Monthly Archives: September 2022

Genetics is the scientific study of inherited variation. Human genetics, then, is the scientific study of inherited human variation.

Why study human genetics? One reason is simply an interest in better understanding ourselves. As a branch of genetics, human genetics concerns itself with what most of us consider to be the most interesting species on earth: Homo sapiens. But our interest in human genetics does not stop at the boundaries of the species, for what we learn about human genetic variation and its sources and transmission inevitably contributes to our understanding of genetics in general, just as the study of variation in other species informs our understanding of our own.

A second reason for studying human genetics is its practical value for human welfare. In this sense, human genetics is more an applied science than a fundamental science. One benefit of studying human genetic variation is the discovery and description of the genetic contribution to many human diseases. This is an increasingly powerful motivation in light of our growing understanding of the contribution that genes make to the development of diseases such as cancer, heart disease, and diabetes. In fact, society has been willing in the past and continues to be willing to pay significant amounts of money for research in this area, primarily because of its perception that such study has enormous potential to improve human health. This perception, and its realization in the discoveries of the past 20 years, have led to a marked increase in the number of people and organizations involved in human genetics.

This second reason for studying human genetics is related to the first. The desire to develop medical practices that can alleviate the suffering associated with human disease has provided strong support to basic research. Many basic biological phenomena have been discovered and described during the course of investigations into particular disease conditions. A classic example is the knowledge about human sex chromosomes that was gained through the study of patients with sex chromosome abnormalities. A more current example is our rapidly increasing understanding of the mechanisms that regulate cell growth and reproduction, understanding that we have gained primarily through a study of genes that, when mutated, increase the risk of cancer.

Likewise, the results of basic research inform and stimulate research into human disease. For example, the development of recombinant DNA techniques () rapidly transformed the study of human genetics, ultimately allowing scientists to study the detailed structure and functions of individual human genes, as well as to manipulate these genes in a variety of previously unimaginable ways.

Recombinant techniques have transformed the study of human genetics.

A third reason for studying human genetics is that it gives us a powerful tool for understanding and describing human evolution. At one time, data from physical anthropology (including information about skin color, body build, and facial traits) were the only source of information available to scholars interested in tracing human evolutionary history. Today, however, researchers have a wealth of genetic data, including molecular data, to call upon in their work.

Two research approaches were historically important in helping investigators understand the biological basis of heredity. The first of these approaches, transmission genetics, involved crossing organisms and studying the offsprings' traits to develop hypotheses about the mechanisms of inheritance. This work demonstrated that in some organisms at least, heredity seems to follow a few definite and rather simple rules.

The second approach involved using cytologic techniques to study the machinery and processes of cellular reproduction. This approach laid a solid foundation for the more conceptual understanding of inheritance that developed as a result of transmission genetics. By the early 1900s, cytologists had demonstrated that heredity is the consequence of the genetic continuity of cells by cell division, had identified the gametes as the vehicles that transmit genetic information from one generation to another, and had collected strong evidence for the central role of the nucleus and the chromosomes in heredity.

As important as they were, the techniques of transmission genetics and cytology were not enough to help scientists understand human genetic variation at the level of detail that is now possible. The central advantage that today's molecular techniques offer is that they allow researchers to study DNA directly. Before the development of these techniques, scientists studying human genetic variation were forced to make inferences about molecular differences from the phenotypes produced by mutant genes. Furthermore, because the genes associated with most single-gene disorders are relatively rare, they could be studied in only a small number of families. Many of the traits associated with these genes also are recessive and so could not be detected in people with heterozygous genotypes. Unlike researchers working with other species, human geneticists are restricted by ethical considerations from performing experimental, "at-will" crosses on human subjects. In addition, human generations are on the order of 20 to 40 years, much too slow to be useful in classic breeding experiments. All of these limitations made identifying and studying genes in humans both tedious and slow.

In the last 50 years, however, beginning with the discovery of the structure of DNA and accelerating significantly with the development of recombinant DNA techniques in the mid-1970s, a growing battery of molecular techniques has made direct study of human DNA a reality. Key among these techniques are restriction analysis and molecular recombination, which allow researchers to cut and rejoin DNA molecules in highly specific and predictable ways; amplification techniques, such as the polymerase chain reaction (PCR), which make it possible to make unlimited copies of any fragment of DNA; hybridization techniques, such as fluorescence in situ hybridization, which allow scientists to compare DNA samples from different sources and to locate specific base sequences within samples; and the automated sequencing techniques that today are allowing workers to sequence the human genome at an unprecedented rate.

On the immediate horizon are even more powerful techniques, techniques that scientists expect will have a formidable impact on the future of both research and clinical genetics. One such technique, DNA chip technology (also called DNA microarray technology), is a revolutionary new tool designed to identify mutations in genes or survey expression of tens of thousands of genes in one experiment.

In one application of this technology, the chip is designed to detect mutations in a particular gene. The DNA microchip consists of a small glass plate encased in plastic. It is manufactured using a process similar to the process used to make computer microchips. On its surface, it contains synthetic single-stranded DNA sequences identical to that of the normal gene and all possible mutations of that gene. To determine whether an individual possesses a mutation in the gene, a scientist first obtains a sample of DNA from the person's blood, as well as a sample of DNA that does not contain a mutation in that gene. After denaturing, or separating, the DNA samples into single strands and cutting them into smaller, more manageable fragments, the scientist labels the fragments with fluorescent dyes: the person's DNA with red dye and the normal DNA with green dye. Both sets of labeled DNA are allowed to hybridize, or bind, to the synthetic DNA on the chip. If the person does not have a mutation in the gene, both DNA samples will hybridize equivalently to the chip and the chip will appear uniformly yellow. However, if the person does possess a mutation, the mutant sequence on the chip will hybridize to the patient's sample, but not to the normal DNA, causing it (the chip) to appear red in that area. The scientist can then examine this area more closely to confirm that a mutation is present.

DNA microarray technology is also allowing scientists to investigate the activity in different cell types of thousands of genes at the same time, an advance that will help researchers determine the complex functional relationships that exist between individual genes. This type of analysis involves placing small snippets of DNA from hundreds or thousands of genes on a single microscope slide, then allowing fluorescently labeled mRNA molecules from a particular cell type to hybridize to them. By measuring the fluorescence of each spot on the slide, scientists can determine how active various genes are in that cell type. Strong fluorescence indicates that many mRNA molecules hybridized to the gene and, therefore, that the gene is very active in that cell type. Conversely, no fluorescence indicates that none of the cell's mRNA molecules hybridized to the gene and that the gene is inactive in that cell type.

Although these technologies are still relatively new and are being used primarily for research, scientists expect that one day they will have significant clinical applications. For example, DNA chip technology has the potential to significantly reduce the time and expense involved in genetic testing. This technology or others like it may one day help make it possible to define an individual's risk of developing many types of hereditary cancer as well as other common disorders, such as heart disease and diabetes. Likewise, scientists may one day be able to classify human cancers based on the patterns of gene activity in the tumor cells and then be able to design treatment strategies that are targeted directly to each specific type of cancer.

Homo sapiens is a relatively young species and has not had as much time to accumulate genetic variation as have the vast majority of species on earth, most of which predate humans by enormous expanses of time. Nonetheless, there is considerable genetic variation in our species. The human genome comprises about 3 109 base pairs of DNA, and the extent of human genetic variation is such that no two humans, save identical twins, ever have been or will be genetically identical. Between any two humans, the amount of genetic variationbiochemical individualityis about .1 percent. This means that about one base pair out of every 1,000 will be different between any two individuals. Any two (diploid) people have about 6 106 base pairs that are different, an important reason for the development of automated procedures to analyze genetic variation.

The most common polymorphisms (or genetic differences) in the human genome are single base-pair differences. Scientists call these differences SNPs, for single-nucleotide polymorphisms. When two different haploid genomes are compared, SNPs occur, on average, about every 1,000 bases. Other types of polymorphismsfor example, differences in copy number, insertions, deletions, duplications, and rearrangementsalso occur, but much less frequently.

Notwithstanding the genetic differences between individuals, all humans have a great deal of their genetic information in common. These similarities help define us as a species. Furthermore, genetic variation around the world is distributed in a rather continuous manner; there are no sharp, discontinuous boundaries between human population groups. In fact, research results consistently demonstrate that about 85 percent of all human genetic variation exists within human populations, whereas about only 15 percent of variation exists between populations (). That is, research reveals that Homo sapiens is one continuously variable, interbreeding species. Ongoing investigation of human genetic variation has even led biologists and physical anthropologists to rethink traditional notions of human racial groups. The amount of genetic variation between these traditional classifications actually falls below the level that taxonomists use to designate subspecies, the taxonomic category for other species that corresponds to the designation of race in Homo sapiens. This finding has caused some biologists to call the validity of race as a biological construct into serious question.

Most variation occurs within populations.

Analysis of human genetic variation also confirms that humans share much of their genetic information with the rest of the natural worldan indication of the relatedness of all life by descent with modification from common ancestors. The highly conserved nature of many genetic regions across considerable evolutionary distance is especially obvious in genes related to development. For example, mutations in the patched gene produce developmental abnormalities in Drosophila, and mutations in the patched homolog in humans produce analogous structural deformities in the developing human embryo.

