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Height prediction based on genetics

Height prediction based on genetics



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My height, as predicted by my genetics, is 156 cm whereas my actual height is 172 cm. What could be the reasons for this substantial discrepancy? Does it just mean I had very good nutrition as a child?


Sources of phenotypic variance

There is phenotypic variance in height in the human population. This phenotypic variance is in part explained by genetic variation, but there are also non-genetic variations, incl environmental variation (what you eat, your physical activity among many other things). See this post for more information.

Sampling error

On top of that, those measures of "genetic height" are based upon a limited number of SNPs and a limited number of individuals sampled. There is therefore a bit of room for a little bit of sampling error here. Note sampling error is not a mistake. It is just the fact that parameters estimated from a sample don't necessarily match perfectly the population parameters.

Training data set

Finally, the estimate is based upon correlation made from previous people. There might have a generational gap in height, typically present in countries that have recently largely changed their diets, such as many Asian countries.

For all of the above reasons, there might have a gap between your actual height and what has been predicted by some genetic testing. In short, yes your nutrition might part of the reason for this gap.


Children's Adult Height Predictor

Its good that you are so eager to know about the growth of your baby. Many a times this has been quite a concern for many parents who feel that their child is avoiding food all the time. And height being one measure to check growth, we provide you with an accurate height calculator that can preditct the required height for your child at his age. Based on the results you can see if your child has over grown or is not having the height for his age. This would give you the idea whether its time for you to meet your pediatrician.

Its true that height in determined by genetic factors, but also nutrition can play a major role in this. So it will be advisable that you meet your pediatrician on time.

This online height predictor makes use of parents height as input and also the age of the baby. Thus providing the accurate results on the heigh of your child.

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Scientific journal articles for further reading

Lango Allen H, Estrada K, Lettre G, et al. Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature. 2010 Oct 14467(7317):832-8. doi: 10.1038/nature09410. Epub 2010 Sep 29. PubMed: 20881960. Free full-text available from PubMed Central: PMC2955183.

Marouli E, Graff M, Medina-Gomez C, Lo KS, et al. Rare and low-frequency coding variants alter human adult height. Nature. 2017 Feb 9542(7640):186-190. doi: 10.1038/nature21039. Epub 2017 Feb 1. PubMed: 28146470. Free full-text available from PubMed Central: PMC5302847.

McEvoy BP, Visscher PM. Genetics of human height. Econ Hum Biol. 2009 Dec7(3):294-306. doi: 10.1016/j.ehb.2009.09.005. Epub 2009 Sep 17. PubMed: 19818695.

Perola M. Genome-wide association approaches for identifying loci for human height genes. Best Pract Res Clin Endocrinol Metab. 2011 Feb25(1):19-23. doi: 10.1016/j.beem.2010.10.013. PubMed: 21396572.


This calculator uses the parents' height only. It can be used to predict the future heights of unborn children or very young infants.

The following converter can be used to convert the body height between the metric unit and the unit used in the United States.

How tall will I be?

"How tall will I be?" or "how tall will my child be?" are questions that are often asked. The height of a person is determined by a combination of genetics and environmental factors. The precise contribution from these two factors is complex. Some studies suggest that genetics contributes 60%-80%. Normally, a child's height is based on parental heights subject to regression toward the mean. This means that very tall or short parents are likely to have a taller or shorter child than average, but the child is likely to be closer to the average height than their parents.

Other important factors that contribute to a child's adult height include nutrition, health, sports activities, health and age of the mother during pregnancy, etc.

Infants and toddlers grow the fastest. The growth rate declines rapidly from birth to roughly age 2 and declines more slowly thereafter. During puberty, growth rate increases again to a second maximum, after which it slowly declines to zero. This is typically referred to as the pubertal growth spurt. On average, female and male growth trails off to zero at about 15 and 18 years old, respectively.

In some cases, a person's height begins to shrink in middle age, though shrinkage of stature is largely universal in the very elderly. This is due to factors such as decreased height of intervertebral discs as well as changes due to degenerative diseases.

