Intelligence

Introduction

Intelligence refers to the general mental capacity to reason, solve problems, plan, think abstractly, comprehend complex ideas, learn quickly, and learn from experience. It encompasses a broad range of cognitive abilities that allow individuals to adapt to new situations and acquire knowledge.

Biological Basis

The biological underpinnings of intelligence involve intricate interactions across various brain regions, particularly those associated with executive functions, memory, and information processing, such as the prefrontal cortex, parietal lobe, and hippocampus. Neurological research suggests that intelligence is linked to brain structure, functional connectivity, and the efficiency of neural networks. Genetically, intelligence is a highly polygenic trait, meaning it is influenced by a multitude of genes, each contributing a small effect. Single nucleotide polymorphisms (SNPs) are common genetic variations that contribute to this genetic architecture, with numerous SNPs across the human genome being associated with variations in cognitive abilities.

Clinical Relevance

Understanding intelligence is critical in clinical settings for diagnosing and managing a wide spectrum of conditions. Cognitive assessments are fundamental for identifying intellectual disabilities, neurodevelopmental disorders, and cognitive decline associated with aging or neurodegenerative diseases. For instance, research often classifies individuals as cognitively impaired or unimpaired based on cognitive scores, highlighting the utility of measuring intelligence in health studies.^[1]Conditions such as ischaemic stroke and Alzheimer’s disease can also lead to cognitive impairment, emphasizing the importance of understanding the genetic and biological factors that contribute to cognitive health and disease.^[2]

Social Importance

Intelligence plays a significant role in individual development and societal progress. It influences educational attainment, occupational success, and overall well-being. From a societal perspective, insight into the factors contributing to intelligence can inform educational strategies, public health initiatives, and interventions aimed at supporting cognitive development and mitigating cognitive decline throughout the lifespan. Research into the genetic and environmental determinants of intelligence helps elucidate individual differences and can guide efforts to foster cognitive potential across diverse populations.

Generalizability and Phenotypic Heterogeneity

The findings regarding intelligence are largely derived from studies focusing on populations of European descent, limiting their direct generalizability to individuals from diverse genetic backgrounds ;.^[3] Maintaining genomic stability and proper gene expression is vital for sustained brain function and cognitive health. Variants rs9401452 , rs10872224 , and rs6928583 are located in the vicinity of _MMS22L_ and _MIR2113_. _MMS22L_ is a protein involved in DNA repair pathways, critical for protecting neurons from damage and preserving genetic information over time. _MIR2113_is a microRNA that can regulate gene expression, impacting various cellular processes. Variations here could affect the efficiency of DNA repair or the fine-tuning of gene regulation, potentially influencing neuronal resilience and susceptibility to cognitive decline. Another gene,_TRAIP_, involved in DNA damage response and protein ubiquitination, includes variants rs2352974 , rs10865959 , and rs59357103 . These genetic differences may alter the cell’s ability to repair DNA or manage protein degradation, both of which are crucial for normal brain development and the maintenance of cognitive abilities throughout life.^{[4], [5]}The single nucleotide polymorphismrs2013208 , found near _RBM6_ and _RBM5_, genes encoding RNA binding motif proteins, might influence RNA splicing and processing. These proteins are key players in regulating which versions of proteins are made from a gene, thereby affecting neuronal development and function.