Geneticists have used the reality of evolutionary conservation to detect genetic variations associated with some cancers. For example, mutations in the genes responsible for repair of DNA mismatches that arise during DNA replication are associated with one form of colon cancer. These mismatched repair genes are conserved in evolutionary history all the way back to the bacterium Escherichia coli, where the genes are designated Mutl and Muts. Geneticists suspected that this form of colon cancer was associated with a failure of mismatch repair, and they used the known sequences from the E. coli genes to probe the human genome for homologous sequences. This work led ultimately to the identification of a gene that is associated with increased risk for colon cancer.

Almost all human genetic variation is relatively insignificant biologically; that is, it has no adaptive significance. Some variation (for example, a neutral mutation) alters the amino acid sequence of the resulting protein but produces no detectable change in its function. Other variation (for example, a silent mutation) does not even change the amino acid sequence. Furthermore, only a small percentage of the DNA sequences in the human genome are coding sequences (sequences that are ultimately translated into protein) or regulatory sequences (sequences that can influence the level, timing, and tissue specificity of gene expression). Differences that occur elsewhere in the DNAin the vast majority of the DNA that has no known functionhave no impact.

Some genetic variation, however, can be positive, providing an advantage in changing environments. The classic example from the high school biology curriculum is the mutation for sickle hemoglobin, which in the heterozygous state provides a selective advantage in areas where malaria is endemic.

More recent examples include mutations in the CCR5 gene that appear to provide protection against AIDS. The CCR5 gene encodes a protein on the surface of human immune cells. HIV, the virus that causes AIDS, infects immune cells by binding to this protein and another protein on the surface of those cells. Mutations in the CCR5 gene that alter its level of expression or the structure of the resulting protein can decrease HIV infection. Early research on one genetic variant indicates that it may have risen to high frequency in Northern Europe about 700 years ago, at about the time of the European epidemic of bubonic plague. This finding has led some scientists to hypothesize that the CCR5 mutation may have provided protection against infection by Yersinia pestis, the bacterium that causes plague. The fact that HIV and Y. pestis both infect macrophages supports the argument for selective advantage of this genetic variant.

The sickle cell and AIDS/plague stories remind us that the biological significance of genetic variation depends on the environment in which genes are expressed. It also reminds us that differential selection and evolution would not proceed in the absence of genetic variation within a species.

Some genetic variation, of course, is associated with disease, as classic single-gene disorders such as sickle cell disease, cystic fibrosis, and Duchenne muscular dystrophy remind us. Increasingly, research also is uncovering genetic variations associated with the more common diseases that are among the major causes of sickness and death in developed countriesdiseases such as heart disease, cancer, diabetes, and psychiatric disorders such as schizophrenia and bipolar disease (manic-depression). Whereas disorders such as cystic fibrosis or Huntington disease result from the effects of mutation in a single gene and are evident in virtually all environments, the more common diseases result from the interaction of multiple genes and environmental variables. Such diseases therefore are termed polygenic and multifactorial. In fact, the vast majority of human traits, diseases or otherwise, are multifactorial.

The genetic distinctions between relatively rare single-gene disorders and the more common multifactorial diseases are significant. Genetic variations that underlie single-gene disorders generally are relatively recent, and they often have a major, detrimental impact, disrupting homeostasis in significant ways. Such disorders also generally exact their toll early in life, often before the end of childhood. In contrast, the genetic variations that underlie common, multifactorial diseases generally are of older origin and have a smaller, more gradual effect on homeostasis. They also generally have their onset in adulthood. The last two characteristics make the ability to detect genetic variations that predispose/increase risk of common diseases especially valuable because people have time to modify their behavior in ways that can reduce the likelihood that the disease will develop, even against a background of genetic predisposition.

As noted earlier, one of the benefits of understanding human genetic variation is its practical value for understanding and promoting health and for understanding and combating disease. We probably cannot overestimate the importance of this benefit. First, as shows, virtually every human disease has a genetic component. In some diseases, such as Huntington disease, Tay-Sachs disease, and cystic fibrosis, this component is very large. In other diseases, such as cancer, diabetes, and heart disease, the genetic component is more modest. In fact, we do not typically think of these diseases as "genetic diseases," because we inherit not the certainty of developing a disease, but only a predisposition to developing it.

Virtually all human diseases, except perhaps trauma, have a genetic component.

In still other diseases, the genetic component is very small. The crucial point, however, is that it is there. Even infectious diseases, diseases that we have traditionally placed in a completely different category than genetic disorders, have a real, albeit small, genetic component. For example, as the CCR5 example described earlier illustrates, even AIDS is influenced by a person's genotype. In fact, some people appear to have genetic resistance to HIV infection as a result of carrying a variant of the CCR5 gene.

Second, each of us is at some genetic risk, and therefore can benefit, at least theoretically, from the progress scientists are making in understanding and learning how to respond to these risks. Scientists estimate that each of us carries between 5 and 50 mutations that carry some risk for disease or disability. Some of us may not experience negative consequences from the mutations we carry, either because we do not live long enough for it to happen or because we may not be exposed to the relevant environmental triggers. The reality, however, is that the potential for negative consequences from our genes exists for each of us.

How is modern genetics helping us address the challenge of human disease? As shows, modern genetic analysis of a human disease begins with mapping and cloning the associated gene or genes. Some of the earliest disease genes to be mapped and cloned were the genes associated with Duchenne muscular dystrophy, retinoblastoma, and cystic fibrosis. More recently, scientists have announced the cloning of genes for breast cancer, diabetes, and Parkinson disease.

Mapping and cloning a gene can lead to strategies that reduce the risk of disease (preventive medicine); guidelines for prescribing drugs based on a person's genotype (pharmacogenomics); procedures that alter the affected gene (gene therapy); or drugs (more...)

As also shows, mapping and cloning a disease-related gene opens the way for the development of a variety of new health care strategies. At one end of the spectrum are genetic tests intended to identify people at increased risk for the disease and recognize genotypic differences that have implications for effective treatment. At the other end are new drug and gene therapies that specifically target the biochemical mechanisms that underlie the disease symptoms or even replace, manipulate, or supplement nonfunctional genes with functional ones. Indeed, as suggests, we are entering the era of molecular medicine.

Genetic testing is not a new health care strategy. Newborn screening for diseases like PKU has been going on for 30 years in many states. Nevertheless, the remarkable progress scientists are making in mapping and cloning human disease genes brings with it the prospect for the development of more genetic tests in the future. The availability of such tests can have a significant impact on the way the public perceives a particular disease and can also change the pattern of care that people in affected families might seek and receive. For example, the identification of the BRCA1 and BRCA2 genes and the demonstration that particular variants of these genes are associated with an increased risk of breast and ovarian cancer have paved the way for the development of guidelines and protocols for testing individuals with a family history of these diseases. BRCA1, located on the long arm of chromosome 17, was the first to be isolated, and variants of this gene account for about 50 percent of all inherited breast cancer, or about 5 percent of all breast cancer. Variants of BRCA2, located on the long arm of chromosome 13, appear to account for about 30 to 40 percent of all inherited breast cancer. Variants of these genes also increase slightly the risk for men of developing breast, prostate, or possibly other cancers.

Scientists estimate that hundreds of thousands of women in the United States have 1 of hundreds of significant mutations already detected in the BRCA1 gene. For a woman with a family history of breast cancer, the knowledge that she carries one of the variants of BRCA1 or BRCA2 associated with increased risk can be important information. If she does carry one of these variants, she and her physician can consider several changes in her health care, such as increasing the frequency of physical examinations; introducing mammography at an earlier age; and even having prophylactic mastectomy. In the future, drugs may also be available that decrease the risk of developing breast cancer.

The ability to test for the presence in individuals of particular gene variants is also changing the way drugs are prescribed and developed. A rapidly growing field known as pharmacogenomics focuses on crucial genetic differences that cause drugs to work well in some people and less well, or with dangerous adverse reactions, in others. For example, researchers investigating Alzheimer disease have found that the way patients respond to drug treatment can depend on which of three genetic variants of the ApoE (Apolipoprotein E) gene a person carries. Likewise, some of the variability in children's responses to therapeutic doses of albuterol, a drug used to treat asthma, was recently linked to genotypic differences in the beta-2-adrenergic receptor. Because beta-2-adrenergic receptor agonists (of which albuterol is one) are the most widely used agents in the treatment of asthma, these results may have profound implications for understanding the genetic factors that determine an individual's response to asthma therapy.

Experts predict that increasingly in the future, physicians will use genetic tests to match drugs to an individual patient's body chemistry, so that the safest and most effective drugs and dosages can be prescribed. After identifying the genotypes that determine individual responses to particular drugs, pharmaceutical companies also likely will set out to develop new, highly specific drugs and revive older ones whose effects seemed in the past too unpredictable to be of clinical value.

