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Finding answers to the nature/nurture question has kept many scientific minds busy for over a century. Yet despite all of this research, the specific nature of the influences of genes and environment on human traits remains controversial. In part, this may rest on the fact that the question implies a dichotomy that in reality is a continuum of genetic-plus-environmental influence. The study of the influence of genetics on behaviour is called ‘behaviour genetics’. One of the main techniques for unravelling nature and nurture has been the study of identical (monozygotic) and non-identical (dizygotic) twins, either reared together or reared apart. Such studies require meticulous attention to detail and the recruitment of large samples of twin participants, which tends to be time-consuming. Data from twin studies are open to interpretation and have often led to controversy.

In discussing heritability, we need to distinguish between a person’s genotype and phenotype. The genotype is the part of the genetic makeup of an individual which determines their potential characteristics, for example eye colour, height, weight, general intelligence and personality traits. The phenotype is the set of observable characteristics of an individual resulting from the interaction of the genotype with the environment. A particular person’s phenotype is the sum of genetic and environmental effects:

Phenotype (P) = Genotype (G) + Environment (E)

Likewise, the phenotypical variance in the trait – Var (P) – is the sum of effects, as follows:

Var(P) = Var(G) + Var(E) + 2 Cov(G,E)

In a planned experiment Cov(G,E) can be controlled and held at 0. In this case, heritability, H2, is defined as:

H2 = Var(G)/Var(P)

An H2 estimate is the proportion of trait variation among individuals that is a consequence of genetic factors; it is not the degree of genetic influence on that trait in any particular individual. For example, if the heritability of personality traits is .60, we can not say that 60% of an individual’s personality is inherited from her/his parents and 40% from the environment. In most usual circumstances, the proportions of genetic and environmental influence for any individual and trait are unknown. In rare cases, when there is an autosomal dominant condition such as Huntington’s disease (1 in 15,000 births) or familial hypercholesterolemia (1 in 500 births), then there is a 50% chance of inheritance in each new birth, providing there is only one affected parent.

There has been a large amount of research using the monozygotic versus dizygotic twin design. Polderman et al. (2015) reported a mammoth meta-analysis of twin correlations with variance estimates for 17,804 traits from 2,748 publications based on 14,558,903 partly dependent twin pairs, i.e., virtually all published twin studies of complex traits. Estimates of heritability were found to cluster strongly within different functional domains. Across all traits the reported, heritability was 49%, indicating an almost exactly equal contribution of genes and environment. For 69% of traits, the observed twin correlations were consistent with a simple, parsimonious model in which twin resemblance is solely due to additive genetic variation (Figure 3.5). The authors concluded that the dataset was ‘inconsistent with substantial influences from shared environment or non-additive genetic variation’ (Polderman et al., 2015). In other words, nurture and nature were independent and equal contributors to individual differences in traits.

Figure 3.5 Twin correlations and heritabilities for all human traits studied

(a) Distribution of rMZ and rDZ estimates across the traits investigated in 2,748 twin studies published between 1958 and 2012. rMZ estimates are based on 9,568 traits and 2,563,628 partly dependent twin pairs; rDZ estimates are based on 5,220 traits and 2,606,252 partly dependent twin pairs. (b) Relationship between rMZ and rDZ, using all 5,185 traits for which both were reported

Source: Reproduced by permission from Polderman et al. (2015)

On the basis of the Polderman et al. (2015) study, it can be concluded that nature and nurture are of equal importance in determining human abilities and character. However, the relative proportions of influence differ from 50:50 for specific functions and characteristics. The largest heritability estimates were for traits in the ophthalmological domain (H2 = 0.71, s.e.m. = 0.04), followed by the ear, nose and throat (H2 = 0.64, s.e.m. = 0.06), dermatological (H2 = 0.60, s.e.m. = 0.04) and skeletal (H2 = 0.60, s.e.m. = 0.02) domains. The lowest heritability estimates were found for traits in the environmental, reproductive and social value domains (Polderman et al., 2015). Nature is more important for structural and anatomical differences, while nurture has greater influence on psychological and social differences.

