Genome-wide association study of cognitive functions and educational attainment in UK Biobank (N=112 151)

Effects of polygenic risk for Alzheimer's disease on rate of cognitive decline in normal aging

Most people's cognitive abilities decline with age, with significant and partly genetically driven, individual differences in rate of change. Although APOE ɛ4 and genetic scores for late-onset Alzheimer's disease (LOAD) have been related to cognitive decline during preclinical stages of dementia, there is limited knowledge concerning genetic factors implied in normal cognitive aging. In the present study, we examined three potential genetic predictors of age-related cognitive decline as follows: (1) the APOE ɛ4 allele, (2) a polygenic score for general cognitive ability (PGS-cog), and (3) a polygenic risk score for late-onset AD (PRS-LOAD). We examined up to six time points of cognitive measurements in the longitudinal population-based Betula study, covering a 25-year follow-up period. Only participants that remained alive and non-demented until the most recent dementia screening (1-3 years after the last test occasion) were included (n = 1087). Individual differences in rate of cognitive change (composite score) were predicted by the PRS-LOAD and APOE ɛ4, but not by PGS-cog. To control for the possibility that the results reflected a preclinical state of Alzheimer's disease in some participants, we re-ran the analyses excluding cognitive data from the last test occasion to model cognitive change up-until a minimum of 6 years before potential onset of clinical Alzheimers. Strikingly, the association of PRS-LOAD, but not APOE ɛ4, with cognitive change remained. The results indicate that PRS-LOAD predicts individual difference in rate of cognitive decline in normal aging, but it remains to be determined to what extent this reflects preclinical Alzheimer's disease brain pathophysiology and subsequent risk to develop the disease.

Genome-wide association study of cognitive function in diverse Hispanics/Latinos: results from the Hispanic Community Health Study/Study of Latinos

Cognitive function such as reasoning, attention, memory, and language is strongly correlated with brain aging. Compared to non-Hispanic whites, Hispanics/Latinos have a higher risk of cognitive impairment and dementia. The genetic determinants of cognitive function have not been widely explored in this diverse and admixed population. We conducted a genome-wide association analysis of cognitive function in up to 7600 middle aged and older Hispanics/Latinos (mean = 55 years) from the Hispanic Community Health Study / Study of Latinos (HCHS/SOL). Four cognitive measures were examined: the Brief Spanish English Verbal Learning Test (B-SEVLT), the Word Fluency Test (WFT), the Digit Symbol Substitution Test (DSST), the Six-Item Screener (SIS). Four novel loci were identified: one for B-SEVLT at 4p14, two for WFT at 3p14.1 and 6p21.32, and one for DSST at 10p13. These loci implicate genes highly expressed in brain and previously connected to neurological diseases (UBE2K, FRMD4B, the HLA gene complex). By applying tissue-specific gene expression prediction models to our genotype data, additional genes highly expressed in brain showed suggestive associations with cognitive measures possibly indicating novel biological mechanisms, including IFT122 in the hippocampus for SIS, SNX31 in the basal ganglia for B-SEVLT, RPS6KB2 in the frontal cortex for WFT, and CSPG5 in the hypothalamus for DSST. These findings provide new information about the genetic determinants of cognitive function in this unique population. In addition, we derived a measure of general cognitive function based on these cognitive tests and generated genome-wide association summary results, providing a resource to the research community for comparison, replication, and meta-analysis in future genetic studies in Hispanics/Latinos.

Genetic Associations Between Executive Functions and a General Factor of Psychopathology

OBJECTIVE

Symptoms of psychopathology covary across diagnostic boundaries, and a family history of elevated symptoms for a single psychiatric disorder places an individual at heightened risk for a broad range of other psychiatric disorders. Both twin-based and genome-wide molecular methods indicate a strong genetic basis for the familial aggregation of psychiatric disease. This has led researchers to prioritize the search for highly heritable childhood risk factors for transdiagnostic psychopathology. Cognitive abilities that involve the selective control and regulation of attention, known as executive functions (EFs), are a promising set of risk factors.

METHOD

In a population-based sample of child and adolescent twins (n = 1,913, mean age = 13.1 years), we examined genetic overlap between both EFs and general intelligence (g) and a transdiagnostic dimension of vulnerability to psychopathology, comprising symptoms of anxiety, depression, neuroticism, aggression, conduct disorder, oppositional defiant disorder, hyperactivity, and inattention. Psychopathology symptoms in children were rated by children and their parents.

RESULTS

Latent factors representing general EF and g were highly heritable (h2 = 86%-92%), and genetic influences on both sets of cognitive abilities were robustly correlated with transdiagnostic genetic influences on psychopathology symptoms (genetic r values ranged from -0.20 to -0.38).

CONCLUSION

General EF and g robustly index genetic risk for transdiagnostic symptoms of psychopathology in childhood. Delineating the developmental and neurobiological mechanisms underlying observed associations between cognitive abilities and psychopathology remains a priority for ongoing research.

Sporadic and Familial Variants in NF1: An Explanation of the Wide Variability in Neurocognitive Phenotype?

Background: Cognitive impairment is the most common neurological manifestation in NF1 and occurs in 30–70% of NF1 cases. The onset and severity of each specific cognitive deficit varies greatly from child to child, with no apparent external causes. The wide variability of phenotype is the most complex aspect in terms of management and care. Despite multiple research, the mechanism underlying the high heterogeneity in NF1 has not yet been elucidated. While many studies have focused on the effects of specific and precise genetic mutations on the NF1 phenotype, little has been done on the impact of NF1 transmission (sporadic vs. familial cases). We used a complete neuropsychological evaluation designed to assess five large cognitive areas: general cognitive functions (WISC-IV and EVIP); reading skills (“L'Alouette,” ODEDYS-2 and Lobrot French reading tests); phonological process (ODEDYS-2 test); visual perceptual skills (JLO, Thurstone and Corsi block tests) and attention (CPT-II), as well as psychosocial adjustments (CBCL) to explore the impact of NF1 transmission on cognitive disease manifestation in 96 children affected by NF1 [55 sporadic cases (29♀, 26♂); 41 familial cases (24♀, 17♂)].

Results: Familial and Sporadic form of NF1 only differ in IQ expression. The families' socioeconomic status (SES) impacts IQ performance but not differently between sporadic and familial variants. However, SES is lower in familial variants than in the sporadic variant of NF1. No other cognitive differences emerge between sporadic and familial NF1.

Conclusions: Inheritance in NF1 failed to explain the phenotype variability in its entirety. IQ differences between groups seems in part linked to the environment where the child grows up. Children with NF1, and especially those that have early diagnoses (most often in inherited cases), must obtain careful monitoring from their early childhood, at home to strengthen investment in education and in school to early detect emerging academic problems and to quickly place them into care.

Trial Registration: IDRCB, IDRCB2008-A01444-51. Registered 19 January 2009.

Identification of genes involved in the evolution of human intelligence through combination of inter-species and intra-species genetic variations

Understanding the evolution of human intelligence is an important undertaking in the science of human genetics. A great deal of biological research has been conducted to search for genes which are related to the significant increase in human brain volume and cerebral cortex complexity during hominid evolution. However, genetic changes affecting intelligence in hominid evolution have remained elusive. We supposed that a subset of intelligence-related genes, which harbored intra-species variations in human populations, may also be evolution-related genes which harbored inter-species variations between humans (Homo sapiens) and great apes (including Pan troglodytes and Pongo abelii). Here we combined inter-species and intra-species genetic variations to discover genes involved in the evolution of human intelligence. Information was collected from published GWAS works on intelligence and a total of 549 genes located within the intelligence-associated loci were identified. The intelligence-related genes containing human-specific variations were detected based on the latest high-quality genome assemblies of three human's closest species. Finally, we identified 40 strong candidates involved in human intelligence evolution. Expression analysis using RNA-Seq data revealed that most of the genes displayed a relatively high expression in the cerebral cortex. For these genes, there is a distinct expression pattern between humans and other species, especially in neocortex tissues. Our work provided a list of strong candidates for the evolution of human intelligence, and also implied that some intelligence-related genes may undergo inter-species evolution and contain intra-species variation.