Knowledge of the molecular structure of disease-related genes also is changing the way researchers approach developing new drugs. A striking example followed the discovery in 1989 of the gene associated with cystic fibrosis (CF). Researchers began to study the function of the normal and defective proteins involved in order to understand the biochemical consequences of the gene's variant forms and to develop new treatment strategies based on that knowledge. The normal protein, called CFTR for cystic fibrosis transmembrane conductance regulator, is embedded in the membranes of several cell types in the body, where it serves as a channel, transporting chloride ions out of the cells. In CF patients, depending on the particular mutation the individual carries, the CFTR protein may be reduced or missing from the cell membrane, or may be present but not function properly. In some mutations, synthesis of CFTR protein is interrupted, and the cells produce no CFTR molecules at all.

Although all of the mutations associated with CF impair chloride transport, the consequences for patients with different mutations vary. For example, patients with mutations causing absent or markedly reduced CFTR protein may have more severe disease than patients with mutations in which CFTR is present but has altered function. The different mutations also suggest different treatment strategies. For example, the most common CF-related mutation (called delta F508) leads to the production of protein molecules (called delta F508 CFTR) that are misprocessed and are degraded prematurely before they reach the cell membrane. This finding suggests that drug treatments that would enhance transport of the defective delta F508 protein to the cell membrane or prevent its degradation could yield important benefits for patients with delta F508 CFTR.

Finally, the identification, cloning, and sequencing of a disease-related gene can open the door to the development of strategies for treating the disease using the instructions encoded in the gene itself. Collectively referred to as gene therapy, these strategies typically involve adding a copy of the normal variant of a disease-related gene to a patient's cells. The most familiar examples of this type of gene therapy are cases in which researchers use a vector to introduce the normal variant of a disease-related gene into a patient's cells and then return those cells to the patient's body to provide the function that was missing. This strategy was first used in the early 1990s to introduce the normal allele of the adenosine deaminase (ADA) gene into the body of a little girl who had been born with ADA deficiency. In this disease, an abnormal variant of the ADA gene fails to make adenosine deaminase, a protein that is required for the correct functioning of T-lymphocytes.

Although researchers are continuing to refine this general approach to gene therapy, they also are developing new approaches. For example, scientists hope that one very new strategy, called chimeraplasty, may one day be used to actually correct genetic defects that involve only a single base change. Chimeraplasty uses specially synthesized molecules that base pair with a patient's DNA and stimulate the cell's normal DNA repair mechanisms to remove the incorrect base and substitute the correct one. At this point, chimeraplasty is still in early development and the first clinical trials are about to get underway.

Yet another approach to gene therapy involves providing new or altered functions to a cell through the introduction of new genetic information. For example, recent experiments have demonstrated that it is possible, under carefully controlled experimental conditions, to introduce genetic information into cancer cells that will alter their metabolism so that they commit suicide when exposed to a normally innocuous environmental trigger. Researchers are also using similar experiments to investigate the feasibility of introducing genetic changes into cells that will make them immune to infection by HIV. Although this research is currently being done only in nonhuman primates, it may eventually benefit patients infected with HIV.

As indicates, the Human Genome Project (HGP) has significantly accelerated the pace of both the discovery of human genes and the development of new health care strategies based on a knowledge of a gene's structure and function. The new knowledge and technologies emerging from HGP-related research also are reducing the cost of finding human genes. For example, the search for the gene associated with cystic fibrosis, which ended in 1989, before the inception of the HGP, required more than eight years and $50 million. In contrast, finding a gene associated with a Mendelian disorder now can be accomplished in less than a year at a cost of approximately $100,000.

The last few years of research into human genetic variation also have seen a gradual transition from a primary focus on genes associated with single-gene disorders, which are relatively rare in the human population, to an increasing focus on genes associated with multifactorial diseases. Because these diseases are not rare, we can expect that this work will affect many more people. Understanding the genetic and environmental bases for these multifactorial diseases also will lead to increased testing and the development of new interventions that likely will have an enormous effect on the practice of medicine in the next century.

What are the implications of using our growing knowledge of human genetic variation to improve personal and public health? As noted earlier, the rapid pace of the discovery of genetic factors in disease has improved our ability to predict the risk of disease in asymptomatic individuals. We have learned how to prevent the manifestations of some of these diseases, and we are developing the capacity to treat others.

Yet, much remains unknown about the benefits and risks of building an understanding of human genetic variation at the molecular level. While this information would have the potential to dramatically improve human health, the architects of the HGP realized that it also would raise a number of complex ethical, legal, and social issues. Thus, in 1990 they established the Ethical, Legal, and Social Implications (ELSI) program to anticipate and address the ethical, legal, and social issues that arise from human genetic research. This program, perhaps more than any other, has focused public attention, as well as the attention of educators, on the increasing importance of preparing citizens to understand and contribute to the ongoing public dialogue related to advances in genetics.

Ethics is the study of right and wrong, good and bad. It has to do with the actions and character of individuals, families, communities, institutions, and societies. During the last two and one-half millennia, Western philosophy has developed a variety of powerful methods and a reliable set of concepts and technical terms for studying and talking about the ethical life. Generally speaking, we apply the terms "right" and "good" to those actions and qualities that foster the interests of individuals, families, communities, institutions, and society. Here, an "interest" refers to a participant's share or participation in a situation. The terms "wrong" or "bad" apply to those actions and qualities that impair interests.

Ethical considerations are complex, multifaceted, and raise many questions. Often, there are competing, well-reasoned answers to questions about what is right and wrong, and good and bad, about an individual's or group's conduct or actions. Typically, these answers all involve appeals to values. A value is something that has significance or worth in a given situation. One of the exciting events to witness in any discussion in ethics is the varying ways in which the individuals involved assign values to things, persons, and states of affairs. Examples of values that students may appeal to in a discussion about ethics include autonomy, freedom, privacy, sanctity of life, religion, protecting another from harm, promoting another's good, justice, fairness, relationships, scientific knowledge, and technological progress.

Acknowledging the complex, multifaceted nature of ethical discussions is not to suggest that "anything goes." Experts generally agree on the following features of ethics. First, ethics is a process of rational inquiry. It involves posing clearly formulated questions and seeking well-reasoned answers to those questions. For example, we can ask questions about an individual's right to privacy regarding personal genetic information; we also can ask questions about the appropriateness of particular uses of gene therapy. Well-reasoned answers to such questions constitute arguments. Ethical analysis and argument, then, result from successful ethical inquiry.

Second, ethics requires a solid foundation of information and rigorous interpretation of that information. For example, one must have a solid understanding of biology to evaluate the recent decision by the Icelandic government to create a database that will contain extensive genetic and medical information about the country's citizens. A knowledge of science also is needed to discuss the ethics of genetic screening or of germ-line gene therapy. Ethics is not strictly a theoretical discipline but is concerned in vital ways with practical matters.

Third, discussions of ethical issues often lead to the identification of very different answers to questions about what is right and wrong and good and bad. This is especially true in a society such as our own, which is characterized by a diversity of perspectives and values. Consider, for example, the question of whether adolescents should be tested for late-onset genetic conditions. Genetic testing centers routinely withhold genetic tests for Huntington disease (HD) from asymptomatic patients under the age of 18. The rationale is that the condition expresses itself later in life and, at present, treatment is unavailable. Therefore, there is no immediate, physical health benefit for a minor from a specific diagnosis based on genetic testing. In addition, there is concern about the psychological effects of knowing that later in life one will get a debilitating, life-threatening condition. Teenagers can wait until they are adults to decide what and when they would like to know. In response, some argue that many adolescents and young children do have sufficient autonomy in consent and decision making and may wish to know their future. Others argue that parents should have the right to have their children tested, because parents make many other medical decisions on behalf of their children. This example illustrates how the tools of ethics can bring clarity and rigor to discussions involving values.

One of the goals of this module is to help students see how understanding science can help individuals and society make reasoned decisions about issues related to genetics and health. Activity 5, Making Decisions in the Face of Uncertainty, presents students with a case of a woman who is concerned that she may carry an altered gene that predisposes her to breast and ovarian cancer. The woman is faced with numerous decisions, which students also consider. Thus, the focus of Activity 5 is prudential decision making, which involves the ability to avoid unnecessary risk when it is uncertain whether an event actually will occur. By completing the activity, students understand that uncertainty is often a feature of questions related to genetics and health, because our knowledge of genetics is incomplete and constantly changing. In addition, students see that making decisions about an uncertain future is complex. In simple terms, students have to ask themselves, "How bad is the outcome and how likely is it to occur?" When the issues are weighed, different outcomes are possible, depending on one's estimate of the incidence of the occurrence and how much burden one attaches to the risk.

Clearly, science as well as ethics play important roles in helping individuals make choices about individual and public health. Science provides evidence that can help us understand and treat human disease, illness, deformity, and dysfunction. And ethics provides a framework for identifying and clarifying values and the choices that flow from these values. But the relationships between scientific information and human choices, and between choices and behaviors, are not straightforward. In other words, human choice allows individuals to choose against sound knowledge, and choice does not require action.

Nevertheless, it is increasingly difficult to deny the claims of science. We are continually presented with great amounts of relevant scientific and medical knowledge that is publicly accessible. As a consequence, we can think about the relationships between knowledge, choice, behavior, and human welfare in the following ways:

One of the goals of this module is to encourage students to think in terms of these relationships, now and as they grow older.

