Multifactorial Traits: Genes and Environmental Interactions PDF

Multifactorial traits: How genes and the environment mold traits  A trait can be described as either single-gene (Mendelian or monogenic) or polygenic. Polygenic trait reflects the activities of more than one gene. Single-gene and polygenic traits can also be multifactorial, which means they a...

Multifactorial traits: How genes and the environment mold traits  A trait can be described as either single-gene (Mendelian or monogenic) or polygenic. Polygenic trait reflects the activities of more than one gene. Single-gene and polygenic traits can also be multifactorial, which means they are influenced by the environment. Purely polygenic traits—those not influenced by the environment at all—are very rare. Eye color is close to being purely polygenic. Polygenic multifactorial traits include such common traits as height, skin color, body weight, many illnesses, and behavioral conditions and tendencies. Behavioral traits are not inherently different from other types of traits; they involve the functioning of the brain, rather than another organ. The genes of a multifactorial trait are not more complicated than others. They follow Mendel’s laws but contribute only partly to a trait and are therefore more difficult to track. A polygenic multifactorial condition reflects additive contributions of several genes. Each gene confers a degree of susceptibility, but the input of these genes is not necessarily equal. Genes may contribute different parts of a phenotype that was once thought to be due to the actions of a single gene. Examples: Lung cancer risk genetic and environmental factors contribute to lung cancer risk. mutations raise lung cancer risk in several ways: impairing DNA repair, promoting inflammation, blocking detoxification of carcinogens, keeping telomeres long, promoting addiction, etc. These genetic risk factors interact with each other and with environmental influences, such as smoking and breathing polluted air. Migraine a gene on chromosome 1 contributes sensitivity to sound a gene on chromosome 5 produces the pulsating headache and sensitivity to light a gene on chromosome 8 is associated with nausea and vomiting. environmental influences trigger migraine in some people, such as eating certain foods. Genetic test panels detect alleles of genes that contribute risk to developing cardiovascular disease. 50 genes regulate blood pressure > 95 contribute to inherited variation in blood cholesterol and triglyceride levels Polygenic Traits Are Continuously Varying For a polygenic trait, the combined action of many genes often produces a “continuously varying” phenotype, also called a quantitative trait. DNA sequences that contribute to polygenic traits are called quantitative trait loci, or QTLs. A multifactorial trait is continuously varying if it is also polygenic. it is the multi-gene component of the trait that contributes the continuing variation of the phenotype. the individual genes that confer a polygenic trait follow Mendel’s laws, but together they do not produce single-gene phenotypic ratios. They all contribute to the phenotype, but without being dominant or recessive to each other. A polygenic trait varies in populations (hair color, body weight, and cholesterol levels). Some genes contribute more to a polygenic trait than others. Within genes, alleles can have differing impacts depending upon exactly how they alter an encoded protein and how common they are in a population. Example: A mutation in the LDL receptor gene greatly raises blood serum cholesterol level. Since fewer than 1% of the individuals in most populations have this mutation, it contributes very little to the variation in cholesterol level at the population level. However, the mutation has a large impact on the person who has it. Example: Although the expression of a polygenic trait is continuous, affected individuals can be categorized into classes and the frequencies of the different classes can be calculated. When the frequency for each phenotype class is plotted, a bell-shaped curve results. Height The effect of the environment on height is obvious—people who do not eat enough do not reach their genetic potential for height. People from the 1920s are on average considerably shorter than students from recent years. The tallest individuals from 1920 were 5'9'', whereas the tallest at the turn of the century are 6'5''. The difference is attributed to improved diet and better overall health. At least 50 genes affect height. Skin color and race More than 100 genes affect pigmentation in skin, hair, and the irises. Melanin pigments color the skin to different degrees in different individuals. Exposure to the sun increases melanin synthesis. All have about the same number of melanocytes per unit area of skin. People have different skin colors because they vary in melanosome number, size, and density of pigment distribution. Skin color is one physical trait that is used to distinguish race, but this trait is not a reliable indicator of ancestry. Methods to predict multifactorial traits Empiric risk – used to predict the chance that a polygenic multifactorial trait will occur in a particular individual based on incidence in a specific population. Incidence is the rate at which a certain event occurs, such as the number of new cases of a disorder diagnosed per year in a population of known size. Prevalence is the proportion or number of individuals in a population who have a particular disorder at a specific time, such as during one year. It is not a calculation, but a population statistic based on