One example of a psychological variable is emotional overeating (EOE), the tendency to eat more in response to negative emotions. Herle et al. (2017) examined the relative genetic and environmental influences on EOE in toddlerhood and early childhood in 2,402 British twins born in 2007. Genetic influences on EOE were found to be minimal, while shared environmental influences explained most of the variance. Herle et al. (2017) stated that EOE is ‘moderately stable from 16 months to 5 years and continuing environmental factors shared by twin pairs at both ages explained the longitudinal association’.

A new approach to the study of nature and nurture has been the genome-wide association studies (GWAS). GWAS examine a genome-wide set of genetic variants in a large sample of individuals to see whether any variant is associated with a trait. GWAS typically focus on associations between single nucleotide polymorphisms (SNPs, pronounced ‘snips’) and traits or major human diseases. A SNP is a DNA sequence variation occurring when a single nucleotide adenine (A), thymine (T), cytosine (C) or guanine (G) in the genome (or other shared sequence) differs between individuals or between paired chromosomes in an individual. SNPs occur throughout a person’s DNA once in every 300 nucleotides on average, which means there are roughly 10 million SNPs in one human genome. Most commonly, SNP variations are found in the DNA lying between genes.

One approach in GWAS is the case-control design, which compares two large groups of individuals, one healthy control group and one case group affected by a disease. Initially, all individuals are genotyped for commonly known SNPs. The exact number of SNPs varies but is typically 1 million or more. For each SNP, the investigators examine whether the allele frequency is significantly altered between the case and the control group. The statistic for reporting effect sizes is the odds ratio, the ratio of disease for individuals having a specific allele and the odds of disease for individuals who do not have that allele. A p-value is calculated using a chi-squared test. An odds ratio that departs significantly from 1.0 indicates that a SNP is associated with disease.

In spite of the precision of the method, GWAS findings have been disappointing. There is a lack of consistency in findings across studies and the amount of variance explained in traits or diseases is very low. For example, known SNPs explain less than 2% of the variation in body mass index (BMI) despite the evidence of greater than 50% heritability from twin and family studies, a phenomenon termed ‘missing heritability’. Llewellyn et al. (2013) used a novel method (Genome-wide Complex Trait Analysis, GCTA) to estimate the total additive genetic influence due to common SNPs on whole-genome arrays. This study provided the first GCTA estimate of genetic influence on adiposity in children. Participants were from the Twins Early Development Study (TEDS), a British twin birth cohort. Selecting one child per family (n = 2,269), GCTA results from 1.7 million DNA markers were used to quantify the additive genetic influence of common SNPs. For direct comparison, a standard twin analysis in the same families estimated the additive genetic influence as 82%. GCTA explained 30% of the variance in BMI-SDS. These results indicate that 37% of the twin-estimated heritability (30/82%) were explained by additive effects of multiple common SNPs, which is indicative of a strong genetic influence on adiposity in childhood. To fully explain this ‘missing heritability’, larger sample sizes are required to improve statistical power. Also, most variants that are associated with obesity from current GWAS are correlational, not causative (Xia and Grant, 2013).

In discussing obesity, Marti and Ordovas (2011: 190) reflected on the lack of progress on the tenth anniversary of the publications that reported the initial human genome sequence: ‘It was stated that the complete genome sequence would “revolutionize the diagnosis, prevention, and treatment of most, if not all, human diseases.” Whereas this is probably true, the question remains about “when” and “how”’. Ten years later the situation remains the same, and it is apparent that the human genome project has yet to reach its full potential. New approaches are required to identify the causative genes for the late onset and progressive nature of most common diseases, complex traits, and the mechanism by which the environment can modulate genetic predisposition to commonly occurring diseases.