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The following glossary was modified from the glossary on the National Human Genome Research Institute's Web site, available at http://www.nhgri.nih.gov.

One of the variant forms of a gene at a particular locus, or location, on a chromosome. Different alleles produce variation in inherited characteristics such as hair color or blood type. In an individual, one form of the allele (the dominant one) may be expressed more than another form (the recessive one).

One of 20 different kinds of small molecules that link together in long chains to form proteins. Amino acids are referred to as the "building blocks" of proteins.

Gene on one of the autosomes that, if present, will almost always produce a specific trait or disease. The chance of passing the gene (and therefore the disease) to children is 50-50 in each pregnancy.

Chromosome other than a sex chromosome. Humans have 22 pairs of autosomes.

Two bases that form a "rung of the DNA ladder." The bases are the "letters" that spell out the genetic code. In DNA, the code letters are A, T, G, and C, which stand for the chemicals adenine, thymine, guanine, and cytosine, respectively. In base pairing, adenine always pairs with thymine, and guanine always pairs with cytosine.

Defect present at birth, whether caused by mutant genes or by prenatal events that are not genetic.

First breast cancer genes to be identified. Mutated forms of these genes are believed to be responsible for about one-half the cases of inherited breast cancer, especially those that occur in younger women, and also to increase a woman's risk for ovarian cancer. Both are tumor suppressor genes.

Diseases in which abnormal cells divide and grow unchecked. Cancer can spread from its original site to other parts of the body and can be fatal if not treated adequately.

Gene, located in a chromosome region suspected of being involved in a disease, whose protein product suggests that it could be the disease gene in question.

Mutation that confers immunity to infection by HIV. The mutation alters the structure of a receptor on the surface of macrophages such that HIV cannot enter the cell.

Collection of DNA sequences generated from mRNA sequences. This type of library contains only protein-coding DNA (genes) and does not include any noncoding DNA.

Basic unit of any living organism. It is a small, watery, compartment filled with chemicals and a complete copy of the organism's genome.

One of the thread like "packages" of genes and other DNA in the nucleus of a cell. Different kinds of organisms have different numbers of chromosomes. Humans have 23 pairs of chromosomes, 46 in all: 44 autosomes and two sex chromosomes. Each parent contributes one chromosome to each pair, so children get one-half of their chromosomes from their mothers and one-half from their fathers.

Process of making copies of a specific piece of DNA, usually a gene. When geneticists speak of cloning, they do not mean the process of making genetically identical copies of an entire organism.

Three bases in a DNA or RNA sequence that specify a single amino acid.

Hereditary disease whose symptoms usually appear shortly after birth. They include faulty digestion, breathing difficulties and respiratory infections due to mucus accumulation, and excessive loss of salt in sweat. In the past, cystic fibrosis was almost always fatal in childhood, but treatment is now so improved that patients commonly live to their 20s and beyond.

Visual appearance of a chromo some when stained and examined under a microscope. Particularly important are visually distinct regions, called light and dark bands, that give each of the chromosomes a unique appearance. This feature allows a person's chromosomes to be studied in a clinical test known as a karyotype, which allows scientists to look for chromosomal alterations.

Particular kind of mutation: loss of a piece of DNA from a chromosome. Deletion of a gene or part of a gene can lead to a disease or abnormality.

Chemical inside the nucleus of a cell that carries the genetic instructions for making living organisms.

Number of chromosomes in most cells except the gametes. In humans, the diploid number is 46.

Technology that identifies mutations in genes. It uses small glass plates that contain synthetic single-stranded DNA sequences identical to those of a normal gene.

Process by which the DNA double helix unwinds and makes an exact copy of itself.

Determining the exact order of the base pairs in a segment of DNA.

Gene that almost always results in a specific physical characteristic (for example, a disease) even though the patient's genome possesses only one copy. With a dominant gene, the chance of passing on the gene (and therefore the disease) to children is 50-50 in each pregnancy.

Structural arrangement of DNA, which looks something like an immensely long ladder twisted into a helix, or coil. The sides of the "ladder" are formed by a backbone of sugar and phosphate molecules, and the "rungs" consist of nucleotide bases joined weakly in the middle by hydrogen bonds.

Particular kind of mutation: production of one or more copies of any piece of DNA, including a gene or even an entire chromosome.

Process in which molecules (such as proteins, DNA, or RNA fragments) can be separated according to size and electrical charge by applying an electric current to them. The current forces the molecules through pores in a thin layer of gel, a firm, jellylike substance. The gel can be made so that its pores are just the right dimensions for separating molecules within a specific range of sizes and shapes. Smaller fragments usually travel further than large ones. The process is sometimes called gel electrophoresis.

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Understanding Human Genetic Variation - NCBI Bookshelf

Why do scientists study the genes of other organisms?

All living things evolved from a common ancestor. Therefore, humans, animals, and other organisms share many of the same genes, and the molecules made from them function in similar ways.

Scientists have found many genes that have been preserved through millions of years of evolution and are present in a range of organisms living today. They can study these preserved genes and compare the genomes of different species to uncover similarities and differences that improve their understanding of how human genes function and are controlled. This knowledge helps researchers develop new strategies to treat and prevent human disease. Scientists also study the genes of bacteria, viruses, and fungi for solutions to prevent or treat infection. Increasingly, these studies are offering insight into how microbes on and in the body affect our health, sometimes in beneficial ways.

Increasingly sophisticated tools and techniques are allowing NIGMS-funded scientists to ask more precise questions about the genetic basis of biology. For example, theyre studying the factors that control when genes are active, the mechanisms DNA uses to repair broken or damaged segments, and the complex ways traits are passed to future generations. Another focus of exploration involves tracing genetic variation over time to detail human evolutionary history and to pinpoint the emergence of disease-related attributes. These areas of basic research will continue to build a strong foundation for more disease-targeted studies.

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Genetics - National Institute of General Medical Sciences (NIGMS)

People who have been diagnosed with myalgic encephalomyelitis (ME) are being invited to take part in the worlds largest genetic study of the disease.

The study, named DecodeME and led by researchers at Edinburgh Universitys MRC Human Genetics Unit, aims to reveal the tiny differences in a persons DNA that can increase their risk of developing ME, also known as chronic fatigue syndrome (CFS).

It is estimated that more than 250,000 people in the UK are affected by the condition, with symptoms including pain, brain fog and extreme exhaustion that cannot be improved with rest.

The causes of the disease are still unknown, and there is no diagnostic test or effective treatments thus far.

Testing DNA in the saliva of 20,000 donated samples will allow for analysis on whether the disease is partly genetic, and if so, research into its cause and effective treatments.

The study has also been expanded to include analysis on the DNA of a further 5,000 people who have been diagnosed with ME or CFS after having Covid-19.

We believe the results should help identify genes, biological molecules and types of cells that may play a part in causing ME/CFS

Professor Chris Ponting

Along with the DNA research, an anonymous survey will provide an insight into the experience of those with the condition.

The research team is being led by Professor Chris Ponting.

He said: This is the first sizable DNA study of ME/CFS, and any differences we find compared to control samples will serve as important biological clues.

Specifically, we believe the results should help identify genes, biological molecules and types of cells that may play a part in causing ME/CFS.

The university is working alongside charity Action for ME, the Forward ME alliance of UK charities, and people with lived experience of the condition.

Chief executive of Action for ME Sonya Chowdhury said: People with lived experience of ME/CFS are at the very heart of the DecodeME project and our Patient and Participant Involvement group has worked closely with researchers on all aspects of the study.

Their profound involvement has been so transformational that we firmly believe it sets a new standard for health research in this country.

Individuals with ME or CFS who are aged 16 and over and based in the UK are invited to take part from home by signing up on the DecodeME website from 12pm on Monday.

See more here:
People with ME invited to take part in major genetic study - The Independent

Ketamine may be an effective treatment for children with activity-dependent neuroprotective protein (ADNP) syndrome, a rare genetic condition associated with intellectual disability and autism spectrum disorder.

Also known as HelsmoortelVan Der Aa syndrome, ADNP syndrome is caused by mutations in the ADNP gene. Studies in animal models suggest that low-dose ketamine increases expression of ADNP and is neuroprotective.

Intrigued by the preclinical evidence, Alexander Kolevzon, MD, clinical director of the Seaver Autism Center at Mount Sinai in New York, and colleagues treated 10 children with ADNP syndrome with a single low dose of ketamine (0.5mg/kg) infused intravenously over 40 minutes. The children ranged in ages 6-12 years.

Using parent-report instruments to assess treatment effects, ketamine was associated with "nominally significant" improvement in a variety of domains, including social behavior, attention-deficit and hyperactivity, restricted and repetitive behaviors, and sensory sensitivities.

Parent reports of improvement in these domains aligned with clinician-rated assessments based on the Clinical Global ImpressionsImprovement scale.

The results also highlight the potential utility of electrophysiological measurement of auditory steady-state response and eye-tracking to track change with ketamine treatment, the researchers say.

The study was published online August 27 in Human Genetics and Genomic (HGG) Advances.

Ketamine was generally well tolerated. There were no clinically significant abnormalities in laboratory or cardiac monitoring, and there were no serious adverse events (AEs).

Treatment emergent AEs were all mild to moderate and no child required any interventions.