The Role of Genetic Variation of BMI, Body Composition, and Fat Distribution for Mental Traits and Disorders: A Look-Up and Mendelian Randomization Study

Anthropometric traits and mental disorders or traits are known to be associated clinically and to show genetic overlap. We aimed to identify genetic variants with relevance for mental disorders/traits and either (i) body mass index (or obesity), (ii) body composition, (and/or) (iii) body fat distribution. We performed a look-up analysis of 1,005 genome-wide significant SNPs for BMI, body composition, and body fat distribution in 15 mental disorders/traits. We identified 40 independent loci with one or more SNPs fulfilling our threshold significance criterion (P < 4.98 × 10-5) for the mental phenotypes. The majority of loci was associated with schizophrenia, educational attainment, and/or intelligence. Fewer associations were found for bipolar disorder, neuroticism, attention deficit/hyperactivity disorder, major depressive disorder, depressive symptoms, and well-being. Unique associations with measures of body fat distribution adjusted for BMI were identified at five loci only. To investigate the potential causality between body fat distribution and schizophrenia, we performed two-sample Mendelian randomization analyses. We found no causal effect of body fat distribution on schizophrenia and vice versa. In conclusion, we identified 40 loci which may contribute to genetic overlaps between mental disorders/traits and BMI and/or shape related phenotypes. The majority of loci identified for body composition overlapped with BMI loci, thus suggesting pleiotropic effects.

Cortical Surfaces Mediate the Relationship Between Polygenic Scores for Intelligence and General Intelligence

Recent large-scale, genome-wide association studies (GWAS) have identified hundreds of genetic loci associated with general intelligence. The cumulative influence of these loci on brain structure is unknown. We examined if cortical morphology mediates the relationship between GWAS-derived polygenic scores for intelligence (PSi) and g-factor. Using the effect sizes from one of the largest GWAS meta-analysis on general intelligence to date, PSi were calculated among 10 P value thresholds. PSi were assessed for the association with g-factor performance, cortical thickness (CT), and surface area (SA) in two large imaging-genetics samples (IMAGEN N = 1651; IntegraMooDS N = 742). PSi explained up to 5.1% of the variance of g-factor in IMAGEN (F1,1640 = 12.2-94.3; P < 0.005), and up to 3.0% in IntegraMooDS (F1,725 = 10.0-21.0; P < 0.005). The association between polygenic scores and g-factor was partially mediated by SA and CT in prefrontal, anterior cingulate, insula, and medial temporal cortices in both samples (PFWER-corrected < 0.005). The variance explained by mediation was up to 0.75% in IMAGEN and 0.77% in IntegraMooDS. Our results provide evidence that cumulative genetic load influences g-factor via cortical structure. The consistency of our results across samples suggests that cortex morphology could be a novel potential biomarker for neurocognitive dysfunction that is among the most intractable psychiatric symptoms.

Parity is associated with cognitive function and brain age in both females and males

Previous studies of the association between parity and long-term cognitive changes have primarily focused on women and have shown conflicting results. We investigated this association by analyzing data collected on 303,196 subjects from the UK Biobank. We found that in both females and males, having offspring was associated with a faster response time and fewer mistakes made in the visual memory task. Subjects with two or three children had the largest differences relative to those who were childless, with greater effects observed in men. We further analyzed the association between parity and relative brain age (n = 13,584), a brain image-based biomarker indicating how old one's brain structure appears relative to peers. We found that in both sexes, subjects with two or three offspring had significantly reduced brain age compared to those without offspring, corroborating our cognitive function results. Our findings suggest that lifestyle factors accompanying having offspring, rather than the physical process of pregnancy experienced only by females, contribute to these associations and underscore the importance of studying such factors, particularly in the context of sex.

Recent Efforts to Dissect the Genetic Basis of Alcohol Use and Abuse

Alcohol use disorder (AUD) is defined by several symptom criteria, which can be dissected further at the genetic level. Over the past several years, our understanding of the genetic factors influencing alcohol use and abuse has progressed tremendously; numerous loci have been implicated in different aspects of alcohol use. Previously known associations with alcohol-metabolizing enzymes (ADH1B, ALDH2) have been replicated definitively. In addition, novel associations with loci containing the genes KLB, GCKR, CRHR1, and CADM2 have been reported. Downstream analyses have leveraged these genetic findings to reveal important relationships between alcohol use behaviors and both physical and mental health. AUD and aspects of alcohol misuse have been shown to overlap strongly with psychiatric disorders, whereas aspects of alcohol consumption have shown stronger links to metabolism. These results demonstrate that the genetic architecture of alcohol consumption only partially overlaps with the genetics of clinically defined AUD. We discuss the limitations of using quantitative measures of alcohol use as proxy measures for AUD, and we outline how future studies will require careful phenotype harmonization to properly capture the genetic liability to AUD.

An epigenome-wide association study of posttraumatic stress disorder in US veterans implicates several new DNA methylation loci

BACKGROUND

Previous studies using candidate gene and genome-wide approaches have identified epigenetic changes in DNA methylation (DNAm) associated with posttraumatic stress disorder (PTSD).

METHODS

In this study, we performed an EWAS of PTSD in a cohort of Veterans (n = 378 lifetime PTSD cases and 135 controls) from the Translational Research Center for TBI and Stress Disorders (TRACTS) cohort assessed using the Illumina EPIC Methylation BeadChip which assesses DNAm at more than 850,000 sites throughout the genome. Our model included covariates for ancestry, cell heterogeneity, sex, age, and a smoking score based on DNAm at 39 smoking-associated CpGs. We also examined in EPIC-based DNAm data generated from pre-frontal cortex (PFC) tissue from the National PTSD Brain Bank (n = 72).

RESULTS

The analysis of blood samples yielded one genome-wide significant association with PTSD at cg19534438 in the gene G0S2 (p = 1.19 × 10-7, padj = 0.048). This association was replicated in an independent PGC-PTSD-EWAS consortium meta-analysis of military cohorts (p = 0.0024). We also observed association with the smoking-related locus cg05575921 in AHRR despite inclusion of a methylation-based smoking score covariate (p = 9.16 × 10-6), which replicates a previously observed PGC-PTSD-EWAS association (Smith et al. 2019), and yields evidence consistent with a smoking-independent effect. The top 100 EWAS loci were then examined in the PFC data. One of the blood-based PTSD loci, cg04130728 in CHST11, which was in the top 10 loci in blood, but which was not genome-wide significant, was significantly associated with PTSD in brain tissue (in blood p = 1.19 × 10-5, padj = 0.60, in brain, p = 0.00032 with the same direction of effect). Gene set enrichment analysis of the top 500 EWAS loci yielded several significant overlapping GO terms involved in pathogen response, including "Response to lipopolysaccharide" (p = 6.97 × 10-6, padj = 0.042).

CONCLUSIONS

The cross replication observed in independent cohorts is evidence that DNA methylation in peripheral tissue can yield consistent and replicable PTSD associations, and our results also suggest that that some PTSD associations observed in peripheral tissue may mirror associations in the brain.

CHIMGEN: a Chinese imaging genetics cohort to enhance cross-ethnic and cross-geographic brain research

The Chinese Imaging Genetics (CHIMGEN) study establishes the largest Chinese neuroimaging genetics cohort and aims to identify genetic and environmental factors and their interactions that are associated with neuroimaging and behavioral phenotypes. This study prospectively collected genomic, neuroimaging, environmental, and behavioral data from more than 7000 healthy Chinese Han participants aged 18-30 years. As a pioneer of large-sample neuroimaging genetics cohorts of non-Caucasian populations, this cohort can provide new insights into ethnic differences in genetic-neuroimaging associations by being compared with Caucasian cohorts. In addition to micro-environmental measurements, this study also collects hundreds of quantitative macro-environmental measurements from remote sensing and national survey databases based on the locations of each participant from birth to present, which will facilitate discoveries of new environmental factors associated with neuroimaging phenotypes. With lifespan environmental measurements, this study can also provide insights on the macro-environmental exposures that affect the human brain as well as their timing and mechanisms of action.

