14 The Shape of the Revolution
A Place to Stand
Science relies on showing clear causes and making predictions. Before the 1960s, social sciences mostly used simple statistics and storytelling, lacking the means to analyze complex human behaviors through numbers. The introduction of computers in the early 1960s changed this, allowing social scientists to handle more complicated data and make better claims about causation. Despite these improvements, researchers still struggle with finding a firm basis for understanding human behavior, especially in the nature versus nurture debate. This debate is crucial for understanding how people think and act, which affects social policies and programs. While new fields like genetics and neuroscience offer hope for better insights, the question of what is innate in human nature remains unanswered.
Interpreting Causation in an Omnigenic, Pleiotropic World
Genetic causation is more complicated than people used to think. At first, it seemed clear that after scientists completed the human genome sequence, they could easily find out which genetic variants caused specific traits. A notable study in 1999 identified at least 15 genetic locations related to autism, which seemed like a lot at the time. However, more recent research shows that many traits are affected by a much larger number of genetic locations, often in the thousands.
Most complex traits are influenced by genetic variants that do not change proteins. Instead, these variants affect how genes are regulated. For example, for height, nearly 62% of common genetic variants are linked to height differences. This could mean about 100,000 potentially important SNPs.
Another key idea is pleiotropy, where one SNP affects several traits. A study found that some genetic variants related to general cognitive ability were also connected to many unrelated health traits. Pleiotropy can be vertical, where one trait leads to another, or horizontal, where a trait affects traits that are not directly related.
When scientists try to determine cause and effect from genetic data, they face many challenges. Gene-environment interactions can make it hard to understand why certain traits, like preferences for certain foods, differ between groups. Also, some genetic variants discovered in studies might just be “tag” SNPs, meaning they are near the real variants but not the ones directly affecting the traits.
Overall, linking genetic differences to specific traits is very complex and often mixed with environmental and cultural influences. While researchers are making progress in identifying important genetic locations, understanding how they relate to traits remains a difficult task.
The Great Debate
Polygenic scores are important tools that help measure how much genetics can influence different traits, including mental health characteristics. Over the past ten years, the understanding of these scores has advanced a lot. For instance, researchers found that polygenic scores could explain 15 percent of the differences in educational achievement, which is often connected to intelligence. This progress has led to different opinions about how significant polygenic scores are.
There are two main views on polygenic scores. One view supports their importance, believing they can predict psychological traits well. Supporters say that polygenic scores work like performance ratings and combine different genetic factors linked to specific traits. They argue that these scores could change clinical psychology by identifying genetic risks for mental health issues before symptoms show up. This means that instead of just diagnosing problems, it would be possible to understand a range of risks for psychological conditions earlier.
Those in favor of polygenic scores suggest five key changes they could bring to clinical psychology. First, they could help find an individual’s genetic risks before any issues develop. Second, the focus could shift from strict diagnoses of disorders to understanding psychological traits on a spectrum. Third, treatment plans could become more personalized based on a person’s genetic information. Fourth, there could be more focus on prevention strategies for those at risk. Finally, polygenic scores could encourage looking at positive traits in mental health instead of just problems.
On the other side, some people question whether polygenic scores can truly show direct causes of complex traits. This perspective highlights the idea of the "Phenotypic Null Hypothesis," which suggests that many traits may be heritable but not necessarily caused by specific genes. For example, while divorce can have genetic links, this doesn’t mean that the reasons for divorce are purely genetic.
This viewpoint claims that behaviors, like divorce, are influenced by many different factors. Thus, trying to find a simple genetic reason for behaviors can be misleading. It emphasizes that human traits come from a combination of genetics and the environment.
In summary, while polygenic scores have great potential to help understand genetics and behavior, figuring out their implications requires careful consideration of how genetic and other factors work together in influencing human traits.
Predictions
There are two main viewpoints about genetics research, represented by Plomin and Turkheimer. While both accept that there are connections between polygenic scores and traits, they differ in how they interpret these connections. Plomin believes that polygenic scores can be useful for predicting traits, even if they don’t explain how those traits develop. In contrast, Turkheimer warns against assuming that these scores show causation. The discussion between these two schools of thought will continue to change as new methods and large genomic databases become available, but some outcomes seem likely.