Cellular signaling, lipid metabolism, and stress responses are also important for brain health. The variants rs2008514 , rs28888764 , and rs28472312 are found in the region of _PLA2G10KP_ and _ATXN2L_. While _PLA2G10KP_ is a pseudogene, _ATXN2L_ is an RNA-binding protein involved in the formation of stress granules, which are protective cellular structures that form under stress to help cells survive. These variants could influence how neurons respond to stress or manage RNA, which can impact their overall health and cognitive performance. Similarly, _IP6K1_(Inositol Hexakisphosphate Kinase 1) is associated with variantsrs7618519 , rs7618501 , and rs115770773 . _IP6K1_plays a role in inositol phosphate signaling, a pathway involved in a wide array of cellular functions, including neurotransmission, synaptic plasticity, and energy metabolism. Genetic variations here may affect the efficiency of these signaling cascades, potentially influencing learning, memory, and overall cognitive flexibility.^{[3], [4]} Epigenetic modifications and transcriptional regulation are fundamental to brain development and function. Variants rs11793831 , rs10733389 , and rs17836155 are located near _LINC01239_ and _SUMO2P2_. _LINC01239_ is a long non-coding RNA, often involved in regulating gene expression, which can influence neuronal differentiation and connectivity. These variants may impact the regulatory landscape of the genome, thereby affecting neural circuitry and cognitive capacity. Furthermore, _TET2-AS1_, an antisense RNA, is linked to variants rs2726491 , rs2726513 , and rs2101975 . _TET2-AS1_ can modulate the activity of the _TET2_ gene, a critical enzyme involved in DNA demethylation, a key epigenetic process that controls gene activity in the brain. Alterations in these variants could lead to changes in epigenetic marks, affecting neuronal plasticity and learning. Finally, variants rs9384679 , rs768023 , and rs9480861 are associated with the _AFG1L_ and _FOXO3_ genes. _FOXO3_ is a well-known transcription factor that regulates genes involved in stress resistance, metabolism, and cell longevity, including neuronal survival and maintenance. These genetic differences might influence _FOXO3_activity, impacting neuronal resilience to stress and contributing to individual variations in cognitive aging and overall intelligence.^{[3], [5]}

Conceptual Frameworks and Definitions of Intelligence

Intelligence is broadly understood as a multifaceted cognitive predictor, characterized by an individual’s general cognitive ability.^[6]Conceptually, it is often framed around a general intelligence factor, or ‘g’, which represents a common underlying cognitive capacity, alongside more specific abilities like fluid intelligence.^[7]Fluid intelligence, a primary measure in some studies, refers to the ability to reason and solve novel problems independently of acquired knowledge. Operationally, intelligence is defined by performance on standardized psychometric assessments designed to capture these diverse cognitive functions. This cognitive trait is recognized as highly heritable and polygenic, indicating that it is influenced by numerous genetic variants.^[8]

Psychometric Assessment and Standardized

The assessment of intelligence primarily relies on comprehensive psychometric tests, which provide operational definitions through their structured approaches. Widely used standardized instruments include the Wechsler Intelligence Scale for Children (WISC, WISC-R, WISC-III, WISC-IV, WISC-V), the Wechsler Adult Intelligence Scale (WAIS, WAIS-R), and the Wechsler Preschool and Primary Scale of Intelligence (WPPSI).^[9] Other established scales like the British Ability Scales and the Woodcock-Johnson III Tests of Cognitive Abilities are also employed.^[10]These tests yield a Full Scale Intelligence Quotient (FSIQ), a key diagnostic criterion, often derived from a composite of various subtest scores, such as those from the North American Adult Reading Test.^[11] Beyond global IQ scores, specific cognitive domains are assessed through tasks measuring working memory (e.g., N-back, Counting Span), processing speed (e.g., Digit Vigilance, Simple and Choice Reaction Time, Sky Search), and inhibitory control (e.g., Stop Signal task).^[7] Research criteria also encompass traits like reading single words, spelling, nonword reading, phoneme manipulation, digit recall (forward and backward), and naming speed for digits, letters, or objects.^[6]These measures are often age-adjusted, standardized, or rank-normalized to account for population variability, and while the concept of “cognitive impairment” implies a threshold below typical functioning, precise universal cut-off values are typically context-dependent.^[6]

Classification of Cognitive Abilities and Clinical Significance

Intelligence is commonly classified into specific abilities, such as general intelligence (‘g’) and fluid intelligence, reflecting a dimensional approach to understanding cognitive function.^[7] Beyond these overarching constructs, related cognitive traits like working memory (WM), processing speed (PS), and inhibitory control (IC) are frequently studied as distinct yet interconnected components of overall cognitive ability.^[7]The nomenclature used in research and clinical contexts distinguishes between lifespan intelligence and child intelligence, acknowledging developmental aspects.^[7]The clinical and scientific significance of intelligence is profound, as it serves as a cognitive predictor for conditions such as dyslexia.^[6]Furthermore, intellectual functioning in childhood has been identified as inversely associated with the risk of cognitive decline later in life, highlighting its long-term health implications.^[12]