Neurology-related protein biomarkers are associated with cognitive ability and brain volume in older age

Identifying biological correlates of late life cognitive function is important if we are to ascertain biomarkers for, and develop treatments to help reduce, age-related cognitive decline. Here, we investigated the associations between plasma levels of 90 neurology-related proteins (Olink® Proteomics) and general fluid cognitive ability in the Lothian Birth Cohort 1936 (LBC1936, N = 798), Lothian Birth Cohort 1921 (LBC1921, N = 165), and the INTERVAL BioResource (N = 4451). In the LBC1936, 22 of the proteins were significantly associated with general fluid cognitive ability (β between -0.11 and -0.17). MRI-assessed total brain volume partially mediated the association between 10 of these proteins and general fluid cognitive ability. In an age-matched subsample of INTERVAL, effect sizes for the 22 proteins, although smaller, were all in the same direction as in LBC1936. Plasma levels of a number of neurology-related proteins are associated with general fluid cognitive ability in later life, mediated by brain volume in some cases.

Polygenic Risk Scores Shed Light on the Relationship between Schizophrenia and Cognitive Functioning: Review and Meta-Analysis

Schizophrenia is a multifactorial disease associated with widespread cognitive impairment. Although cognitive deficits are one of the factors most strongly associated with functional impairment in schizophrenia (SZ), current treatment strategies hardly tackle these impairments. To develop more efficient treatment strategies in patients, a better understanding of their pathogenesis is needed. Recent progress in genetics, driven by large genome-wide association studies (GWAS) and the use of polygenic risk scores (PRS), has provided new insights about the genetic architecture of complex human traits, including cognition and SZ. Here, we review the recent findings examining the genetic links between SZ and cognitive functions in population-based samples as well as in participants with SZ. The performed meta-analysis showed a negative correlation between the polygenetic risk score of schizophrenia and global cognition (p < 0.001) when the samples rely on general and healthy participants, while no significant correlation was detected when the three studies devoted to schizophrenia patients were meta-analysed (p > 0.05). Our review and meta-analysis therefore argues against universal pleiotropy for schizophrenia alleles and cognition, since cognition in SZ patients would be underpinned by the same genetic factors than in the general population, and substantially independent of common variant liability to the disorder.

Single nucleotide polymorphism heritability and differential patterns of genetic overlap between inattention and four neurocognitive factors in youth

Theoretical models of attention-deficit/hyperactivity disorder implicate neurocognitive dysfunction, yet neurocognitive functioning covers a range of abilities that may not all be linked with inattention. This study (a) investigated the single nucleotide polymorphism (SNP) heritability (h2SNP) of inattention and aspects of neurocognitive efficiency (memory, social cognition, executive function, and complex cognition) based on additive genome-wide effects; (b) examined if there were shared genetic effects among inattention and each aspect of neurocognitive efficiency; and (c) conducted an exploratory genome-wide association study to identify genetic regions associated with inattention. The sample included 3,563 participants of the Philadelphia Neurodevelopmental Cohort, a general population sample aged 8-21 years who completed the Penn Neurocognitive Battery. Data on inattention was obtained with the Kiddie Schedule of Affective Disorders (adapted). Genomic relatedness matrix restricted maximum likelihood was implemented in genome-wide complex trait analysis. Analyses revealed significant h2SNP for inattention (20%, SE = 0.08), social cognition (13%, SE = 0.08), memory (17%, SE = 0.08), executive function (25%, SE = 0.08), and complex cognition (24%, SE = 0.08). There was a positive genetic correlation (0.67, SE = 0.37) and a negative residual covariance (-0.23, SE = 0.06) between inattention and social cognition. No SNPs reached genome-wide significance for inattention. Results suggest specificity in genetic overlap among inattention and different aspects of neurocognitive efficiency.

Cognitive Genomics: Recent Advances and Current Challenges

PURPOSE OF REVIEW

We review recent progress in uncovering the complex genetic architecture of cognition, arising primarily from genome-wide association studies (GWAS). We explore the genetic correlations between cognitive performance and neuropsychiatric disorders, the genetic and environmental factors associated with age-related cognitive decline, and speculate about the future role of genomics in the understanding of cognitive processes.

RECENT FINDINGS

Improvements in genomic methods, and the increasing availability of large datasets via consortia cooperation, have led to a greater understanding of the role played by common and rare variants in the genomics of cognition, the highly polygenic basis of cognitive function and dysfunction, and the multiple biological processes involved. Recent research has aided in our understanding of the complex biological nature of genomics of cognition. Further development of data banks and techniques to analyze this data hold significant promise for understanding cognitive ability, and for treating cognitively related disability.

The genome-wide risk alleles for psychiatric disorders at 3p21.1 show convergent effects on mRNA expression, cognitive function, and mushroom dendritic spine

Schizophrenia and bipolar disorder (BPD) are believed to share clinical features, etiological factors, and disease pathologies (such as impaired cognitive functions and dendritic spine pathology). Meanwhile, there is growing evidence of shared genetic risk between schizophrenia and BPD, despite that our knowledge of the functional risk variations and biological mechanisms is still limited. Here, we conduct summary data-based Mendelian randomization (SMR) analyses through combining the statistical data from genome-wide association studies (GWAS) of both schizophrenia and BPD and multiple expression quantitative trait loci (eQTL) datasets of the human brain dorsolateral prefrontal cortex (DLPFC) tissues. These integrative investigations identify a lead risk locus at the chromosome 3p21.1 region, which contains numerous single-nucleotide polymorphisms (SNPs) in varied linkage disequilibrium (LD) and encompasses more than 20 genes. Further analyses suggest that many SNPs at 3p21.1 are significantly associated with both schizophrenia and BPD, and even depression, and the psychiatric risk alleles at 3p21.1 are correlated with mRNA expression of multiple genes such as NEK4, GNL3, and PBRM1. We also identify a 335-bp functional Alu polymorphism rs71052682 in significant LD with the psychiatric GWAS risk SNP rs2251219, and confirm the regulatory effects of this Alu polymorphism on transcription activities. We then explore the involvement of the 3p21.1 locus in the common clinical features and etiology of these illnesses. We reveal that psychiatric risk alleles at 3p21.1 in low-to-high LD consistently predict worse cognitive functions in humans, and manipulating the gene expression (NEK4, GNL3, and PBRM1) linked with higher genetic risk could reduce the density of mushroom dendritic spines in rat primary cortical neurons, mirroring the spine pathology in the prefrontal cortex of psychiatric patients. Our results find that, although the risk alleles at 3p21.1 are in low-to-moderate LD spanning a large genomic area, their underlying biological mechanisms in psychiatric disorders likely converge. These results provide essential insights into the neural mechanisms underlying the chromosome 3p21.1 risk locus in the shared pathological and etiological features of both schizophrenia and BPD.

Polygenic Risk Scores for Subtyping of Schizophrenia

Schizophrenia is a complex disorder with many comorbid conditions. In this study, we used polygenic risk scores (PRSs) from schizophrenia and comorbid traits to explore consistent cluster structure in schizophrenia patients. With 10 comorbid traits, we found a stable 4-cluster structure in two datasets (MGS and SSCCS). When the same traits and parameters were applied for the patients in a clinical trial of antipsychotics, the CATIE study, a 5-cluster structure was observed. One of the 4 clusters found in the MGS and SSCCS was further split into two clusters in CATIE, while the other 3 clusters remained unchanged. For the 5 CATIE clusters, we evaluated their association with the changes of clinical symptoms, neurocognitive functions, and laboratory tests between the enrollment baseline and the end of Phase I trial. Class I was found responsive to treatment, with significant reduction for the total, positive, and negative symptoms (p = 0.0001, 0.0099, and 0.0028, respectively), and improvement for cognitive functions (VIGILANCE, p = 0.0099; PROCESSING SPEED, p = 0.0006; WORKING MEMORY, p = 0.0023; and REASONING, p = 0.0015). Class II had modest reduction of positive symptoms (p = 0.0492) and better PROCESSING SPEED (p = 0.0071). Class IV had a specific reduction of negative symptoms (p = 0.0111) and modest cognitive improvement for all tested domains. Interestingly, Class IV was also associated with decreased lymphocyte counts and increased neutrophil counts, an indication of ongoing inflammation or immune dysfunction. In contrast, Classes III and V showed no symptom reduction but a higher level of phosphorus. Overall, our results suggest that PRSs from schizophrenia and comorbid traits can be utilized to classify patients into subtypes with distinctive clinical features. This genetic susceptibility based subtyping may be useful to facilitate more effective treatment and outcome prediction.