The most common AEs were elation/silliness in five children (50%), all of whom had a history of similar symptoms. Drowsiness and fatigue occurred in four children (40%) and two of them had a history of drowsiness. Aggression was likewise relatively common, reported in four children (40%), all of whom had aggression at baseline.

Decreased appetite emerged as a new AE in three children (30%), increased anxiety occurred in three children (30%), and irritability, nausea/vomiting, and restlessness each occurred in two children (20%).

The researchers caution that the findings are intended to be "hypothesis generating."

"We are encouraged by these findings, which provide preliminary support for ketamine to help reduce negative effects of this devastating syndrome," Kolevzon said in a news release from Mount Sinai.

Ketamine might help ease symptoms of ADNP syndrome "by increasing expression of the ADNP gene or by promoting synaptic plasticity through glutamatergic pathways," Kolevzon told Medscape Medical News.

The next step, he said, is to get "a larger, placebo-controlled study approved for funding using repeated dosing over a longer duration of time. We are working with the FDA to get the design approved for an investigational new drug application."

Support for the study was provided by the ADNP Kids Foundation and the Foundation for Mood Disorders. Support for mediKanren was provided by the National Center for Advancing Translational Sciences, and National Institutes of Health through the Biomedical Data Translator Program. Kolevzon is on the scientific advisory board of Ovid Therapeutics, Ritrova Therapeutics, and Jaguar Therapeutics and consults to Acadia, Alkermes, GW Pharmaceuticals, Neuren Pharmaceuticals, Clinilabs Drug Development Corporation, and Scioto Biosciences.

HGG Advances. Published online August 27, 2022. Full text

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Ketamine Promising for Rare Condition Linked to Autism - Medscape

Jesse Weber collects stickleback with a minnow trap in the Kenai Peninsula of Alaska. Photo by Matt Chotlos

At first blush, sticklebacks might seem a bit pedestrian. The finger-length, unassuming fish with a few small dorsal spines are a ubiquitous presence in oceans and coastal watersheds around the northern hemisphere. But these small creatures are also an excellent subject for investigating the complex dance of evolutionary adaptations.

A new study published Sept. 8 in Science sheds light on the genetic basis by which stickleback populations inhabiting ecosystems near each other developed a strong immune response to tapeworm infections, and how some populations later came to tolerate the parasites.

Evolutionary biologist Jesse Weber, a professor of integrative biology at the University of WisconsinMadison, is one of the studys lead authors. Sticklebacks have long been a source of fascination not only for Weber, but for biologists all over the world so much so that the fish are among the most closely studied species.

An aerial view of an experiment in the Kenai Peninsula of Alaska studying changes in stickleback traits in response to a new environment. Photo by Andrew Hendry

We arguably know more about stickleback ecology and evolution than any other vertebrate, says Weber.

This is in part because of sticklebacks rich abundance in places like Western Europe, where the fish have long been involved in biological study, Weber says. But the reasons for the species star status go well beyond happenstance.

Sticklebacks are also just super charismatic, Weber adds, noting the species complex courtship and territorial behaviors, as well as their diverse colors, shapes and sizes, all of which vary depending on the specific ecosystem they inhabit.

While sticklebacks diversity provides a foothold for understanding why animals evolve different traits, their value for scientists like Weber is boosted by their genetics. The fish have approximately as many genes as humans, but their genetic material is packed much more tightly sticklebacks genome is about one-sixth the size of the human genome.

Their genome is amazingly useful, Weber says. As far as we can tell, its just packed more densely. This means we can efficiently investigate their genetic diversity, allowing us to ask not only, Why do new traits evolve? but also, How are adaptations programmed into the genome?'

On top of all that, sticklebacks take well to captive breeding. A single female can produce hundreds of offspring multiple times over the course of just a few months.

All these traits make stickleback an almost uniquely valuable species for studying the genetic basis for many types of biological adaptations. So, when Weber arrived at UWMadison in the fall of 2020 from the University of Alaska Anchorage, he came with an entire fish colony in tow. Living in tanks, the colony contains fish from genetically distinct populations originating from different lakes and estuaries dotting northwestern North America.

A three spine stickleback with tapeworms recently dissected from the body of the same animal. Photo by Natalie Steinel

In their quest to understand why and how the fish sometimes evolve to look and behave very differently even in relatively nearby lake systems, Weber and his colleagues can crossbreed these populations in various ways and map changes to their genomes across multiple generations relatively quickly.

Much of Webers scientific career to this point has focused on developing tools to make this type of work more efficient. More recently, Weber has turned to using these tools to investigate coevolution the process by which two species adapt to the presence of one another within a shared habitat.

Specifically, Weber and his colleagues have sought to understand why sticklebacks in some lakes are much more likely to be infected with tapeworms than their counterparts in nearby lakes where the tapeworms are also present.

These investigations are beginning to bear fruit. Weber, along with colleagues at the University of Connecticut and University of Massachusetts Lowell, recently identified key genetic differences between the populations.

These differences indicate that all fish populations developed a robust immune response to the tapeworms when they first moved from the sea to new freshwater habitats near the end of the last ice age. But the immune response is costly in terms of both energy and reproduction. It also leads to a large amount of inflammation and internal scarring.

Webers work and that of his colleagues suggest that numerous populations eventually evolved to avoid these costs by ignoring, or in the lingo of immunologists tolerating, the parasite infestation. But the tolerant population still carries the genes that produce the immune response to the tapeworms.

While they havent yet tested it, Weber says it appears that these sticklebacks may have mutations to these fibrosis-associated genes that render them non-functional.

While the results are exciting for Weber, hes already looking toward future research that he hopes will further tell the genetic story of sticklebacks abundant adaptations, and by extension reveal biological processes with implications across the wide diversity of life on Earth.

Read more about the study and its findings from the University of Connecticut.

This study was supported by the Howard Hughes Medical Institute Early Career Scientist fellowship, as well as grants from the National Institutes of Health (1R01AI123659-01A1, 1R01AI146168 and 1R35GM142891).

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How a small, unassuming fish helps reveal gene adaptations - University of Wisconsin-Madison

Anything that changes the way individuals and medical professionals view nutrition is undoubtedly going to be reflected in other areas. And an obvious one, no doubt, is the food industry. Whatever the real difference gene variations make in terms of health, the reality is this: The more that's discovered, the more reactions are going to be experienced in different ways, and on different levels.

It's already the case that foods are sold that are enriched in some way, or it's highlighted how they're rich in certain nutrients. At the same time, foods for specific diets, such as keto, to treat certain ailments are also available. As nutrigenomics advances, nutrition plans can be created for certain genetic groups (viaIndian Journal of Horticulture).

There have long been diets and food products targeted at specific health conditions keto is aimed at lowering blood sugar levels and tackling type 2 diabetes, for example (perHealthline). This is whereby a variant of one gene has led to a disorder of some kind and there's a direct connection. However, nutrigenomics is more expansive, and more complex perhaps, as it may be that a number of genetic variations impact a number of different responses to nutrition. It's when these multiple changes are combined that they create an outcome.

The result is food that's created to deal with these differences. A University of Auckland study, highlighted in aHealthy Food Guidearticle, focuses on a gene-diet factor in why Crohn's disease is higher in New Zealand, and one area in particular. The guide explains, "The research team is studying the link between foods eaten by people with Crohn's disease and different variations of the disease-related genes. Information about lifestyle and symptoms are also collected to learn more about the disease and potentially to allow tailoring of foods to genetic type."

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How Nutrigenomics Explores Links Between Nutrition And Genes - Health Digest

image:Dr. J. Andrew Pospisilik, Chair of the Department of Epigenetics, Van Andel Institute view more

Credit: Courtesy of Van Andel Institute

GRAND RAPIDS, Mich. (September 12, 2022) A team led by Van Andel Institute scientists has identified two distinct types of obesity with physiological and molecular differences that may have lifelong consequences for health, disease and response to medication.

The findings, published today in the journal Nature Metabolism, offer a more nuanced understanding of obesity than current definitions and may one day inform more precise ways to diagnose and treat obesity and associated metabolic disorders.

The study also reveals new details about the role of epigenetics and chance in health and provides insights into the link between insulin and obesity.

Nearly two billion people worldwide are considered overweight and there are more than 600 million people with obesity, yet we have no framework for stratifying individuals according to their more precise disease etiologies, said J. Andrew Pospisilik, Ph.D., chair of Van Andel Institutes Department of Epigenetics and corresponding author of the study. Using a purely data-driven approach, we see for the first time that there are at least two different metabolic subtypes of obesity, each with their own physiological and molecular features that influence health. Translating these findings into a clinically usable test could help doctors provide more precise care for patients.

Currently, obesity is diagnosed using body mass index (BMI), an index correlated to body fat that is generated by comparing weight in relation to height. It is an imperfect measure, Pospisilik says, because it doesnt account for underlying biological differences and can misrepresent an individuals health status.

Using a combination of laboratory studies in mouse models and deep analysis of data from TwinsUK, a pioneering research resource and study cohort developed in the United Kingdom, Pospisilik and his collaborators discovered four metabolic subtypes that influence individual body types: two prone to leanness and two prone to obesity.