Genetic Foundations of Cognitive Abilities

Human intelligence is a highly heritable and complex trait, with a substantial portion of individual differences attributable to genetic factors.^[8]Research, particularly genome-wide association studies (GWAS), reveals that intelligence is massively polygenic, meaning it is influenced by a large number of genes, each contributing a small effect.^[13]These studies have identified hundreds of genetic loci associated with general cognitive function and fluid intelligence, highlighting a complex interplay of genetic mechanisms that underpin cognitive abilities.^[14] Specific genes and regulatory elements play roles in various cognitive domains. For instance, the CADM2gene has been implicated in executive function and processing speed, two cognitive components strongly linked to intelligence.^[15] Other genetic regions, such as SEMA3B-AS1, RNASEK-C17orf49, and STAG3L5P-PVRIG2P-PILRB, are associated with various cognitive domains, including reasoning and problem-solving, suggesting that gene expression patterns and their regulatory networks are crucial for optimal cognitive performance.^[16]The cumulative effect of these genetic variations, along with epigenetic modifications influencing gene expression, shapes the intricate biological architecture of intelligence.

Neural Development and Structural Plasticity

The development and plasticity of the central nervous system are fundamental biological underpinnings of intelligence. Key cellular functions such as neurogenesis, the birth of new neurons, and myelination, the formation of the insulating myelin sheath around nerve fibers, are critical processes identified as having a role in intelligence.^[14] These developmental processes contribute to the efficiency and speed of neural communication, which are essential for complex cognitive functions like processing speed and working memory.^[17] At the tissue and organ level, the cerebral cortex, the brain’s outer layer, undergoes significant global and regional development that is associated with general learning ability.^[18]The intricate structural components within the brain, including neuronal networks and glial cells, are shaped by these molecular and cellular pathways throughout life. This ongoing structural plasticity allows the brain to adapt and refine its processing capabilities, supporting the continuous development of cognitive functions such as executive function, which shows age-related changes across the lifespan.^[19]

Molecular and Cellular Mechanisms of Brain Function

Intelligence relies on complex molecular and cellular pathways that facilitate efficient information processing within the brain. Critical proteins, enzymes, and receptors are involved in neurotransmission and synaptic plasticity, which are the basis for learning and memory. Although not explicitly detailed for intelligence in all contexts, the involvement of specific genes likeCADM2in processing speed and executive function implies the action of biomolecules that mediate cell adhesion and signaling pathways, crucial for neuronal connectivity and information flow.^[15]These intricate regulatory networks involve transcription factors and other key biomolecules that control gene expression, influencing the development and maintenance of neural circuits. Metabolic processes provide the necessary energy for these highly active brain cells, ensuring the sustained functioning of cognitive processes. The efficiency of these molecular and cellular functions collectively contributes to overall cognitive performance, enabling abilities like fluid intelligence and complex reasoning.^[20]

Pathophysiological Influences on Cognitive Function

Various pathophysiological processes can disrupt the homeostatic balance of the brain and negatively impact cognitive function, thereby affecting intelligence. Developmental processes are particularly sensitive to such disruptions; for instance, craniospinal irradiation, a treatment for pediatric central nervous system tumors, is known to cause cognitive decline, demonstrating how external interventions can interfere with the brain’s normal development and function.^[12]Disease mechanisms also play a significant role in cognitive impairment. Genes likeNDST3, for example, are implicated in psychiatric disorders such as schizophrenia and bipolar disorder.^[21]These disorders often present with significant cognitive domain deficits, including impairments in reasoning, problem-solving, and executive functions, highlighting the systemic consequences of disrupted neural pathways on intelligence.^[16] Understanding these mechanisms is crucial for identifying compensatory responses and potential interventions to preserve or enhance cognitive abilities.