From Polygenic Scores to Precision Medicine in Alzheimer's Disease: A Systematic Review

BACKGROUND

Late-onset Alzheimer's disease (AD) is highly heritable. The effect of many common genetic variants, single nucleotide polymorphisms (SNPs), confer risk. Variants are clustered in areas of biology, notably immunity and inflammation, cholesterol metabolism, endocytosis, and ubiquitination. Polygenic scores (PRS), which weight the sum of an individual's risk alleles, have been used to draw inferences about the pathological processes underpinning AD.

OBJECTIVE

This paper aims to systematically review how AD PRS are being used to study a range of outcomes and phenotypes related to neurodegeneration.

METHODS

We searched the literature from July 2008-July 2018 following PRISMA guidelines.

RESULTS

57 studies met criteria. The AD PRS can distinguish AD cases from controls. The ability of AD PRS to predict conversion from mild cognitive impairment (MCI) to AD was less clear. There was strong evidence of association between AD PRS and cognitive impairment. AD PRS were correlated with a number of biological phenotypes associated with AD pathology, such as neuroimaging changes and amyloid and tau measures. Pathway-specific polygenic scores were also associated with AD-related biologically relevant phenotypes.

CONCLUSION

PRS can predict AD effectively and are associated with cognitive impairment. There is also evidence of association between AD PRS and other phenotypes relevant to neurodegeneration. The associations between pathway specific polygenic scores and phenotypic changes may allow us to define the biology of the disease in individuals and indicate who may benefit from specific treatments. Longitudinal cohort studies are required to test the ability of PGS to delineate pathway-specific disease activity.

Morphometric traits predict educational attainment independently of socioeconomic background

Background

Aim of this study is to describe the relationship between anthropometric traits and educational attainment among Estonian schoolchildren born between 1937 and 1962. We asked whether height, cranial volume and face width (a testosterone-dependent trait), measured in childhood predict later educational attainment independently of each other, family socioeconomic position (SEP) and sex. Associations between morphometric traits and education and their interactions with biosocial variables are of scholarly importance because higher education is nearly universally associated with low fertility in women, and often with high fertility in men. Hence, morphometric traits associated with educational attainment are targeted by natural selection and describing the exact nature of these associations is relevant for understanding the current patterns of evolution of human body size.

Methods

Data on morphometric measurements and family background of 11,032 Estonian schoolchildren measured between seven and 19 years of age were obtained from the study performed by Juhan Aul between 1956 and 1969. Ordinal logistic regression was used for testing the effects of morphometric traits, biosocial variables and their interaction on the cumulative probability of obtaining education beyond primary level.

Results

Of biosocial variables, family SEP was the most important determinant of educational attainment, followed by the sex, rural vs urban origin and the number of siblings. No significant interactions with morphometric traits were detected, i.e., within each category of SEP, rural vs urban origin and sex, taller children and those with larger heads and relatively narrower faces were more likely to proceed to secondary and/or tertiary education. The effect of height on education was independent of cranial volume, indicating that taller children did not obtain more educations because their brains were larger than those of shorter children; height per se was important.

Conclusions

Our main finding – that adjusting for other morphometric traits and biosocial variables, morphometric traits still robustly predicted educational attainment, is relevant for understanding the current patterns of evolution of human body size. Our findings suggest that fecundity selection acting on educational attainment could be partly responsible for the concurrent selection for smaller stature and cranial volume in women and opposite trends in men.

The polyamine transporter Slc18b1(VPAT) is important for both short and long time memory and for regulation of polyamine content in the brain

SLC18B1 is a sister gene to the vesicular monoamine and acetylcholine transporters, and the only known polyamine transporter, with unknown physiological role. We reveal that Slc18b1 knock out mice has significantly reduced polyamine content in the brain providing the first evidence that Slc18b1 is functionally required for regulating polyamine levels. We found that this mouse has impaired short and long term memory in novel object recognition, radial arm maze and self-administration paradigms. We also show that Slc18b1 KO mice have altered expression of genes involved in Long Term Potentiation, plasticity, calcium signalling and synaptic functions and that expression of components of GABA and glutamate signalling are changed. We further observe a partial resistance to diazepam, manifested as significantly lowered reduction in locomotion after diazepam treatment. We suggest that removal of Slc18b1 leads to reduction of polyamine contents in neurons, resulting in reduced GABA signalling due to long-term reduction in glutamatergic signalling.

A fundamental function of the nervous system is its ability to modulate and change the connections between nerve cells, and this forms the basis for memory and learning. This is most well studied for synapses that are using the neurotransmitter glutamate, and a central part of this is referred to Long Term Potentiation. This process is dependent on a specific glutamate receptor called the NMDA receptor, and the function of this receptor can be controlled by various mechanisms. Here, we show that polyamines can regulate this receptor and that lack of polyamines result in impaired learning and memory. Polyamines are small peptides made by many different cells in the body, including cells in the brain, and by removing a gene coding for a transporter important for the release of polyamines in nerve cells of mice, we show that polyamines are important for proper function of the glutamate system. We also show the deletion of this gene result in fundamentally rearranged GABA and glutamate systems, resulting in the mice having a much higher tolerance for the sedative drug benzodiazepines. Polyamines and targets for these molecules could be important points of intervention for future drugs aiming at modulating the glutamatergic system.

Impact of AKAP6 polymorphisms on Glioma susceptibility and prognosis

PURPOSE

Glioma is the most common primary malignant brain tumor with high mortality and poor prognosis. Our aim was to clarify the correlation between Kinase-anchored protein 6 (AKAP6) gene polymorphisms and glioma susceptibility and prognosis in Chinese Han population.

METHODS

Five single-nucleotide polymorphisms (SNPs) of AKAP6 were genotyped by Agena MassARRAY in 575 glioma patients and 500 healthy controls. Logistic regression model was utilized to calculate odds ratios (OR) and 95% confidence intervals (CI). The associations between polymorphisms and survival were assessed using the log-rank test, Kaplan-Meier analysis and Cox regression model.

RESULTS

We found that rs2239647 polymorphism was strongly associated with an increased risk of glioma (OR = 1.90, p = 0.007) and a worse prognosis for glioma, especially in high-grade glioma (HR = 1.67, p = 0.034). Stratified analysis showed that rs2239647 increased the risk of glioma in female (OR = 1.62, p = 0.016). Whereas, rs4261436 (HR = 0.70, p = 0.045) and rs17522122 (HR = 0.75, p = 0.016) were associated with better prognosis of astrocytoma. In addition, we also found that surgical methods and chemotherapy are critical factors for the prognosis of glioma patients.

CONCLUSIONS

This study firstly provided evidence for the impact of AKAP6 polymorphisms on susceptibility and prognosis of glioma, suggesting AKAP6 variants might have potential roles in the etiology of glioma.

Comparative genetic architectures of schizophrenia in East Asian and European populations

Schizophrenia is a debilitating psychiatric disorder with approximately 1% lifetime risk globally. Large-scale schizophrenia genetic studies have reported primarily on European ancestry samples, potentially missing important biological insights. Here, we report the largest study to date of East Asian participants (22,778 schizophrenia cases and 35,362 controls), identifying 21 genome-wide significant associations in 19 genetic loci. Common genetic variants that confer risk for schizophrenia have highly similar effects between East Asian and European ancestries (r_g = 0.98 ± 0.03), indicating that the genetic basis of schizophrenia and its biology are broadly shared across populations. A fixed-effect meta-analysis including individuals from East Asian and European ancestries identified 208 significant associations in 176 genetic loci (53 novel). Trans-ancestry fine-mapping reduced the sets of candidate causal variants in 44 loci. Polygenic risk scores had reduced performance when transferred across ancestries, highlighting the importance of including sufficient samples of major ancestral groups to ensure their generalizability across populations.