One obesity subtype is characterized by greater fat mass while the other was characterized by both greater fat mass and lean muscle mass. Somewhat surprisingly, the team found that the second obesity type also was associated with increased inflammation, which can elevate the risk of certain cancers and other diseases. Both subtypes were observed across multiple study cohorts, including in children. These insights are an important step toward understanding how these different types impact disease risk and treatment response.

After the subtypes were identified in the human data, the team verified the results in mouse models. This approach allowed the scientists to compare individual mice that are genetically identical, raised in the same environment and fed the same amounts of food. The study revealed that the inflammatory subtype appears to result from epigenetic changes triggered by pure chance. They also found that there seems to be no middle ground the genetically identical sibling mice either grew to a larger size or remained smaller, with no gradient between them. A similar pattern was seen in data from more than 150 human twin pairs, each of whom were virtually the same genetically.

Our findings in the lab almost carbon copied the human twin data. We again saw two distinct subtypes of obesity, one of which appeared to be epigenetically triggerable, and was marked by higher lean mass and higher fat, high inflammatory signals, high insulin levels, and a strong epigenetic signature, Pospisilik said.

Depending on the calculation and traits in question, only 30%50% of human trait outcomes can be linked to genetics or environmental influences. That means as much as half of who we are is governed by something else. This phenomenon is called unexplained phenotypic variation (UPV) and it offers both a challenge and untapped potential to scientists like Pospisilik and his collaborators.

The study indicates that the roots of UPV likely lie in epigenetics, the processes that govern when and to what extent the instructions in DNA are used. Epigenetic mechanisms are the reason that individuals with the same genetic instruction manual, such as twins, may grow to have different traits, such as eye color and hair color. Epigenetics also offer tantalizing targets for precision treatment.

This unexplained variation is difficult to study but the payoff of a deeper understanding is immense, Pospisilik said. Epigenetics can act like a light switch that flips genes on or off, which can promote health or, when things go wrong, disease. Accounting for UPV doesnt exist in precision medicine right now, but it looks like it could be half the puzzle. Todays findings underscore the power of recognizing these subtle differences between people to guide more precise ways to treat disease.

Pospisilik is hopeful that the teams findings will inform development of future precision medicine strategies and lead to a version of their method that may be used in doctors offices to better understand individual patients health and inform care.

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Chih-Hsiang Yang, Ph.D., and Luca Fagnocchi, Ph.D., of VAI are co-first authors of the study. Other authors include Stefanos Apostle, M.S., Vanessa Wegert, M.Sc., Ilaria Panzeri, Ph.D., Darrell P. Chandler, Ph.D., Di Lu, Ph.D., Tao Yang, Ph.D., Elizabeth Gibbons, Ph.D., Rita Guerreiro, Ph.D., and Jos Brs, Ph.D. of VAI; Erez Dror, Ph.D., Steffen Heyne, Ph.D., Till Wrpel of Max Planck Institute of Immunobiology and Epigenetics; Salvador Casani-Galdn, Ph.D. of BioBam Bioinformatics; Kathrin Landgraf, Ph.D., of University of Leipzig; Martin Thomasen, Louise G. Grunnet, Ph.D., and Allan A. Vaag, M.D., Ph.D., D.MSc., of Rigshospitalet; Linn Gillberg, Ph.D., of University of Copenhagen; Elin Grundberg, Ph.D., of Childrens Mercy Research Institute; Ana Conesa, Ph.D., of the Spanish National Research Council and University of Florida; Antje Krner, M.D., of University of Leipzig and Helmholtz Institute for Metabolic, Obesity and Vascular Research; and PERMUTE. The authors thank the MPI-IE Facilities, and Van Andel Institutes Bioinformatics and Biostatistics Core, Genomics Core, Optical Imaging Core, Pathology and Biorepository Core, and Vivarium Core. Access to twin data was generously provided by UKTwins, without whom this study would not have been possible.

Research reported in this publication was supported by Van Andel Institute; Max Planck Gesellschaft; the European Unions Horizon 2020 Research and Innovation Program under Marie Skodowska-Curie grant agreement no. 675610; the Novo Nordisk Foundation and the European Foundation for the Study of Diabetes; the Danish Council for Independent Research; the National Human Genome Research Institute of the National Institutes of Health under award no. R21HG011964 (Pospisilik); and the NIH Common Fund, through the Office of the NIH Director (OD), and the National Human Genome Research Institute of the National Institutes of Health under award no. R01HG012444 (Pospisilik and Nadeau). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or other granting organizations. Approximately 5% ($50,000) of funding for this study is from federal sources; approximately 95% ($950,000) is from non-U.S. governmental sources.

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ABOUT VAN ANDEL INSTITUTEVan Andel Institute (VAI) is committed to improving the health and enhancing the lives of current and future generations through cutting-edge biomedical research and innovative educational offerings. Established in Grand Rapids, Michigan, in 1996 by the Van Andel family, VAI is now home to nearly 500 scientists, educators and support staff, who work with a growing number of national and international collaborators to foster discovery. The Institutes scientists study the origins of cancer, Parkinsons and other diseases and translate their findings into breakthrough prevention and treatment strategies. Our educators develop inquiry-based approaches for K-12 education to help students and teachers prepare the next generation of problem-solvers, while our Graduate School offers a rigorous, research-intensive Ph.D. program in molecular and cellular biology. Learn more at vai.org.

Nature Metabolism

Independent phenotypic plasticity axes define distinct obesity sub-types

12-Sep-2022

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Scientists redefine obesity with discovery of two major subtypes - EurekAlert

Ethics statement

All experimental procedures were approved by the Animal Ethics Committee of KU Leuven (P004/2020), in accordance with European Community Council Directive 86/609/EEC, the ARRIVE guidelines and the ILAR Guide to the Care and Use of Experimental Animals. Researchers obtained informed consent for publication from all identifiable persons to display and reuse videos.

The study was carried out on 794 female and 746 castrated male Pitrain x PIC Camborough pigs (Vlaamse Pitrain Fokkerij, Belgium; offspring from 73 different sires and 204 dams), which had a mean age of 83.4 (2.2) days and a mean weight of 30.6 (5.1) kg at the start of the experiment. Observations were made during the fattening period which could span up to 120days and ended when pigs reached a body weight of approximately 115kg. Per sire, a median of 26 crossbred piglets (full-sibs and half-sibs from the same Pitrain sire) were allocated in equal numbers to two identical pens in mixed-sex groups. The pig building (experimental farm, located in Belgium) consisted of seventeen identical compartments with eight semi-slatted pens (2.5m4.0m) per compartment and on average thirteen pigs per pen (0.77m2 per pig). Food and water were provided ad-libitum in each pen throughout, from one trough and one nipple drinker.

Pigs were weighed individually over their fattening period every two weeks from January to July 2021. Pen-by-pen, all individuals were driven to the stables central hallway, after which pigs were weighed sequentially. Weighing was carried out between 08:00 a.m. and 16:00 p.m. and was video-recorded. All piglets were weighed for the first at thirteen days after arrival at the fattening farm. For practical limitations, only one out of two pens per sire was hereafter selected for subsequent follow-up. All 1556 pigs were weighed up to eight times, resulting in a total of 7428 records.

Additionally, each pig was scored manually during weighing on the following physical abnormalities: ear swellings or hematomas (0=none, 1=one ear, 2=both ears); the presence and size of umbilical hernia (0=not present, 1=present); ear biting wounds (0=none, 1=one ear, 2=both ears) and tail biting wounds (0=none, 1=small scratches, 3=bloody and/or infected tail; Additional File 1). All recordings were collected by the same trained professional. Lean meat percentage was recorded individually at the slaughterhouse of the Belgian Pork Group in Meer (Belgium) using AutoFom III (Frontmatec, Smoerum A/S, Denmark)31. Feed intake was measured at the pen level.

The walk-through pig weighing setup consisted of a ground scale weighing platform, a radio frequency identification (RFID) reader, a video camera and a computer (Fig.1). The ground scale platform (3.4m1.8m) had an accuracy of0.5kg (T.E.L.L. EAG80, Vreden, Germany) and was situated in the central hallway of the pig building. A wooden aisle helped pigs to walk individually and forward over the balance (2.5m0.6m; Fig.1a; Additional File 2Video S1). Body weights were registered electronically and coupled to the pigs ID using an RFID-reader and custom-made software. The camera (Dahua IPC-HDW4831EMP-ASE, Dahua Technology Co., Ltd, Hangzhou, China) was mounted 2.5m above floor at the center of the weighing scale. Pigs were recorded from an overhead camera perspective with a frame rate of 15 frames per second and a resolution of 38402160. An example of our data collection and a video recording is provided in Fig.1b.

Experimental setup (created with BioRender.com). (a) Schematic top view diagram of the experimental setup used in this study in the center hallway of the pig building. The blue area indicates the ground scale platform with a wooden aisle (in red). The red dashed lines indicate gates to regulate individual pig passage. (b) Schematic side view diagram of the experimental setup.