observation. The population might be broad, such as an ethnic group or community, or genetically more well defined, such as families that have certain genetic disorders. It increases with the severity of the disorder, the number of affected family members, and how closely related a person is to affected individuals. If a trait has an inherited component, then it makes sense that the closer the relationship between two individuals, one of whom has the trait, the greater the probability that the second individual has the trait, too, because they share more genes. Methods to predict multifactorial traits Heritability – designated H, estimates the proportion of the phenotypic variation for a trait that is due to genetic differences in a certain population at a certain time. Heritability refers to the degree of variation in a trait due to genetics, and not to the proportion of the trait itself attributed to genes. The distinction between empiric risk and heritability is that empiric risk could result from nongenetic influences, whereas heritability focuses on the genetic component of the variation in a trait. Heritability equals 1.0 for a trait whose variability is completely the result of gene action (e.g. in a population of laboratory mice who share the same environment). Without environmental variability, genetic differences alone determine expression of the trait in the population. Variability of most traits, however, is due to differences among genes and environmental components. Heritability changes as the environment changes (e.g. populations in equatorial Africa, have darker skin than sun-deprived Scandinavians).  Genetic variance for a polygenic trait is mostly due to the additive effects of recessive alleles of different genes. For some traits, a few dominant alleles can greatly influence the phenotype, but because they are rare, they do not contribute greatly to heritability. Epistasis (interaction between alleles of different genes) can also influence heritability. To account for the fact that different genes affect a phenotype to differing degrees, geneticists calculate: a “narrow” heritability that considers only additive recessive effects a “broad” heritability that also considers the effects of rare dominant alleles and epistasis. Study of adopted individuals vs study of twins An adopted person typically shares environmental influences, but not many gene variants, with the adoptive family. Conversely, they share genes, but not the exact environment, with their biological parents. It is assumed that similarities between adopted people and adoptive parents reflect mostly environmental influences, whereas similarities between adoptees and their biological parents reflect mostly genetic influences. Information on both sets of parents can reveal how heredity and the environment contribute to a trait. Study of adopted individuals vs study of twins Example from database of all adopted children in Denmark and their families from 1924 to 1947, a study examined correlations between causes of death among biological and adoptive parents and adopted children. If a biological parent died of infection before age 50, the child he or she gave up for adoption was five times more likely to die of infection at a young age than a similar person in the general population. This may be because inherited variants in immune system genes increase susceptibility to certain infections. The risk that an adopted individual would die young from infection did not correlate with adoptive parents’ death from infection before age 50. Researchers concluded that genetics mostly determines length of life, but they did find evidence of environmental influences. For example, if adoptive parents died before age 50 of cardiovascular disease, their adopted children were three times as likely to die of heart and blood vessel disease as a person in the general population. What environmental factor might explain this correlation?  Studies that use twins to separate the genetic from the environmental contribution to a phenotype provide more meaningful information than studying adopted individuals. Using twins to study genetic influence on traits, German dermatologist Hermann Siemens reported that grades and teachers’ comments were much more alike for identical twins than for fraternal twins and proposed that genes contribute to intelligence (1924). A trait that occurs more frequently in both members of identical (monozygotic or MZ) twin pairs than in both members of fraternal (dizygotic or DZ) twin pairs is at least partly controlled by heredity. Concordance of a trait is the percentage of pairs in which both twins express the trait among pairs of twins in whom at least one has the trait. Twins who differ in a trait are said to be discordant for it. In one study, 142 MZ twin pairs and 142 DZ twin pairs took a “distorted tunes test,” in which 26 familiar songs were played, each with at least one note altered. Concordance for “tune deafness” was 67 % for MZ twins, but only 44 %for DZ twins, indicating a considerable inherited component in the ability to accurately perceive musical pitch.  Diseases caused by single genes that approach 100 percent penetrance, whether dominant or recessive, also approach 100 percent concordance in MZ twins. That is, if one identical twin has the disease, so does the other. Among DZ twins, concordance generally is 50 percent for a dominant trait and 25 percent for a recessive trait - the Mendelian values that apply to any two non-twin siblings. For a polygenic trait with little environmental input, concordance values for MZ twins are significantly greater than for DZ twins. A trait molded mostly by the environment exhibits similar concordance values for both types of twins. Comparing twin types assumes that both types of twins share similar experiences. In fact, MZ twins are often closer emotionally than DZ twins.  