Neuronal Development and Structural Plasticity

Intelligence relies fundamentally on the precise development and dynamic structural adaptations of the nervous system, orchestrated by intricate molecular pathways. Neurogenesis, the birth of new neurons, and myelination, the formation of insulating myelin sheaths around axons, are critical processes identified as playing roles in intelligence.^[7] These developmental events are tightly regulated by signaling cascades that dictate cell proliferation, differentiation, migration, and survival, ultimately shaping brain architecture and optimizing signal transmission speed. For instance, the process of axon guidance, which directs neuronal connections, is a key pathway influencing neural network formation and efficiency.^[22] Furthermore, the proper formation of primary cilia, involving proteins like intraflagellar transport protein 172, is essential for patterning the mammalian brain, highlighting the role of these cellular antennae in developmental signaling that underpins cognitive capacity.^[23]

Intracellular Signaling and Synaptic Function

The ability of neurons to communicate and adapt underlies all cognitive functions, driven by complex intracellular signaling networks. Key pathways such as the mTOR signaling pathway and Ephrin receptor signaling are implicated in memory performance, a core component of intelligence.^[22] The mTOR pathway integrates nutrient and growth factor signals to regulate cell growth, proliferation, and protein synthesis, all vital for synaptic plasticity and long-term potentiation. Similarly, Ephrin receptors and their ligands mediate cell-cell communication crucial for axon guidance, synapse formation, and dendritic spine remodeling. Additionally, presenilins are known to mediate the activation of phosphatidylinositol 3-kinase/AKT and ERK pathways via specific signaling receptors, underscoring the broad involvement of these ubiquitous cascades in cellular responses critical for neuronal health and function.^[24]

Metabolic Homeostasis and Energetic Support

The brain is an exceptionally energy-demanding organ, and efficient metabolic regulation is paramount for sustained cognitive function. Pathways involved in energy metabolism, such as those regulated by glucokinase, are crucial for glucose utilization, the brain’s primary fuel.^[23]Glucokinase’s role in glucose phosphorylation directly impacts metabolic flux and ATP production, which is essential for maintaining neuronal excitability and synaptic transmission. Another critical regulator is AMP-activated protein kinase (AMPK), which acts as a cellular energy sensor; its activation promotes catabolic processes to generate ATP while inhibiting anabolic pathways, ensuring energy balance under varying conditions.^[23] Furthermore, the regulation of autophagy, a cellular recycling process, contributes to neuronal health by clearing damaged organelles and proteins, which is vital for maintaining cellular integrity and preventing metabolic stress that could impair cognitive performance.^[22]

Gene Expression and Post-Translational Control

The dynamic regulation of gene expression and protein activity is fundamental to neuronal adaptability and cognitive processing. Mechanisms governing mRNA end processing and stability directly influence the repertoire and abundance of proteins available for synaptic function and structural maintenance.^[22]These regulatory steps determine how genetic information is translated into functional cellular components, affecting everything from neurotransmitter synthesis to receptor trafficking. Beyond gene expression, post-translational modifications, such as phosphorylation, ubiquitination, and acetylation, provide rapid and reversible control over protein activity, localization, and interactions. This intricate layer of regulation allows neurons to fine-tune their responses to environmental stimuli, adapt synaptic strength, and consolidate memories, contributing to the flexibility and efficiency characteristic of higher intelligence.

Systems-Level Integration and Cognitive Resilience

Intelligence emerges from the complex interplay and integration of numerous molecular pathways across various cellular systems. This systems-level integration involves extensive pathway crosstalk and hierarchical regulation, where the output of one pathway can modulate or be modulated by others, leading to emergent properties at the neural network level. For example, genetic studies have identified loci, including theCADM2gene, associated with executive function and processing speed, highlighting how specific genetic variations can influence these integrated cognitive abilities.^[15] Dysregulation within these pathways can lead to cognitive impairments; for instance, GAB2 alleles modify Alzheimer’s risk in APOEepsilon4 carriers, demonstrating how genetic interactions within complex networks contribute to disease susceptibility and affect cognitive resilience.^[24]Understanding these integrated mechanisms and their potential dysregulation offers promising avenues for identifying therapeutic targets to enhance cognitive function or mitigate decline.

