.L., A.
Tsuchida, M.W.A.T., N.A., Y.P., D.L., M. Sargurupremraj, F.B., R.N.B., S. Dal-vie, M.J.G., S.H., N.J., Y.K., A.R.K., S. Li, K.L., S.E.M., S.N., N.D.P., Y.Q., W.R.R., G.V.R., S.Y.S., W.V.W., K.W., M.J.C., C.-L.C., and H.H.H.A. Acquired data: T.E.E., I.C.H., D.H.K.v.D.-N., M.A.P., T.G.M.v.E., A.K.H., A.S.B., F.B., J.C.B., D.B., R.N.B., R.B., S. Caspers, G.C., C.A.M.C., J.-F.D., C.D., M.E.-C., J.M.F., B.F., B.I.F., N.F., C.H., P.H., G.H., M.K.I., C.R.J., C.J., Y.K., A.R.K., W.T.L., F. Macciardi, O.M., B.M., S.E.M., S. Miyamoto, S. Moebus, T.H.M., R.M., T.W.M., M.N., Z.P., A.P., R.S., P.J.S., K. Setoh, S. Sidney, B.S.P., J.L.S., Y.T., A. Teumer, A.U., Av.d.L., M.W.V., D.J.W., B.G.W., A.V.W., Q.Y., K.Y., H.G.B., Q.L.G., K. Sim, D.J.S., D.W.B., M.J.C., A.R.H., S.A., A.V., T.P., S. Cichon, V.D.C., F.C., L.J.L., T.W., P.J.K., H.H., M.F., F. Matsuda, H.J.G., M.A.I., S. Debette, P.M.T., S. Seshadri, and H.H.H.A. Drafted the manuscript: M.J.K., R.A.P., and H.H.H.A. Revised the manuscript for important intellectual content: M.J.K., R.A.P., T.E.E., C.L.S., A.M., S.v.d.A., M.-G.D., X.J., I.C.H., D.H.K.v.D.-N., S. Lamballais, M.A.P., C.E.L., A.C.-C., T.G.M.v.E., C.S.R., J.S., M. Scholz, A.K.H., A.K., G.H.Y.L., R.A., J.R.A., F.-C.H., A.R.A., M.L., A. Tsuchida, M.W.A.T., N.A., Y.P., D.L., M. Sarguru-premraj, A.S.B., F.B., J.C.B., D.B., R.N.B., R.B., S. Caspers, G.C., C.A.M.C., S. Dalvie, J.-F.D., C.D., M.E.-C., J.M.F., B.F., B.I.F., N.F., M.J.G., S.H., C.H., P.H., G.H., M.K.I., C.R.J., N.J., C.J., Y.K., A.R.K., S. Li, K.L., W.T.L., F. Macciardi, O.M., B.M., S.E.M., S. Miyamoto, S. Moebus, T.H.M., R.M., T.W.M., M.N., S.N., N.D.P., Z.P., A.P., Y.Q., W.R.R., G.V.R., R.S., P.J.S., K. Setoh, C.Y.S., S. Seshadri, B.S.P., J.L.S., Y.T., A. Teumer, A.U., Av.d.L., M.W.V., D.J.W., B.G.W., A.V.W., K.W., Q.Y., K.Y., H.G.B., Q.L.G., K. Sim, D.J.S., D.W.B., M.J.C., A.R.H., C.-L.C., S.A., A.V., T.P., S. Cichon, V.D.C., F.C., L.J.L., T.W., P.J.K., H.H., M.F., F. Matsuda, H.J.G., M.A.I., S. Debette, P.M.T., S. Seshadri, and H.H.H.A.

## DECLARATION OF INTERESTS

H.H. and I.C.H. received funding from Alzheimer's Research UK and the Dunhill Medical Trust Foundation. M.A.P. reported receiving grants and personal and travel fees from Roche, Novartis, Merck, and Biogen outside the submitted work. M. Scholz receives funding from Pfizer Inc. for a project not related to this research. C.D. serves as a consultant of Novartis Pharmaceuticals. B.F. has received educational speaking fees from Medice. N.J. and P.M.T. are MPIs of a research grant from Biogen Inc. for work unrelated to the contents of this manuscript. D.J.W. received funding from the Stroke Foundation/British Heart Foundation. D.J.S. has received consultancy honoraria from Discovery Vitality, Johnson & Johnson, Kanna, L'Oreal, Lundbeck, Orion, Sanofi, Servier, Takeda, and Vistagen. H.H. received funding from MRC, Wellcome Trust, and NIHR UCLH BRC. H.J.G. has received travel grants and speaker's honoraria from Fresenius Medical Care, Neuraxpharm, and Janssen Cilag as well as research funding from Fresenius Medical Care.