The author thinks that in applied social science, being able to predict outcomes is more important than understanding the exact causes. Right now, traditional measures like IQ scores do a better job of predicting cognitive ability than polygenic scores can. However, the potential of using genomic data is compared to the early stages of aviation, suggesting that significant advancements are on the way. By the end of the 2020s, it is expected that research in social behavior that does not include polygenic scores will be considered incomplete, as these scores will provide valuable predictive information, even if the exact causes remain unclear.
The impact of genomic research is expected to affect all fields of social science. For instance, psychology will increasingly use genome data to understand better human thoughts, feelings, and behaviors. In anthropology, the subfields of archaeology and physical anthropology can benefit from studying ancient DNA. Cultural and linguistic anthropology may also incorporate genomic information, though this could vary among researchers. Sociology, especially, is poised for change, as much of its research already concerns traits that can be influenced by genetics. In economics and political science, understanding how genetics affects decision-making will become more relevant.
In addition, genomic research is predicted to play a significant role in public policy analysis across various topics, including education, crime, and welfare. The use of polygenic scores in education research is already showing that these scores can help improve educational practices and policies.
Genomic data can also help researchers understand the complex roles of genetics and the environment, especially when it comes to issues like socioeconomic disadvantage. Polygenic scores could reveal how much a person's potential is related to their genetic background, which could lead to better programs aimed at helping those in need. This change may clear up ongoing debates about how much traits are passed down through genes compared to the effects of the environment.
Additionally, using genomic data will allow researchers to explore the connections between genetics and the environment more deeply than traditional twin studies. This could help them understand patterns of behavior and outcomes across different groups of people. The improved methods could provide new insights and change how researchers think about the importance of genetic and environmental influences on individuals.
Recapitulation
The debate about the relevance and effects of polygenic scores continues among experts, with differing views on their significance in causation and prediction. However, it is clear that the use of these scores is becoming widespread, particularly in medical research, where their usage has rapidly increased in publications. This trend is expected to extend to the social sciences, indicating a significant shift in research approaches. Polygenic scores are viewed as a powerful new tool that will expand the range of questions researchers can explore, ultimately transforming social sciences.
A Place to Stand
Science relies on showing clear causes and making predictions. Before the 1960s, social sciences mostly used simple statistics and storytelling, lacking the means to analyze complex human behaviors through numbers. The introduction of computers in the early 1960s changed this, allowing social scientists to handle more complicated data and make better claims about causation. Despite these improvements, researchers still struggle with finding a firm basis for understanding human behavior, especially in the nature versus nurture debate. This debate is crucial for understanding how people think and act, which affects social policies and programs. While new fields like genetics and neuroscience offer hope for better insights, the question of what is innate in human nature remains unanswered.
Interpreting Causation in an Omnigenic, Pleiotropic World
Genetic causation is more complicated than people used to think. At first, it seemed clear that after scientists completed the human genome sequence, they could easily find out which genetic variants caused specific traits. A notable study in 1999 identified at least 15 genetic locations related to autism, which seemed like a lot at the time. However, more recent research shows that many traits are affected by a much larger number of genetic locations, often in the thousands.
Most complex traits are influenced by genetic variants that do not change proteins. Instead, these variants affect how genes are regulated. For example, for height, nearly 62% of common genetic variants are linked to height differences. This could mean about 100,000 potentially important SNPs.
Another key idea is pleiotropy, where one SNP affects several traits. A study found that some genetic variants related to general cognitive ability were also connected to many unrelated health traits. Pleiotropy can be vertical, where one trait leads to another, or horizontal, where a trait affects traits that are not directly related.
When scientists try to determine cause and effect from genetic data, they face many challenges. Gene-environment interactions can make it hard to understand why certain traits, like preferences for certain foods, differ between groups. Also, some genetic variants discovered in studies might just be “tag” SNPs, meaning they are near the real variants but not the ones directly affecting the traits.
Overall, linking genetic differences to specific traits is very complex and often mixed with environmental and cultural influences. While researchers are making progress in identifying important genetic locations, understanding how they relate to traits remains a difficult task.