Large-scale Cohort Studies and Longitudinal Patterns

Population-level studies of intelligence leverage extensive cohorts to understand its genetic and environmental underpinnings across the lifespan. Research on lifespan intelligence has involved 78,308 individuals from 13 distinct cohorts of European descent, encompassing both children under 18 years (N = 19,509) and adults aged 18–78 years (N = 58,799).^[7]These studies typically measure general intelligence (g) or primary fluid intelligence, with a specific child-only subsample (6–18 years) of 17,989 individuals also contributing to insights into childhood intelligence.^[7]Beyond direct intelligence measures, large-scale genome-wide association studies (GWAS) have also explored related traits like educational attainment, including years spent in education (N discovery = 293,723; N replication = 405,072) and college completion, providing robust data on socioeconomic correlates of cognitive function.^[7]Further longitudinal insights come from cohorts such as the Lothian Birth Cohorts (LBC1921 and LBC1936) in Scotland, comprising relatively healthy individuals assessed on cognitive and medical traits at mean ages of 79.1 and 69.6 years, respectively.^[25]These cohorts, predominantly Caucasian and living independently, offer valuable data on intelligence trajectories in aging populations.^[25]Other large cohorts like the Health and Retirement Study (HRS), ARIC, MESA, FHS, and CHS contribute to this understanding, with thousands of participants providing DNA and biomarker samples and undergoing multiple follow-up examinations over many years, allowing for the analysis of intelligence and its decline over time.^[1]Such extensive datasets are critical for identifying temporal patterns and the genetic architecture of intelligence through advanced genotyping and imputation methodologies.^[26]

Cross-Population Comparisons and Genetic Ancestry

Many large-scale genetic studies on intelligence and related cognitive measures have predominantly focused on populations of European descent. For instance, studies on lifespan intelligence, childhood intelligence, and educational attainment consistently include individuals primarily of European ancestry.^[7]This focus is further exemplified in research on cognitive decline in pediatric central nervous system tumor patients, where participants were classified by genetic ancestry, distinguishing between individuals of predominantly European ancestry (≥80%) for discovery and those of other ancestries for replication.^[12] Despite differences in genetic ancestry, demographic and clinical characteristics were often found to be comparable between these discovery and replication subsets, allowing for robust cross-ancestry analyses.^[12] Methodological approaches for addressing genetic ancestry in population studies include the use of principal components analysis to account for population stratification in statistical models.^[27] This helps to mitigate spurious associations that might arise from underlying population structure. However, some studies may apply stringent cohort filtering based on self-described ethnicity, such as excluding children not of ‘white’ ethnicity or those with a PIQ score below 80, which can influence the generalizability of findings to broader, more diverse populations.^[28]The careful consideration and explicit reporting of genetic ancestry are essential for understanding the universality or population-specific effects of genetic variants on intelligence.

Epidemiological Associations and Cognitive Trait

Intelligence is epidemiologically linked to various demographic and socioeconomic factors, with age being a prominent correlate of cognitive function. Research on large samples, such as the Health and Retirement Study, demonstrates a statistically significant age difference, where individuals classified as cognitively impaired have a mean age notably higher than their unimpaired counterparts.^[1]Furthermore, educational attainment, measured by years spent in education or college completion, is frequently used as an indicator strongly associated with intelligence in extensive genetic association studies.^[7] Demographic variables like gender and age are commonly included as fixed effects in statistical models to adjust for their influence on cognitive traits and to prevent confounding in epidemiological analyses.^[27]The assessment of intelligence in population studies employs a variety of standardized measures to capture different cognitive domains. General intelligence (g) and fluid intelligence are common primary measures across lifespan and childhood cohorts.^[7] More granular cognitive components are also assessed, including sustained attention (e.g., Digit Vigilance task), working memory (e.g., N-back, Counting Span, Dual tasks), inhibitory control (e.g., Stop Signal task), and processing speed (e.g., Simple and Choice Reaction Time).^[7]These detailed cognitive measures, often derived from instruments like the Wechsler Intelligence Scale or Woodcock Johnson Tests of Cognitive Abilities, enable comprehensive analysis of intelligence trajectories and specific cognitive deficits in diverse populations, including those with conditions like pediatric central nervous system tumors.^[12]