Predicting a child's adult height

Many different methods have been developed to predict a child's adult height, some more accurate than others. Regardless how accurate the method, height prediction is not an exact science, and it is possible that a child's height can deviate significantly from what is predicted.

Bone age, skeletal maturity method

Bone age can be used to predict height and is considered more accurate than the other methods listed below. One such method is the Greulich-Pyle method that involves left hand and wrist radiographs to measure bone age. This method compares the radiograph of the patient to that of the nearest standard radiograph in the Greulich-Pyle atlas, a compilation of bone age data. Based on bone age, the height of the child, and the data compiled in the atlas, it is possible to predict height based on the percentage of height growth remaining at a given bone age. Note that the data in the atlas were obtained between 1931 and 1942 from Caucasian children, which may limit how accurately the Greulich-Pyle method can be used for current children. 1

The Khamis-Roche method 2

The Khamis-Roche method is considered to be one of the more accurate height prediction methods that do not require the measurement of bone age. It is based on the child's stature, weight, and the average stature of the two parents. The first calculator above is mainly based on this method.

Note that it is most applicable to Caucasian children between the ages of 4 and 9 who are free from any growth-related condition or disease.

CDC Growth Charts of the United States are good sources of information to evaluate the growth situation of a child. These growth charts consist of percentile curves illustrating the distribution of specific body measurements of children in the United States. In total, there are 16 charts that contain data that can be used to compare the growth of a child over time. Measurements such as height, weight, and head circumference of a child can be compared to the expected values based on data from these growth charts of children of the same age and sex. In general, children maintain a fairly constant growth curve, which is why these charts can be used to predict the adult height of a child to a certain extent.

There are also some very simple, but less accurate, methods available. One of them is adding 2.5 inches (7.6 cm) to the average of the parent's height for a boy and subtracting 2.5 inches (7.6 cm) for a girl. The second calculator above is based on this method.

Another simple method is to double the height achieved by the child by age 2 for a boy, or age 18 months for girl.

How to get taller?

Height, for better or for worse, is largely (60-80%) determined by genetics. As mentioned above, very tall parents are more likely to have a taller child, while very short parents are more likely to have a shorter child, with the child being more likely than their parents to be closer to average height. After the growth spurt during puberty, which differs slightly for girls and boys, neither will typically grow much more, and girls typically stop growing by 15, while boys stop at around 18 years of age.

That being said, there are environmental factors that can affect the height of a child. Some of these may be within the control of the child, while many may not. Nutrition and health of the mother during pregnancy can affect the height of their unborn child. Nutrition as well as exercise after birth can also affect height.

Recommendations for providing the best conditions for your body to grow follow typical guidelines for healthy living (in no particular order):

  1. Eat as much unprocessed foods as possible such as fresh fruits, vegetables, whole grains, proteins, and dairy.
  2. Avoid eating foods that are high in sugar, trans fats, saturated fats, and sodium.
  3. Exercise regularly to strengthen bones and muscles, maintain a healthy weight, and reduce the risk of diseases such as osteoporosis and other issues that could arise from poor health, that could in turn affect growth and height.
  4. Pay attention to good posture. Aside from looking shorter due to poor posture, it can affect actual height in the long term if the back starts curving to accommodate a regular slouching posture.
  5. Sleep regularly. Human growth hormone, a factor that affects growth, is released while you sleep. A regularly poor sleeping schedule during adolescence can affect growth in the long term. How much a person should sleep is dependent on their age, with more sleep being recommended the younger the child is.

In fringe cases, it is possible that some disease or condition could be hampering your growth, and it is possible that a doctor may be able to assist you in such a case, which may in turn affect height. For the most part however, peak height is reached by the time a child has gone through puberty, and it is likely that any child past puberty will maintain their height throughout adulthood.


