DNA Test maybe used to determine intelligence in children up to 16.

[Secure Da Bag]

These tests aren't new. They've been talked about as early as 2011. Though the test themselves have interesting applications in being used to determine learning difficulties, the most immediate concern is if they'll be used to discriminate and segregate children. Will such a test actually provide better learning and education facilities or just be the equivalent of Special Ed/Learning classes (used to deal with children who don't follow the status quo)? Will these tests be used justify the old myths of race and inherit intelligence? Or the justify the nature vs nurture debates?

Intelligence tests highlight importance of genetic differences
DNA test could reveal how you will do in exams according to King's College scientists | Daily Mail Online
DNA tests can predict intelligence, scientists show for first time
DNA tests can predict intelligence, scientists show for first time

 

[Starman]

Comes closer everyday. And yes this will be used to discriminate if the law allows it. Hell maybe even if it doesn't. Companies or schools will find a way to get DNA samples.

 

[newworldafro]

Comes closer everyday. And yes this will be used to discriminate if the law allows it. Hell maybe even if it doesn't. Companies or schools will find a way to get DNA samples.

They will use it on anything they can manipulate or have data points to segregate clients or possible consumers.....insurance, credit, banking, etc.

 

[Koichos]

Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence: (Sniekers et al., 2017)

Abstract
Intelligence is associated with important economic and health-related life outcomes1. Despite intelligence having substantial heritability2(0.54) and a confirmed polygenic nature, initial genetic studies were mostly underpowered3,4,5. Here we report a meta-analysis for intelligence of 78,308 individuals. We identify 336 associated SNPs (METAL P < 5 × 10−8) in 18 genomic loci, of which 15 are new. Around half of the SNPs are located inside a gene, implicating 22 genes, of which 11 are new findings. Gene-based analyses identified an additional 30 genes (MAGMA P < 2.73 × 10−6), of which all but one had not been implicated previously. We show that the identified genes are predominantly expressed in brain tissue, and pathway analysis indicates the involvement of genes regulating cell development (MAGMA competitive P = 3.5 × 10−6). Despite the well-known difference in twin-based heritability2 for intelligence in childhood (0.45) and adulthood (0.80), we show substantial genetic correlation (rg = 0.89, LD score regression P = 5.4 × 10−29). These findings provide new insight into the genetic architecture of intelligence.

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A genome-wide association study for extremely high intelligence: (Zabaneh et al., 2017)

Abstract
We used a case–control genome-wide association (GWA) design with cases consisting of 1238 individuals from the top 0.0003 (~170 mean IQ) of the population distribution of intelligence and 8172 unselected population-based controls. The single-nucleotide polymorphism heritability for the extreme IQ trait was 0.33 (0.02), which is the highest so far for a cognitive phenotype, and significant genome-wide genetic correlations of 0.78 were observed with educational attainment and 0.86 with population IQ. Three variants in locus ADAM12 achieved genome-wide significance, although they did not replicate with published GWA analyses of normal-range IQ or educational attainment. A genome-wide polygenic score constructed from the GWA results accounted for 1.6% of the variance of intelligence in the normal range in an unselected sample of 3414 individuals, which is comparable to the variance explained by GWA studies of intelligence with substantially larger sample sizes. The gene family plexins, members of which are mutated in several monogenic neurodevelopmental disorders, was significantly enriched for associations with high IQ. This study shows the utility of extreme trait selection for genetic study of intelligence and suggests that extremely high intelligence is continuous genetically with normal-range intelligence in the population.

