Week 1 What We Know and What We Don’t

Behavior Genetics is a field that is defined by a common set of questions and methods, rather than being focused on any particular topic of study. This week we discuss some of the commonalities, or themes, that recur throughout research across topics, in terms of the questions we ask, what we know, and what we don’t (and maybe can’t) know.

Objectives

  • Introduce common terminology and themes in behavior genetics.
  • Become comfortable with the typical weekly course structure.
  • Evaluate and share what knowledge you come to this course with and what you hope to learn.

Lecture Notes

Hello and welcome to Week 1 of Psyc 408!

Each week will begin with some (variably brief) notes by me, your instructor, about the topics, activities, and expectations for that week.

This week, our major goal is to get oriented to the course (both in terms of –gesturing big– meta theoretic pedagogical conceptualization and, also, how to use the website).

About Me

I am a recently tenured (this summer, yay!) Associate Professor in the Psychology Department. Within Psychology, I’m formally part of the Social-Personality area. I do have a Ph.D., so my titles are either Dr. or Professor. However, Dr./Professor Derringer sounds like a supervillain, and now that you are taking my class we are friends, so you may call me Jaime. (Important note: for ALL of your instructors, default to Dr. or Professor until/unless they invite you to do otherwise; it costs you nothing and buys a lot of goodwill.)

I went to undergrad at Carnegie Mellon University in Pittsburgh (go Steelers!), where I majored in Psychology and minored in Architecture (after dropping my major in Architecture due to a D in Physics and a Withdraw-Rather-Than-Fail in Freehand Drawing). As an undergrad I worked as a research assistant in an infant cognition lab where I learned that I loved research but would very much prefer to NOT work directly with participants - the babies weren’t so bad, but the parents… parents are a lot.

I decided to go to grad school because by that point I had gotten pretty good at school in general and learned that Ph.D. programs for psychology (and many of the social/less-social sciences) finally start PAYING YOU to go to school. I had a general interest in serial killers so I googled “psychology grad school psychopathy” and found the person who would become my grad school advisor, Dr. Bob Krueger, at the University of Minnesota. (Actually, I found his advisor, Dr. Avshalom Caspi, first, but Avshalom was not taking grad students that year and recommended I look into his plucky former student. Plucky is my word, not his.)

At the University of Minnesota, I was in the Personality, Individual differences, and Behavior genetics (PIB) area within their Psychology Department. Behavior genetics seemed interesting on paper, but I had never taken a genetics course (and, honestly, still haven’t - I tried to take one my last semester of undergrad but hadn’t taken the prerequisite of Organic Chemistry). Minnesota is home to one of the longest-running modern twin studies, and I spent my first two years working with their data (comparing twins - both identical and fraternal - is one of the most common, classic methods in human behavior genetics). Then, just at the point that I had completed my Master’s degree and was about to formally become a Doctoral Candidate, my advisor took a new job at Washington University in St. Louis and our whole lab up and moved. There was no behavior genetics area at WashU, so I had a choice to make: Clinical Psychology or Social-Personality. I chose Clinical because there are no jobs in Social-Personality.

So I began, from scratch, clinical coursework and training to become a therapist. I saw clients and quickly realized that I. Am. Not. Cut. Out. To. Be. A. Therapist. But, happily, WashU had access to something that, at the time, Minnesota did not: genome-wide molecular genetic data. The Psychiatry department in their medical school houses a research group focused primarily on the genetics of addiction and I was fortunate to be able to begin working with them, and their incredibly rich data (which at the time was much more expensive than it is now, and so much harder to come by). I was bopping along happily learning all about molecular genetics when - boom - my advisor took a job BACK at Minnesota.

Four years and two moves into my Ph.D., I found myself finishing my dissertation back in Minnesota, back in the PIB area (which suited me just fine, as I’m not sure I could have completed the 1-year clinical internship required to complete a Ph.D. in Clinical Psychology). My dissertation was on the genetics of substance use, examining in BOTH the Minnesota population-representative twin sample AND the WashU clinically-ascertained sample whether (1) measures of substance use function similarly across general and clinical samples (they do), (2) general heritability of substance use changes with exposure to childhood maltreatment (maybe), and (3) the effects of certain specific genes are altered by exposure to childhood maltreatment (probably not, but the data at the time weren’t good enough to properly test this).