DeepLabCut 2.2b.827 was installed in an Anaconda environment with Python 3.7.7.30 on a custom-built computer running a Windows 10 64-bit operating system with Intel Core i5-vPro CPU processor (2.60GHz) and 8GB RAM memory. Training, evaluation and analysis of the neural network was performed using DeepLabCut in the Google Colaboratory (COLAB) (https://colab.research.google.com/).

To detect body parts on a pig that is walking through the experimental setup, a neural network was trained using DeepLabCut 2.2b27 as described in Nath et al.32. A minimalistic eight body part configuration (Fig.2a; Table 1) was necessary to estimate hip width, shoulder width and body length. Operational definitions can be found in Table 1. Head body parts (Nose, Ear left, and Ear right) were also labeled, but not included in our final structural model as these body parts were frequently occluded in consecutive frames.

(a) Schematic overview of the eight body positions annotated for pose configuration in DeepLabCut27 (created with BioRender.com). 1=Spine1; 2=Shoulder left; 3=shoulder right; 4=Center; 5=Spine2; 6=Hip left; 7=Hip right; 8=Tail base. (b) Example of a labeled pig during weighing using the DeepLabCut software.

Seven videos of approximately one hour recorded on two different days were selected to include variable pig sizes (20120kg) and each video contained multiple pig weighings. From these seven videos, several frames were extracted for annotation using k-means clustering in DeepLabCut. We first annotated 457 frames (~1 frame per pig) which were split into a training dataset (95%; 434 frames) and a test dataset (5%; 23 frames). The network was trained in Google Colaboratory using the ResNet-50 architecture with a batch size of 2. We trained our algorithm until the loss function reached an optimum, which indicated a minimal loss with a minimum number of iterations in this study. Next, we compared mean pixel errors of several models within this optimal region. Models with lowest mean pixel errors were visually checked for body part tracking performance on entire videos. Hereafter, the model that performed optimal was tested for flexibility using unseen single pig videos with pigs of variable size (20 vs 120kg) weighed on different days. As model performance was suboptimal at first, poorly tracked outlier frames were extracted using the DeepLabCut jump algorithm32. This algorithm identifies frames in which one or more body parts jumped more than a criterion value (in pixels) from the last frame32. These outlier frames were refined manually and hereafter added to the training dataset for re-training. In total, 150 outlier frames were extracted from six novel videos containing one single pig to improve tracking performance (25 frames per pig). The final training dataset consisted of 577 (95%) frames and a test dataset of 30 frames (5%). The network was then trained again using the same features as the first training. Additional File 3Video S2 shows an example of a pig with body part tracking.

After posture extractions of body parts using DeepLabCut, body dimension parameters were estimated. The raw dataset contained body part positions and tracking probabilities of 5,102,260 frames. Individual pig IDs were first coupled with video recordings based on time of measurement from the weight dataset. The following steps and analyses were performed in R33. Frames with a mean tracking probability<0.1 over all eight body parts were removed (2,792,252 frames left). This large reduction in number of frames (50% removed) was mainly caused by video frames without any pigs, for example in between weighing of different pens or in between weighings of pigs.

Next, for every weighing event, start and end points were determined to estimate body dimensions and activity traits. For a specific weighing event, a subset was first created containing all frames between the previous and next weighing event. The time of entrance and departure of the pig on the weighing scale was estimated using the x-position (in pixels) of the tail base, as the movement of pigs was predominantly along the x-axis (from right to left; Fig.2b). The frame of entrance was defined as the first frame of a subset where the rolling median (per 10 frames) of the tail base x-position exceeded 1100 pixels (Fig.3). Likewise, the first frame after a pigs weighing event with a rolling median tail base x-position<250 pixels was used to determine time of departure. If these criteria were not met, the first frame and/or the frame at which the weight record took place were used for the time of entrance/departure.

Determination of time window for a weight recording. (a) First, a subset is created as all tail base x-positions between time of recording of the next (orange) and previous (red) weight recording. The start time of the time window is determined as the first value before the own weight recording (green) above the threshold of 1100 pixels (dashed purple line; pig entering weighing scale). The end time of the time window is determined as the first value after the own weight recording (green) below the threshold of 250 pixels (dashed purple line; pig leaving weighing scale). (b) The extracted time window on which body part dimensions will be estimated and trajectory analysis will be performed.

Hip width, shoulder width and body length of a pig were estimated by using the median value of the distance between certain body parts over all frames for a specific weight recording (Table 1, Fig.2). These body dimensions in pixels, were transformed to metrics as 1cm was calculated to be equivalent to 29.1 pixels. The conversion ratio from pixels to centimeters was based on the distance between tiles of the weighing scale, which was known to be exactly 50cm. Total surface area was estimated using the mean value of the area calculated with the st_area function in R from the R-package sf34 using all outer body part locations. Standard deviations of the body part positions were also calculated for all frames between entrance and departure after quality control (as described above), to assess the stability of estimates.

Trajectory analysis was performed using the R-package trajr35 for left and right shoulder, left and right hip and the tail base. For each body part, pixel coordinates were extracted, trajectories were rescaled from pixels to cm and a smoothed trajectory was created using the TrajSmoothSG function. From these smoothed trajectories, the following activity-related features were derived: mean and standard deviation of speed and acceleration (TrajDerivatives), a straightness index (TrajStraightness) and sinuosity (TrajSinuosity2).

The straightness index and sinuosity are related to the concept of tortuosity and associated with an animals orientation and searching behavior35,36. The straightness index is calculated as the Euclidean distance between the start and the endpoint divided by the total length of the movement36. The straightness index is an indication of how close the animals path was to a straight line connecting the start and final point and varies from 0 to 1. Thus it quantifies path efficiency whereas the closer to 1, the higher the efficiency. In our experiment, this path efficiency will be highest when a pigs walks in a straight line during weighing (straightness index=1). Any deviations from this straight linedue to an increased activity of the pig during weighingwill lower the straightness index towards zero. Sinuosity tries to estimate the tortuosity of a random research path by combining step length and the mean cosine of an animals turning angles35,36,37. The sinuosity of a trajectory varies between 0 (random movement) and 1 (directed movement).

In this study we hypothesize that mean speed, straightness index and sinuosity are related to pigs activity during weighing. In an extreme case, a pig will walk in a straight line towards the RFID reader, stand motionless until weight is recorded and continues its walk in a straight line after the gate is opened. This would result in a low mean speed (m/s), a sinuosity >0 and a straightness index of 1. We hypothesize that more active pigs will present more lateral movements, increasing the mean speed and lowering the straightness index and sinuosity. So generally, more calm pigs during weighing will display a lower mean speed, although they might have run with a high speed towards the RFID reader.

The estimations of body dimensions using video recordings analyzed with DeepLabCut were validated by an independent set of 60 pigs after the initial experiment. These pigs came from five pens of different ages (92166days) and were measured manually for tail-neck length and hip width using a simple measuring tape. Pig surface area was estimated for the manual recordings as the multiplication of tail-neck length and hip width. The manual estimates for tail-neck length, hip width and pig surface area were then compared to the estimates from the video analysis by calculating Pearson correlations and root mean squared error (RMSE).

Automated activity traits were validated by comparing these values with manual activity scores given by five trained observers. Video footage of 1748 pig weighings were manually scored for pig activity by at least two observers per pig on a scale from 1 (calm) to 5 (very active). This ordinal activity scale was constructed based on DEath et al. and Holl et al.17,24. The average activity score per pig was then compared with automated activity scores by calculating Pearson correlations.

After estimation of body dimension and activity traits, additional quality control was performed. First, estimates of hip and shoulder width, tail-neck length and pig surface area were set to missing for records with frame by frame standard deviation estimates higher than the mean+3 standard deviations for all records. The thresholds were 10.2cm for hip distance (132 records), 11.8cm for shoulder distance (135 records), 20.6cm for tail-neck length (121 records) and 0.058 m2 for pig surface area (96 records). If the standard deviation of the estimated hip widths over frames within one weighing event of a pig was>8.9cm, the record was set to missing.

Second, for every individual with at least four records (941 pigs, 6807 records), outliers were determined using a second order polynomial regression on the variable of interest in function of age in days. Based on the distribution of the difference between observed and predicted phenotypes for all animals, a threshold for exclusion (record set to missing) was set as three times the standard deviation of the differences. The thresholds were 2.1cm for hip distance (61 records), 2.2cm for shoulder distance (58 records), 6.4cm for tail-neck length (75 records), 0.021 m2 for pig surface area (85 records) and 3.7kg for weight (86 records).

The final dataset after data cleaning included 7428 records from 1556 finishing pigs descending from 73 Pitrain sires and 204 crossbred dams. Pedigree comprised 4089 animals, where the median pedigree depth of Pitrain sires was 15 generations (min 10; max 17) and 3 (min 0; max 6) for crossbred dams.

We estimated genetic parameters (heritability and genetic correlations) using the blupf90 suite of programs38. Genetic variances and heritabilities were estimated with average information REML, implemented in airemlf90 and invoked with the R-package breedR39 with the options EM-REML 20, "use_yams" and se_covar_function. Genetic parameters were first estimated on the full dataset and thereafter on subsets per pigs weight recording (1 to 8). The first weight recording, for example, corresponds with a dataset of 1176 pigs between 78 and 89days of age (Table 2). We estimated h2 as the proportion of additive genetic variance divided by total variance, whereas the common environmental effect (c2) was estimated as the proportion of variance explained by random environmental effects (c), divided by total variance.