Computational tools for geroscience

The rapid progress of the past three decades has led the geroscience field near a point where human interventions in aging are plausible. Advances across scientific areas, such as high throughput "-omics" approaches, have led to an exponentially increasing quantity of data available for biogerontologists. To best translate the lifespan and healthspan extending interventions discovered by basic scientists into preventative medicine, it is imperative that the current data are comprehensively utilized to generate testable hypotheses about translational interventions. Building a translational pipeline for geroscience will require both systematic efforts to identify interventions that extend healthspan across taxa and diagnostics that can identify patients who may benefit from interventions prior to the onset of an age-related morbidity. Databases and computational tools that organize and analyze both the wealth of information available on basic biogerontology research and clinical data on aging populations will be critical in developing such a pipeline. Here, we review the current landscape of databases and computational resources available for translational aging research. We discuss key platforms and tools available for aging research, with a focus on how each tool can be used in concert with hypothesis driven experiments to move closer to human interventions in aging.

Genome-wide association analysis of 19,629 individuals identifies variants influencing regional brain volumes and refines their genetic co-architecture with cognitive and mental health traits

Volumetric variations of the human brain are heritable and are associated with many brain-related complex traits. Here we performed genome-wide association studies (GWAS) of 101 brain volumetric phenotypes using the UK Biobank sample including 19,629 participants. GWAS identified 365 independent genetic variants exceeding a significance threshold of 4.9 × 10-10, adjusted for testing multiple phenotypes. A gene-based association study found 157 associated genes (124 new), and functional gene mapping analysis linked 146 additional genes. Many of the discovered genetic variants and genes have previously been implicated in cognitive and mental health traits. Through genome-wide polygenic-risk-score prediction, more than 6% of the phenotypic variance (P = 3.13 × 10-24) in four other independent studies could be explained by the UK Biobank GWAS results. In conclusion, our study identifies many new genetic associations at the variant, locus and gene levels and advances our understanding of the pleiotropy and genetic co-architecture between brain volumes and other traits.

The CADM2 gene is associated with processing speed performance - evidence among elderly with type 2 diabetes

Objectives: Recent large-scale meta-analysis of genome-wide association studies (GWAS) from multiple cohorts, demonstrated the association of the single nucleotide polymorphism (SNP) rs17518584, with processing speed (measured by the Digit Symbol Substitution Test (DSST) or the Letter Digit Substitution Test (LDST)), at GWAS significance level. This SNP is located within the cell adhesion molecule 2 (CADM2) gene. We aimed to validate this finding in our sample of 944 cognitively normal Jewish elderly individuals with type 2 diabetes (T2D), a population which is at risk for cognitive decline and dementia.Methods: Using linear regression, we studied the association of rs17518584 with DSST performance, adjusting for demographic, T2D-related characteristics and cardiovascular factors. In secondary analyses, associations with performance in four cognitive domains (episodic memory, language/semantic categorisation, attention/working memory and executive function) and overall cognition were examined.Results: Controlling for sex, age at cognitive assessment, years of education and ancestry, we found a significant association of rs17518584 with DSST performance (P = 0.013), consistent with the originally reported effect direction. Results remained significant even when the additional covariates (T2D-related and cardiovascular factors) were included in the analysis (P = 0.034). Moreover, this SNP was significantly associated with performance in the cognitive domains of language/semantic categorisation and executive function, as well as overall cognition.Conclusions: Taken together, irrespective of T2D-related characteristics and cardiovascular factors, our findings provide independent support for the association of CADM2 SNP rs17518584 with processing speed (and demonstrate association with additional cognitive phenotypes), among cognitively normal elderly individuals with T2D.

The genetic relationship between educational attainment and cognitive performance in major psychiatric disorders

Cognitive deficits are a core feature of psychiatric disorders like schizophrenia and bipolar disorder. Evidence supports a genome-wide polygenic score (GPS) for educational attainment (GPSEDU) can be used to explain variability in cognitive performance. We aimed to identify different cognitive domains associated with GPSEDU in a transdiagnostic clinical cohort of chronic psychiatric patients with known cognitive deficits. Bipolar and schizophrenia patients from the PsyCourse cohort (N = 730; 43% female) were used. Likewise, we tested whether GPSs for schizophrenia (GPSSZ) and bipolar disorder (GPSBD) were associated with cognitive outcomes. GPSEDU explained 1.5% of variance in the backward verbal digit span, 1.9% in the number of correctly recalled words of the Verbal Learning and Memory Test, and 1.1% in crystallized intelligence. These effects were robust to the influences of treatment and diagnosis. No significant associations between GPSSZ or GPSBD with cognitive outcomes were found. Furthermore, these risk scores did not confound the effect of GPSEDU on cognitive outcomes. GPSEDU explains a small fraction of cognitive performance in adults with psychiatric disorders, specifically for domains related to linguistic learning and working memory. Investigating such a proxy-phenotype longitudinally, could give intriguing insight into the disease course, highlighting at what time genes play a more influential role on cognitive performance. Better understanding the origin of these deficits might help identify those patients at risk for lower levels of functioning and poor social outcomes. Polygenic estimates may in the future be part of predictive models for more personalized interventions.

Genetically modulated educational attainment and coronary disease risk

AIMS

Genetic disposition and lifestyle factors are understood as independent components underlying the risk of multiple diseases. In this study, we aim to investigate the interplay between genetics, educational attainment-an important denominator of lifestyle-and coronary artery disease (CAD) risk.

METHODS AND RESULTS

Based on the effect sizes of 74 genetic variants associated with educational attainment, we calculated a 'genetic education score' in 13 080 cases and 14 471 controls and observed an inverse correlation between the score and risk of CAD [P = 1.52 × 10-8; odds ratio (OR) 0.79, 95% confidence interval (CI) 0.73-0.85 for the higher compared with the lowest score quintile]. We replicated in 146 514 individuals from UK Biobank (P = 1.85 × 10-6) and also found strong associations between the 'genetic education score' with 'modifiable' risk factors including smoking (P = 5.36 × 10-23), body mass index (BMI) (P = 1.66 × 10-30), and hypertension (P = 3.86 × 10-8). Interestingly, these associations were only modestly attenuated by adjustment for years spent in school. In contrast, a model adjusting for BMI and smoking abolished the association signal between the 'genetic education score' and CAD risk suggesting an intermediary role of these two risk factors. Mendelian randomization analyses performed with summary statistics from large genome-wide meta-analyses and sensitivity analysis using 1271 variants affecting educational attainment (OR 0.68 for the higher compared with the lowest score quintile; 95% CI 0.63-0.74; P = 3.99 × 10-21) further strengthened these findings.

CONCLUSION

Genetic variants known to affect educational attainment may have implications for a health-conscious lifestyle later in life and subsequently affect the risk of CAD.

Pleiotropic Meta-Analysis of Cognition, Education, and Schizophrenia Differentiates Roles of Early Neurodevelopmental and Adult Synaptic Pathways

Susceptibility to schizophrenia is inversely correlated with general cognitive ability at both the phenotypic and the genetic level. Paradoxically, a modest but consistent positive genetic correlation has been reported between schizophrenia and educational attainment, despite the strong positive genetic correlation between cognitive ability and educational attainment. Here we leverage published genome-wide association studies (GWASs) in cognitive ability, education, and schizophrenia to parse biological mechanisms underlying these results. Association analysis based on subsets (ASSET), a pleiotropic meta-analytic technique, allowed jointly associated loci to be identified and characterized. Specifically, we identified subsets of variants associated in the expected ("concordant") direction across all three phenotypes (i.e., greater risk for schizophrenia, lower cognitive ability, and lower educational attainment); these were contrasted with variants that demonstrated the counterintuitive ("discordant") relationship between education and schizophrenia (i.e., greater risk for schizophrenia and higher educational attainment). ASSET analysis revealed 235 independent loci associated with cognitive ability, education, and/or schizophrenia at p < 5 × 10-8. Pleiotropic analysis successfully identified more than 100 loci that were not significant in the input GWASs. Many of these have been validated by larger, more recent single-phenotype GWASs. Leveraging the joint genetic correlations of cognitive ability, education, and schizophrenia, we were able to dissociate two distinct biological mechanisms-early neurodevelopmental pathways that characterize concordant allelic variation and adulthood synaptic pruning pathways-that were linked to the paradoxical positive genetic association between education and schizophrenia. Furthermore, genetic correlation analyses revealed that these mechanisms contribute not only to the etiopathogenesis of schizophrenia but also to the broader biological dimensions implicated in both general health outcomes and psychiatric illness.