Received: November 30, 2021

Revised: September 18, 2023

Accepted: April 4, 2024

Published: May 3, 2024

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9. Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y., and Morishima, K. (2017). KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 45, D353-D361.

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13. Stecca, B., and Ruiz i Altaba, A. (2009). A GLI1-p53 inhibitory loop controls neural stem cell and tumour cell numbers. EMBO J. 28, 663-676. https://doi.org/10.1038/emboj.2009.16.

14. Inestrosa, N.C., and Varela-Nallar, L. (2015). Wnt signalling in neuronal differentiation and development. Cell Tissue Res. 359, 215-223. https://doi.org/10.1007/s00441-014-1996-4.

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18. Wasserman, J.D., Tomlinson, G.E., Druker, H., Kamihara, J., Kohlmann, W.K., Kratz, C.P., Nathanson, K.L., Pajtler, K.W., Parareda, A., Rednam, S.P., et al. (2017). Multiple Endocrine Neoplasia and Hyperparathyroid-Jaw Tumor Syndromes: Clinical Features, Genetics, and Surveillance Recommendations in Childhood. Clin. Cancer Res. 23, e123-e132.

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20. Davies, M.A., Stemke-Hale, K., Tellez, C., Calderone, T.L., Deng, W., Prieto, V.G., Lazar, A.J.F., Gershenwald, J.E., and Mills, G.B. (2008). A novel AKT3 mutation in melanoma tumours and cell lines. Br. J. Cancer 99, 1265-1268.

21. Mei, L., and Nave, K.A. (2014). Neuregulin-ERBB signaling in the nervous system and neuropsychiatric diseases. Neuron 83, 27-49.
Tsuchida, M.W.A.T., N.A., Y.P., D.L., M. Sargurupremraj, F.B., R.N.B., S. Dal-vie, M.J.G., S.H., N.J., Y.K., A.R.K., S. Li, K.L., S.E.M., S.N., N.D.P., Y.Q., W.R.R., G.V.R., S.Y.S., W.V.W., K.W., M.J.C., C.-L.C., and H.H.H.A. Acquired data: T.E.E., I.C.H., D.H.K.v.D.-N., M.A.P., T.G.M.v.E., A.K.H., A.S.B., F.B., J.C.B., D.B., R.N.B., R.B., S. Caspers, G.C., C.A.M.C., J.-F.D., C.D., M.E.-C., J.M.F., B.F., B.I.F., N.F., C.H., P.H., G.H., M.K.I., C.R.J., C.J., Y.K., A.R.K., W.T.L., F. Macciardi, O.M., B.M., S.E.M., S. Miyamoto, S. Moebus, T.H.M., R.M., T.W.M., M.N., Z.P., A.P., R.S., P.J.S., K. Setoh, S. Sidney, B.S.P., J.L.S., Y.T., A. Teumer, A.U., Av.d.L., M.W.V., D.J.W., B.G.W., A.V.W., Q.Y., K.Y., H.G.B., Q.L.G., K. Sim, D.J.S., D.W.B., M.J.C., A.R.H., S.A., A.V., T.P., S. Cichon, V.D.C., F.C., L.J.L., T.W., P.J.K., H.H., M.F., F. Matsuda, H.J.G., M.A.I., S. Debette, P.M.T., S. Seshadri, and H.H.H.A. Drafted the manuscript: M.J.K., R.A.P., and H.H.H.A. Revised the manuscript for important intellectual content: M.J.K., R.A.P., T.E.E., C.L.S., A.M., S.v.d.A., M.-G.D., X.J., I.C.H., D.H.K.v.D.-N., S. Lamballais, M.A.P., C.E.L., A.C.-C., T.G.M.v.E., C.S.R., J.S., M. Scholz, A.K.H., A.K., G.H.Y.L., R.A., J.R.A., F.-C.H., A.R.A., M.L., A. Tsuchida, M.W.A.T., N.A., Y.P., D.L., M. Sargurupremraj, A.S.B., F.B., J.C.B., D.B., R.N.B., R.B., S. Caspers, G.C., C.A.M.C., S. Dalvie, J.-F.D., C.D., M.E.-C., J.M.F., B.F., B.I.F., N.F., M.J.G., S.H., C.H., P.H., G.H., M.K.I., C.R.J., N.J., C.J., Y.K., A.R.K., S. Li, K.L., W.T.L., F. Macciardi, O.M., B.M., S.E.M., S. Miyamoto, S. Moebus, T.H.M., R.M., T.W.M., M.N., S.N., N.D.P., Z.P., A.P., Y.Q., W.R.R., G.V.R., R.S., P.J.S., K. Setoh, C.Y.S., S. Seshadri, B.S.P., J.L.S., Y.T., A. Teumer, A.U., Av.d.L., M.W.V., D.J.W., B.G.W., A.V.W., K.W., Q.Y., K.Y., H.G.B., Q.L.G., K. Sim, D.J.S., D.W.B., M.J.C., A.R.H., C.-L.C., S.A., A.V., T.P., S. Cichon, V.D.C., F.C., L.J.L., T.W., P.J.K., H.H., M.F., F. Matsuda, H.J.G., M.A.I., S. Debette, P.M.T., S. Seshadri, and H.H.H.A.