Key Variants

RS ID	Gene	Related Traits
rs1906252 rs2388334 rs12206087	MIR2113 - EIF4EBP2P3	self reported educational attainment social interaction cognitive function cognitive function , self reported educational attainment household income
rs9401452 rs10872224 rs6928583	MMS22L - MIR2113	intelligence
rs2352974 rs10865959 rs59357103	TRAIP	waist-hip ratio verbal-numerical reasoning cognitive function , self reported educational attainment intelligence cognitive function
rs7623659 rs7650253 rs11716948	RHOA	cognitive function , self reported educational attainment intelligence cognitive function body mass index
rs2008514 rs28888764 rs28472312	PLA2G10KP - ATXN2L	physical activity , body mass index body mass index intelligence
rs11793831 rs10733389 rs17836155	LINC01239 - SUMO2P2	intelligence health study participation verbal-numerical reasoning cognitive function , self reported educational attainment insomnia
rs2726491 rs2726513 rs2101975	TET2-AS1	lean body mass intelligence
rs2013208	RBM6, RBM5	high density lipoprotein cholesterol alcohol consumption quality, high density lipoprotein cholesterol alcohol drinking, high density lipoprotein cholesterol HDL cholesterol change , physical activity intelligence
rs7618519 rs7618501 rs115770773	IP6K1	intelligence
rs9384679 rs768023 rs9480861	AFG1L - FOXO3	intelligence cortical thickness cognitive function verbal-numerical reasoning cognitive function , self reported educational attainment

Frequently Asked Questions About Intelligence

These questions address the most important and specific aspects of intelligence based on current genetic research.

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1. Will my kids be as smart as I am?

Yes, intelligence has a strong genetic component, meaning your children will inherit some predispositions. However, it’s a highly polygenic trait influenced by a multitude of genes, each contributing a small effect. Their unique environment and experiences also play a crucial role in shaping their cognitive development.

2. Does my family background affect my cognitive abilities?

Research on the genetic underpinnings of intelligence has largely focused on individuals of European descent. This means we still need more studies across diverse ethnic groups to fully understand potentially unique genetic contributions and ensure findings are generalizable to everyone.

3. Does everyone’s intelligence decline with age?

While cognitive decline can be associated with aging or neurodegenerative diseases like Alzheimer’s, it’s not a universal experience for everyone. Genetic and environmental factors play a significant role in maintaining cognitive health throughout life, and some cognitive abilities can even improve with age and experience.

4. Can what I do daily make me smarter?

Yes, absolutely! Environmental factors and gene-environment interactions play a substantial role in shaping cognitive development. Engaging in learning, new experiences, and maintaining a healthy lifestyle can support synaptic plasticity and the formation of new memories, which are fundamental processes for learning and general intelligence.

5. Why is learning easy for some but hard for me?

Intelligence is a highly polygenic trait, meaning it’s influenced by a multitude of genes, each contributing a small effect, which leads to individual differences. These genetic predispositions, combined with varying environmental exposures and experiences, explain why learning can feel different for each person.

6. If intelligence is genetic, why isn’t it predictable?

While intelligence has a strong genetic component, the common genetic variants identified so far don’t explain all the differences. A significant portion, known as “missing heritability,” might be due to rarer genetic variants, complex gene-gene interactions, epigenetic factors, and crucial environmental influences that are challenging to comprehensively measure.

7. Can brain games boost my intelligence?

Engaging in mentally stimulating activities can certainly support cognitive function by promoting synaptic plasticity and memory formation. While the direct impact of specific “brain training” apps on general intelligence is debated, consistent learning and new experiences are known to foster overall cognitive development.

8. Could a stroke affect my intelligence permanently?

Yes, conditions such as ischaemic stroke can indeed lead to cognitive impairment, affecting various aspects of intelligence long-term. Understanding the genetic and biological factors contributing to cognitive health is important for managing and potentially mitigating these effects on cognitive function.

9. Do early childhood experiences impact my intelligence?

Absolutely. Environmental factors and gene-environment interactions play a substantial role in shaping cognitive development throughout the lifespan, especially during formative years. Diverse environmental exposures, including educational opportunities and nutrition, significantly influence how your cognitive potential unfolds.

10. What would a DNA test tell me about my intelligence?

Currently, a DNA test can identify some genetic variations associated with intelligence, but it won’t give you a precise “score.” Intelligence is influenced by thousands of genes, each with tiny effects, and many environmental factors. Such tests provide only a partial picture of your genetic predispositions.

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This FAQ was automatically generated based on current genetic research and may be updated as new information becomes available.

Disclaimer: This information is for educational purposes only and should not be used as a substitute for professional medical advice. Always consult with a healthcare provider for personalized medical guidance.

References

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[4] Wilk JB et al. Framingham Heart Study genome-wide association: results for pulmonary function measures. BMC Med Genet. 2007;8 Suppl 1:S8.