Genetic correlations (rg) between traits were estimated using bivariate animal models (airemlf90). Genetic correlations were first calculated between all possible trait combinations using the full dataset. Hereafter, the genetic correlations within traits for all pairwise weighing events were estimated (so two recordings of the same trait were treated as two different traits). By doing this, we can evaluate if a trait genetically changes over time.

The estimated animal models were of the form:

where y is the vector with phenotypes for the studied trait(s); b is the vector containing the fixed effects (sex, 2 levels; parity of dam, 4 levels) and covariates (age); a is the vector of additive genetic effects (4089 levels); c is the vector of random environmental effects (65 levels); e is the vector of residual effects; X, Z and W are incidence matrices for respectively fixed effects, random animal effects and random permanent environmental effects. The random environmental effect c is a combination of date of entrance at the fattening farm and weighing date. Every two weeks, a new batch of pigs arrived at fattening farm. Parity of dams consisted of four classes (1, 23, 45, 6+).

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Estimating genetics of body dimensions and activity levels in pigs using automated pose estimation | Scientific Reports - Nature.com

THOUSAND OAKS, Calif., Sept. 12, 2022 /PRNewswire/ -- Amgen AMGN will present at Bank of America Merrill Lynch's 2022 Global Healthcare Conference at 4:55 a.m. ET on Thursday, Sept. 15, 2022. Peter H. Griffith, executive vice president and chief financial officer at Amgen, will present at the conference. The webcast will be broadcast over the internet simultaneously and will be available to members of the news media, investors and the general public.

The webcast, as with other selected presentations regarding developments in Amgen's business given by management at certain investor and medical conferences, can be found on Amgen's website, http://www.amgen.com, under Investors. Information regarding presentation times, webcast availability and webcast links are noted on Amgen's Investor Relations Events Calendar. The webcast will be archived and available for replay for at least 90 days after the event.

About AmgenAmgen is committed to unlocking the potential of biology for patients suffering from serious illnesses by discovering, developing, manufacturing and delivering innovative human therapeutics. This approach begins by using tools like advanced human genetics to unravel the complexities of disease and understand the fundamentals of human biology.

Amgen focuses on areas of high unmet medical need and leverages its expertise to strive for solutions that improve health outcomes and dramatically improve people's lives. A biotechnology pioneer since 1980, Amgen has grown to beone ofthe world'sleadingindependent biotechnology companies, has reached millions of patients around the world and is developing a pipeline of medicines with breakaway potential.

Amgen is one of the 30 companies that comprise the Dow Jones Industrial Average and is also part of the Nasdaq-100 index. In 2021, Amgen was named one of the 25 World's Best Workplaces by Fortune and Great Place to Work and one of the 100 most sustainable companies in the world by Barron's.

For more information, visitwww.amgen.comand follow us onwww.twitter.com/amgen.

CONTACT: Amgen, Thousand OaksMegan Fox, 805-447-1423 (media)Jessica Akopyan, 805-447-0974 (media)Arvind Sood, 805-447-1060 (investors)

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Amgen (NASDAQ:AMGN) AMGEN ANNOUNCES WEBCAST OF 2022 BANK OF AMERICA MERRILL LYNCH GLOBAL HEALTHCARE CON - Benzinga

BY GARETH WILLMER

Game theory mathematics is used to predict outcomes in conflict situations. Now it is being adapted through big data to resolve highly contentious issues between people and the environment.

Game theory is a mathematical concept that aims to predict outcomes and solutions to an issue in which parties with conflicting, overlapping or mixed interests interact.

In theory, the game will bring everyone towards an optimal solution or equilibrium. It promises a scientific approach to understanding how people make decisions and reach compromises in real-world situations.

Game theory originated in the 1940s in the field of economics. The Oscar-winning movieA Beautiful Mind (2001)is about the life of mathematician John Nash (played by Russell Crowe), who was awarded the1994 Nobel Prize in Economic Sciencesfor his work in this area.

Although the concept has been around for many decades, the difference now is the ability to build it into computer-based algorithms, games and apps to apply it more broadly, said Professor Nils Bunnefeld, a social and environmental scientist at the University of Stirling, UK. This is particularly true in the age of big data.

Game theory as a theoretical idea has long been around to show solutions to conflict problems, he said. We really see the potential to move this to a computer to make the most of the data that can be collected, but also reach many more people.

Conservation conflicts

Prof Bunnefeld led the EU-backedConFooBioproject, which applied game theory to scenarios where people were in conflict over resources and the environment. His team wanted to develop a model for predicting solutions to conflicts between food security and biodiversity.

The starting point was that when we have two or more parties at loggerheads, what should we do, for example, with land or natural resources? Should we produce more food? Or should we protect a certain area for biodiversity? he said.

The team focused on seven case studies, ranging from conflicts involving farmers and conservation of geese in Scotland to ones about elephants and crop raiding in Gabon.

ConFooBio conducted more than 300 game workshops with over 900 people in numerous locations including Gabon, Kenya, Madagascar, Tanzania and Scotland.

Ecological challenges

Prof Bunnefeld realised it became necessary to step back from pure game theory and instead build more complex games to incorporate ecological challenges the world currently faces, like climate change. It also became necessary to adopt a more people-based approach than initially planned, to better target the games.

Participants included people directly involved in these conflicts, and in many cases that were very unhappy, said Prof Bunnefeld.

Through the games, we got high engagement from communities, even from those where conflict is high and people can be reluctant to engage in research. We showed that people are able to solve conflicts when they trust each other and have a say, and when they get adequate payments for conservation efforts.

The team developed a modelling framework to predict wildlife management outcomes amid conflict. Freely available, it has been downloaded thousands of times from theConFooBio website.

Conservation game

The researchers also created an accessible game about conservation calledCrops vs Creatures, in which players decide between a range of options from shooting creatures to allocating habitat for conservation.

Prof Bunnefeld hopes these types of game become more available on a mainstream basis via app stores such as one on conflicts in the realm of biodiversity and energy justice in a separate initiative he works on called the Beacon Project.If you tell people you have an exciting game or you have a complex model, which one are they going to engage with? I think the answer is pretty easy, he said.

In the ConFooBio project, weve been able to show that our new models and algorithms can adapt to new situations and respond to environmental and social changes, added Prof Bunnefeld. Our models are useful for suggesting ways of managing conflicts between stakeholders with competing objectives.

Social media dynamics

Another project,Odycceus, harnessed elements of game theory to investigate what social media can tell us about social dynamics and potentially assist in the early detection of emerging social conflicts.

They analysed the language, content and opinions of social media discussions using data tools.

Such tools are required to analyse the vast amount of information in public discourse, explained Eckehard Olbrich, coordinator of the Odycceus project, and a physicist at the Max Planck Institute for Mathematics in the Sciences in Leipzig, Germany.

His work is partially motivated by trying to understand the reasons behind the polarisation of views and the growth of populist movements like far-right organisation Pegida, which was founded in his hometown of Dresden in 2014.

The team created a variety of tools accessible to researchers via an open platform known asPenelope. These included the likes of theTwitter Explorer, which enables researchers to visualise connections between Twitter users and trending topics to help understand how societal debates evolve.

Others included two participatory apps known as the Opinion Observatory and the Opinion Facilitator, which enable people to monitor the dynamics of conflict situations, such as by helping interlink news articles containing related concepts.

Patterns of polarisation

These tools have already allowed us to get a better insight into patterns of polarisation and understanding different world views, said Olbrich.

He said, for example, that his team managed to develop a model about the effect of social feedback on polarisation thatincorporated game-theoretic ideas.

The findings suggested that the formation of polarised groups online was less about the traditional concept of social media bubbles and echo chambers than the way people build their identity by gaining approval from their peers.

He added that connecting the dots between game theory and polarisation could have real-life applications for things like how best to regulate social media.

In a game-theoretic formulation, you start with the incentives of the players, and they select their actions to maximise their expected utility, he said. This allows predictions to be made of how people would change their behaviour if you, for instance, regulate social media.

Olbrich added that he hopes such modelling can furnish a better understanding of democracy and debates in the public sphere, as well as indicating to people better ways to participate in public debates. Then we would have better ways to deal with the conflicts we have and that we have to solve, he said.

But there are also significant challenges in using game theory for real-world situations, explained Olbrich.

Varying outlooks

For example, incorporating cultural differences into game theory has proved difficult because such differences may mean two people have hugely varying ways of looking at a problem.

The problem with game theory is that its looking for solutions to the way a problem can be solved, added Prof Bunnefeld.

Having looked at conflicts over the last few years, to me it is clear that we cant solve conflicts, we can only manage them. Building in factors like climate change and local context is also complex.

But game theory is a useful way to explore models, games and apps for dealing with conflicts, he said. Game theory is, from its very simple basics to quite complex situations, a good entry point, said Prof Bunnefeld.

It gives us a framework that you can work through and also captures peoples imagination.

Research in this article was funded via the EUsEuropean Research Council and originally publishedin Horizon, the EU Research and Innovation Magazine.

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