The Great Debate
Polygenic scores are important tools that help measure how much genetics can influence different traits, including mental health characteristics. Over the past ten years, the understanding of these scores has advanced a lot. For instance, researchers found that polygenic scores could explain 15 percent of the differences in educational achievement, which is often connected to intelligence. This progress has led to different opinions about how significant polygenic scores are.
There are two main views on polygenic scores. One view supports their importance, believing they can predict psychological traits well. Supporters say that polygenic scores work like performance ratings and combine different genetic factors linked to specific traits. They argue that these scores could change clinical psychology by identifying genetic risks for mental health issues before symptoms show up. This means that instead of just diagnosing problems, it would be possible to understand a range of risks for psychological conditions earlier.
Those in favor of polygenic scores suggest five key changes they could bring to clinical psychology. First, they could help find an individual’s genetic risks before any issues develop. Second, the focus could shift from strict diagnoses of disorders to understanding psychological traits on a spectrum. Third, treatment plans could become more personalized based on a person’s genetic information. Fourth, there could be more focus on prevention strategies for those at risk. Finally, polygenic scores could encourage looking at positive traits in mental health instead of just problems.
On the other side, some people question whether polygenic scores can truly show direct causes of complex traits. This perspective highlights the idea of the "Phenotypic Null Hypothesis," which suggests that many traits may be heritable but not necessarily caused by specific genes. For example, while divorce can have genetic links, this doesn’t mean that the reasons for divorce are purely genetic.
This viewpoint claims that behaviors, like divorce, are influenced by many different factors. Thus, trying to find a simple genetic reason for behaviors can be misleading. It emphasizes that human traits come from a combination of genetics and the environment.
In summary, while polygenic scores have great potential to help understand genetics and behavior, figuring out their implications requires careful consideration of how genetic and other factors work together in influencing human traits.
Predictions
There are two main viewpoints about genetics research, represented by Plomin and Turkheimer. While both accept that there are connections between polygenic scores and traits, they differ in how they interpret these connections. Plomin believes that polygenic scores can be useful for predicting traits, even if they don’t explain how those traits develop. In contrast, Turkheimer warns against assuming that these scores show causation. The discussion between these two schools of thought will continue to change as new methods and large genomic databases become available, but some outcomes seem likely.
The author thinks that in applied social science, being able to predict outcomes is more important than understanding the exact causes. Right now, traditional measures like IQ scores do a better job of predicting cognitive ability than polygenic scores can. However, the potential of using genomic data is compared to the early stages of aviation, suggesting that significant advancements are on the way. By the end of the 2020s, it is expected that research in social behavior that does not include polygenic scores will be considered incomplete, as these scores will provide valuable predictive information, even if the exact causes remain unclear.
The impact of genomic research is expected to affect all fields of social science. For instance, psychology will increasingly use genome data to understand better human thoughts, feelings, and behaviors. In anthropology, the subfields of archaeology and physical anthropology can benefit from studying ancient DNA. Cultural and linguistic anthropology may also incorporate genomic information, though this could vary among researchers. Sociology, especially, is poised for change, as much of its research already concerns traits that can be influenced by genetics. In economics and political science, understanding how genetics affects decision-making will become more relevant.
In addition, genomic research is predicted to play a significant role in public policy analysis across various topics, including education, crime, and welfare. The use of polygenic scores in education research is already showing that these scores can help improve educational practices and policies.
Genomic data can also help researchers understand the complex roles of genetics and the environment, especially when it comes to issues like socioeconomic disadvantage. Polygenic scores could reveal how much a person's potential is related to their genetic background, which could lead to better programs aimed at helping those in need. This change may clear up ongoing debates about how much traits are passed down through genes compared to the effects of the environment.
Additionally, using genomic data will allow researchers to explore the connections between genetics and the environment more deeply than traditional twin studies. This could help them understand patterns of behavior and outcomes across different groups of people. The improved methods could provide new insights and change how researchers think about the importance of genetic and environmental influences on individuals.
Recapitulation
The debate about the relevance and effects of polygenic scores continues among experts, with differing views on their significance in causation and prediction. However, it is clear that the use of these scores is becoming widespread, particularly in medical research, where their usage has rapidly increased in publications. This trend is expected to extend to the social sciences, indicating a significant shift in research approaches. Polygenic scores are viewed as a powerful new tool that will expand the range of questions researchers can explore, ultimately transforming social sciences.