[5] Neale BM et al. Meta-analysis of genome-wide association studies of attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry. 2010;49(9):884-897.

[6] Gialluisi, A., et al. “Genome-wide association scan identifies new variants associated with a cognitive predictor of dyslexia.” Transl Psychiatry, 2019.

[7] Donati, G., et al. “Genome-Wide Association Study of Latent Cognitive Measures in Adolescence: Genetic Overlap With Intelligence and Education.”Mind Brain and Education.

[8] Adams HH, et al. “Heritability and Genome-Wide Association Analyses of Human Gait Suggest Contribution of Common Variants.” J Gerontol A Biol Sci Med Sci, 2015.

[9] Wechsler, D. Manual for the Wechsler Intelligence Scale for Children – Revised. The Psychological Corporation, 1974.

[10] Elliot Murray, D. J., and L. S. C. D. Pearson. The British Ability Scales. NFER, 1979.

[11] Potkin, S. G., et al. “A genome-wide association study of schizophrenia using brain activation as a quantitative phenotype.”Schizophrenia Bulletin.

[12] Brown AL, et al. “Genetic susceptibility to cognitive decline following craniospinal irradiation for pediatric central nervous system tumors.”Neuro Oncol, 2023.

[13] Kirkpatrick, R. M., et al. “Results of a “GWAS plus:” General cognitive ability is substantially heritable and massively polygenic.” PLoS One, vol. 9, no. 11, 2013, e112390.

[14] Hill WD, et al. “A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence.”Mol Psychiatry, vol. 24, no. 2, 2019, pp. 169–181.

[15] Ibrahim-Verbaas, C. A., et al. “GWAS for executive function and processing speed suggests involvement of theCADM2 gene.” Molecular Psychiatry, vol. 21, 2016, pp. 189–197.

[16] Nakahara S, et al. “Polygenic risk score, genome-wide association, and gene set analyses of cognitive domain deficits in schizophrenia.”Schizophr Res, 2019.

[17] Kail, R. “Speed of information processing: Developmental change and links to intelligence.”Journal of School Psychology, vol. 38, no. 1, 2000, pp. 51–61.

[18] Shin J, et al. “Global and Regional Development of the Human Cerebral Cortex: Molecular Architecture and Occupational Aptitudes.” Cereb Cortex, 2020.

[19] Huizinga, M., C. V. Dolan, and M. W. van der Molen. “Age-related change in executive function: Developmental trends and a latent variable analysis.”Neuropsychologia, vol. 44, 2006, pp. 2017–2036.

[20] Kievit, R. A., et al. “A watershed model of individual differences in fluid intelligence.”Neuropsychologia, vol. 91, Supplement C, 2016, pp. 186–198.

[21] Lencz T, et al. “Genome-wide association study implicates NDST3in schizophrenia and bipolar disorder.”Nat Commun, 2013.

[22] Zhu, Z., et al. “Multi-level genomic analyses suggest new genetic variants involved in human memory.” Eur J Hum Genet, vol. 26, no. 9, 2018, pp. 1308–1319.

[23] Kottgen, A., et al. “New loci associated with kidney function and chronic kidney disease.”Nat Genet, vol. 42, no. 4, 2010, pp. 370–375.

[24] Reiman, E. M., et al. “GAB2 alleles modify Alzheimer’s risk in APOE epsilon4 carriers.” Neuron, vol. 54, no. 5, 2007, pp. 713–723.

[25] Houlihan, L. M., et al. “Common variants of large effect in F12, KNG1, and HRG are associated with activated partial thromboplastin time.” Am J Hum Genet, vol. 86, no. 4, 2010, pp. 433-441.

[26] He, L., et al. “Pleiotropic Meta-Analyses of Longitudinal Studies Discover Novel Genetic Variants Associated with Age-Related Diseases.” Front Genet, vol. 7, 2016, p. 193.

[27] Yousaf, A., et al. “Quantitative genome-wide association study of six phenotypic subdomains identifies novel genome-wide significant variants in autism spectrum disorder.” Transl Psychiatry, 2020.

[28] Nudel, R., et al. “Genome-wide association analyses of child genotype effects and parent-of-origin effects in specific language impairment.” Genes Brain Behav, vol. 13, no. 4, 2014, pp. 418-429.