Toward the end of my Ph.D., a relatively new method, the genome-wide association study (GWAS, pronounced “GEE-wahss”) was becoming more common. In a GWAS, rather than testing specific genes theoretically identified as potentially important for certain outcomes for association with or modification of the outcome, millions of individual variants from all across the genome are all tested for association with an outcome (literally: “Variant 1 correlated with the outcome? No. Variant 2 correlated with the outcome? No… Variant 2,000,042 correlated with the outcome?…”). At the same time, it was becoming clear that there are NO large-effect single-variant genetic effects on human behavioral outcomes - and (because of how our statistics work) if we wanted to find individual variants that were reliably and replicably correlated with human behavior, we were going to need HUGE sample sizes (like, 100,000 participants or don’t even bother). My advisor was contacted by a group of economists who were interested in putting together the first-ever 100,000+ person GWAS of a behavioral outcome, and he recommended me to serve as a primary data analyst. I pointed out to him that I had never done anything even close to that. His advice: “Say yes, and figure out how later.” I took a postdoctoral research position at the Institute for Behavioral Genetics at the University of Colorado - Boulder and spent the next two years doing GWAS.

The outcome the economists wanted to look at was educational attainment: how many years of schooling you’ve attended and whether or not you graduated college. It’s “weakly heritable” (~10-20%) but it has one thing going for it - it’s a piece of data that’s collected in pretty much every study ever. At the time (this is way back in 2010), the largest GWAS datasets were mostly from medical studies and so had sparse behavioral data available. If we wanted to get to 100,000 participants, we had to work with what we had (at the time, GWAS data on a single participant cost ~$1000 - now it’s down to <$50). Educational attainment is interesting to economists because it’s correlated with a Whole Bunch of Stuff - not necessarily causally, but that’s not always the goal. The psychologists on the project, myself included, didn’t think it would “work” (that is, find any associated genetic variants). Educational attainment is a “noisy” variable - a lot of things influence it, both systematically (personal, family, cultural characteristics) and randomly (luck, war, pandemics). But we figured the first truly large-scale behavioral GWAS was bound to get published somewhere decent, so might as well go along for the ride.

We found 3 genetic variants associated with educational attainment, published the paper in Science, and that is the project that (arguably*) landed me this job.

  • Rietveld, C. A., Medland, S. E., Derringer, J., Yang, J., Esko, T., Martin, N. W., … & Albrecht, E. (2013). GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science, 340(6139), 1467-1471. http://doi.org/10.1126/science.1235488

*My other area of research is measurement development and evaluation - it probably didn’t hurt my application for my job at UIUC as a Personality Psychologist that I helped develop the Personality Inventory for DSM-5, a continuous/non-categorical measure of personality disorder traits commissioned by the American Psychiatric Association and formally used in the DSM-5:

  • Krueger, R. F., Derringer, J., Markon, K. E., Watson, D., & Skodol, A. E. (2012). Initial construction of a maladaptive personality trait model and inventory for DSM-5. Psychological medicine, 42(9), 1879. https://doi.org/10.1017/S0033291711002674

What is Behavior Genetics?

Behavior genetics is a field that is defined by a common set of methods which broadly attempt to answer two questions:

  • Why do individuals differ from one another? and
  • What causes someone to be who they are?

These questions are related but can require very different approaches to address, and we will spend the semester discussing the approaches and limitations of our attempts to understand the answers to both of them.

Like any field, behavior genetics commonly uses a unique set of terms that is quite inscrutable to outsiders. Some that will come up CONSTANTLY throughout the semester:

  • Phenotype: This is any outcome that we are interested in. It can be a behavior, a physical characteristic, a low-level biological function, literally (almost) anything - except for the genotype itself.
  • Genotype: The sequence of As, Cs, Gs, and Ts that make (or rather, represent) the rungs on the ladder of everyone’s DNA (humans and non-humans alike).
  • Environment: Everything that is not the genotype. This can be what we usually think of when we hear the word environment (family, culture), it can be your experiences, personal traits, it can even be biological environments, like hormones and what you’ve had to eat today, or ever. (Note: the difference between a “phenotype” and an “environment” is in the eye of the beholder - phenotypes can be environments and vice versa.)