## DECLARATION OF INTERESTS

H.H. and I.C.H. received funding from Alzheimer's Research UK and the Dunhill Medical Trust Foundation. M.A.P. reported receiving grants and personal and travel fees from Roche, Novartis, Merck, and Biogen outside the submitted work. M. Scholz receives funding from Pfizer Inc. for a project not related to this research. C.D. serves as a consultant of Novartis Pharmaceuticals. B.F. has received educational speaking fees from Medice. N.J. and P.M.T. are MPIs of a research grant from Biogen Inc. for work unrelated to the contents of this manuscript. D.J.W. received funding from the Stroke Foundation/British Heart Foundation. D.J.S. has received consultancy honoraria from Discovery Vitality, Johnson & Johnson, Kanna, L'Oreal, Lundbeck, Orion, Sanofi, Servier, Takeda, and Vistagen. H.H. received funding from MRC, Wellcome Trust, and NIHR UCLH BRC. H.J.G. has received travel grants and speaker's honoraria from Fresenius Medical Care, Neuraxpharm, and Janssen Cilag as well as research funding from Fresenius Medical Care.

Received: November 30, 2021

Revised: September 18, 2023

Accepted: April 4, 2024

Published: May 3, 2024

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## STAR★METHODS

### KEY RESOURCES TABLE

<table><thead><tr><th>REAGENT or RESOURCE</th><th>SOURCE</th><th>IDENTIFIER</th></tr></thead><tbody><tr><td colspan="3">Deposited data</td></tr><tr><td>Genome-wide association study summary statistics</td><td>CHARGE dbGaP and <a href="http://enigma.ini.usc.edu/research/download-enigma-gwas-results">http://enigma.ini.usc.edu/research/download-enigma-gwas-results</a></td><td>phs000930 (dbGaP accession number)</td></tr><tr><td colspan="3">Software and algorithms</td></tr><tr><td>EasyQC</td><td>Winkler et al.<sup>51</sup></td><td>Software - Universität Regensburg (uni-regensburg.de)</td></tr><tr><td>METAL</td><td>Willer et al.<sup>52</sup></td><td>METAL Documentation - Genome Analysis Wiki (umich.edu)</td></tr><tr><td>LD score regression</td><td>Bulik-Sullivan et al.<sup>53</sup></td><td>GitHub - bulik/ldsc: LD Score Regression (LDSC)</td></tr><tr><td>LocusZoom</td><td>Pruim et al.<sup>54</sup></td><td>LocusZoom - Create Plots of Genetic Data</td></tr><tr><td>FUMA GWAS</td><td>Watanabe et al.<sup>55</sup></td><td>Functional Mapping and Annotation of Genome-wide association studies (ctglab.nl)</td></tr><tr><td>TWAS-Fusion</td><td>Gusev et al.<sup>56</sup></td><td>TWAS/FUSION (gusevlab.org)</td></tr><tr><td>DOMINO</td><td>Quinodoz et al.<sup>57</sup></td><td>Domino (iob.ch)</td></tr><tr><td colspan="3">Other</td></tr><tr><td>OMIM database</td><td>Amberger et al.<sup>58</sup></td><td>Home - OMIM</td></tr><tr><td>Cortical organoids' scRNA-seq data</td><td>Bhaduri et al.<sup>34</sup></td><td><a href="https://organoidreportcard cells.ucsc.edu">https://organoidreportcard cells.ucsc.edu</a></td></tr><tr><td>e/sQTLs, and allele-specific expression in cultured primary human neural progenitors and their sorted neuronal progeny</td><td>Aygün et al.<sup>32</sup></td><td><a href="https://bitbucket.org/steinlabunc/expression_splicing_qtls_public/src/master/">https://bitbucket.org/steinlabunc/expression_splicing_qtls_public/src/master/</a></td></tr></tbody></table>

### RESOURCE AVAILABILITY

#### Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Hieab H.H. Adams (Hieab.Adams@radboudumc.nl).