Other methods for predicting a child's adult stature

A number of methods for height prediction relying on examinations of skeletal structure are often used by pediatricians, for example the Bayley-Pinneau [2] , the Roche-Wainer-Thissen RWT [3] and the Tanner-Whitehouse 3 method [4] . However, all these methods are subject to a wide range of error, at least partly because of the use of bone age estimations. Determination of skeletal age is relatively subjective, with a high interobserver error rate, and the relationship of skeletal age to chronologic age has been shown to differ among various ethnic groups [1] . While methods for automated bone age determination were proposed in recent years, they still require a visit to the doctor, unlike the multiplicator method.

Most online height calculators tend to use the Khamis-Roche prediction equations [5] or estimations based on the height of the mid-parent. The Khamis-Roche method has slightly larger errors than those for the Roche-Wainer-Thissen method and it requires more data than our approach using multipliers. Furthermore, the applicability of the Khamis-Roche method is limited to white American children only [5] , making it unsuitable for a height predictor intended for wider application.

The mid-parent height method suffers from an issue wherein if parents are unusually tall or short, their children would be relatively less tall or short, respectively, and the mid-parental height is then a poor predictor of attained height [6] and would thus provide a poor answer to the question many adolescent boys and girls ask themselves: how tall will i grow up to be?


Background

The processes that lead humans to choose a particular mate and the extent to which these choices are governed by genes or environment have been widely debated. Here, we use 32,000 human couples and height as a model trait of human attractiveness to shed light onto these processes.

Height is a model quantitative trait that is determined by the interplay of large numbers of genetic and environmental factors. Narrow-sense heritability for height, which measures the relative importance of additive genetic factors and environmental factors in the expression of a trait, has been consistently estimated to be high, typically around 0.8 [1, 2]. Height has been associated with numerous diseases such as cancers [3], dementia death [4], and coronary artery disease [5]. However, all these associations, whether genetically or environmentally determined, are poorly understood.

The correlation in height between members of a couple is much larger than that expected by chance [6–10]. This indicates that humans tend to be attracted to mates that have a similar height to their own. Understanding this behaviour is sociologically important, but it is also biologically important. The consequences of assortative mating at the genetic level depend on the correlation among the breeding (or additive genetic) values of the mates. Assortative mating increases both the genetic and phenotypic variance compared to that observed in a random mating population [1] and plays a crucial role in shaping the genome structure of the population (i.e. how alleles are assorted) through increased coupling of alleles with positive or negative effects on the trait. Furthermore, because height is a highly polygenic trait [11], with hundreds of genes of small effect scattered across the genome contributing to its variation, it is possible that the build-up of directional linkage disequilibrium (LD) that arises from assortative mating impacts not only on the genetic architecture of height but also on that of many other complex traits. Despite its importance, the forces that drive mate choice for height and other traits are as yet unknown. To address this, we took height as a model trait and estimated to what degree mate height choice is genetically determined, and to what degree genes that contribute to one’s height are the same as those that affect individual preferences for mate height.


Child height predictors

The child height calculator uses a series of formulas and statistical data to predict a child&rsquos adult height based on 6 simple variables (child&rsquos gender, age, height and weight, mother and father&rsquos heights).

A second method that can be used is the gender-specific mid-parental three step method:

■ The first step is to add the parental heights together (whether provided in inches or centimeters).

Mid-parental height = (mother&rsquos height + father&rsquos height) / 2

■ The second step is to add to the value obtained at step 1, either 5 inches (13cm) if the child&rsquos gender is male or subtract 5 inches if the gender of the child is female.

■ The third step is to divide the value obtained at the second step by two, which finds the end results &ndash the child&rsquos future adult predicted height.

Girls Height Formula = (Mid-parental height &ndash 5 inches) / 2

Boys Height Formula = (Mid-parental height + 5 inches) / 2

Whilst height predictors can estimate a future adult height to a degree of accuracy, ultimately the rhythm in which children develop is determined by genetic and environmental factors, general health, nutrition and level of exercise during childhood, factors which cannot be completely accounted for in a model.