Why do we use jargon? Well, it makes us sound fancy and, as with all language, it provides shortcuts to understanding that save time once you’re familiar with it. But in behavior genetics, we have another layer of communication to contend with: historical context. Behavior genetics, as a field, is inextricably linked with eugenics (the “father” of behavior genetics, Francis Galton, coined the term eugenics and most of the prominent early scientists in the field were avid advocates). Jargon makes our papers hard to read, and when they are hard to read, fewer people will read them, and we (the scientists) spend less time having to publicly contend with that historical (and, honestly, present) context. We’ll talk more about eugenics and the real-world applications of behavior genetics (both good and evil - but, on balance, mostly evil) in the coming weeks.

So, we have a whole field of defensive scientists writing dense papers, either on purpose or (for the same reason MOST academic writing is dense and boring) because we’re not trained to write well. That’s fine if there’s nothing terribly interesting or practically important in those papers. But the reality is this information, and how we arrive at it, is becoming critically more important all the time as technology advances and the potential applications expand.

In the past few years, we’ve seen a rapid decline in the cost of genotyping, combined with an incredible explosion in the development of new technologies. Genetic information is used in reproductive decision making (from pre-conception genetic counseling to embryo selection to prenatal and neonatal screening), diagnosis and prediction of disease and non-disease phenotypes (in medical and non-medical settings, including direct-to-consumer genotyping services), and criminal proceedings (identification of individuals and, occasionally, determining responsibility). I keep seeing a sponsored tweet advertising a service to tell me what I should eat based on my DNA.

I have one goal for this course: Scientific Literacy. In life, and soon if not already, you are going to be asked to make decisions and buy services based on the research we talk about in this class. I want you to be an educated consumer.

There are no course prerequisites for Psyc 408, but there is a personal one: you need to be interested in the journey we are about to embark on. This material is not easy, but motivation will take you as far as you need to go. If you’ve made it this far, and you’ve browsed the course website, and you are still thinking “this sounds interesting!”: you are ready to go.

Themes in Behavior Genetics

Although there is essentially an infinite number of phenotypes that a person might be interested in, as a field organized around a common set of methods we’ve noticed over the years that, regardless of the phenotype, some consistencies tend to emerge, in both basic findings and new questions/theories that emerge. In this course, we will refer to these as Themes in Behavior Genetics, and we will use these Themes to organize the many topics (and many, MANY readings and other source materials) that we will cover.

These themes are drawn from:

  • Plomin, R., DeFries, J. C., Knopik, V. S., & Neiderhiser, J. M. (2016). Top 10 replicated findings from behavioral genetics. Perspectives on Psychological Science, 11(1), 3-23. https://doi.org/10.1177/1745691615617439
  • Briley, D. A., Livengood, J., Derringer, J., Tucker-Drob, E. M., Fraley, R. C., & Roberts, B. W. (2019). Interpreting behavior genetic models: seven developmental processes to understand. Behavior Genetics, 49(2), 196-210. https://doi.org/10.1007/s10519-018-9939-6

These happen to be this week’s options for the Read & Discuss via Perusall participation activities - they go into more detail about how we’ve arrived at or current thinking about each of the following themes.

We will refer to these extensively throughout the semester, so keep this list (and the readings, for more details) handy.

  • Everything is at least a little bit heritable (that is, more closely genetically related individuals are more similar phenotypically)
  • Nothing is 100% heritable (even identical twins are a little different from one another on anything we can measure)
  • Heritability is caused by many genes of small effect (there is no “gene for” in psychology, human behavior, or indeed ANY trait that commonly varies between people)
  • Correlations between phenotypes are partly due to correlated genetic/heritable influences
  • Heritability increases through development (at least through middle adulthood)
  • Trait stability or consistency across time within an individual is due to stable genetic influences
  • Even things we think of as “the environment” show non-zero heritability (example: divorce)
  • Correlations between phenotypes and environments are partly due to correlated genetic/heritable influences
  • Most environments are not shared between people, even siblings or twins raised together
  • Abnormal is normal (influences on extremes that we label as “disorders” versus normal-range traits are not different in kind, just amount)
  • Phenotypes (means, variances, and presentations) change over development - we cannot use the same measures or interpretations without knowing the developmental context
  • Most behavior genetic research necessarily assumes (because of data limitations) that genetic and environmental influences are independent (that is, uncorrelated)
  • Mating is non-random (although random mating is an assumption of many of our models, again because of data limitations)
  • The development of an individual is not necessarily the same as the average developmental course Gene-environment correlation (rGE) exists and, if not accounted for, causes biases in our estimation of heritability and genetic effects
  • Gene-environment interaction (GxE) potentially explains why people exposed to the same environments respond differently
  • None of these influences exist in a vacuum: simultaneous gene-environment interplay (rGE & GxE) is almost certainly happening all the time, to all of us, in parallel, in sequence, reciprocally. The True Model (if such a thing exists) is almost certainly more complex than we could ever gather data for and test.