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Genome-wide association study identifies 74 loci associated with educational attainment: (Okay et al., 2016)

Abstract
Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals1 . Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Singlenucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases

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Predicting educational achievement from DNA: (Krapohl et al., 2016)

Abstract
A genome-wide polygenic score (GPS), derived from a 2013 genome-wide association study (N=127,000), explained 2% of the variance in total years of education (EduYears). In a follow-up study (N=329,000), a new EduYears GPS explains up to 4%. Here, we tested the association between this latest EduYears GPS and educational achievement scores at ages 7, 12 and 16 in an independent sample of 5825 UK individuals. We found that EduYears GPS explained greater amounts of variance in educational achievement over time, up to 9% at age 16, accounting for 15% of the heritable variance. This is the strongest GPS prediction to date for quantitative behavioral traits. Individuals in the highest and lowest GPS septiles differed by a whole school grade at age 16. Furthermore, EduYears GPS was associated with general cognitive ability (~3.5%) and family socioeconomic status (~7%). There was no evidence of an interaction between EduYears GPS and family socioeconomic status on educational achievement or on general cognitive ability. These results are a harbinger of future widespread use of GPS to predict genetic risk and resilience in the social and behavioral sciences.

Discussion
Our results show that DNA can be used to predict educational achievement, especially at the end of the compulsory school years. Although the 2016 EduYears GPS accounted for ~4% of the variance in the GWA target trait of years of education in independent samples, we found that the 2016 EduYears GPS accounted for 9% of the variance in educational achievement at age 16, tripling the effect size from previous reports13 based on the 2013 EduYears GPS.9 The predictive power of EduYears GPS can be seen especially at the extremes of the distribution of GPS scores, suggesting that it is possible to identify individuals early in life at genetic risk and resilience, moving us closer to the possibility of early intervention and personalized learning.37

We have previously reported a heritability estimate of 60% for educational achievement at age 16 using a sample from which the present sample was drawn.14 The present study demonstrated that EduYears GPS predicts 9% of the total variance in educational achievement, thus accounting for only 15% of the heritability estimated by the twin design. However, unlike twin study estimates of heritability, GPS is derived from GWA studies, which are limited to additive effects of the common variants employed on SNP arrays. For this reason, SNP-based estimates of heritability, which have these same limitations, represent the current upper limit for GPS prediction. For educational achievement, SNP-based estimates of heritability are about 30%,13 and EduYears GPS explains almost one-third of the heritable variance from SNP-based studies at age 16.

We believe that the substantial increase in heritability explained by the 2016 EduYears GPS represents a turning point in the social and behavioral sciences because it makes it possible to predict educational achievement for individuals directly from their DNA. Although other variables account for more of the variance of educational achievement, DNA has a unique predictive status in that inherited DNA sequence variation does not change from the single cell with which life begins. For this reason, unlike the case with many other predictors, the correlation between EduYears GPS and educational attainment cannot feasibly be interpreted in terms of reverse causation. That is, the correlation between EduYears GPS and educational achievement cannot be caused by the effect of educational achievement on inherited DNA sequence variation. In contrast, although g predicts much more of the variance of educational achievement at age 16 (29% in our study), this correlation could be confounded by factors related to both educational achievement and g, such as social and family risk factors. Similarly, educational achievement at age 7 predicts 35% of the variance of educational achievement at age 16 but this correlation could also be due to other factors, including genetics,14 that affect educational achievement at both ages.

 

[Professor Emeritus]

Some of those titles are WAY overexaggerating the results.

They are predicting less than 10% of the variance. That means 90% is unaccounted for.

Adoption studies, Flynn effect, dropout studies, etc. have all already well proven that most of our intellectual achievement cannot be explained by DNA alone.

 

[el_oh_el]

Some of those titles are WAY overexaggerating the results.

They are predicting less than 10% of the variance. That means 90% is unaccounted for.

Adoption studies, Flynn effect, dropout studies, etc. have all already well proven that most of our intellectual achievement cannot be explained by DNA alone.

...cause the last thing this fukkin planet needs is MORE discrimination..backed by science, no less. It would be disastrous for many

 

[Koichos]

Comes closer everyday. And yes this will be used to discriminate if the law allows it. Hell maybe even if it doesn't. Companies or schools will find a way to get DNA samples.

The Wonderlic Personnel Test is more than apt to asses a prospective employee's cognitive ability, given its strong correlation with that of the Wechsler.

 

[Mowgli]

Cacs will move onto eugenics.

The faggits racism