Association of Rare Copy Number Variants With Risk of Depression

IMPORTANCE

The role of large, rare copy number variants (CNVs) in neuropsychiatric disorders is well established, but their association with common psychiatric disorders, such as depression, remains unclear.

OBJECTIVE

To examine the association of a group of 53 CNVs associated with neurodevelopmental disorders and burden of rare CNVs with risk of depression.

DESIGN, SETTING, AND PARTICIPANTS

This case-control study used data from the UK Biobank study sample, which comprised 502 534 individuals living in the United Kingdom. Individuals with autism spectrum disorder, intellectual disability, attention-deficit/hyperactivity disorder, schizophrenia, or bipolar affective disorder diagnoses were excluded. Analyses were further restricted to individuals of European genetic ancestry (n = 407 074). The study was conducted from January 2017 to September 2018.

EXPOSURES

CNV carrier status.

MAIN OUTCOMES AND MEASURES

For the primary outcome, individuals who reported that a physician had told them they had a depression diagnosis were defined as cases. Analyses were repeated using 2 alternative depression definitions: self-reported lifetime depression with current antidepressant prescription at the time of visit 1, and hospital discharge diagnosis of depression.

RESULTS

Copy number variants were identified in 488 366 individuals aged 37 to 73 years. In total, 407 074 individuals with European genetic ancestry (220 201 female [54.1%]; mean [SD] age of 56.9 [8.0] years) were included in the study. Of these individuals, 23 979 (5.9%) had self-reported lifetime depression and 383 095 (94.1%) reported no lifetime depression. The group of 53 neurodevelopmental CNVs was associated with self-reported depression (odds ratio [OR], 1.34; 95% CI, 1.19-1.49, uncorrected P = 1.38 × 10-7), and these results were consistent when using 2 alternative definitions of depression. This association was partially explained by physical health, educational attainment, social deprivation, smoking status, and alcohol consumption. A strong independent association remained between the neurodevelopmental CNVs and depression in analyses that incorporated these other measures (OR, 1.26; 95% CI, 1.11-1.43; P = 2.87 × 10-4). Eight individual CNVs were nominally associated with risk of depression, and 3 of these 8 CNVs (1q21.1 duplication, Prader-Willi syndrome duplication, and 16p11.2 duplication) survived Bonferroni correction for the 53 CNVs tested. After the exclusion of carriers of neurodevelopmental CNVs, no association was found between measures of CNV burden and depression.

CONCLUSIONS AND RELEVANCE

Neurodevelopmental CNVs appear to be associated with depression, extending the spectrum of clinical phenotypes that are associated with CNV carrier status.

Genome-Wide Association Study of Latent Cognitive Measures in Adolescence: Genetic Overlap With Intelligence and Education

Individual differences in executive functions (EF) are heritable and predictive of academic attainment (AA). However, little is known about genetic contributions to EFs or their genetic relationship with AA and intelligence. We conducted genome-wide association analyses for processing speed (PS) and the latent EF measures of working memory (WM) and inhibitory control (IC) in 4,611 adolescents from the Avon Longitudinal Study of Parents and Children. While no loci reached genome-wide significance, common genetic variants explained 30% of the variance in WM and 19% in PS. In contrast, we failed to find common genetic contributions to IC. Finally, we examined shared genetic effects between EFs and general intelligence, AA and ADHD. We identified significant genetic correlations between WM, intelligence, and AA. A more specific pattern was observed for PS, with modest genetic overlap with intelligence. Together these findings highlight diversity in the genetic contributions to specific cognitive functions and their genetic relationship with educational and psychiatric outcomes.

Genetic Contributions to Health Literacy

Higher health literacy is associated with higher cognitive function and better health. Despite its wide use in medical research, no study has investigated the genetic contributions to health literacy. Using 5783 English Longitudinal Study of Ageing (ELSA) participants (mean age = 65.49, SD = 9.55) who had genotyping data and had completed a health literacy test at wave 2 (2004-2005), we carried out a genome-wide association study (GWAS) of health literacy. We estimated the proportion of variance in health literacy explained by all common single nucleotide polymorphisms (SNPs). Polygenic profile scores were calculated using summary statistics from GWAS of 21 cognitive and health measures. Logistic regression was used to test whether polygenic scores for cognitive and health-related traits were associated with having adequate, compared to limited, health literacy. No SNPs achieved genome-wide significance for association with health literacy. The proportion of variance in health literacy accounted for by common SNPs was 8.5% (SE = 7.2%). Greater odds of having adequate health literacy were associated with a 1 standard deviation higher polygenic score for general cognitive ability [OR = 1.34, 95% CI (1.26, 1.42)], verbal-numerical reasoning [OR = 1.30, 95% CI (1.23, 1.39)], and years of schooling [OR = 1.29, 95% CI (1.21, 1.36)]. Reduced odds of having adequate health literacy were associated with higher polygenic profiles for poorer self-rated health [OR = 0.92, 95% CI (0.87, 0.98)] and schizophrenia [OR = 0.91, 95% CI (0.85, 0.96)). The well-documented associations between health literacy, cognitive function and health may partly be due to shared genetic etiology. Larger studies are required to obtain accurate estimates of SNP-based heritability and to discover specific health literacy-associated genetic variants.

Gene and environment interplay in cognition: Evidence from twin and molecular studies, future directions and suggestions for effective candidate gene x environment (cGxE) research

Last decade of molecular research in the field of cognitive science has shown that no single approach can give satisfactory results as far as gene hunt is concerned. Cohesive theory of gene-environment interaction seems to be a rational idea for bridging the gap in our knowledge of disorders involving cognitive deficit. It may even be helpful to some extent in resolving issues of missing heritability. We review the current state of play in the area of cognition at genetic and environmental fronts. Evidence of apparent gene-environment (GxE) interactions from various studies has been mentioned with the aim of redirecting the focus of research community towards studying such interactions with the help of sensitive designs and molecular techniques. We re-evaluate candidate gene-environment research in order to emphasize its potential if carried out strategically.

A statistical approach to fine-mapping for the identification of potential causal variants related to human intelligence

Genome-wide association studies (GWASs) have identified >20 genetic loci associated with human intelligence. However, due to correlations between the trait-associated SNPs, only a few of the loci are confirmed to have a true biological effect. In order to distinguish the SNPs that have a causal effect on human intelligence, we must eliminate the noise from the high degree of linkage disequilibrium that persists throughout the genome. In this study, we apply a novel PAINTOR fine-mapping method, which uses a Bayesian approach to determine the SNPs with the highest probability of causality. This technique incorporates the GWAS summary statistics, linkage disequilibrium structure, and functional annotations to compute the posterior probability of causality for all SNPs in the GWAS-associated regions. We found five SNPs (rs6002620, rs41352752, rs6568547, rs138592330, and rs28371699) with a high probability of causality, three of which have posterior probabilities >0.60. The SNP rs6002620 (NDUFA6), which is involved in mitochondrial function, has the highest likelihood of causality. These findings provide important insight into the genetic determinants contributing to human intelligence.

Assessing for interaction between APOE ε4, sex, and lifestyle on cognitive abilities

OBJECTIVE

To test for interactions between APOE ε4 genotype and lifestyle factors on worse cognitive abilities in UK Biobank.

METHODS

Using UK Biobank cohort data, we tested for interactions between APOE ε4 allele presence, lifestyle factors of alcohol intake, smoking, total physical activity and obesity, and sex, on cognitive tests of reasoning, information processing speed, and executive function (n range = 70,988-324,725 depending on the test). We statistically adjusted for potential confounders of age, sex, deprivation, cardiometabolic conditions, and educational attainment.

RESULTS

There were significant associations between APOE ε4 and worse cognitive abilities, independent of potential confounders, and between lifestyle risk factors and worse cognitive abilities; however, there were no interactions at multiple correction-adjusted p < 0.05, against our hypotheses.