A more informative way to assess the genetic component of a multifactorial trait is to study MZ twins who were separated at birth, then raised in very different environments. Study by Thomas Bouchard at the University of Minnesota on twins and triplets who were separated at birth for distinguishing nature from nurture: Many of their common traits can be attributed to genetics, especially if their environments have been very different. Their differences tend to come from differences in upbringing, because their genes are identical (MZ twins and triplets) or similar (DZ twins and triplets). Some MZ twins separated at birth and reunited later are remarkably similar, even when they grow up in very different adoptive families.  The “twins reared apart” approach is not an ideal way to separate nature from nurture. MZ twins and other multiples share an environment in the uterus and possibly in early infancy that may affect later development. Siblings, whether adoptive or biological, do not always share identical home environments. Differences in sex, general health, school and peer experiences, temperament, and personality affect each individual’s perception of such environmental influences as parental affection and discipline. Genome-wide association study (GWAS) Compares large sets of landmarks (genetic markers) across the genome between two large groups of people—one with a particular trait or disease and one without it. Identifying parts of the genome that are much more common among the people with the trait or illness can lead researchers to genes that contribute to the phenotype. Genome-wide association studies use genetic markers Single nucleotide polymorphisms (SNPs) is a site in the genome that has a different DNA base in at least one percent of a population Copy number variants (CNVs) are DNA sequences that repeats a different number of times in different individuals A CNV does not provide information in the way that a gene that encodes protein does, but it is another way to distinguish individuals. Gene expression patterns - represent which proteins are overproduced or underproduced in people with the trait or illness, compared to unaffected controls. Another way to compare genomes is by the sites to which methyl (CH 3 ) groups bind, shutting off gene expression. This is an epigenetic change because it doesn’t affect the DNA base sequence.  To achieve statistical significance, a genome-wide association study must include >100,000 markers. It is the association of markers to a trait or disease that is informative. Typically, genome-wide association studies use >1 M SNPs, grouped into 0.5 M or so haplotypes. A specific “tag SNP” is used to identify a haplotype. A GWAS is a stepwise focusing in on parts of the genome responsible to some degree for a trait. A group of people with the same condition or trait and a control group have their DNA genotyped for the 0.5 M tag SNPs and statistical algorithms identify the uniquely shared SNPs in the group with the trait or disorder. Repeating the process on additional populations narrows the SNPs and strengthens the association. It is important to validate a SNP association in different population groups, to be certain that it is the trait of interest that is being tracked, and not another part of the genome that members of one population share due to their common ancestry. Study designs for genome-wide association studies Cohort study - follow a large group of individuals over time and measure many aspects of their health. (e.g. Framingham Heart Study, which from 1968 track thousands of people and their descendants in Massachusetts). Case-control study - each individual in one group is matched to an individual in another group who shares as many characteristics as possible, such as age, sex, activity level, and environmental exposures; SNP differences are then associated with the presence or absence of the disorder or trait Example - if 5,000 individuals with hypertension have particular DNA bases at six sites in the genome, and 5,000 matched individuals who do not have hypertension have different bases at only these six sites, then these genome regions may include genes whose protein products control blood pressure. Affected sibling pair - follows the logic that because siblings share 50 percent of their genes, a trait or condition that many siblings share is likely to be inherited. Genomes are scanned for SNPs that most siblings who have the same condition share, but that siblings who do not both have the condition do not often share. Such genome regions may have genes that contribute to the condition. Study designs for genome-wide association studies Homozygous mapping - a variation on the affected sibling pair strategy which is performed on families that are consanguineous—that is, the parents are related. The genomes of children whose parents share recent ancestors have more homozygous regions than do other children, and therefore greater likelihood that they have inherited two copies of a susceptibility or disease causing mutation. After a SNP association has been validated in diverse and large populations, the next step is gene identification. The human genome sequence near the SNPs might reveal “candidate” genes whose known functions explain the condition.  