#### Materials availability

This study did not generate new unique reagents.

#### Data and code availability

The genome-wide summary statistics that support the findings of this study will be made available through the CHARGE dbGaP (accession number phs000930) and ENIGMA (http://enigma.ini.usc.edu/research/download-enigma-gwas-results) websites.

No previously unreported custom computer code or mathematical algorithm was used to generate results central to the conclusions.

Any additional information required to re-analyse the data reported in this work paper is available from the lead contact upon request.

### EXPERIMENTAL MODEL AND SUBJECT DETAILS

#### Study population

Most studies participate in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)⁵⁹ or the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA)⁶⁰ consortium. We also included the results of the most recent head
## STAR★METHODS

### KEY RESOURCES TABLE

<table><thead><tr><th>REAGENT or RESOURCE</th><th>SOURCE</th><th>IDENTIFIER</th></tr></thead><tbody><tr><td colspan="3">Deposited data</td></tr><tr><td>Genome-wide association study summary statistics</td><td>CHARGE dbGaP and <a href="http://enigma.ini.usc.edu/research/download-enigma-gwas-results">http://enigma.ini.usc.edu/research/download-enigma-gwas-results</a></td><td>phs000930 (dbGaP accession number)</td></tr><tr><td colspan="3">Software and algorithms</td></tr><tr><td>EasyQC</td><td>Winkler et al.<sup>51</sup></td><td>Software - Universität Regensburg (uni-regensburg.de)</td></tr><tr><td>METAL</td><td>Willer et al.<sup>52</sup></td><td>METAL Documentation - Genome Analysis Wiki (umich.edu)</td></tr><tr><td>LD score regression</td><td>Bulik-Sullivan et al.<sup>53</sup></td><td>GitHub - bulik/ldsc: LD Score Regression (LDSC)</td></tr><tr><td>LocusZoom</td><td>Pruim et al.<sup>54</sup></td><td>LocusZoom - Create Plots of Genetic Data</td></tr><tr><td>FUMA GWAS</td><td>Watanabe et al.<sup>55</sup></td><td>Functional Mapping and Annotation of Genome-wide association studies (ctglab.nl)</td></tr><tr><td>TWAS-Fusion</td><td>Gusev et al.<sup>56</sup></td><td>TWAS/FUSION (gusevlab.org)</td></tr><tr><td>DOMINO</td><td>Quinodoz et al.<sup>57</sup></td><td>Domino (iob.ch)</td></tr><tr><td colspan="3">Other</td></tr><tr><td>OMIM database</td><td>Amberger et al.<sup>58</sup></td><td>Home - OMIM</td></tr><tr><td>Cortical organoids' scRNA-seq data</td><td>Bhaduri et al.<sup>34</sup></td><td><a href="https://organoidreportcard cells.ucsc.edu">https://organoidreportcard cells.ucsc.edu</a></td></tr><tr><td>e/sQTLs, and allele-specific expression in cultured primary human neural progenitors and their sorted neuronal progeny</td><td>Aygün et al.<sup>32</sup></td><td><a href="https://bitbucket.org/steinlabunc/expression_splicing_qtls_public/src/master/">https://bitbucket.org/steinlabunc/expression_splicing_qtls_public/src/master/</a></td></tr></tbody></table>

### RESOURCE AVAILABILITY

#### Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Hieab H.H. Adams (Hieab.Adams@radboudumc.nl).

#### Materials availability

This study did not generate new unique reagents.

#### Data and code availability

The genome-wide summary statistics that support the findings of this study will be made available through the CHARGE dbGaP (accession number phs000930) and ENIGMA (http://enigma.ini.usc.edu/research/download-enigma-gwas-results) websites.

No previously unreported custom computer code or mathematical algorithm was used to generate results central to the conclusions.

Any additional information required to re-analyse the data reported in this work paper is available from the lead contact upon request.

### EXPERIMENTAL MODEL AND SUBJECT DETAILS

#### Study population

Most studies participate in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)⁵⁹ or the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA)⁶⁰ consortium. We also included the results of the most recent head