CONCLUSIONS

Our results do not provide support for the idea that ε4 genotype increases vulnerability to the negative effects of lifestyle risk factors on cognitive ability, but rather support a primarily outright association between APOE ε4 genotype and worse cognitive ability.

Genomic prediction of cognitive traits in childhood and adolescence

Recent advances in genomics are producing powerful DNA predictors of complex traits, especially cognitive abilities. Here, we leveraged summary statistics from the most recent genome-wide association studies of intelligence and educational attainment, with highly genetically correlated traits, to build prediction models of general cognitive ability and educational achievement. To this end, we compared the performances of multi-trait genomic and polygenic scoring methods. In a representative UK sample of 7,026 children at ages 12 and 16, we show that we can now predict up to 11% of the variance in intelligence and 16% in educational achievement. We also show that predictive power increases from age 12 to age 16 and that genomic predictions do not differ for girls and boys. We found that multi-trait genomic methods were effective in boosting predictive power. Prediction accuracy varied across polygenic score approaches, however results were similar for different multi-trait and polygenic score methods. We discuss general caveats of multi-trait methods and polygenic score prediction, and conclude that polygenic scores for educational attainment and intelligence are currently the most powerful predictors in the behavioural sciences.

Post-traumatic stress following military deployment: Genetic associations and cross-disorder genetic correlations

BACKGROUND

Post-traumatic stress disorder (PTSD) is a complex psychiatric disorder that occurs with relatively high frequency after deployment to warzones (∼10%). While twin studies have estimated the heritability to be up to 40%, thus indicating a considerable genetic component in the etiology, the biological mechanisms underlying risk and development of PTSD remain unknown.

METHODS

Here, we conduct a genome-wide association study (GWAS; N = 2,481) to identify genome regions that associate with PTSD in a highly homogenous, trauma-exposed sample of Danish soldiers deployed to war and conflict zones. We perform integrated analyses of our results with gene-expression and chromatin-contact datasets to prioritized genes. We also leverage on other large GWAS (N>300,000) to investigate genetic correlations between PTSD and other psychiatric disorders and traits.

RESULTS

We discover, but do not replicate, one region, 4q31, close to the IL15 gene, which is genome-wide significantly associated with PTSD. We demonstrate that gene-set enrichment, polygenic risk score and genetic correlation analyses show consistent and significant genetic correlations between PTSD and depression, insomnia and schizophrenia.

LIMITATIONS

The limited sample size, the lack of replication, and the PTSD case definition by questionnaire are limitations to the study.

CONCLUSIONS

Our results suggest that genetic perturbations of inflammatory response may contribute to the risk of PTSD. In addition, shared genetic components contribute to observed correlations between PTSD and depression, insomnia and schizophrenia.

Assortative Mating on Ancestry-Variant Traits in Admixed Latin American Populations

Assortative mating is a universal feature of human societies, and individuals from ethnically diverse populations are known to mate assortatively based on similarities in genetic ancestry. However, little is currently known regarding the exact phenotypic cues, or their underlying genetic architecture, which inform ancestry-based assortative mating. We developed a novel approach, using genome-wide analysis of ancestry-specific haplotypes, to evaluate ancestry-based assortative mating on traits whose expression varies among the three continental population groups – African, European, and Native American – that admixed to form modern Latin American populations. Application of this method to genome sequences sampled from Colombia, Mexico, Peru, and Puerto Rico revealed widespread ancestry-based assortative mating. We discovered a number of anthropometric traits (body mass, height, and facial development) and neurological attributes (educational attainment and schizophrenia) that serve as phenotypic cues for ancestry-based assortative mating. Major histocompatibility complex (MHC) loci show population-specific patterns of both assortative and disassortative mating in Latin America. Ancestry-based assortative mating in the populations analyzed here appears to be driven primarily by African ancestry. This study serves as an example of how population genomic analyses can yield novel insights into human behavior.

Genetic determinants of beverage consumption: Implications for nutrition and health

Beverages make important contributions to nutritional intake and their role in health has received much attention. This review focuses on the genetic determinants of common beverage consumption and how research in this field is contributing insight to what and how much we consume and why this genetic knowledge matters from a research and public health perspective. The earliest efforts in gene-beverage behavior mapping involved genetic linkage and candidate gene analysis but these approaches have been largely replaced by genome-wide association studies (GWAS). GWAS have identified biologically plausible loci underlying alcohol and coffee drinking behavior. No GWAS has identified variants specifically associated with consumption of tea, juice, soda, wine, beer, milk or any other common beverage. Thus far, GWAS highlight an important behavior-reward component (as opposed to taste) to beverage consumption which may serve as a potential barrier to dietary interventions. Loci identified have been used in Mendelian randomization and gene×beverage interaction analysis of disease but results have been mixed. This research is necessary as it informs the clinical relevance of SNP-beverage associations and thus genotype-based personalized nutrition, which is gaining interest in the commercial and public health sectors.

Predictive Big Data Analytics using the UK Biobank Data

The UK Biobank is a rich national health resource that provides enormous opportunities for international researchers to examine, model, and analyze census-like multisource healthcare data. The archive presents several challenges related to aggregation and harmonization of complex data elements, feature heterogeneity and salience, and health analytics. Using 7,614 imaging, clinical, and phenotypic features of 9,914 subjects we performed deep computed phenotyping using unsupervised clustering and derived two distinct sub-cohorts. Using parametric and nonparametric tests, we determined the top 20 most salient features contributing to the cluster separation. Our approach generated decision rules to predict the presence and progression of depression or other mental illnesses by jointly representing and modeling the significant clinical and demographic variables along with the derived salient neuroimaging features. We reported consistency and reliability measures of the derived computed phenotypes and the top salient imaging biomarkers that contributed to the unsupervised clustering. This clinical decision support system identified and utilized holistically the most critical biomarkers for predicting mental health, e.g., depression. External validation of this technique on different populations may lead to reducing healthcare expenses and improving the processes of diagnosis, forecasting, and tracking of normal and pathological aging.

A QTL on chromosome 3q23 influences processing speed in humans

Processing speed is a psychological construct that refers to the speed with which an individual can perform any cognitive operation. Processing speed correlates strongly with general cognitive ability, declines sharply with age and is impaired across a number of neurological and psychiatric disorders. Thus, identifying genes that influence processing speed will likely improve understanding of the genetics of intelligence, biological aging and the etiologies of numerous disorders. Previous genetics studies of processing speed have relied on simple phenotypes (eg, mean reaction time) derived from single tasks. This strategy assumes, erroneously, that processing speed is a unitary construct. In the present study, we aimed to characterize the genetic architecture of processing speed by using a multidimensional model applied to a battery of cognitive tasks. Linkage and QTL-specific association analyses were performed on the factors from this model. The randomly ascertained sample comprised 1291 Mexican-American individuals from extended pedigrees. We found that performance on all three distinct processing-speed factors (Psychomotor Speed; Sequencing and Shifting and Verbal Fluency) were moderately and significantly heritable. We identified a genome-wide significant quantitative trait locus (QTL) on chromosome 3q23 for Psychomotor Speed (LOD = 4.83). Within this locus, we identified a plausible and interesting candidate gene for Psychomotor Speed (Z = 2.90, P = 1.86 × 10-03 ).

Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data

Genetic variants identified by three large genome-wide association studies (GWAS) of educational attainment (EA) were used to test a polygenic selection model. Weighted and unweighted polygenic scores (PGS) were calculated and compared across populations using data from the 1000 Genomes (n = 26), HGDP-CEPH (n = 52) and gnomAD (n = 8) datasets. The PGS from the largest EA GWAS was highly correlated to two previously published PGSs (r = 0.96–0.97, N = 26). These factors are both highly predictive of average population IQ (r = 0.9, N = 23) and Learning index (r = 0.8, N = 22) and are robust to tests of spatial autocorrelation. Monte Carlo simulations yielded highly significant p values. In the gnomAD samples, the correlation between PGS and IQ was almost perfect (r = 0.98, N = 8), and ANOVA showed significant population differences in allele frequencies with positive effect. Socioeconomic variables slightly improved the prediction accuracy of the model (from 78–80% to 85–89%), but the PGS explained twice as much of the variance in IQ compared to socioeconomic variables. In both 1000 Genomes and gnomAD, there was a weak trend for lower GWAS significance SNPs to be less predictive of population IQ. Additionally, a subset of SNPs were found in the HGDP-CEPH sample (N = 127). The analysis of this sample yielded a positive correlation with latitude and a low negative correlation with distance from East Africa. This study provides robust results after accounting for spatial autocorrelation with Fst distances and random noise via an empirical Monte Carlo simulation using null SNPs.