Genome-wide association studies have limitations, and are being replaced by direct analysis of the human genome sequence, as the functions of genes are being discovered. GWAS reveal associations between sets of information, and not causes. An association only means that one event or characteristic occurs when another occurs. A correlation is a directional association: If one measurement increases, so does the other (e.g. stress and blood pressure). Establishing a cause requires that a specific mechanism explains how one event makes another happen (e.g. how does stress elevate blood pressure?) GWAS does not provide information on a gene’s function—it is more a discovery tool.  GWAS was very helpful, for example, in explaining why some people who live on the Solomon Islands have blond hair. Most people living on these equatorial islands have dark hair and skin, similar to people who live in equatorial Africa. A case-control genome-wide association study on 43 blond Solomon Islanders and 42 darkhaired islanders clearly showed that the blonds were much more likely to have a particular SNP in a region on chromosome 9 where a gene tyrosine-related protein 1 (TYRP1) is found whose protein product controls melanin pigmentation and the mutant gene causes a form of human albinism. A single DNA base change is responsible for the unusual blond hair of some Solomon Islanders. Multifactorial trait: Body weight Body weight reflects energy balance, which is the rate of food taken in versus the rate at which the body uses it for fuel. Excess food means, ultimately, excess weight. Being overweight or obese raises the risk of developing hypertension, diabetes, stroke, gallstones, sleep apnea, and some cancers. Body mass index (BMI) is weight in proportion to height. Heritability for BMI is 0.55, which leaves room for environmental influences on appetites and sizes. Dozens of genes affect how much a person eats, how one uses calories, and how fat is distributed in the body. The biochemical pathways and hormonal interactions that control weight may reveal points for drug intervention. Genes That Affect Weight Genetics became prominent in obesity research in 1994, when Jeffrey Friedman at Rockefeller University discovered a gene that encodes the protein hormone leptin in mice and in humans. Normally, eating stimulates fat cells (adipocytes) to secrete leptin, which binds to receptors on nerve cells in the hypothalamus and signals the neurons to release another type of hormone which function as an appetite “brake,” while speeding digestion. When a person hasn’t eaten in several hours, leptin levels fall, which triggers the release of an appetite “accelerator.” The discovery of genes and proteins that affect appetite led to great interest in targeting them with drugs to either lose or gain weight. Mice given extra leptin, ate less and lost weight. Leptin was tested on obese people, assuming that they had a deficiency, to trick them into feeling full. Only about 15 percent of the people lost weight, but the other 85 percent did not actually lack leptin. Instead, most of them had leptin resistance, which is a diminished ability to recognize the hormone due to defective leptin receptors. Genes That Affect Weight Ghrelin is a peptide hormone produced in the stomach that responds to hunger, signaling the hypothalamus to produce more of the appetite accelerator. While leptin acts in the long term to maintain weight, the stomach’s appetite control hormones function in the short term. Identifying single genes that influence weight paved the way for considering the trait to be multifactorial and how combinations of genes control weight is being investigated. One study looked at 21 genes in which mutations cause syndromes that include obesity, as well as 37 genes whose products are part of biochemical pathways related to weight. This approach identified many rare gene variants that could, in combinations, explain many people’s tendency to gain weight. Genome-wide association studies that compare gene expression patterns have also enhanced understanding of body weight. One study compared the sets of genes that are expressed in adipose (fat) tissue to other tissues. Samples from more than 1,600 people in Iceland revealed a set of genes whose products take part in inflammation and the immune response, but also contribute obesity-related traits. Environmental influences on weight Studies on adopted individuals and twins suggest that obesity has a heritability of 75 %. Because the heritability for BMI is lower than this, the discrepancy suggests that genes play a larger role in those who tend to gain weight easily. The role of genes in obesity is seen when populations that have an inherited tendency to easily gain weight experience a large and sudden plunge in the quality of the diet. Example: in Western Samoa, the residents’ lifestyles changed greatly when they found a market for bird droppings on their island as commercial fertilizer. The money led to inactivity and a high-calorie, high-fat diet, replacing an agricultural lifestyle and diet of fish and vegetables. Within a generation, the population was 2/3 obese, and 1/3 had type 2 diabetes. Example: Pima Indians were separated into two populations during the Middle Ages, one group settling in the Sierra Madre mountains of Mexico, the other in southern Arizona. By the 1970s, the Arizona Indians no longer farmed nor ate a low-calorie, low-fat diet, but instead consumed 40 % of their calories from fat and developed the highest prevalence of obesity globally (50% had diabetes by age 35, weighing, on average, 57 pounds (26 kilograms) more than their southern relatives, who still eat a low-fat diet and are very active.