It is not my expectation that you memorize or understand these this first week. The goal now is awareness - these themes will pop up over and over again, throughout the course, across topics both in class and in your paper. Keep them handy as a reference, and know that you’re going to learn so much about all of them by the end of the semester.

Prep Work

Below is a list of materials to review early in the week. Although these activities do not earn points, they will prepare you to undertake the Participation Activities and Course Project assignments.

  • Fill out the Start of Semester Student Survey
    • Let me know who you are & how you see this course going.
  • Browse the course website and Syllabus
    • I’d recommend starting with the Schedule and looking up the late work policies.
  • Distinguish between Scholarly and Popular sources
  • (optional) Watch some Crash Course: Biology videos

Participation Activities

You can earn up to 4 points for participation activities each week by selecting and completing tasks from the “menu” listed below. You may complete more than four tasks if you’d like, but the maximum number of points awarded will be 4 per week. Each activity is worth 1 point.

You can manually keep track of the activities you’ve completed in Moodle by ticking the checkbox to the right of each item. Points will be posted to the grade book within a week.

Unless otherwise specified, participation activities are due before Friday 5:00 p.m. Central Time (CT) (time zone conversion) during the weekly module in which they are listed.

  • Try the Genetic Knowledge Quiz
    • Check your starting knowledge of genetic information. You get a participation point for doing it, regardless of your score (and will be able to take it again at the end of the course to see how your knowledge has changed).
    • This quiz comes from: Chapman, R., Likhanov, M., Selita, F., Zakharov, I., Smith-Woolley, E., & Kovas, Y. (2019). New literacy challenge for the twenty-first century: genetic knowledge is poor even among well educated. Journal of Community Genetics, 10(1), 73-84. https://doi.org/10.1007/s12687-018-0363-7
  • Ask a question in the Course Help Discussion Forum
    • (I’m offering a point for this in the first week to encourage engagement :)
  • Read & Discuss via Perusall: Plomin et al 2016 Top 10 Replicated Findings From Behavioral Genetics. Perspectives on Psychological Science, 11(1), 3-23. https://doi.org/10.1177/1745691615617439
    • This review article describes in-depth some of the common themes in human behavior genetics that we’ll be identifying in materials we encounter throughout the course.
  • Read & Discuss via Perusall: Briley et al 2019 Interpreting Behavior Genetic Models- Seven Developmental Processes to Understand. Behavior Genetics, 49(2), 196-210. https://doi.org/10.1007/s10519-018-9939-6
    • This review article describes in-depth some of the common themes in human behavior genetics that we’ll be identifying in materials we encounter throughout the course.
  • Find & Share a popular media piece (eg. blog post, news story) about recent research in human behavior genetics and the APA-formatted citation for the paper it is reporting to the News, Memes, and Everything In Between Discussion Forum
    • Format: Make the subject of your thread the headline of the Popular source you’re sharing. Include in the text of your post (1) a brief 1-2 sentence summary in your own words of what the scholarly source is about, (2) a link to the Popular source, and (2) the APA-formatted citation for the Scholarly source it is reporting on.
    • Tip 1: You can search general news feeds by topic, e.g. https://news.google.com/search?q=behavior+genetics
    • Tip 2: Use Google Scholar to find the Scholarly source (using author names, topic keywords, journal name, and/or the article title - whatever clues you can find in the Popular source). Once you’ve found the correct Scholarly source entry in Google Scholar, click on the icon of quotation marks below the listing to bring up the citation in a variety of formats (including APA).
    • Caveat: A point will only be awarded to the first person to post any given news story or blog post (different stories/posts about the same source paper are fine, though)
  • Class Chat on Thursday, 11:00 am - 12:20 pm (CT)
    • This is your chance to ask me questions LIVE. I’ll talk for a bit, we’ll do some breakout activities, it’ll be fun!