Population-based genome-wide association study of cognitive decline in older adults free of dementia: identification of a novel locus for the attention domain

To identify novel loci that affect cognitive decline in older adults free of dementia, we conducted genome-wide and gene-based meta-analyses on longitudinal slopes of 5 cognitive domains (memory, executive function, language, attention/processing speed, and visuospatial ability) derived from 2 population-based cohorts. For decline over time in each cognitive domain, we normalized intraindividual slopes within each cohort, accounting for baseline age, sex, and years of education. Normalized slope for each domain was used in cohort-specific genome-wide analyses after including top principal components as covariates followed by genome-wide and gene-based meta-analyses. Both analyses revealed a novel WDFY2 locus at genome-wide (p = 3.37E-08) and gene-wide (p = 7.10E-07) significance levels for the attention/processing speed domain. In the GTEx eQTL analysis, genome-wide significant single-nucleotide polymorphism was associated with RNA expression levels of WDFY2 in several brain regions: cerebellar hemisphere (p = 1.07E-04), cerebellum (p = 6.92E-04), hippocampus (p = 2.18E-03) and cortex (p = 2.29E-02), and in whole blood (p = 4.41E-05). Our results suggest that WDFY2 genetic variation may affect individual differences in decline over time on tests of attention/processing speed.

Structural and Functional Neuroimaging of Polygenic Risk for Schizophrenia: A Recall-by-Genotype-Based Approach

Risk profile scores (RPS) derived from genome-wide association studies (GWAS) explain a considerable amount of susceptibility for schizophrenia (SCZ). However, little is known about how common genetic risk factors for SCZ influence the structure and function of the human brain, largely due to the constraints of imaging sample sizes. In the current study, we use a novel recall-by-genotype (RbG) methodological approach, where we sample young adults from a population cohort (Avon Longitudinal Study of Parents and Children: N genotyped = 8365) based on their SCZ-RPS. We compared 197 healthy individuals at extremes of low (N = 99) or high (N = 98) SCZ-RPS with behavioral tests, and structural and functional magnetic resonance imaging (fMRI). We first provide methodological details that will inform the design of future RbG studies for common SCZ genetic risk. We further provide an between group analysis of the RbG individuals (low vs high SCZ-RPS) who underwent structural neuroimaging data (T1-weighted scans) and fMRI data during a reversal learning task. While we found little evidence for morphometric differences between the low and high SCZ-RPS groups, we observed an impact of SCZ-RPS on blood oxygen level-dependent (BOLD) signal during reward processing in the ventral striatum (PFWE-VS-CORRECTED = .037), a previously investigated broader reward-related network (PFWE-ROIS-CORRECTED = .008), and across the whole brain (PFWE-WHOLE-BRAIN-CORRECTED = .013). We also describe the study strategy and discuss specific challenges of RbG for SCZ risk (such as SCZ-RPS related homoscedasticity). This study will help to elucidate the behavioral and imaging phenotypes that are associated with SCZ genetic risk.

A decade in psychiatric GWAS research

After more than 10 years of accumulated efforts, genome-wide association studies (GWAS) have led to many findings, most of which have been deposited into the GWAS Catalog. Between GWAS's inception and March 2017, the GWAS Catalog has collected 2429 studies, 1818 phenotypes, and 28,462 associated SNPs. We reclassified the psychology-related phenotypes into 217 reclassified phenotypes, which accounted for 514 studies and 7052 SNPs. In total, 1223 of the SNPs reached genome-wide significance. Of these, 147 were replicated for the same psychological trait in different studies. Another 305 SNPs were replicated within one original study. The SNPs rs2075650 and rs4420638 were linked to the most replications within a single reclassified phenotype or very similar reclassified phenotypes; both were associated with Alzheimer's disease (AD). Schizophrenia was associated with 74 within-phenotype SNPs reported in independents studies. Alzheimer's disease and schizophrenia were both linked to some physical phenotypes, including cholesterol and body mass index, through common GWAS signals. Alzheimer's disease also shared risk SNPs with age-related phenotypes such as age-related macular degeneration and longevity. Smoking-related SNPs were linked to lung cancer and respiratory function. Alcohol-related SNPs were associated with cardiovascular and digestive system phenotypes and disorders. Two separate studies also identified a shared risk SNP for bipolar disorder and educational attainment. This review revealed a list of reproducible SNPs worthy of future functional investigation. Additionally, by identifying SNPs associated with multiple phenotypes, we illustrated the importance of studying the relationships among phenotypes to resolve the nature of their causal links. The insights within this review will hopefully pave the way for future evidence-based genetic studies.

Identification of common genetic risk variants for autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.

Genes, Cells and Brain Areas of Intelligence

What is the neurobiological basis of human intelligence? The brains of some people seem to be more efficient than those of others. Understanding the biological foundations of these differences is of great interest to basic and applied neuroscience. Somehow, the secret must lie in the cells in our brain with which we think. However, at present, research into the neurobiology of intelligence is divided between two main strategies: brain imaging studies investigate macroscopic brain structure and function to identify brain areas involved in intelligence, while genetic associations studies aim to pinpoint genes and genetic loci associated with intelligence. Nothing is known about how properties of brain cells relate to intelligence. The emergence of transcriptomics and cellular neuroscience of intelligence might, however, provide a third strategy and bridge the gap between identified genes for intelligence and brain function and structure. Here, we discuss the latest developments in the search for the biological basis of intelligence. In particular, the recent availability of very large cohorts with hundreds of thousands of individuals have propelled exciting developments in the genetics of intelligence. Furthermore, we discuss the first studies that show that specific populations of brain cells associate with intelligence. Finally, we highlight how specific genes that have been identified generate cellular properties associated with intelligence and may ultimately explain structure and function of the brain areas involved. Thereby, the road is paved for a cellular understanding of intelligence, which will provide a conceptual scaffold for understanding how the constellation of identified genes benefit cellular functions that support intelligence.

Genetic basis of motoric cognitive risk syndrome in the Health and Retirement Study

OBJECTIVE

To examine polygenic inheritance of motoric cognitive risk syndrome (MCR), a predementia syndrome characterized by the presence of subjective cognitive complaints and slow gait.

METHODS

We analyzed 4,915 individuals, age 65 years and above, with European ancestry (mean age 75.0 ± 6.8 years, 56.6% women) in the Health and Retirement Study. Polygenic scores (PGS) were calculated as weighted sums of the effect of single nucleotide polymorphisms, with effect sizes derived from genome-wide association studies. The association between PGSs of 9 phenotypes (general cognition, body mass index [BMI], mean arterial pressure, education, Alzheimer disease [AD], neuroticism, well-being, waist circumference, and depressive symptoms) and MCR as well as its key components (cognitive complaints and slow gait) were examined by logistic regression, adjusting for age, sex, education, and genetic ancestry, and reported as odds ratios (ORs) with 95% confidence intervals (CIs).

RESULTS

There were 260 prevalent MCR cases, 529 with slow gait, and 1,928 with subjective cognitive complaints. Higher PGSs for BMI (OR 1.22, 95% CI 1.07-1.39) and waist circumference (OR 1.23, 95% CI 1.07-1.40) were associated with MCR, and PGS of AD showed a suggestive association (OR 1.16, 95% CI 1.02-1.32). Higher PGS for neuroticism (OR 1.10, 95% CI 1.03-1.18) was associated with cognitive complaints, whereas higher well-being PGS (OR 0.92, 95% CI 0.87-0.98) was protective. PGS for BMI (OR 1.16, 95% CI 1.06-1.28), waist circumference (OR 1.19, 95% CI 1.08-1.31), and AD (OR 1.13, 95% CI 1.03-1.24) was associated with slow gait.

CONCLUSION

Obesity-related genetic traits increase risk of MCR syndrome; further investigation is required to identify potential therapeutic targets.