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Good Genes Come in Packages

IdealMaxilla

IdealMaxilla

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Nov 8, 2017
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That meme you saw from Hollywood of ugly incels being smart and robust jocks being dumb - false. 

The genetically superior are superior in ALL ways. Height. symmetry and intelligences are directly correlated. 

Health indicators = superior human bean.
 
Look at Dolph Lundgren. High IQ, insane bones, tall, thick hairline.
 
Most of then the time, yes. But I have seen this stereotype reflected accurately in the real world a few times.

Mostly, intelligence is just a genetic mistake of nature and doesn’t really matter to the human race at all. This is why femoids don’t care about intelligence.
.
 
wot

i have good eye area but bird bones

explain pls
 
It isn't difficult to understand how it was determined.

1698414181600

1698414194312
 
We'll start from the duller half:

1698414279444

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1698414527751

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...

1698414582736

1698414590489


...

We conduct a large-scale genetic association analysis of educational attainment in a sample of ~1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of ~0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11–13% of the variance in educational attainment and 7–10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.


Educational attainment (EA) is moderately heritable1 and an important correlate of many social, economic, and health outcomes2,3. Because of its relationship with many health outcomes, measures of EA are available in most medical data sets. Partly for this reason, EA was the focus of the first large-scale genome-wide association study (GWAS) of a social-science phenotype4 and has continued to serve as a “model phenotype” for behavioral traits (analogous to height for medical traits). Genetic associations with EA identified via GWAS have been used in follow-up work examining biologizcal5 and behavioral mechanisms6,7 and genetic overlap with health outcomes8,9.

The largest (N = 293,723) GWAS of EA to date identified 74 approximately independent SNPs at genome-wide significance (hereafter, lead SNPs) and reported that a 10-million-SNP linear predictor (hereafter, polygenic score) had an out-of-sample predictive power of 3.2%10. Here, we expand the sample size to over a million individuals (N = 1,131,881). We identify 1,271 lead SNPs. In a subsample (N = 694,894), we also conduct genome-wide association analyses of variants on the X chromosome, identifying ten lead SNPs.

The dramatic increase in our GWAS sample size enables us to conduct a number of informative additional analyses. For example, we show that the lead SNPs have heterogeneous effects, and we perform within-family association analyses that probe the robustness of our results. Our biological annotation analyses, which focus on the results from the autosomal GWAS, reinforce the main findings from earlier GWAS in smaller samples, such as the role of many of the prioritized genes in brain development. However, the newly identified SNPs also lead to several new findings. For example, they strongly implicate genes involved in almost all aspects of neuron-to-neuron communication.

Rs176218EA


1000Genomes_30x Global Study-wide6404G=0.7313T=0.2687
1000Genomes_30x African Sub1786G=0.8303T=0.1697
1000Genomes_30x Europe Sub1266G=0.8104T=0.1896
1000Genomes_30x South Asian Sub1202G=0.7180T=0.2820
1000Genomes_30x East Asian Sub1170G=0.4265T=0.5735
1000Genomes_30x American Sub980G=0.829T=0.171
Rs9307160M

 
1698414942024


...



Intelligence in childhood, as measured by psychometric cognitive tests, is a strong predictor of many important life outcomes, including educational attainment, income, health and lifespan. Results from twin, family and adoption studies are consistent with general intelligence being highly heritable and genetically stable throughout the life course. No robustly associated genetic loci or variants for childhood intelligence have been reported. Here, we report the first genome-wide association study (GWAS) on childhood intelligence (age range 6–18 years) from 17 989 individuals in six discovery and three replication samples. Although no individual single-nucleotide polymorphisms (SNPs) were detected with genome-wide significance, we show that the aggregate effects of common SNPs explain 22–46% of phenotypic variation in childhood intelligence in the three largest cohorts (P=3.9 × 10−15, 0.014 and 0.028). FNBP1L, previously reported to be the most significantly associated gene for adult intelligence, was also significantly associated with childhood intelligence (P=0.003). Polygenic prediction analyses resulted in a significant correlation between predictor and outcome in all replication cohorts. The proportion of childhood intelligence explained by the predictor reached 1.2% (P=6 × 10−5), 3.5% (P=10−3) and 0.5% (P=6 × 10−5) in three independent validation cohorts. Given the sample sizes, these genetic prediction results are consistent with expectations if the genetic architecture of childhood intelligence is like that of body mass index or height. Our study provides molecular support for the heritability and polygenic nature of childhood intelligence. Larger sample sizes will be required to detect individual variants with genome-wide significance.

1698416319822


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Rs7291469CI

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That explains why I am low iq.
 
We'll start from the duller half:

View attachment 919623
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View attachment 919626View attachment 919627
View attachment 919628

...

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View attachment 919631

1000Genomes_30x Global Study-wide6404G=0.7313T=0.2687
1000Genomes_30x African Sub1786G=0.8303T=0.1697
1000Genomes_30x Europe Sub1266G=0.8104T=0.1896
1000Genomes_30x South Asian Sub1202G=0.7180T=0.2820
1000Genomes_30x East Asian Sub1170G=0.4265T=0.5735
1000Genomes_30x American Sub980G=0.829T=0.171
View attachment 919632
23andMe, Ancestry.com or MyHeritageDNA for south Asian descent?
 
Ahhhh intellau necroposting
 

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