1. Genetic determination &ndash child&rsquos adult height linked to that of the mother and father

2. Nutrition &ndash a child with a nutritiously rich diet during childhood and adolescence will develop harmoniously

3. Hormone influence &ndash with specific importance of the thyroid and growth hormones

4. Exercise levels &ndash children who practice sports tend to develop better than their non-exercising peers

5. Genetic conditions &ndash some syndromes impact on height growth

6. Corticosteroid medications &ndash can also affect rate of growth.


Meta-analysis of genome-wide association studies for height and body mass index in ∼700000 individuals of European ancestry

Recent genome-wide association studies (GWAS) of height and body mass index (BMI) in ∼250000 European participants have led to the discovery of ∼700 and ∼100 nearly independent single nucleotide polymorphisms (SNPs) associated with these traits, respectively. Here we combine summary statistics from those two studies with GWAS of height and BMI performed in ∼450000 UK Biobank participants of European ancestry. Overall, our combined GWAS meta-analysis reaches N ∼700000 individuals and substantially increases the number of GWAS signals associated with these traits. We identified 3290 and 941 near-independent SNPs associated with height and BMI, respectively (at a revised genome-wide significance threshold of P < 1 × 10-8), including 1185 height-associated SNPs and 751 BMI-associated SNPs located within loci not previously identified by these two GWAS. The near-independent genome-wide significant SNPs explain ∼24.6% of the variance of height and ∼6.0% of the variance of BMI in an independent sample from the Health and Retirement Study (HRS). Correlations between polygenic scores based upon these SNPs with actual height and BMI in HRS participants were ∼0.44 and ∼0.22, respectively. From analyses of integrating GWAS and expression quantitative trait loci (eQTL) data by summary-data-based Mendelian randomization, we identified an enrichment of eQTLs among lead height and BMI signals, prioritizing 610 and 138 genes, respectively. Our study demonstrates that, as previously predicted, increasing GWAS sample sizes continues to deliver, by the discovery of new loci, increasing prediction accuracy and providing additional data to achieve deeper insight into complex trait biology. All summary statistics are made available for follow-up studies.

Figures

Manhattan plot showing association statistics…

Manhattan plot showing association statistics of association between SNPs and height (A) or…

Regression of SNPs effect estimated…

Regression of SNPs effect estimated from the meta-analysis of GWAS of height in…

Variance explained and prediction accuracy…

Variance explained and prediction accuracy (squared correlation between trait value and its predictor…


Author information

Yurii S Aulchenko and Maksim V Struchalin: These authors contributed equally to the work.

Affiliations

Department of Epidemiology and Biostatistics and Clinical Genetics, Erasmus MC, Rotterdam, The Netherlands

Yurii S Aulchenko, Maksim V Struchalin, Albert Hofman, Ben A Oostra, Cornelia M van Duijn & A Cecile J W Janssens

Laboratory of Recombination and Segregation Analysis, Institute of Cytology and Genetics SD RAS, Novosibirsk, Russia

Yurii S Aulchenko, Nadezhda M Belonogova, Tatiana I Axenovich & Pavel M Borodin

Department of Forensic Molecular Biology, Erasmus MC, Rotterdam, The Netherlands

Maksim V Struchalin & Manfred Kayser

Department of Cytology and Genetics, Novosibirsk State University, Novosibirsk, Russia

Nadezhda M Belonogova & Pavel M Borodin

Department of Genetics of Complex Traits and Diabetes Genetics, Peninsula College of Medicine and Dentistry, Exeter, UK


Two Years Times Two Method

The "two years times two" method for predicting your child's future height is as easy as it sounds. The drawback is that you need to wait until they are 2 years old or find the measurements you took then. This method has been used for a long time, though no research is available to back up its accuracy.  

To predict your child's height with this method:

  1. Figure out how tall your child is or was when she was two years old.
  2. Multiply that height by two.

The result is her predicted height.

For example, if your daughter is 34 inches tall when she is 2 years old, it is possible for her to be 68 inches (5 feet 8 inches) tall as an adult. The equation is: 34 inches x 2 = 68 inches.

The American Academy of Pediatrics points out that girls develop quicker than boys. Due to this, you might get a more accurate prediction for your daughter by using her height at 18 months.